Datasets:

sciosystems
/

test

+{
+  "gardian_id": "81b327112543c55e8444014a9d7f7c09",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/164105",
+  "description": "NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.",
+  "id": "1ce7237e59f562de78057440e86a0d79",
+  "title": "Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2022",
+  "rights": "CC-BY",
+  "dataNODE_id": "81b327112543c55e8444014a9d7f7c09",
+  "keywords": [
+    "computers in earth sciences",
+    "geology",
+    "soil science",
+    "geographic regions",
+    "biomass",
+    "density",
+    "models",
+    "dynamics",
+    "lidar",
+    "data",
+    "paper",
+    "development",
+    "selection",
+    "calibration"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available."
+}

ABSTRACTS_ONLY/EN/JSON/00bc5768da212a91c6f39955f963df89.json ADDED Viewed

	@@ -0,0 +1,39 @@

+{
+  "gardian_id": "34f979859a5314f8c4c7b70d020ee133",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/NRUYGD",
+  "description": "This dataset originates from the survey of women with children under 2 years, conducted as part of the baseline for the impact evaluation of the Alive & Thrive (A&T) project in Gujarat, India. The survey was designed to assess the effectiveness of systems-strengthening interventions and local governance engagement in improving the quality and co-coverage of health and nutrition services during the first 1,000 days of life.</p>\n\nThe baseline survey used a quasi-experimental design and was conducted in three districts—Bharuch, Surat, and Mahesana—covering 26 blocks. Thirteen blocks (4 from Bharuch, 4 from Surat, and 5 from Mahesana) were randomly assigned to the intervention and control groups, with an additional urban block from Surat included. Data collection took place between March and May 2022 and was led by the International Food Policy Research Institute (IFPRI) in collaboration with the survey firm Network for Engineering and Economics Research and Management (NEERMAN). </p>\n\nThe Women with Children Survey includes modules on:\n<ul>\n<li>Administrative Details</li>\n\n<li>Personal and Household Schedule\n\n<li>Household Assets and Dwelling Characteristics\n\n<li>Household-Level Social Protection\n\n<li>Exposure to Services During Pregnancy\n\n<li>Exposure to Services During Delivery and Early Childhood\n\n<li>Interaction with Frontline Workers (FLWs)\n\n<li>Take-Home Rations (THR)\n\n<li>Knowledge of Maternal Nutrition and Infant and Young Child Feeding (IYCF) Practices\n\n<li>Household Food Security\n<li>\nWomen’s Dietary Intake\n\n<li>Infant and Young Child Feeding Practices (for the youngest child aged 0–24 months)\n</ul>\nThese data provide rich insights into maternal and child health behaviors, service access and quality, and the pathways through which systems-strengthening interventions may improve nutrition outcomes during the critical early years of life.",
+  "id": "00bc5768da212a91c6f39955f963df89",
+  "title": "A&T Gujarat Implementation Research Baseline Survey 2022: Women with Children",
+  "language": "English",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2022",
+  "rights": "CC-BY",
+  "dataNODE_id": "34f979859a5314f8c4c7b70d020ee133",
+  "keywords": [
+    "baseline studies",
+    "children",
+    "decision making",
+    "health",
+    "health communication",
+    "nutrition",
+    "nutrition education",
+    "maternal nutrition",
+    "infant feeding",
+    "breast feeding",
+    "india",
+    "south asia",
+    "asia"
+  ],
+  "geography": {
+    "regions": [
+      "Southern Asia",
+      "Asia",
+      "World"
+    ],
+    "countries": [
+      "India"
+    ]
+  },
+  "content": "This dataset originates from the survey of women with children under 2 years, conducted as part of the baseline for the impact evaluation of the Alive & Thrive (A&T) project in Gujarat, India. The survey was designed to assess the effectiveness of systems-strengthening interventions and local governance engagement in improving the quality and co-coverage of health and nutrition services during the first 1,000 days of life.</p>\n\nThe baseline survey used a quasi-experimental design and was conducted in three districts—Bharuch, Surat, and Mahesana—covering 26 blocks. Thirteen blocks (4 from Bharuch, 4 from Surat, and 5 from Mahesana) were randomly assigned to the intervention and control groups, with an additional urban block from Surat included. Data collection took place between March and May 2022 and was led by the International Food Policy Research Institute (IFPRI) in collaboration with the survey firm Network for Engineering and Economics Research and Management (NEERMAN). </p>\n\nThe Women with Children Survey includes modules on:\n<ul>\n<li>Administrative Details</li>\n\n<li>Personal and Household Schedule\n\n<li>Household Assets and Dwelling Characteristics\n\n<li>Household-Level Social Protection\n\n<li>Exposure to Services During Pregnancy\n\n<li>Exposure to Services During Delivery and Early Childhood\n\n<li>Interaction with Frontline Workers (FLWs)\n\n<li>Take-Home Rations (THR)\n\n<li>Knowledge of Maternal Nutrition and Infant and Young Child Feeding (IYCF) Practices\n\n<li>Household Food Security\n<li>\nWomen’s Dietary Intake\n\n<li>Infant and Young Child Feeding Practices (for the youngest child aged 0–24 months)\n</ul>\nThese data provide rich insights into maternal and child health behaviors, service access and quality, and the pathways through which systems-strengthening interventions may improve nutrition outcomes during the critical early years of life."
+}

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+{
+  "gardian_id": "54a432df3c9cd273fdd391e616e2691b",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ONVACP",
+  "description": "This dataset is the result of the community survey that was conducted to gather data at endline as a part of the impact evaluation of the Alive & Thrive (A&T) interventions in Ethiopia. The broad objective of the impact evaluation in Ethiopia is to measure the impact of A&T’s community-based interventions, delivered through the government's health extension program (HEP) platform, in the reduction of stunting and improvement of IYCF practices in two regions where the IFHP operates, namely Tigray and SNNPR (Southern Nations, Nationalities, and People’s Region).</p>\r\nA&T is a six-year initiative to facilitate change for improved infant and young child feeding (IYCF) practices at scale in Bangladesh, Ethiopia, and Viet Nam. The goal of A&T is to reduce avoidable death and disability due to suboptimal IYCF in the developing world by increasing exclusive breastfeeding (EBF) until 6 months of age and reducing stunting of children 0-24 months of age.</p>\r\nThe impact evaluation of A&T’s community-based intervention and mass media activities applied an “adequacy design,” which involves pre- and post-intervention assessments without a non-intervention comparison group.  A total of 75 enumeration areas (EAs) were randomly selected from woredas (districts) that were part of the IFHP platform for A&T in Tigray and SNNPR.  Repeated cross-sectional surveys were conducted at baseline (2010) and endline (2014) in the 75 EAs.</p>\r\nA short questionnaire was administered to community leaders to gather information on the contextual factors at the community level as well as to understand differences in characteristics across the clusters (EA) over time. One questionnaire was completed for each cluster (EA). This information at the community level is critical to control for externalities that could influence the outcome of the program.</p>\r\nThe Ethiopia endline community questionnaire provided information on the following: 1) General characteristics of the EA/kebele (population, livelihood, season of food shortage), 2) Infrastructure (access to main road, electricity, access to clean water, 3) Distance from the nearest major town, type of transportation use to reach the town, 4) Access to the nearest market, 5) Migration patterns, 6) Social and food assistance (productive safety net program, community-based nutrition program), 7) Natural disasters occurred in the area during the last year, 8) Availability and access to health and education facilities (health post, government hospital, private clinic, junior and high school, college).",
+  "id": "0a0438c5461834634fd5590189516395",
+  "title": "Ethiopia Alive & Thrive Endline Survey 2014: Community",
+  "language": "English",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2014",
+  "rights": "CC-BY",
+  "dataNODE_id": "54a432df3c9cd273fdd391e616e2691b",
+  "keywords": [
+    "endline surveys",
+    "communities",
+    "infrastructure",
+    "market access",
+    "food prices",
+    "health services",
+    "food security",
+    "education",
+    "social safety nets",
+    "migration",
+    "natural disasters",
+    "developing countries",
+    "ethiopia",
+    "east africa",
+    "africa south of sahara",
+    "africa"
+  ],
+  "geography": {
+    "regions": [
+      "Southern Asia",
+      "Asia",
+      "World",
+      "Eastern Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "South-eastern Asia"
+    ],
+    "countries": [
+      "Viet Nam",
+      "Ethiopia",
+      "Bangladesh"
+    ]
+  },
+  "content": "This dataset is the result of the community survey that was conducted to gather data at endline as a part of the impact evaluation of the Alive & Thrive (A&T) interventions in Ethiopia. The broad objective of the impact evaluation in Ethiopia is to measure the impact of A&T’s community-based interventions, delivered through the government's health extension program (HEP) platform, in the reduction of stunting and improvement of IYCF practices in two regions where the IFHP operates, namely Tigray and SNNPR (Southern Nations, Nationalities, and People’s Region).</p>\r\nA&T is a six-year initiative to facilitate change for improved infant and young child feeding (IYCF) practices at scale in Bangladesh, Ethiopia, and Viet Nam. The goal of A&T is to reduce avoidable death and disability due to suboptimal IYCF in the developing world by increasing exclusive breastfeeding (EBF) until 6 months of age and reducing stunting of children 0-24 months of age.</p>\r\nThe impact evaluation of A&T’s community-based intervention and mass media activities applied an “adequacy design,” which involves pre- and post-intervention assessments without a non-intervention comparison group.  A total of 75 enumeration areas (EAs) were randomly selected from woredas (districts) that were part of the IFHP platform for A&T in Tigray and SNNPR.  Repeated cross-sectional surveys were conducted at baseline (2010) and endline (2014) in the 75 EAs.</p>\r\nA short questionnaire was administered to community leaders to gather information on the contextual factors at the community level as well as to understand differences in characteristics across the clusters (EA) over time. One questionnaire was completed for each cluster (EA). This information at the community level is critical to control for externalities that could influence the outcome of the program.</p>\r\nThe Ethiopia endline community questionnaire provided information on the following: 1) General characteristics of the EA/kebele (population, livelihood, season of food shortage), 2) Infrastructure (access to main road, electricity, access to clean water, 3) Distance from the nearest major town, type of transportation use to reach the town, 4) Access to the nearest market, 5) Migration patterns, 6) Social and food assistance (productive safety net program, community-based nutrition program), 7) Natural disasters occurred in the area during the last year, 8) Availability and access to health and education facilities (health post, government hospital, private clinic, junior and high school, college)."
+}

ABSTRACTS_ONLY/EN/JSON/0a0588e6fdc920eb4fd8d6763bf9b7b3.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "gardian_id": "d77aff47fc33c4c8c51b2e03efe80f29",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/M6F0UX",
+  "description": "The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand.</p>\nImproving women’s decision-making power is crucial for advancing gender equality and is most commonly measured by asking respondents who usually makes decisions over a standard set of domains (e.g., major household purchases, children’s education, health, how earned money is used, etc.). However, interpreting being a decision maker as a proxy of empowerment is only valid if the respondent desires to be involved in the decision. It is not hard to imagine situations in which not being a decision maker reflects an individual acting on their own desires. Understanding preferences and mechanisms behind desired non-involvement provides critical information to inform global initiatives designed to promote women’s decision-making power and agency. This tool, Preferences over Decision-making, aims to capture whether respondents want to be involved in the decisions they are part of and those they are not part of, as well as the reasons for which they might not want to be involved. This tool is suited for nationally representative individual- or household-level surveys, and for targeted thematic or impact evaluation surveys designed to understand women’s agency and decision-making. Other variables you may want to collect alongside this module include marital status and age.</p>\nThis data study includes following files.\n</p>1. A survey document (including implementation guidelines)",
+  "id": "0a0588e6fdc920eb4fd8d6763bf9b7b3",
+  "title": "Preferences Over Decision-Making",
+  "language": "English",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2024",
+  "rights": "CC-BY",
+  "dataNODE_id": "d77aff47fc33c4c8c51b2e03efe80f29",
+  "keywords": [
+    "gender equality",
+    "women",
+    "assets",
+    "ownership",
+    "women's empowerment",
+    "property rights",
+    "data collection",
+    "research",
+    "survey methods",
+    "households",
+    "africa south of sahara",
+    "marital status",
+    "measurement"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand.</p>\nImproving women’s decision-making power is crucial for advancing gender equality and is most commonly measured by asking respondents who usually makes decisions over a standard set of domains (e.g., major household purchases, children’s education, health, how earned money is used, etc.). However, interpreting being a decision maker as a proxy of empowerment is only valid if the respondent desires to be involved in the decision. It is not hard to imagine situations in which not being a decision maker reflects an individual acting on their own desires. Understanding preferences and mechanisms behind desired non-involvement provides critical information to inform global initiatives designed to promote women’s decision-making power and agency. This tool, Preferences over Decision-making, aims to capture whether respondents want to be involved in the decisions they are part of and those they are not part of, as well as the reasons for which they might not want to be involved. This tool is suited for nationally representative individual- or household-level surveys, and for targeted thematic or impact evaluation surveys designed to understand women’s agency and decision-making. Other variables you may want to collect alongside this module include marital status and age.</p>\nThis data study includes following files.\n</p>1. A survey document (including implementation guidelines)"
+}

ABSTRACTS_ONLY/EN/JSON/0e35b9e67482634a3062de212712f334.json ADDED Viewed

	@@ -0,0 +1,42 @@

+{
+  "gardian_id": "f58a5b81ce9a3f99164cef8b7e6d2e23",
+  "source": "gardian_index",
+  "url": "https://www.cifor-icraf.org/knowledge/publication/6605",
+  "description": "Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds. Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds.Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements.AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics.Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.",
+  "id": "0e35b9e67482634a3062de212712f334",
+  "title": "Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2018",
+  "rights": "CC-BY",
+  "dataNODE_id": "f58a5b81ce9a3f99164cef8b7e6d2e23",
+  "keywords": [
+    "above-ground biomass",
+    "carbon",
+    "emission",
+    "models",
+    "trees",
+    "tropical forests",
+    "climate change",
+    "estimation",
+    "biomass",
+    "lidar",
+    "modelling"
+  ],
+  "geography": {
+    "regions": [
+      "South America",
+      "Latin America and the Caribbean",
+      "Americas",
+      "World",
+      "South-eastern Asia",
+      "Asia"
+    ],
+    "countries": [
+      "Peru",
+      "Indonesia",
+      "Guyana"
+    ]
+  },
+  "content": "Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds. Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds.Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements.AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics.Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests."
+}

ABSTRACTS_ONLY/EN/JSON/1ce7237e59f562de78057440e86a0d79.json ADDED Viewed

	@@ -0,0 +1,34 @@

+{
+  "gardian_id": "81b327112543c55e8444014a9d7f7c09",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/164105",
+  "description": "NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.",
+  "id": "1ce7237e59f562de78057440e86a0d79",
+  "title": "Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2022",
+  "rights": "CC-BY",
+  "dataNODE_id": "81b327112543c55e8444014a9d7f7c09",
+  "keywords": [
+    "computers in earth sciences",
+    "geology",
+    "soil science",
+    "geographic regions",
+    "biomass",
+    "density",
+    "models",
+    "dynamics",
+    "lidar",
+    "data",
+    "paper",
+    "development",
+    "selection",
+    "calibration"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available."
+}

ABSTRACTS_ONLY/EN/JSON/1db545267e16ee3611ccce98348ca3aa.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "gardian_id": "b337236f86c1b99846d4002f723b64c5",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/164434",
+  "description": "Early seedling vigor is an essential trait of direct-seeded rice. It helps the seedlings to compete with weeds for water and nutrient availability, and contributes to better seedling establishment during the initial phase of crop growth. Seedling vigor is a complex trait, and phenotyping by a destructive method limits the improvement of this trait through traditional breeding. Hence, a non-invasive, rapid, and precise image-based phenotyping technique is developed to increase the possibility to improve early seedling vigor through breeding in rice and other field crops. Results To establish and assess the methodology using free-source software, early seedling vigor was estimated from images captured with a digital SLR camera in a non-destructive way. Here, the legitimacy and strength of the method have been proved through screening seven diverse rice cultivars varying for early seedling vigor. In the regression analysis, whole-plant area (WPA) estimated by destructive-flatbed scanner (WPAs) and non-destructive imaging (WPAi) approaches was strongly related (R2 > 83%) and suggested that WPA<jats:sub>i</jats:sub> can be adapted in place of destructive methods to estimate seedling vigor. In addition, this study has identified a set of new geometric traits (convex hull and top view area) for screening breeding lines for early seedling vigor in rice, which decreased the time by 80% and halved the cost of labor in data observation.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The method demonstrated here is affordable and easy to establish as a phenotypic platform. It is suitable for most glasshouses/net houses for characterizing genotypes to understand the plasticity of shoots under a given environment at the seedling stage. The methodology explained in this experiment has been proven to be practical and suggested as a technique for researchers involved in direct-seeded rice. Consequently, it will help in the simultaneous screening of genotypes in large numbers, the identification of donors, and in gaining information on the genetic basis of the trait to design a breeding program for direct-seeded rice.</jats:p> </jats:sec>",
+  "id": "1db545267e16ee3611ccce98348ca3aa",
+  "title": "Non-destructive phenotyping for early seedling vigor in direct-seeded rice",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2020",
+  "rights": "CC-BY",
+  "dataNODE_id": "b337236f86c1b99846d4002f723b64c5",
+  "keywords": [
+    "biotechnology",
+    "genetics",
+    "plant science",
+    "rice",
+    "nutrient availability",
+    "field crops",
+    "regression analysis",
+    "breeding lines",
+    "seedling stage",
+    "vigor",
+    "seedlings",
+    "weeds",
+    "water"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "Early seedling vigor is an essential trait of direct-seeded rice. It helps the seedlings to compete with weeds for water and nutrient availability, and contributes to better seedling establishment during the initial phase of crop growth. Seedling vigor is a complex trait, and phenotyping by a destructive method limits the improvement of this trait through traditional breeding. Hence, a non-invasive, rapid, and precise image-based phenotyping technique is developed to increase the possibility to improve early seedling vigor through breeding in rice and other field crops. Results To establish and assess the methodology using free-source software, early seedling vigor was estimated from images captured with a digital SLR camera in a non-destructive way. Here, the legitimacy and strength of the method have been proved through screening seven diverse rice cultivars varying for early seedling vigor. In the regression analysis, whole-plant area (WPA) estimated by destructive-flatbed scanner (WPAs) and non-destructive imaging (WPAi) approaches was strongly related (R2 > 83%) and suggested that WPA<jats:sub>i</jats:sub> can be adapted in place of destructive methods to estimate seedling vigor. In addition, this study has identified a set of new geometric traits (convex hull and top view area) for screening breeding lines for early seedling vigor in rice, which decreased the time by 80% and halved the cost of labor in data observation.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The method demonstrated here is affordable and easy to establish as a phenotypic platform. It is suitable for most glasshouses/net houses for characterizing genotypes to understand the plasticity of shoots under a given environment at the seedling stage. The methodology explained in this experiment has been proven to be practical and suggested as a technique for researchers involved in direct-seeded rice. Consequently, it will help in the simultaneous screening of genotypes in large numbers, the identification of donors, and in gaining information on the genetic basis of the trait to design a breeding program for direct-seeded rice.</jats:p> </jats:sec>"
+}

ABSTRACTS_ONLY/EN/JSON/1fad4b28ea10e2ce8e4c767fb10b909b.json ADDED Viewed

	@@ -0,0 +1,32 @@

+{
+  "gardian_id": "111b3e0a28e236149f6aaa486b00770e",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/92923",
+  "description": "Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.",
+  "id": "1fad4b28ea10e2ce8e4c767fb10b909b",
+  "title": "ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2018",
+  "rights": "CC-BY",
+  "dataNODE_id": "111b3e0a28e236149f6aaa486b00770e",
+  "keywords": [
+    "research",
+    "water",
+    "energy",
+    "temperature",
+    "soil hydraulic properties",
+    "climate change",
+    "shallow water",
+    "water table",
+    "primary production",
+    "scales",
+    "peatlands",
+    "carbon"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value."
+}

ABSTRACTS_ONLY/EN/JSON/3bbd17b582ac859bbd395d86373914d9.json ADDED Viewed

	@@ -0,0 +1,41 @@

+{
+  "gardian_id": "85da9f653ab24330f9297aab7e86046c",
+  "source": "gardian_index",
+  "url": "https://www.cifor-icraf.org/knowledge/publication/8087",
+  "description": "Peatland pole forest is the most carbon-dense ecosystem in Amazonia, but its spatial distribution and species composition are poorly known. To address this knowledge gap, we quantified variation in the floristic composition, peat thickness, and the amount of carbon stored above and below ground of 102 forest plots and 53 transects in northern Peruvian Amazonia. This large dataset includes 571 ground reference points of peat thickness measurements across six ecosystem types. These field data were also used to generate a new land-cover classification based on multiple satellite products using a random forest classification. Peatland pole forests are floristically distinctive and dominated by thin-stemmed woody species such as Pachira nitida (Malvaceae), Platycarpum loretense (Rubiaceae), and Hevea guianensis (Euphorbiaceae). In contrast, palm swamps and open peatlands are dominated by Mauritia flexuosa (Arecaceae). Peatland pole forests have high peat thickness (274 ± 22 cm, mean ± 95% CI, n = 184) similar to open peatlands (282 ± 46 cm, n = 46), but greater than palm swamps (161 ± 17 cm, n = 220) and seasonally-flooded forest, terra firme, and white-sand forest where peat is rare or absent. As a result, peatland pole forest has exceptional carbon density (1,133 ± 93 Mg C ha−1). The new sites expand the known distribution of peatland pole forest by 61% within the Pastaza-Marañón Foreland basin, mainly alongside the Tigre river, to cover a total of 7540 km2 in northern Peruvian Amazonia. However, only 15% of the pole forest area is within a protected area, whilst an additional 26% lies within indigenous territories. The current low levels of protection and forest degradation but high threat from road paving projects makes the Tigre river basin a priority for conservation. The long-term conservation of peatland pole forests has the potential to make a large contribution towards international commitments to mitigate climate change.",
+  "id": "3bbd17b582ac859bbd395d86373914d9",
+  "title": "Intensive field sampling increases the known extent of carbon-rich Amazonian peatland pole forests",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2021",
+  "rights": "CC-BY",
+  "dataNODE_id": "85da9f653ab24330f9297aab7e86046c",
+  "keywords": [
+    "carbon sinks",
+    "peatlands",
+    "remote sensing",
+    "satellite imagery",
+    "spatial distribution",
+    "species composition",
+    "forest management",
+    "rubber tree",
+    "cashew",
+    "sampling",
+    "forests",
+    "amazonia",
+    "distribution",
+    "species"
+  ],
+  "geography": {
+    "regions": [
+      "South America",
+      "Latin America and the Caribbean",
+      "Americas",
+      "World"
+    ],
+    "countries": [
+      "Peru"
+    ]
+  },
+  "content": "Peatland pole forest is the most carbon-dense ecosystem in Amazonia, but its spatial distribution and species composition are poorly known. To address this knowledge gap, we quantified variation in the floristic composition, peat thickness, and the amount of carbon stored above and below ground of 102 forest plots and 53 transects in northern Peruvian Amazonia. This large dataset includes 571 ground reference points of peat thickness measurements across six ecosystem types. These field data were also used to generate a new land-cover classification based on multiple satellite products using a random forest classification. Peatland pole forests are floristically distinctive and dominated by thin-stemmed woody species such as Pachira nitida (Malvaceae), Platycarpum loretense (Rubiaceae), and Hevea guianensis (Euphorbiaceae). In contrast, palm swamps and open peatlands are dominated by Mauritia flexuosa (Arecaceae). Peatland pole forests have high peat thickness (274 ± 22 cm, mean ± 95% CI, n = 184) similar to open peatlands (282 ± 46 cm, n = 46), but greater than palm swamps (161 ± 17 cm, n = 220) and seasonally-flooded forest, terra firme, and white-sand forest where peat is rare or absent. As a result, peatland pole forest has exceptional carbon density (1,133 ± 93 Mg C ha−1). The new sites expand the known distribution of peatland pole forest by 61% within the Pastaza-Marañón Foreland basin, mainly alongside the Tigre river, to cover a total of 7540 km2 in northern Peruvian Amazonia. However, only 15% of the pole forest area is within a protected area, whilst an additional 26% lies within indigenous territories. The current low levels of protection and forest degradation but high threat from road paving projects makes the Tigre river basin a priority for conservation. The long-term conservation of peatland pole forests has the potential to make a large contribution towards international commitments to mitigate climate change."
+}

ABSTRACTS_ONLY/EN/JSON/f49f5f642a89935da3948885e1a68b63.json ADDED Viewed

	@@ -0,0 +1,38 @@

+{
+  "gardian_id": "57e15202958e87eec45744f52480f4b0",
+  "source": "gardian_index",
+  "url": "https://www.cifor-icraf.org/knowledge/publication/6993",
+  "description": "Abstract. Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed.",
+  "id": "f49f5f642a89935da3948885e1a68b63",
+  "title": "Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations",
+  "language": "English",
+  "resource_type": "Scientific Publication",
+  "release_year": "2017",
+  "rights": "CC-BY",
+  "dataNODE_id": "57e15202958e87eec45744f52480f4b0",
+  "keywords": [
+    "carbon dioxide",
+    "climate change",
+    "emission",
+    "spatial data",
+    "carbon cycle",
+    "carbon",
+    "data"
+  ],
+  "geography": {
+    "regions": [
+      "Australia and New Zealand",
+      "Oceania",
+      "World",
+      "South-eastern Asia",
+      "Asia",
+      "Eastern Europe",
+      "Europe"
+    ],
+    "countries": [
+      "Russia",
+      "Indonesia"
+    ]
+  },
+  "content": "Abstract. Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed."
+}

ABSTRACTS_ONLY/EN/Markdown/00bc5768da212a91c6f39955f963df89.md ADDED Viewed

	@@ -0,0 +1,47 @@

+---
+gardian_id: "34f979859a5314f8c4c7b70d020ee133"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/NRUYGD"
+description: "This dataset originates from the survey of women with children under 2 years, conducted as part of the baseline for the impact evaluation of the Alive & Thrive (A&T) project in Gujarat, India. The survey was designed to assess the effectiveness of systems-strengthening interventions and local governance engagement in improving the quality and co-coverage of health and nutrition services during the first 1,000 days of life.</p>\n\nThe baseline survey used a quasi-experimental design and was conducted in three districts—Bharuch, Surat, and Mahesana—covering 26 blocks. Thirteen blocks (4 from Bharuch, 4 from Surat, and 5 from Mahesana) were randomly assigned to the intervention and control groups, with an additional urban block from Surat included. Data collection took place between March and May 2022 and was led by the International Food Policy Research Institute (IFPRI) in collaboration with the survey firm Network for Engineering and Economics Research and Management (NEERMAN). </p>\n\nThe Women with Children Survey includes modules on:\n<ul>\n<li>Administrative Details</li>\n\n<li>Personal and Household Schedule\n\n<li>Household Assets and Dwelling Characteristics\n\n<li>Household-Level Social Protection\n\n<li>Exposure to Services During Pregnancy\n\n<li>Exposure to Services During Delivery and Early Childhood\n\n<li>Interaction with Frontline Workers (FLWs)\n\n<li>Take-Home Rations (THR)\n\n<li>Knowledge of Maternal Nutrition and Infant and Young Child Feeding (IYCF) Practices\n\n<li>Household Food Security\n<li>\nWomen’s Dietary Intake\n\n<li>Infant and Young Child Feeding Practices (for the youngest child aged 0–24 months)\n</ul>\nThese data provide rich insights into maternal and child health behaviors, service access and quality, and the pathways through which systems-strengthening interventions may improve nutrition outcomes during the critical early years of life."
+id: "00bc5768da212a91c6f39955f963df89"
+title: "A&T Gujarat Implementation Research Baseline Survey 2022: Women with Children"
+language: "English"
+resource_type: "Dataset / Tabular"
+release_year: "2022"
+rights: "CC-BY"
+dataNODE_id: "34f979859a5314f8c4c7b70d020ee133"
+keywords: ["baseline studies", "children", "decision making", "health", "health communication", "nutrition", "nutrition education", "maternal nutrition", "infant feeding", "breast feeding", "india", "south asia", "asia"]
+geography: {"regions": ["Southern Asia", "Asia", "World"], "countries": ["India"]}
+---
+This dataset originates from the survey of women with children under 2 years, conducted as part of the baseline for the impact evaluation of the Alive & Thrive (A&T) project in Gujarat, India. The survey was designed to assess the effectiveness of systems-strengthening interventions and local governance engagement in improving the quality and co-coverage of health and nutrition services during the first 1,000 days of life.</p>
+The baseline survey used a quasi-experimental design and was conducted in three districts—Bharuch, Surat, and Mahesana—covering 26 blocks. Thirteen blocks (4 from Bharuch, 4 from Surat, and 5 from Mahesana) were randomly assigned to the intervention and control groups, with an additional urban block from Surat included. Data collection took place between March and May 2022 and was led by the International Food Policy Research Institute (IFPRI) in collaboration with the survey firm Network for Engineering and Economics Research and Management (NEERMAN). </p>
+The Women with Children Survey includes modules on:
+<ul>
+<li>Administrative Details</li>
+<li>Personal and Household Schedule
+<li>Household Assets and Dwelling Characteristics
+<li>Household-Level Social Protection
+<li>Exposure to Services During Pregnancy
+<li>Exposure to Services During Delivery and Early Childhood
+<li>Interaction with Frontline Workers (FLWs)
+<li>Take-Home Rations (THR)
+<li>Knowledge of Maternal Nutrition and Infant and Young Child Feeding (IYCF) Practices
+<li>Household Food Security
+<li>
+Women’s Dietary Intake
+<li>Infant and Young Child Feeding Practices (for the youngest child aged 0–24 months)
+</ul>
+These data provide rich insights into maternal and child health behaviors, service access and quality, and the pathways through which systems-strengthening interventions may improve nutrition outcomes during the critical early years of life.

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+---
+gardian_id: "54a432df3c9cd273fdd391e616e2691b"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ONVACP"
+description: "This dataset is the result of the community survey that was conducted to gather data at endline as a part of the impact evaluation of the Alive & Thrive (A&T) interventions in Ethiopia. The broad objective of the impact evaluation in Ethiopia is to measure the impact of A&T’s community-based interventions, delivered through the government's health extension program (HEP) platform, in the reduction of stunting and improvement of IYCF practices in two regions where the IFHP operates, namely Tigray and SNNPR (Southern Nations, Nationalities, and People’s Region).</p>\r\nA&T is a six-year initiative to facilitate change for improved infant and young child feeding (IYCF) practices at scale in Bangladesh, Ethiopia, and Viet Nam. The goal of A&T is to reduce avoidable death and disability due to suboptimal IYCF in the developing world by increasing exclusive breastfeeding (EBF) until 6 months of age and reducing stunting of children 0-24 months of age.</p>\r\nThe impact evaluation of A&T’s community-based intervention and mass media activities applied an “adequacy design,” which involves pre- and post-intervention assessments without a non-intervention comparison group.  A total of 75 enumeration areas (EAs) were randomly selected from woredas (districts) that were part of the IFHP platform for A&T in Tigray and SNNPR.  Repeated cross-sectional surveys were conducted at baseline (2010) and endline (2014) in the 75 EAs.</p>\r\nA short questionnaire was administered to community leaders to gather information on the contextual factors at the community level as well as to understand differences in characteristics across the clusters (EA) over time. One questionnaire was completed for each cluster (EA). This information at the community level is critical to control for externalities that could influence the outcome of the program.</p>\r\nThe Ethiopia endline community questionnaire provided information on the following: 1) General characteristics of the EA/kebele (population, livelihood, season of food shortage), 2) Infrastructure (access to main road, electricity, access to clean water, 3) Distance from the nearest major town, type of transportation use to reach the town, 4) Access to the nearest market, 5) Migration patterns, 6) Social and food assistance (productive safety net program, community-based nutrition program), 7) Natural disasters occurred in the area during the last year, 8) Availability and access to health and education facilities (health post, government hospital, private clinic, junior and high school, college)."
+id: "0a0438c5461834634fd5590189516395"
+title: "Ethiopia Alive & Thrive Endline Survey 2014: Community"
+language: "English"
+resource_type: "Dataset / Tabular"
+release_year: "2014"
+rights: "CC-BY"
+dataNODE_id: "54a432df3c9cd273fdd391e616e2691b"
+keywords: ["endline surveys", "communities", "infrastructure", "market access", "food prices", "health services", "food security", "education", "social safety nets", "migration", "natural disasters", "developing countries", "ethiopia", "east africa", "africa south of sahara", "africa"]
+geography: {"regions": ["Southern Asia", "Asia", "World", "Eastern Africa", "Sub-Saharan Africa", "Africa", "South-eastern Asia"], "countries": ["Viet Nam", "Ethiopia", "Bangladesh"]}
+---
+This dataset is the result of the community survey that was conducted to gather data at endline as a part of the impact evaluation of the Alive & Thrive (A&T) interventions in Ethiopia. The broad objective of the impact evaluation in Ethiopia is to measure the impact of A&T’s community-based interventions, delivered through the government's health extension program (HEP) platform, in the reduction of stunting and improvement of IYCF practices in two regions where the IFHP operates, namely Tigray and SNNPR (Southern Nations, Nationalities, and People’s Region).</p>
+A&T is a six-year initiative to facilitate change for improved infant and young child feeding (IYCF) practices at scale in Bangladesh, Ethiopia, and Viet Nam. The goal of A&T is to reduce avoidable death and disability due to suboptimal IYCF in the developing world by increasing exclusive breastfeeding (EBF) until 6 months of age and reducing stunting of children 0-24 months of age.</p>
+The impact evaluation of A&T’s community-based intervention and mass media activities applied an “adequacy design,” which involves pre- and post-intervention assessments without a non-intervention comparison group.  A total of 75 enumeration areas (EAs) were randomly selected from woredas (districts) that were part of the IFHP platform for A&T in Tigray and SNNPR.  Repeated cross-sectional surveys were conducted at baseline (2010) and endline (2014) in the 75 EAs.</p>
+A short questionnaire was administered to community leaders to gather information on the contextual factors at the community level as well as to understand differences in characteristics across the clusters (EA) over time. One questionnaire was completed for each cluster (EA). This information at the community level is critical to control for externalities that could influence the outcome of the program.</p>
+The Ethiopia endline community questionnaire provided information on the following: 1) General characteristics of the EA/kebele (population, livelihood, season of food shortage), 2) Infrastructure (access to main road, electricity, access to clean water, 3) Distance from the nearest major town, type of transportation use to reach the town, 4) Access to the nearest market, 5) Migration patterns, 6) Social and food assistance (productive safety net program, community-based nutrition program), 7) Natural disasters occurred in the area during the last year, 8) Availability and access to health and education facilities (health post, government hospital, private clinic, junior and high school, college).

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+---
+gardian_id: "d77aff47fc33c4c8c51b2e03efe80f29"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/M6F0UX"
+description: "The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand.</p>\nImproving women’s decision-making power is crucial for advancing gender equality and is most commonly measured by asking respondents who usually makes decisions over a standard set of domains (e.g., major household purchases, children’s education, health, how earned money is used, etc.). However, interpreting being a decision maker as a proxy of empowerment is only valid if the respondent desires to be involved in the decision. It is not hard to imagine situations in which not being a decision maker reflects an individual acting on their own desires. Understanding preferences and mechanisms behind desired non-involvement provides critical information to inform global initiatives designed to promote women’s decision-making power and agency. This tool, Preferences over Decision-making, aims to capture whether respondents want to be involved in the decisions they are part of and those they are not part of, as well as the reasons for which they might not want to be involved. This tool is suited for nationally representative individual- or household-level surveys, and for targeted thematic or impact evaluation surveys designed to understand women’s agency and decision-making. Other variables you may want to collect alongside this module include marital status and age.</p>\nThis data study includes following files.\n</p>1. A survey document (including implementation guidelines)"
+id: "0a0588e6fdc920eb4fd8d6763bf9b7b3"
+title: "Preferences Over Decision-Making"
+language: "English"
+resource_type: "Dataset / Tabular"
+release_year: "2024"
+rights: "CC-BY"
+dataNODE_id: "d77aff47fc33c4c8c51b2e03efe80f29"
+keywords: ["gender equality", "women", "assets", "ownership", "women's empowerment", "property rights", "data collection", "research", "survey methods", "households", "africa south of sahara", "marital status", "measurement"]
+geography: {"regions": [], "countries": []}
+---
+The Measures for Advancing Gender Equality (MAGNET) initiative aims to broaden and deepen the measurement of women’s agency, based on the development of new tools and rigorous testing and comparison of both new and existing methods for measuring agency, and promoting the adoption of these measures at scale. By increasing the availability of innovative meaningful measures of agency for a broad range of contexts, we hope our work will lead to an improved understanding of what women’s agency is, how it manifests and how it can best be measured across contexts given the research question at hand.</p>
+Improving women’s decision-making power is crucial for advancing gender equality and is most commonly measured by asking respondents who usually makes decisions over a standard set of domains (e.g., major household purchases, children’s education, health, how earned money is used, etc.). However, interpreting being a decision maker as a proxy of empowerment is only valid if the respondent desires to be involved in the decision. It is not hard to imagine situations in which not being a decision maker reflects an individual acting on their own desires. Understanding preferences and mechanisms behind desired non-involvement provides critical information to inform global initiatives designed to promote women’s decision-making power and agency. This tool, Preferences over Decision-making, aims to capture whether respondents want to be involved in the decisions they are part of and those they are not part of, as well as the reasons for which they might not want to be involved. This tool is suited for nationally representative individual- or household-level surveys, and for targeted thematic or impact evaluation surveys designed to understand women’s agency and decision-making. Other variables you may want to collect alongside this module include marital status and age.</p>
+This data study includes following files.
+</p>1. A survey document (including implementation guidelines)

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+---
+gardian_id: "f58a5b81ce9a3f99164cef8b7e6d2e23"
+source: "gardian_index"
+url: "https://www.cifor-icraf.org/knowledge/publication/6605"
+description: "Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds. Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds.Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements.AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics.Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests."
+id: "0e35b9e67482634a3062de212712f334"
+title: "Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR"
+language: "English"
+resource_type: "Scientific Publication"
+release_year: "2018"
+rights: "CC-BY"
+dataNODE_id: "f58a5b81ce9a3f99164cef8b7e6d2e23"
+keywords: ["above-ground biomass", "carbon", "emission", "models", "trees", "tropical forests", "climate change", "estimation", "biomass", "lidar", "modelling"]
+geography: {"regions": ["South America", "Latin America and the Caribbean", "Americas", "World", "South-eastern Asia", "Asia"], "countries": ["Peru", "Indonesia", "Guyana"]}
+---
+Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds. Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements. AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics. Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.Tropical forest biomass is a crucial component of global carbon emission estimations. However, calibration and validation of such estimates require accurate and effective methods to estimate in situ above‐ground biomass (AGB). Present methods rely on allometric models that are highly uncertain for large tropical trees. Terrestrial laser scanning (TLS) tree modelling has demonstrated to be more accurate than these models to infer forest AGB. Nevertheless, applying TLS methods on tropical large trees is still challenging. We propose a method to estimate AGB of large tropical trees by three‐dimensional (3D) tree modelling of TLS point clouds.Twenty‐nine plots were scanned with a TLS in three study sites (Peru, Indonesia and Guyana). We identified the largest tree per plot (mean diameter at breast height of 73.5 cm), extracted its point cloud and calculated its volume by 3D modelling its structure using quantitative structure models (QSM) and converted to AGB using species‐specific wood density. We also estimated AGB using pantropical and local allometric models. To assess the accuracy of our and allometric methods, we harvest the trees and took destructive measurements.AGB estimates by the TLS–QSM method showed the best agreement in comparison to destructive harvest measurements (28.37% coefficient of variation of root mean square error [CV‐RMSE] and concordance correlation coefficient [CCC] of 0.95), outperforming the pantropical allometric models tested (35.6%–54.95% CV‐RMSE and CCC of 0.89–0.73). TLS–QSM showed also the lowest bias (overall underestimation of 3.7%) and stability across tree size range, contrasting with the allometric models that showed a systematic bias (overall underestimation ranging 15.2%–35.7%) increasing linearly with tree size. The TLS–QSM method also provided accurate tree wood volume estimates (CV RMSE of 23.7%) with no systematic bias regardless the tree structural characteristics.Our TLS–QSM method accounts for individual tree biophysical structure more effectively than allometric models, providing more accurate and less biased AGB estimates for large tropical trees, independently of their morphology. This non‐destructive method can be further used for testing and calibrating new allometric models, reducing the current under‐representation of large trees in and enhancing present and past estimates of forest biomass and carbon emissions from tropical forests.

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+---
+gardian_id: "81b327112543c55e8444014a9d7f7c09"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/164105"
+description: "NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available."
+id: "1ce7237e59f562de78057440e86a0d79"
+title: "Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission"
+language: "English"
+resource_type: "Scientific Publication"
+release_year: "2022"
+rights: "CC-BY"
+dataNODE_id: "81b327112543c55e8444014a9d7f7c09"
+keywords: ["computers in earth sciences", "geology", "soil science", "geographic regions", "biomass", "density", "models", "dynamics", "lidar", "data", "paper", "development", "selection", "calibration"]
+geography: {"regions": [], "countries": []}
+---
+NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

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+---
+gardian_id: "b337236f86c1b99846d4002f723b64c5"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/164434"
+description: "Early seedling vigor is an essential trait of direct-seeded rice. It helps the seedlings to compete with weeds for water and nutrient availability, and contributes to better seedling establishment during the initial phase of crop growth. Seedling vigor is a complex trait, and phenotyping by a destructive method limits the improvement of this trait through traditional breeding. Hence, a non-invasive, rapid, and precise image-based phenotyping technique is developed to increase the possibility to improve early seedling vigor through breeding in rice and other field crops. Results To establish and assess the methodology using free-source software, early seedling vigor was estimated from images captured with a digital SLR camera in a non-destructive way. Here, the legitimacy and strength of the method have been proved through screening seven diverse rice cultivars varying for early seedling vigor. In the regression analysis, whole-plant area (WPA) estimated by destructive-flatbed scanner (WPAs) and non-destructive imaging (WPAi) approaches was strongly related (R2 > 83%) and suggested that WPA<jats:sub>i</jats:sub> can be adapted in place of destructive methods to estimate seedling vigor. In addition, this study has identified a set of new geometric traits (convex hull and top view area) for screening breeding lines for early seedling vigor in rice, which decreased the time by 80% and halved the cost of labor in data observation.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The method demonstrated here is affordable and easy to establish as a phenotypic platform. It is suitable for most glasshouses/net houses for characterizing genotypes to understand the plasticity of shoots under a given environment at the seedling stage. The methodology explained in this experiment has been proven to be practical and suggested as a technique for researchers involved in direct-seeded rice. Consequently, it will help in the simultaneous screening of genotypes in large numbers, the identification of donors, and in gaining information on the genetic basis of the trait to design a breeding program for direct-seeded rice.</jats:p> </jats:sec>"
+id: "1db545267e16ee3611ccce98348ca3aa"
+title: "Non-destructive phenotyping for early seedling vigor in direct-seeded rice"
+language: "English"
+resource_type: "Scientific Publication"
+release_year: "2020"
+rights: "CC-BY"
+dataNODE_id: "b337236f86c1b99846d4002f723b64c5"
+keywords: ["biotechnology", "genetics", "plant science", "rice", "nutrient availability", "field crops", "regression analysis", "breeding lines", "seedling stage", "vigor", "seedlings", "weeds", "water"]
+geography: {"regions": [], "countries": []}
+---
+Early seedling vigor is an essential trait of direct-seeded rice. It helps the seedlings to compete with weeds for water and nutrient availability, and contributes to better seedling establishment during the initial phase of crop growth. Seedling vigor is a complex trait, and phenotyping by a destructive method limits the improvement of this trait through traditional breeding. Hence, a non-invasive, rapid, and precise image-based phenotyping technique is developed to increase the possibility to improve early seedling vigor through breeding in rice and other field crops. Results To establish and assess the methodology using free-source software, early seedling vigor was estimated from images captured with a digital SLR camera in a non-destructive way. Here, the legitimacy and strength of the method have been proved through screening seven diverse rice cultivars varying for early seedling vigor. In the regression analysis, whole-plant area (WPA) estimated by destructive-flatbed scanner (WPAs) and non-destructive imaging (WPAi) approaches was strongly related (R2 > 83%) and suggested that WPA<jats:sub>i</jats:sub> can be adapted in place of destructive methods to estimate seedling vigor. In addition, this study has identified a set of new geometric traits (convex hull and top view area) for screening breeding lines for early seedling vigor in rice, which decreased the time by 80% and halved the cost of labor in data observation.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The method demonstrated here is affordable and easy to establish as a phenotypic platform. It is suitable for most glasshouses/net houses for characterizing genotypes to understand the plasticity of shoots under a given environment at the seedling stage. The methodology explained in this experiment has been proven to be practical and suggested as a technique for researchers involved in direct-seeded rice. Consequently, it will help in the simultaneous screening of genotypes in large numbers, the identification of donors, and in gaining information on the genetic basis of the trait to design a breeding program for direct-seeded rice.</jats:p> </jats:sec>

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+---
+gardian_id: "111b3e0a28e236149f6aaa486b00770e"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/92923"
+description: "Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value."
+id: "1fad4b28ea10e2ce8e4c767fb10b909b"
+title: "ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales"
+language: "English"
+resource_type: "Scientific Publication"
+release_year: "2018"
+rights: "CC-BY"
+dataNODE_id: "111b3e0a28e236149f6aaa486b00770e"
+keywords: ["research", "water", "energy", "temperature", "soil hydraulic properties", "climate change", "shallow water", "water table", "primary production", "scales", "peatlands", "carbon"]
+geography: {"regions": [], "countries": []}
+---
+Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

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+---
+gardian_id: "85da9f653ab24330f9297aab7e86046c"
+source: "gardian_index"
+url: "https://www.cifor-icraf.org/knowledge/publication/8087"
+description: "Peatland pole forest is the most carbon-dense ecosystem in Amazonia, but its spatial distribution and species composition are poorly known. To address this knowledge gap, we quantified variation in the floristic composition, peat thickness, and the amount of carbon stored above and below ground of 102 forest plots and 53 transects in northern Peruvian Amazonia. This large dataset includes 571 ground reference points of peat thickness measurements across six ecosystem types. These field data were also used to generate a new land-cover classification based on multiple satellite products using a random forest classification. Peatland pole forests are floristically distinctive and dominated by thin-stemmed woody species such as Pachira nitida (Malvaceae), Platycarpum loretense (Rubiaceae), and Hevea guianensis (Euphorbiaceae). In contrast, palm swamps and open peatlands are dominated by Mauritia flexuosa (Arecaceae). Peatland pole forests have high peat thickness (274 ± 22 cm, mean ± 95% CI, n = 184) similar to open peatlands (282 ± 46 cm, n = 46), but greater than palm swamps (161 ± 17 cm, n = 220) and seasonally-flooded forest, terra firme, and white-sand forest where peat is rare or absent. As a result, peatland pole forest has exceptional carbon density (1,133 ± 93 Mg C ha−1). The new sites expand the known distribution of peatland pole forest by 61% within the Pastaza-Marañón Foreland basin, mainly alongside the Tigre river, to cover a total of 7540 km2 in northern Peruvian Amazonia. However, only 15% of the pole forest area is within a protected area, whilst an additional 26% lies within indigenous territories. The current low levels of protection and forest degradation but high threat from road paving projects makes the Tigre river basin a priority for conservation. The long-term conservation of peatland pole forests has the potential to make a large contribution towards international commitments to mitigate climate change."
+id: "3bbd17b582ac859bbd395d86373914d9"
+title: "Intensive field sampling increases the known extent of carbon-rich Amazonian peatland pole forests"
+language: "English"
+resource_type: "Scientific Publication"
+release_year: "2021"
+rights: "CC-BY"
+dataNODE_id: "85da9f653ab24330f9297aab7e86046c"
+keywords: ["carbon sinks", "peatlands", "remote sensing", "satellite imagery", "spatial distribution", "species composition", "forest management", "rubber tree", "cashew", "sampling", "forests", "amazonia", "distribution", "species"]
+geography: {"regions": ["South America", "Latin America and the Caribbean", "Americas", "World"], "countries": ["Peru"]}
+---
+Peatland pole forest is the most carbon-dense ecosystem in Amazonia, but its spatial distribution and species composition are poorly known. To address this knowledge gap, we quantified variation in the floristic composition, peat thickness, and the amount of carbon stored above and below ground of 102 forest plots and 53 transects in northern Peruvian Amazonia. This large dataset includes 571 ground reference points of peat thickness measurements across six ecosystem types. These field data were also used to generate a new land-cover classification based on multiple satellite products using a random forest classification. Peatland pole forests are floristically distinctive and dominated by thin-stemmed woody species such as Pachira nitida (Malvaceae), Platycarpum loretense (Rubiaceae), and Hevea guianensis (Euphorbiaceae). In contrast, palm swamps and open peatlands are dominated by Mauritia flexuosa (Arecaceae). Peatland pole forests have high peat thickness (274 ± 22 cm, mean ± 95% CI, n = 184) similar to open peatlands (282 ± 46 cm, n = 46), but greater than palm swamps (161 ± 17 cm, n = 220) and seasonally-flooded forest, terra firme, and white-sand forest where peat is rare or absent. As a result, peatland pole forest has exceptional carbon density (1,133 ± 93 Mg C ha−1). The new sites expand the known distribution of peatland pole forest by 61% within the Pastaza-Marañón Foreland basin, mainly alongside the Tigre river, to cover a total of 7540 km2 in northern Peruvian Amazonia. However, only 15% of the pole forest area is within a protected area, whilst an additional 26% lies within indigenous territories. The current low levels of protection and forest degradation but high threat from road paving projects makes the Tigre river basin a priority for conservation. The long-term conservation of peatland pole forests has the potential to make a large contribution towards international commitments to mitigate climate change.

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+---
+gardian_id: "57e15202958e87eec45744f52480f4b0"
+source: "gardian_index"
+url: "https://www.cifor-icraf.org/knowledge/publication/6993"
+description: "Abstract. Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed."
+id: "f49f5f642a89935da3948885e1a68b63"
+title: "Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations"
+language: "English"
+resource_type: "Scientific Publication"
+release_year: "2017"
+rights: "CC-BY"
+dataNODE_id: "57e15202958e87eec45744f52480f4b0"
+keywords: ["carbon dioxide", "climate change", "emission", "spatial data", "carbon cycle", "carbon", "data"]
+geography: {"regions": ["Australia and New Zealand", "Oceania", "World", "South-eastern Asia", "Asia", "Eastern Europe", "Europe"], "countries": ["Russia", "Indonesia"]}
+---
+Abstract. Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of surface–atmosphere fluxes. However, relevant C cycle observations are highly variable in their coverage and reporting standards. Especially problematic is the lack of integration of the carbon dioxide (CO2) exchange of the ocean, inland freshwaters and the land surface with the atmosphere. Here we adopt a data-driven approach to synthesize a wide range of observation-based spatially explicit surface–atmosphere CO2 fluxes from 2001 to 2010, to identify the state of today's observational opportunities and data limitations. The considered fluxes include net exchange of open oceans, continental shelves, estuaries, rivers, and lakes, as well as CO2 fluxes related to net ecosystem productivity, fire emissions, loss of tropical aboveground C, harvested wood and crops, as well as fossil fuel and cement emissions. Spatially explicit CO2 fluxes are obtained through geostatistical and/or remote-sensing-based upscaling, thereby minimizing biophysical or biogeochemical assumptions encoded in process-based models. We estimate a bottom-up net C exchange (NCE) between the surface (land, ocean, and coastal areas) and the atmosphere. Though we provide also global estimates, the primary goal of this study is to identify key uncertainties and observational shortcomings that need to be prioritized in the expansion of in situ observatories. Uncertainties for NCE and its components are derived using resampling. In many regions, our NCE estimates agree well with independent estimates from other sources such as process-based models and atmospheric inversions. This holds for Europe (mean ± 1 SD: 0.8 ± 0.1 PgC yr−1, positive numbers are sources to the atmosphere), Russia (0.1 ± 0.4 PgC yr−1), East Asia (1.6 ± 0.3 PgC yr−1), South Asia (0.3 ± 0.1 PgC yr−1), Australia (0.2 ± 0.3 PgC yr−1), and most of the Ocean regions. Our NCE estimates give a likely too large CO2 sink in tropical areas such as the Amazon, Congo, and Indonesia. Overall, and because of the overestimated CO2 uptake in tropical lands, our global bottom-up NCE amounts to a net sink of −5.4 ± 2.0 PgC yr−1. By contrast, the accurately measured mean atmospheric growth rate of CO2 over 2001–2010 indicates that the true value of NCE is a net CO2 source of 4.3 ± 0.1 PgC yr−1. This mismatch of nearly 10 PgC yr−1 highlights observational gaps and limitations of data-driven models in tropical lands, but also in North America. Our uncertainty assessment provides the basis for setting priority regions where to increase carbon observations in the future. High on the priority list are tropical land regions, which suffer from a lack of in situ observations. Second, extensive pCO2 data are missing in the Southern Ocean. Third, we lack observations that could enable seasonal estimates of shelf, estuary, and inland water–atmosphere C exchange. Our consistent derivation of data uncertainties could serve as prior knowledge in multicriteria optimization such as the Carbon Cycle Data Assimilation System (CCDAS) and atmospheric inversions, without over- or under-stating bottom-up data credibility. In the future, NCE estimates of carbon sinks could be aggregated at national scale to compare with the official national inventories of CO2 fluxes in the land use, land use change, and forestry sector, upon which future emission reductions are proposed.

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+{
+  "gardian_id": "fdb32db1cf609648a49c2ce5a2c9893e",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/WKAOIL",
+  "description": "<strong>English</strong>\r\n<p>\r\nThe Digital Soil Mapping (DSM) approach was used to generate maps of the soil texture (sand, silt, and clay) in Colombia, based on the soil geomorphology. The soil units were differentiated by land shapes using a STRM 90-m DEM, and stratified by geopedological units from the Agustín Codazzi Geographic Institute (IGAC). The digital maps of soil texture were generated using the fuzzy logic approach, which enabled determining statistically the value limits of percent-slope classes, moisture index and standardized height on each of the soil units. Data inherited from IGAC’s soil profiles were used to determine the gauge values for the mapping model (80% of total data) for sand, stilt, and clay, as well as to validate (20% of total data) based on the DSM approach. The root mean squared error (RMSE) was 21, 12, and 15% for sand, stilt, and clay, respectively, and these values are the same as the standard deviation of the field data. The map of texture classes was generated with the information on sand, stilt, and clay.\r\n</p>\r\n<strong>Español</strong>\r\n<p>\r\nSe usó el enfoque de Mapeo Digital del Suelo (MDS) para generar los mapas de textura del suelo (arena, limo y arcilla) para Colombia basado en la geomorfología del suelo. Las unidades del suelo fueron diferenciadas por formas del terreno usando un DEM SRTM de 90 m de resolución y además, estratificadas por unidades geopedológicas del Instituto Geográfico Agustín Codazzi (IGAC). Los mapas digitales de textura del suelo fueron generados usando el enfoque de lógica difusa, donde se determinaron estadísticamente los límites de los valores de las clases de porcentaje de pendiente, índice de humedad y altura normalizada en cada una de las unidades de suelo. Se usaron datos heredados de perfiles de suelos de IGAC, para determinar los valores de calibración del modelo de mapeo (80% del total de los datos) para arena, limo y arcilla, así como para validar (20% del total de los datos) según el enfoque de MDS. La raíz del error medio cuadrado (RMSE) fue 21, 12 y 15 % para arena, limo y arcilla respectivamente, valores que son iguales a la desviación estándar de los datos de campo. Con la información de arena, arcilla y limo se generó el mapa de clases de textura.\r\n</p>",
+  "id": "7b38fdf775abe1ee4037c2d15f067c4e",
+  "title": "Textural classification of soils in rice-growing areas in Colombia",
+  "language": "Spanish, Castilian",
+  "resource_type": "Dataset / Geospatial",
+  "release_year": "2015",
+  "rights": "CC-BY",
+  "dataNODE_id": "fdb32db1cf609648a49c2ce5a2c9893e",
+  "keywords": [
+    "soil texture",
+    "digital soil mapping",
+    "cartography",
+    "latin america and the caribbean",
+    "soils",
+    "rice",
+    "sand",
+    "soil mapping",
+    "soil units",
+    "soil profiles",
+    "classification",
+    "colombia",
+    "maps"
+  ],
+  "geography": {
+    "regions": [
+      "South America",
+      "Latin America and the Caribbean",
+      "Americas",
+      "World"
+    ],
+    "countries": [
+      "Colombia"
+    ]
+  },
+  "content": "<strong>English</strong>\r\n<p>\r\nThe Digital Soil Mapping (DSM) approach was used to generate maps of the soil texture (sand, silt, and clay) in Colombia, based on the soil geomorphology. The soil units were differentiated by land shapes using a STRM 90-m DEM, and stratified by geopedological units from the Agustín Codazzi Geographic Institute (IGAC). The digital maps of soil texture were generated using the fuzzy logic approach, which enabled determining statistically the value limits of percent-slope classes, moisture index and standardized height on each of the soil units. Data inherited from IGAC’s soil profiles were used to determine the gauge values for the mapping model (80% of total data) for sand, stilt, and clay, as well as to validate (20% of total data) based on the DSM approach. The root mean squared error (RMSE) was 21, 12, and 15% for sand, stilt, and clay, respectively, and these values are the same as the standard deviation of the field data. The map of texture classes was generated with the information on sand, stilt, and clay.\r\n</p>\r\n<strong>Español</strong>\r\n<p>\r\nSe usó el enfoque de Mapeo Digital del Suelo (MDS) para generar los mapas de textura del suelo (arena, limo y arcilla) para Colombia basado en la geomorfología del suelo. Las unidades del suelo fueron diferenciadas por formas del terreno usando un DEM SRTM de 90 m de resolución y además, estratificadas por unidades geopedológicas del Instituto Geográfico Agustín Codazzi (IGAC). Los mapas digitales de textura del suelo fueron generados usando el enfoque de lógica difusa, donde se determinaron estadísticamente los límites de los valores de las clases de porcentaje de pendiente, índice de humedad y altura normalizada en cada una de las unidades de suelo. Se usaron datos heredados de perfiles de suelos de IGAC, para determinar los valores de calibración del modelo de mapeo (80% del total de los datos) para arena, limo y arcilla, así como para validar (20% del total de los datos) según el enfoque de MDS. La raíz del error medio cuadrado (RMSE) fue 21, 12 y 15 % para arena, limo y arcilla respectivamente, valores que son iguales a la desviación estándar de los datos de campo. Con la información de arena, arcilla y limo se generó el mapa de clases de textura.\r\n</p>"
+}

ABSTRACTS_ONLY/ES/JSON/8784fdc543cba16ae7737de5fbea7ad3.json ADDED Viewed

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+{
+  "gardian_id": "64b6e4c183dcb4527834b572df7f6109",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZB4DYK",
+  "description": "In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)\r\n<p>\r\nTo fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.\r\n<p>\r\nHowever, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems. \r\n<p>\r\nIn the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.\r\n<p>\r\nThis dataset provides RIEPT trial data for activities conducted in semievergreen seasonal tropical forests",
+  "id": "8784fdc543cba16ae7737de5fbea7ad3",
+  "title": "RIEPT Trials - Ecosystems E: Semievergreen Seasonal Tropical Forests",
+  "language": "Spanish, Castilian",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2015",
+  "rights": "CC-BY",
+  "dataNODE_id": "64b6e4c183dcb4527834b572df7f6109",
+  "keywords": [
+    "research networks",
+    "pastures",
+    "variety trials",
+    "acid soils",
+    "semievergreen seasonal forests",
+    "latin america and the caribbean",
+    "agrobiodiversity - agbio",
+    "forages",
+    "calf",
+    "soil",
+    "beef",
+    "tropical forests"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)\r\n<p>\r\nTo fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.\r\n<p>\r\nHowever, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems. \r\n<p>\r\nIn the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.\r\n<p>\r\nThis dataset provides RIEPT trial data for activities conducted in semievergreen seasonal tropical forests"
+}

ABSTRACTS_ONLY/ES/JSON/93b6298f4d88db184195244867b380f4.json ADDED Viewed

	@@ -0,0 +1,33 @@

+{
+  "gardian_id": "568b3e854bb49a29e1e7026ba701d08a",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GA2WLQ",
+  "description": "In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)\r\n<p>\r\nTo fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.\r\n<p>\r\nHowever, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems. \r\n<p>\r\nIn the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.\r\n<p>\r\nThis dataset provides RIEPT trial data for activities conducted in tropical rain forests.",
+  "id": "93b6298f4d88db184195244867b380f4",
+  "title": "RIEPT Trials - Ecosystems L: Tropical rain forests",
+  "language": "Spanish, Castilian",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2015",
+  "rights": "CC-BY",
+  "dataNODE_id": "568b3e854bb49a29e1e7026ba701d08a",
+  "keywords": [
+    "research networks",
+    "pastures",
+    "variety trials",
+    "acid soils",
+    "tropical rain forests",
+    "latin america and the caribbean",
+    "agrobiodiversity - agbio",
+    "forages",
+    "calf",
+    "soil",
+    "beef",
+    "research institutions",
+    "production systems"
+  ],
+  "geography": {
+    "regions": [],
+    "countries": []
+  },
+  "content": "In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)\r\n<p>\r\nTo fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.\r\n<p>\r\nHowever, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems. \r\n<p>\r\nIn the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.\r\n<p>\r\nThis dataset provides RIEPT trial data for activities conducted in tropical rain forests."
+}

ABSTRACTS_ONLY/ES/Markdown/7b38fdf775abe1ee4037c2d15f067c4e.md ADDED Viewed

	@@ -0,0 +1,24 @@

+---
+gardian_id: "fdb32db1cf609648a49c2ce5a2c9893e"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/WKAOIL"
+description: "<strong>English</strong>\r\n<p>\r\nThe Digital Soil Mapping (DSM) approach was used to generate maps of the soil texture (sand, silt, and clay) in Colombia, based on the soil geomorphology. The soil units were differentiated by land shapes using a STRM 90-m DEM, and stratified by geopedological units from the Agustín Codazzi Geographic Institute (IGAC). The digital maps of soil texture were generated using the fuzzy logic approach, which enabled determining statistically the value limits of percent-slope classes, moisture index and standardized height on each of the soil units. Data inherited from IGAC’s soil profiles were used to determine the gauge values for the mapping model (80% of total data) for sand, stilt, and clay, as well as to validate (20% of total data) based on the DSM approach. The root mean squared error (RMSE) was 21, 12, and 15% for sand, stilt, and clay, respectively, and these values are the same as the standard deviation of the field data. The map of texture classes was generated with the information on sand, stilt, and clay.\r\n</p>\r\n<strong>Español</strong>\r\n<p>\r\nSe usó el enfoque de Mapeo Digital del Suelo (MDS) para generar los mapas de textura del suelo (arena, limo y arcilla) para Colombia basado en la geomorfología del suelo. Las unidades del suelo fueron diferenciadas por formas del terreno usando un DEM SRTM de 90 m de resolución y además, estratificadas por unidades geopedológicas del Instituto Geográfico Agustín Codazzi (IGAC). Los mapas digitales de textura del suelo fueron generados usando el enfoque de lógica difusa, donde se determinaron estadísticamente los límites de los valores de las clases de porcentaje de pendiente, índice de humedad y altura normalizada en cada una de las unidades de suelo. Se usaron datos heredados de perfiles de suelos de IGAC, para determinar los valores de calibración del modelo de mapeo (80% del total de los datos) para arena, limo y arcilla, así como para validar (20% del total de los datos) según el enfoque de MDS. La raíz del error medio cuadrado (RMSE) fue 21, 12 y 15 % para arena, limo y arcilla respectivamente, valores que son iguales a la desviación estándar de los datos de campo. Con la información de arena, arcilla y limo se generó el mapa de clases de textura.\r\n</p>"
+id: "7b38fdf775abe1ee4037c2d15f067c4e"
+title: "Textural classification of soils in rice-growing areas in Colombia"
+language: "Spanish, Castilian"
+resource_type: "Dataset / Geospatial"
+release_year: "2015"
+rights: "CC-BY"
+dataNODE_id: "fdb32db1cf609648a49c2ce5a2c9893e"
+keywords: ["soil texture", "digital soil mapping", "cartography", "latin america and the caribbean", "soils", "rice", "sand", "soil mapping", "soil units", "soil profiles", "classification", "colombia", "maps"]
+geography: {"regions": ["South America", "Latin America and the Caribbean", "Americas", "World"], "countries": ["Colombia"]}
+---
+<strong>English</strong>
+<p>
+The Digital Soil Mapping (DSM) approach was used to generate maps of the soil texture (sand, silt, and clay) in Colombia, based on the soil geomorphology. The soil units were differentiated by land shapes using a STRM 90-m DEM, and stratified by geopedological units from the Agustín Codazzi Geographic Institute (IGAC). The digital maps of soil texture were generated using the fuzzy logic approach, which enabled determining statistically the value limits of percent-slope classes, moisture index and standardized height on each of the soil units. Data inherited from IGAC’s soil profiles were used to determine the gauge values for the mapping model (80% of total data) for sand, stilt, and clay, as well as to validate (20% of total data) based on the DSM approach. The root mean squared error (RMSE) was 21, 12, and 15% for sand, stilt, and clay, respectively, and these values are the same as the standard deviation of the field data. The map of texture classes was generated with the information on sand, stilt, and clay.
+</p>
+<strong>Español</strong>
+<p>
+Se usó el enfoque de Mapeo Digital del Suelo (MDS) para generar los mapas de textura del suelo (arena, limo y arcilla) para Colombia basado en la geomorfología del suelo. Las unidades del suelo fueron diferenciadas por formas del terreno usando un DEM SRTM de 90 m de resolución y además, estratificadas por unidades geopedológicas del Instituto Geográfico Agustín Codazzi (IGAC). Los mapas digitales de textura del suelo fueron generados usando el enfoque de lógica difusa, donde se determinaron estadísticamente los límites de los valores de las clases de porcentaje de pendiente, índice de humedad y altura normalizada en cada una de las unidades de suelo. Se usaron datos heredados de perfiles de suelos de IGAC, para determinar los valores de calibración del modelo de mapeo (80% del total de los datos) para arena, limo y arcilla, así como para validar (20% del total de los datos) según el enfoque de MDS. La raíz del error medio cuadrado (RMSE) fue 21, 12 y 15 % para arena, limo y arcilla respectivamente, valores que son iguales a la desviación estándar de los datos de campo. Con la información de arena, arcilla y limo se generó el mapa de clases de textura.
+</p>

ABSTRACTS_ONLY/ES/Markdown/8784fdc543cba16ae7737de5fbea7ad3.md ADDED Viewed

	@@ -0,0 +1,25 @@

+---
+gardian_id: "64b6e4c183dcb4527834b572df7f6109"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZB4DYK"
+description: "In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)\r\n<p>\r\nTo fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.\r\n<p>\r\nHowever, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems. \r\n<p>\r\nIn the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.\r\n<p>\r\nThis dataset provides RIEPT trial data for activities conducted in semievergreen seasonal tropical forests"
+id: "8784fdc543cba16ae7737de5fbea7ad3"
+title: "RIEPT Trials - Ecosystems E: Semievergreen Seasonal Tropical Forests"
+language: "Spanish, Castilian"
+resource_type: "Dataset / Tabular"
+release_year: "2015"
+rights: "CC-BY"
+dataNODE_id: "64b6e4c183dcb4527834b572df7f6109"
+keywords: ["research networks", "pastures", "variety trials", "acid soils", "semievergreen seasonal forests", "latin america and the caribbean", "agrobiodiversity - agbio", "forages", "calf", "soil", "beef", "tropical forests"]
+geography: {"regions": [], "countries": []}
+---
+In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)
+<p>
+To fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.
+<p>
+However, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems.
+<p>
+In the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.
+<p>
+This dataset provides RIEPT trial data for activities conducted in semievergreen seasonal tropical forests

ABSTRACTS_ONLY/ES/Markdown/93b6298f4d88db184195244867b380f4.md ADDED Viewed

	@@ -0,0 +1,25 @@

+---
+gardian_id: "568b3e854bb49a29e1e7026ba701d08a"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GA2WLQ"
+description: "In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)\r\n<p>\r\nTo fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.\r\n<p>\r\nHowever, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems. \r\n<p>\r\nIn the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.\r\n<p>\r\nThis dataset provides RIEPT trial data for activities conducted in tropical rain forests."
+id: "93b6298f4d88db184195244867b380f4"
+title: "RIEPT Trials - Ecosystems L: Tropical rain forests"
+language: "Spanish, Castilian"
+resource_type: "Dataset / Tabular"
+release_year: "2015"
+rights: "CC-BY"
+dataNODE_id: "568b3e854bb49a29e1e7026ba701d08a"
+keywords: ["research networks", "pastures", "variety trials", "acid soils", "tropical rain forests", "latin america and the caribbean", "agrobiodiversity - agbio", "forages", "calf", "soil", "beef", "research institutions", "production systems"]
+geography: {"regions": [], "countries": []}
+---
+In 1978, CIAT's Tropical Pastures Program, with the cooperation of national research institutions active in pastures research, took the initiative of forming the RIEPT  (Red Internacional de Evaluación de Pastos Tropicales - i.e . lnternational Tropical Pastures Evaluation Network). Its central objectives were defined as, To contribute to the search for new pasture germplasm for the different production ecosystems prevalent in the poor, acid soils of the vast agricultural frontiers of the continent; Developing extrapolations based on knowledge of the range of ecosystems and subecosystems to which germplasm can adapt; Developing and promoting scientific capabilities within the network in order to achieve efficiency in the experimentation process, which, in a dynamic and sequential manner, will incorporate promising germplasm in pastures and put these in appropriate production systems.(Toledo, 1982)
+<p>
+To fulfill these objectives, RIEPT was relied on Regional Trials A (RTAs) representing major ecosystems (well-drained isohyperthennic and isothennic savannas; poorly drained savannas; and rainy and semievergreen seasonal tropical forests), and carried out Regional Trials B (RTBs) at sites representative of the subecosystems found within these five major ecosystems. In the RTAs, an evaluation of the adaptation potential of germplasm under the conditions of a major ecosystem was first made, that is, the potential survival of the germplasm is assessed. The materials that survive and also show a high degree of productivity were exposed to subecosystem conditions in the RTBs, where evaluations were conducted under cutting to measure seasonal productivity (that is, under maximum and minimum rainfall), and so obtain a measurement that integrates adaptability and productivity potential. Until this stage, evaluations were made monoculture, in small plots, with the only purpose of selecting germplasm adapted to the natural conditions (soil, climate, biotic pressures) of different ecosystems. By using uniform evaluation methodologies, it was possible to make multilocational analyses that could extrapolate from known adaptation ranges of the selected germplasm.
+<p>
+However, that agronomic experimentation (RTAs and RTBs) was not in any way sufficient to comply with the final objective of incorporating new germplasm options in pastures for animal production systems at the continent's agricultural frontiers. RIEPT therefore proposed to carry out regional trials under grazing in two phases. In the first, known as Regional Trials C (RTCs), the idea was to incorporate new germplasm in pastures to study its potential compatibility under grazing in small plots in terms of productivity (dry-matter yields and carrying capacity) and persistence (dynamics of botanical composition, changes in plant architecture, and seed reserves) under different grazing management systems.
+<p>
+In the second phase, Regional Trials D (RTDs), the best pastures in terms of productivity, persistence, and ease of management were compared with the best pastures under traditional use. In these trials, pasture productivity as animal products (beef, milk, and calves) within the context of the predominant production system in each region were measured.
+<p>
+This dataset provides RIEPT trial data for activities conducted in tropical rain forests.

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+{
+  "gardian_id": "80d348c4006d91e864b73afd040e96bd",
+  "source": "gardian_index",
+  "url": "https://data.iita.org/dataset/small_n_household_survey_in_drc_2024",
+  "description": "In postconflict complex humanitarian situations, there is consensus on the need to “build back better” and support efforts to strengthen resilience among farmer groups vulnerable to climate-related shocks. In many contexts (e.g., the Great Lakes region in sub-Saharan Africa), roots, tubers, and bananas (RTB) are crucial crops for food security, nutrition, and income. RTB crops are versatile, nutritious staples that produce more food per unit area of land than many other crops, contribute directly to household food security, are often under women’s management, and are projected to be more climate resilient than grain crops. Yet, humanitarian actors often have limited awareness of RTB crops' current role and contribution to local farming systems to rebuild better, sustainable livelihoods. Thus, humanitarian interventions are underperforming in these contexts. Humanitarian crises can impact seed systems in multidimensional ways depending on the cause and duration of the shock (i.e., drought, floods, plant or human disease outbreak, conflict). Seed insecurity manifests as reduced seed availability, difficulty in sourcing or accessing seed when required, and poor phytosanitary or physical quality of seed. The overall purpose is to enhance the effectiveness and appropriateness of USAID BHA’s agricultural programming investments in countries with RTB agrifood systems to achieve food security and resilience goals. The purpose will be achieved by assessing current intervention needs and providing advanced training as well as technical support in partnership with local training/research institutions to private and public-sector stakeholders for seed value chains of RTB crops. The project is implemented in Eastern DRC and has three objectives linked to three intermediate outcomes",
+  "id": "96db78cf9ecb1acc133ebe03d3d9b612",
+  "title": "Small_N_Household_survey_in_DRC_2024",
+  "language": "French",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2025",
+  "rights": "CC-BY",
+  "dataNODE_id": "80d348c4006d91e864b73afd040e96bd",
+  "keywords": [
+    "household food security",
+    "great lakes",
+    "sub-saharan africa",
+    "food security",
+    "grain crops",
+    "farming systems",
+    "sustainable livelihoods",
+    "seed systems",
+    "disease outbreak",
+    "seed insecurity",
+    "agrifood systems",
+    "value chains"
+  ],
+  "geography": {
+    "regions": [
+      "Middle Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "World"
+    ],
+    "countries": [
+      "Democratic Republic of the Congo"
+    ]
+  },
+  "content": "In postconflict complex humanitarian situations, there is consensus on the need to “build back better” and support efforts to strengthen resilience among farmer groups vulnerable to climate-related shocks. In many contexts (e.g., the Great Lakes region in sub-Saharan Africa), roots, tubers, and bananas (RTB) are crucial crops for food security, nutrition, and income. RTB crops are versatile, nutritious staples that produce more food per unit area of land than many other crops, contribute directly to household food security, are often under women’s management, and are projected to be more climate resilient than grain crops. Yet, humanitarian actors often have limited awareness of RTB crops' current role and contribution to local farming systems to rebuild better, sustainable livelihoods. Thus, humanitarian interventions are underperforming in these contexts. Humanitarian crises can impact seed systems in multidimensional ways depending on the cause and duration of the shock (i.e., drought, floods, plant or human disease outbreak, conflict). Seed insecurity manifests as reduced seed availability, difficulty in sourcing or accessing seed when required, and poor phytosanitary or physical quality of seed. The overall purpose is to enhance the effectiveness and appropriateness of USAID BHA’s agricultural programming investments in countries with RTB agrifood systems to achieve food security and resilience goals. The purpose will be achieved by assessing current intervention needs and providing advanced training as well as technical support in partnership with local training/research institutions to private and public-sector stakeholders for seed value chains of RTB crops. The project is implemented in Eastern DRC and has three objectives linked to three intermediate outcomes"
+}

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+{
+  "gardian_id": "ff3b60bdf3605f99137f9b52a0561d5b",
+  "source": "gardian_index",
+  "url": "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YARWM5",
+  "description": "In 2014 the Government of Mali began implementing its “Filets Sociaux (Jigisémèjiri)” program that aims at reducing poverty and improving human capital accumulation through targeted cash transfers, accompanying measures (or trainings), and preventive nutrition packages. In order to rigorously and independently assess the impacts of the program, the Government of Mali collaborated with research partners, International Food Policy Research Institute (IFPRI) and Institut de recherché pour le développement (IRD), to undertake an impact evaluation. The impact evaluation assesses how the “Jigisémèjiri” program impacts household welfare, and, in particular, household food consumption, food security, and dietary diversity, in addition to child nutrition and development. The impact evaluation is designed as a two-stage randomized control trial in which 96 communes were randomly assigned to begin receiving the program in 2014 or 2015 (early treatment) or in 2016 or 2017 (late treatment). Within a subset of the early treatment communes deemed eligible for nutrition packages, villages were randomly assigned to receive the nutrition packages or not receive them. </p>\n\nThis dataset is from the baseline survey conducted from September 2014–February 2015, before the start of the program across 5 regions of Mali. The baseline sample was designed to be representative of Jigisemejiri beneficiaries with a child 6-23 months old. In total, 3,175 households across the 96 communes were planned to be sampled at baseline. Due to security concerns, 6 communes in Mopti were not sampled, leading to 3,080 households across 90 communes that were actually sampled in the baseline data.",
+  "id": "e1cbde8b81ea94798bdcb4c23b28983d",
+  "title": "Programme de Filets Sociaux Jigisemejiri: Baseline Survey",
+  "language": "French",
+  "resource_type": "Dataset / Tabular",
+  "release_year": "2014",
+  "rights": "CC-BY",
+  "dataNODE_id": "ff3b60bdf3605f99137f9b52a0561d5b",
+  "keywords": [
+    "impact assessment",
+    "gender-based violence",
+    "social protection",
+    "cash flow",
+    "cash transfers",
+    "nutrition",
+    "gender",
+    "mali",
+    "west africa",
+    "africa south of sahara",
+    "africa",
+    "human capital"
+  ],
+  "geography": {
+    "regions": [
+      "Western Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "World"
+    ],
+    "countries": [
+      "Mali"
+    ]
+  },
+  "content": "In 2014 the Government of Mali began implementing its “Filets Sociaux (Jigisémèjiri)” program that aims at reducing poverty and improving human capital accumulation through targeted cash transfers, accompanying measures (or trainings), and preventive nutrition packages. In order to rigorously and independently assess the impacts of the program, the Government of Mali collaborated with research partners, International Food Policy Research Institute (IFPRI) and Institut de recherché pour le développement (IRD), to undertake an impact evaluation. The impact evaluation assesses how the “Jigisémèjiri” program impacts household welfare, and, in particular, household food consumption, food security, and dietary diversity, in addition to child nutrition and development. The impact evaluation is designed as a two-stage randomized control trial in which 96 communes were randomly assigned to begin receiving the program in 2014 or 2015 (early treatment) or in 2016 or 2017 (late treatment). Within a subset of the early treatment communes deemed eligible for nutrition packages, villages were randomly assigned to receive the nutrition packages or not receive them. </p>\n\nThis dataset is from the baseline survey conducted from September 2014–February 2015, before the start of the program across 5 regions of Mali. The baseline sample was designed to be representative of Jigisemejiri beneficiaries with a child 6-23 months old. In total, 3,175 households across the 96 communes were planned to be sampled at baseline. Due to security concerns, 6 communes in Mopti were not sampled, leading to 3,080 households across 90 communes that were actually sampled in the baseline data."
+}

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+---
+gardian_id: "80d348c4006d91e864b73afd040e96bd"
+source: "gardian_index"
+url: "https://data.iita.org/dataset/small_n_household_survey_in_drc_2024"
+description: "In postconflict complex humanitarian situations, there is consensus on the need to “build back better” and support efforts to strengthen resilience among farmer groups vulnerable to climate-related shocks. In many contexts (e.g., the Great Lakes region in sub-Saharan Africa), roots, tubers, and bananas (RTB) are crucial crops for food security, nutrition, and income. RTB crops are versatile, nutritious staples that produce more food per unit area of land than many other crops, contribute directly to household food security, are often under women’s management, and are projected to be more climate resilient than grain crops. Yet, humanitarian actors often have limited awareness of RTB crops' current role and contribution to local farming systems to rebuild better, sustainable livelihoods. Thus, humanitarian interventions are underperforming in these contexts. Humanitarian crises can impact seed systems in multidimensional ways depending on the cause and duration of the shock (i.e., drought, floods, plant or human disease outbreak, conflict). Seed insecurity manifests as reduced seed availability, difficulty in sourcing or accessing seed when required, and poor phytosanitary or physical quality of seed. The overall purpose is to enhance the effectiveness and appropriateness of USAID BHA’s agricultural programming investments in countries with RTB agrifood systems to achieve food security and resilience goals. The purpose will be achieved by assessing current intervention needs and providing advanced training as well as technical support in partnership with local training/research institutions to private and public-sector stakeholders for seed value chains of RTB crops. The project is implemented in Eastern DRC and has three objectives linked to three intermediate outcomes"
+id: "96db78cf9ecb1acc133ebe03d3d9b612"
+title: "Small_N_Household_survey_in_DRC_2024"
+language: "French"
+resource_type: "Dataset / Tabular"
+release_year: "2025"
+rights: "CC-BY"
+dataNODE_id: "80d348c4006d91e864b73afd040e96bd"
+keywords: ["household food security", "great lakes", "sub-saharan africa", "food security", "grain crops", "farming systems", "sustainable livelihoods", "seed systems", "disease outbreak", "seed insecurity", "agrifood systems", "value chains"]
+geography: {"regions": ["Middle Africa", "Sub-Saharan Africa", "Africa", "World"], "countries": ["Democratic Republic of the Congo"]}
+---
+In postconflict complex humanitarian situations, there is consensus on the need to “build back better” and support efforts to strengthen resilience among farmer groups vulnerable to climate-related shocks. In many contexts (e.g., the Great Lakes region in sub-Saharan Africa), roots, tubers, and bananas (RTB) are crucial crops for food security, nutrition, and income. RTB crops are versatile, nutritious staples that produce more food per unit area of land than many other crops, contribute directly to household food security, are often under women’s management, and are projected to be more climate resilient than grain crops. Yet, humanitarian actors often have limited awareness of RTB crops' current role and contribution to local farming systems to rebuild better, sustainable livelihoods. Thus, humanitarian interventions are underperforming in these contexts. Humanitarian crises can impact seed systems in multidimensional ways depending on the cause and duration of the shock (i.e., drought, floods, plant or human disease outbreak, conflict). Seed insecurity manifests as reduced seed availability, difficulty in sourcing or accessing seed when required, and poor phytosanitary or physical quality of seed. The overall purpose is to enhance the effectiveness and appropriateness of USAID BHA’s agricultural programming investments in countries with RTB agrifood systems to achieve food security and resilience goals. The purpose will be achieved by assessing current intervention needs and providing advanced training as well as technical support in partnership with local training/research institutions to private and public-sector stakeholders for seed value chains of RTB crops. The project is implemented in Eastern DRC and has three objectives linked to three intermediate outcomes

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+---
+gardian_id: "ff3b60bdf3605f99137f9b52a0561d5b"
+source: "gardian_index"
+url: "https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/YARWM5"
+description: "In 2014 the Government of Mali began implementing its “Filets Sociaux (Jigisémèjiri)” program that aims at reducing poverty and improving human capital accumulation through targeted cash transfers, accompanying measures (or trainings), and preventive nutrition packages. In order to rigorously and independently assess the impacts of the program, the Government of Mali collaborated with research partners, International Food Policy Research Institute (IFPRI) and Institut de recherché pour le développement (IRD), to undertake an impact evaluation. The impact evaluation assesses how the “Jigisémèjiri” program impacts household welfare, and, in particular, household food consumption, food security, and dietary diversity, in addition to child nutrition and development. The impact evaluation is designed as a two-stage randomized control trial in which 96 communes were randomly assigned to begin receiving the program in 2014 or 2015 (early treatment) or in 2016 or 2017 (late treatment). Within a subset of the early treatment communes deemed eligible for nutrition packages, villages were randomly assigned to receive the nutrition packages or not receive them. </p>\n\nThis dataset is from the baseline survey conducted from September 2014–February 2015, before the start of the program across 5 regions of Mali. The baseline sample was designed to be representative of Jigisemejiri beneficiaries with a child 6-23 months old. In total, 3,175 households across the 96 communes were planned to be sampled at baseline. Due to security concerns, 6 communes in Mopti were not sampled, leading to 3,080 households across 90 communes that were actually sampled in the baseline data."
+id: "e1cbde8b81ea94798bdcb4c23b28983d"
+title: "Programme de Filets Sociaux Jigisemejiri: Baseline Survey"
+language: "French"
+resource_type: "Dataset / Tabular"
+release_year: "2014"
+rights: "CC-BY"
+dataNODE_id: "ff3b60bdf3605f99137f9b52a0561d5b"
+keywords: ["impact assessment", "gender-based violence", "social protection", "cash flow", "cash transfers", "nutrition", "gender", "mali", "west africa", "africa south of sahara", "africa", "human capital"]
+geography: {"regions": ["Western Africa", "Sub-Saharan Africa", "Africa", "World"], "countries": ["Mali"]}
+---
+In 2014 the Government of Mali began implementing its “Filets Sociaux (Jigisémèjiri)” program that aims at reducing poverty and improving human capital accumulation through targeted cash transfers, accompanying measures (or trainings), and preventive nutrition packages. In order to rigorously and independently assess the impacts of the program, the Government of Mali collaborated with research partners, International Food Policy Research Institute (IFPRI) and Institut de recherché pour le développement (IRD), to undertake an impact evaluation. The impact evaluation assesses how the “Jigisémèjiri” program impacts household welfare, and, in particular, household food consumption, food security, and dietary diversity, in addition to child nutrition and development. The impact evaluation is designed as a two-stage randomized control trial in which 96 communes were randomly assigned to begin receiving the program in 2014 or 2015 (early treatment) or in 2016 or 2017 (late treatment). Within a subset of the early treatment communes deemed eligible for nutrition packages, villages were randomly assigned to receive the nutrition packages or not receive them. </p>
+This dataset is from the baseline survey conducted from September 2014–February 2015, before the start of the program across 5 regions of Mali. The baseline sample was designed to be representative of Jigisemejiri beneficiaries with a child 6-23 months old. In total, 3,175 households across the 96 communes were planned to be sampled at baseline. Due to security concerns, 6 communes in Mopti were not sampled, leading to 3,080 households across 90 communes that were actually sampled in the baseline data.

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+{
+  "gardian_id": "53b58c1eb4f7cfdccd8f9cc3f0ce9962",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/163311",
+  "description": "The CGIAR Mixed Farming Systems Initiative seeks to improve the productivity, income, and resilience of mixed farming systems in Malawi. Studies have shown that this nexus is achievable through increased adoption and effective utilization of advanced agricultural technologies, supported by well-informed decision-making at all levels of the agricultural value chain. Achieving this vision relies on equipping stakeholders with the necessary skills and knowledge to manage these technologies and navigate the complexities of agricultural systems. To support this, a comprehensive capacity needs assessment was conducted, identifying skill and knowledge gaps across stakeholders in Malawi's mixed farming landscape. Based on these findings, this document presents a Capacity Development Roadmap that outlines tools and methods for targeted interventions. These interventions are tailored to enhance the roles and contributions of farmers, researchers, extension workers, cooperatives, financial institutions, am9ong other players of the mixed farming landscape in Malawi.",
+  "id": "000e7c618e71674cd9ebc7c19d7ce3c1",
+  "title": "Capacity Development Roadmap for Strengthening Stakeholder Skills, Knowledge, and Resilience of Mixed Farming Systems in Malawi",
+  "language": "English",
+  "resource_type": "Report",
+  "release_year": "2024",
+  "rights": "CC-BY",
+  "dataNODE_id": "53b58c1eb4f7cfdccd8f9cc3f0ce9962",
+  "keywords": [
+    "resilient agrifood systems",
+    "climate adaptation and mitigation",
+    "nutrition, health and food security",
+    "poverty reduction, livelihoods and jobs",
+    "sdg 1 - no poverty",
+    "sdg 2 - zero hunger",
+    "sdg 8 - decent work and economic growth",
+    "sdg 13 - climate action",
+    "sdg 15 - life on land",
+    "sdg 17 - partnerships for the goals",
+    "farming systems",
+    "capacity development",
+    "sustainable intensification",
+    "stakeholder analysis",
+    "agricultural productivity",
+    "climate resilience"
+  ],
+  "geography": {
+    "regions": [
+      "Eastern Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "World",
+      "Southern Africa"
+    ],
+    "countries": [
+      "Malawi"
+    ]
+  },
+  "content": "Mixed Farming\r\n\r\nSystems\r\n\r\nCGIAR\r\n\r\nCapacity Development Roadmap for Strengthening Stakeholder Skills, Knowledge; and Resilience of Mixed Farming Systems in Malawi.\r\n\r\nRighteous Kachali' and Vimbayi Chimonyoz\r\n\r\nAuthor affiliation\r\n\r\nPublished by\r\n\r\nNovember 2024\r\n\r\n'International Maize and Wheat Improvement Center (Malawi) and 2International Maize and Wheat Improvement Center (Zimbabwe) Consultative Group on International Agricultural Research (CGIAR)\r\n\r\nThe Sustainable Intensification of Mixed Earminq Systems Initiative aims to provide equitable; transformative pathways for improved livelihoods of actors in mixed farming systems through sustainable intensification within target agroecologies and socio-economic settings.\r\n\r\nThrough action research and development partnerships; the Initiative will improve smallholder farmers' resilience to weather-induced shocks; provide a more stable income and significant benefits in welfare; and enhance social justice and inclusion for 13 million people by 2030.\r\n\r\nActivities will be implemented in six focus countries globally representing diverse mixed  farming systems as follows:  Ghana (cereal-root crop mixed), Ethiopia (highland mixed), Malawi: (maize mixed) , Bangladesh (rice mixed), Nepal (highland mixed), and Lao People's Democratic Republic (upland intensive mixed/ highland extensive mixed).\r\n\r\n2024\r\n\r\nBY This publication is licensed for use under the Creative Commons Attribution 4.0 International Licence\r\n\r\nUnless otherwise noted, you are free to share (copy and redistribute the material in any medium or format) adapt (remix; transform; and build upon the material) for any purpose; even commercially; under the following conditions:\r\n\r\nATTRIBUTION. The work must be attributed; but not in any way that suggests endorsement by the publisher or the author(s) .\r\n\r\nTABLE OF CONTENTS\r\n\r\n| TABLE OF CONTENTS                                                                      |\r\n|----------------------------------------------------------------------------------------|\r\n| ABBREVIATIONS AND ACRONYMS _                                                           |\r\n| Executive Summary                                                                      |\r\n| Introduction                                                                           |\r\n| Training Needs for Enhanced Skills and Knowledge in Technical Aspects of Mixed Farming |\r\n| Framework for Capacity Development Implementation: Strategies and Key Consideration    |\r\n| Monitoring, Knowledge Flows, and Evaluation in Mixed Farming Systems.9                 |\r\n| Conclusion and Recommendations 10                                                      |\r\n| References _ 0000000                                                                   |\r\n\r\nABBREVIATIONS AND ACRONYMS\r\n\r\n| SI-MFS   | Sustainable Intensification of Mixed Farming Systems Initiative                                     |\r\n|----------|-----------------------------------------------------------------------------------------------------|\r\n| ABC      | Alliance of   Bioversity International and the International Center for Tropical Agriculture (CIAT) |\r\n| CIMMYT   | International Maize and Wheat Improvement Center                                                    |\r\n| DARS     | Department of Agricultural Research Services- Malawi                                                |\r\n| ICARDA   | International Centre for Agricultural Research in the Areas Dry                                     |\r\n| IITA     | International Institute of Tropical Agriculture                                                     |\r\n| ILRI     | International Livestock Research Institute                                                          |\r\n| IRRI     | International Rice Research Institute                                                               |\r\n| IWMI     | International Water Management Institute                                                            |\r\n| WP       | Work Package                                                                                        |\r\n| UNDP     | United Nations Development Programme                                                                |\r\n| STEM     | Science; Technology, Engineering; and Mathematics                                                   |\r\n| FGD      | Focus Group Discussion                                                                              |\r\n| NEEF     | National Economic Empowerment Fund                                                                  |\r\n| DAECC    | District Agriculture Extension Coordinating Committee                                               |\r\n| NGOs     | Non-Governmental Organizations                                                                      |\r\n| GoM      | Government of Malawi                                                                                |\r\n| USAID    | United States Agency for International Development                                                  |\r\n| CGIAR    | Consultative Group on International Agricultural Research                                           |\r\n| IPM      | Integrated Pest Management                                                                          |\r\n| DAECC    | District Agriculture Extension Coordinating Committee.                                              |\r\n\r\nCapacity Development Roadmap for Strengthening Stakeholder Skills, Knowledge, and Resilience of Mixed Farming Systems in Malawi.\r\n\r\nExecutive Summary\r\n\r\nThe CGIAR Mixed Farming Systems Initiative seeks to improve the productivity; income; and resilience of mixed farming systems in Malawi. Studies have shown that this nexus is achievable through increased adoption and effective utilization of advanced agricultural technologies; supported by well-informed decision-making at all levels of the agricultural value chain.\r\n\r\nAchieving this vision relies on equipping stakeholders with the necessary skills and knowledge to manage these technologies and navigate the complexities of agricultural  systems. To support this; a comprehensive capacity needs assessment was conducted; identifying skill and knowledge gaps across stakeholders in Malawi's mixed farming landscape: Based on these findings; this document presents a Capacity Development Roadmap that outlines tools and methods for targeted interventions These interventions are tailored to enhance the roles and contributions of farmers; researchers; extension workers; cooperatives; financial institutions; am9ong other players of the mixed farming landscape in Malawi.\r\n\r\nIntroduction\r\n\r\nThis document provides the CGIAR Mixed Farming Systems Initiative with an implementation plan to support its Capacity Development Strategy. It offers a structured and coordinated approach to addressing the critical capacity gaps identified in Malawi's Mixed Farming Systems landscape. The roadmap outlines strategies to enhance stakeholder skills; knowledge; and collaboration;   facilitating the effective  implementation of resilient and productive mixed farming:\r\n\r\nThe capacity needs and gaps were identified through a comprehensive participatory capacity needs assessment; utilizing focus group discussions; workshops; and structured interviews across the districts of Mzimba, Kasungu; Balaka; Zomba; and Mangochi. Stakeholders including farmers; cooperatives; financial institutions; extension workers; researchers; NGOs; input suppliers; value chain actors; and local officials were actively engaged in the process.\r\n\r\nThrough participatory techniques; such as focus group discussions; the World Café approach; and structured interviews; stakeholders collaboratively identified and prioritized challenges related to technical knowledge; systems-thinking; and market access. Consequently; proposed various capacity interventions essential for effectively addressing these challenges (Kachali et al., 2024). they\r\n\r\nThis roadmap seeks to facilitate the implementation of co-created innovations; such as crop-livestock integration; maize-legumelforage integration; and other climate-resilient   technologies in Malawi's mixed farming systems.\r\n\r\nThe objectives of this roadmap are to:\r\n\r\n- Guide capacity-building efforts to address identified gaps in mixed farming practices.\r\n- Provide targeted training programs and support tools to enhance stakeholder competencies\r\n- Foster collaboration among stakeholders for continuous learning and adaptation within the MFS initiative.\r\n\r\nStakeholder Analysis and Capacity Needs\r\n\r\nDuring the stakeholder engagements in the MFS districts; stakeholders classified themselves based on their level of engagement and the type of support provide to farmers. At the core are Farmers, who are the primary beneficiaries and implementers of Mixed Farming System practices. Directly supporting farmers are Agriculture Extension Workers (Crops; Animals; & Fisheries Officers) who interact closely with farmers; offering technical guidance and facilitating access to markets. they\r\n\r\nThe Directly Engaged Stakeholders include Input Suppliers; Agriculture Researchers; Value-Adding Players; Non-Governmental Organizations (NGOs), Lending Institutions; and Nutrition & Health Workers. These entities provide essential inputs; financial support; research insights; value addition; and health and nutritional services to strengthen farmers' capacity and productivity.\r\n\r\nLastly; the Systemicloverarching Stakeholders encompass bodies with regulatory or broader institutional roles; such as the Ministry of Agriculture; Off-takers; Traditional Authorities; Councillors & Members of Parliament, and Farmer Unions. These stakeholders shape policies and provide the framework within which Mixed Farming Systems can thrive\r\n\r\nThe stakeholder capacity needs workshops identified several challenges within the mixed farming landscape and proposed a range of training interventions to address these. While some challenges required stakeholders to acquire skills, information; and knowledge related to the technical aspects of sustainable mixed farming, which are often technology-driven or goal-specific; others called for systems-thinking skills to build stakeholders' ability to continuously innovate and adapt to changes in the farming landscape:\r\n\r\nIn addition to evaluating the level of engagement and type of support stakeholders provide to farmers, stakeholders in the mixed   farming landscape of Malawi were categorized based on their power to influence pathways; policies; decisions; or norms, and their interest in shaping the mixed farming systems. Different stakeholders expressed   opinions on which actors hold the most interest and power in the landscape across districts A consolidated Power-Interest Grid was developed to categorize stakeholders working within the mixed farming systems; providing insights into their potential roles in influencing or shaping the sector. Interestingly; the analysis revealed consistency across districts regarding power-Interest stakeholder categorization:\r\n\r\nThe Power-Interest Grid classifies stakeholders in Malawi's Mixed Farming Systems Initiative based on their power to influence policies; decisions; and norms; as well as their level of interest in the outcomes of mixed farming systems.\r\n\r\nStakeholders in the High Power - High Interest category include the Malawi Government/Ministry of Agriculture; Farmer Unions and Cooperatives; and Agriculture Extension Workers These groups were reported critical in shaping agricultural policy; providing support to farmers; and driving the implementation of mixed farming practices.\r\n\r\nIn the High Power_Low Interest category were Lending Institutions; Ward Councillors; MPs, and Traditional Authorities/Chiefs Despite their authority to settle land and farming issues and influence norms regarding farming operations; impact financing, and policy frameworks; their direct interest in the specifics of mixed farming systems remains limited. Their focus tends to be broader; often centered on financial returns or political agendas.\r\n\r\nThe High Interest Low Power stakeholders; including Non-Governmental Organizations (NGOs), Input Suppliers; Off-takers/alue Adding Players; Agriculture Researchers; and Farmers; are deeply involved in the operational aspects of mixed farming. Despite their enthusiasm and active participation; these groups have limited power to influence national policies or large-scale decisions; but play a crucial role in the practical implementation of the systems. they\r\n\r\nFigure 1: Power-Interest Grid for Mixed Farming Systems Stakeholders on Malawi\r\n\r\nMalawi Government/Ministry\r\n\r\nFarmers\r\n\r\nof Agriculture\r\n\r\nNon-Governmental\r\n\r\nFarmer Unions and\r\n\r\nHigh\r\n\r\nOrganizations (NGOs)\r\n\r\nCooperatives\r\n\r\nInterest\r\n\r\nInput Suppliers\r\n\r\nAgriculture Extension Workers\r\n\r\nAgriculture Researchers\r\n\r\n1\r\n\r\nOff-takersNalue Adding Players\r\n\r\nLending Institutions\r\n\r\nLow\r\n\r\nWard Councillors & MPs\r\n\r\nInterest\r\n\r\nTraditional Authorities/chiefs\r\n\r\nLow Power\r\n\r\nHigh Power\r\n\r\nPower\r\n\r\nThe results of the stakeholder analysis   provide a clear pathway for prioritizing   capacity development efforts in Malawi's Mixed Farming Systems (MFS). Given the diverse roles and varying levels of power and interest among stakeholders; a strategic approach to capacity enhancement is required to ensure that resources are allocated efficiently, and impact is maximized. It is critical to acknowledge that not all stakeholder capacities can be developed simultaneously; therefore; capacity development must be linked to the roles stakeholders play; their engagement level with farmers; and their   position within the Power - Interest Grid. Stakeholders in the High Power - High Interest category; such as the Malawi Government/Ministry of Agriculture; Farmer Unions and Cooperatives; and Agriculture Extension Workers should be prioritized in capacity development efforts. These stakeholders are decision-makers and directly influence policy and practice in the mixed farming landscape. Their ability to drive change and implement innovations effectively makes them the first candidates for capacity-building programs; particularly in areas such as systems-thinking;  decision-making frameworks; and integrated mixed farming technologies. Previous studies have shown that empowering high-power stakeholders with enhanced skills in policy advocacy, program implementation; and monitoring can lead to transformative sector-wide improvements (Kassie et al., 2015; Meijer et al., 2015) Next in line are stakeholders with High Interest but Low Power, including NGOS, Input Suppliers; Off-takers/alue Adding Players; Agriculture Researchers; and Farmers. Deeply involved in the day-to-day implementation of mixed farming practices; these groups play a critical role in operations but have limited influence over high-level policy or resource allocation. According to Leeuwis and Aarts; (2011), capacity-building efforts for these stakeholders should emphasize technical skills; such as sustainable farming practices; market linkages; and value-chain development. By enhancing their capacity to innovate and adapt to changing agricultural conditions; the operational aspects of mixed farming systems can be significantly strengthened. Research by Vanlauwe; Coe; et al., (2019) highlights how improving the technical capabilities of such actors creates strong feedback loops that contribute to continuous learning and refined practices at the grassroots level. For stakeholders in the High Power-Low Interest quadrant; such as Lending Institutions and Ward Councillors & MPs; capacity development should adopt a more targeted approach. While these groups wield considerable influence over financing and policy frameworks; their direct engagement with mixed farming systems remains limited. Klapper and Lusardi, 2020) suggest that capacity-building programs for these stakeholders should aim to align their interests with mixed farming objectives; particularly by fostering   political support for agricultural innovations and developing favourable financial products for farmers. Engaging effectively with these key stakeholders could enhance financial access and create a more supportive regulatory environment for farmers.\r\n\r\nTraining Needs for Enhanced Skills and Knowledge in Technical Aspects of Mixed Farming\r\n\r\nStakeholders identified both technical and systems-thinking   capacity needs based on the challenges and aspirations they face in mixed farming: These needs were outlined by each stakeholder group and validated by others through focus group discussions and the World Café approach. Below (Table 7) is a consolidated list of interventions demanded by stakeholders in the mixed farming landscape of Malawi; summarizing the key capacity needs of MFS stakeholders\r\n\r\nExtension workers expressed a strong demand for modern extension tools and technology and climate-smart farming techniques; showing the need for skills to support farmers in adapting to climate change:  They also emphasized financial management literacy; market linkages; and project monitoring and evaluation; while transportation and route planning was noted as a logistical need. Cooperatives prioritized leadership and communication and management of inputs and facilities as critical areas for strengthening their operations.  There was also significant focus on market  linkage and collective bargaining skills and skills for asset and income generation to improve financial resilience and market access.\r\n\r\nfarming strategies and livestock management and breeding  reflecting their need for practical guidance and improved animal husbandry. They also stressed efficient use of seeds and fertilizers; market linkages and value addition; sustainable grazing and feed production; and farm mechanization: Agriculture researchers identified grant proposal   writing and funding strategies and modern data analysis tools as to supporting research sustainability. They also noted the importance of   advanced research techniques and policy advocacy and strategic planning to influence broader agricultural development. key\r\n\r\nValue chain actors highlighted the need for business finance management and loan application skills and certification and export   compliance procedures; along with an emphasis on understanding climate-smart and eco-friendly agricultural inputs to align with sustainability goals. NGOs focused on principles of effective extension work; knowledge of seed quality and viability, and techniques in water management and irrigation to improve their impact in the agricultural sector. Value chain development and program management strategies were also areas of need:. Lending institutions showed the highest demand for financial literacy for agriculture clients and agri-business familiarization training, highlighting the need to improve client financial management. key\r\n\r\nTable 1: Stakeholder Capacity Needs and Demand Levels Across Mixed Farming System Roles in Malawi\r\n\r\n| Stakeholder                                  | Capacity needs                                          |   Proportion of Stakeholders Expressing Demand |\r\n|----------------------------------------------|---------------------------------------------------------|------------------------------------------------|\r\n| Extension                                    | Modern extension tools and technology                   |                                             75 |\r\n| Workers/Ministry of                          | Climate-smart farming techniques                        |                                             72 |\r\n| Agriculture (Total: 33)                      | Financial management literacy                           |                                             65 |\r\n| (Males n=-15; Females n-18                   | Market linkages                                         |                                             65 |\r\n|                                              | Project Monitoring and evaluation                       |                                             61 |\r\n|                                              | Transportation and route planning                       |                                             45 |\r\n|                                              | Leadership and communication                            |                                             80 |\r\n| Farmer Cooperatives                          | Management of inputs and facilities                     |                                             75 |\r\n| (Total: 15) (Males n=6; Females              | Market linkage and collective bargaining skills         |                                             65 |\r\n| n-9)                                         | Skills Asset and Income Generation for                  |                                             60 |\r\n| n-9)                                         | Decision Tools for Selecting Mixed Farming Strategies   |                                                |\r\n| n-9)                                         | Livestock management and breeding                       |                                                |\r\n| n-9)                                         | Efficient use of seeds and fertilizers                  |                                                |\r\n| Farmers (Total: 89) (Males n=52;             | Market linkage strategies and value addition            |                                             65 |\r\n| Females n=37)                                | Sustainable grazing and feed production                 |                                             65 |\r\n| Females n=37)                                | Farm mechanisation                                      |                                             65 |\r\n| Females n=37)                                | Integrated pest management (IPM)                        |                                             60 |\r\n|                                              | Water conservation and irrigation                       |                                             60 |\r\n|                                              | Farm business management                                |                                             55 |\r\n|                                              | Soil health management                                  |                                             50 |\r\n| Agriculture                                  | Grant proposal writing and funding strategies           |                                             70 |\r\n| Researchers (Total: 22) (Males n-I3; Females | Advanced research techniques                            |                                             60 |\r\n| n-9)                                         | Policy advocacy and strategic planning                  |                                             50 |\r\n|                                              | Modern data analysis tools                              |                                             75 |\r\n| Value Chain Actors                           | Business Finance Management and Loan Application Skills |                                             50 |\r\n| (Total: 28)                                  | Certification and Export Compliance Procedures          |                                             55 |\r\n\r\n| (Males n-15; Females n=13)            | Knowledge of Agricultural Product Quality Standards and Best Practices                    |   60 |\r\n|---------------------------------------|-------------------------------------------------------------------------------------------|------|\r\n|                                       | Understanding Climate-Smart and Eco- Friendly Agricultural Inputs and their Usage_        |   65 |\r\n|                                       | Principles of Effective Extension Work                                                    |   65 |\r\n|                                       | Knowledge of Seed Quality and Viability                                                   |   65 |\r\n| Non-Governmental Organizations (NGOs) | Techniques in Water Management and Irrigation                                             |   60 |\r\n| (Total: 25)                           | Fundamentals of Value Chain Development                                                   |   60 |\r\n| (Males n=12; Females n-13)            | Strategies for Program Management and Collaboration                                       |   55 |\r\n|                                       | Community Engagement and Participatory Methods                                            |   55 |\r\n|                                       | Sourcing and managing financial resources                                                 |   50 |\r\n| Lending                               | Financial literacy for agriculture clients                                                |      |\r\n| Institutions (Total: 14) (Males n=-8; | Agri-Business Familiarization Training                                                    |   75 |\r\n| Females n=6)                          | Development of diverse and specialized Ioan products tailored for the agricultural sector |   61 |\r\n\r\nFramework for Capacity Development Implementation: Strategies and Key Consideration\r\n\r\nTwo capacity domains were identified as central to enhancing capacity within the mixed farming landscape: technical needs and systems-thinking needs. Technical needs focus on the practical skills and knowledge required to effectively use mixed farming tools and technologies; enabling stakeholders to meet specific goals within the farming system. Systemsthinking needs; in contrast involve building skills to recognize and understand the interconnections within the farming stakeholders to make decisions that account for how components such as production; marketing; and environmental sustainability interact to impact overall resilience and income stability. Systems-thinking skills are particularly valuable as they help stakeholders analyse interactions within the agricultural system and make informed decisions that support the broader farming ecosystem: key\r\n\r\nThe capacity development framework is developed to address these needs through a holistic and user-centered approach; enabling stakeholders to build skills at a pace; in spaces; and within contexts that best support their learning: The tools and methods proposed bridge what and how stakeholders want to learn with practical ways to deliver this knowledge within their economic; technological, and social settings. Workshops; trainings; and demonstrations will be specifically tailored to not only provide these skills effectively but also to motivate ongoing practice and reinforcement; with follow-up support:.\r\n\r\nTable 2outlines the tailored capacity development approaches designed for each stakeholder in Malawi's mixed farming systems. For each identified need, there are development methods proposed, such as workshops; practical demonstrations; or training modules;   detailing the specific contexts these methods are best suited for. It also identifies partnerships necessary to enhance  training effectiveness. Each entry further assesses the resource implications associated with each method, including time requirements; financial costs; and infrastructure needs. This structured approach; adopted from Framework; 2008, is intended to allow for efficient planning by directly linking capacity-building actions with the operational needs and strengths of each stakeholder group. key In developing capacity enhancement programs for stakeholders in Malawi's mixed farming systems; it is essential to consider several factors that ensure targeted; impactful, and sustainable outcomes. The developmental impact of any capacity initiative should be at the forefront of planning; as it defines the tangible benefits that the program will bring to the farming systems. This impact may vary across stakeholders from improving market   linkages and agricultural resilience to fostering the adoption of climate-smart practices By setting clear expectations for developmental outcomes; programs can align their activities to address pressing needs within the agricultural sector and yield meaningful results: key Equally critical is determining the level of focus for capacity enhancement. Capacity-building activities may target individual skills; organizational efficiencies; or broader systems and institutions; each with distinct goals and implications. For instance; focusing on individual   skill-building in technical areas like livestock management or crop production equips stakeholders to implement immediate changes on the ground. Conversely; targeting broader systems such as policy advocacy within research institutions or improved financial management for cooperatives aims at creating sustained structural improvements that can positively affect the entire farming ecosystem: Choosing the appropriate focus level ensures that resources are allocated where they will have the most significant and far-reaching impact.\r\n\r\nTable 2: Stakeholder Capacity Development Methods; Targeted Capacities; and their Resource Implications\r\n\r\n| Stakeholder group   | Capacity Need                                                                                                                                          | Capacity Development Method                                                                                                                                                                                          | Useful for?                                                                                                                                                                                                                                                                                                                                                                                                                   | Helped by?                                                                                                                                                                                                                                                                                                                             | Resource Implications                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |\r\n|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\r\n|                     | Modern extension tools and technology Climate-smart farming techniques Financial management literacy Project Monitoring and Evaluation Market linkages | Workshops & Practical Demonstrations Training on Information Access & Verification Workshops Financial Literacy Training Programs & Manuals Workshops on Monitoring Tools & Techniques Workshops & Networking Events | Building capacity to utilize and adapt modern extension tools and technologies Equipping workers with skills to access; assess; and apply emerging climate- smart technologies Strengthening financial planning and literacy for project and resource management Enhancing ability to implement; monitor; and evaluate mixed farming projects Connecting extension workers with market players and understanding value chains | Collaboration with technology providers; field experts Access to online platforms; climate data providers; and technology specialists Agricultural finance experts; NGOs providing funding support M&E specialists; software providers for data collection and analysis Market linkage experts; agribusiness specialists; cooperatives | Time for training; adequate technological infrastructure, trainers with technical skills, financial investment purchasing or hiring tools and conducting workshops Time for continuous learning; access to reliable information sources; trainers skilled in climate- smart methods; funding for access to online resources and trainers Training manuals; financial tools; time commitment for hands-on practice; costs associated with running the training sessions and providing financial tools Time for fieldwork, project management tools; skilled trainers; project documentation; funding for tools and software licenses Time for networking; skills in communication and negotiation; moderate infrastructure costs, budget for organizing events and travel expenses for |\r\n\r\n|   Stakeholder group | Capacity Need                                                                           | Capacity Development Method Leadership Training                                                                        | Useful for?                                                                                                                                                                 | Helped by?                                                                                                    | Resource Implications                                                                                                                                                                                               |\r\n|---------------------|-----------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\r\n|                     | Leadership and communication                                                            | Strengthening Workshops & Communication Skills and improving Seminars cooperative communication for better decision-   | leadership capacities making and coordination                                                                                                                               | Leadership experts; communication specialists; NGO facilitators                                               | Time workshop preparation; skilled trainers; moderate cost associated with venues, materials, and facilitators for                                                                                                  |\r\n|                     | Management of inputs and facilities                                                     | Workshops on Inventory Management & Best Practices in Facility Use                                                     | Improving efficiency in the management of agricultural inputs and cooperative facilities                                                                                    | Supply chain experts; facility management professionals                                                       | Time investment; skilled facilitators; moderate cost for training materials; venue; and logistical support                                                                                                          |\r\n|                   1 | Market linkage and collective bargaining skills Skills for Asset and Income Generation  | Networking Events & Training in Negotiation & Market Analysis Financial Literacy Training & Asset Management Workshops | Enhancing skills in market negotiation and building stronger market linkages Enabling cooperatives to effectively manage assets and generate                                | Market linkage specialists; agribusiness experts Financial experts; cooperative development trainers          | Time for networking and workshops; moderate to high cost for event organization and expert facilitation Time for training; moderate cost for skilled trainers and learning materials                                |\r\n|                     | Decision Tools for Selecting Mixed Farming Strategies Livestock management and breeding | Workshops on Decision - Making Tools & Scenario Analysis On-Farm Demonstrations & Breeding Training Programs           | sustainable income Equipping farmers with decision - making skills to optimize farming strategies Enhancing knowledge of livestock breeding, care; and management practices | Agricultural extension experts; farming systems analysts Veterinary specialists; livestock management experts | Moderate costs for workshops; time investment; and facilitators for scenario-based learning High cost due to on-farm demonstrations; experts; and livestock resources; requires substantial time and infrastructure |\r\n\r\n| Stakeholder group   | Capacity Need                                | Capacity Development Method                                            | Useful for?                                                                                                                                                                                          | Helped by?                                                  | Resource Implications                                                                  |\r\n|---------------------|----------------------------------------------|------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------|----------------------------------------------------------------------------------------|\r\n|                     | Efficient use of seeds and fertilizers       | Practical Workshops on Seed Selection & Fertilizer Application         | Teaching optimal seed and fertilizer use for increased productivity Building farmer capacity to access markets and enhance product value Promoting health to mechanized farming tools and techniques | Agricultural input specialists; seed and fertilizer experts | Moderate costs for venue; training materials; and agricultural input samples           |\r\n|                     | Market linkage strategies and value addition | Market Linkage Forums & Value-Addition Workshops                       |                                                                                                                                                                                                      | Agribusiness experts; value-chain specialists               | Moderate to high costs depending on scale of forums and value- addition demonstrations |\r\n|                     | Sustainable grazing and feed production      | Sustainable Grazing Workshops & On-Farm Feed Production Demonstrations | sustainable grazing and feed production to improve livestock                                                                                                                                         | Grazing and pasture experts; livestock nutritionists        | High costs for feed production demonstrations and grazing resource management          |\r\n|                     | Farm mechanization                           | Mechanization Training & Demonstrations                                | Introducing farmers                                                                                                                                                                                  | Agricultural engineering experts; mechanization trainers    | High costs due to machinery requirements and on-field demonstration logistics          |\r\n|                     | Integrated pest management (IPM)             | Workshops on IPM Practices & Biological Control Techniques             | Enabling farmers to control pests using sustainable and eco- friendly methods                                                                                                                        | Entomologists; IPM specialists                              | Moderate costs for workshops, materials; and biological control agents                 |\r\n|                     | Water conservation and irrigation            | Field Demonstrations on Water Conservation & Irrigation Techniques     | Improving water management and irrigation practices to boost crop productivity                                                                                                                       | Irrigation experts; water management specialists            | High cost due to field demonstrations and infrastructure needs for irrigation systems  |\r\n|                     | arm business management                      | Training on Financial Planning & Farm Management                       | Strengthening farmers' ability to manage farm operations and finances                                                                                                                                | Agribusiness consultants, financial management experts      | Moderate costs for training, skilled consultants; and financial tools                  |\r\n\r\n|   Stakeholder group | Capacity Need                                                                                                                                | Capacity Development Method                                                                                                                                                                                                  | Useful for?                                                                                                                                                                                                                                         | Helped by?                                                                                                                                                                                   | Resource Implications                                                                                                                                                                                                                                                                                                                       |\r\n|---------------------|----------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\r\n|                     | Soil health management                                                                                                                       | Soil Health Workshops & On-Farm Soil Testing Demonstrations                                                                                                                                                                  | Enhancing understanding of soil management for sustainable farming                                                                                                                                                                                  | Soil scientists; agronomists                                                                                                                                                                 | High costs for soil testing equipment and expert facilitators for demonstrations                                                                                                                                                                                                                                                            |\r\n|                   1 | Grant proposal writing and funding strategies Advanced research techniques Policy advocacy and strategic planning Modern data analysis tools | Workshops on Grant Writing and Funding Acquisition Training Programs in Cutting-Edge Research Methodologies Workshops on Policy Engagement & Strategic Planning Courses on Data Analysis Software and Statistical Techniques | Equipping researchers with skills to develop competitive funding proposals Enhancing research skills to adopt new; innovative methodologies Enabling researchers to influence policy through advocacy analyse complex agricultural data effectively | Grant writing specialists; funding agencies Research methodologists; experienced researchers Policy experts; strategic planning specialists Data scientists, statisticians; software experts | Moderate costs for workshops; skilled facilitators; and proposal writing materials High costs due to specialized training programs; expert facilitators; and technology requirements Moderate costs for expert-led workshops and policy engagement materials High costs for software licenses; specialized training programs; and equipment |\r\n|                     | Business Finance Management and Loan Application Skillsfication and Export Compliance Procedures                                             | Financial Management Training and Loan Application Workshops Workshops on Export Compliance and Certification Standards                                                                                                      | Building skills in managing finances and applying for agricultural loans Understanding the certification processes for agricultural exports                                                                                                         | Financial experts; lending institutions Export agencies; trade experts                                                                                                                       | Moderate costs for expert facilitators; financial tools, and venue setup Moderate costs for expert-led workshops and export compliance materials                                                                                                                                                                                            |\r\n\r\n|   Stakeholder group | Capacity Need                                                                     | Capacity Development Method                                   | Useful for?                                                           | Helped by?                                                              | Resource Implications                                                          |\r\n|---------------------|-----------------------------------------------------------------------------------|---------------------------------------------------------------|-----------------------------------------------------------------------|-------------------------------------------------------------------------|--------------------------------------------------------------------------------|\r\n|                     | Knowledge of Agricultural Product Quality Standards and Best Practices            | Training Programs on Product Quality Standards                | Ensuring agricultural products meet local and international standards | Agricultural quality control agencies; industry standards organizations | Moderate costs for training programs and access to quality standards resources |\r\n|                     | Understanding Climate-Smart and Eco- Friendly Agricultural Inputs and their Usage | Seminars on Climate- Smart Agriculture and Sustainable Inputs | Promoting the adoption of eco- friendly inputs in agriculture         | Environmental scientists; agronomists                                   | Moderate costs for organizing seminars and procuring relevant materials        |\r\n|                   1 | Principles of Effective Extension Service Delivery                                | Workshops and Training on Extension Service Principles        | Strengthening NGO capacity to deliver high-quality agricultural       | Extension experts; agriculture institutions                             | Moderate costs for workshops; materials; and expert facilitators               |\r\n|                     | Knowledge of Seed Quality and Viability                                           | Workshops on Seed Quality and Management Practices            | ability to promote good seed practices among farmers                  | Seed certification agencies; agricultural researchers                   | Moderate costs for expert-led workshops and seed quality tools                 |\r\n|                   1 | Fundamentals of Value Chain Development                                           | Training Programs on Value Chain Analysis and Development     | Building knowledge in developing sustainable value chains for         | Value chain experts, economists                                         | Moderate costs for training and value chain analysis materials                 |\r\n|                     | Strategies for Program Management and Collaboration                               | Training in Program Management and Collaborative Approaches   | with the tools to manage agricultural programs effectively            | Program management specialists; collaboration facilitators              | Moderate costs for training and collaboration tools                            |\r\n\r\n|   Stakeholder group | Capacity Need                                                                        | Capacity Development Method                                                                                                                                                     | Useful for?                                                                                                       | Helped by?                                                                                                                     | Resource Implications                                                                                                          |\r\n|---------------------|--------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|\r\n|                     | Community Engagement and Participatory Methods Organization                          | Workshops Participatory Approaches and Stakeholder Engagement Financial Management on                                                                                           | Improving NGOs' skills in engaging communities in decision-making processes Ensuring financial accountability and | Community development experts                                                                                                  | Moderate costs for organizing participatory workshops and sessions Moderate costs for financial                                |\r\n|                     | Financing and Integrity with Donor Funds                                             | and Donor Compliance Training                                                                                                                                                   | effective use of donor funds                                                                                      | Donor agencies; financial management experts                                                                                   | workshops and compliance materials                                                                                             |\r\n|                   1 | Financial literacy for agriculture clients                                           | Conduct workshops and develop practical training modules on financial literacy for agriculture: Focus on managing agriculture-based loans and understanding farming cash flows. | Enhancing the ability to manage agricultural clients and better understand their financial needs.                 | Support from financial experts in agriculture and tailored case studies for agricultural finance:                              | Moderate costrequires financial experts and well-structured learning modules. Some infrastructure (training spaces) needed.    |\r\n|                   1 | Agri-Business Familiarization Training                                               | Structured seminars and on-the-job training to familiarize with the unique aspects of agri - business; such as risk management and market fluctuations.                         | Building competency in handling agriculture businesses and understanding sector-specific challenges and           | Trainers with experience in agri - business sectors and real-life case studies for practical application:                      | Moderate cost_needs expert trainers and access to agri - business resources.                                                   |\r\n|                   1 | Development of diverse and specialized loan products tailored for agriculture sector | Technical workshops and collaborative meetings to co-create specialized loan products. Design innovative loan models considering crop cycles; climate risks, and seasonality.   | development of loan products that respond to the needs of diverse agriculture sectors and conditions.             | Collaboration with agriculture sector experts; risk analysts; and financial product designers for innovation in loan products. | High cost-requires collaboration; development time; expert consultants; and infrastructure (meeting venues; online resources). |\r\n\r\nTo achieve these developmental goals; it is essential to adopt suitable process improvement procedures that align with the specific needs and goals of the stakeholders: Tailored process improvements; like conducting hands-on workshops for farmers or establishing networking platforms for cooperatives; facilitate the effective and sustained implementation of skills and practices. Each improvement process should be carefully designed to yield desired performance outcomes;   ensuring stakeholders develop the competencies needed to drive progress within the mixed farming landscape.\r\n\r\nAnother essential aspect is the focus on capacity domains; distinguishing between technical skills such as the practical knowledge required for specific farming practices and systems thinking skills; which equip stakeholders to adapt to complex agricultural environments. Systems thinking skills are particularly valuable; as they enable stakeholders to analyse interactions within the agricultural system and make informed decisions that support the broader farming ecosystem:\r\n\r\nTable 4 provides a structured overview of how capacity development interventions align with developmental impacts; capacity and performance; and process improvements across various stakeholders in Malawi's mixed farming systems adapted from Morgan; 1998). It details the specific focus level targeted by each capacity development need and identifies the capacity domain enhanced by each proposed method.\r\n\r\nTable 1: Summary of Stakeholder Training Needs; Focus Levels; and Capacity Building Impact in Mixed Farming Systems\r\n\r\n| Stakeholder Group                 | Training Needs                        | Level of Focus       | Developmental                                      | Capacity & Performance                                       | Process Improvement                               | Capacity domains               |\r\n|-----------------------------------|---------------------------------------|----------------------|----------------------------------------------------|--------------------------------------------------------------|---------------------------------------------------|--------------------------------|\r\n|                                   | Modern extension tools and technology | Individual           | Improved use of modern tools in extension services | Enhanced technological skills                                | Improved extension services                       | Technical                      |\r\n|                                   | Climate-smart farming techniques      | Individual           | Adoption of sustainable farming practices          | Improved ability to assess and adopt climate-smart practices | Improved adoption of new techniques               | Technical and Systems Thinking |\r\n| literacy                          | Financial management                  | Organizational       | Improved financial management capacity             | Stronger financial management                                | Better financial planning and resource management | Technical and Systems Thinking |\r\n| Project Monitoring and Evaluation |                                       | Organizational       | Enhanced project oversight and evaluation          | Better project tracking and evaluation                       | Better project evaluation systems                 | Technical and Systems Thinking |\r\n| Market linkages                   | Broader                               | SystemslInstitutions | Improved market linkages                           | Enhanced ability to form market linkages                     | Improved market systems                           | Technical and Systems Thinking |\r\n\r\n|   Stakeholder Group | Training Needs                                        | Level of Focus               | Developmental                                    | Capacity & Performance                | Process Improvement                   | Capacity domains               |\r\n|---------------------|-------------------------------------------------------|------------------------------|--------------------------------------------------|---------------------------------------|---------------------------------------|--------------------------------|\r\n|                     | Leadership and communication                          | Individual                   | Strengthened leadership in cooperatives          | Improved communication skills         | Improved decision - making processes  | Technical and Systems Thinking |\r\n|                   1 | Management of inputs and facilities                   | Organizational               | Improved management of inputs and facilities     | Better input and facility management  | Better facility and input utilization | Technical                      |\r\n|                     | Market linkage and collective bargaining skills       | Organizational               | Stronger market negotiations                     | Improved market negotiation skills    | Improved market access                | Technical and Systems Thinking |\r\n|                     | Skills for Asset and Income Generation                | Broader SystemslInstitutions | Increased income generation and asset management | Stronger asset management             | Better income management              | Technical and Systems Thinking |\r\n|                     | Decision Tools for Selecting Mixed Farming Strategies | Individual                   | Improved decision-making for farm strategies     | Better decision - making capabilities | Better decision - making tools        | Technical and Systems Thinking |\r\n|                     | Livestock management and breeding                     | Individual                   | Enhanced livestock health and productivity       | Improved livestock management         | Better livestock health management    | Technical                      |\r\n\r\n| Stakeholder Group   | Training Needs                               | Level of Focus               | Developmental                                     | Capacity & Performance                                | Process Improvement                    | Capacity domains               |\r\n|---------------------|----------------------------------------------|------------------------------|---------------------------------------------------|-------------------------------------------------------|----------------------------------------|--------------------------------|\r\n|                     | Efficient use of seeds and fertilizers       | Individual                   | Optimized seed and fertilizer use                 | Enhanced input use                                    | Improved seed and fertilizer practices | Technical                      |\r\n|                     | Market linkage strategies and value addition | Broader SystemslInstitutions | Improved market access and product value          | Improved market participation                         | Improved market access                 | Technical and Systems Thinking |\r\n|                     | Sustainable grazing and feed production      | Broader SystemslInstitutions | Sustainable livestock grazing and feed production | Better livestock management and grazing practices     | Sustainable livestock management       | Technical and Systems Thinking |\r\n|                     | Farm mechanization                           | Individual                   | Increased mechanization for productivity          | Improved adoption of mechanization                    | Increased use of mechanization         | Technical                      |\r\n|                     | Integrated pest management (IPM)             | Broader SystemslInstitutions | Sustainable pest management                       | Improved pest management                              | Improved pest control practices        | Technical                      |\r\n|                     | Water conservation and irrigation            | Broader SystemslInstitutions | Improved water use and irrigation efficiency      | Enhanced water conservation and irrigation techniques | Better water use                       | Technical and Systems Thinking |\r\n|                     | Farm business management                     | Organizational               | Improved farm business practices                  | Better farm management practices                      | Improved business management           | Technical and Systems Thinking |\r\n\r\n| Stakeholder Group   | Training Needs                                                         | Level of Focus               | Developmental                                          | Capacity & Performance                  | Process Improvement                      | Capacity domains               |\r\n|---------------------|------------------------------------------------------------------------|------------------------------|--------------------------------------------------------|-----------------------------------------|------------------------------------------|--------------------------------|\r\n|                     | Grant proposal writing and funding strategies                          | Individual                   | Increased funding for research                         | Stronger proposal writing skills        | Increased research funding               | Technical                      |\r\n| 1                   | Advanced research techniques                                           | Individual                   | Innovative research methodologies adopted              | Improved research capacity              | Adoption of advanced research techniques | Technical                      |\r\n|                     | Policy advocacy and strategic planning                                 | Broader SystemslInstitutions | Influence on agricultural policy and planning          | Better policy engagement                | Improved policy advocacy                 | Technical and Systems Thinking |\r\n|                     | Modern data analysis tools                                             | Organizational               | Enhanced data analysis capabilities                    | Improved data management skills         | Improved data analysis systems           | Technical and Systems Thinking |\r\n| Loan Skills         | Business Finance Management and Application                            | Individual                   | Improved access to finance for agricultural businesses | Better financial management skills      | Better access to finance                 | Technical and Systems Thinking |\r\n| Certification and 8 | Export Compliance Procedures                                           | Organizational               | Improved compliance with certification standards       | Improved export procedures              | Better certification processes           | Technical and Systems Thinking |\r\n|                     | Knowledge of Agricultural Product Quality Standards and Best Practices | Broader SystemslInstitutions | Enhanced product quality for export                    | Better understanding of product quality | Improved product quality                 | Technical and Systems Thinking |\r\n\r\n|   Stakeholder Group | Training Needs                                                                   | Level of Focus               | Developmental                                   | Capacity & Performance                   | Process Improvement              | Capacity domains               |\r\n|---------------------|----------------------------------------------------------------------------------|------------------------------|-------------------------------------------------|------------------------------------------|----------------------------------|--------------------------------|\r\n|                     | Understanding Climate-Smart and Eco-Friendly Agricultural Inputs and their Usage | Broader SystemslInstitutions | Adoption of climate-smart inputs                | Improved knowledge of sustainable inputs | Better use of sustainable inputs | Technical and Systems Thinking |\r\n|                     | Principles of Effective Extension Service Delivery                               | Organizational               | Improved delivery of extension services         | Improved extension service practices     | Improved extension services      | Technical and Systems Thinking |\r\n|                     | Knowledge of Seed Quality and Viability                                          | Individual                   | Improved seed quality management                | Enhanced seed quality knowledge          | Improved seed management         | Technical                      |\r\n|                   1 | Fundamentals of Value Chain Development                                          | Broader SystemslInstitutions | Better understanding of value chain development | Better understanding of value chains     | Better value chain development   | Technical and Systems Thinking |\r\n|                     | Strategies for Program Management and Collaboration                              | Broader SystemslInstitutions | Improved program management                     | Stronger program management              | Better program coordination      | Technical and Systems Thinking |\r\n|                     | Community Engagement and Participatory Methods                                   | Broader SystemslInstitutions | Enhanced community engagement                   | Improved participatory methods           | Better stakeholder engagement    | Technical and Systems Thinking |\r\n\r\n| Stakeholder Group   | Training Needs                                                                | Level of Focus               | Developmental                                     | Capacity & Performance                        | Process Improvement             | Capacity domains               |\r\n|---------------------|-------------------------------------------------------------------------------|------------------------------|---------------------------------------------------|-----------------------------------------------|---------------------------------|--------------------------------|\r\n|                     | Organization Financing and Integrity with Donor Funds                         | Individual                   | Improved financial accountability                 | Improved financial management                 | Better financial management     | Technical and Systems Thinking |\r\n|                     | Financial literacy for agriculture clients                                    | Organizational               | Improved financial literacy                       | Better financial literacy                     | Better financial management     | Technical and Systems Thinking |\r\n|                     | Agri-Business Familiarization Training                                        | Individual                   | Enhanced understanding of agribusiness challenges | Improved agribusiness knowledge               | Better agribusiness knowledge   | Technical and Systems Thinking |\r\n|                     | Development of diverse and specialized loan products tailored for agriculture | Broader SystemslInstitutions | Development of tailored financial products        | Enhanced ability to create financial products | Better loan product development | Technical and Systems Thinking |\r\n\r\nMonitoring, Knowledge Flows, and Evaluation in Mixed Farming Systems\r\n\r\nCapacity development initiatives within Malawi's mixed farming systems will ultimately transition from planning to active implementation: This process demands a well-defined framework that supports the monitoring of knowledge flows; fosters   knowledge-sharing and encourages continuous learning through systematic evaluation (adopted from Adesina et al., 2014). A structured approach to monitoring and evaluating these flows is essential for adapting interventions to meet evolving stakeholder needs within the dynamic agricultural landscape:\r\n\r\nKnowledge flows within this framework will follow a structured path among data collection; insight; Gap Analysis & Prioritization; Capacity Program Development and implementation; and validation: Data, insights; and feedback collected undergo rigorous prioritization through gap analysis. Following this;   capacity program development is conducted.\r\n\r\nThe implementation and validation phase then evaluates outcomes to verifjy the effectiveness of  capacity-building efforts and MFS technologies This structured approach is summarized into three phases: Phase 1 (Planning and Assessment), Phase 2 (Execution and Adaptation) and Phase 3 (Evaluation and Refinement) This framework is designed to facilitate ongoing reflection and adaptation; ensuring that capacity development activities remain responsive to stakeholder needs and contribute to sustainable improvements within Malawi's mixed farming systems (see Figure 2)\r\n\r\nFigure 2: Knowledge Flows for Capacity Enhancement in Mixed Farming\r\n\r\nData Collection &\r\n\r\nAnalysis &\r\n\r\nCapacity Program\r\n\r\nImplementation\r\n\r\nInsights\r\n\r\nPrioritization\r\n\r\nDevelopment\r\n\r\n& Validation\r\n\r\nField observations\r\n\r\nSelfassessments\r\n\r\nRefreshinglupdating\r\n\r\nObservation\r\n\r\nMonitoring reports\r\n\r\nMonitoring reports\r\n\r\nCapacity development\r\n\r\nMonitoring progress\r\n\r\nNeeds assessments\r\n\r\nData review\r\n\r\napproaches for\r\n\r\nPerformance\r\n\r\nEvaluations\r\n\r\nPrioritization workshopsl\r\n\r\nAdoptionlde-adoption;\r\n\r\nPerformance\r\n\r\ntracking\r\n\r\nStakeholder feedback\r\n\r\nConsensus\r\n\r\nbuilding\r\n\r\nAdvisory services; Policy\r\n\r\nValidation of Results\r\n\r\nDialogue_Training\r\n\r\nPhase 1\r\n\r\nPhase 2\r\n\r\nPhase 3\r\n\r\nPhase 1: Planning and Assessment; Phase 2: Execution and Adaptation; Phase 3: Evaluation and Refinement\r\n\r\nGap\r\n\r\nConclusion and Recommendations\r\n\r\nThis Capacity Development Roadmap   provides a strategic pathway to enhance stakeholder skills, knowledge; and resilience across the Malawi's agricultural   landscape. Addressing both technical and systems-thinking needs, are to empowering stakeholders with the competencies required to improve productivity, make informed decisions; and adapt to complex The framework is grounded in practical; locally tailored interventions; including hands-on training, field trials; and collaborative initiatives, all  designed to create meaningful,   long-term impacts that align with stakeholders' unique operational contexts. key\r\n\r\nAchieving this will require coordinated efforts; ongoing learning, and strong institutions; policymakers and other relevant stakeholders. This roadmap promotes a phased approach that addresses immediate needs while laying the foundation for sustained growth; and adaptability. This document serves as a blueprint for fostering continuous learning; collaborative problem-solving, and effective knowledge-sharing, aimed at building technical capacity and empowering stakeholders to navigate the evolving agricultural landscape\r\n\r\nThe success of this roadmap will depend on strategic; collaborative partnerships across public;   private; and research sectors to secure the resources; expertise; and support needed to maximize its reach and impact. These alliances can harness diverse strengths to sustain and expand capacity - building efforts. Equally vital is a commitment to integrated learning; where systems-thinking approaches are embedded in technical training. This combination enables stakeholders to view mixed farming systems holistically, recognizing interconnections within the  system and making informed decisions that enhance both current resilience and long-term productivity .\r\n\r\nFocusing on early, high-impact interventions is also expected to further drive success. Starting with targeted interventions that address immediate needs and visibly demonstrate the value of capacity-building will build momentum and strengthen engagement among stakeholders; creating a foundation for sustained support.\r\n\r\nReferences\r\n\r\nAdesina; A. A, Langyintuo; A, Bugo; N., Makinde; K, Bigirwa; G., & Wakiumu; J (2014). 25OImproving farmers' access to agricultural inputs and finance: approaches and lessons from sub-Saharan Africa: In P. B. Hazell & A Rahman (Eds.) New Directions for Smallholder Agriculture (p. 0). Oxford University Press.\r\n\r\nhttps:lldoiorgho.1og3lacprof:oso/9780199689347.003.0009\r\n\r\n- Framework. (2008) Capacity Development Methods. Www.frameworkorg.uk\r\n- Kassie; M. Teklewold, H. Jaleta, M. Marenya; P & Erenstein; O. (2015) . Understanding the adoption of a portfolio of sustainable intensification practices in eastern and southern Africa. Land Use Policy, 42, 400-471. https:lldoiorg/o.1oI6/j.landusepol.2014.08.016\r\n- Klapper, & Lusardi, (2020). Financial   literacy and financial resilience: Evidence from around the world. Financial Management; 49(3), 589-614. https:lldoiorgh0.1111/fima.12283\r\n- Leeuwis; C. & Aarts, N. (2077) . Rethinking communication in innovation processes: Creating space for change in complex systems. Journal of Agricultural Education and Extension, 21-36. https:lldoiorg/0.1080/1389224X.2011.536344\r\n- The role of knowledge; attitudes perceptions in the uptake of agricultural and agroforestry innovations among smallholder farmers in sub-Saharan Africa. International Journal of Agricultural Sustainability, 13(1), 40-54. https:lldoiorg/0.1080/14735903.2014.912493\r\n- Morgan; P. (1998). CAPACITY AND CAPACITY DEVELOPMENT SOME STRATEGIES. 16(1), 1-23.\r\n- Capacity Needs Assessment and Needs Matrix Validation: Case Study of initiative on Mixed Farming Systems (MFS). International Maize and Wheat Improvement Center. Lilongwe; Malawi.\r\n- Vanlauwe B. Coe, R. C., & Giller, K. E. (2019). BEYOND AVERAGES: NEW APPROACHES to UNDERSTAND HETEROGENEITY and RISK of TECHNOLOGY SUCCESS or FAILURE in SMALLHOLDER FARMING. Experimental Agriculture; 84-106. https:|ldoiorg/0.1017/50014479716000193\r\n\r\nIITA\r\n\r\nTransforming African Agriculture\r\n\r\nINITIATIVE ON\r\n\r\nMixed Farming\r\n\r\nSystems\r\n\r\nCGIAR\r\n\r\ncqiar orginitiativelmixed-farming-systems\r\n\r\nICARDA\r\n\r\nICIMMYT\r\n\r\nILRI\r\n\r\nINTERNATIONAL\r\n\r\nLIVESTOCK RESEARCH\r\n\r\nIRRI\r\n\r\nInternational Rice\r\n\r\nResearch Institute\r\n\r\nIWMI\r\n\r\nInternational Water\r\n\r\nManagement Institute\r\n\r\nAlliance\r\n\r\nBioversity & CIAT\r\n\r\nINTERNATIONAL CROPS RESEARCH\r\n\r\nINSTITUTE FOR THE SEMI-ARID TROPICS"
+}

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+{
+  "gardian_id": "f21a27230e320d42f5814e2750685093",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/180451",
+  "description": "This study is part of a two-phase research initiative conducted between 2022 and 2025 in Wakiso and Soroti districts, Uganda, examining antimicrobial use (AMU), antimicrobial resistance (AMR), and farm management practices in smallholder poultry systems. The overall study objective was to generate evidence to inform policy and support practical, on-farm interventions to reduce unnecessary antimicrobial use. The longitudinal phase presented here was initiated in response to persistent high levels of routine AMU identified during the first phase. Using a longitudinal observational design, semi-intensive broiler flocks were followed across the full production cycle to examine patterns of antimicrobial use alongside biosecurity practices and vaccine performance under real-world farm conditions.  Data were collected through repeated farm visits, structured treatment and cost records, and standardized biosecurity assessments. This enabled a detailed, production-stage specific analysis of AMU and its underlying structural drivers, generating actionable insights for antimicrobial stewardship in Uganda’s rapidly expanding poultry sector.",
+  "id": "00a3f1a08f104cc9a1cdf519ca27cc43",
+  "title": "Challenges in biosecurity implementation and implications for antimicrobial use in Uganda’s poultry sector",
+  "language": "English",
+  "resource_type": "Brief",
+  "release_year": "2025",
+  "rights": "CC-BY",
+  "dataNODE_id": "f21a27230e320d42f5814e2750685093",
+  "keywords": [
+    "systems transformation",
+    "amr",
+    "animal health",
+    "capacity strengthening",
+    "chickens",
+    "farm management",
+    "gender",
+    "poultry",
+    "environmental health and biodiversity",
+    "poverty reduction, livelihoods and jobs",
+    "gender equality, youth and social inclusion",
+    "livelihoods",
+    "antimicrobial resistance",
+    "vaccination",
+    "broiler"
+  ],
+  "geography": {
+    "regions": [
+      "Eastern Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "World"
+    ],
+    "countries": [
+      "Uganda"
+    ]
+  },
+  "content": "CGIAR\r\n\r\nSCIENCE FOR A FOOD-SECURE FUTURE\r\n\r\nChallenges in biosecurity implementation and implications for antimicrobial use in Uganda's poultry sector\r\n\r\nDecember 2025\r\n\r\nKnowledge Brief\r\n\r\nContents\r\n\r\n| BACKGROUND                                              | 3   |\r\n|---------------------------------------------------------|-----|\r\n| KEYMESSAGES                                             | 3   |\r\n| WHY ITMATTERS                                           | 3   |\r\n| EVIDENCE FROM QUR STUDY                                 | 3   |\r\n| BIOSECURITY PERFORMANCE                                 |     |\r\n| ANTIMICROBIAL USE PATTERNS                              | ;   |\r\n| VACCINATION USE AND OUTCOMES                            |     |\r\n| FLOCK HEALTH PERFORMANCE                                |     |\r\n| HOW THIS WORK SUPPORTS UGANDAS AMR NATIONAL ACTION PLAN | 6   |\r\n| RECOMMENDATIONS                                         | 7   |\r\n| SHORT TERM (FARM-LEVEL)                                 | ;   |\r\n| MEDIUM TERM (SERVICE DELIVERY)                          |     |\r\n| SYSTEM LEVEL                                            |     |\r\n| CROSS-CUTTING GENDER AND LIVELIHOOD OUTCOMES            |     |\r\n| RESOURCES                                               | 7   |\r\n\r\nAuthors: Dreck Ayebare1 and Arshnee Moodley1,2\r\n\r\n'International Livestock Research Institute\r\n\r\n2Department of Veterinary and Animal Sciences; University of Copenhagen; Denmark\r\n\r\nSuggested citation: Ayebare; D. and Moodley; A. 2025. Challenges in biosecurity implementation and implications for antimicrobial use in Uganda's poultry sector. Nairobi, Kenya: International Livestock Research Institute (ILRI).\r\n\r\nCover photo: Pamela N. Wairagalal ILRI\r\n\r\nCopyright: 2025. ILRI. This publication is licensed for use under a Creative Commons Attribution 4.0\r\n\r\nDisclaimers: This publication has been prepared as an output of the CGIAR Sustainable Animal and Aquatic Foods (SAAF) Science Program. views and opinions expressed in this publication are those of the author(s) and are not necessarily representative of or endorsed by the CGIAR System Organization. Any7\r\n\r\nAcknowledgements: This work was conducted as part of the CGIAR Sustainable Animal and Aquatic Foods (SAAF) Science Program. CGIAR research is supported by contributions to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food; land; and water systems in a climate crisis_\r\n\r\nBackground\r\n\r\nThis study is part of a two-phase research initiative conducted between 2022 and 2025 in Wakiso and Soroti districts; Uganda; examining antimicrobial use (AMU), antimicrobial resistance (AMR); and farm management practices in smallholder poultry systems. The overall study objective was to generate evidence to inform policy and support practical; on-farm interventions to reduce unnecessary antimicrobial use\r\n\r\nThe longitudinal phase presented here was initiated in response to persistent high levels of routine AMU identified during the first phase. Using a longitudinal observational design; semi-intensive broiler flocks were followed across the full production cycle to examine patterns of antimicrobial use alongside biosecurity practices and vaccine performance under real-world farm conditions.\r\n\r\nData were collected through repeated farm visits, structured treatment and cost records, and standardized biosecurity assessments. This enabled a detailed; production-stage specific analysis of AMU and its underlying structural drivers, generating actionable insights for antimicrobial stewardship in Uganda's rapidly expanding poultry sector.\r\n\r\nmessages Key\r\n\r\n- External biosecurity is the weakest link and the primary driver of prophylactic antibiotic use_\r\n- Antibiotics are routinely administered early in the production cycle, indicating preventive rather than therapeutic use\r\n- Poor vaccine performance undermines farmer confidence in preventive measures, reinforcing dependence on antibiotics.\r\n- Targeted; low-cost biosecurity investments during brooding could deliver the largest AMU reductions .\r\n- Targeted; low-cost biosecurity improvements during the brooding phase could yield substantial reductions in AMU.\r\n- These findings identify practical entry points for implementing Uganda's AMR National Action Plan (NAP) at farm level.\r\n\r\nWhy it matters\r\n\r\nAntimicrobial resistance (AMR) is a growing public health and economic threat across low- and middle-income countries. At the same time; semi-intensive poultry production is rapidly expanding to meet rising demand for affordable animal-source foods. In these systems, disease prevention continues to rely heavily on routine antibiotic use, driven by weak biosecurity; inconsistent vaccine handling and delivery; and limited access to quality veterinary advisory services.\r\n\r\nUnderstanding how these factors interact to shape antimicrobial use is critical for designing effective; prevention - focused interventions that improve poultry health; safeguard livelihoods; and reduce AMR risks.\r\n\r\nEvidence from our study\r\n\r\nBiosecurity performance\r\n\r\nThe results indicate generally poor biosecurity across the surveyed poultry farms; with an overall median biosecurity score of only 38.5%, reflecting substantial exposure to disease risks as shown in Figure 1. External biosecurity scored the lowest at 26.3%, highlighting a critical vulnerability to the introduction of pathogens through uncontrolled movement of people; animals; equipment; and vehicles onto farms; suggesting that most farms lack effective measures to prevent disease entry.\r\n\r\nInternal biosecurity performed relatively better at 55.6%, indicating that farmers have some practices in place to limit disease spread within the farms. However; this level remains insufficient to reliably contain infections once introduced. Together; these findings suggest that weak external biosecurity is the primary risk factor for disease incursions; while inadequate internal controls further exacerbate transmission; reinforcing reliance on preventive antimicrobial use. The extremely low external biosecurity score explains the widespread prophylactic antibiotic use observed during brooding.\r\n\r\nFigure 1: Biosecurity performance across surveyed farms\r\n\r\n60\r\n\r\n40\r\n\r\n20\r\n\r\nExternal\r\n\r\nInternal\r\n\r\nOverall\r\n\r\ncomponent\r\n\r\nAntimicrobial use patterns\r\n\r\nThe findings show widespread and routine antibiotic use across production cycles; with 84% of farms using antibiotics in cycle and 77% in cycle 2, indicating that antimicrobial use is a normalized practice rather than an exception: The consistently high usage across cycles suggests limited learning or behavioral change over time\r\n\r\nAntibiotic use was highest during the brooding phase (72%), declining through the growing (56%) and finishing (47%) phases as shown in Figures 2 and 3. This pattern indicates that antibiotics are predominantly used preventively rather than therapeutically; likely as a risk-management strategy during brooding; which is the most vulnerable stage of production; when chicks are highly susceptible to disease.\r\n\r\nThe predominance of tetracyclines; macrolides; and fluoroquinolones; all critically important antimicrobial classes , raises significant public health concerns due to their relevance in human medicine and their potential to drive antimicrobial resistance\r\n\r\nThe study further found that farmers commonly used combinations of antibiotic and vitamin products, often without the farmers' knowledge of the antibiotic content of the products. This furthered the unnecessary exposure to antibiotics .\r\n\r\nFigure 2: Antimicrobial use per flock by production phase\r\n\r\nAntimicrobial Use per Flock Production Phase by\r\n\r\n107\r\n\r\nKruskal-Wallis: X? = 34.49, p = 3.2e-08\r\n\r\np < 0.0001\r\n\r\np\r\n\r\n0.0007\r\n\r\nP = 0.058\r\n\r\n106\r\n\r\n104\r\n\r\nbrooding\r\n\r\ngrowing\r\n\r\nfinishing\r\n\r\nProduction Phase\r\n\r\n105\r\n\r\nFigure 3: Treatment incidence per production phase\r\n\r\nFirst\r\n\r\nSecond\r\n\r\nhrooding\r\n\r\nAntibiotic class\r\n\r\nAminoglycosides\r\n\r\nFluoroquinolones\r\n\r\ngrowing\r\n\r\nMacrolides\r\n\r\n1\r\n\r\nPolyonarises\r\n\r\nTetracyclines\r\n\r\nfinishing\r\n\r\n25\r\n\r\n50\r\n\r\n75\r\n\r\n25\r\n\r\n50\r\n\r\n75\r\n\r\nTreatment incidence (% of total)\r\n\r\ncycle\r\n\r\ncycle\r\n\r\nVaccination use and outcomes\r\n\r\nAlthough all farms reported using at least one vaccine, overall vaccine performance was poor. Median seropositivity levels were 72.2% for both Newcastle disease (NCD) and infectious bronchitis (IB), but markedly lower for Gumboro disease (IBD) at 27.8%, indicating inadequate immune protection across flocks as shown in Figure 4\r\n\r\nfew farms achieved antibody levels considered sufficient for effective protection; only two farms for NCD, three for IBD; and one for IB. This suggests that vaccination alone did not translate into reliable immunity. Very\r\n\r\nPoor vaccine performance likely undermines farmer confidence in preventive measures and reinforces reliance on routine antibiotic use as a substitute for effective disease prevention; perpetuating cycles of prophylactic antimicrobial use and increasing AMR risk.\r\n\r\nFigure 4: Vaccination outcomes\r\n\r\n100\r\n\r\n75\r\n\r\n1\r\n\r\n50\r\n\r\n25\r\n\r\nNCD\r\n\r\nIB\r\n\r\nIBD\r\n\r\nVaccine\r\n\r\nFlock health performance\r\n\r\nLow mortality despite high disease reporting suggests antibiotics may be suppressing symptoms rather than eliminating infection risk.\r\n\r\nClinical signs of disease, predominantly respiratory; were widely reported across farms (17 of 19 farms in cycle and 11 of 13 farms in 2), indicating substantial and persistent disease pressure within the production systems. cycle\r\n\r\nHowever; mortality rates remained relatively low (2.5% in cycle 1 and 3.9% in cycle 2), suggesting that routine antibiotic use may be suppressing clinical severity rather than preventing disease occurrence.\r\n\r\nHow this work supports Uganda's AMR National Action Plan\r\n\r\nThis study is among the first longitudinal investigations in Uganda to concurrently assess farm-level biosecurity; vaccine seroconversion; and real-time antimicrobial use across multiple poultry production cycles; providing direct; actionable evidence to support implementation of Uganda's AMR National Action Plan.\r\n\r\nFrom a surveillance perspective, the findings identify the brooding phase as the highest-risk period for antimicrobial use. From a stewardship lens, the widespread presence of antibiotics in commonly used vitamin premixes exposes farmers to unintentional antimicrobial use; underscoring the need to strengthen AMU literacy and regulate agro-veterinary inputs.\r\n\r\nFrom a prevention standpoint; consistently poor vaccine-induced antibody responses point to systemic weaknesses in vaccine delivery; cold-chain management; and field administration; thereby corroborating the AMR NAP principle that infection prevention is fundamental to reducing antimicrobial use_\r\n\r\nFinally; from a governance perspective; the results highlight critical gaps in vaccine cold-chain systems, regulatory oversight of veterinary inputs; and the urgent need to scale behavior change interventions targeting veterinarians; agro-vet retailers, and farmers.\r\n\r\nRecommendations\r\n\r\nShort term (farm-level)\r\n\r\n- Introduce low-cost external biosecurity packages tailored for brooding units to reduce early-cycle disease risk.\r\n- Introduce practical; farmer-friendly antimicrobial use (AMU) decision-support tools to guide appropriate treatment choices.\r\n\r\nMedium term (service delivery)\r\n\r\n- Establish cold-chain certification systems for poultry vaccines to improve handling; storage; and field efficacy:\r\n- Implement standardized training and accreditation for vaccinators and para-veterinarians to strengthen preventive service quality:\r\n\r\nSystem level\r\n\r\n- Set district-level AMU reduction targets aligned with national antimicrobial resistance (AMR) strategies and monitoring frameworks.\r\n- Introduce regulatory controls on antibiotic-vitamin premixes to curb unintended antimicrobial exposure and misuse.\r\n\r\nCross-cutting gender and livelihood outcomes\r\n\r\nGiven the strong participation of women in semi-intensive poultry value chains; strengthening preventive health systems has the potential to generate significant gender and livelihood co-benefits; enhancing productivity while empowering women as key drivers of sustainable poultry production.\r\n\r\nResources\r\n\r\nAyebare; D. Muloi, D.M , Ibayi, EL Nielsen; S.S., Ndoboli, D Roesel K Tenhagen; B.A. and Moodley; A. 2025. Biosecurity measures and effects on health performance and antibiotic use in semi-intensive broiler farms in Uganda. One Health 20:101039.\r\n\r\nAyebare; D., Mbatidde; I., Muloi, D.M , Ndoboli; D._ Roesel, K, Tenhagen; B.A. and Moodley; A. 2025.\r\n\r\nQuantification of antimicrobial use and economic burden in semi-intensive broiler farms in Uganda. Under review.\r\n\r\nContact: animal_aquatic@cgiar org\r\n\r\nCGIAR is a global research partnership for a food-secure future. CGIAR science is dedicated to transforming food, land, and water systems in a climate crisis. Its research is carried out by 13 CGIAR CenterslAlliances in close collaboration with hundreds of partners, including national and regional research institutes, civil society organizations , academia, development organizations and the private sector: www.cgiar org\r\n\r\nWe would like to thank all funders who support this research through their contributions to the CGIAR Trust Fund: WWWcgiar orglfunders\r\n\r\nTo learn more about the Sustainable Animal and Aquatic Foods Program, please visit this webpage:\r\n\r\nTo learn more about this and other Science Programs and Accelerators in the CGIAR Research Portfolio 2025-2030, please visit www cgiar orglcgiar-research-porfolio-2025-2030/\r\n\r\nCopyright: 2025. International Livestock Research Institute. This publication is licensed for use under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view this license; visit https: Ilcreativecommons orqllicenseslbyl4 0\r\n\r\nCGIAR\r\n\r\nSUSTAINABLE ANIMAL AND AQUATIC FOODS\r\n\r\nSCIENCE FOR A FOOD-SECURE FUTURE"
+}

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+{
+  "gardian_id": "0f99848c5d087bf0260af761b2935cf6",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/176172",
+  "description": "This policy brief presents a comprehensive assessment of Vietnam’s national food environment policy landscape, using the INFORMAS Food-EPI framework. As Vietnam’s food environments undergo rapid transformation, the brief highlights persistent regulatory gaps in key domains such as food marketing, nutritional labeling, procurement standards, and fiscal policy. While food safety regulations have advanced, policies to improve the nutritional quality, affordability, and accessibility of healthy foods remain underdeveloped. The brief calls for stronger, more coherent policy action that goes beyond consumer education to address structural drivers of unhealthy diets. It outlines five priority areas for reform: strengthening nutrition standards for processed foods; rebalancing modern retail expansion with support for informal and traditional food outlets; tightening regulations on food marketing and labeling; introducing fiscal measures to make healthy diets more affordable; and evaluating and improving the implementation of current nutrition-related policies. The findings aim to support policymakers and stakeholders working to create healthier, more equitable food systems in Vietnam.",
+  "id": "00aa38a2443c231d6e7a644a335568f4",
+  "title": "Vietnam food environment: Unpacking the national policy landscape",
+  "language": "English",
+  "resource_type": "Brief",
+  "release_year": "2025",
+  "rights": "CC-BY",
+  "dataNODE_id": "0f99848c5d087bf0260af761b2935cf6",
+  "keywords": [
+    "resilient agrifood systems",
+    "systems transformation",
+    "food systems",
+    "governance",
+    "health",
+    "markets",
+    "policy",
+    "gender equality, youth and social inclusion",
+    "nutrition, health and food security",
+    "sdg 1 - no poverty",
+    "sdg 2 - zero hunger",
+    "sdg 3 - good health and well-being",
+    "sdg 8 - decent work and economic growth",
+    "sdg 10 - reduce inequalities",
+    "sdg 11 - sustainable cities and communities",
+    "sdg 12 - responsible production and consumption",
+    "nutrition",
+    "diet",
+    "sustainability",
+    "policy briefs",
+    "food environment",
+    "policy analysis"
+  ],
+  "geography": {
+    "regions": [
+      "South-eastern Asia",
+      "Asia",
+      "World"
+    ],
+    "countries": [
+      "Viet Nam"
+    ]
+  },
+  "content": "Alliance\r\n\r\nBioversity & CIAT\r\n\r\nISPAE\r\n\r\nCGIAR\r\n\r\nBETTER DIETS\r\n\r\nAND NUTRITION\r\n\r\nTAR\r\n\r\nSTAR\r\n\r\nSTAR\r\n\r\nTAR\r\n\r\nSTAP\r\n\r\nice\r\n\r\ngood\r\n\r\nmood\r\n\r\nVietnam Food Environment\r\n\r\nUnpacking the national policy landscape\r\n\r\noosr\r\n\r\nJIter\r\n\r\nThe Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) delivers research-based solutions that address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation:\r\n\r\nThe Alliance focuses on the nexus of agriculture, nutrition, and environment. Latin America and the Caribbean, and with the public and private sectors and civil society. With novel partnerships, the Alliance generates evidence and mainstreams innovations to transform food systems and landscapes so that sustain the planet, drive prosperity, and nourish people in a climate crisis. they\r\n\r\nThe Alliance is part of CGIAR, a global research partnership for a food-secure future dedicated to transforming food, Iand, and water systems in a climate crisis.\r\n\r\nWWWalliancebioversityciat org WWW cgiar org\r\n\r\nSuggested citation:\r\n\r\nEven Brice, Trang Thi Thu Truong, Duong Thu Nguyen, Huong Thi Mai Pham, Hang Thi Minh Thai, Anh Thi Viet Bui, and Christophe Béné. 2025. Vietnam Food Environment: Unpacking the national policy landscape. Policy Brief. International Center for Tropical Agriculture (CIAT), Hanoi, Vietnam. 15 pages.\r\n\r\nAcknowledgements:\r\n\r\nNutrition (BDN) Science Program of CGIAR. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Eund. The funders had no role in the design of the study; in the collection; analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results . and\r\n\r\nWe express our gratitude to Dr. Dao The Anh, Vice-President of the Vietnamese Academy of Agricultural Sciences (VAAS), Dr. Truong Tuyet Mai, Vice-Director of the National Institute of Nutrition (NIN) , and Dr. Tran Cong Thang, Director General of the Institute of Strategy and Policy on Agriculture and Environment (ISPAE), for their valuable contributions to the review of our findings. Our sincere appreciation also goes out to the members of the panel of experts who played a decisive role in the analysis and validation process. Special thanks to Carolina Polo from the Alliance of Bioversity and CIAT for her efforts in formatting this brief.\r\n\r\nCover photo: Ha Dao/CIAT.\r\n\r\nCIAT 2025. Some rights reserved.\r\n\r\nThis work is licensed under a Creative Commons Attribution 4.0 International License (CC-BY 4.0)-\r\n\r\nAugust 2025\r\n\r\nIntroduction\r\n\r\nFood environments refer to the physical, economic; political, and socio-cultural settings that influence how people access, prepare, and consume food [1].\r\n\r\nFood environments are central to shaping diets, health outcomes, and broader sustainability goals. In Vietnam, as in many other countries, food environments are changing fast, driven by urbanization, rising incomes, evolving lifestyles, marketing dynamics, digital platforms, and global food system shifts [2, 3].\r\n\r\nThe aim of this policy brief is to enhance understanding about food environments and to investigate how policies in Vietnam can be improved to contribute to the transition towards healthier and more sustainable food systems in Vietnam.\r\n\r\nFood environments influence what people eat The food environment is the interface between food systems and people's diets. It refers to the settings in which food is accessed, as well as the characteristics of that food_how it is priced, marketed, distributed, and consumed [4, 5]. Core dimensions of food environments include:\r\n\r\nChildren contemplating shelves filled with ultra-processed snacks in a Hanoi supermarket.\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\n- Food availability: what is physically present and reachable.\r\n- Food prices: how much it costs in relation to people's resources.\r\n- Food products properties: including nutritional quality safety; and level of processing.\r\n- Food outlets properties: including type, location, and vendor practices.\r\n- Food messaging: including marketing, advertising, and labelling.\r\n\r\nThese dimensions are shaped by policy choices, market dynamics, and underlying food system structures; and they can be transformed through specific, targeted interventions.\r\n\r\nIndividuals experience food environments through personal filters (e.g., income, knowledge, cultural values, or mobility constraints, etc.) which condition how they perceive, prioritize, and access different food options.\r\n\r\nTo be effective, food policies must address both the structural features of food environments and the individual-level factors that mediate consumer behavior; ensuring that healthier options are accessible, affordable, and desirable for all [6].\r\n\r\nWhat are food environments?\r\n\r\nFood environment framework. Source: adapted from Turner et al. (2018) and UNSCN (2019).\r\n\r\nAND\r\n\r\nFOOD\r\n\r\nENVIRONMENT\r\n\r\nFood\r\n\r\nFood prices\r\n\r\nINDIVIDUAL\r\n\r\navailability\r\n\r\nCost of food\r\n\r\nFILTERS\r\n\r\nof food\r\n\r\nEconomic\r\n\r\nCONSUMER\r\n\r\nCognitive\r\n\r\nfilters\r\n\r\nBEHAVIORS\r\n\r\nfilters\r\n\r\nPurchasing\r\n\r\nAND DIETS\r\n\r\nKnowledge,\r\n\r\npower\r\n\r\nFood acquisltion;\r\n\r\npreferences\r\n\r\nvalues\r\n\r\npreparation;\r\n\r\neating habits\r\n\r\nFood\r\n\r\nFood\r\n\r\nproducts\r\n\r\nmessaging\r\n\r\nproperties\r\n\r\nSituational filters\r\n\r\nAdvertising,\r\n\r\nPhysical (spatial and temporal)\r\n\r\nNutritional quality,\r\n\r\nlabeling; and\r\n\r\naccess to food\r\n\r\nsafety; and level\r\n\r\npackaging\r\n\r\nof processing\r\n\r\nFood outlets\r\n\r\nproperties\r\n\r\nType and features\r\n\r\nof food vendors\r\n\r\nFOOD SYSTEM\r\n\r\nREGULATIONS\r\n\r\nPOLICY\r\n\r\nDRIVERS\r\n\r\nTransforming food systems requires policies that reshape food environments\r\n\r\nMAX\r\n\r\nIQ\r\n\r\nMAY\r\n\r\nAdolescents crowding in a newly-open convenience store in Hanoi.\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\nWhy focus on food environments?\r\n\r\nPolicy responses to poor diets often overemphasize individual responsibility [7] (relying on education, awareness, or behavior change campaigns to encourage healthier choices) even though food choices are shaped by systemic conditions [8]. This focus shifts the burden to consumers, overlooks the powerful influence of food environments, and diverts accountability from industry and regulators.\r\n\r\nfood environment lens shifts the focus from individual knowledge and choices to the broader conditions that determine what foods are accessible, affordable, and appealing, thereby enabling more systemic and equitable policy interventions. These measures are most effective when part of coherent policy packages that combine regulation; fiscal tools, and strong public leadership.\r\n\r\nThe Food Environment Policy Index (Food-EPI), developed by INFORMAS [6], offers a structured tool to assess the extent to which existing policies promote healthy food environments, and to identify critical policy gaps and opportunities for policy action.\r\n\r\nRapidly evolving food environments: shifting supply & demand\r\n\r\nFood environments in Vietnam are undergoing rapid transformation, as in many other LMICs. Ultra-processed foods (typically high in fat, sugar; and salt) have become increasingly available, affordable, and prominently marketed. Comparatively; nutrient-dense foods may become less accessible and more expensive, particularly for low-income populations [3].\r\n\r\nThese shifts in food supply are closely linked to broader changes in the retail landscape. Traditional markets are losing ground to a fastgrowing network of supermarkets and convenience stores, reshaping how and where people buy food.\r\n\r\nAccompanying these changes is a rising public health concern: between 2010 and 2020, the national prevalence of overweight children in Vietnam more than doubled, increasing from 8.5% to 19% [9].\r\n\r\nIGA\r\n\r\nIstrol\r\n\r\nOR\r\n\r\nGÀRÁNFKI\r\n\r\nOverweight and obesity rates have been increasing concurrently to the evolution of food environments\r\n\r\nScenes from contemporary food environments in urban Vietnam. Photos: Ha Dao/CIAT.\r\n\r\nWhat does policy assessment reveal in Vietnam?\r\n\r\nThe assessment of Vietnam's food environment policies, conducted using the INFORMAS Food Environment Policy Index, reveals substantial regulatory gaps The following sections of this brief present a narrative summary of the key policy gaps identified.\r\n\r\nFood-EPI evaluates national policies against international best practice across key domains of the food environment, such as food labelling, marketing, and fiscal policies. In Vietnam, 35 indicators were assessed through a structured process led by independent researchers, with active participation from a transdisciplinary panel of national experts.\r\n\r\nA large majority of the indicators evaluated (74%) received low or very low scores, indicating limited policy action across most domains of the food environment. In contrast, only 12% of indicators were rated high, and these were largely confined to food safety regulations and public education initiatives .\r\n\r\nThese findings suggest that while some foundational policies exist, they remain fragmented and insufficient. A more comprehensive and coherent policy framework is urgently needed to enable healthier; more equitable food environments across the country.\r\n\r\nHigh score\r\n\r\nIntermediate score\r\n\r\nLow score\r\n\r\nVery low score\r\n\r\n35\r\n\r\nindicators\r\n\r\nscore\r\n\r\nFood product properties\r\n\r\nVietnam has made only modest progress in improving the nutritional quality of food products. Until recently; policy efforts focused primarily on salt reduction. But these measures lacked concrete targets, enforcement mechanisms, and clear institutional oversight. No formal standards or limits exist for sugar or trans-fat content in packaged foods, leaving critical regulatory gaps.\r\n\r\nA notable recent development is the excise tax on sugar-sweetened beverages (SSBs) , adopted in June 2025 and scheduled to take effect in 2027. This marks an important step toward regulating unhealthy food products and aligning fiscal tools with public health goals.\r\n\r\nUltra-processed foods are not regulated beyond basic food safety oversight In contrast, food safety policy has advanced more systematically. The Food Safety Law clarified mandates and introduced technical standards, but implementation remains uneven. Local inspection capacity is often constrained by shortages of trained staff, equipment, and infrastructure. Food safety training and communication are inconsistently applied; while some provinces, with international support or strong leadership, have improved outreach and inspector training, others, especially in rural areas, still face major gaps in awareness and compliance.\r\n\r\nRAU VIETGAP\r\n\r\nSafe, certified tomatoes on display in a Hanoi supermarket.\r\n\r\nPhoto: Ha Dao/CIAT_\r\n\r\nShelves packed with instant noodles in a convenience store in Moc Chau.\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\nUltra-processed snacks in a convenience store, Hanoi.\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\nIstas\r\n\r\nFAMI\r\n\r\nFood outlet properties\r\n\r\nCurrent policies in Vietnam make no distinction between food outlets based on the nutritional quality of what they sell. National strategies and urban land use planning generally promote the expansion of modern retail outlets (e.g. supermarkets, convenience stores) without requiring them to prioritize healthy options or limit unhealthy ones.\r\n\r\nInformal vendors (often a source of fresh, affordable foods for low-income households) come under growing regulatory pressure, mainly through measures designed to improve food-safety oversight. While these rules aim to protect consumers, they can also raise compliance costs for small vendors and unintentionally favour larger; with often less-nutritious food options, retail channels. key\r\n\r\nMIXUE\r\n\r\nFranchise ice cream and milk tea shop in a peri-urban area.\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\nFast food chain outlet, Hanoi. Photo: Ha Dao/CIAT) .\r\n\r\nInformal street vendor selling fresh vegetables in Hanoi. Photo: Ha Dao/CIAT.\r\n\r\nModern retail expansion is encouraged\r\n\r\nPublic food procurement and provision policies also remain underdeveloped. While the Food Safety Law sets general standards, there are few specific requirements to ensure the nutritional quality of food served in public and private institutions.\r\n\r\nSchool food guidelines are in place but are mostly non-binding, leading to uneven implementation across the country. In other institutional settings (such as workplaces and hospitals) existing meal guidelines are also voluntary and rarely enforced, leaving significant gaps in the regulation of everyday food provision.\r\n\r\nFood messaging\r\n\r\nRegulations on food marketing remain weak in Vietnam. Although national policy documents acknowledge the need to limit advertising around schools, there are no explicit restrictions on the marketing of unhealthy foods and beverages, especially those targeting children.\r\n\r\nFood labeling regulations require packaged products to display ingredient lists and nutritional information, but enforcement is weak due to the absence of clear monitoring and approval mechanisms. Health claims on processed foods are poorly regulated, and front-of-pack labeling remains voluntary and lacks standardized implementation guidelines, limiting consumers' ability to quickly assess product healthfulness.\r\n\r\nBINGXUE\r\n\r\nIce-cream shop, Hanoi. Photo: Ha Dao/CIAT.\r\n\r\nCurrent policies and public initiatives place strong emphasis on consumer education. Public awareness campaigns are used to disseminate dietary guidelines. These efforts also include nutrition training for health communicators and health workers. However; most initiatives are nonbinding and inconsistently implemented, limiting their reach and long-term impact.\r\n\r\nConvenience store in Hanoi displaying processed and ultra-processed products under the \"fresh food\" Iabel. Photo: Ha Dao/CIAT.\r\n\r\nFood\r\n\r\nFresh_\r\n\r\nGS25\r\n\r\nG525\r\n\r\nAdvertising of nutrient-poor foods; particularly to children; Iacks strong regulations\r\n\r\nFood prices & affordability\r\n\r\nVietnam has made limited policy progress in improving the affordability of healthy foods or using fiscal tools to curb the consumption of unhealthy products. While some tax exemptions apply to minimally processed foods, there are no direct financial incentives in place to actively promote healthier dietary choices.\r\n\r\nUntil recently; taxation of unhealthy foods had remained largely aspirational. However; in June 2025, Vietnam adopted an excise tax on sugar-sweetened beverages, set to take effect in 2027_marking a significant step toward aligning fiscal policy with nutrition goals.\r\n\r\nDespite this progress, broader fiscal strategies still fall short. Subsidy programs continue to prioritize price stabilization for staple foods such as rice, salt, and sugar rather than improving access to nutrient-dense foods like fruits, vegetables, and legumes. A shift in focus is needed to realign food price policies with health and sustainability objectives .\r\n\r\nFiscal policies to promote healthy diets remain underdeveloped; despite recent progress on sugary drink taxation\r\n\r\n69k\r\n\r\nGiáchi\r\n\r\n129k\r\n\r\nLow-cost promotional signage for fast food items outside a restaurant in Hanoi. Photo: Ha Dao/CIAT.\r\n\r\nKhUYEN MAI\r\n\r\nMua 2 Tang\r\n\r\n10\r\n\r\n12\r\n\r\none-get-one promotions for sugary drinks in a Hanoi supermarket. Aggressive discounting of nutrient-poor beverages remains widespread and unregulated Photo: Ha Dao/CIAT_\r\n\r\nFood availability and accessibility\r\n\r\nHealthy food access is left to the market. Policy support remains largely absent\r\n\r\nVietnam currently lacks targeted policies to enhance the availability of healthy food options or to regulate access to unhealthy ones. There are no incentives for retailers to promote nutritious foods, and no mechanisms to discourage the widespread sale of ultra-processed or lownutrient products.\r\n\r\nSimilarly; zoning laws do not address the spatial distribution of food outlets. There are no restrictions on the clustering of unhealthy vendors, nor policies to encourage the establishment of outlets offering healthier options.\r\n\r\nIn the absence of proactive regulation; market forces continue to shape food environments, often in ways that reinforce unhealthy dietary patterns and widen disparities in food access.\r\n\r\nKFC\r\n\r\nHere\r\n\r\nJollibee\r\n\r\nGà Rán Giòn\r\n\r\nNgon Tuyêt\r\n\r\n0\r\n\r\n7\r\n\r\nTan,\r\n\r\nFast food chains have become increasingly visible across urban Vietnam. Photos: Ha Dao/CIAT.\r\n\r\nMcDonalc\r\n\r\nConcrete next steps\r\n\r\ncomprehensive food environment policy package should address both structural drivers and equity concerns. priorities include: Key\r\n\r\n- Move beyond food safety to address nutritional quality more comprehensively. Develop and enforce standards for processed foods; including clear nutrient profiling, standardized definitions of \"healthy\" and \"unhealthy\" foods, mandatory targets for salt, sugar; and trans - fat reduction, and recognition of ultra-processed foods as a public health risk.\r\n- Balance the expansion of modern retail with measures that safeguard access to fresh and healthy foods. This includes supporting traditional markets and informal vendors as sources of safe, fresh, affordable food; creating incentives for retailers to offer healthy foods; implementing nutrition standards in public procurement (especially in schools and hospitals); and implementing zoning regulations to limit unhealthy outlet proliferation and reduce exposure to unhealthy foods. key\r\n- Strengthen regulations on food marketing and labeling. Restrict unhealthy food marketing to children, introduce mandatory front-of-pack labeling, and regulate health /nutrition claims. Complement regulatory tools with nutrition education campaigns and clearer dietary guidelines to empower consumer choices.\r\n- Introduce fiscal measures that support healthy diets. Build on recent progress such as the adoption of an excise tax on sugar-sweetened beverages (effective 2027) by considering its extension to ultra-processed foods. Expand subsidies or tax exemptions for nutrient-rich foods to enhance affordability and reduce health inequities.\r\n- Evaluate and strengthen the impact of current policies aimed at healthier diets. Build on emerging initiatives such as the upcoming subsidy for semi-boarding meals in Hanoi primary schools (2025-2026) by ensuring alignment with nutrition standards and robust implementation monitoring. Broader policy evaluation can help identify gaps, improve effectiveness, and guide future actions.\r\n\r\nWhat principles should guide food environment regulation?\r\n\r\nElevate public health over short-term economic gains.\r\n\r\nAddress Big Food lobbying power and corporate influence through transparency & accountability:\r\n\r\nAdopt binding regulations beyond voluntary self-governance.\r\n\r\nStrengthen local capacities and multisectoral collaboration.\r\n\r\n&\r\n\r\nHEALTHY\r\n\r\nORGANIC\r\n\r\nCustomers buying fresh produce from the Organic & Healthy section at a supermarket in Hanoi\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\nA roadside vendor sells vegetables at an informal market in Hanoi.\r\n\r\nPhoto: Ha Dao/CIAT.\r\n\r\nRelated publications to go further\r\n\r\nUnpacking food environment policy landscapes for healthier diets in 'emerging' countries: the case of Viet Nam\r\n\r\nEven et al., 2025\r\n\r\nNavigating the politics and processes of food systems transformation: guidance from a holistic framework\r\n\r\nBéné and Abdulai, 2024\r\n\r\nDefining barriers to food systems sustainability: a novel conceptual framework\r\n\r\nEven et al., 2024\r\n\r\nAlliance\r\n\r\nBioversity & CIAT\r\n\r\nISPAE\r\n\r\nCGIAR\r\n\r\nBETTER DIETS\r\n\r\nAND NUTRITION\r\n\r\nSpecial Issue:\r\n\r\nSustainable Approaches to Public Health Via Food Policy_Actions\r\n\r\nSpecial Issue:\r\n\r\nThe Many Faces of Sustainable Food\r\n\r\nContact:\r\n\r\nBrice Even beven@cgiarorg Scientist, Vietnam, International Center for Tropical Agriculture"
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+{
+  "gardian_id": "64fcb5fb989738953832ec5fb09e8123",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/182409",
+  "description": "From Data Islands to Data Highways: A Practitioner’s Guide to Building Agricultural Digital Public Infrastructures presents a practical methodology for designing and implementing Digital Public Infrastructure (DPI) in agricultural sectors, particularly in the Global South. Based on the experience of the coffee sector in Honduras and parallel initiatives in Kenya, Peru, Guatemala, and Costa Rica, the guide proposes a replicable approach to transform fragmented data ecosystems into shared and interoperable infrastructures governed as digital commons.\n\nThe guide is structured in four sequential phases. First, it describes the enabling conditions necessary to initiate a DPI process, including institutional alignment, minimum team capabilities, and feasibility analysis. Second, it presents a participatory methodology for transitioning from mapping the data ecosystem to building a collective mandate, combining AI-assisted analysis with multi-stakeholder consultations and workshops that enable agreements on shared objectives. Third, it explains the technological architecture of a sectoral DPI, including identity and access systems, open-source tools organized by functions, interoperable data spaces, and payment components. Fourth, it proposes a governance framework that integrates principles from commons theory with operational rules to ensure sustainability, institutional legitimacy, and long-term coordination.\n\nThe central argument is that building a DPI is primarily a governance challenge rather than a technological one. Although technical tools are increasingly mature, success depends on generating institutional trust, maintaining neutrality in facilitation, securing sustained financing, and managing collaborative processes among multiple actors. The guide emphasizes that deploying technology alone is insufficient: without shared governance agreements, efforts tend to reproduce the same data silos they aim to overcome.\n\nOverall, the document provides a practical roadmap for governments, research organizations, donors, and sectoral actors interested in developing shared digital infrastructures that improve data interoperability, facilitate regulatory compliance, and contribute to more inclusive and efficient agricultural systems.",
+  "id": "1b70beaec340de95c21c3b9364d92eff",
+  "title": "From data islands to data highways: A practitioner’s guide to building agricultural digital public infrastructures",
+  "language": "English",
+  "resource_type": "Training Material",
+  "release_year": "2026",
+  "rights": "CC-BY",
+  "dataNODE_id": "64fcb5fb989738953832ec5fb09e8123",
+  "keywords": [
+    "systems transformation",
+    "markets",
+    "policy",
+    "value chains",
+    "environmental health and biodiversity",
+    "poverty reduction, livelihoods and jobs",
+    "sdg 1 - no poverty",
+    "sdg 8 - decent work and economic growth",
+    "sdg 9 - industry, innovation and infrastructure",
+    "sdg 12 - responsible production and consumption",
+    "governance",
+    "institutional development",
+    "digital public infrastructure"
+  ],
+  "geography": {
+    "regions": [
+      "Central America",
+      "Latin America and the Caribbean",
+      "Americas",
+      "World",
+      "Eastern Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "South America"
+    ],
+    "countries": [
+      "Peru",
+      "Honduras",
+      "Guatemala",
+      "Kenya",
+      "Costa Rica"
+    ]
+  },
+  "content": "FROM DATA ISLANDS TO DATA HIGHWAYS\r\n\r\nA Practitioner’s Guide to Building Agricultural Digital Public Infrastructures\r\n\r\nFederico Ceballos-Sierra¹, Brian King¹, and Christian Hennig²\r\n\r\n¹ International Center for Tropical Agriculture (CIAT)\r\n\r\n² Permarobotics GmbH\r\n\r\nIntroduction: How to Use This Guide\r\n\r\nThis guide documents, for the first time, a complete methodology for building Digital Public Infrastructures (DPIs) for agricultural sectors in the Global South. It draws on real experience from Honduras’s coffee sector — our primary case — and from parallel work in Kenya, Peru, Guatemala, and Costa Rica. It is written for practitioners who want to understand and replicate the process, not for academics who want to theorize about it.\r\n\r\nThe guide is the product of a collaboration between CIAT (Alliance Bioversity-CIAT) and Permarobotics GmbH, combining institutional research on commons governance with deep technical expertise in data space architecture. It reflects the accumulated lessons of building a DPI from scratch in a complex institutional environment — lessons that include failures, dead ends, and uncomfortable compromises alongside the successes.\r\n\r\nWe wrote this guide because we believe the agricultural DPI model is replicable. The specific actors, regulations, and politics vary from country to country and commodity to commodity, but the structural pattern — data fragmentation, institutional silos, the need for shared infrastructure governed as a commons — is remarkably consistent. If you are working in an agricultural sector where multiple institutions collect overlapping data about the same farmers with no mechanism to connect those datasets, this guide is for you.\r\n\r\nHow to Navigate the Four Chapters\r\n\r\nThe guide is organized in four chapters that follow the chronological sequence of building a DPI. Each chapter builds on the previous one, so we recommend reading them in order the first time through. After that, each chapter can be used independently as a reference for its specific phase of the process.\r\n\r\nChapter 1: Enabling Conditions and Setting the Scene\r\n\r\nRead this first. Chapter 1 covers everything that must be in place before the DPI process formally begins: the definition of a DPI and its three-layer architecture, the minimum viable team (a Lead Researcher and an Associate Researcher), the entry points through which DPI conversations typically emerge from existing projects, and the scoping exercise that determines whether the conditions for a DPI process exist in your context. If you are unsure whether your sector is ready for a DPI, start here. The chapter concludes with a ten-item checklist of enabling conditions. If you cannot answer “yes” to most of them, focus on building the preconditions before proceeding.\r\n\r\nChapter 2: From Mapping to Mandate\r\n\r\nRead this when you are ready to begin. Chapter 2 guides you through the core process that converts enabling conditions into collective commitment. It covers the AI-mediated data ecosystem mapping (an express methodology that uses AI deep research to produce a comprehensive sector mapping in hours rather than weeks), two rounds of consultation (first with piggyback partners, then semi-structured interviews with key sector actors), the one-day multi-stakeholder workshop that produces a joint statement, and the proof of concept that validates the DPI as a minimum viable product. The chapter introduces the consensus-and-dissent methodology and the commons debate — the physical deliberation exercises that structure the workshop. If you are planning a workshop, this is your operational manual.\r\n\r\nChapter 3: The Technology\r\n\r\nRead this to understand what you are building. Chapter 3 explains the complete technology architecture of a sectoral DPI, structured around its three layers. It covers the Identity and Access Management system (including farmer ID cards with NFC and QR-encoded GeoIDs), the Open-Source Stack organized by function (spatial identity, polygon capture, deforestation risk assessment, supply chain traceability, agricultural services, and the Pancake unifying layer), the Data Space (IDSA-compliant connectors, broker, contracts, and rulebook), and the Payments component. It is the most technical chapter, but it is written for practitioners, not engineers. If you need to explain the DPI architecture to an institutional partner, a donor, or a government official, the step-by-step data exchange scenario in Section 3.4.5 is your best starting point.\r\n\r\nChapter 4: Building the Governance\r\n\r\nRead this when the joint statement is signed. Chapter 4 provides the governance framework that ensures the DPI is not just built but sustained. It marries Elinor Ostrom’s Institutional Analysis and Development (IAD) framework with the IDSA Rulebook to produce a Governance Design Roadmap: a structured process from a founding workshop through six design sessions to a closing constitutional convention. The chapter covers the eight Ostrom design principles applied to data spaces, the three-level institutional grammar (constitutional, collective-choice, operational), the AI-facilitated “Thomas Jefferson” protocol for governance design, the legal entity question, and realistic timelines. This is the chapter that ensures long-term sustainability.\r\n\r\nReading Paths by Role\r\n\r\nNot every reader needs to read every chapter with equal depth. Here are suggested reading paths based on your role:\r\n\r\nIf you are a program manager or donor official evaluating whether to fund a DPI process: read Chapter 1 (especially the scoping checklist) and Chapter 4, Section 4.8 (timeline and realistic expectations). These sections will help you assess feasibility and set appropriate expectations for what can be achieved within a project cycle.\r\n\r\nIf you are a technical lead or CTO responsible for deploying the DPI infrastructure: read Chapter 3 in its entirety, with particular attention to the data space architecture (Section 3.4) and the checklist (Section 3.8). Cross-reference with Chapter 4, Section 4.7 (the adapted rulebook) for governance requirements that affect technical design.\r\n\r\nIf you are a facilitator or researcher leading the multi-stakeholder process: read Chapter 2 (the workshop methodology) and Chapter 4 (the governance design sessions) as your operational manuals. The consensus-and-dissent methodology (Chapter 2) and the Light Governance protocol (Chapter 4) are the tools you will use most directly.\r\n\r\nIf you are an institutional leader (from a coffee institute, a cooperative, a ministry) invited to participate in a DPI process: read Chapter 1, Section 1.1 (what a DPI is and why it matters) and Chapter 2, Section 2.3 (what will happen at the workshop and what your participation involves). These sections are designed to be accessible to participants who are not DPI specialists.\r\n\r\nBefore You Begin: What This Process Requires\r\n\r\nBuilding a Digital Public Infrastructure is one of the most rewarding and impactful things you can do in agricultural development. It is also one of the most demanding. We have written this guide to make the process as transparent and replicable as possible, but transparency demands that we be equally clear about what it requires. The following cautionary statements are not disclaimers — they are hard-won lessons from our own experience.\r\n\r\n⚠ CAUTION\r\n\r\nThis process requires institutional navigation skills, not just technical skills. A DPI is thirty percent technology and seventy percent governance. The technology components described in Chapter 3 are well-documented, open-source, and increasingly mature. The hard part is not deploying a data space connector; it is convincing an institutional director that their organization should connect to one. If your team consists entirely of engineers and data scientists, you are missing the most critical capability. You need people who can read institutional politics, translate technical concepts into the language of each partner’s priorities, and sustain multi-stakeholder relationships over years. Without these skills, the technology will be built and the governance will fail.\r\n\r\n⚠ CAUTION\r\n\r\nThis process requires deep knowledge of the sector and the country. The guide provides a methodology, but the methodology must be applied with intimate knowledge of the specific agricultural value chain, its institutions, its power dynamics, its history, and its culture. A practitioner who has never worked in the coffee sector attempting to build a DPI for coffee will struggle in ways that no guide can prevent. The Associate Researcher, in particular, must have working knowledge of the country’s institutional landscape and ideally be based in or from the country. Cultural competence and local networks cannot be imported or improvised.\r\n\r\n⚠ CAUTION\r\n\r\nThis process requires sustained funding and institutional patience. The mapping-to-mandate phase (Chapter 2) can be completed in six to twelve months. The technology deployment (Chapter 3) can run in parallel. But the governance process (Chapter 4) requires twelve to twenty-four at minimum to reach a signed constitutional charter. Most donor project cycles are twelve to twenty-four months. This means that building a DPI almost always requires overlapping funding streams, institutional mandates that extend beyond a single project, and donors who understand that governance cannot be rushed. If your funding horizon is twelve months with no realistic prospect of continuation, we recommend investing in the AI-mediated mapping and consultation phases (Chapter 2, Sections 2.1–2.2), which produce standalone value, rather than attempting the full process and leaving it incomplete.\r\n\r\n⚠ CAUTION\r\n\r\nThis process requires honest brokering and perceived neutrality. The convening organization must not be a market competitor to any potential participant. International research centers, academic institutions, and certain international organizations can serve this role. Private companies, even well-intentioned ones, will struggle to build the trust required for multi-stakeholder governance design. If you are from a private company and want to support a DPI process, your most effective role is as a technology partner (Chapter 3), not as the convener (Chapter 2) or the governance facilitator (Chapter 4). Perceived neutrality is not a nice-to-have; it is a prerequisite for every institution in the room to speak candidly about their data, their interests, and their red lines.\r\n\r\n⚠ CAUTION\r\n\r\nThis process requires comfort with ambiguity and emergent outcomes. A DPI process is not a project with a fixed scope, a Gantt chart, and predetermined deliverables. It is an emergent process where the outcome is shaped by the interactions of the participants. The joint statement that comes out of the workshop will not be the statement you would have written alone. The governance framework that emerges from Sessions 2–8 will reflect compromises that no single actor would have chosen. If you need to control outcomes, this is not the right approach. The practitioner’s role is to design the process, facilitate the interactions, and trust the community to produce governance that serves its own needs.\r\n\r\n⚠ CAUTION\r\n\r\nDo not confuse deploying technology with building a DPI. It is possible — and tempting — to deploy the Open-Source Stack (Chapter 3), register polygons, issue farmer ID cards, and call the result a DPI. It is not. A DPI without governance is a platform with public branding. The technology creates the possibility of shared infrastructure; the governance creates the reality . If you deploy the technology without building the institutional architecture described in Chapter 4, you will have created a useful set of tools that will be adopted by some, ignored by others, and governed by no one. Within two project cycles, it will fragment into the same data islands it was meant to replace.\r\n\r\nWhat This Guide Is and What It Is Not\r\n\r\nThis guide is a practitioner’s how-to manual based on real experience. It describes what we did, what worked, what did not, and what we would do differently. It provides concrete methodologies, checklists, and examples that can be adapted to other contexts.\r\n\r\nThis guide is not a definitive or complete manual. It documents a process that is still underway. The Honduras Coffee Data Space has not yet completed its full governance cycle; no agricultural DPI anywhere in the world has demonstrated long-term financial sustainability without donor support. We flag knowledge gaps honestly throughout the text, and we invite practitioners in other countries and commodities to contribute their own experience to future editions.\r\n\r\nThis guide is not a substitute for expertise. Reading it will give you a clear understanding of the DPI-building process, but executing that process requires the skills, knowledge, and relationships described in Chapter 1, Section 1.2. We have tried to be as transparent as possible about what those requirements are, precisely so that practitioners can make informed decisions about whether and how to proceed.\r\n\r\nWe believe that shared digital infrastructure for agricultural sectors is not a luxury — it is a necessity. The alternative — continued fragmentation, vertical data silos, invisible farmers, redundant collection, and institutional isolation — is not sustainable. But building the alternative requires doing it right: with the right team, the right partnerships, the right governance, and the right expectations. This guide is our contribution to making that possible.\r\n\r\n— Federico Ceballos-Sierra, Brian King, and Christian Hennig\r\n\r\nMarch 2026"
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+  "gardian_id": "4bf9bc897505b2d7ae8f281db7014be2",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/10568/134709",
+  "description": "",
+  "id": "3cba80ccb4934f588b679a8db9c01158",
+  "title": "Transforming Agrifood Systems in West and Central Africa (TAFS-WCA): guidelines for community engagement for introducing climate-resilient crop varieties, enhancing adoption of improved crop management practices, and setting up small and medium-scale enterprises",
+  "language": "English",
+  "resource_type": "Training Material",
+  "release_year": "2023",
+  "rights": "CC-BY",
+  "dataNODE_id": "4bf9bc897505b2d7ae8f281db7014be2",
+  "keywords": [
+    "agribusiness",
+    "capacity development",
+    "crop systems",
+    "food security",
+    "impact assessment",
+    "livelihoods",
+    "plant production",
+    "policies and institutions",
+    "smallholder farmers",
+    "nutrition, health and food security",
+    "sdg 1 - no poverty",
+    "sdg 2 - zero hunger",
+    "guidelines",
+    "manuals",
+    "climate resilience",
+    "community development",
+    "decision making",
+    "engagement",
+    "crop management"
+  ],
+  "geography": {
+    "regions": [
+      "Western Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "World",
+      "Middle Africa"
+    ],
+    "countries": [
+      "Nigeria"
+    ]
+  },
+  "content": "Transforming Agrifood Systems in West and Central Africa (TAFS-WCA)\r\n\r\nGuidelines for community engagement\r\n\r\nfor\r\n\r\nintroducing climate-resilient crop varieties, enhancing adoption of improved crop management practices, and setting up small and medium-scale enterprises\r\n\r\nElizabeth Babalola and Ramota Oladejo\r\n\r\nInternational Institute of Tropical Agriculture (IITA)\r\n\r\nNovember 2023\r\n\r\nAcknowledgment\r\n\r\nWe have drawn inspiration and knowledge from diverse sources and dedicated individuals to create these guidelines for community engagement in introducing climate-resilient crops, improved management practices associated with selected crops, and setting up Small and Medium Enterprises.\r\n\r\nWe are particularly grateful to the research and development teams, organizations, and institutions involved in the write-up and publication of the following articles:\r\n\r\n- A scoping review of the adoption of climate-resilient crops by small-scale producers in low- and middle-income countries ( Maricelis Acevedo et al.)\r\n- The adaptive research model of CIALCA (B. Vanlauwe and P. Pypers)\r\n- Participatory Research Extension Approach: N2Africa Extension Method (Hakeem A. Ajeigbe and Kenton Dashiell).\r\n\r\nAcronyms\r\n\r\nCDC – Center for Disease Control and Prevention\r\n\r\nCSR – Corporate Social Responsibility\r\n\r\nEAs – Extension Agents\r\n\r\nGOs – Government Organizations\r\n\r\nIP – Innovation Platform\r\n\r\nM&E – Monitoring and Evaluation\r\n\r\nPREA – Participatory Research Extension Approach\r\n\r\nSMEs – Small and Medium Enterprises\r\n\r\nTAFS-WCA – Transforming Agrifood systems in West and Central Africa\r\n\r\nMBILI – Managing Beneficial Interactions for Legume Intercrops\r\n\r\nNGO – Non-Governmental Organization\r\n\r\nRTBs – Root, Tuber, and Banana\r\n\r\nContents\r\n\r\nAcknowledgment\t1\r\n\r\nAcronyms\t2\r\n\r\nList of tables\t4\r\n\r\n1.0 Introduction\t5\r\n\r\n2.0 Literature review\t6\r\n\r\n2.1 Evidence on the adoption of climate-resilient crops\t6\r\n\r\n2.2 Evidence on the dis-adoption of climate-resilient crops\t6\r\n\r\n3.0 Introducing climate-resilient crops (Crops targeted under WCA for selected countries, esp. RTBs and bio-fortified crops)\t6\r\n\r\n3.1 Recommendations on guidelines to introduce climate–resilient crops\t6\r\n\r\n4.0 Best techniques for getting uptake of improved management practices associated with selected crops\t7\r\n\r\n4.1 Practical approaches\t8\r\n\r\n4.1.1   The demonstration-adaptation-adoption cycle\t9\r\n\r\n4.1.2 Participatory research and extension approach (PREA): The process\t12\r\n\r\n5.0 Setting up small and medium enterprises (SMEs)\t17\r\n\r\n6.0 Key and general principles, guidelines, and standards when engaging farmers.\t19\r\n\r\n6.1 Key principles, guidelines, and standards when engaging farmers\t19\r\n\r\n6.2 General principles, guidelines, and standards when engaging farmers\t21\r\n\r\n7.0 Steps for sustaining community engagement year-round\t22\r\n\r\nStep 1: Pause for a strategic review and reset\t22\r\n\r\nStep 2: Prioritize efforts to improve your focus\t22\r\n\r\nStep 3: Create a community super user program\t22\r\n\r\n8.0 Conclusion\t22\r\n\r\nAnnexes\t24\r\n\r\nAnnex A: Meaning of words\t24\r\n\r\nAnnex B:  References\t24\r\n\r\nList of tables\r\n\r\nTable 1: Selected characteristics of the various steps in the adaptive research cycle------------9\r\n\r\nTable 2: Training activities associated with the various steps in the adaptive research cycle---10\r\n\r\nTable 3: Changes from the use of conventional to participatory-----------------------------------12\r\n\r\nTable 4: Changing roles for partners in PREA----------------------------------------------------------12\r\n\r\nTable 5: Key principles of community engagement-----------------------------------------------20\r\n\r\n1.0 Introduction\r\n\r\nThe Transforming Agrifood Systems in West and Central Africa (TAFS-WCA) is a transformative initiative aiming at nutritious, climate-adapted, and market-driven food systems. It will do so through developing and scaling novel and inclusive production and postharvest technologies, participatory decision-making and planning, informed governance, and the strengthening of gender and youth transformative business hubs.\r\n\r\nThe Initiative works on RTB Crops, including yam, cassava, sweet potato, and banana; nutritious vegetables; and bio-fortified varieties of crops like yellow maize, yellow cassava, and orange-fleshed sweet potato. The uptake of the outputs produced by the innovators (scientists, breeders, and processors) is paramount in achieving the Initiative's goal. This write-up serves the purpose of guiding and helping the Initiative and its partners (implementing partners and others) to have good entry points to penetrate and access the community for better uptake of the products by the farmers and other beneficiaries. Successful engagement creates trust for mutual benefit.\r\n\r\nCommunity engagement seeks better participation from community members to achieve long-term and sustainable outcomes, processes, relationships, discourse, decision-making, or implementation. To succeed, it must encompass strategies and processes that are sensitive to the community context in which it occurs. Engaging the community can be complex. However, according to the CDC (1997), community engagement is \"The process of working collaboratively with and through groups of people affiliated by geographic proximity, special interest, or similar situations to address issues affecting the well-being of those people. It is a powerful vehicle for bringing about environmental and behavioral changes that will improve the livelihood of the community and its members. It often involves partnerships and coalitions that help mobilize resources and influence systems, change relationships among partners, and serve as catalysts for changing policies, programs, and practices.\"\r\n\r\nTo be effective, we need to recognize and respect the diversity and assets of the communities we engage with. Building strong relationships takes time, and it takes even longer to repair relationships that have been damaged. Approach all groups with humility and anticipate learning about the subtle nuances of each community.\r\n\r\nInvestors should drive the community engagement process, with support from the government and civil society, where appropriate. Yet, although government agencies and civil society can provide an entry point into communities, their interests and limited capacity can sometimes compromise the process.\r\n\r\n2.0 Literature review\r\n\r\n2.1 Evidence on the adoption of climate-resilient crops\r\n\r\nExamining the conditions that have led to the adoption of climate-resilient crops over the past 30 years in lower- and middle-income countries, the descriptive analysis performed by Maricelis Acevedo 1 et al. shows that small-scale producers adopted climate-resilient crops and varieties to cope with abiotic stresses such as drought, heat, flooding, and salinity. The most prevalent trait in the dataset was drought tolerance, followed by water-use efficiency. The analysis found that the most important determinants of the adoption of climate-resilient crops were the availability and effectiveness of extension services and outreach, followed by education levels of heads of households, farmers' access to inputs—especially seeds and fertilizers—and the socio-economic status of farming families. About 53% of studies reported that social differences such as sex, age, marital status, and ethnicity affected the adoption of varieties or crops as climate change adaptation strategies.\r\n\r\nTo cope with climate change, farmers need to modify production and farm management practices, such as adjusting planting time, supplementing irrigation (when possible), intercropping, adopting conservation agriculture, accessing short- and long-term crop and seed storage infrastructure, and changing crops or planting more climate-resilient crop varieties.\r\n\r\nFor all countries, but especially those that rely on domestic agricultural production for food security, one of the most critical and proactive measures that can be taken to cope with food insecurity caused by unpredictable weather patterns is for farmers to adopt climate-resilient crops.\r\n\r\nThe socio-economic status of farmers plays a large part in their adoption of climate-resilient technologies.\r\n\r\n2.2 Evidence on the dis-adoption of climate-resilient crops\r\n\r\nDis-adoption of climate-resilient crops and crop varieties was discussed and included in the evidence synthesis. The major reasons for dis-adoption included technology not meeting expectations due to poor performance or quality of the technology or a variety of government policies, technical constraints, labor shortages, or financial constraints. The studies indicated that dis-adoption was specifically due to the performance of a crop variety.\r\n\r\n3.0 Introducing climate-resilient crops (Crops targeted under WCA for selected countries, esp. RTBs and bio-fortified crops)\r\n\r\n3.1 Recommendations on guidelines to introduce climate–resilient crops\r\n\r\nThe following are recommended as guidelines to introduce climate–resilient crops.\r\n\r\n- There is no single profile that applies to all farmers. Therefore, extension services will need to continue to evolve to be:\r\n    - 1) Participatory, (2) Information and communications technology-enhanced (3) partnership-based.\r\n    - This partnership should include various actors, such as women's groups, universities, the private sector, and non-governmental organizations, to provide customized and appropriate information for diverse needs.\r\n- Access and availability of climate-resilient crop seeds must be combined with relevant and timely advisory services, such as early-warning systems for the weather.\r\n- Ensuring that farmers have multiple options to access seeds for a range of climate-resilient crops and varieties is essential. Empowering existing social networks, such as farmer organizations, can achieve this.\r\n- High-quality studies are needed on how members of households, and not just heads of households, make decisions about how to respond to climate change.\r\n- National policies need to support farmers' access to other assets and services, such as education, land, finance services, and diverse income-earning opportunities. Adopting climate-resilient crops and technologies will be limited without these provisions, especially education.\r\n- Farmers will not adopt climate-resilient crops solely based on environmental-adaptation qualities. Development and breeding programs must consider farmer and market trait preferences.\r\n- Mandating disaggregated data collection to identify strategies that are working and who they are working for in agricultural surveys and research will enable policymakers and donors to respond with more appropriate and informed interventions.\r\n\r\n4.0 Best techniques for getting uptake of improved management practices associated with selected crops\r\n\r\nA multiple-intervention approach is needed if countries want to promote the adoption of climate-resilient crops. Farmers do not adopt climate-resilient crop(s) varieties without changing other practices, such as planting dates, water-conserving technologies, etc. This approach can be an effective way to introduce management practices to a community, and it involves using various methods to convey information and skills to community members, with the goal of promoting the adoption and sustained use of the desired management practices. Some examples of interventions that could be used in this approach include:\r\n\r\n1. Training sessions : Conduct training sessions that teach community members about management practices and provide them with the necessary skills to implement them. For example, in the case of introducing climate-resilient yam to the community, all the following management practices on the yam must be demonstrated to the farmers.\r\n\r\nYam is an important staple crop that is widely cultivated in tropical regions of the world. There are several agronomic practices associated with yam cultivation, including:\r\n\r\n- i. Land preparation : The land should be cleared of all vegetation and prepared by plowing, harrowing, and ridging. The ridges should be made in such a way that they can retain water.\r\n- ii. Planting: Yam is usually propagated by using seed yams, which are small pieces of yam tubers. These seed yams are planted in mounds or ridges, with a spacing of about 1 meter between mounds.\r\n- iii. Fertilization: Yam requires adequate amounts of nitrogen, phosphorus, and potassium for optimal growth. Organic manure such as poultry droppings, cow dung, or compost can be applied before planting or as a side dressing during the growing period.\r\n- iv. Weed control: Weeds can compete with yam for nutrients and reduce yield, but can be controlled through hand weeding, hoeing, or applying herbicides.\r\n- v. Irrigation: Yam requires a consistent supply of water during its growing period. If the rainfall is inadequate, irrigation may be necessary to maintain optimal growth.\r\n- vi. Disease and pest control: Yam can be attacked by various pests and diseases such as nematodes, yam beetles, and anthracnose. Farmers should use disease-resistant varieties, practice crop rotation, and apply appropriate pesticides when necessary.\r\n- vii. Harvesting : Yam is usually harvested 7-12 months after planting when the leaves start to turn yellow and dry out. Harvesting should be done carefully to avoid damage to the tubers.\r\n- viii. Storage: Yam tubers can be stored for several months under appropriate conditions, such as in a cool, dry, and dark place. This helps to reduce spoilage and maintain their quality.\r\n\r\nTop of Form\r\n\r\nBottom of Form\r\n\r\n2. Informational materials: Develop and distribute informational materials such as brochures, posters, or videos that explain management practices and their benefits.\r\n3. Peer-to-peer education : Encourage community members who have successfully implemented management practices to share their experiences and knowledge with other community members.\r\n4. Community engagement activities: Organize events or activities that promote community engagement and participation, such as workshops or discussion groups.\r\n5. Incentives: Provide incentives to encourage community members to adopt and maintain the management practices, such as financial rewards or recognition for successful implementation.\r\n6. Brainstorming and discussion sessions: Invitate community members to participate in brainstorming and discussion sessions to build consensus on the most feasible ways to introduce improved management practices for each crop.\r\n\r\nBy using a combination of these interventions, community members can be exposed to the management practices through multiple channels, which can increase their understanding of the practices and their motivation to implement them. This can lead to greater adoption and sustained use of the desired management practices, ultimately benefiting the whole community.\r\n\r\n4.1 Practical approaches\r\n\r\nThe use of real observations and experiences on how resilient crops are expected to be different from other crops that cannot survive climate change hardships are paramount practical approaches to showcase to the community members to explain best techniques for getting uptake of improved management practices associated with selected crops. Then, using demonstration farms, grow some resilient crops against non–resilient ones for farmers to see as evidence of the explanations given.\r\n\r\nThe next session below (Adaptive research cycle: The demonstration-adaptation-adoption cycle)\r\n\r\nprovides explicit practical approaches.\r\n\r\n4.1.1   The demonstration-adaptation-adoption cycle\r\n\r\nAfter initial problem diagnosis, the adaptive research cycle is implemented and usually consists of different, logically linked steps with feedback cycles between each step. The three steps involved are discussed below.\r\n\r\n1) Demonstration step: Demonstration trials will consist of multiple best-bet technologies derived from earlier, eventually on-station, activities or from experiences in other areas under similar agro-ecological conditions. Such technologies could include improved agronomic practices (e.g., adapted cassava spacing to enable a higher population of intercropped legumes), improved nutrient management practices (e.g., micro-doses of fertilizer in combination with locally available organic resources), or improved cropping systems (e.g., the MBILI intercropping arrangement to allow soybean-maize intercropping). All demonstrations normally integrate improved germplasm. Observations taken in demonstration trials include the agronomic and economic performance of the tested technologies (against the local practice) and gender-segregated participatory evaluation of the technologies. Demonstration trials are usually installed at the Action Site level and are relatively few, depending on the overall goals of the initiatives.\r\n\r\n2) Adaptation step: Based on the performance of the tested technologies at the demonstration sites, a few of the most promising technologies are transformed into adaptation packages, consisting of those technologies (2-3 maximally) and local practice. The packages themselves contain the needed seed, inputs, and information tools to allow the household to install the package in an area of about 10 by 10 m per treatment, with the assistance of NGO facilitators and members of the technical committees of the participating farmers' associations. The participating households also receive a field book that allows taking records of all important farm activities, observations on yields and pests/diseases, with the assistance of the technical committee member of the farmer associations, and visits to the adaptation site. Adaptation trials are many (e.g., 200 – 1000 per site per season), and their final number depends on the overall goals of the Initiative. Such trails can eventually be accompanied by soil and plant sampling on a sub-sample of sites to better understand plant-soil relationships underlying the performance of a specific technology.\r\n\r\n3) Adoption step : After participating households have tested and evaluated (a set of) specific technologies against local practice, some of these will continue using those specific (sets of) technologies. This number will vary and depend on the nature of the technology and the creation of enabling conditions for technology uptake. In this step, farmers are completely free to implement the technologies, and, in terms of observations, attempts are made to observe the impact of those technologies against an identified area where the farmer still uses local practices (Table 1). Note that the improved technology and local practice are not laid out as in a demonstration or adaptation trial; such areas are identified by pegging out specific areas within the farm managed by the household. Obviously, this can only be achieved on a sub-sample of adopting households.\r\n\r\nTable 1: Selected characteristics of the various steps in the adaptive research cycle.\r\n\r\n| Step             | Number of treatments and plot size                                                                                        | Number of sites and geographical focus                                           | Management                                                                                                 | Observations taken                                                                              | Level of understanding by farmer households                                                                                               |\r\n|------------------|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------|\r\n| Demonstration  * | Relatively many (8-15), including a local practice; plot size varies between 25 and 100 m  2                              | Few test sites (5-10) at the Action Site level                                   | Co-managed by researchers and communities, the latter most often through collective action by associations | Agronomic performance, changes in soil fertility, economic evaluation, participatory evaluation | Good since farmers get a good idea of the performance of technology (though not all farmers are fully involved during the full crop cycle |\r\n| Adaptation       | Few (3-4), including a local practice; plot size varies between 64 and 100 m  2                                           | Many test sites (several hundred) at the Action and Satellite Site level         | Managed by individual farmer households with direct technical backstopping by facilitators                 | Agronomic and economic evaluation on a sub-sample, participatory evaluation                     | Very good since households apply each technology on their own farm and are fully responsible for the management                           |\r\n| Adoption         | No treatments, although an improved practice is usually compared to a local one; plot size is determined by the household | Unlimited for promising technologies both at the Action and Satellite Site level | Managed by individual farmer households with indirect technical backstopping by facilitators               | Agronomic and economic evaluation on a sub-sample, participatory evaluation                     | Excellent since households gather several seasons of experience with the new technology                                                   |\r\n\r\n* In some cases where problems persist and technological solutions are not easily identified, some trials can move to researcher-managed on-station trials to develop a better understanding of the major constraints at hand and explore potential solutions.\r\n\r\n4.1.1.1 Training activities around the demonstration-adaptation-adoption cycle\r\n\r\nThe adaptive research cycle is accompanied by a specific training and evaluation program involving technical research staff, NGO facilitators, technical committee members from farmer associations, and individual households. The various training activities and some details on their implementation are detailed in Table 2.\r\n\r\nTable 2: Training activities associated with the various steps in the adaptive research cycle.\r\n\r\n| Step             | Training activity                                                                                                                                                                        | Number of training sessions and participants                                                                                                     | Facilitated by whom and number of facilitators                                                                                         |\r\n|------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------|\r\n| Demonstration  * | Training of NGO facilitators and the technical committees of the associations hosting the demonstration sites                                                                            | Usually one training session per demonstration with the involvement of NGO staff, governmental extension staff, and farmer group representatives | National research staff (e.g., INERA); a few facilitators (2-3) are sufficient to handle the training within a limited period.         |\r\n| Adaptation       | Training the technical committees of the associations hosting the demonstration sites; the technical committees then train individual households for installing the adaptation packages. | One training session per association per season, including all households that have agreed to install an adaptation package.                     | NGO facilitators: at least one facilitator is needed for 10-15 farmer associations in order to complete the training in due time.      |\r\n| Adoption         | The technical committees of the associations backstop individual households in implementing the improved technology.                                                                     | One training session per association per season; participants include all interested community members                                           | Technical committee members of the farmer associations; at least two members per association would be needed to absorb staff turnover. |\r\n\r\n4.1.1.2 Timing\r\n\r\nThe timing of each of the steps depends on the level below:\r\n\r\nLevel of knowledge: If one has experience in a certain area, one could drop the demonstration step and move straight into the adaptation step, especially if one has gone through the demonstration step through earlier initiatives.\r\n\r\nTarget crop: Depending on the growth cycle of a crop, each step could take one (e.g., maize, legumes), two (e.g., cassava), or more (e.g., bananas) cropping seasons.\r\n\r\nTarget cropping system: Depending on the type of cropping system, each step could take one (e.g., monocrops and intercropping with maize and legumes), two (e.g., maize-legume rotations, cassava-legume intercrops), or more (e.g., bean-banana intercrops) cropping seasons.\r\n\r\n4.1.1.3 Necessary conditions for the adaptive research cycle to function\r\n\r\nThe following issues need to be addressed to create an enabling environment to facilitate the adoption of soil management technologies:\r\n\r\nLocal seed systems : Since the number of adaptation packages can be high and increasing over time, the seed component to be included in these packages needs to be addressed through community-based seed multiplication efforts or other means (e.g., agro-dealer networks).\r\n\r\nAccess to inputs and output markets : Technologies including agricultural inputs (e.g., micro-doses of fertilizer) need to be necessarily accompanied by activities facilitating access to those inputs and access to output markets so farmers have access to income to purchase these inputs.\r\n\r\nFarmer capacity and training : Farmer knowledge and training are crucial for the adoption of improved soil management technologies. Literacy levels must be considered when developing training materials and organizing farmer training events.\r\n\r\nTechnical backstopping and facilitation : During the initial stages, appropriate and effective facilitation and technical backstopping are crucial for its success.\r\n\r\n4.1.2 Participatory research and extension approach (PREA): The process\r\n\r\nThe process of PREA requires an interaction among stakeholders that is fundamentally different from conveying standard messages from the top down. This requires processes that must be carefully managed, facilitated, and stimulated with partners contributing, particularly where they have a unique role. Table 4 highlights the changing roles of partners in PREA and the\r\n\r\nexpected contributions from the different partnership sectors.\r\n\r\nTable 3. Changes from the use of conventional to participatory\r\n\r\n| Conventional approach (T&V)                      | Participatory approach (PREA)           |\r\n|--------------------------------------------------|-----------------------------------------|\r\n| Telling farmers what to do                       | Discussing with farmers                 |\r\n| Making farmers change                            | Working with farmers to effect change   |\r\n| Extension workers and researchers  know best     | Learning from farmers                   |\r\n| Modern methods are better than  traditional ones | Building on local traditional knowledge |\r\n| Teaching                                         | Providing feedback to communities       |\r\n| Use of contact farmers and  demonstrations       | Promoting farmer-to-farmer extension    |\r\n\r\nTable 4. Changing roles for partners in PREA\r\n\r\n| Partners                | Role changes                                                                                                                                   | Unique contributions                                                         |\r\n|-------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|\r\n| Farmers                 | From passive recipients of  messages to active participants in  their own development process                                                  | Knowledge of their own  natural, financial, economic  and social environment |\r\n| Extension agents        | From providers of messages to  facilitators of learning processes                                                                              | Facilitation skills                                                          |\r\n| Researchers             | From detached scientists to  facilitators and participants in on-farm  research                                                                | Experimental design,  knowledge                                              |\r\n| Private sector          | From pushing inputs and buying  produce at prices unfavorable  to farmers to support farmers  in the more efficient market-related  production | Information provision  specific to the products  they buy and sell           |\r\n| NGOs                    | Organizing production means  to facilitate conditions conducive to  participatory development                                                  | Process management and  facilitation skills                                  |\r\n| Governments and  donors | From implementing projects defined  in time and space to support  long-term development processes                                              | Enabling policies  Resources                                                 |\r\n\r\n4.1.2.1 Action planning\r\n\r\nThis is planning by the community, which helps motivate the people and gives opportunities to male and female farmers and disadvantaged groups to express their views. The findings from the initial situation analysis are important and help outsiders to know the community, but the results are even more important for the community members. Request them  to think about possible solutions and which local institutions can play a role in resolving these problems. Collective decision-making and local ownership are essential for success.\r\n\r\nBecause of their involvement from the beginning, the community will:\r\n\r\n1. Motivate people to become more involved in an action research and development process that can improve their livelihoods\r\n2. Allow the poorer and disadvantaged groups to express their views once household and community issues have been explored\r\n3. Provide feedback to the rest of the community on the issues and needs identified in the situation analysis\r\n4. Analyze with the community the underlying causes of the problems identified and identify possible solutions\r\n5. Identify possible local institutions to help take forward some of these solutions. This is best achieved in community workshops by nominated members of each group who provide reports from each of their groups. After this, it is important to:\r\n6. Agree on a schedule of work to be undertaken in addressing those needs;\r\n7. Agree on the criteria and indicators, which enable the community to see whether their work is genuinely leading to an improved situation\r\n\r\n4.1.2.2 Local groups and lead farmers\r\n\r\nThe main approach is to work with local groups and lead farmers selected by the community-based organizations that they represent. They should undertake the piloting and testing of new technologies. Regular feedback from the lead farmers to the groups will ensure the groups' involvement in planning and implementation and encourage further farmer-to-farmer testing and adaptation (and diffusion). The lead farmer is not a title but a role to be played by the actor with specific reference to the current activities. In certain situations, or by some other organizations, the lead farmer is called a master/volunteer/demo farmer. Whatever the nomenclature, the roles are similar. As usual, we must undertake to have female lead farmers who should be not less than 50% in number. The responsibilities of lead farmers and the groups also need to be agreed upon.\r\n\r\n4.1.2.2a Potential role of local groups\r\n\r\n1. To formally adopt the program into their activities\r\n2. To appoint a person or persons responsible for reporting on progress and identifying issues/problems that affect the program; this is likely to be the lead farmer\r\n3. To encourage participation by other farmers in trying out the new techniques\r\n4. To invite the extension worker to attend meetings regularly\r\n5. To arrange field days that cover all farmers\r\n6. To evaluate the new methods at the end of the season and plan for the new season\r\n\r\n4.1.2.2b Potential responsibilities of lead farmers\r\n\r\n1. To motivate other farmers to try out new technologies\r\n2. To assist with the project planning process using participatory methods\r\n3. To assist the extension agent (EA) in training the group and other farmers\r\n4. To host mid- and end-of-season evaluations of the test plots and demonstrations\r\n5. To ensure that information is disseminated to the community at large\r\n6. To hold regular meetings with other farmers and present concerns to the group and the EA\r\n7. To facilitate coordination between the group and the EA\r\n\r\n4.1.2.3 Participatory monitoring and evaluation\r\n\r\nExperience sharing, self-evaluation, and planning for the next season: Exchange visits, field days, and crop evaluations will provide opportunities for farmers to learn and share; these\r\n\r\nwill increase awareness among lead and secondary farmers and the adoption of new technologies. Monitoring and evaluation (M&E) form an integral part of the PREA process, and the earlier it is incorporated into program activities, the better. M&E allows farmers, researchers, and EAs to ensure that stages in the PREA address identified problems and concerns and the project objectives. This requires two steps that are more formal:\r\n\r\n1. A mid-season evaluation and monitoring of the new practices being tested\r\n2. An end-of-season evaluation where the whole process can be evaluated and plans made for the coming season\r\n\r\n4.1.2.4 Share innovations and lessons\r\n\r\nEngagement outcomes (including the M&E results) should be shared among those involved in the engagement process. This enables validation of the approach and increases motivation for further engagement and action. Often, only successes are communicated.\r\n\r\nHowever, failures should also be highlighted—within a culture of transparency and trust—to avoid future ineffective or maladaptive investments of time and resources. In addition, while the context of adaptation may be unique to particular communities of place and interest, there may be innovations and other lessons that may apply beyond one particular network, benefiting others across many networks. Sharing engagement outcomes engenders increased motivation, transparency, and trust for future engagement and action. Innovations from one network may also apply to other networks.\r\n\r\n4.1.2.5 Capacity building for implementing PREA\r\n\r\nSuccessfully implementing PREA requires new skills, knowledge, and attitudes, not only for extension workers but also for farmers who are used to working with conventional approaches.\r\n\r\nPREA is a process learning cycle, which requires flexibility in its implementation. The complexities of rural situations require that capacity is developed and the institutional approach to create an environment conducive for the process to be accepted. It may require EAs to change from only being technical advisors to being process leaders and facilitators.\r\n\r\nParticipatory development processes are not blueprints and cannot be predicted in terms of output.\r\n\r\nThe projects need to allocate resources for training at different levels. Dissemination begins within the project through a series of training activities: Training of Trainers in best techniques for getting uptake of improved management practices associated with selected crops. These specialists will return to their respective hubs and countries and organize workshops of national cooperators, particularly the representatives of large farmers' associations and NGOs active within each country. Initiative staff will provide technical and logistic backstopping for these national cooperator workshops. Finally, each trainer will schedule a series of stakeholder workshops within the Initiative action sites where specific Initiative activities and cooperators' responsibilities are discussed, technologies demonstrated, and the use of project dissemination tools explained.\r\n\r\n4.1.2.6 Documentation\r\n\r\nRecord keeping and documentation are immensely important. The researchers, EAs, and the lead farmers should endeavor to document every activity, whether major or minor. The number of participants present during meetings, field days, etc., should be recorded with a note of the number of males and females present. During visits to the field, record anything abnormal or outstanding you noticed. These details are crucial in PREA as they will ultimately help in interpreting results. Records should be kept of all meetings, stating the decisions and commendations made and the follow-up activities. During field days and other meetings or when interacting with farmers, ask open-ended and probing questions to fully understand their opinions and experiences. Technicians, EAs, and lead farmers should report successes to their superiors, who should publicize them. They should be reported to other partners, farmers, neighboring communities, projects, etc., to appreciate and share experiences.\r\n\r\n4.1.2.7 Gender dimensions of PREA\r\n\r\nIn many cases, men and women may be better suited to or prefer to undertake different tasks. This must be considered in the dissemination exercise. PREA allows the mainstreaming of gender, providing an opportunity for encouraging gender equity through the inclusion of women as participants and promoting equal access to resources with benefits for both men and women. This does, however, require commitment from implementing partners to ensure that gender issues are given appropriate consideration.\r\n\r\n4.1.2.7a Some considerations for mainstreaming gender.\r\n\r\n1. Discussion among partners on gender issues and development constraints\r\n2. Capacity building for partners on gender interventions\r\n3. Disaggregation and evaluation of project data according to gender\r\n4. Assessment of progress on lowering gender barriers\r\n5. Commitment to gender mainstreaming from policymakers and decision-takers, where applicable\r\n6. Policy changes towards the adoption of gender-sensitive approaches, where applicable\r\n\r\nGender analysis explores the norm of male and female behaviors and experiences, and the implications of the different ways that men and women contribute to and benefit from the development processes. The introduction of any intervention needs to be negotiated and integrated by both male and female farmers for it to be sustainable. The Gender Equality Wheel is a tool that identifies four stages of the progress toward gender equality. This tool, described below, would be used in gender mainstreaming by the project.\r\n\r\n• Empowerment: This refers to resources such as ideas, knowledge, and skills that become available to the community as a result of collaboration with the project. Such resources are the cornerstone of social capital, building self-confidence in women and men as they explore new ways of seeing and acting.\r\n\r\n• Engagement: This refers to the stage at which people (especially women) come out of isolation, discover new possibilities for their lives, and begin to build mutual support. In Initiative Work Packages, attention will be paid to the composition of lead farmers and farmers' groups to ensure gender balance during the selection of participants.\r\n\r\n• Enhancement: This refers to the process when women and men begin to apply new ideas, knowledge, and skills to enhance the lives of family and community members and to provide household and community gains. Training will be given to all farmers, including special training for women farmers and some women collaborators on processing to enhance income generation and improve household nutrition and health.\r\n\r\n• Emergence: This refers to the process when women and men move onto the public stage to take social and political action that transforms their social, cultural, and political environment. Field days and mid-season evaluations would be conducted on women farmers' fields to voice their experience to fellow women farmers and the larger populace.\r\n\r\n4.1.2.8 Building an innovation platform (IP)\r\n\r\nAs part of the PREA and the dissemination strategy, Initiative Work Packages will work with several partners. This entails the formation of platforms at different levels for the execution of Initiative activities. As the Initiative will be disseminating climate-resilient crops and other innovations, the platform so formed is an innovation platform (IP). An IP consists of a set of stakeholders bound together by their individual interests in a shared issue, objective, challenge, or opportunity, with the potential to improve livelihoods, businesses, and other interests. An IP refers both to the emergent properties of groupings of players and their processes, practices, and habits, as well as to the formal structures that might give operational focus to activities and interactions. This platform will be at different levels of operation, with overlapping interests. At the Initiative level, it would comprise all the partners that interact to influence Initiative activities in all target countries and outside those countries. At the country level, it would be composed of those partners whose effect is limited to that country. At the action site, the platform would be made up of groups and individuals who implement or facilitate initiative\r\n\r\ns to achieve set objectives there. A complete IP for the Initiative Work Packages comprises researchers, extension groups, farmers' groups, input/output marketers, NGOs, GOs, and leaders at various levels, all of whom have a vested interest in the outcome of the Initiative.\r\n\r\n5.0 Setting up small and medium enterprises (SMEs)\r\n\r\nCommunity engagement is essential in setting up small and medium enterprises (SMEs) as it helps to create a conducive environment that enables the success of the enterprises. SMEs play a vital role in economic development, job creation, and fostering innovation. To ensure their success, it is essential to establish a strong foundation that supports SMEs and engages the local community. Community engagement serves as a catalyst for SME growth and sustainability by fostering collaboration, generating awareness, and creating a favorable business environment. Here are some ways community engagement can be fostered in setting up SMEs:\r\n\r\n- Understanding the local community: Before engaging with the community, take the time to understand its unique characteristics, demographics, culture, and economic landscape. Conduct market research and analysis to identify the needs, preferences, and challenges of the local market. This knowledge will help tailor your approach, products, and services to better meet the community's requirements.\r\n- Involving community members in the planning process: Community members should be involved in the planning process of SMEs. This can be done through meetings, focus groups, and surveys, where community members can provide feedback and ideas that can inform the planning process.\r\n- Identifying and engaging with the key stakeholders and support organizations: Identify and connect with key stakeholders in the community, including local government representatives, community leaders, business associations, educational institutions, and relevant organizations. Build relationships based on trust, open communication, and mutual benefit to foster collaboration and support for your SME. Engaging with local authorities, such as city councils and regulatory bodies, is crucial for SMEs to navigate legal requirements, obtain necessary licenses and permits, and ensure compliance with regulations. Additionally, connecting with economic development organizations, business support centers, and entrepreneurial networks in the community can provide valuable guidance, resources, and networking opportunities. These entities can assist in business planning, financing options, mentorship, and access to training programs.\r\n- Accessing funding: Access to funding is a critical factor in the success of SMEs. Community members can be engaged in setting up financing mechanisms such as community funds, crowdfunding platforms, and government grants, which can provide financial support to SMEs.\r\n- Building and engaging the workforce: Building a skilled and dedicated workforce is crucial for SMEs' long-term success. Engaging with the local community regarding recruitment, talent development, and skills training is essential. SMEs can collaborate with educational institutions, vocational training centers, and job placement agencies to identify and train potential employees. By investing in the local workforce, SMEs reduce unemployment, enhance skill levels, and foster socio-economic growth within the community. This can be done through workshops, seminars, and mentorship programs.\r\n- Creating awareness and customer base: Community engagement is a powerful tool for raising awareness about SMEs' products or services. By actively participating in community events, sponsorships, and outreach programs, SMEs can introduce themselves to a broader audience and build a loyal customer base. Moreover, engaging with local residents through social media, community newsletters, and word-of-mouth marketing can create brand recognition and attract potential customers, ultimately driving business growth.\r\n- Providing access to markets: SMEs need to access markets to sell their products and services. Community engagement can involve setting up local markets, fairs, and festivals to provide a platform for SMEs to showcase their products and services to the community.\r\n- Engaging in Corporate Social Responsibility (CSR) initiatives: Implement CSR initiatives that align with the community's values and address local social or environmental concerns. This could involve supporting local charities, participating in sustainability programs, organizing community service activities, sponsoring community projects, or participating in environmentally friendly practices. Communicate your CSR efforts transparently to the community, showcasing your commitment to making a positive impact beyond business operations. Actively participate in community events, festivals, and initiatives to establish a presence and demonstrate your commitment to the community. Sponsor or support local events, volunteer for community projects, and engage in activities that align with your business values. This involvement helps build brand visibility and connects you with potential customers and partners.\r\n- Fostering innovation and collaboration: Community engagement brings together diverse perspectives and expertise, fostering an environment that encourages innovation and collaboration among SMEs. Collaborative initiatives, such as incubators, co-working spaces, and industry-specific clusters, provide SMEs with shared resources, mentoring, and knowledge exchange opportunities. By collaborating with other entrepreneurs, SMEs can leverage complementary skills, share costs, and drive collective growth through joint ventures or partnerships.\r\n- Listening and responding to community needs: Regularly seek feedback from the community regarding your products, services, and business operations. Actively listen to their suggestions, concerns, and expectations. Use this feedback to improve your offerings and demonstrate that you value their input. Respond to customer inquiries and complaints promptly and transparently. By addressing community needs, you build trust, loyalty, and customer satisfaction.\r\n- Promoting local economic development: Contribute to the local economy by sourcing goods and services from local suppliers and service providers whenever possible. Support other local businesses by referring customers or collaborating on projects. Participate in initiatives that promote entrepreneurship, skills development, and economic growth within the community. You foster a sense of shared prosperity when you actively contribute to the local economy.\r\n- Communicating effectively: Establish regular and transparent communication channels with the community. Utilize social media, newsletters, community forums, and public meetings to share updates, seek input, and address concerns. Effective communication fosters trust, encourages community involvement, and helps build a positive brand image.\r\n- Evaluating and adapting: Regularly evaluate the impact and effectiveness of your community engagement initiatives. Measure key performance indicators such as community satisfaction, brand recognition, customer loyalty, and community partnerships. Use this feedback to refine your strategies, adapt your approach, and continuously improve your community engagement efforts.\r\n\r\n6.0 Key and general principles, guidelines, and standards when engaging farmers.\r\n\r\n6.1 Key principles, guidelines, and standards when engaging farmers\r\n\r\nThe key principles and standards when engaging farmers are presented below (Table 5).\r\n\r\nTable 5: Key principles of community engagement\r\n\r\nSource: https://doh.wa.gov/sites/default/files/legacy/Documents/1000/CommEngageGuide.pdf\r\n\r\n6.2 General principles, guidelines, and standards when engaging farmers\r\n\r\nSeveral values can be applied while engaging farmers, and these can be summarized as follows:\r\n\r\n- Honor confidentiality : Farmers providing information should be informed about the Initiative's purpose and told that all information they provide is confidential.\r\n- Build trust : Creating trust with farmers on the Initiative is a must to create ownership. This is achieved by respecting and engaging all groups of farmers' representatives in all the project phases. There are cases when farmers would need to be compensated for opportunity costs if, for some reason, the research commodity or treatment did not perform to the expected standard.\r\n- Respect views and opinions: Farmers' views and opinions are valued while engaging in research, workshops, and training. The farmers are free to modify, accept, or reject a given technology or practice.\r\n    - Value indigenous knowledge : Farmers have good reasons for making their own decisions in their livelihoods. A trade-off analysis between the traditional and improved practices proved that the opportunity costs associated with the loss in weed biomass due to the adoption of improved practices are not adequately offset by the economic gains from increased grain yield and crop residue biomass. As a result, it is recommended that researchers and development practitioners should consider indigenous knowledge and a broader systems approach and total plot productivity rather than just the partial benefits (for instance, from grain productivity gains) from specific plots of land under smallholder production systems.\r\n    - Be inclusive : The project engages all groups of farmers (men, women, youth, wealthy, influential, discriminated, poor, and landless) during diagnosis and targets most of them based on priorities.\r\n    - Build their local capacity to innovate : All participating farmers should be grouped based on the commodity as an innovation cluster/farmers research groups to strengthen their collaboration and information sharing in each research.\r\n    - Learn from the farmers : This means starting with both male and female farmers in their knowledge, awareness, attitude, beliefs, feelings, and practical habits.\r\n    - Discuss and share experiences : As a facilitator, speak less and listen more.\r\n    - Involve all groups in the community : Male, female, the youth, rich and poor .\r\n    - Facilitate, do not lecture: Create a learning environment for everybody by communicating openly and constructively based on mutual trust, respect  and confidence.\r\n    - Aim at practical orientation : Adult learning is life- or work-centered.\r\n    - Triangulate information : Use information from different sources. Use different tools to collect information. Triangulation is used for crosschecking information.\r\n    - Avoid biases : Fit your objectives into local situations. Biases, such as those for a special crop, a time (season), people, and a project, can adversely affect the effectiveness of agricultural programs.\r\n    - Learn from mistakes : Adapt and develop tools and techniques in the field.\r\n    - Uphold sustainability: Activities should be sustainable and continue after donor support has ceased.\r\n\r\n7.0 Steps for sustaining community engagement year-round\r\n\r\nStep 1: Pause for a strategic review and reset\r\n\r\nTake time for a strategic reset. Stop executing for a set period and arrange a time to meet in a distraction-free environment. Focus on debriefing and sharing your thoughts. What engagement tactics are working? What could be improved? What seems surprising? It is a good time to check in with the community and integrate the community more deeply into your organization's initiatives.\r\n\r\nStep 2: Prioritize efforts to improve your focus\r\n\r\nMost likely, during your team debriefs, everyone will have recommendations for tactics to implement. However, recognize that you have limited time and resources and must prioritize your time accordingly. One way to navigate this challenge is to build a community roadmap. See what you would like to pursue and prioritize it based on the needs and time of your team. With this approach, you will ensure that all ideas are represented, and suggestions do not fall through the cracks. What is essential right now? What is a nice-to-have? What can wait? This sense of focus will help your team make more impactful decisions.\r\n\r\nStep 3: Create a community super user program\r\n\r\nIdentify your most involved community members and create an official program with responsibilities. It might make sense right now to have many super users so that you can give them each a small chunk of the responsibility. Create a shared plan for maintaining discussions, sharing fresh content, and keeping discussions going.\r\n\r\n8.0 Conclusion\r\n\r\nAcceptance and adoption of climate-resilient crops by the farmers have to be accompanied by associated agronomic and management practices for the crops in question. Practical approaches to demonstrate the evidence are important in achieving effective and sustainable transfer of the various climate-resilient crops.\r\n\r\nA multiple-intervention approach can be an effective way to introduce management practices to a community. This approach involves using various methods to convey information and skills to community members, with the goal of promoting the adoption and sustained use of the desired management practices.\r\n\r\nThe use of real observations and experiences on how resilient crops are expected to be different from other crops that cannot survive climate change hardships are paramount practical approaches to showcase to the community members to explain best techniques for getting uptake of improved management practices associated with selected crops. The adaptive research cycle, which contains three steps (demonstration, adaptation, and adoption steps), is a good method for addressing this.\r\n\r\nThe introduction of PREA is a key component in promoting improved agricultural technologies to farmers by the Initiative. The PREA focuses on encouraging the active participation of local leaders, farmers, researchers, extension agents (EAs), and the private sector in identifying the problems of local communities and their possible solutions. It involves communities in analyzing their situation, planning, trying, monitoring, and evaluating new technologies. This will result in the widespread adoption of identified and relevant new practices and new varieties as a result of farmer-to-farmer extension. Many of Initiative's partners have already recorded successes in disseminating technologies, but we encourage them to continue using extension methods that have worked well for them in the past and possibly incorporate some of the PREA concepts. Using the diversity of dissemination approaches would make it possible to compare the efficiency and impact of the different methods.\r\n\r\nCommunity engagement is essential in setting up SMEs. By involving community members in the planning process and providing training and education, access to funding, collaboration with local institutions, and access to markets, SMEs can succeed and contribute to the community's economic development.\r\n\r\nAnnexes\r\n\r\nAnnex A: Meaning of words\r\n\r\nMandate areas: These are the target areas for the impact of the work packages of initiative interventions. Mandate areas are different in surface area between the countries.\r\n\r\nAction site: Action sites are geographical areas encompassing a community or a cluster of communities in each mandate area where the field activities related to technology identification, evaluation, and adaptation are implemented in partnership with development agencies.\r\n\r\nSatellite sites: Satellite sites are similar in terms of geographical area, population, and other general characteristics to action sites but more numerous, and the total number depends on the overall objectives and targets of a specific work package. These sites are used to disseminate best-bet options, developed at the Action Sites under the leadership of development partners, while activities at the Action Sites are led by the project.\r\n\r\nAnnex B:  References"
+}

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+{
+  "gardian_id": "907df02b565e9b4776452910981bebde",
+  "source": "gardian_index",
+  "url": "https://hdl.handle.net/20.500.11766/5791",
+  "description": "Seed producer cooperatives involved directly in different projects with ICRISAT and IER in Mali as partners were targeted for this activity. These cooperatives were trained from 2014 to 2016 on seed production techniques, communication tools for seed marketing and internal capacity building of the organization.  Information were then collected each year to evaluate the performance of these cooperatives. Workshops and interviews were organized to discuss problems occurring during the seed production, cooperatives management, and organizational progress. Results",
+  "id": "3d473c4f29c10674ea431984cd4c60e5",
+  "title": "Documentation of performances of at least 10 seed cooperatives in Mali",
+  "language": "English",
+  "resource_type": "Report",
+  "release_year": "2017",
+  "rights": "CC-BY",
+  "dataNODE_id": "907df02b565e9b4776452910981bebde",
+  "keywords": [
+    "agriculture",
+    "agriculture |",
+    "producer cooperatives",
+    "seed production",
+    "capacity building",
+    "documentation",
+    "seed",
+    "cooperatives",
+    "mali",
+    "projects",
+    "techniques",
+    "communication",
+    "tools"
+  ],
+  "geography": {
+    "regions": [
+      "Western Africa",
+      "Sub-Saharan Africa",
+      "Africa",
+      "World"
+    ],
+    "countries": [
+      "Mali"
+    ]
+  },
+  "content": "Flagship Project: 2:  Improved Varieties and Hybrids\r\n\r\nCOA: Sorghum-WCA\r\n\r\nDocumentation of performances of at least 10 seed cooperatives in Mali\r\n\r\nAboubacar Toure 1 , Baloua Nebie 1 , Mamourou Sidibe 1 , Abdoulaye Diallo 2 , Bocar Diallo 2 , Krista Isaacs 1 , Ramadjita Tabo 1\r\n\r\n1 ICRISAT-Mali, 2 IER\r\n\r\nObjective of the activity\r\n\r\nThe objectives were to:\r\n\r\n- Evaluate the performance of seed cooperatives in seed production and commercialization\r\n\r\n- Identify specific success experiences in order to share them with other seed cooperatives\r\n\r\nMethodology\r\n\r\nSeed producer cooperatives involved directly in different projects with ICRISAT and IER in Mali as partners were targeted for this activity. These cooperatives were trained from 2014 to 2016 on seed production techniques, communication tools for seed marketing and internal capacity building of the organization.  Information were then collected each year to evaluate the performance of these cooperatives. Workshops and interviews were organized to discuss problems occurring during the seed production, cooperatives management, and organizational progress. Results\r\n\r\nFrom 2015 to 2016, seed sales have increased on average by 77% for the 11 seed cooperatives in the study (Figure1). Nine out the eleven seed cooperatives showed higher quantity of seed sold in 2016 compared to that of 2015. A key result of this activity is the networking of these cooperatives in supplying emergency seeds to various projects involved in food s security For the ULPC (Union Locale des Producteurs de Semences) at Dioila, the cooperative has institutionalized new rules for profit sharing, decision making and information sharing. This internal rules have increased farmers trust in the seed business. Another key element of this success was the commitment of ULPC to produce and sell locally quality seed to farmers. As consequence the Union received a grant to build 4 seed stores close to the farmers. COOPROSEM realized a significant economic progress in 2016 with 2,000 $US of net profit compared to 2015. The cooperative was able to pay all its seed producers members on time. Some seed producers gained more than 1,600$US.\r\n\r\nBar chart\r\n\r\n|               |   2015 |   2016 |\r\n|---------------|--------|--------|\r\n| Jiguiya       |    753 |   3219 |\r\n| Seneyiriwaton |   2200 |   2742 |\r\n| Womukon       |   2675 |   2100 |\r\n| Jiguiseme     |   1088 |    910 |\r\n| PDRN          |   1165 |   4700 |\r\n| Jiguisemè     |    773 |    890 |\r\n| Dunkafa       |    232 |    544 |\r\n| Nupaganion    |     90 |    700 |\r\n| Union Nietaa  |   1436 |   3322 |\r\n| COOPROSEM     |   3946 |   6294 |\r\n| ULPC          |   1534 |   2742 |\r\n\r\nFig. 1. Sorghum hybrid seed sale by 11 Malian farmers’ cooperatives in 2016 and 2015\r\n\r\nNext step\r\n\r\nInformation are being collected on the current weaknesses of cooperatives. Based on the analysis of these information, specific actions have been developed to strengthen the seed cooperatives.\r\n\r\nA deeper analysis of the specific performance of cooperatives and the factors of this progress will be analyzed and documented for sharing experience to others seed cooperatives."
+}

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+---
+gardian_id: "53b58c1eb4f7cfdccd8f9cc3f0ce9962"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/163311"
+description: "The CGIAR Mixed Farming Systems Initiative seeks to improve the productivity, income, and resilience of mixed farming systems in Malawi. Studies have shown that this nexus is achievable through increased adoption and effective utilization of advanced agricultural technologies, supported by well-informed decision-making at all levels of the agricultural value chain. Achieving this vision relies on equipping stakeholders with the necessary skills and knowledge to manage these technologies and navigate the complexities of agricultural systems. To support this, a comprehensive capacity needs assessment was conducted, identifying skill and knowledge gaps across stakeholders in Malawi's mixed farming landscape. Based on these findings, this document presents a Capacity Development Roadmap that outlines tools and methods for targeted interventions. These interventions are tailored to enhance the roles and contributions of farmers, researchers, extension workers, cooperatives, financial institutions, am9ong other players of the mixed farming landscape in Malawi."
+id: "000e7c618e71674cd9ebc7c19d7ce3c1"
+title: "Capacity Development Roadmap for Strengthening Stakeholder Skills, Knowledge, and Resilience of Mixed Farming Systems in Malawi"
+language: "English"
+resource_type: "Report"
+release_year: "2024"
+rights: "CC-BY"
+dataNODE_id: "53b58c1eb4f7cfdccd8f9cc3f0ce9962"
+keywords: ["resilient agrifood systems", "climate adaptation and mitigation", "nutrition, health and food security", "poverty reduction, livelihoods and jobs", "sdg 1 - no poverty", "sdg 2 - zero hunger", "sdg 8 - decent work and economic growth", "sdg 13 - climate action", "sdg 15 - life on land", "sdg 17 - partnerships for the goals", "farming systems", "capacity development", "sustainable intensification", "stakeholder analysis", "agricultural productivity", "climate resilience"]
+geography: {"regions": ["Eastern Africa", "Sub-Saharan Africa", "Africa", "World", "Southern Africa"], "countries": ["Malawi"]}
+---
+<!-- image -->
+Mixed Farming
+Systems
+CGIAR
+## Capacity Development Roadmap for Strengthening Stakeholder Skills, Knowledge; and Resilience of Mixed Farming Systems in Malawi.
+Righteous Kachali' and Vimbayi Chimonyoz
+<!-- image -->
+Author affiliation
+Published by
+November 2024
+'International Maize and Wheat Improvement Center (Malawi) and 2International Maize and Wheat Improvement Center (Zimbabwe) Consultative Group on International Agricultural Research (CGIAR)
+The Sustainable Intensification of Mixed Earminq Systems Initiative aims to provide equitable; transformative pathways for improved livelihoods of actors in mixed farming systems through sustainable intensification within target agroecologies and socio-economic settings.
+Through action research and development partnerships; the Initiative will improve smallholder farmers' resilience to weather-induced shocks; provide a more stable income and significant benefits in welfare; and enhance social justice and inclusion for 13 million people by 2030.
+Activities will be implemented in six focus countries globally representing diverse mixed  farming systems as follows:  Ghana (cereal-root crop mixed), Ethiopia (highland mixed), Malawi: (maize mixed) , Bangladesh (rice mixed), Nepal (highland mixed), and Lao People's Democratic Republic (upland intensive mixed/ highland extensive mixed).
+2024
+<!-- image -->
+BY This publication is licensed for use under the Creative Commons Attribution 4.0 International Licence
+Unless otherwise noted, you are free to share (copy and redistribute the material in any medium or format) adapt (remix; transform; and build upon the material) for any purpose; even commercially; under the following conditions:
+ATTRIBUTION. The work must be attributed; but not in any way that suggests endorsement by the publisher or the author(s) .
+## TABLE OF CONTENTS
+| TABLE OF CONTENTS                                                                      |
+|----------------------------------------------------------------------------------------|
+| ABBREVIATIONS AND ACRONYMS _                                                           |
+| Executive Summary                                                                      |
+| Introduction                                                                           |
+| Training Needs for Enhanced Skills and Knowledge in Technical Aspects of Mixed Farming |
+| Framework for Capacity Development Implementation: Strategies and Key Consideration    |
+| Monitoring, Knowledge Flows, and Evaluation in Mixed Farming Systems.9                 |
+| Conclusion and Recommendations 10                                                      |
+| References _ 0000000                                                                   |
+## ABBREVIATIONS AND ACRONYMS
+| SI-MFS   | Sustainable Intensification of Mixed Farming Systems Initiative                                     |
+|----------|-----------------------------------------------------------------------------------------------------|
+| ABC      | Alliance of   Bioversity International and the International Center for Tropical Agriculture (CIAT) |
+| CIMMYT   | International Maize and Wheat Improvement Center                                                    |
+| DARS     | Department of Agricultural Research Services- Malawi                                                |
+| ICARDA   | International Centre for Agricultural Research in the Areas Dry                                     |
+| IITA     | International Institute of Tropical Agriculture                                                     |
+| ILRI     | International Livestock Research Institute                                                          |
+| IRRI     | International Rice Research Institute                                                               |
+| IWMI     | International Water Management Institute                                                            |
+| WP       | Work Package                                                                                        |
+| UNDP     | United Nations Development Programme                                                                |
+| STEM     | Science; Technology, Engineering; and Mathematics                                                   |
+| FGD      | Focus Group Discussion                                                                              |
+| NEEF     | National Economic Empowerment Fund                                                                  |
+| DAECC    | District Agriculture Extension Coordinating Committee                                               |
+| NGOs     | Non-Governmental Organizations                                                                      |
+| GoM      | Government of Malawi                                                                                |
+| USAID    | United States Agency for International Development                                                  |
+| CGIAR    | Consultative Group on International Agricultural Research                                           |
+| IPM      | Integrated Pest Management                                                                          |
+| DAECC    | District Agriculture Extension Coordinating Committee.                                              |
+## Capacity Development Roadmap for Strengthening Stakeholder Skills, Knowledge, and Resilience of Mixed Farming Systems in Malawi.
+## Executive Summary
+The CGIAR Mixed Farming Systems Initiative seeks to improve the productivity; income; and resilience of mixed farming systems in Malawi. Studies have shown that this nexus is achievable through increased adoption and effective utilization of advanced agricultural technologies; supported by well-informed decision-making at all levels of the agricultural value chain.
+Achieving this vision relies on equipping stakeholders with the necessary skills and knowledge to manage these technologies and navigate the complexities of agricultural  systems. To support this; a comprehensive capacity needs assessment was conducted; identifying skill and knowledge gaps across stakeholders in Malawi's mixed farming landscape: Based on these findings; this document presents a Capacity Development Roadmap that outlines tools and methods for targeted interventions These interventions are tailored to enhance the roles and contributions of farmers; researchers; extension workers; cooperatives; financial institutions; am9ong other players of the mixed farming landscape in Malawi.
+## Introduction
+This document provides the CGIAR Mixed Farming Systems Initiative with an implementation plan to support its Capacity Development Strategy. It offers a structured and coordinated approach to addressing the critical capacity gaps identified in Malawi's Mixed Farming Systems landscape. The roadmap outlines strategies to enhance stakeholder skills; knowledge; and collaboration;   facilitating the effective  implementation of resilient and productive mixed farming:
+The capacity needs and gaps were identified through a comprehensive participatory capacity needs assessment; utilizing focus group discussions; workshops; and structured interviews across the districts of Mzimba, Kasungu; Balaka; Zomba; and Mangochi. Stakeholders including farmers; cooperatives; financial institutions; extension workers; researchers; NGOs; input suppliers; value chain actors; and local officials were actively engaged in the process.
+Through participatory techniques; such as focus group discussions; the World Café approach; and structured interviews; stakeholders collaboratively identified and prioritized challenges related to technical knowledge; systems-thinking; and market access. Consequently; proposed various capacity interventions essential for effectively addressing these challenges (Kachali et al., 2024). they
+This roadmap seeks to facilitate the implementation of co-created innovations; such as crop-livestock integration; maize-legumelforage integration; and other climate-resilient   technologies in Malawi's mixed farming systems.
+The objectives of this roadmap are to:
+- Guide capacity-building efforts to address identified gaps in mixed farming practices.
+- Provide targeted training programs and support tools to enhance stakeholder competencies
+- Foster collaboration among stakeholders for continuous learning and adaptation within the MFS initiative.
+## Stakeholder Analysis and Capacity Needs
+During the stakeholder engagements in the MFS districts; stakeholders classified themselves based on their level of engagement and the type of support provide to farmers. At the core are Farmers, who are the primary beneficiaries and implementers of Mixed Farming System practices. Directly supporting farmers are Agriculture Extension Workers (Crops; Animals; &amp; Fisheries Officers) who interact closely with farmers; offering technical guidance and facilitating access to markets. they
+The Directly Engaged Stakeholders include Input Suppliers; Agriculture Researchers; Value-Adding Players; Non-Governmental Organizations (NGOs), Lending Institutions; and Nutrition &amp; Health Workers. These entities provide essential inputs; financial support; research insights; value addition; and health and nutritional services to strengthen farmers' capacity and productivity.
+Lastly; the Systemicloverarching Stakeholders encompass bodies with regulatory or broader institutional roles; such as the Ministry of Agriculture; Off-takers; Traditional Authorities; Councillors &amp; Members of Parliament, and Farmer Unions. These stakeholders shape policies and provide the framework within which Mixed Farming Systems can thrive
+The stakeholder capacity needs workshops identified several challenges within the mixed farming landscape and proposed a range of training interventions to address these. While some challenges required stakeholders to acquire skills, information; and knowledge related to the technical aspects of sustainable mixed farming, which are often technology-driven or goal-specific; others called for systems-thinking skills to build stakeholders' ability to continuously innovate and adapt to changes in the farming landscape:
+In addition to evaluating the level of engagement and type of support stakeholders provide to farmers, stakeholders in the mixed   farming landscape of Malawi were categorized based on their power to influence pathways; policies; decisions; or norms, and their interest in shaping the mixed farming systems. Different stakeholders expressed   opinions on which actors hold the most interest and power in the landscape across districts A consolidated Power-Interest Grid was developed to categorize stakeholders working within the mixed farming systems; providing insights into their potential roles in influencing or shaping the sector. Interestingly; the analysis revealed consistency across districts regarding power-Interest stakeholder categorization:
+The Power-Interest Grid classifies stakeholders in Malawi's Mixed Farming Systems Initiative based on their power to influence policies; decisions; and norms; as well as their level of interest in the outcomes of mixed farming systems.
+Stakeholders in the High Power - High Interest category include the Malawi Government/Ministry of Agriculture; Farmer Unions and Cooperatives; and Agriculture Extension Workers These groups were reported critical in shaping agricultural policy; providing support to farmers; and driving the implementation of mixed farming practices.
+In the High Power\_Low Interest category were Lending Institutions; Ward Councillors; MPs, and Traditional Authorities/Chiefs Despite their authority to settle land and farming issues and influence norms regarding farming operations; impact financing, and policy frameworks; their direct interest in the specifics of mixed farming systems remains limited. Their focus tends to be broader; often centered on financial returns or political agendas.
+The High Interest Low Power stakeholders; including Non-Governmental Organizations (NGOs), Input Suppliers; Off-takers/alue Adding Players; Agriculture Researchers; and Farmers; are deeply involved in the operational aspects of mixed farming. Despite their enthusiasm and active participation; these groups have limited power to influence national policies or large-scale decisions; but play a crucial role in the practical implementation of the systems. they
+Figure 1: Power-Interest Grid for Mixed Farming Systems Stakeholders on Malawi
+<!-- image -->
+Malawi Government/Ministry
+Farmers
+of Agriculture
+Non-Governmental
+Farmer Unions and
+High
+Organizations (NGOs)
+Cooperatives
+Interest
+Input Suppliers
+Agriculture Extension Workers
+Agriculture Researchers
+1
+Off-takersNalue Adding Players
+Lending Institutions
+Low
+Ward Councillors &amp; MPs
+Interest
+Traditional Authorities/chiefs
+Low Power
+High Power
+Power
+The results of the stakeholder analysis   provide a clear pathway for prioritizing   capacity development efforts in Malawi's Mixed Farming Systems (MFS). Given the diverse roles and varying levels of power and interest among stakeholders; a strategic approach to capacity enhancement is required to ensure that resources are allocated efficiently, and impact is maximized. It is critical to acknowledge that not all stakeholder capacities can be developed simultaneously; therefore; capacity development must be linked to the roles stakeholders play; their engagement level with farmers; and their   position within the Power - Interest Grid. Stakeholders in the High Power - High Interest category; such as the Malawi Government/Ministry of Agriculture; Farmer Unions and Cooperatives; and Agriculture Extension Workers should be prioritized in capacity development efforts. These stakeholders are decision-makers and directly influence policy and practice in the mixed farming landscape. Their ability to drive change and implement innovations effectively makes them the first candidates for capacity-building programs; particularly in areas such as systems-thinking;  decision-making frameworks; and integrated mixed farming technologies. Previous studies have shown that empowering high-power stakeholders with enhanced skills in policy advocacy, program implementation; and monitoring can lead to transformative sector-wide improvements (Kassie et al., 2015; Meijer et al., 2015) Next in line are stakeholders with High Interest but Low Power, including NGOS, Input Suppliers; Off-takers/alue Adding Players; Agriculture Researchers; and Farmers. Deeply involved in the day-to-day implementation of mixed farming practices; these groups play a critical role in operations but have limited influence over high-level policy or resource allocation. According to Leeuwis and Aarts; (2011), capacity-building efforts for these stakeholders should emphasize technical skills; such as sustainable farming practices; market linkages; and value-chain development. By enhancing their capacity to innovate and adapt to changing agricultural conditions; the operational aspects of mixed farming systems can be significantly strengthened. Research by Vanlauwe; Coe; et al., (2019) highlights how improving the technical capabilities of such actors creates strong feedback loops that contribute to continuous learning and refined practices at the grassroots level. For stakeholders in the High Power-Low Interest quadrant; such as Lending Institutions and Ward Councillors &amp; MPs; capacity development should adopt a more targeted approach. While these groups wield considerable influence over financing and policy frameworks; their direct engagement with mixed farming systems remains limited. Klapper and Lusardi, 2020) suggest that capacity-building programs for these stakeholders should aim to align their interests with mixed farming objectives; particularly by fostering   political support for agricultural innovations and developing favourable financial products for farmers. Engaging effectively with these key stakeholders could enhance financial access and create a more supportive regulatory environment for farmers.
+## Training Needs for Enhanced Skills and Knowledge in Technical Aspects of Mixed Farming
+Stakeholders identified both technical and systems-thinking   capacity needs based on the challenges and aspirations they face in mixed farming: These needs were outlined by each stakeholder group and validated by others through focus group discussions and the World Café approach. Below (Table 7) is a consolidated list of interventions demanded by stakeholders in the mixed farming landscape of Malawi; summarizing the key capacity needs of MFS stakeholders
+Extension workers expressed a strong demand for modern extension tools and technology and climate-smart farming techniques; showing the need for skills to support farmers in adapting to climate change:  They also emphasized financial management literacy; market linkages; and project monitoring and evaluation; while transportation and route planning was noted as a logistical need. Cooperatives prioritized leadership and communication and management of inputs and facilities as critical areas for strengthening their operations.  There was also significant focus on market  linkage and collective bargaining skills and skills for asset and income generation to improve financial resilience and market access.
+farming strategies and livestock management and breeding  reflecting their need for practical guidance and improved animal husbandry. They also stressed efficient use of seeds and fertilizers; market linkages and value addition; sustainable grazing and feed production; and farm mechanization: Agriculture researchers identified grant proposal   writing and funding strategies and modern data analysis tools as to supporting research sustainability. They also noted the importance of   advanced research techniques and policy advocacy and strategic planning to influence broader agricultural development. key
+Value chain actors highlighted the need for business finance management and loan application skills and certification and export   compliance procedures; along with an emphasis on understanding climate-smart and eco-friendly agricultural inputs to align with sustainability goals. NGOs focused on principles of effective extension work; knowledge of seed quality and viability, and techniques in water management and irrigation to improve their impact in the agricultural sector. Value chain development and program management strategies were also areas of need:. Lending institutions showed the highest demand for financial literacy for agriculture clients and agri-business familiarization training, highlighting the need to improve client financial management. key
+Table 1: Stakeholder Capacity Needs and Demand Levels Across Mixed Farming System Roles in Malawi
+| Stakeholder                                  | Capacity needs                                          |   Proportion of Stakeholders Expressing Demand |
+|----------------------------------------------|---------------------------------------------------------|------------------------------------------------|
+| Extension                                    | Modern extension tools and technology                   |                                             75 |
+| Workers/Ministry of                          | Climate-smart farming techniques                        |                                             72 |
+| Agriculture (Total: 33)                      | Financial management literacy                           |                                             65 |
+| (Males n=-15; Females n-18                   | Market linkages                                         |                                             65 |
+|                                              | Project Monitoring and evaluation                       |                                             61 |
+|                                              | Transportation and route planning                       |                                             45 |
+|                                              | Leadership and communication                            |                                             80 |
+| Farmer Cooperatives                          | Management of inputs and facilities                     |                                             75 |
+| (Total: 15) (Males n=6; Females              | Market linkage and collective bargaining skills         |                                             65 |
+| n-9)                                         | Skills Asset and Income Generation for                  |                                             60 |
+| n-9)                                         | Decision Tools for Selecting Mixed Farming Strategies   |                                                |
+| n-9)                                         | Livestock management and breeding                       |                                                |
+| n-9)                                         | Efficient use of seeds and fertilizers                  |                                                |
+| Farmers (Total: 89) (Males n=52;             | Market linkage strategies and value addition            |                                             65 |
+| Females n=37)                                | Sustainable grazing and feed production                 |                                             65 |
+| Females n=37)                                | Farm mechanisation                                      |                                             65 |
+| Females n=37)                                | Integrated pest management (IPM)                        |                                             60 |
+|                                              | Water conservation and irrigation                       |                                             60 |
+|                                              | Farm business management                                |                                             55 |
+|                                              | Soil health management                                  |                                             50 |
+| Agriculture                                  | Grant proposal writing and funding strategies           |                                             70 |
+| Researchers (Total: 22) (Males n-I3; Females | Advanced research techniques                            |                                             60 |
+| n-9)                                         | Policy advocacy and strategic planning                  |                                             50 |
+|                                              | Modern data analysis tools                              |                                             75 |
+| Value Chain Actors                           | Business Finance Management and Loan Application Skills |                                             50 |
+| (Total: 28)                                  | Certification and Export Compliance Procedures          |                                             55 |
+| (Males n-15; Females n=13)            | Knowledge of Agricultural Product Quality Standards and Best Practices                    |   60 |
+|---------------------------------------|-------------------------------------------------------------------------------------------|------|
+|                                       | Understanding Climate-Smart and Eco- Friendly Agricultural Inputs and their Usage_        |   65 |
+|                                       | Principles of Effective Extension Work                                                    |   65 |
+|                                       | Knowledge of Seed Quality and Viability                                                   |   65 |
+| Non-Governmental Organizations (NGOs) | Techniques in Water Management and Irrigation                                             |   60 |
+| (Total: 25)                           | Fundamentals of Value Chain Development                                                   |   60 |
+| (Males n=12; Females n-13)            | Strategies for Program Management and Collaboration                                       |   55 |
+|                                       | Community Engagement and Participatory Methods                                            |   55 |
+|                                       | Sourcing and managing financial resources                                                 |   50 |
+| Lending                               | Financial literacy for agriculture clients                                                |      |
+| Institutions (Total: 14) (Males n=-8; | Agri-Business Familiarization Training                                                    |   75 |
+| Females n=6)                          | Development of diverse and specialized Ioan products tailored for the agricultural sector |   61 |
+## Framework for Capacity Development Implementation: Strategies and Key Consideration
+Two capacity domains were identified as central to enhancing capacity within the mixed farming landscape: technical needs and systems-thinking needs. Technical needs focus on the practical skills and knowledge required to effectively use mixed farming tools and technologies; enabling stakeholders to meet specific goals within the farming system. Systemsthinking needs; in contrast involve building skills to recognize and understand the interconnections within the farming stakeholders to make decisions that account for how components such as production; marketing; and environmental sustainability interact to impact overall resilience and income stability. Systems-thinking skills are particularly valuable as they help stakeholders analyse interactions within the agricultural system and make informed decisions that support the broader farming ecosystem: key
+The capacity development framework is developed to address these needs through a holistic and user-centered approach; enabling stakeholders to build skills at a pace; in spaces; and within contexts that best support their learning: The tools and methods proposed bridge what and how stakeholders want to learn with practical ways to deliver this knowledge within their economic; technological, and social settings. Workshops; trainings; and demonstrations will be specifically tailored to not only provide these skills effectively but also to motivate ongoing practice and reinforcement; with follow-up support:.
+Table 2outlines the tailored capacity development approaches designed for each stakeholder in Malawi's mixed farming systems. For each identified need, there are development methods proposed, such as workshops; practical demonstrations; or training modules;   detailing the specific contexts these methods are best suited for. It also identifies partnerships necessary to enhance  training effectiveness. Each entry further assesses the resource implications associated with each method, including time requirements; financial costs; and infrastructure needs. This structured approach; adopted from Framework; 2008, is intended to allow for efficient planning by directly linking capacity-building actions with the operational needs and strengths of each stakeholder group. key In developing capacity enhancement programs for stakeholders in Malawi's mixed farming systems; it is essential to consider several factors that ensure targeted; impactful, and sustainable outcomes. The developmental impact of any capacity initiative should be at the forefront of planning; as it defines the tangible benefits that the program will bring to the farming systems. This impact may vary across stakeholders from improving market   linkages and agricultural resilience to fostering the adoption of climate-smart practices By setting clear expectations for developmental outcomes; programs can align their activities to address pressing needs within the agricultural sector and yield meaningful results: key Equally critical is determining the level of focus for capacity enhancement. Capacity-building activities may target individual skills; organizational efficiencies; or broader systems and institutions; each with distinct goals and implications. For instance; focusing on individual   skill-building in technical areas like livestock management or crop production equips stakeholders to implement immediate changes on the ground. Conversely; targeting broader systems such as policy advocacy within research institutions or improved financial management for cooperatives aims at creating sustained structural improvements that can positively affect the entire farming ecosystem: Choosing the appropriate focus level ensures that resources are allocated where they will have the most significant and far-reaching impact.
+Table 2: Stakeholder Capacity Development Methods; Targeted Capacities; and their Resource Implications
+| Stakeholder group   | Capacity Need                                                                                                                                          | Capacity Development Method                                                                                                                                                                                          | Useful for?                                                                                                                                                                                                                                                                                                                                                                                                                   | Helped by?                                                                                                                                                                                                                                                                                                                             | Resource Implications                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|                     | Modern extension tools and technology Climate-smart farming techniques Financial management literacy Project Monitoring and Evaluation Market linkages | Workshops & Practical Demonstrations Training on Information Access & Verification Workshops Financial Literacy Training Programs & Manuals Workshops on Monitoring Tools & Techniques Workshops & Networking Events | Building capacity to utilize and adapt modern extension tools and technologies Equipping workers with skills to access; assess; and apply emerging climate- smart technologies Strengthening financial planning and literacy for project and resource management Enhancing ability to implement; monitor; and evaluate mixed farming projects Connecting extension workers with market players and understanding value chains | Collaboration with technology providers; field experts Access to online platforms; climate data providers; and technology specialists Agricultural finance experts; NGOs providing funding support M&E specialists; software providers for data collection and analysis Market linkage experts; agribusiness specialists; cooperatives | Time for training; adequate technological infrastructure, trainers with technical skills, financial investment purchasing or hiring tools and conducting workshops Time for continuous learning; access to reliable information sources; trainers skilled in climate- smart methods; funding for access to online resources and trainers Training manuals; financial tools; time commitment for hands-on practice; costs associated with running the training sessions and providing financial tools Time for fieldwork, project management tools; skilled trainers; project documentation; funding for tools and software licenses Time for networking; skills in communication and negotiation; moderate infrastructure costs, budget for organizing events and travel expenses for |
+|   Stakeholder group | Capacity Need                                                                           | Capacity Development Method Leadership Training                                                                        | Useful for?                                                                                                                                                                 | Helped by?                                                                                                    | Resource Implications                                                                                                                                                                                               |
+|---------------------|-----------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|                     | Leadership and communication                                                            | Strengthening Workshops & Communication Skills and improving Seminars cooperative communication for better decision-   | leadership capacities making and coordination                                                                                                                               | Leadership experts; communication specialists; NGO facilitators                                               | Time workshop preparation; skilled trainers; moderate cost associated with venues, materials, and facilitators for                                                                                                  |
+|                     | Management of inputs and facilities                                                     | Workshops on Inventory Management & Best Practices in Facility Use                                                     | Improving efficiency in the management of agricultural inputs and cooperative facilities                                                                                    | Supply chain experts; facility management professionals                                                       | Time investment; skilled facilitators; moderate cost for training materials; venue; and logistical support                                                                                                          |
+|                   1 | Market linkage and collective bargaining skills Skills for Asset and Income Generation  | Networking Events & Training in Negotiation & Market Analysis Financial Literacy Training & Asset Management Workshops | Enhancing skills in market negotiation and building stronger market linkages Enabling cooperatives to effectively manage assets and generate                                | Market linkage specialists; agribusiness experts Financial experts; cooperative development trainers          | Time for networking and workshops; moderate to high cost for event organization and expert facilitation Time for training; moderate cost for skilled trainers and learning materials                                |
+|                     | Decision Tools for Selecting Mixed Farming Strategies Livestock management and breeding | Workshops on Decision - Making Tools & Scenario Analysis On-Farm Demonstrations & Breeding Training Programs           | sustainable income Equipping farmers with decision - making skills to optimize farming strategies Enhancing knowledge of livestock breeding, care; and management practices | Agricultural extension experts; farming systems analysts Veterinary specialists; livestock management experts | Moderate costs for workshops; time investment; and facilitators for scenario-based learning High cost due to on-farm demonstrations; experts; and livestock resources; requires substantial time and infrastructure |
+| Stakeholder group   | Capacity Need                                | Capacity Development Method                                            | Useful for?                                                                                                                                                                                          | Helped by?                                                  | Resource Implications                                                                  |
+|---------------------|----------------------------------------------|------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------|----------------------------------------------------------------------------------------|
+|                     | Efficient use of seeds and fertilizers       | Practical Workshops on Seed Selection & Fertilizer Application         | Teaching optimal seed and fertilizer use for increased productivity Building farmer capacity to access markets and enhance product value Promoting health to mechanized farming tools and techniques | Agricultural input specialists; seed and fertilizer experts | Moderate costs for venue; training materials; and agricultural input samples           |
+|                     | Market linkage strategies and value addition | Market Linkage Forums & Value-Addition Workshops                       |                                                                                                                                                                                                      | Agribusiness experts; value-chain specialists               | Moderate to high costs depending on scale of forums and value- addition demonstrations |
+|                     | Sustainable grazing and feed production      | Sustainable Grazing Workshops & On-Farm Feed Production Demonstrations | sustainable grazing and feed production to improve livestock                                                                                                                                         | Grazing and pasture experts; livestock nutritionists        | High costs for feed production demonstrations and grazing resource management          |
+|                     | Farm mechanization                           | Mechanization Training & Demonstrations                                | Introducing farmers                                                                                                                                                                                  | Agricultural engineering experts; mechanization trainers    | High costs due to machinery requirements and on-field demonstration logistics          |
+|                     | Integrated pest management (IPM)             | Workshops on IPM Practices & Biological Control Techniques             | Enabling farmers to control pests using sustainable and eco- friendly methods                                                                                                                        | Entomologists; IPM specialists                              | Moderate costs for workshops, materials; and biological control agents                 |
+|                     | Water conservation and irrigation            | Field Demonstrations on Water Conservation & Irrigation Techniques     | Improving water management and irrigation practices to boost crop productivity                                                                                                                       | Irrigation experts; water management specialists            | High cost due to field demonstrations and infrastructure needs for irrigation systems  |
+|                     | arm business management                      | Training on Financial Planning & Farm Management                       | Strengthening farmers' ability to manage farm operations and finances                                                                                                                                | Agribusiness consultants, financial management experts      | Moderate costs for training, skilled consultants; and financial tools                  |
+|   Stakeholder group | Capacity Need                                                                                                                                | Capacity Development Method                                                                                                                                                                                                  | Useful for?                                                                                                                                                                                                                                         | Helped by?                                                                                                                                                                                   | Resource Implications                                                                                                                                                                                                                                                                                                                       |
+|---------------------|----------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+|                     | Soil health management                                                                                                                       | Soil Health Workshops & On-Farm Soil Testing Demonstrations                                                                                                                                                                  | Enhancing understanding of soil management for sustainable farming                                                                                                                                                                                  | Soil scientists; agronomists                                                                                                                                                                 | High costs for soil testing equipment and expert facilitators for demonstrations                                                                                                                                                                                                                                                            |
+|                   1 | Grant proposal writing and funding strategies Advanced research techniques Policy advocacy and strategic planning Modern data analysis tools | Workshops on Grant Writing and Funding Acquisition Training Programs in Cutting-Edge Research Methodologies Workshops on Policy Engagement & Strategic Planning Courses on Data Analysis Software and Statistical Techniques | Equipping researchers with skills to develop competitive funding proposals Enhancing research skills to adopt new; innovative methodologies Enabling researchers to influence policy through advocacy analyse complex agricultural data effectively | Grant writing specialists; funding agencies Research methodologists; experienced researchers Policy experts; strategic planning specialists Data scientists, statisticians; software experts | Moderate costs for workshops; skilled facilitators; and proposal writing materials High costs due to specialized training programs; expert facilitators; and technology requirements Moderate costs for expert-led workshops and policy engagement materials High costs for software licenses; specialized training programs; and equipment |
+|                     | Business Finance Management and Loan Application Skillsfication and Export Compliance Procedures                                             | Financial Management Training and Loan Application Workshops Workshops on Export Compliance and Certification Standards                                                                                                      | Building skills in managing finances and applying for agricultural loans Understanding the certification processes for agricultural exports                                                                                                         | Financial experts; lending institutions Export agencies; trade experts                                                                                                                       | Moderate costs for expert facilitators; financial tools, and venue setup Moderate costs for expert-led workshops and export compliance materials                                                                                                                                                                                            |
+|   Stakeholder group | Capacity Need                                                                     | Capacity Development Method                                   | Useful for?                                                           | Helped by?                                                              | Resource Implications                                                          |
+|---------------------|-----------------------------------------------------------------------------------|---------------------------------------------------------------|-----------------------------------------------------------------------|-------------------------------------------------------------------------|--------------------------------------------------------------------------------|
+|                     | Knowledge of Agricultural Product Quality Standards and Best Practices            | Training Programs on Product Quality Standards                | Ensuring agricultural products meet local and international standards | Agricultural quality control agencies; industry standards organizations | Moderate costs for training programs and access to quality standards resources |
+|                     | Understanding Climate-Smart and Eco- Friendly Agricultural Inputs and their Usage | Seminars on Climate- Smart Agriculture and Sustainable Inputs | Promoting the adoption of eco- friendly inputs in agriculture         | Environmental scientists; agronomists                                   | Moderate costs for organizing seminars and procuring relevant materials        |
+|                   1 | Principles of Effective Extension Service Delivery                                | Workshops and Training on Extension Service Principles        | Strengthening NGO capacity to deliver high-quality agricultural       | Extension experts; agriculture institutions                             | Moderate costs for workshops; materials; and expert facilitators               |
+|                     | Knowledge of Seed Quality and Viability                                           | Workshops on Seed Quality and Management Practices            | ability to promote good seed practices among farmers                  | Seed certification agencies; agricultural researchers                   | Moderate costs for expert-led workshops and seed quality tools                 |
+|                   1 | Fundamentals of Value Chain Development                                           | Training Programs on Value Chain Analysis and Development     | Building knowledge in developing sustainable value chains for         | Value chain experts, economists                                         | Moderate costs for training and value chain analysis materials                 |
+|                     | Strategies for Program Management and Collaboration                               | Training in Program Management and Collaborative Approaches   | with the tools to manage agricultural programs effectively            | Program management specialists; collaboration facilitators              | Moderate costs for training and collaboration tools                            |
+|   Stakeholder group | Capacity Need                                                                        | Capacity Development Method                                                                                                                                                     | Useful for?                                                                                                       | Helped by?                                                                                                                     | Resource Implications                                                                                                          |
+|---------------------|--------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|
+|                     | Community Engagement and Participatory Methods Organization                          | Workshops Participatory Approaches and Stakeholder Engagement Financial Management on                                                                                           | Improving NGOs' skills in engaging communities in decision-making processes Ensuring financial accountability and | Community development experts                                                                                                  | Moderate costs for organizing participatory workshops and sessions Moderate costs for financial                                |
+|                     | Financing and Integrity with Donor Funds                                             | and Donor Compliance Training                                                                                                                                                   | effective use of donor funds                                                                                      | Donor agencies; financial management experts                                                                                   | workshops and compliance materials                                                                                             |
+|                   1 | Financial literacy for agriculture clients                                           | Conduct workshops and develop practical training modules on financial literacy for agriculture: Focus on managing agriculture-based loans and understanding farming cash flows. | Enhancing the ability to manage agricultural clients and better understand their financial needs.                 | Support from financial experts in agriculture and tailored case studies for agricultural finance:                              | Moderate costrequires financial experts and well-structured learning modules. Some infrastructure (training spaces) needed.    |
+|                   1 | Agri-Business Familiarization Training                                               | Structured seminars and on-the-job training to familiarize with the unique aspects of agri - business; such as risk management and market fluctuations.                         | Building competency in handling agriculture businesses and understanding sector-specific challenges and           | Trainers with experience in agri - business sectors and real-life case studies for practical application:                      | Moderate cost_needs expert trainers and access to agri - business resources.                                                   |
+|                   1 | Development of diverse and specialized loan products tailored for agriculture sector | Technical workshops and collaborative meetings to co-create specialized loan products. Design innovative loan models considering crop cycles; climate risks, and seasonality.   | development of loan products that respond to the needs of diverse agriculture sectors and conditions.             | Collaboration with agriculture sector experts; risk analysts; and financial product designers for innovation in loan products. | High cost-requires collaboration; development time; expert consultants; and infrastructure (meeting venues; online resources). |
+To achieve these developmental goals; it is essential to adopt suitable process improvement procedures that align with the specific needs and goals of the stakeholders: Tailored process improvements; like conducting hands-on workshops for farmers or establishing networking platforms for cooperatives; facilitate the effective and sustained implementation of skills and practices. Each improvement process should be carefully designed to yield desired performance outcomes;   ensuring stakeholders develop the competencies needed to drive progress within the mixed farming landscape.
+Another essential aspect is the focus on capacity domains; distinguishing between technical skills such as the practical knowledge required for specific farming practices and systems thinking skills; which equip stakeholders to adapt to complex agricultural environments. Systems thinking skills are particularly valuable; as they enable stakeholders to analyse interactions within the agricultural system and make informed decisions that support the broader farming ecosystem:
+Table 4 provides a structured overview of how capacity development interventions align with developmental impacts; capacity and performance; and process improvements across various stakeholders in Malawi's mixed farming systems adapted from Morgan; 1998). It details the specific focus level targeted by each capacity development need and identifies the capacity domain enhanced by each proposed method.
+Table 1: Summary of Stakeholder Training Needs; Focus Levels; and Capacity Building Impact in Mixed Farming Systems
+| Stakeholder Group                 | Training Needs                        | Level of Focus       | Developmental                                      | Capacity & Performance                                       | Process Improvement                               | Capacity domains               |
+|-----------------------------------|---------------------------------------|----------------------|----------------------------------------------------|--------------------------------------------------------------|---------------------------------------------------|--------------------------------|
+|                                   | Modern extension tools and technology | Individual           | Improved use of modern tools in extension services | Enhanced technological skills                                | Improved extension services                       | Technical                      |
+|                                   | Climate-smart farming techniques      | Individual           | Adoption of sustainable farming practices          | Improved ability to assess and adopt climate-smart practices | Improved adoption of new techniques               | Technical and Systems Thinking |
+| literacy                          | Financial management                  | Organizational       | Improved financial management capacity             | Stronger financial management                                | Better financial planning and resource management | Technical and Systems Thinking |
+| Project Monitoring and Evaluation |                                       | Organizational       | Enhanced project oversight and evaluation          | Better project tracking and evaluation                       | Better project evaluation systems                 | Technical and Systems Thinking |
+| Market linkages                   | Broader                               | SystemslInstitutions | Improved market linkages                           | Enhanced ability to form market linkages                     | Improved market systems                           | Technical and Systems Thinking |
+|   Stakeholder Group | Training Needs                                        | Level of Focus               | Developmental                                    | Capacity & Performance                | Process Improvement                   | Capacity domains               |
+|---------------------|-------------------------------------------------------|------------------------------|--------------------------------------------------|---------------------------------------|---------------------------------------|--------------------------------|
+|                     | Leadership and communication                          | Individual                   | Strengthened leadership in cooperatives          | Improved communication skills         | Improved decision - making processes  | Technical and Systems Thinking |
+|                   1 | Management of inputs and facilities                   | Organizational               | Improved management of inputs and facilities     | Better input and facility management  | Better facility and input utilization | Technical                      |
+|                     | Market linkage and collective bargaining skills       | Organizational               | Stronger market negotiations                     | Improved market negotiation skills    | Improved market access                | Technical and Systems Thinking |
+|                     | Skills for Asset and Income Generation                | Broader SystemslInstitutions | Increased income generation and asset management | Stronger asset management             | Better income management              | Technical and Systems Thinking |
+|                     | Decision Tools for Selecting Mixed Farming Strategies | Individual                   | Improved decision-making for farm strategies     | Better decision - making capabilities | Better decision - making tools        | Technical and Systems Thinking |
+|                     | Livestock management and breeding                     | Individual                   | Enhanced livestock health and productivity       | Improved livestock management         | Better livestock health management    | Technical                      |
+| Stakeholder Group   | Training Needs                               | Level of Focus               | Developmental                                     | Capacity & Performance                                | Process Improvement                    | Capacity domains               |
+|---------------------|----------------------------------------------|------------------------------|---------------------------------------------------|-------------------------------------------------------|----------------------------------------|--------------------------------|
+|                     | Efficient use of seeds and fertilizers       | Individual                   | Optimized seed and fertilizer use                 | Enhanced input use                                    | Improved seed and fertilizer practices | Technical                      |
+|                     | Market linkage strategies and value addition | Broader SystemslInstitutions | Improved market access and product value          | Improved market participation                         | Improved market access                 | Technical and Systems Thinking |
+|                     | Sustainable grazing and feed production      | Broader SystemslInstitutions | Sustainable livestock grazing and feed production | Better livestock management and grazing practices     | Sustainable livestock management       | Technical and Systems Thinking |
+|                     | Farm mechanization                           | Individual                   | Increased mechanization for productivity          | Improved adoption of mechanization                    | Increased use of mechanization         | Technical                      |
+|                     | Integrated pest management (IPM)             | Broader SystemslInstitutions | Sustainable pest management                       | Improved pest management                              | Improved pest control practices        | Technical                      |
+|                     | Water conservation and irrigation            | Broader SystemslInstitutions | Improved water use and irrigation efficiency      | Enhanced water conservation and irrigation techniques | Better water use                       | Technical and Systems Thinking |
+|                     | Farm business management                     | Organizational               | Improved farm business practices                  | Better farm management practices                      | Improved business management           | Technical and Systems Thinking |
+| Stakeholder Group   | Training Needs                                                         | Level of Focus               | Developmental                                          | Capacity & Performance                  | Process Improvement                      | Capacity domains               |
+|---------------------|------------------------------------------------------------------------|------------------------------|--------------------------------------------------------|-----------------------------------------|------------------------------------------|--------------------------------|
+|                     | Grant proposal writing and funding strategies                          | Individual                   | Increased funding for research                         | Stronger proposal writing skills        | Increased research funding               | Technical                      |
+| 1                   | Advanced research techniques                                           | Individual                   | Innovative research methodologies adopted              | Improved research capacity              | Adoption of advanced research techniques | Technical                      |
+|                     | Policy advocacy and strategic planning                                 | Broader SystemslInstitutions | Influence on agricultural policy and planning          | Better policy engagement                | Improved policy advocacy                 | Technical and Systems Thinking |
+|                     | Modern data analysis tools                                             | Organizational               | Enhanced data analysis capabilities                    | Improved data management skills         | Improved data analysis systems           | Technical and Systems Thinking |
+| Loan Skills         | Business Finance Management and Application                            | Individual                   | Improved access to finance for agricultural businesses | Better financial management skills      | Better access to finance                 | Technical and Systems Thinking |
+| Certification and 8 | Export Compliance Procedures                                           | Organizational               | Improved compliance with certification standards       | Improved export procedures              | Better certification processes           | Technical and Systems Thinking |
+|                     | Knowledge of Agricultural Product Quality Standards and Best Practices | Broader SystemslInstitutions | Enhanced product quality for export                    | Better understanding of product quality | Improved product quality                 | Technical and Systems Thinking |
+|   Stakeholder Group | Training Needs                                                                   | Level of Focus               | Developmental                                   | Capacity & Performance                   | Process Improvement              | Capacity domains               |
+|---------------------|----------------------------------------------------------------------------------|------------------------------|-------------------------------------------------|------------------------------------------|----------------------------------|--------------------------------|
+|                     | Understanding Climate-Smart and Eco-Friendly Agricultural Inputs and their Usage | Broader SystemslInstitutions | Adoption of climate-smart inputs                | Improved knowledge of sustainable inputs | Better use of sustainable inputs | Technical and Systems Thinking |
+|                     | Principles of Effective Extension Service Delivery                               | Organizational               | Improved delivery of extension services         | Improved extension service practices     | Improved extension services      | Technical and Systems Thinking |
+|                     | Knowledge of Seed Quality and Viability                                          | Individual                   | Improved seed quality management                | Enhanced seed quality knowledge          | Improved seed management         | Technical                      |
+|                   1 | Fundamentals of Value Chain Development                                          | Broader SystemslInstitutions | Better understanding of value chain development | Better understanding of value chains     | Better value chain development   | Technical and Systems Thinking |
+|                     | Strategies for Program Management and Collaboration                              | Broader SystemslInstitutions | Improved program management                     | Stronger program management              | Better program coordination      | Technical and Systems Thinking |
+|                     | Community Engagement and Participatory Methods                                   | Broader SystemslInstitutions | Enhanced community engagement                   | Improved participatory methods           | Better stakeholder engagement    | Technical and Systems Thinking |
+| Stakeholder Group   | Training Needs                                                                | Level of Focus               | Developmental                                     | Capacity & Performance                        | Process Improvement             | Capacity domains               |
+|---------------------|-------------------------------------------------------------------------------|------------------------------|---------------------------------------------------|-----------------------------------------------|---------------------------------|--------------------------------|
+|                     | Organization Financing and Integrity with Donor Funds                         | Individual                   | Improved financial accountability                 | Improved financial management                 | Better financial management     | Technical and Systems Thinking |
+|                     | Financial literacy for agriculture clients                                    | Organizational               | Improved financial literacy                       | Better financial literacy                     | Better financial management     | Technical and Systems Thinking |
+|                     | Agri-Business Familiarization Training                                        | Individual                   | Enhanced understanding of agribusiness challenges | Improved agribusiness knowledge               | Better agribusiness knowledge   | Technical and Systems Thinking |
+|                     | Development of diverse and specialized loan products tailored for agriculture | Broader SystemslInstitutions | Development of tailored financial products        | Enhanced ability to create financial products | Better loan product development | Technical and Systems Thinking |
+## Monitoring, Knowledge Flows, and Evaluation in Mixed Farming Systems
+Capacity development initiatives within Malawi's mixed farming systems will ultimately transition from planning to active implementation: This process demands a well-defined framework that supports the monitoring of knowledge flows; fosters   knowledge-sharing and encourages continuous learning through systematic evaluation (adopted from Adesina et al., 2014). A structured approach to monitoring and evaluating these flows is essential for adapting interventions to meet evolving stakeholder needs within the dynamic agricultural landscape:
+Knowledge flows within this framework will follow a structured path among data collection; insight; Gap Analysis &amp; Prioritization; Capacity Program Development and implementation; and validation: Data, insights; and feedback collected undergo rigorous prioritization through gap analysis. Following this;   capacity program development is conducted.
+The implementation and validation phase then evaluates outcomes to verifjy the effectiveness of  capacity-building efforts and MFS technologies This structured approach is summarized into three phases: Phase 1 (Planning and Assessment), Phase 2 (Execution and Adaptation) and Phase 3 (Evaluation and Refinement) This framework is designed to facilitate ongoing reflection and adaptation; ensuring that capacity development activities remain responsive to stakeholder needs and contribute to sustainable improvements within Malawi's mixed farming systems (see Figure 2)
+Figure 2: Knowledge Flows for Capacity Enhancement in Mixed Farming
+<!-- image -->
+Data Collection &amp;
+Analysis &amp;
+Capacity Program
+Implementation
+Insights
+Prioritization
+Development
+&amp; Validation
+Field observations
+Selfassessments
+Refreshinglupdating
+Observation
+Monitoring reports
+Monitoring reports
+Capacity development
+Monitoring progress
+Needs assessments
+Data review
+approaches for
+Performance
+Evaluations
+Prioritization workshopsl
+Adoptionlde-adoption;
+Performance
+tracking
+Stakeholder feedback
+Consensus
+building
+Advisory services; Policy
+Validation of Results
+Dialogue\_Training
+Phase 1
+Phase 2
+Phase 3
+Phase 1: Planning and Assessment; Phase 2: Execution and Adaptation; Phase 3: Evaluation and Refinement
+Gap
+## Conclusion and Recommendations
+This Capacity Development Roadmap   provides a strategic pathway to enhance stakeholder skills, knowledge; and resilience across the Malawi's agricultural   landscape. Addressing both technical and systems-thinking needs, are to empowering stakeholders with the competencies required to improve productivity, make informed decisions; and adapt to complex The framework is grounded in practical; locally tailored interventions; including hands-on training, field trials; and collaborative initiatives, all  designed to create meaningful,   long-term impacts that align with stakeholders' unique operational contexts. key
+Achieving this will require coordinated efforts; ongoing learning, and strong institutions; policymakers and other relevant stakeholders. This roadmap promotes a phased approach that addresses immediate needs while laying the foundation for sustained growth; and adaptability. This document serves as a blueprint for fostering continuous learning; collaborative problem-solving, and effective knowledge-sharing, aimed at building technical capacity and empowering stakeholders to navigate the evolving agricultural landscape
+The success of this roadmap will depend on strategic; collaborative partnerships across public;   private; and research sectors to secure the resources; expertise; and support needed to maximize its reach and impact. These alliances can harness diverse strengths to sustain and expand capacity - building efforts. Equally vital is a commitment to integrated learning; where systems-thinking approaches are embedded in technical training. This combination enables stakeholders to view mixed farming systems holistically, recognizing interconnections within the  system and making informed decisions that enhance both current resilience and long-term productivity .
+Focusing on early, high-impact interventions is also expected to further drive success. Starting with targeted interventions that address immediate needs and visibly demonstrate the value of capacity-building will build momentum and strengthen engagement among stakeholders; creating a foundation for sustained support.
+## References
+Adesina; A. A, Langyintuo; A, Bugo; N., Makinde; K, Bigirwa; G., &amp; Wakiumu; J (2014). 25OImproving farmers' access to agricultural inputs and finance: approaches and lessons from sub-Saharan Africa: In P. B. Hazell &amp; A Rahman (Eds.) New Directions for Smallholder Agriculture (p. 0). Oxford University Press.
+https:lldoiorgho.1og3lacprof:oso/9780199689347.003.0009
+- Framework. (2008) Capacity Development Methods. Www.frameworkorg.uk
+- Kassie; M. Teklewold, H. Jaleta, M. Marenya; P &amp; Erenstein; O. (2015) . Understanding the adoption of a portfolio of sustainable intensification practices in eastern and southern Africa. Land Use Policy, 42, 400-471. https:lldoiorg/o.1oI6/j.landusepol.2014.08.016
+- Klapper, &amp; Lusardi, (2020). Financial   literacy and financial resilience: Evidence from around the world. Financial Management; 49(3), 589-614. https:lldoiorgh0.1111/fima.12283
+- Leeuwis; C. &amp; Aarts, N. (2077) . Rethinking communication in innovation processes: Creating space for change in complex systems. Journal of Agricultural Education and Extension, 21-36. https:lldoiorg/0.1080/1389224X.2011.536344
+- The role of knowledge; attitudes perceptions in the uptake of agricultural and agroforestry innovations among smallholder farmers in sub-Saharan Africa. International Journal of Agricultural Sustainability, 13(1), 40-54. https:lldoiorg/0.1080/14735903.2014.912493
+- Morgan; P. (1998). CAPACITY AND CAPACITY DEVELOPMENT SOME STRATEGIES. 16(1), 1-23.
+- Capacity Needs Assessment and Needs Matrix Validation: Case Study of initiative on Mixed Farming Systems (MFS). International Maize and Wheat Improvement Center. Lilongwe; Malawi.
+- Vanlauwe B. Coe, R. C., &amp; Giller, K. E. (2019). BEYOND AVERAGES: NEW APPROACHES to UNDERSTAND HETEROGENEITY and RISK of TECHNOLOGY SUCCESS or FAILURE in SMALLHOLDER FARMING. Experimental Agriculture; 84-106. https:|ldoiorg/0.1017/50014479716000193
+<!-- image -->
+IITA
+Transforming African Agriculture
+<!-- image -->
+INITIATIVE ON
+Mixed Farming
+Systems
+CGIAR
+## cqiar orginitiativelmixed-farming-systems
+<!-- image -->
+ICARDA
+<!-- image -->
+ICIMMYT
+<!-- image -->
+ILRI
+INTERNATIONAL
+LIVESTOCK RESEARCH
+<!-- image -->
+IRRI
+International Rice
+Research Institute
+<!-- image -->
+IWMI
+International Water
+Management Institute
+<!-- image -->
+Alliance
+Bioversity &amp; CIAT
+<!-- image -->
+INTERNATIONAL CROPS RESEARCH
+INSTITUTE FOR THE SEMI-ARID TROPICS

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+---
+gardian_id: "f21a27230e320d42f5814e2750685093"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/180451"
+description: "This study is part of a two-phase research initiative conducted between 2022 and 2025 in Wakiso and Soroti districts, Uganda, examining antimicrobial use (AMU), antimicrobial resistance (AMR), and farm management practices in smallholder poultry systems. The overall study objective was to generate evidence to inform policy and support practical, on-farm interventions to reduce unnecessary antimicrobial use. The longitudinal phase presented here was initiated in response to persistent high levels of routine AMU identified during the first phase. Using a longitudinal observational design, semi-intensive broiler flocks were followed across the full production cycle to examine patterns of antimicrobial use alongside biosecurity practices and vaccine performance under real-world farm conditions.  Data were collected through repeated farm visits, structured treatment and cost records, and standardized biosecurity assessments. This enabled a detailed, production-stage specific analysis of AMU and its underlying structural drivers, generating actionable insights for antimicrobial stewardship in Uganda’s rapidly expanding poultry sector."
+id: "00a3f1a08f104cc9a1cdf519ca27cc43"
+title: "Challenges in biosecurity implementation and implications for antimicrobial use in Uganda’s poultry sector"
+language: "English"
+resource_type: "Brief"
+release_year: "2025"
+rights: "CC-BY"
+dataNODE_id: "f21a27230e320d42f5814e2750685093"
+keywords: ["systems transformation", "amr", "animal health", "capacity strengthening", "chickens", "farm management", "gender", "poultry", "environmental health and biodiversity", "poverty reduction, livelihoods and jobs", "gender equality, youth and social inclusion", "livelihoods", "antimicrobial resistance", "vaccination", "broiler"]
+geography: {"regions": ["Eastern Africa", "Sub-Saharan Africa", "Africa", "World"], "countries": ["Uganda"]}
+---
+<!-- image -->
+CGIAR
+SCIENCE FOR A FOOD-SECURE FUTURE
+## Challenges in biosecurity implementation and implications for antimicrobial use in Uganda's poultry sector
+December 2025
+Knowledge Brief
+<!-- image -->
+## Contents
+| BACKGROUND                                              | 3   |
+|---------------------------------------------------------|-----|
+| KEYMESSAGES                                             | 3   |
+| WHY ITMATTERS                                           | 3   |
+| EVIDENCE FROM QUR STUDY                                 | 3   |
+| BIOSECURITY PERFORMANCE                                 |     |
+| ANTIMICROBIAL USE PATTERNS                              | ;   |
+| VACCINATION USE AND OUTCOMES                            |     |
+| FLOCK HEALTH PERFORMANCE                                |     |
+| HOW THIS WORK SUPPORTS UGANDAS AMR NATIONAL ACTION PLAN | 6   |
+| RECOMMENDATIONS                                         | 7   |
+| SHORT TERM (FARM-LEVEL)                                 | ;   |
+| MEDIUM TERM (SERVICE DELIVERY)                          |     |
+| SYSTEM LEVEL                                            |     |
+| CROSS-CUTTING GENDER AND LIVELIHOOD OUTCOMES            |     |
+| RESOURCES                                               | 7   |
+Authors: Dreck Ayebare1 and Arshnee Moodley1,2
+'International Livestock Research Institute
+2Department of Veterinary and Animal Sciences; University of Copenhagen; Denmark
+Suggested citation: Ayebare; D. and Moodley; A. 2025. Challenges in biosecurity implementation and implications for antimicrobial use in Uganda's poultry sector. Nairobi, Kenya: International Livestock Research Institute (ILRI).
+Cover photo: Pamela N. Wairagalal ILRI
+Copyright: 2025. ILRI. This publication is licensed for use under a Creative Commons Attribution 4.0
+Disclaimers: This publication has been prepared as an output of the CGIAR Sustainable Animal and Aquatic Foods (SAAF) Science Program. views and opinions expressed in this publication are those of the author(s) and are not necessarily representative of or endorsed by the CGIAR System Organization. Any7
+Acknowledgements: This work was conducted as part of the CGIAR Sustainable Animal and Aquatic Foods (SAAF) Science Program. CGIAR research is supported by contributions to the CGIAR Trust Fund. CGIAR is a global research partnership for a food-secure future dedicated to transforming food; land; and water systems in a climate crisis\_
+## Background
+This study is part of a two-phase research initiative conducted between 2022 and 2025 in Wakiso and Soroti districts; Uganda; examining antimicrobial use (AMU), antimicrobial resistance (AMR); and farm management practices in smallholder poultry systems. The overall study objective was to generate evidence to inform policy and support practical; on-farm interventions to reduce unnecessary antimicrobial use
+The longitudinal phase presented here was initiated in response to persistent high levels of routine AMU identified during the first phase. Using a longitudinal observational design; semi-intensive broiler flocks were followed across the full production cycle to examine patterns of antimicrobial use alongside biosecurity practices and vaccine performance under real-world farm conditions.
+Data were collected through repeated farm visits, structured treatment and cost records, and standardized biosecurity assessments. This enabled a detailed; production-stage specific analysis of AMU and its underlying structural drivers, generating actionable insights for antimicrobial stewardship in Uganda's rapidly expanding poultry sector.
+## messages Key
+- External biosecurity is the weakest link and the primary driver of prophylactic antibiotic use\_
+- Antibiotics are routinely administered early in the production cycle, indicating preventive rather than therapeutic use
+- Poor vaccine performance undermines farmer confidence in preventive measures, reinforcing dependence on antibiotics.
+- Targeted; low-cost biosecurity investments during brooding could deliver the largest AMU reductions .
+- Targeted; low-cost biosecurity improvements during the brooding phase could yield substantial reductions in AMU.
+- These findings identify practical entry points for implementing Uganda's AMR National Action Plan (NAP) at farm level.
+## Why it matters
+Antimicrobial resistance (AMR) is a growing public health and economic threat across low- and middle-income countries. At the same time; semi-intensive poultry production is rapidly expanding to meet rising demand for affordable animal-source foods. In these systems, disease prevention continues to rely heavily on routine antibiotic use, driven by weak biosecurity; inconsistent vaccine handling and delivery; and limited access to quality veterinary advisory services.
+Understanding how these factors interact to shape antimicrobial use is critical for designing effective; prevention - focused interventions that improve poultry health; safeguard livelihoods; and reduce AMR risks.
+## Evidence from our study
+## Biosecurity performance
+The results indicate generally poor biosecurity across the surveyed poultry farms; with an overall median biosecurity score of only 38.5%, reflecting substantial exposure to disease risks as shown in Figure 1. External biosecurity scored the lowest at 26.3%, highlighting a critical vulnerability to the introduction of pathogens through uncontrolled movement of people; animals; equipment; and vehicles onto farms; suggesting that most farms lack effective measures to prevent disease entry.
+Internal biosecurity performed relatively better at 55.6%, indicating that farmers have some practices in place to limit disease spread within the farms. However; this level remains insufficient to reliably contain infections once introduced. Together; these findings suggest that weak external biosecurity is the primary risk factor for disease incursions; while inadequate internal controls further exacerbate transmission; reinforcing reliance on preventive antimicrobial use. The extremely low external biosecurity score explains the widespread prophylactic antibiotic use observed during brooding.
+Figure 1: Biosecurity performance across surveyed farms
+<!-- image -->
+60
+40
+20
+External
+Internal
+Overall
+component
+## Antimicrobial use patterns
+The findings show widespread and routine antibiotic use across production cycles; with 84% of farms using antibiotics in cycle and 77% in cycle 2, indicating that antimicrobial use is a normalized practice rather than an exception: The consistently high usage across cycles suggests limited learning or behavioral change over time
+Antibiotic use was highest during the brooding phase (72%), declining through the growing (56%) and finishing (47%) phases as shown in Figures 2 and 3. This pattern indicates that antibiotics are predominantly used preventively rather than therapeutically; likely as a risk-management strategy during brooding; which is the most vulnerable stage of production; when chicks are highly susceptible to disease.
+The predominance of tetracyclines; macrolides; and fluoroquinolones; all critically important antimicrobial classes , raises significant public health concerns due to their relevance in human medicine and their potential to drive antimicrobial resistance
+The study further found that farmers commonly used combinations of antibiotic and vitamin products, often without the farmers' knowledge of the antibiotic content of the products. This furthered the unnecessary exposure to antibiotics .
+Figure 2: Antimicrobial use per flock by production phase
+## Antimicrobial Use per Flock Production Phase by
+<!-- image -->
+107
+Kruskal-Wallis: X? = 34.49, p = 3.2e-08
+p &lt; 0.0001
+p
+0.0007
+P = 0.058
+106
+104
+brooding
+growing
+finishing
+Production Phase
+105
+Figure 3: Treatment incidence per production phase
+<!-- image -->
+First
+Second
+hrooding
+Antibiotic class
+Aminoglycosides
+Fluoroquinolones
+growing
+Macrolides
+1
+Polyonarises
+Tetracyclines
+finishing
+25
+50
+75
+25
+50
+75
+Treatment incidence (% of total)
+cycle
+cycle
+## Vaccination use and outcomes
+Although all farms reported using at least one vaccine, overall vaccine performance was poor. Median seropositivity levels were 72.2% for both Newcastle disease (NCD) and infectious bronchitis (IB), but markedly lower for Gumboro disease (IBD) at 27.8%, indicating inadequate immune protection across flocks as shown in Figure 4
+few farms achieved antibody levels considered sufficient for effective protection; only two farms for NCD, three for IBD; and one for IB. This suggests that vaccination alone did not translate into reliable immunity. Very
+Poor vaccine performance likely undermines farmer confidence in preventive measures and reinforces reliance on routine antibiotic use as a substitute for effective disease prevention; perpetuating cycles of prophylactic antimicrobial use and increasing AMR risk.
+Figure 4: Vaccination outcomes
+<!-- image -->
+100
+75
+1
+50
+25
+NCD
+IB
+IBD
+Vaccine
+## Flock health performance
+Low mortality despite high disease reporting suggests antibiotics may be suppressing symptoms rather than eliminating infection risk.
+Clinical signs of disease, predominantly respiratory; were widely reported across farms (17 of 19 farms in cycle and 11 of 13 farms in 2), indicating substantial and persistent disease pressure within the production systems. cycle
+However; mortality rates remained relatively low (2.5% in cycle 1 and 3.9% in cycle 2), suggesting that routine antibiotic use may be suppressing clinical severity rather than preventing disease occurrence.
+## How this work supports Uganda's AMR National Action Plan
+This study is among the first longitudinal investigations in Uganda to concurrently assess farm-level biosecurity; vaccine seroconversion; and real-time antimicrobial use across multiple poultry production cycles; providing direct; actionable evidence to support implementation of Uganda's AMR National Action Plan.
+From a surveillance perspective, the findings identify the brooding phase as the highest-risk period for antimicrobial use. From a stewardship lens, the widespread presence of antibiotics in commonly used vitamin premixes exposes farmers to unintentional antimicrobial use; underscoring the need to strengthen AMU literacy and regulate agro-veterinary inputs.
+From a prevention standpoint; consistently poor vaccine-induced antibody responses point to systemic weaknesses in vaccine delivery; cold-chain management; and field administration; thereby corroborating the AMR NAP principle that infection prevention is fundamental to reducing antimicrobial use\_
+Finally; from a governance perspective; the results highlight critical gaps in vaccine cold-chain systems, regulatory oversight of veterinary inputs; and the urgent need to scale behavior change interventions targeting veterinarians; agro-vet retailers, and farmers.
+## Recommendations
+## Short term (farm-level)
+- Introduce low-cost external biosecurity packages tailored for brooding units to reduce early-cycle disease risk.
+- Introduce practical; farmer-friendly antimicrobial use (AMU) decision-support tools to guide appropriate treatment choices.
+## Medium term (service delivery)
+- Establish cold-chain certification systems for poultry vaccines to improve handling; storage; and field efficacy:
+- Implement standardized training and accreditation for vaccinators and para-veterinarians to strengthen preventive service quality:
+## System level
+- Set district-level AMU reduction targets aligned with national antimicrobial resistance (AMR) strategies and monitoring frameworks.
+- Introduce regulatory controls on antibiotic-vitamin premixes to curb unintended antimicrobial exposure and misuse.
+## Cross-cutting gender and livelihood outcomes
+Given the strong participation of women in semi-intensive poultry value chains; strengthening preventive health systems has the potential to generate significant gender and livelihood co-benefits; enhancing productivity while empowering women as key drivers of sustainable poultry production.
+## Resources
+Ayebare; D. Muloi, D.M , Ibayi, EL Nielsen; S.S., Ndoboli, D Roesel K Tenhagen; B.A. and Moodley; A. 2025. Biosecurity measures and effects on health performance and antibiotic use in semi-intensive broiler farms in Uganda. One Health 20:101039.
+Ayebare; D., Mbatidde; I., Muloi, D.M , Ndoboli; D.\_ Roesel, K, Tenhagen; B.A. and Moodley; A. 2025.
+Quantification of antimicrobial use and economic burden in semi-intensive broiler farms in Uganda. Under review.
+<!-- image -->
+## Contact: animal\_aquatic@cgiar org
+CGIAR is a global research partnership for a food-secure future. CGIAR science is dedicated to transforming food, land, and water systems in a climate crisis. Its research is carried out by 13 CGIAR CenterslAlliances in close collaboration with hundreds of partners, including national and regional research institutes, civil society organizations , academia, development organizations and the private sector: www.cgiar org
+We would like to thank all funders who support this research through their contributions to the CGIAR Trust Fund: WWWcgiar orglfunders
+To learn more about the Sustainable Animal and Aquatic Foods Program, please visit this webpage:
+To learn more about this and other Science Programs and Accelerators in the CGIAR Research Portfolio 2025-2030, please visit www cgiar orglcgiar-research-porfolio-2025-2030/
+Copyright: 2025. International Livestock Research Institute. This publication is licensed for use under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view this license; visit https: Ilcreativecommons orqllicenseslbyl4 0
+<!-- image -->
+<!-- image -->
+CGIAR
+SUSTAINABLE ANIMAL AND AQUATIC FOODS
+SCIENCE FOR A FOOD-SECURE FUTURE

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+---
+gardian_id: "0f99848c5d087bf0260af761b2935cf6"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/176172"
+description: "This policy brief presents a comprehensive assessment of Vietnam’s national food environment policy landscape, using the INFORMAS Food-EPI framework. As Vietnam’s food environments undergo rapid transformation, the brief highlights persistent regulatory gaps in key domains such as food marketing, nutritional labeling, procurement standards, and fiscal policy. While food safety regulations have advanced, policies to improve the nutritional quality, affordability, and accessibility of healthy foods remain underdeveloped. The brief calls for stronger, more coherent policy action that goes beyond consumer education to address structural drivers of unhealthy diets. It outlines five priority areas for reform: strengthening nutrition standards for processed foods; rebalancing modern retail expansion with support for informal and traditional food outlets; tightening regulations on food marketing and labeling; introducing fiscal measures to make healthy diets more affordable; and evaluating and improving the implementation of current nutrition-related policies. The findings aim to support policymakers and stakeholders working to create healthier, more equitable food systems in Vietnam."
+id: "00aa38a2443c231d6e7a644a335568f4"
+title: "Vietnam food environment: Unpacking the national policy landscape"
+language: "English"
+resource_type: "Brief"
+release_year: "2025"
+rights: "CC-BY"
+dataNODE_id: "0f99848c5d087bf0260af761b2935cf6"
+keywords: ["resilient agrifood systems", "systems transformation", "food systems", "governance", "health", "markets", "policy", "gender equality, youth and social inclusion", "nutrition, health and food security", "sdg 1 - no poverty", "sdg 2 - zero hunger", "sdg 3 - good health and well-being", "sdg 8 - decent work and economic growth", "sdg 10 - reduce inequalities", "sdg 11 - sustainable cities and communities", "sdg 12 - responsible production and consumption", "nutrition", "diet", "sustainability", "policy briefs", "food environment", "policy analysis"]
+geography: {"regions": ["South-eastern Asia", "Asia", "World"], "countries": ["Viet Nam"]}
+---
+<!-- image -->
+Alliance
+Bioversity &amp; CIAT
+<!-- image -->
+ISPAE
+<!-- image -->
+CGIAR
+BETTER DIETS
+AND NUTRITION
+<!-- image -->
+TAR
+STAR
+STAR
+TAR
+STAP
+ice
+good
+mood
+## Vietnam Food Environment
+Unpacking the national policy landscape
+oosr
+JIter
+The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) delivers research-based solutions that address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation:
+The Alliance focuses on the nexus of agriculture, nutrition, and environment. Latin America and the Caribbean, and with the public and private sectors and civil society. With novel partnerships, the Alliance generates evidence and mainstreams innovations to transform food systems and landscapes so that sustain the planet, drive prosperity, and nourish people in a climate crisis. they
+The Alliance is part of CGIAR, a global research partnership for a food-secure future dedicated to transforming food, Iand, and water systems in a climate crisis.
+WWWalliancebioversityciat org WWW cgiar org
+## Suggested citation:
+Even Brice, Trang Thi Thu Truong, Duong Thu Nguyen, Huong Thi Mai Pham, Hang Thi Minh Thai, Anh Thi Viet Bui, and Christophe Béné. 2025. Vietnam Food Environment: Unpacking the national policy landscape. Policy Brief. International Center for Tropical Agriculture (CIAT), Hanoi, Vietnam. 15 pages.
+## Acknowledgements:
+Nutrition (BDN) Science Program of CGIAR. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Eund. The funders had no role in the design of the study; in the collection; analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results . and
+We express our gratitude to Dr. Dao The Anh, Vice-President of the Vietnamese Academy of Agricultural Sciences (VAAS), Dr. Truong Tuyet Mai, Vice-Director of the National Institute of Nutrition (NIN) , and Dr. Tran Cong Thang, Director General of the Institute of Strategy and Policy on Agriculture and Environment (ISPAE), for their valuable contributions to the review of our findings. Our sincere appreciation also goes out to the members of the panel of experts who played a decisive role in the analysis and validation process. Special thanks to Carolina Polo from the Alliance of Bioversity and CIAT for her efforts in formatting this brief.
+Cover photo: Ha Dao/CIAT.
+CIAT 2025. Some rights reserved.
+This work is licensed under a Creative Commons Attribution 4.0 International License (CC-BY 4.0)-
+August 2025
+## Introduction
+Food environments refer to the physical, economic; political, and socio-cultural settings that influence how people access, prepare, and consume food [1].
+Food environments are central to shaping diets, health outcomes, and broader sustainability goals. In Vietnam, as in many other countries, food environments are changing fast, driven by urbanization, rising incomes, evolving lifestyles, marketing dynamics, digital platforms, and global food system shifts [2, 3].
+The aim of this policy brief is to enhance understanding about food environments and to investigate how policies in Vietnam can be improved to contribute to the transition towards healthier and more sustainable food systems in Vietnam.
+Food environments influence what people eat The food environment is the interface between food systems and people's diets. It refers to the settings in which food is accessed, as well as the characteristics of that food\_how it is priced, marketed, distributed, and consumed [4, 5]. Core dimensions of food environments include:
+<!-- image -->
+Children contemplating shelves filled with ultra-processed snacks in a Hanoi supermarket.
+Photo: Ha Dao/CIAT.
+- Food availability: what is physically present and reachable.
+- Food prices: how much it costs in relation to people's resources.
+- Food products properties: including nutritional quality safety; and level of processing.
+- Food outlets properties: including type, location, and vendor practices.
+- Food messaging: including marketing, advertising, and labelling.
+These dimensions are shaped by policy choices, market dynamics, and underlying food system structures; and they can be transformed through specific, targeted interventions.
+Individuals experience food environments through personal filters (e.g., income, knowledge, cultural values, or mobility constraints, etc.) which condition how they perceive, prioritize, and access different food options.
+To be effective, food policies must address both the structural features of food environments and the individual-level factors that mediate consumer behavior; ensuring that healthier options are accessible, affordable, and desirable for all [6].
+## What are food environments?
+Food environment framework. Source: adapted from Turner et al. (2018) and UNSCN (2019).
+<!-- image -->
+AND
+FOOD
+ENVIRONMENT
+Food
+Food prices
+INDIVIDUAL
+availability
+Cost of food
+FILTERS
+of food
+Economic
+CONSUMER
+Cognitive
+filters
+BEHAVIORS
+filters
+Purchasing
+AND DIETS
+Knowledge,
+power
+Food acquisltion;
+preferences
+values
+preparation;
+eating habits
+Food
+Food
+products
+messaging
+properties
+Situational filters
+Advertising,
+Physical (spatial and temporal)
+Nutritional quality,
+labeling; and
+access to food
+safety; and level
+packaging
+of processing
+Food outlets
+properties
+Type and features
+of food vendors
+FOOD SYSTEM
+REGULATIONS
+POLICY
+DRIVERS
+Transforming food systems requires policies that reshape food environments
+<!-- image -->
+MAX
+IQ
+MAY
+Adolescents crowding in a newly-open convenience store in Hanoi.
+Photo: Ha Dao/CIAT.
+## Why focus on food environments?
+Policy responses to poor diets often overemphasize individual responsibility [7] (relying on education, awareness, or behavior change campaigns to encourage healthier choices) even though food choices are shaped by systemic conditions [8]. This focus shifts the burden to consumers, overlooks the powerful influence of food environments, and diverts accountability from industry and regulators.
+food environment lens shifts the focus from individual knowledge and choices to the broader conditions that determine what foods are accessible, affordable, and appealing, thereby enabling more systemic and equitable policy interventions. These measures are most effective when part of coherent policy packages that combine regulation; fiscal tools, and strong public leadership.
+The Food Environment Policy Index (Food-EPI), developed by INFORMAS [6], offers a structured tool to assess the extent to which existing policies promote healthy food environments, and to identify critical policy gaps and opportunities for policy action.
+## Rapidly evolving food environments: shifting supply &amp; demand
+Food environments in Vietnam are undergoing rapid transformation, as in many other LMICs. Ultra-processed foods (typically high in fat, sugar; and salt) have become increasingly available, affordable, and prominently marketed. Comparatively; nutrient-dense foods may become less accessible and more expensive, particularly for low-income populations [3].
+These shifts in food supply are closely linked to broader changes in the retail landscape. Traditional markets are losing ground to a fastgrowing network of supermarkets and convenience stores, reshaping how and where people buy food.
+Accompanying these changes is a rising public health concern: between 2010 and 2020, the national prevalence of overweight children in Vietnam more than doubled, increasing from 8.5% to 19% [9].
+<!-- image -->
+IGA
+Istrol
+OR
+GÀRÁNFKI
+Overweight and obesity rates have been increasing concurrently to the evolution of food environments
+Scenes from contemporary food environments in urban Vietnam. Photos: Ha Dao/CIAT.
+## What does policy assessment reveal in Vietnam?
+The assessment of Vietnam's food environment policies, conducted using the INFORMAS Food Environment Policy Index, reveals substantial regulatory gaps The following sections of this brief present a narrative summary of the key policy gaps identified.
+Food-EPI evaluates national policies against international best practice across key domains of the food environment, such as food labelling, marketing, and fiscal policies. In Vietnam, 35 indicators were assessed through a structured process led by independent researchers, with active participation from a transdisciplinary panel of national experts.
+A large majority of the indicators evaluated (74%) received low or very low scores, indicating limited policy action across most domains of the food environment. In contrast, only 12% of indicators were rated high, and these were largely confined to food safety regulations and public education initiatives .
+These findings suggest that while some foundational policies exist, they remain fragmented and insufficient. A more comprehensive and coherent policy framework is urgently needed to enable healthier; more equitable food environments across the country.
+<!-- image -->
+High score
+Intermediate score
+Low score
+Very low score
+35
+indicators
+score
+## Food product properties
+Vietnam has made only modest progress in improving the nutritional quality of food products. Until recently; policy efforts focused primarily on salt reduction. But these measures lacked concrete targets, enforcement mechanisms, and clear institutional oversight. No formal standards or limits exist for sugar or trans-fat content in packaged foods, leaving critical regulatory gaps.
+A notable recent development is the excise tax on sugar-sweetened beverages (SSBs) , adopted in June 2025 and scheduled to take effect in 2027. This marks an important step toward regulating unhealthy food products and aligning fiscal tools with public health goals.
+Ultra-processed foods are not regulated beyond basic food safety oversight In contrast, food safety policy has advanced more systematically. The Food Safety Law clarified mandates and introduced technical standards, but implementation remains uneven. Local inspection capacity is often constrained by shortages of trained staff, equipment, and infrastructure. Food safety training and communication are inconsistently applied; while some provinces, with international support or strong leadership, have improved outreach and inspector training, others, especially in rural areas, still face major gaps in awareness and compliance.
+<!-- image -->
+RAU VIETGAP
+Safe, certified tomatoes on display in a Hanoi supermarket.
+Photo: Ha Dao/CIAT\_
+<!-- image -->
+Shelves packed with instant noodles in a convenience store in Moc Chau.
+Photo: Ha Dao/CIAT.
+<!-- image -->
+Ultra-processed snacks in a convenience store, Hanoi.
+Photo: Ha Dao/CIAT.
+Istas
+FAMI
+## Food outlet properties
+Current policies in Vietnam make no distinction between food outlets based on the nutritional quality of what they sell. National strategies and urban land use planning generally promote the expansion of modern retail outlets (e.g. supermarkets, convenience stores) without requiring them to prioritize healthy options or limit unhealthy ones.
+Informal vendors (often a source of fresh, affordable foods for low-income households) come under growing regulatory pressure, mainly through measures designed to improve food-safety oversight. While these rules aim to protect consumers, they can also raise compliance costs for small vendors and unintentionally favour larger; with often less-nutritious food options, retail channels. key
+<!-- image -->
+MIXUE
+Franchise ice cream and milk tea shop in a peri-urban area.
+Photo: Ha Dao/CIAT.
+<!-- image -->
+Fast food chain outlet, Hanoi. Photo: Ha Dao/CIAT) .
+<!-- image -->
+Informal street vendor selling fresh vegetables in Hanoi. Photo: Ha Dao/CIAT.
+## Modern retail expansion is encouraged
+Public food procurement and provision policies also remain underdeveloped. While the Food Safety Law sets general standards, there are few specific requirements to ensure the nutritional quality of food served in public and private institutions.
+School food guidelines are in place but are mostly non-binding, leading to uneven implementation across the country. In other institutional settings (such as workplaces and hospitals) existing meal guidelines are also voluntary and rarely enforced, leaving significant gaps in the regulation of everyday food provision.
+## Food messaging
+Regulations on food marketing remain weak in Vietnam. Although national policy documents acknowledge the need to limit advertising around schools, there are no explicit restrictions on the marketing of unhealthy foods and beverages, especially those targeting children.
+Food labeling regulations require packaged products to display ingredient lists and nutritional information, but enforcement is weak due to the absence of clear monitoring and approval mechanisms. Health claims on processed foods are poorly regulated, and front-of-pack labeling remains voluntary and lacks standardized implementation guidelines, limiting consumers' ability to quickly assess product healthfulness.
+<!-- image -->
+BINGXUE
+Ice-cream shop, Hanoi. Photo: Ha Dao/CIAT.
+Current policies and public initiatives place strong emphasis on consumer education. Public awareness campaigns are used to disseminate dietary guidelines. These efforts also include nutrition training for health communicators and health workers. However; most initiatives are nonbinding and inconsistently implemented, limiting their reach and long-term impact.
+<!-- image -->
+Convenience store in Hanoi displaying processed and ultra-processed products under the "fresh food" Iabel. Photo: Ha Dao/CIAT.
+Food
+Fresh\_
+GS25
+G525
+Advertising of nutrient-poor foods; particularly to children; Iacks strong regulations
+## Food prices &amp; affordability
+Vietnam has made limited policy progress in improving the affordability of healthy foods or using fiscal tools to curb the consumption of unhealthy products. While some tax exemptions apply to minimally processed foods, there are no direct financial incentives in place to actively promote healthier dietary choices.
+Until recently; taxation of unhealthy foods had remained largely aspirational. However; in June 2025, Vietnam adopted an excise tax on sugar-sweetened beverages, set to take effect in 2027\_marking a significant step toward aligning fiscal policy with nutrition goals.
+Despite this progress, broader fiscal strategies still fall short. Subsidy programs continue to prioritize price stabilization for staple foods such as rice, salt, and sugar rather than improving access to nutrient-dense foods like fruits, vegetables, and legumes. A shift in focus is needed to realign food price policies with health and sustainability objectives .
+Fiscal policies to promote healthy diets remain underdeveloped; despite recent progress on sugary drink taxation
+<!-- image -->
+69k
+Giáchi
+129k
+Low-cost promotional signage for fast food items outside a restaurant in Hanoi. Photo: Ha Dao/CIAT.
+<!-- image -->
+KhUYEN MAI
+Mua 2 Tang
+10
+12
+one-get-one promotions for sugary drinks in a Hanoi supermarket. Aggressive discounting of nutrient-poor beverages remains widespread and unregulated Photo: Ha Dao/CIAT\_
+## Food availability and accessibility
+Healthy food access is left to the market. Policy support remains largely absent
+Vietnam currently lacks targeted policies to enhance the availability of healthy food options or to regulate access to unhealthy ones. There are no incentives for retailers to promote nutritious foods, and no mechanisms to discourage the widespread sale of ultra-processed or lownutrient products.
+Similarly; zoning laws do not address the spatial distribution of food outlets. There are no restrictions on the clustering of unhealthy vendors, nor policies to encourage the establishment of outlets offering healthier options.
+In the absence of proactive regulation; market forces continue to shape food environments, often in ways that reinforce unhealthy dietary patterns and widen disparities in food access.
+<!-- image -->
+KFC
+Here
+<!-- image -->
+Jollibee
+Gà Rán Giòn
+Ngon Tuyêt
+0
+7
+Tan,
+Fast food chains have become increasingly visible across urban Vietnam. Photos: Ha Dao/CIAT.
+<!-- image -->
+McDonalc
+## Concrete next steps
+comprehensive food environment policy package should address both structural drivers and equity concerns. priorities include: Key
+- Move beyond food safety to address nutritional quality more comprehensively. Develop and enforce standards for processed foods; including clear nutrient profiling, standardized definitions of "healthy" and "unhealthy" foods, mandatory targets for salt, sugar; and trans - fat reduction, and recognition of ultra-processed foods as a public health risk.
+- Balance the expansion of modern retail with measures that safeguard access to fresh and healthy foods. This includes supporting traditional markets and informal vendors as sources of safe, fresh, affordable food; creating incentives for retailers to offer healthy foods; implementing nutrition standards in public procurement (especially in schools and hospitals); and implementing zoning regulations to limit unhealthy outlet proliferation and reduce exposure to unhealthy foods. key
+- Strengthen regulations on food marketing and labeling. Restrict unhealthy food marketing to children, introduce mandatory front-of-pack labeling, and regulate health /nutrition claims. Complement regulatory tools with nutrition education campaigns and clearer dietary guidelines to empower consumer choices.
+- Introduce fiscal measures that support healthy diets. Build on recent progress such as the adoption of an excise tax on sugar-sweetened beverages (effective 2027) by considering its extension to ultra-processed foods. Expand subsidies or tax exemptions for nutrient-rich foods to enhance affordability and reduce health inequities.
+- Evaluate and strengthen the impact of current policies aimed at healthier diets. Build on emerging initiatives such as the upcoming subsidy for semi-boarding meals in Hanoi primary schools (2025-2026) by ensuring alignment with nutrition standards and robust implementation monitoring. Broader policy evaluation can help identify gaps, improve effectiveness, and guide future actions.
+## What principles should guide food environment regulation?
+Elevate public health over short-term economic gains.
+Address Big Food lobbying power and corporate influence through transparency &amp; accountability:
+Adopt binding regulations beyond voluntary self-governance.
+Strengthen local capacities and multisectoral collaboration.
+<!-- image -->
+&amp;
+HEALTHY
+ORGANIC
+Customers buying fresh produce from the Organic &amp; Healthy section at a supermarket in Hanoi
+Photo: Ha Dao/CIAT.
+<!-- image -->
+A roadside vendor sells vegetables at an informal market in Hanoi.
+Photo: Ha Dao/CIAT.
+## Related publications to go further
+Unpacking food environment policy landscapes for healthier diets in 'emerging' countries: the case of Viet Nam
+<!-- image -->
+Even et al., 2025
+Navigating the politics and processes of food systems transformation: guidance from a holistic framework
+<!-- image -->
+Béné and Abdulai, 2024
+Defining barriers to food systems sustainability: a novel conceptual framework
+<!-- image -->
+Even et al., 2024
+<!-- image -->
+Alliance
+Bioversity &amp; CIAT
+<!-- image -->
+ISPAE
+<!-- image -->
+CGIAR
+BETTER DIETS
+AND NUTRITION
+## Special Issue:
+Sustainable Approaches to Public Health Via Food Policy\_Actions
+## Special Issue:
+The Many Faces of Sustainable Food
+<!-- image -->
+<!-- image -->
+## Contact:
+Brice Even beven@cgiarorg Scientist, Vietnam, International Center for Tropical Agriculture

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+---
+gardian_id: "64fcb5fb989738953832ec5fb09e8123"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/182409"
+description: "From Data Islands to Data Highways: A Practitioner’s Guide to Building Agricultural Digital Public Infrastructures presents a practical methodology for designing and implementing Digital Public Infrastructure (DPI) in agricultural sectors, particularly in the Global South. Based on the experience of the coffee sector in Honduras and parallel initiatives in Kenya, Peru, Guatemala, and Costa Rica, the guide proposes a replicable approach to transform fragmented data ecosystems into shared and interoperable infrastructures governed as digital commons.\n\nThe guide is structured in four sequential phases. First, it describes the enabling conditions necessary to initiate a DPI process, including institutional alignment, minimum team capabilities, and feasibility analysis. Second, it presents a participatory methodology for transitioning from mapping the data ecosystem to building a collective mandate, combining AI-assisted analysis with multi-stakeholder consultations and workshops that enable agreements on shared objectives. Third, it explains the technological architecture of a sectoral DPI, including identity and access systems, open-source tools organized by functions, interoperable data spaces, and payment components. Fourth, it proposes a governance framework that integrates principles from commons theory with operational rules to ensure sustainability, institutional legitimacy, and long-term coordination.\n\nThe central argument is that building a DPI is primarily a governance challenge rather than a technological one. Although technical tools are increasingly mature, success depends on generating institutional trust, maintaining neutrality in facilitation, securing sustained financing, and managing collaborative processes among multiple actors. The guide emphasizes that deploying technology alone is insufficient: without shared governance agreements, efforts tend to reproduce the same data silos they aim to overcome.\n\nOverall, the document provides a practical roadmap for governments, research organizations, donors, and sectoral actors interested in developing shared digital infrastructures that improve data interoperability, facilitate regulatory compliance, and contribute to more inclusive and efficient agricultural systems."
+id: "1b70beaec340de95c21c3b9364d92eff"
+title: "From data islands to data highways: A practitioner’s guide to building agricultural digital public infrastructures"
+language: "English"
+resource_type: "Training Material"
+release_year: "2026"
+rights: "CC-BY"
+dataNODE_id: "64fcb5fb989738953832ec5fb09e8123"
+keywords: ["systems transformation", "markets", "policy", "value chains", "environmental health and biodiversity", "poverty reduction, livelihoods and jobs", "sdg 1 - no poverty", "sdg 8 - decent work and economic growth", "sdg 9 - industry, innovation and infrastructure", "sdg 12 - responsible production and consumption", "governance", "institutional development", "digital public infrastructure"]
+geography: {"regions": ["Central America", "Latin America and the Caribbean", "Americas", "World", "Eastern Africa", "Sub-Saharan Africa", "Africa", "South America"], "countries": ["Peru", "Honduras", "Guatemala", "Kenya", "Costa Rica"]}
+---
+**FROM DATA ISLANDS TO DATA HIGHWAYS**
+A Practitioner’s Guide to Building Agricultural Digital Public Infrastructures
+*Federico Ceballos-Sierra¹, Brian King¹, and Christian Hennig²*
+*¹ International Center for Tropical Agriculture (CIAT)*
+*² Permarobotics GmbH*
+## Introduction: How to Use This Guide
+This guide documents, for the first time, a complete methodology for building Digital Public Infrastructures (DPIs) for agricultural sectors in the Global South. It draws on real experience from Honduras’s coffee sector — our primary case — and from parallel work in Kenya, Peru, Guatemala, and Costa Rica. It is written for practitioners who want to understand and replicate the process, not for academics who want to theorize about it.
+The guide is the product of a collaboration between CIAT (Alliance Bioversity-CIAT) and Permarobotics GmbH, combining institutional research on commons governance with deep technical expertise in data space architecture. It reflects the accumulated lessons of building a DPI from scratch in a complex institutional environment — lessons that include failures, dead ends, and uncomfortable compromises alongside the successes.
+We wrote this guide because we believe the agricultural DPI model is replicable. The specific actors, regulations, and politics vary from country to country and commodity to commodity, but the structural pattern — data fragmentation, institutional silos, the need for shared infrastructure governed as a commons — is remarkably consistent. If you are working in an agricultural sector where multiple institutions collect overlapping data about the same farmers with no mechanism to connect those datasets, this guide is for you.
+### How to Navigate the Four Chapters
+The guide is organized in four chapters that follow the chronological sequence of building a DPI. Each chapter builds on the previous one, so we recommend reading them in order the first time through. After that, each chapter can be used independently as a reference for its specific phase of the process.
+#### Chapter 1: Enabling Conditions and Setting the Scene
+**Read this first.** Chapter 1 covers everything that must be in place before the DPI process formally begins: the definition of a DPI and its three-layer architecture, the minimum viable team (a Lead Researcher and an Associate Researcher), the entry points through which DPI conversations typically emerge from existing projects, and the scoping exercise that determines whether the conditions for a DPI process exist in your context. If you are unsure whether your sector is ready for a DPI, start here. The chapter concludes with a ten-item checklist of enabling conditions. If you cannot answer “yes” to most of them, focus on building the preconditions before proceeding.
+#### Chapter 2: From Mapping to Mandate
+**Read this when you are ready to begin.** Chapter 2 guides you through the core process that converts enabling conditions into collective commitment. It covers the AI-mediated data ecosystem mapping (an express methodology that uses AI deep research to produce a comprehensive sector mapping in hours rather than weeks), two rounds of consultation (first with piggyback partners, then semi-structured interviews with key sector actors), the one-day multi-stakeholder workshop that produces a joint statement, and the proof of concept that validates the DPI as a minimum viable product. The chapter introduces the consensus-and-dissent methodology and the commons debate — the physical deliberation exercises that structure the workshop. If you are planning a workshop, this is your operational manual.
+#### Chapter 3: The Technology
+**Read this to understand what you are building.** Chapter 3 explains the complete technology architecture of a sectoral DPI, structured around its three layers. It covers the Identity and Access Management system (including farmer ID cards with NFC and QR-encoded GeoIDs), the Open-Source Stack organized by function (spatial identity, polygon capture, deforestation risk assessment, supply chain traceability, agricultural services, and the Pancake unifying layer), the Data Space (IDSA-compliant connectors, broker, contracts, and rulebook), and the Payments component. It is the most technical chapter, but it is written for practitioners, not engineers. If you need to explain the DPI architecture to an institutional partner, a donor, or a government official, the step-by-step data exchange scenario in Section 3.4.5 is your best starting point.
+#### Chapter 4: Building the Governance
+**Read this when the joint statement is signed.** Chapter 4 provides the governance framework that ensures the DPI is not just built but sustained. It marries Elinor Ostrom’s Institutional Analysis and Development (IAD) framework with the IDSA Rulebook to produce a Governance Design Roadmap: a structured process from a founding workshop through six design sessions to a closing constitutional convention. The chapter covers the eight Ostrom design principles applied to data spaces, the three-level institutional grammar (constitutional, collective-choice, operational), the AI-facilitated “Thomas Jefferson” protocol for governance design, the legal entity question, and realistic timelines. This is the chapter that ensures long-term sustainability.
+#### Reading Paths by Role
+Not every reader needs to read every chapter with equal depth. Here are suggested reading paths based on your role:
+**If you are a program manager or donor official** evaluating whether to fund a DPI process: read Chapter 1 (especially the scoping checklist) and Chapter 4, Section 4.8 (timeline and realistic expectations). These sections will help you assess feasibility and set appropriate expectations for what can be achieved within a project cycle.
+**If you are a technical lead or CTO** responsible for deploying the DPI infrastructure: read Chapter 3 in its entirety, with particular attention to the data space architecture (Section 3.4) and the checklist (Section 3.8). Cross-reference with Chapter 4, Section 4.7 (the adapted rulebook) for governance requirements that affect technical design.
+**If you are a facilitator or researcher** leading the multi-stakeholder process: read Chapter 2 (the workshop methodology) and Chapter 4 (the governance design sessions) as your operational manuals. The consensus-and-dissent methodology (Chapter 2) and the Light Governance protocol (Chapter 4) are the tools you will use most directly.
+**If you are an institutional leader** (from a coffee institute, a cooperative, a ministry) invited to participate in a DPI process: read Chapter 1, Section 1.1 (what a DPI is and why it matters) and Chapter 2, Section 2.3 (what will happen at the workshop and what your participation involves). These sections are designed to be accessible to participants who are not DPI specialists.
+### Before You Begin: What This Process Requires
+Building a Digital Public Infrastructure is one of the most rewarding and impactful things you can do in agricultural development. It is also one of the most demanding. We have written this guide to make the process as transparent and replicable as possible, but transparency demands that we be equally clear about what it requires. The following cautionary statements are not disclaimers — they are hard-won lessons from our own experience.
+**⚠ CAUTION**
+**This process requires institutional navigation skills, not just technical skills.** A DPI is thirty percent technology and seventy percent governance. The technology components described in Chapter 3 are well-documented, open-source, and increasingly mature. The hard part is not deploying a data space connector; it is convincing an institutional director that their organization should connect to one. If your team consists entirely of engineers and data scientists, you are missing the most critical capability. You need people who can read institutional politics, translate technical concepts into the language of each partner’s priorities, and sustain multi-stakeholder relationships over years. Without these skills, the technology will be built and the governance will fail.
+**⚠ CAUTION**
+**This process requires deep knowledge of the sector and the country.** The guide provides a methodology, but the methodology must be applied with intimate knowledge of the specific agricultural value chain, its institutions, its power dynamics, its history, and its culture. A practitioner who has never worked in the coffee sector attempting to build a DPI for coffee will struggle in ways that no guide can prevent. The Associate Researcher, in particular, must have working knowledge of the country’s institutional landscape and ideally be based in or from the country. Cultural competence and local networks cannot be imported or improvised.
+**⚠ CAUTION**
+**This process requires sustained funding and institutional patience.** The mapping-to-mandate phase (Chapter 2) can be completed in six to twelve months. The technology deployment (Chapter 3) can run in parallel. But the governance process (Chapter 4) requires twelve to twenty-four at minimum to reach a signed constitutional charter. Most donor project cycles are twelve to twenty-four months. This means that building a DPI almost always requires overlapping funding streams, institutional mandates that extend beyond a single project, and donors who understand that governance cannot be rushed. If your funding horizon is twelve months with no realistic prospect of continuation, we recommend investing in the AI-mediated mapping and consultation phases (Chapter 2, Sections 2.1–2.2), which produce standalone value, rather than attempting the full process and leaving it incomplete.
+**⚠ CAUTION**
+**This process requires honest brokering and perceived neutrality.** The convening organization must not be a market competitor to any potential participant. International research centers, academic institutions, and certain international organizations can serve this role. Private companies, even well-intentioned ones, will struggle to build the trust required for multi-stakeholder governance design. If you are from a private company and want to support a DPI process, your most effective role is as a technology partner (Chapter 3), not as the convener (Chapter 2) or the governance facilitator (Chapter 4). Perceived neutrality is not a nice-to-have; it is a prerequisite for every institution in the room to speak candidly about their data, their interests, and their red lines.
+**⚠ CAUTION**
+**This process requires comfort with ambiguity and emergent outcomes.** A DPI process is not a project with a fixed scope, a Gantt chart, and predetermined deliverables. It is an emergent process where the outcome is shaped by the interactions of the participants. The joint statement that comes out of the workshop will not be the statement you would have written alone. The governance framework that emerges from Sessions 2–8 will reflect compromises that no single actor would have chosen. If you need to control outcomes, this is not the right approach. The practitioner’s role is to design the process, facilitate the interactions, and trust the community to produce governance that serves its own needs.
+**⚠ CAUTION**
+**Do not confuse deploying technology with building a DPI.** It is possible — and tempting — to deploy the Open-Source Stack (Chapter 3), register polygons, issue farmer ID cards, and call the result a DPI. It is not. A DPI without governance is a platform with public branding. The technology creates the *possibility* of shared infrastructure; the governance creates the *reality* . If you deploy the technology without building the institutional architecture described in Chapter 4, you will have created a useful set of tools that will be adopted by some, ignored by others, and governed by no one. Within two project cycles, it will fragment into the same data islands it was meant to replace.
+### What This Guide Is and What It Is Not
+**This guide is** a practitioner’s how-to manual based on real experience. It describes what we did, what worked, what did not, and what we would do differently. It provides concrete methodologies, checklists, and examples that can be adapted to other contexts.
+**This guide is not** a definitive or complete manual. It documents a process that is still underway. The Honduras Coffee Data Space has not yet completed its full governance cycle; no agricultural DPI anywhere in the world has demonstrated long-term financial sustainability without donor support. We flag knowledge gaps honestly throughout the text, and we invite practitioners in other countries and commodities to contribute their own experience to future editions.
+**This guide is not** a substitute for expertise. Reading it will give you a clear understanding of the DPI-building process, but executing that process requires the skills, knowledge, and relationships described in Chapter 1, Section 1.2. We have tried to be as transparent as possible about what those requirements are, precisely so that practitioners can make informed decisions about whether and how to proceed.
+We believe that shared digital infrastructure for agricultural sectors is not a luxury — it is a necessity. The alternative — continued fragmentation, vertical data silos, invisible farmers, redundant collection, and institutional isolation — is not sustainable. But building the alternative requires doing it right: with the right team, the right partnerships, the right governance, and the right expectations. This guide is our contribution to making that possible.
+*— Federico Ceballos-Sierra, Brian King, and Christian Hennig*
+*March 2026*

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+---
+gardian_id: "4bf9bc897505b2d7ae8f281db7014be2"
+source: "gardian_index"
+url: "https://hdl.handle.net/10568/134709"
+description: ""
+id: "3cba80ccb4934f588b679a8db9c01158"
+title: "Transforming Agrifood Systems in West and Central Africa (TAFS-WCA): guidelines for community engagement for introducing climate-resilient crop varieties, enhancing adoption of improved crop management practices, and setting up small and medium-scale enterprises"
+language: "English"
+resource_type: "Training Material"
+release_year: "2023"
+rights: "CC-BY"
+dataNODE_id: "4bf9bc897505b2d7ae8f281db7014be2"
+keywords: ["agribusiness", "capacity development", "crop systems", "food security", "impact assessment", "livelihoods", "plant production", "policies and institutions", "smallholder farmers", "nutrition, health and food security", "sdg 1 - no poverty", "sdg 2 - zero hunger", "guidelines", "manuals", "climate resilience", "community development", "decision making", "engagement", "crop management"]
+geography: {"regions": ["Western Africa", "Sub-Saharan Africa", "Africa", "World", "Middle Africa"], "countries": ["Nigeria"]}
+---
+**Transforming Agrifood Systems in West and Central Africa (TAFS-WCA)**
+**Guidelines for community engagement**
+***for***
+***introducing climate-resilient crop varieties, enhancing adoption of improved crop management practices, and setting up small and medium-scale enterprises***
+Elizabeth Babalola and Ramota Oladejo
+International Institute of Tropical Agriculture (IITA)
+November 2023
+## Acknowledgment
+We have drawn inspiration and knowledge from diverse sources and dedicated individuals to create these guidelines for community engagement in introducing climate-resilient crops, improved management practices associated with selected crops, and setting up Small and Medium Enterprises.
+We are particularly grateful to the research and development teams, organizations, and institutions involved in the write-up and publication of the following articles:
+- A scoping review of the adoption of climate-resilient crops by small-scale producers in low- and middle-income countries ( [Maricelis Acevedo](https://pubmed.ncbi.nlm.nih.gov/?term=Acevedo%20M%5BAuthor%5D) et al.)
+- The adaptive research model of CIALCA (B. Vanlauwe and P. Pypers)
+- Participatory Research Extension Approach: N2Africa Extension Method (Hakeem A. Ajeigbe and Kenton Dashiell).
+## Acronyms
+**CDC** – Center for Disease Control and Prevention
+**CSR** – Corporate Social Responsibility
+**EAs** – Extension Agents
+**GOs** – Government Organizations
+**IP** – Innovation Platform
+**M&amp;E** – Monitoring and Evaluation
+**PREA** – Participatory Research Extension Approach
+**SMEs** – Small and Medium Enterprises
+**TAFS-WCA** – Transforming Agrifood systems in West and Central Africa
+**MBILI** – Managing Beneficial Interactions for Legume Intercrops
+**NGO** – Non-Governmental Organization
+**RTBs** – Root, Tuber, and Banana
+## Contents
+Acknowledgment	1
+Acronyms	2
+**List of tables	4**
+**1.0 Introduction	5**
+**2.0 Literature review	6**
+**2.1 Evidence on the adoption of climate-resilient crops	6**
+**2.2 Evidence on the dis-adoption of climate-resilient crops	6**
+**3.0 Introducing climate-resilient crops (Crops targeted under WCA for selected countries, esp. RTBs and bio-fortified crops)	6**
+**3.1 Recommendations on guidelines to introduce climate–resilient crops	6**
+**4.0 Best techniques for getting uptake of improved management practices associated with selected crops	7**
+**4.1 Practical approaches	8**
+4.1.1   The demonstration-adaptation-adoption cycle	9
+4.1.2 Participatory research and extension approach (PREA): The process	12
+**5.0 Setting up small and medium enterprises (SMEs)	17**
+**6.0 Key and general principles, guidelines, and standards when engaging farmers.	19**
+**6.1 Key principles, guidelines, and standards when engaging farmers	19**
+**6.2 General principles, guidelines, and standards when engaging farmers	21**
+**7.0 Steps for sustaining community engagement year-round	22**
+**Step 1: Pause for a strategic review and reset	22**
+**Step 2: Prioritize efforts to improve your focus	22**
+**Step 3: Create a community super user program	22**
+**8.0 Conclusion	22**
+Annexes	24
+Annex A: Meaning of words	24
+Annex B:  References	24
+## List of tables
+Table 1: Selected characteristics of the various steps in the adaptive research cycle------------9
+Table 2: Training activities associated with the various steps in the adaptive research cycle---10
+Table 3: Changes from the use of conventional to participatory-----------------------------------12
+Table 4: Changing roles for partners in PREA----------------------------------------------------------12
+Table 5: Key principles of community engagement-----------------------------------------------20
+## 1.0 Introduction
+The Transforming Agrifood Systems in West and Central Africa (TAFS-WCA) is a transformative initiative aiming at nutritious, climate-adapted, and market-driven food systems. It will do so through developing and scaling novel and inclusive production and postharvest technologies, participatory decision-making and planning, informed governance, and the strengthening of gender and youth transformative business hubs.
+The Initiative works on RTB Crops, including yam, cassava, sweet potato, and banana; nutritious vegetables; and bio-fortified varieties of crops like yellow maize, yellow cassava, and orange-fleshed sweet potato. The uptake of the outputs produced by the innovators (scientists, breeders, and processors) is paramount in achieving the Initiative's goal. This write-up serves the purpose of guiding and helping the Initiative and its partners (implementing partners and others) to have good entry points to penetrate and access the community for better uptake of the products by the farmers and other beneficiaries. Successful engagement creates trust for mutual benefit.
+Community engagement seeks better participation from community members to achieve long-term and sustainable outcomes, processes, relationships, discourse, decision-making, or implementation. To succeed, it must encompass strategies and processes that are sensitive to the community context in which it occurs. Engaging the community can be complex. However, according to the CDC (1997), community engagement is "The process of working collaboratively with and through groups of people affiliated by geographic proximity, special interest, or similar situations to address issues affecting the well-being of those people. It is a powerful vehicle for bringing about environmental and behavioral changes that will improve the livelihood of the community and its members. It often involves partnerships and coalitions that help mobilize resources and influence systems, change relationships among partners, and serve as catalysts for changing policies, programs, and practices."
+To be effective, we need to recognize and respect the diversity and assets of the communities we engage with. Building strong relationships takes time, and it takes even longer to repair relationships that have been damaged. Approach all groups with humility and anticipate learning about the subtle nuances of each community.
+Investors should drive the community engagement process, with support from the government and civil society, where appropriate. Yet, although government agencies and civil society can provide an entry point into communities, their interests and limited capacity can sometimes compromise the process.
+## 2.0 Literature review
+### 2.1 Evidence on the adoption of climate-resilient crops
+Examining the conditions that have led to the adoption of climate-resilient crops over the past 30 years in lower- and middle-income countries, the descriptive analysis performed by [Maricelis Acevedo](https://pubmed.ncbi.nlm.nih.gov/?term=Acevedo%20M%5BAuthor%5D) 1 et al. shows that small-scale producers adopted climate-resilient crops and varieties to cope with abiotic stresses such as drought, heat, flooding, and salinity. The most prevalent trait in the dataset was drought tolerance, followed by water-use efficiency. The analysis found that the most important determinants of the adoption of climate-resilient crops were the availability and effectiveness of extension services and outreach, followed by education levels of heads of households, farmers' access to inputs—especially seeds and fertilizers—and the socio-economic status of farming families. About 53% of studies reported that social differences such as sex, age, marital status, and ethnicity affected the adoption of varieties or crops as climate change adaptation strategies.
+To cope with climate change, farmers need to modify production and farm management practices, such as adjusting planting time, supplementing irrigation (when possible), intercropping, adopting conservation agriculture, accessing short- and long-term crop and seed storage infrastructure, and changing crops or planting more climate-resilient crop varieties.
+For all countries, but especially those that rely on domestic agricultural production for food security, one of the most critical and proactive measures that can be taken to cope with food insecurity caused by unpredictable weather patterns is for farmers to adopt climate-resilient crops.
+The socio-economic status of farmers plays a large part in their adoption of climate-resilient technologies.
+### 2.2 Evidence on the dis-adoption of climate-resilient crops
+Dis-adoption of climate-resilient crops and crop varieties was discussed and included in the evidence synthesis. The major reasons for dis-adoption included technology not meeting expectations due to poor performance or quality of the technology or a variety of government policies, technical constraints, labor shortages, or financial constraints. The studies indicated that dis-adoption was specifically due to the performance of a crop variety.
+## 3.0 Introducing climate-resilient crops (Crops targeted under WCA for selected countries, esp. RTBs and bio-fortified crops)
+### 3.1 Recommendations on guidelines to introduce climate–resilient crops
+The following are recommended as guidelines to introduce climate–resilient crops.
+- There is no single profile that applies to all farmers. Therefore, extension services will need to continue to evolve to be:
+    - 1) Participatory, (2) Information and communications technology-enhanced (3) partnership-based.
+    - This partnership should include various actors, such as women's groups, universities, the private sector, and non-governmental organizations, to provide customized and appropriate information for diverse needs.
+- Access and availability of climate-resilient crop seeds must be combined with relevant and timely advisory services, such as early-warning systems for the weather.
+- Ensuring that farmers have multiple options to access seeds for a range of climate-resilient crops and varieties is essential. Empowering existing social networks, such as farmer organizations, can achieve this.
+- High-quality studies are needed on how members of households, and not just heads of households, make decisions about how to respond to climate change.
+- National policies need to support farmers' access to other assets and services, such as education, land, finance services, and diverse income-earning opportunities. Adopting climate-resilient crops and technologies will be limited without these provisions, especially education.
+- Farmers will not adopt climate-resilient crops solely based on environmental-adaptation qualities. Development and breeding programs must consider farmer and market trait preferences.
+- Mandating disaggregated data collection to identify strategies that are working and who they are working for in agricultural surveys and research will enable policymakers and donors to respond with more appropriate and informed interventions.
+## 4.0 Best techniques for getting uptake of improved management practices associated with selected crops
+A multiple-intervention approach is needed if countries want to promote the adoption of climate-resilient crops. Farmers do not adopt climate-resilient crop(s) varieties without changing other practices, such as planting dates, water-conserving technologies, etc. This approach can be an effective way to introduce management practices to a community, and it involves using various methods to convey information and skills to community members, with the goal of promoting the adoption and sustained use of the desired management practices. Some examples of interventions that could be used in this approach include:
+1. **Training sessions** : Conduct training sessions that teach community members about management practices and provide them with the necessary skills to implement them. For example, in the case of introducing climate-resilient yam to the community, all the following management practices on the yam must be demonstrated to the farmers.
+Yam is an important staple crop that is widely cultivated in tropical regions of the world. There are several agronomic practices associated with yam cultivation, including:
+- i. **Land preparation** : The land should be cleared of all vegetation and prepared by plowing, harrowing, and ridging. The ridges should be made in such a way that they can retain water.
+- ii. **Planting:** Yam is usually propagated by using seed yams, which are small pieces of yam tubers. These seed yams are planted in mounds or ridges, with a spacing of about 1 meter between mounds.
+- iii. **Fertilization:** Yam requires adequate amounts of nitrogen, phosphorus, and potassium for optimal growth. Organic manure such as poultry droppings, cow dung, or compost can be applied before planting or as a side dressing during the growing period.
+- iv. **Weed control:** Weeds can compete with yam for nutrients and reduce yield, but can be controlled through hand weeding, hoeing, or applying herbicides.
+- v. **Irrigation:** Yam requires a consistent supply of water during its growing period. If the rainfall is inadequate, irrigation may be necessary to maintain optimal growth.
+- vi. **Disease and pest control:** Yam can be attacked by various pests and diseases such as nematodes, yam beetles, and anthracnose. Farmers should use disease-resistant varieties, practice crop rotation, and apply appropriate pesticides when necessary.
+- vii. **Harvesting** : Yam is usually harvested 7-12 months after planting when the leaves start to turn yellow and dry out. Harvesting should be done carefully to avoid damage to the tubers.
+- viii. **Storage:** Yam tubers can be stored for several months under appropriate conditions, such as in a cool, dry, and dark place. This helps to reduce spoilage and maintain their quality.
+**Top of Form**
+**Bottom of Form**
+2. **Informational materials:** Develop and distribute informational materials such as brochures, posters, or videos that explain management practices and their benefits.
+3. **Peer-to-peer education** : Encourage community members who have successfully implemented management practices to share their experiences and knowledge with other community members.
+4. **Community engagement activities:** Organize events or activities that promote community engagement and participation, such as workshops or discussion groups.
+5. **Incentives:** Provide incentives to encourage community members to adopt and maintain the management practices, such as financial rewards or recognition for successful implementation.
+6. **Brainstorming and discussion sessions:** Invitate community members to participate in brainstorming and discussion sessions to build consensus on the most feasible ways to introduce improved management practices for each crop.
+By using a combination of these interventions, community members can be exposed to the management practices through multiple channels, which can increase their understanding of the practices and their motivation to implement them. This can lead to greater adoption and sustained use of the desired management practices, ultimately benefiting the whole community.
+### 4.1 Practical approaches
+The use of real observations and experiences on how resilient crops are expected to be different from other crops that cannot survive climate change hardships are paramount practical approaches to showcase to the community members to explain best techniques for getting uptake of improved management practices associated with selected crops. Then, using demonstration farms, grow some resilient crops against non–resilient ones for farmers to see as evidence of the explanations given.
+The next session below (Adaptive research cycle: The demonstration-adaptation-adoption cycle)
+provides explicit practical approaches.
+#### 4.1.1   The demonstration-adaptation-adoption cycle
+After initial problem diagnosis, the adaptive research cycle is implemented and usually consists of different, logically linked steps with feedback cycles between each step. The three steps involved are discussed below.
+**1) Demonstration step:** Demonstration trials will consist of multiple best-bet technologies derived from earlier, eventually on-station, activities or from experiences in other areas under similar agro-ecological conditions. Such technologies could include improved agronomic practices (e.g., adapted cassava spacing to enable a higher population of intercropped legumes), improved nutrient management practices (e.g., micro-doses of fertilizer in combination with locally available organic resources), or improved cropping systems (e.g., the MBILI intercropping arrangement to allow soybean-maize intercropping). All demonstrations normally integrate improved germplasm. Observations taken in demonstration trials include the agronomic and economic performance of the tested technologies (against the local practice) and gender-segregated participatory evaluation of the technologies. Demonstration trials are usually installed at the Action Site level and are relatively few, depending on the overall goals of the initiatives.
+**2) Adaptation step:** Based on the performance of the tested technologies at the demonstration sites, a few of the most promising technologies are transformed into adaptation packages, consisting of those technologies (2-3 maximally) and local practice. The packages themselves contain the needed seed, inputs, and information tools to allow the household to install the package in an area of about 10 by 10 m per treatment, with the assistance of NGO facilitators and members of the technical committees of the participating farmers' associations. The participating households also receive a field book that allows taking records of all important farm activities, observations on yields and pests/diseases, with the assistance of the technical committee member of the farmer associations, and visits to the adaptation site. Adaptation trials are many (e.g., 200 – 1000 per site per season), and their final number depends on the overall goals of the Initiative. Such trails can eventually be accompanied by soil and plant sampling on a sub-sample of sites to better understand plant-soil relationships underlying the performance of a specific technology.
+**3) Adoption step** : After participating households have tested and evaluated (a set of) specific technologies against local practice, some of these will continue using those specific (sets of) technologies. This number will vary and depend on the nature of the technology and the creation of enabling conditions for technology uptake. In this step, farmers are completely free to implement the technologies, and, in terms of observations, attempts are made to observe the impact of those technologies against an identified area where the farmer still uses local practices (Table 1). Note that the improved technology and local practice are not laid out as in a demonstration or adaptation trial; such areas are identified by pegging out specific areas within the farm managed by the household. Obviously, this can only be achieved on a sub-sample of adopting households.
+**Table 1: Selected characteristics of the various steps in the adaptive research cycle.**
+| **Step**         | **Number of treatments and plot size**                                                                                    | **Number of sites and geographical focus**                                       | **Management**                                                                                             | **Observations taken**                                                                          | **Level of understanding by farmer households**                                                                                           |
+|------------------|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------|
+| Demonstration  * | Relatively many (8-15), including a local practice; plot size varies between 25 and 100 m  2                              | Few test sites (5-10) at the Action Site level                                   | Co-managed by researchers and communities, the latter most often through collective action by associations | Agronomic performance, changes in soil fertility, economic evaluation, participatory evaluation | Good since farmers get a good idea of the performance of technology (though not all farmers are fully involved during the full crop cycle |
+| Adaptation       | Few (3-4), including a local practice; plot size varies between 64 and 100 m  2                                           | Many test sites (several hundred) at the Action and Satellite Site level         | Managed by individual farmer households with direct technical backstopping by facilitators                 | Agronomic and economic evaluation on a sub-sample, participatory evaluation                     | Very good since households apply each technology on their own farm and are fully responsible for the management                           |
+| Adoption         | No treatments, although an improved practice is usually compared to a local one; plot size is determined by the household | Unlimited for promising technologies both at the Action and Satellite Site level | Managed by individual farmer households with indirect technical backstopping by facilitators               | Agronomic and economic evaluation on a sub-sample, participatory evaluation                     | Excellent since households gather several seasons of experience with the new technology                                                   |
+* In some cases where problems persist and technological solutions are not easily identified, some trials can move to researcher-managed on-station trials to develop a better understanding of the major constraints at hand and explore potential solutions.
+##### 4.1.1.1 Training activities around the demonstration-adaptation-adoption cycle
+The adaptive research cycle is accompanied by a specific training and evaluation program involving technical research staff, NGO facilitators, technical committee members from farmer associations, and individual households. The various training activities and some details on their implementation are detailed in Table 2.
+**Table 2: Training activities associated with the various steps in the adaptive research cycle.**
+| **Step**         | **Training activity**                                                                                                                                                                    | **Number of training sessions and participants**                                                                                                 | **Facilitated by whom and number of facilitators**                                                                                     |
+|------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------|
+| Demonstration  * | Training of NGO facilitators and the technical committees of the associations hosting the demonstration sites                                                                            | Usually one training session per demonstration with the involvement of NGO staff, governmental extension staff, and farmer group representatives | National research staff (e.g., INERA); a few facilitators (2-3) are sufficient to handle the training within a limited period.         |
+| Adaptation       | Training the technical committees of the associations hosting the demonstration sites; the technical committees then train individual households for installing the adaptation packages. | One training session per association per season, including all households that have agreed to install an adaptation package.                     | NGO facilitators: at least one facilitator is needed for 10-15 farmer associations in order to complete the training in due time.      |
+| Adoption         | The technical committees of the associations backstop individual households in implementing the improved technology.                                                                     | One training session per association per season; participants include all interested community members                                           | Technical committee members of the farmer associations; at least two members per association would be needed to absorb staff turnover. |
+##### 4.1.1.2 Timing
+The timing of each of the steps depends on the level below:
+**Level of knowledge:** If one has experience in a certain area, one could drop the demonstration step and move straight into the adaptation step, especially if one has gone through the demonstration step through earlier initiatives.
+**Target crop:** Depending on the growth cycle of a crop, each step could take one (e.g., maize, legumes), two (e.g., cassava), or more (e.g., bananas) cropping seasons.
+**Target cropping system:** Depending on the type of cropping system, each step could take one (e.g., monocrops and intercropping with maize and legumes), two (e.g., maize-legume rotations, cassava-legume intercrops), or more (e.g., bean-banana intercrops) cropping seasons.
+##### 4.1.1.3 Necessary conditions for the adaptive research cycle to function
+The following issues need to be addressed to create an enabling environment to facilitate the adoption of soil management technologies:
+**Local seed systems** : Since the number of adaptation packages can be high and increasing over time, the seed component to be included in these packages needs to be addressed through community-based seed multiplication efforts or other means (e.g., agro-dealer networks).
+**Access to inputs and output markets** : Technologies including agricultural inputs (e.g., micro-doses of fertilizer) need to be necessarily accompanied by activities facilitating access to those inputs and access to output markets so farmers have access to income to purchase these inputs.
+**Farmer capacity and training** : Farmer knowledge and training are crucial for the adoption of improved soil management technologies. Literacy levels must be considered when developing training materials and organizing farmer training events.
+**Technical backstopping and facilitation** : During the initial stages, appropriate and effective facilitation and technical backstopping are crucial for its success.
+#### 4.1.2 Participatory research and extension approach (PREA): The process
+The process of PREA requires an interaction among stakeholders that is fundamentally different from conveying standard messages from the top down. This requires processes that must be carefully managed, facilitated, and stimulated with partners contributing, particularly where they have a unique role. Table 4 highlights the changing roles of partners in PREA and the
+expected contributions from the different partnership sectors.
+**Table 3. Changes from the use of conventional to participatory**
+| **Conventional approach (T&amp;V)**              | **Participatory approach (PREA)**       |
+|--------------------------------------------------|-----------------------------------------|
+| Telling farmers what to do                       | Discussing with farmers                 |
+| Making farmers change                            | Working with farmers to effect change   |
+| Extension workers and researchers  know best     | Learning from farmers                   |
+| Modern methods are better than  traditional ones | Building on local traditional knowledge |
+| Teaching                                         | Providing feedback to communities       |
+| Use of contact farmers and  demonstrations       | Promoting farmer-to-farmer extension    |
+**Table 4. Changing roles for partners in PREA**
+| **Partners**            | **Role changes**                                                                                                                               | **Unique contributions**                                                     |
+|-------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
+| Farmers                 | From passive recipients of  messages to active participants in  their own development process                                                  | Knowledge of their own  natural, financial, economic  and social environment |
+| Extension agents        | From providers of messages to  facilitators of learning processes                                                                              | Facilitation skills                                                          |
+| Researchers             | From detached scientists to  facilitators and participants in on-farm  research                                                                | Experimental design,  knowledge                                              |
+| Private sector          | From pushing inputs and buying  produce at prices unfavorable  to farmers to support farmers  in the more efficient market-related  production | Information provision  specific to the products  they buy and sell           |
+| NGOs                    | Organizing production means  to facilitate conditions conducive to  participatory development                                                  | Process management and  facilitation skills                                  |
+| Governments and  donors | From implementing projects defined  in time and space to support  long-term development processes                                              | Enabling policies  Resources                                                 |
+##### 4.1.2.1 Action planning
+This is planning by the community, which helps motivate the people and gives opportunities to male and female farmers and disadvantaged groups to express their views. The findings from the initial situation analysis are important and help outsiders to know the community, but the results are even more important for the community members. Request them  to think about possible solutions and which local institutions can play a role in resolving these problems. Collective decision-making and local ownership are essential for success.
+Because of their involvement from the beginning, the community will:
+1. Motivate people to become more involved in an action research and development process that can improve their livelihoods
+2. Allow the poorer and disadvantaged groups to express their views once household and community issues have been explored
+3. Provide feedback to the rest of the community on the issues and needs identified in the situation analysis
+4. Analyze with the community the underlying causes of the problems identified and identify possible solutions
+5. Identify possible local institutions to help take forward some of these solutions. This is best achieved in community workshops by nominated members of each group who provide reports from each of their groups. After this, it is important to:
+6. Agree on a schedule of work to be undertaken in addressing those needs;
+7. Agree on the criteria and indicators, which enable the community to see whether their work is genuinely leading to an improved situation
+##### 4.1.2.2 Local groups and lead farmers
+The main approach is to work with local groups and lead farmers selected by the community-based organizations that they represent. They should undertake the piloting and testing of new technologies. Regular feedback from the lead farmers to the groups will ensure the groups' involvement in planning and implementation and encourage further farmer-to-farmer testing and adaptation (and diffusion). The lead farmer is not a title but a role to be played by the actor with specific reference to the current activities. In certain situations, or by some other organizations, the lead farmer is called a master/volunteer/demo farmer. Whatever the nomenclature, the roles are similar. As usual, we must undertake to have female lead farmers who should be not less than 50% in number. The responsibilities of lead farmers and the groups also need to be agreed upon.
+###### 4.1.2.2a Potential role of local groups
+1. To formally adopt the program into their activities
+2. To appoint a person or persons responsible for reporting on progress and identifying issues/problems that affect the program; this is likely to be the lead farmer
+3. To encourage participation by other farmers in trying out the new techniques
+4. To invite the extension worker to attend meetings regularly
+5. To arrange field days that cover all farmers
+6. To evaluate the new methods at the end of the season and plan for the new season
+###### 4.1.2.2b Potential responsibilities of lead farmers
+1. To motivate other farmers to try out new technologies
+2. To assist with the project planning process using participatory methods
+3. To assist the extension agent (EA) in training the group and other farmers
+4. To host mid- and end-of-season evaluations of the test plots and demonstrations
+5. To ensure that information is disseminated to the community at large
+6. To hold regular meetings with other farmers and present concerns to the group and the EA
+7. To facilitate coordination between the group and the EA
+##### 4.1.2.3 Participatory monitoring and evaluation
+Experience sharing, self-evaluation, and planning for the next season: Exchange visits, field days, and crop evaluations will provide opportunities for farmers to learn and share; these
+will increase awareness among lead and secondary farmers and the adoption of new technologies. Monitoring and evaluation (M&amp;E) form an integral part of the PREA process, and the earlier it is incorporated into program activities, the better. M&amp;E allows farmers, researchers, and EAs to ensure that stages in the PREA address identified problems and concerns and the project objectives. This requires two steps that are more formal:
+1. A mid-season evaluation and monitoring of the new practices being tested
+2. An end-of-season evaluation where the whole process can be evaluated and plans made for the coming season
+##### 4.1.2.4 Share innovations and lessons
+Engagement outcomes (including the M&amp;E results) should be shared among those involved in the engagement process. This enables validation of the approach and increases motivation for further engagement and action. Often, only successes are communicated.
+However, failures should also be highlighted—within a culture of transparency and trust—to avoid future ineffective or maladaptive investments of time and resources. In addition, while the context of adaptation may be unique to particular communities of place and interest, there may be innovations and other lessons that may apply beyond one particular network, benefiting others across many networks. Sharing engagement outcomes engenders increased motivation, transparency, and trust for future engagement and action. Innovations from one network may also apply to other networks.
+##### 4.1.2.5 Capacity building for implementing PREA
+Successfully implementing PREA requires new skills, knowledge, and attitudes, not only for extension workers but also for farmers who are used to working with conventional approaches.
+PREA is a process learning cycle, which requires flexibility in its implementation. The complexities of rural situations require that capacity is developed and the institutional approach to create an environment conducive for the process to be accepted. It may require EAs to change from only being technical advisors to being process leaders and facilitators.
+Participatory development processes are not blueprints and cannot be predicted in terms of output.
+The projects need to allocate resources for training at different levels. Dissemination begins within the project through a series of training activities: Training of Trainers in best techniques for getting uptake of improved management practices associated with selected crops. These specialists will return to their respective hubs and countries and organize workshops of national cooperators, particularly the representatives of large farmers' associations and NGOs active within each country. Initiative staff will provide technical and logistic backstopping for these national cooperator workshops. Finally, each trainer will schedule a series of stakeholder workshops within the Initiative action sites where specific Initiative activities and cooperators' responsibilities are discussed, technologies demonstrated, and the use of project dissemination tools explained.
+##### 4.1.2.6 Documentation
+Record keeping and documentation are immensely important. The researchers, EAs, and the lead farmers should endeavor to document every activity, whether major or minor. The number of participants present during meetings, field days, etc., should be recorded with a note of the number of males and females present. During visits to the field, record anything abnormal or outstanding you noticed. These details are crucial in PREA as they will ultimately help in interpreting results. Records should be kept of all meetings, stating the decisions and commendations made and the follow-up activities. During field days and other meetings or when interacting with farmers, ask open-ended and probing questions to fully understand their opinions and experiences. Technicians, EAs, and lead farmers should report successes to their superiors, who should publicize them. They should be reported to other partners, farmers, neighboring communities, projects, etc., to appreciate and share experiences.
+##### 4.1.2.7 Gender dimensions of PREA
+In many cases, men and women may be better suited to or prefer to undertake different tasks. This must be considered in the dissemination exercise. PREA allows the mainstreaming of gender, providing an opportunity for encouraging gender equity through the inclusion of women as participants and promoting equal access to resources with benefits for both men and women. This does, however, require commitment from implementing partners to ensure that gender issues are given appropriate consideration.
+###### 4.1.2.7a Some considerations for mainstreaming gender.
+1. Discussion among partners on gender issues and development constraints
+2. Capacity building for partners on gender interventions
+3. Disaggregation and evaluation of project data according to gender
+4. Assessment of progress on lowering gender barriers
+5. Commitment to gender mainstreaming from policymakers and decision-takers, where applicable
+6. Policy changes towards the adoption of gender-sensitive approaches, where applicable
+Gender analysis explores the norm of male and female behaviors and experiences, and the implications of the different ways that men and women contribute to and benefit from the development processes. The introduction of any intervention needs to be negotiated and integrated by both male and female farmers for it to be sustainable. The Gender Equality Wheel is a tool that identifies four stages of the progress toward gender equality. This tool, described below, would be used in gender mainstreaming by the project.
+***• Empowerment:*** This refers to resources such as ideas, knowledge, and skills that become available to the community as a result of collaboration with the project. Such resources are the cornerstone of social capital, building self-confidence in women and men as they explore new ways of seeing and acting.
+***• Engagement:*** This refers to the stage at which people (especially women) come out of isolation, discover new possibilities for their lives, and begin to build mutual support. In Initiative Work Packages, attention will be paid to the composition of lead farmers and farmers' groups to ensure gender balance during the selection of participants.
+***• Enhancement:*** This refers to the process when women and men begin to apply new ideas, knowledge, and skills to enhance the lives of family and community members and to provide household and community gains. Training will be given to all farmers, including special training for women farmers and some women collaborators on processing to enhance income generation and improve household nutrition and health.
+***• Emergence:*** This refers to the process when women and men move onto the public stage to take social and political action that transforms their social, cultural, and political environment. Field days and mid-season evaluations would be conducted on women farmers' fields to voice their experience to fellow women farmers and the larger populace.
+##### 4.1.2.8 Building an innovation platform (IP)
+As part of the PREA and the dissemination strategy, Initiative Work Packages will work with several partners. This entails the formation of platforms at different levels for the execution of Initiative activities. As the Initiative will be disseminating climate-resilient crops and other innovations, the platform so formed is an innovation platform (IP). An IP consists of a set of stakeholders bound together by their individual interests in a shared issue, objective, challenge, or opportunity, with the potential to improve livelihoods, businesses, and other interests. An IP refers both to the emergent properties of groupings of players and their processes, practices, and habits, as well as to the formal structures that might give operational focus to activities and interactions. This platform will be at different levels of operation, with overlapping interests. At the Initiative level, it would comprise all the partners that interact to influence Initiative activities in all target countries and outside those countries. At the country level, it would be composed of those partners whose effect is limited to that country. At the action site, the platform would be made up of groups and individuals who implement or facilitate initiative
+**s to achieve set objectives there. A complete IP for the Initiative Work Packages comprises researchers, extension groups, farmers' groups, input/output marketers, NGOs, GOs, and leaders at various levels, all of whom have a vested interest in the outcome of the Initiative.**
+## 5.0 Setting up small and medium enterprises (SMEs)
+Community engagement is essential in setting up small and medium enterprises (SMEs) as it helps to create a conducive environment that enables the success of the enterprises. SMEs play a vital role in economic development, job creation, and fostering innovation. To ensure their success, it is essential to establish a strong foundation that supports SMEs and engages the local community. Community engagement serves as a catalyst for SME growth and sustainability by fostering collaboration, generating awareness, and creating a favorable business environment. Here are some ways community engagement can be fostered in setting up SMEs:
+- **Understanding the local community:** Before engaging with the community, take the time to understand its unique characteristics, demographics, culture, and economic landscape. Conduct market research and analysis to identify the needs, preferences, and challenges of the local market. This knowledge will help tailor your approach, products, and services to better meet the community's requirements.
+- **Involving community members in the planning process:** Community members should be involved in the planning process of SMEs. This can be done through meetings, focus groups, and surveys, where community members can provide feedback and ideas that can inform the planning process.
+- **Identifying and engaging with the key stakeholders and support organizations:** Identify and connect with key stakeholders in the community, including local government representatives, community leaders, business associations, educational institutions, and relevant organizations. Build relationships based on trust, open communication, and mutual benefit to foster collaboration and support for your SME. Engaging with local authorities, such as city councils and regulatory bodies, is crucial for SMEs to navigate legal requirements, obtain necessary licenses and permits, and ensure compliance with regulations. Additionally, connecting with economic development organizations, business support centers, and entrepreneurial networks in the community can provide valuable guidance, resources, and networking opportunities. These entities can assist in business planning, financing options, mentorship, and access to training programs.
+- **Accessing funding:** Access to funding is a critical factor in the success of SMEs. Community members can be engaged in setting up financing mechanisms such as community funds, crowdfunding platforms, and government grants, which can provide financial support to SMEs.
+- **Building and engaging the workforce:** Building a skilled and dedicated workforce is crucial for SMEs' long-term success. Engaging with the local community regarding recruitment, talent development, and skills training is essential. SMEs can collaborate with educational institutions, vocational training centers, and job placement agencies to identify and train potential employees. By investing in the local workforce, SMEs reduce unemployment, enhance skill levels, and foster socio-economic growth within the community. This can be done through workshops, seminars, and mentorship programs.
+- **Creating awareness and customer base:** Community engagement is a powerful tool for raising awareness about SMEs' products or services. By actively participating in community events, sponsorships, and outreach programs, SMEs can introduce themselves to a broader audience and build a loyal customer base. Moreover, engaging with local residents through social media, community newsletters, and word-of-mouth marketing can create brand recognition and attract potential customers, ultimately driving business growth.
+- **Providing access to markets:** SMEs need to access markets to sell their products and services. Community engagement can involve setting up local markets, fairs, and festivals to provide a platform for SMEs to showcase their products and services to the community.
+- **Engaging in Corporate Social Responsibility (CSR) initiatives:** Implement CSR initiatives that align with the community's values and address local social or environmental concerns. This could involve supporting local charities, participating in sustainability programs, organizing community service activities, sponsoring community projects, or participating in environmentally friendly practices. Communicate your CSR efforts transparently to the community, showcasing your commitment to making a positive impact beyond business operations. Actively participate in community events, festivals, and initiatives to establish a presence and demonstrate your commitment to the community. Sponsor or support local events, volunteer for community projects, and engage in activities that align with your business values. This involvement helps build brand visibility and connects you with potential customers and partners.
+- **Fostering innovation and collaboration:** Community engagement brings together diverse perspectives and expertise, fostering an environment that encourages innovation and collaboration among SMEs. Collaborative initiatives, such as incubators, co-working spaces, and industry-specific clusters, provide SMEs with shared resources, mentoring, and knowledge exchange opportunities. By collaborating with other entrepreneurs, SMEs can leverage complementary skills, share costs, and drive collective growth through joint ventures or partnerships.
+- **Listening and responding to community needs:** Regularly seek feedback from the community regarding your products, services, and business operations. Actively listen to their suggestions, concerns, and expectations. Use this feedback to improve your offerings and demonstrate that you value their input. Respond to customer inquiries and complaints promptly and transparently. By addressing community needs, you build trust, loyalty, and customer satisfaction.
+- **Promoting local economic development:** Contribute to the local economy by sourcing goods and services from local suppliers and service providers whenever possible. Support other local businesses by referring customers or collaborating on projects. Participate in initiatives that promote entrepreneurship, skills development, and economic growth within the community. You foster a sense of shared prosperity when you actively contribute to the local economy.
+- **Communicating effectively:** Establish regular and transparent communication channels with the community. Utilize social media, newsletters, community forums, and public meetings to share updates, seek input, and address concerns. Effective communication fosters trust, encourages community involvement, and helps build a positive brand image.
+- **Evaluating and adapting:** Regularly evaluate the impact and effectiveness of your community engagement initiatives. Measure key performance indicators such as community satisfaction, brand recognition, customer loyalty, and community partnerships. Use this feedback to refine your strategies, adapt your approach, and continuously improve your community engagement efforts.
+## 6.0 Key and general principles, guidelines, and standards when engaging farmers.
+### 6.1 Key principles, guidelines, and standards when engaging farmers
+The key principles and standards when engaging farmers are presented below (Table 5).
+Table 5: Key principles of community engagement
+<!-- image -->
+Source: [https://doh.wa.gov/sites/default/files/legacy/Documents/1000/CommEngageGuide.pdf](https://doh.wa.gov/sites/default/files/legacy/Documents/1000/CommEngageGuide.pdf)
+### 6.2 General principles, guidelines, and standards when engaging farmers
+Several values can be applied while engaging farmers, and these can be summarized as follows:
+- **Honor confidentiality** : Farmers providing information should be informed about the Initiative's purpose and told that all information they provide is confidential.
+- **Build trust** : Creating trust with farmers on the Initiative is a must to create ownership. This is achieved by respecting and engaging all groups of farmers' representatives in all the project phases. There are cases when farmers would need to be compensated for opportunity costs if, for some reason, the research commodity or treatment did not perform to the expected standard.
+- **Respect views and opinions: Farmers' views and opinions are valued while engaging in research, workshops, and training. The farmers are free to modify, accept, or reject a given technology or practice.**
+    - **Value indigenous knowledge** : Farmers have good reasons for making their own decisions in their livelihoods. A trade-off analysis between the traditional and improved practices proved that the opportunity costs associated with the loss in weed biomass due to the adoption of improved practices are not adequately offset by the economic gains from increased grain yield and crop residue biomass. As a result, it is recommended that researchers and development practitioners should consider indigenous knowledge and a broader systems approach and total plot productivity rather than just the partial benefits (for instance, from grain productivity gains) from specific plots of land under smallholder production systems.
+    - **Be inclusive** : The project engages all groups of farmers (men, women, youth, wealthy, influential, discriminated, poor, and landless) during diagnosis and targets most of them based on priorities.
+    - **Build their local capacity to innovate** : All participating farmers should be grouped based on the commodity as an innovation cluster/farmers research groups to strengthen their collaboration and information sharing in each research.
+    - **Learn from the farmers** : This means starting with both male and female farmers in their knowledge, awareness, attitude, beliefs, feelings, and practical habits.
+    - **Discuss and share experiences** : As a facilitator, speak less and listen more.
+    - **Involve all groups in the community** : Male, female, the youth, rich and poor .
+    - **Facilitate, do not lecture:** Create a learning environment for everybody by communicating openly and constructively based on mutual trust, respect  and confidence.
+    - **Aim at practical orientation** : Adult learning is life- or work-centered.
+    - **Triangulate information** : Use information from different sources. Use different tools to collect information. Triangulation is used for crosschecking information.
+    - **Avoid biases** : Fit your objectives into local situations. Biases, such as those for a special crop, a time (season), people, and a project, can adversely affect the effectiveness of agricultural programs.
+    - **Learn from mistakes** : Adapt and develop tools and techniques in the field.
+    - **Uphold sustainability:** Activities should be sustainable and continue after donor support has ceased.
+## 7.0 Steps for sustaining community engagement year-round
+**Step 1: Pause for a strategic review and reset**
+Take time for a strategic reset. Stop executing for a set period and arrange a time to meet in a distraction-free environment. Focus on debriefing and sharing your thoughts. What [engagement tactics](https://www.higherlogic.com/blog/online-community-engagement-tactics/) are working? What could be improved? What seems surprising? It is a good time to check in with the community and integrate the community more deeply into your organization's initiatives.
+**Step 2: Prioritize efforts to improve your focus**
+Most likely, during your team debriefs, everyone will have recommendations for tactics to implement. However, recognize that you have limited time and resources and must prioritize your time accordingly. One way to navigate this challenge is to build a community roadmap. See what you would like to pursue and prioritize it based on the needs and time of your team. With this approach, you will ensure that all ideas are represented, and suggestions do not fall through the cracks. What is essential right now? What is a nice-to-have? What can wait? This sense of focus will help your team make more impactful decisions.
+**Step 3: Create a community super user program**
+Identify your most involved community members and create an official program with responsibilities. It might make sense right now to have many super users so that you can give them each a small chunk of the responsibility. Create a shared plan for maintaining discussions, sharing fresh content, and keeping discussions going.
+## 8.0 Conclusion
+Acceptance and adoption of climate-resilient crops by the farmers have to be accompanied by associated agronomic and management practices for the crops in question. Practical approaches to demonstrate the evidence are important in achieving effective and sustainable transfer of the various climate-resilient crops.
+A multiple-intervention approach can be an effective way to introduce management practices to a community. This approach involves using various methods to convey information and skills to community members, with the goal of promoting the adoption and sustained use of the desired management practices.
+The use of real observations and experiences on how resilient crops are expected to be different from other crops that cannot survive climate change hardships are paramount practical approaches to showcase to the community members to explain best techniques for getting uptake of improved management practices associated with selected crops. The adaptive research cycle, which contains three steps (demonstration, adaptation, and adoption steps), is a good method for addressing this.
+The introduction of PREA is a key component in promoting improved agricultural technologies to farmers by the Initiative. The PREA focuses on encouraging the active participation of local leaders, farmers, researchers, extension agents (EAs), and the private sector in identifying the problems of local communities and their possible solutions. It involves communities in analyzing their situation, planning, trying, monitoring, and evaluating new technologies. This will result in the widespread adoption of identified and relevant new practices and new varieties as a result of farmer-to-farmer extension. Many of Initiative's partners have already recorded successes in disseminating technologies, but we encourage them to continue using extension methods that have worked well for them in the past and possibly incorporate some of the PREA concepts. Using the diversity of dissemination approaches would make it possible to compare the efficiency and impact of the different methods.
+Community engagement is essential in setting up SMEs. By involving community members in the planning process and providing training and education, access to funding, collaboration with local institutions, and access to markets, SMEs can succeed and contribute to the community's economic development.
+## Annexes
+### Annex A: Meaning of words
+**Mandate areas: These are the target areas for the impact of the work packages of initiative interventions. Mandate areas are different in surface area between the countries.**
+**Action site:** Action sites are geographical areas encompassing a community or a cluster of communities in each mandate area where the field activities related to technology identification, evaluation, and adaptation are implemented in partnership with development agencies.
+**Satellite sites:** Satellite sites are similar in terms of geographical area, population, and other general characteristics to action sites but more numerous, and the total number depends on the overall objectives and targets of a specific work package. These sites are used to disseminate best-bet options, developed at the Action Sites under the leadership of development partners, while activities at the Action Sites are led by the project.
+### Annex B:  References

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+---
+gardian_id: "907df02b565e9b4776452910981bebde"
+source: "gardian_index"
+url: "https://hdl.handle.net/20.500.11766/5791"
+description: "Seed producer cooperatives involved directly in different projects with ICRISAT and IER in Mali as partners were targeted for this activity. These cooperatives were trained from 2014 to 2016 on seed production techniques, communication tools for seed marketing and internal capacity building of the organization.  Information were then collected each year to evaluate the performance of these cooperatives. Workshops and interviews were organized to discuss problems occurring during the seed production, cooperatives management, and organizational progress. Results"
+id: "3d473c4f29c10674ea431984cd4c60e5"
+title: "Documentation of performances of at least 10 seed cooperatives in Mali"
+language: "English"
+resource_type: "Report"
+release_year: "2017"
+rights: "CC-BY"
+dataNODE_id: "907df02b565e9b4776452910981bebde"
+keywords: ["agriculture", "agriculture |", "producer cooperatives", "seed production", "capacity building", "documentation", "seed", "cooperatives", "mali", "projects", "techniques", "communication", "tools"]
+geography: {"regions": ["Western Africa", "Sub-Saharan Africa", "Africa", "World"], "countries": ["Mali"]}
+---
+***Flagship Project: 2:  Improved Varieties and Hybrids***
+***COA: Sorghum-WCA***
+**Documentation of performances of at least 10 seed cooperatives in Mali**
+*Aboubacar Toure* *1* *, Baloua Nebie* *1* *, Mamourou Sidibe* *1* *, Abdoulaye Diallo* *2* *, Bocar Diallo* *2* *, Krista Isaacs* *1* *,* Ramadjita Tabo *1*
+*1* *ICRISAT-Mali,* *2* *IER*
+**Objective of the activity**
+The objectives were to:
+- Evaluate the performance of seed cooperatives in seed production and commercialization
+- Identify specific success experiences in order to share them with other seed cooperatives
+### Methodology
+Seed producer cooperatives involved directly in different projects with ICRISAT and IER in Mali as partners were targeted for this activity. These cooperatives were trained from 2014 to 2016 on seed production techniques, communication tools for seed marketing and internal capacity building of the organization.  Information were then collected each year to evaluate the performance of these cooperatives. Workshops and interviews were organized to discuss problems occurring during the seed production, cooperatives management, and organizational progress. Results
+From 2015 to 2016, seed sales have increased on average by 77% for the 11 seed cooperatives in the study (Figure1). Nine out the eleven seed cooperatives showed higher quantity of seed sold in 2016 compared to that of 2015. A key result of this activity is the networking of these cooperatives in supplying emergency seeds to various projects involved in food s security For the ULPC (Union Locale des Producteurs de Semences) at Dioila, the cooperative has institutionalized new rules for profit sharing, decision making and information sharing. This internal rules have increased farmers trust in the seed business. Another key element of this success was the commitment of ULPC to produce and sell locally quality seed to farmers. As consequence the Union received a grant to build 4 seed stores close to the farmers. COOPROSEM realized a significant economic progress in 2016 with 2,000 $US of net profit compared to 2015. The cooperative was able to pay all its seed producers members on time. Some seed producers gained more than 1,600$US.
+<!-- image -->
+Bar chart
+|               |   2015 |   2016 |
+|---------------|--------|--------|
+| Jiguiya       |    753 |   3219 |
+| Seneyiriwaton |   2200 |   2742 |
+| Womukon       |   2675 |   2100 |
+| Jiguiseme     |   1088 |    910 |
+| PDRN          |   1165 |   4700 |
+| Jiguisemè     |    773 |    890 |
+| Dunkafa       |    232 |    544 |
+| Nupaganion    |     90 |    700 |
+| Union Nietaa  |   1436 |   3322 |
+| COOPROSEM     |   3946 |   6294 |
+| ULPC          |   1534 |   2742 |
+**Fig. 1. Sorghum hybrid seed sale by 11 Malian farmers’ cooperatives in 2016 and 2015**
+**Next step**
+Information are being collected on the current weaknesses of cooperatives. Based on the analysis of these information, specific actions have been developed to strengthen the seed cooperatives.
+A deeper analysis of the specific performance of cooperatives and the factors of this progress will be analyzed and documented for sharing experience to others seed cooperatives.

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+version https://git-lfs.github.com/spec/v1
+oid sha256:65c9575eb8cc43eaa836d5c759b0e77de203662097eb34b1b56e27bc48db7490
+size 69627

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+---
+license: cc-by-4.0
+pretty_name: "GAIA / GARDIAN-CIGI Agricultural Research Corpus"
+tags:
+  - "science"
+  - "agriculture"
+  - "academic"
+  - "rag"
+  - "cgiar"
+  - "multilingual"
+  - "documents"
+  - "research"
+  - "food-security"
+  - "climate-adaptation"
+  - "sdg 1 - no poverty"
+  - "nutrition"
+  - "food security"
+  - "africa south of sahara"
+  - "carbon"
+  - "climate change"
+  - "latin america and the caribbean"
+  - "nutrition, health and food security"
+  - "poverty reduction, livelihoods and jobs"
+  - "sdg 2 - zero hunger"
+  - "sdg 8 - decent work and economic growth"
+  - "systems transformation"
+  - "decision making"
+  - "health"
+  - "africa"
+task_categories:
+  - summarization
+  - text-retrieval
+  - question-answering
+  - text-generation
+  - feature-extraction
+size_categories:
+  - n<1K
+configs:
+  - config_name: full_text_en
+    default: true
+    data_files:
+      - split: train
+        path: "FULL_TEXT/EN/Parquet/*.parquet"
+  - config_name: abstracts_only_en
+    data_files:
+      - split: train
+        path: "ABSTRACTS_ONLY/EN/Parquet/*.parquet"
+  - config_name: abstracts_only_es
+    data_files:
+      - split: train
+        path: "ABSTRACTS_ONLY/ES/Parquet/*.parquet"
+  - config_name: abstracts_only_fr
+    data_files:
+      - split: train
+        path: "ABSTRACTS_ONLY/FR/Parquet/*.parquet"
+---
+# GAIA / GARDIAN-CIGI Agricultural Research Corpus
+This dataset contains **20** agricultural research records from the GARDIAN repository, processed through the CIGI pipeline: **6** with full text and **14** with metadata and abstract only.
+## Repository Layout
+```
+FULL_TEXT/<LANG>/        documents with extracted full text
+ABSTRACTS_ONLY/<LANG>/   documents with metadata and abstract only
+    JSON/                one JSON file per document (metadata + content)
+    Markdown/            one Markdown file per document (metadata front matter + text)
+    Parquet/             all documents of the folder in Parquet (part files)
+```
+Each `FULL_TEXT`/`ABSTRACTS_ONLY` + language folder is available as a separate config in the dataset viewer, e.g. `load_dataset("sciosystems/test", "full_text_en")`.
+| Folder | Documents | Tokens | Files | Size |
+|---|---:|---:|---:|---:|
+| `ABSTRACTS_ONLY/EN` | 9 | 0 | 20 | 146.30 KB |
+| `ABSTRACTS_ONLY/ES` | 3 | 0 | 7 | 73.58 KB |
+| `ABSTRACTS_ONLY/FR` | 2 | 0 | 5 | 40.12 KB |
+| `FULL_TEXT/EN` | 6 | 29,954 | 13 | 468.00 KB |
+## Dataset Overview
+| Property | Value |
+|----------|-------|
+| **Total Documents** | 20 |
+| **Full-Text Documents** | 6 |
+| **Abstract-Only Documents** | 14 |
+| **Total Size (all formats)** | 728.00 KB |
+| **Total Tokens (full text)** | 29,954 |
+| **Total Characters (full text)** | 188,904 |
+| **Avg. Tokens per Full-Text Document** | 4,992 |
+| **Total Pages (partly est.)** | 76 |
+| **Languages** | 3 |
+| **Countries** | 18 |
+| **Unique Keywords** | 211 |
+| **Resource Types** | 6 |
+| **Documents with Source URL** | 20 (100.0%) |
+| **Date Generated** | 2026-11-04 18:27:07 |
+Tokens are counted on the `content` field of full-text documents using the `o200k_base` tokenizer (tiktoken). 3 of 6 full-text documents have a real page count; the rest are estimated at 500 words per page.
+## Language Distribution
+| Language | Count | Percentage |
+|----------|------:|-----------:|
+| English | 15 | 75.0% |
+| Spanish | 3 | 15.0% |
+| French | 2 | 10.0% |
+## Resource Types
+| Type | Count | Percentage |
+|------|------:|-----------:|
+| Dataset / Tabular | 7 | 35.0% |
+| Scientific Publication | 6 | 30.0% |
+| Report | 2 | 10.0% |
+| Brief | 2 | 10.0% |
+| Training Material | 2 | 10.0% |
+| Dataset / Geospatial | 1 | 5.0% |
+## Top Countries
+| Country | Count | Percentage |
+|---------|------:|-----------:|
+| Peru | 3 | 15.0% |
+| Viet Nam | 2 | 10.0% |
+| Indonesia | 2 | 10.0% |
+| Mali | 2 | 10.0% |
+| India | 1 | 5.0% |
+| Ethiopia | 1 | 5.0% |
+| Bangladesh | 1 | 5.0% |
+| Guyana | 1 | 5.0% |
+| Russia | 1 | 5.0% |
+| Colombia | 1 | 5.0% |
+| Democratic Republic of the Congo | 1 | 5.0% |
+| Malawi | 1 | 5.0% |
+| Uganda | 1 | 5.0% |
+| Honduras | 1 | 5.0% |
+| Guatemala | 1 | 5.0% |
+| Kenya | 1 | 5.0% |
+| Costa Rica | 1 | 5.0% |
+| Nigeria | 1 | 5.0% |
+## Top Keywords
+sdg 1 - no poverty, nutrition, food security, africa south of sahara, carbon, climate change, latin america and the caribbean, nutrition, health and food security, poverty reduction, livelihoods and jobs, sdg 2 - zero hunger, sdg 8 - decent work and economic growth, systems transformation, decision making, health, africa, research, emission, models, tropical forests, biomass
+## Publication Years
+2026 (1), 2025 (3), 2024 (2), 2023 (1), 2022 (2), 2021 (1), 2020 (1), 2018 (2), 2017 (2), 2015 (3), 2014 (2)
+## Rights
+Per-document licensing varies. Distribution of the `rights` field:
+| Rights | Docs | Share |
+|---|---:|---:|
+| CC-BY | 20 | 100.0% |
+> **Rights are heterogeneous.** The repo-level `cc-by-4.0` tag reflects the curation of the collection, **not** a uniform document license. **Always check the per-document `rights` field (and the source at `url`, where available) before redistributing or using individual documents commercially.**
+## Document JSON Schema
+```json
+{
+  "gardian_id": "string",
+  "source": "string",
+  "url": "string",
+  "description": "string",
+  "id": "string",
+  "title": "string",
+  "language": "string",
+  "resource_type": "string",
+  "release_year": "string",
+  "rights": "string",
+  "dataNODE_id": "string",
+  "keywords": "list[string]",
+  "geography": {
+    "regions": "list[string]",
+    "countries": "list[string]"
+  },
+  "content": "string"
+}
+```
+## License
+This dataset is released under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/).
+## Acknowledgements
+This dataset was developed for the [Generative AI for Agriculture (GAIA)](https://www.ifpri.org/project/generative-ai-for-agriculture-gaia/) project, funded by the Gates Foundation and UK International Development (FCDO), in collaboration between [CGIAR](https://www.cgiar.org/) and [SCiO](https://scio.systems/).
+---
+*Generated automatically on 2026-11-04 18:27:07*