2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)

This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Doyogena Climate Smart Village (Ethiopia) in October 2019. This monitoring framework developed by CCAFS is meant to be deployed annually across the global ne...

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Main Authors: Bonilla Findji, Osana, Eitzinger, Anton, Andrieu, Nadine, Jarvis, Andy, Recha, John W.M., Ambaw, Gebermedihin, Tadesse, Meron
Format: Conjunto de datos
Language:Inglés
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/10568/108910
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author Bonilla Findji, Osana
Eitzinger, Anton
Andrieu, Nadine
Jarvis, Andy
Recha, John W.M.
Ambaw, Gebermedihin
Tadesse, Meron
author_browse Ambaw, Gebermedihin
Andrieu, Nadine
Bonilla Findji, Osana
Eitzinger, Anton
Jarvis, Andy
Recha, John W.M.
Tadesse, Meron
author_facet Bonilla Findji, Osana
Eitzinger, Anton
Andrieu, Nadine
Jarvis, Andy
Recha, John W.M.
Ambaw, Gebermedihin
Tadesse, Meron
author_sort Bonilla Findji, Osana
collection Repository of Agricultural Research Outputs (CGSpace)
description This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Doyogena Climate Smart Village (Ethiopia) in October 2019. This monitoring framework developed by CCAFS is meant to be deployed annually across the global network of Climate-Smart Villages to gather field-based evidence by tracking the progress on: adoption of CSA practices and technologies, as well as access to climate information services and their related impacts at household level and farm level This framework proposes standard Descriptive Indicators to track changes in: 5 enabling dimensions that might affect adoption patterns, a set of 5 CORE indicators at Household level to assess perceived effects of CSA practices on Food Security, Productivity, Income and Climate vulnerability and 4 CORE indicators on Gender aspects (Participation in decision-making, Participation in implementation, Access/control over Resources and work time). At farm level, 7 CORE indicators are suggested to determine farms CSA performance, as well as synergies and trade-offs among the three pillars. This integrated framework is associated with a cost-effective data collection App (Geofarmer) that allowed capturing information in almost real time. The survey questionnaire is structured around different thematic modules (Demographic, Livelihoods, Food Security, Climate events, Climate Services, CSA practices, Financial Services) connected to standard CSA metrics and the specific indicators. The framework responds to three main research questions: Within each CSV community, who adopts which CSA technologies and practices and what are their motivations, enabling/constraining factors? What are the gender-disaggregated perceived effects of CSA options on farmers’ livelihood (agricultural production, income, food security, food diversity and adaptive capacity) and on key gender dimensions (participation in decision-making, participation in CSA implementation and dis-adoption, control and access over resources and labour)? How does CSA perform at farm level, and what synergies and trade-offs exist (whole farm model analysis)? NOTE: In the case of the 2019 Implementation in Doyogena only questions 1 and 2 where addressed (The “Calculator Modules” of the survey allowing assessing farm level effects of CSA practice on performance were not applied). (2020-03-30)
format Conjunto de datos
id CGSpace108910
institution CGIAR Consortium
language Inglés
publishDate 2020
publishDateRange 2020
publishDateSort 2020
record_format dspace
spelling CGSpace1089102025-01-27T15:00:52Z 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia) Bonilla Findji, Osana Eitzinger, Anton Andrieu, Nadine Jarvis, Andy Recha, John W.M. Ambaw, Gebermedihin Tadesse, Meron monitoring vigilancia climate smart agriculture agricultura climaticamente inteligente households hogares livelihoods medios de vida farmers agricultores adaptation adaptacion food security seguridad alimentaría This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Doyogena Climate Smart Village (Ethiopia) in October 2019. This monitoring framework developed by CCAFS is meant to be deployed annually across the global network of Climate-Smart Villages to gather field-based evidence by tracking the progress on: adoption of CSA practices and technologies, as well as access to climate information services and their related impacts at household level and farm level This framework proposes standard Descriptive Indicators to track changes in: 5 enabling dimensions that might affect adoption patterns, a set of 5 CORE indicators at Household level to assess perceived effects of CSA practices on Food Security, Productivity, Income and Climate vulnerability and 4 CORE indicators on Gender aspects (Participation in decision-making, Participation in implementation, Access/control over Resources and work time). At farm level, 7 CORE indicators are suggested to determine farms CSA performance, as well as synergies and trade-offs among the three pillars. This integrated framework is associated with a cost-effective data collection App (Geofarmer) that allowed capturing information in almost real time. The survey questionnaire is structured around different thematic modules (Demographic, Livelihoods, Food Security, Climate events, Climate Services, CSA practices, Financial Services) connected to standard CSA metrics and the specific indicators. The framework responds to three main research questions: Within each CSV community, who adopts which CSA technologies and practices and what are their motivations, enabling/constraining factors? What are the gender-disaggregated perceived effects of CSA options on farmers’ livelihood (agricultural production, income, food security, food diversity and adaptive capacity) and on key gender dimensions (participation in decision-making, participation in CSA implementation and dis-adoption, control and access over resources and labour)? How does CSA perform at farm level, and what synergies and trade-offs exist (whole farm model analysis)? NOTE: In the case of the 2019 Implementation in Doyogena only questions 1 and 2 where addressed (The “Calculator Modules” of the survey allowing assessing farm level effects of CSA practice on performance were not applied). (2020-03-30) 2020-05-08 2020-07-31T00:31:27Z 2020-07-31T00:31:27Z Dataset https://hdl.handle.net/10568/108910 en Open Access Bonilla-Findji, O.; Eitzinger, A.; Andrieu, N.; Jarvis, A.; Recha, J.; Ambaw, G.; Tadesse, M. (2020) 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia), https://doi.org/10.7910/DVN/DOPMQY, Harvard Dataverse, V3
spellingShingle monitoring
vigilancia
climate smart agriculture
agricultura climaticamente inteligente
households
hogares
livelihoods
medios de vida
farmers
agricultores
adaptation
adaptacion
food security
seguridad alimentaría
Bonilla Findji, Osana
Eitzinger, Anton
Andrieu, Nadine
Jarvis, Andy
Recha, John W.M.
Ambaw, Gebermedihin
Tadesse, Meron
2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)
title 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)
title_full 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)
title_fullStr 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)
title_full_unstemmed 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)
title_short 2019 - CSA Monitoring: Doyogena Climate-Smart Village (Ethiopia)
title_sort 2019 csa monitoring doyogena climate smart village ethiopia
topic monitoring
vigilancia
climate smart agriculture
agricultura climaticamente inteligente
households
hogares
livelihoods
medios de vida
farmers
agricultores
adaptation
adaptacion
food security
seguridad alimentaría
url https://hdl.handle.net/10568/108910
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