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

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    Authors
    Bonilla Findji, Osana
    Eitzinger, Anton
    Andrieu, Nadine
    Jarvis, Andy
    Recha, John W.M.
    Ambaw, Gebermedihin
    Tadesse, Meron
    Date Issued
    2020-05
    Language
    en
    Type
    Dataset
    Accessibility
    Open Access
    Usage rights
    CC-BY-4.0
    Metadata
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    Citation
    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
    Permanent link to cite or share this item: https://hdl.handle.net/10568/108910
    DOI: https://doi.org/10.7910/DVN/DOPMQY
    Abstract/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)
    CGIAR Author ORCID iDs
    Osana Bonilla-Findjihttps://orcid.org/0000-0002-6098-000X
    Anton Eitzingerhttps://orcid.org/0000-0001-7317-3381
    Andy Jarvishttps://orcid.org/0000-0001-6543-0798
    Other CGIAR Affiliations
    Climate Change, Agriculture and Food Security
    AGROVOC Keywords
    monitoring; vigilancia; climate smart agriculture; agricultura climaticamente inteligente; households; hogares; livelihoods; medios de vida; farmers; agricultores; adaptation; adaptacion; food security; seguridad alimentaría
    Subjects
    AGRICULTURE; CLIMATE CHANGE ADAPTATION; MONITORING AND REPORTING;
    Countries
    Ethiopia
    Regions
    Africa; Eastern Africa
    Organizations Affiliated to the Authors
    Alliance of Bioversity International and CIAT; Centre de Coopération Internationale en Recherche Agronomique pour le Développement; International Livestock Research Institute
    Investors/sponsors
    International Fund for Agricultural Development
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    • Alliance Bioversity CIAT Datasets [170]

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