2018- CSA Monitoring: Hoima Climate-Smart Village (Uganda)

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Bonilla-Findji, Osana; Eitzinger, Anton; Andrieu, Nadine; Jarvis, Andy; Recha, John; Ambaw, Gebermedihin; Kakeeto, Ronald, 2019, "2018- CSA Monitoring: Hoima Climate-Smart Village (Uganda)", https://doi.org/10.7910/DVN/RJGSDF, Harvard Dataverse, V3, UNF:6:coXhMAAzBe0u6RpHTfz1bA== [fileUNF]

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Description	This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Hoima Climate Smart Village (Uganda) in October 2018. 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)?
Subject	Earth and Environmental Sciences; Agricultural Sciences
Keyword	Monitoring, Climate Smart Agriculture, Households, Livelihoods, Adaptation, Food Security, Climate Shocks, Farm, East Africa, Decision and Policy Analysis - DAPA
Related Publication	Kristjanson, P., Neufeldt, H., Gassner, A. et al. 2012. Are food insecure smallholder households making changes in their farming practices? Evidence from East Africa. Food Sec. 4, 381–397 doi:10.1007/s12571-012-0194-z
Notes	Universe: At the time of data collection, all survey participants resided within 7 communities in Hoima Climate Smart Villages, Uganda ("Kibaire", "Kiranga", "Kyamongi", "Kasinina", "Mparangasi", "Nyakakonge", or "Katikara"). Implementation was carried out by locally trained enumerators using the Geofarmer Smart Monitoring App for data collection. A total of 453 farmers were interviewed: 115 adult females, 145 adult males (age 35 or over), 108 young females and 76 young males (under age 35). Where possible, two adults and one “young” person were surveyed from each household. 9 individuals had unrecorded birth years.
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	1. 2018_EA_UGA-HMA Questionnaire Codified.xls EA_UGA-HMA_Additional information/MS Excel Spreadsheet - 101.5 KB Published Dec 20, 2019 0 Downloads MD5: cefedde547f30d115023175a07515265	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	10. 2018 EA UGA HMA_CSA Monitoring Results.xls EA_UGA-HMA_Additional information/MS Excel Spreadsheet - 37.0 KB Published Feb 17, 2020 3 Downloads MD5: b956bbb8b52b16f89c7aa901839f9361	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	2. 2018_EA_UGA-HMA_Questions Tree Short.pdf EA_UGA-HMA_Additional information/Adobe PDF - 1.0 MB Published Dec 20, 2019 0 Downloads MD5: dac2c91b75da7d4a5cb62c493fda9735	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	3. 2018_EA_UGA-HMA_Glossary_Main_CSA_practices.pdf EA_UGA-HMA_Additional information/Adobe PDF - 855.4 KB Published Dec 20, 2019 0 Downloads MD5: ed25354c4d5ed5764c294a8dd8df08cf	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	4. 2018_EA_UGA-HMA_Inform Consent.docx EA_UGA-HMA_Additional information/MS Word - 223.8 KB Published Dec 20, 2019 0 Downloads MD5: d627b1a144d55d603e1abed821e1c0b9	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	5. Comments on Hoima data cleaning anonimized.xls EA_UGA-HMA_Additional information/MS Excel Spreadsheet - 33.5 KB Published Dec 20, 2019 0 Downloads MD5: 6d29262d7555697976d72a3054d62feb	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	6. 2018_EA_UGA-HMA_PROTOCOL OF CLEANING AND PREPARATION OF DATA FOR ANALYSIS AND PUBLICATION IN REPOSITORY.docx EA_UGA-HMA_Additional information/MS Word - 30.5 KB Published Dec 20, 2019 0 Downloads MD5: 200539b5ae213f4c66dbc539ba9aac3b	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	7. Minimum Risk Review Application_ME for IDRC_20180628.doc EA_UGA-HMA_Additional information/MS Word - 227.0 KB Published Dec 20, 2019 0 Downloads MD5: 464072f897ec9c63b5a56d4cf67d13c8	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	8. IRB Approval Letter_CSA_perf - extension 2019 4.pdf EA_UGA-HMA_Additional information/Adobe PDF - 590.1 KB Published Dec 20, 2019 0 Downloads MD5: da82441f686afcc7357f37c74fe096c3	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	9. Final_Enumerators Recordings anonymized_ Hoima_2018.xls EA_UGA-HMA_Additional information/MS Excel Spreadsheet - 330.0 KB Published Mar 11, 2021 1 Download MD5: 426ab60f78bdbaaea41849917ee01764	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX

Citation Metadata

Persistent Identifier	doi:10.7910/DVN/RJGSDF
Publication Date	2019-12-20
Title	2018- CSA Monitoring: Hoima Climate-Smart Village (Uganda)
Author	International Center for Tropical Agriculture - CIAT; Climate Change, Agriculture and Food Security – CCAFS0000-0002-6098-000X International Center for Tropical Agriculture - CIAT0000-0001-7317-3381 Centre de coopération internationale en recherche agronomique pour le développement – CIRAD0000-0001-9558-9302 International Center for Tropical Agriculture - CIAT; Climate Change, Agriculture and Food Security – CCAFS0000-0001-6543-0798 International Livestock Research Institute - ILRI; Climate Change, Agriculture and Food Security – CCAFS0000-0002-1146-7197 International Livestock Research Institute - ILRI; Climate Change, Agriculture and Food Security – CCAFS0000-0002-0827-4466 National Agricultural Research Organisation - NARO0000-0001-7622-6944
Point of Contact	Use email button above to contact. Recha, John (International Livestock Research Institute - ILRI; Climate Change, Agriculture and Food Security – CCAFS) Bonilla-Findji, Osana (International Center for Tropical Agriculture - CIAT; Climate Change, Agriculture and Food Security – CCAFS)
Description	This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Hoima Climate Smart Village (Uganda) in October 2018. 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)?
Subject	Earth and Environmental Sciences; Agricultural Sciences
Keyword	Monitoring (AGROVOC) http://aims.fao.org/aos/agrovoc/c_4911 Climate Smart Agriculture (AGROVOC) http://aims.fao.org/aos/agrovoc/c_1361789093890 Households (AGROVOC) http://aims.fao.org/aos/agrovoc/c_3676 Livelihoods (AGROVOC) http://aims.fao.org/aos/agrovoc/c_1374498089962 Adaptation (AGROVOC) http://aims.fao.org/aos/agrovoc/c_117 Food Security (AGROVOC) http://aims.fao.org/aos/agrovoc/c_10967 Climate Shocks Farm East Africa (CIAT Region) Decision and Policy Analysis - DAPA (CIAT Research Area)
Related Publication	Kristjanson, P., Neufeldt, H., Gassner, A. et al. 2012. Are food insecure smallholder households making changes in their farming practices? Evidence from East Africa. Food Sec. 4, 381–397 doi:10.1007/s12571-012-0194-z Kristjanson P, Garlick C, Cramer L, Förch W, Thornton PK Ngungu A. 2014. Global Summary of Baseline Household Survey Results. Version 2. CCAFS Working Paper no. 56. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Copenhagen, Denmark. Available online at: www.ccafs.cgiar.org handle 10568/16426 https://hdl.handle.net/10568/16426 Recha J, Radeny M, Kimeli P, Hafashimana D, Masanyu J, Ssekiwoko F, Odongo W. 2016. Progress in achieving household food security in climate-smart villages in the Albertine Rift, western Uganda. CCAFS Info Note. Copenhagen, Denmark: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). handle 10568/79933 https://hdl.handle.net/10568/79933 Recha J, Kimeli P, Atakos V, Radeny M, Mungai C. 2017. Stories of Success: Climate-Smart Villages in East Africa. Wageningen, Netherlands: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). handle 10568/81030 http://hdl.handle.net/10568/81030 Mubiru, D.N., Radeny, M., Kyazze, F.B., Zziwa, A., Lwasa, J., Kinyangi, J. and Mungai, C. 2018. Climate trends, risks and coping strategies in smallholder farming systems in Uganda. Climate Risk Management 22: 4-21 https://doi.org/10.1016/j.crm.2018.08.004 handle 10568/98910 https://hdl.handle.net/10568/98910 Radeny M, Desalegn A, Mubiru D, Kyazze F, Mahoo H, Recha J, Kimeli P, Solomon D. 2019. Indigenous knowledge for seasonal weather and climate forecasting across East Africa. Climatic Change 156(4):509-526. https://doi.org/10.1007/s10584-019-02476-9 handle 10568/103231 https://hdl.handle.net/10568/103231
Notes	Universe: At the time of data collection, all survey participants resided within 7 communities in Hoima Climate Smart Villages, Uganda ("Kibaire", "Kiranga", "Kyamongi", "Kasinina", "Mparangasi", "Nyakakonge", or "Katikara"). Implementation was carried out by locally trained enumerators using the Geofarmer Smart Monitoring App for data collection. A total of 453 farmers were interviewed: 115 adult females, 145 adult males (age 35 or over), 108 young females and 76 young males (under age 35). Where possible, two adults and one “young” person were surveyed from each household. 9 individuals had unrecorded birth years.
Language	English
Producer	International Center for Tropical Agriculture (CIAT) / CGIAR Research Program on Climate Change, Agriculture and Food Security (Flagship 2) (CIAT / CCAFS Flagship 2)
Production Date	2019-12-20
Funding Information	CCAFS Flagship 2 Climate Smart Technologies and Practices funds 2018: G135
Distribution Date	2019-12-20
Depositor	Ortega, Angelly
Deposit Date	2019-12-20
Time Period	Start Date: 2017-10-01; End Date: 2018-10-01
Date of Collection	Start Date: 2018-10-01; End Date: 2018-10-24
Data Type	Survey data; Socio-economic Data; Geographic Data; Environmental Data; Capacity Building
Related Material	EA_UGA-HMA Cleaned anonymized responses M0-M5 EA_UGA-HMA_Anonymized responses_Calculator EA_UGA-HMA_Additional information 2018_ EA_UGA-HMA Questionnaire Codified 2018_EA_UGA-HMA_Questions Tree Short 2018_EA_UGA-HMA_Glossary_Main_CSA_practices 2018_EA_UGA-HMA_Inform Consent Comments on Hoima data cleaning anonimized 2018_EA_UGA-HMA_PROTOCOL OF CLEANING AND PREPARATION OF DATA FOR ANALYSIS AND PUBLICATION IN REPOSITORY Minimum Risk Review Application_ME for IDRC_20180628 IRB Approval Letter_CSA_perf - extension 2019 4 Final_Enumerators Recordings anonymized_ Hoima_2018
Other Reference	https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/WQALYL; https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/IUJQZV; https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/Q7PKLN

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