2018- CSA Monitoring: Barisal Climate-Smart Village (Bangladesh)

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Bonilla-Findji, Osana; Eitzinger, Anton; Andrieu, Nadine; Jarvis, Andy; Khatri-Chhetri, Arun; Nagpal, Mansi; Hossain, Emdad; Rashid, Harun Or, 2020, "2018- CSA Monitoring: Barisal Climate-Smart Village (Bangladesh)", https://doi.org/10.7910/DVN/ODBHNG, Harvard Dataverse, V2

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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 Barisal Climate Smart Village (Bangladesh) in December 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 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)? The survey questionnaire is structured around different thematic modules (Demographic, Livelihoods, Food Security, Climate events, Climate Services, CSA practices, Financial Services) whose questions allow assessing standard CSA metrics and the specific indicators associated with the research questions 1 and 2. Data required for assessing farm level CSA performance are collected through the Farm, the Crop, the animals and the Tree Calculator modules. (2020-04-01)
Subject	Earth and Environmental Sciences; Agricultural Sciences
Keyword	Monitoring, Climate Smart Agriculture, Households, Livelihoods, Farm, Farmers, Adaptation, Food Security, Climate Shocks
License/Data Use Agreement	CC0 1.0

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	1. 2018_SA_BDS_BAR_Questionnaire_Codified.xls 2018_BDS-BAR_Additional_Information/MS Excel Spreadsheet - 88.5 KB Published May 15, 2020 0 Downloads MD5: d91ef1d9911bcaefeb5500f5b05fdc83	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	2. 2018_SA_BDS_BAR_Questions_Tree.pdf 2018_BDS-BAR_Additional_Information/Adobe PDF - 878.7 KB Published May 15, 2020 0 Downloads MD5: ef57be2007ec660599da56befa432082	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	3. 2018_SA_BDS_BAR_Glossary_Main_CSA_practices.pdf 2018_BDS-BAR_Additional_Information/Adobe PDF - 1.3 MB Published May 15, 2020 0 Downloads MD5: eed1063d7414aa445ea667e03fb898b4	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	4. 2018_SA_BDS_BAR_Inform_Consents.pdf 2018_BDS-BAR_Additional_Information/Adobe PDF - 505.9 KB Published May 15, 2020 0 Downloads MD5: b455580d785c7e29057c6177a512f637	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	5. 2018_SA_BDS_BAR_PROTOCOL OF CLEANING AND PREPARATION OF DATA FOR ANALYSIS.pdf 2018_BDS-BAR_Additional_Information/Adobe PDF - 145.6 KB Published May 15, 2020 0 Downloads MD5: b9ff19853e957ba432023a831afd24fe	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	6. 2018_SA_BDS_BAR_Minimum_Risk_Review_Application.pdf 2018_BDS-BAR_Additional_Information/Adobe PDF - 1.1 MB Published May 15, 2020 0 Downloads MD5: c2141cd4992be85e13f53ec41cc97902	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	7. 2018_SA_BDS_BAR_IRB_Approval_Letter.pdf 2018_BDS-BAR_Additional_Information/Adobe PDF - 590.1 KB Published May 15, 2020 0 Downloads MD5: da82441f686afcc7357f37c74fe096c3	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	8. 2018_SA_BDS_BAR_Enumerators_Recording.xls 2018_BDS-BAR_Additional_Information/MS Excel Spreadsheet - 124.5 KB Published May 15, 2020 0 Downloads MD5: 436e694482036e8d264350a7b26a19dd	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	9- 2018_SA_BDS_BAR_CSAMonitoringResults_GF_Links.xls 2018_BDS-BAR_Additional_Information/MS Excel Spreadsheet - 47.5 KB Published May 15, 2020 0 Downloads MD5: c43856bde0eb959ba99ddf74497bd287	Access File File Access Restricted Request Access Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	2018_BDS-BAR_M0-M5_responses-anonymized.xls 2018_BDS-BAR_Anonymized_Cleaned_Data_M0-M5/MS Excel Spreadsheet - 537.5 KB Published Mar 11, 2021 0 Downloads MD5: c0b9c131017a1d703ebc30bc9b32807b	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/ODBHNG
Publication Date	2020-05-15
Title	2018- CSA Monitoring: Barisal Climate-Smart Village (Bangladesh)
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 Maize and Wheat Improvement Center - (CIMMYT); Climate Change, Agriculture and Food Security - CCAFS0000-0003-1968-3166 Nagpal, MansiInternational Maize and Wheat Improvement Center - (CIMMYT); Climate Change, Agriculture and Food Security - CCAFS WorldFish0000-0001-5077-8740 WorldFish0000-0001-5172-9502
Point of Contact	Use email button above to contact. SHIRSATH, Paresh (International Maize and Wheat Improvement Center - (CIMMYT)) 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 Barisal Climate Smart Village (Bangladesh) in December 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 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)? The survey questionnaire is structured around different thematic modules (Demographic, Livelihoods, Food Security, Climate events, Climate Services, CSA practices, Financial Services) whose questions allow assessing standard CSA metrics and the specific indicators associated with the research questions 1 and 2. Data required for assessing farm level CSA performance are collected through the Farm, the Crop, the animals and the Tree Calculator modules. (2020-04-01)
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 Farm Farmers (AGROVOC) http://aims.fao.org/aos/agrovoc/c_2805 Adaptation (AGROVOC) http://aims.fao.org/aos/agrovoc/c_117 Food Security (AGROVOC) http://aims.fao.org/aos/agrovoc/c_10967 Climate Shocks
Topic Classification	Monitoring (AGROVOC) http://aims.fao.org/aos/agrovoc/c_4911 Climate Smart Agriculture (AGROVOC) http://aims.fao.org/aos/agrovoc/c_1361789093890
Language	English
Producer	International Center for Tropical Agriculture (CIAT) / CGIAR Research Program on Climate Change, Agriculture and Food Security (Flagship 2) (CGIAR Research Program on Climate Change, Agriculture and Food Security - CCAFS) (CIAT / CCAFS Flagship 2) https://ccafs.cgiar.org/es/home
Production Date	2020-04-01
Funding Information	CCAFS Flagship 2 Climate Smart Technologies and Practices funds 2018 (code for CCAFS contract with CIAT: G135); CCAFS South Asia program funds 2018.: G135
Distributor	CCAFS Flagship 2 Climate Smart Technologies and Practices.
Distribution Date	2020-04-01
Depositor	Ortega, Angelly
Deposit Date	2020-04-01
Time Period	Start Date: 2018-11-25; End Date: 2018-12-01
Date of Collection	Start Date: 2018-12-11; End Date: 2018-12-15
Data Type	Survey data; Socio-economic Data
Series	Seven villages from the Barisal region of Bangladesh were targeted by the CSA monitoring. The villages were Galua, Bagri, Biraljuri, Galua-Durgapur, Noikathi, Nangguli and Pargopalpur. In each of the 7 villages 11 households were direct CCAFS beneficiaries (that had participated in PAR activities implementing CSA practices) and 10 non-implementing households were included in survey. The CSA monitoring survey targeted two adults from each households actively involved in agricultural activities of the farm. One was the main person involved in deciding and implementing on-farm activities. This person had to respond to Modules 0 (Demographic), 1 (climate events),2 (Climate services), 3 (Livelihood Security),5 (CSA practices) and if women also to module 4 (Food Security).The second person had to be of opposite sex also involved in on-farm activities. This second person responded Modules 0, module 5 and –if women- also Module 4. A total of 149 households, 289 farmers (146 adult males and 143 adult females) were interviewed. Implementation was carried out by locally trained enumerators using the Geofarmer Smart Monitoring App for data collection.
Related Material	2018_BDS-BAR_Anonymized_Cleaned_Data_M0-M5 2018_BDS-BAR_Data_Calculator_Anonymized 2018_BDS-BAR_Additional_Information 2018_SA_BDS_BAR_Questionnaire_Codified 2018_SA_BDS_BAR_Questions_Tree 2018_SA_BDS_BAR_Glossary_Main_CSA_practices 2018_SA_BDS_BAR_Inform_Consents 2018_SA_BDS_BAR_PROTOCOL OF CLEANING AND PREPARATION OF DATA FOR ANALYSIS AND PUBLICATION IN REPOSITORY 2018_SA_BDS_BAR_Minimum_Risk_Review_Application 2018_SA_BDS_BAR_IRB_Approval_Letter 2018_SA_BDS_BAR_Enumerators_Recording - 2018_SA_BDS_BAR_CSAMonitoringResults_GF_Links

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