10.7910/DVN/FNWDAX Bonilla-Findji, Osana Osana Bonilla-Findji https://orcid.org/0000-0002-6098-000X Climate Change, Agriculture and Food Security Eitzinger, Anton Anton Eitzinger https://orcid.org/0000-0001-7317-3381 International Center for Tropical Agriculture Andrieu, Nadine Nadine Andrieu https://orcid.org/0000-0001-9558-9302 Centre de coopération internationale en recherche agronomique pour le développement Jarvis, Andy Andy Jarvis https://orcid.org/0000-0001-6543-0798 International Center for Tropical Agriculture Martínez- Barón, Deissy Deissy Martínez- Barón https://orcid.org/0000-0003-2317-8760 Climate Change, Agriculture and Food Security Ortega, Luis Alfonso Luis Alfonso Ortega Fundación Ecohabitats Mañunga, Jimmy Jimmy Mañunga Asociacion de Juntas de Acción Comunal del noroccidente de Popayan Harvard Dataverse 2019 Agricultural Sciences Monitoring Climate Smart Agriculture Households Livelihoods Adaptation Food Security Climate Shocks Latin America and the Caribbean Decision and Policy Analysis - DAPA International Center for Tropical Agriculture CGIAR Research Program on Climate Change, Agriculture and Food Security CCAFS Flagship 2: Climate Smart Technologies and Practices Bonilla-Findji, Osana Osana Bonilla-Findji Climate Change, Agriculture and Food Security Martinez Salgado, Jesus David Jesus David Martinez Salgado Climate Change, Agriculture and Food Security 2019-12-02 2019-12-02 2019-12-02 2021-03-11 2018-02-01/2018-03-01 2017-02-01/2018-02-01 Survey data;Socio-economic Data;Geographic Data;Environmental Data;Capacity Building 10568/16426 10.7910/DVN/FNWDAX/URNCMJ 10.7910/DVN/FNWDAX/XABVTG 10.7910/DVN/FNWDAX/K6K2E8 10.7910/DVN/FNWDAX/WBJP7M 10.7910/DVN/FNWDAX/9H01X0 10.7910/DVN/FNWDAX/AYPKNU 10.7910/DVN/FNWDAX/VUZS9B 10.7910/DVN/FNWDAX/2SDAGX 10.7910/DVN/FNWDAX/ULRX6D 10.7910/DVN/FNWDAX/WU3J7J 10.7910/DVN/FNWDAX/VYQZDI 10.7910/DVN/FNWDAX/PEPFWJ 10.7910/DVN/FNWDAX/ZYQ4FR 10.7910/DVN/FNWDAX/GSDBAE 10.7910/DVN/FNWDAX/FI1RSC 91124 62235 88904 268146 45219 48326 232960 2839483 77194 2967011 406016 604234 862 1712759 66462 110971 604234 232960 56801 2967011 406016 99599 1712759 35328 2839483 358927 120320 56296 38400 text/comma-separated-values text/comma-separated-values text/comma-separated-values text/csv application/vnd.ms-excel text/comma-separated-values application/msword application/pdf text/tab-separated-values application/pdf application/msword application/pdf text/tab-separated-values application/pdf text/tab-separated-values text/tab-separated-values application/pdf application/msword text/tab-separated-values application/pdf application/msword text/tab-separated-values application/pdf application/vnd.ms-excel application/pdf text/tab-separated-values application/vnd.ms-excel text/tab-separated-values application/vnd.ms-excel 3.1 Creative Commons CC0 1.0 Universal Public Domain Dedication. This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Cauca Climate Smart Village (Colombia) in February 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: <ul> <li> adoption of CSA practices and technologies, as well as access to climate information services and <li> their related impacts at household level (and farm level, in selected sites). </ul> This framework proposes standard Descriptive Indicators to track changes in: <ul> <li> 5 enabling dimensions that might affect adoption patterns, <li> 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 <li> 4 CORE indicators on Gender aspects (Participation in decision-making, Participation in implementation, Access/control over Resources and work time). <li> 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. </ul> The framework responds to three main research questions: <ol> <li value="1"> Within each CSV community, who adopts which CSA technologies and practices and what are their motivations, enabling/constraining factors? </li> <li> 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)? </li> <li> How does CSA perform at farm level, and what synergies and trade-offs exist (whole farm model analysis)? </li> </ol> NOTE: In the case of the 2018 Implementation in Cauca, only questions 1 and 2 where addressed (The “Calculator Modules” of the survey allowing to address farm level CSA effects on performance were not applied). Universe: At the time of data collection, all survey participants resided within 7 communities in Cauca: "San Antonio", "La Mota", "Los Tendidos", "Las Mercedes", "Los Cerrillos", “El Danubio", or "San Rafael". Los Cerrillos and Las Mercedes is where most of the CCAFS PAR activities were focused until then. The initial sample target included the 140 households covered in the initial CCAFS Baseline (HBS) and the households directly involved in CCAFS activities. Implementation was carried out by locally trained enumerators using the Geofarmer Smart Monitoring App for data collection. A total of 262 individuals were sampled: 108 adult females, 113 adult males (age 35 or over), 22 young females and 10 young males (under 35). Two persons were surveyed from each household. 9 individuals had unrecorded birth years.