2018- CSA Monitoring: Olopa Climate Smart-Village (Guatemala)doi:10.7910/DVN/3GICDIHarvard Dataverse2019-12-113Bonilla-Findji, Osana; Eitzinger, Anton; Andrieu, Nadine; Jarvis, Andy; Martínez, Deissy, 2019, "2018- CSA Monitoring: Olopa Climate Smart-Village (Guatemala)", https://doi.org/10.7910/DVN/3GICDI, Harvard Dataverse, V3, UNF:6:V7iOPIQdiuFL0BnX0BpmZg== [fileUNF]2018- CSA Monitoring: Olopa Climate Smart-Village (Guatemala)doi:10.7910/DVN/3GICDIBonilla-Findji, OsanaEitzinger, AntonAndrieu, NadineJarvis, AndyMartínez, DeissyInternational Center for Tropical Agriculture (CIAT), CGIAR Research Program on Climate Change, Agriculture and Food Security (Flagship 2)2019-12-10G135G151Harvard DataverseClimate Smart Technologies and PracticesMartinez Salgado, Jesus DavidBonilla-Findji, OsanaOrtega, Angelly2019-12-092019-12-10Agricultural SciencesEarth and Environmental SciencesMonitoringClimate Smart AgricultureHouseholdsLivelihoodsAdaptationFood SecurityClimate ShocksLatin America and the CaribbeanDecision and Policy Analysis - DAPAMonitoringClimate Smart AgricultureThis dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Olopa Climate Smart Village (Guatemala) in April 2018. <br> 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 type= disc> Adoption of CSA practices and technologies, as well as access to climate information services and <li type= disc> Their related impacts at household level (and farm level, in selected sites). <ul> This framework proposes standard Descriptive Indicators to track changes in: <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. </ul> </ul> This integrated framework is associated with a cost-effective data collection App (Geofarmer) that allowed capturing information in almost real-time. <br> 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. <br> 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 labor)?</li> <li>How does CSA perform at farm level, and what synergies and trade-offs exist (whole farm model analysis)?</li> </ol>2017-04-012018-05-012018-04-012018-05-01Survey dataSocio-economic DataGeographic DataEnvironmental DataCapacity BuildingUniverse: At the time of data collection, all survey participants resided within 7 communities in Olopa Village, Guatemala ("Tituque", " Valle nuevo", " El Guayabo Tercer Caserio", " Tuticopote Abajo Caserio El Bendito", " Tuticopote Abajo Caserio El Bendito", " Nochan", or " La Prensa"). Implementation was carried out by locally trained enumerators using the Geofarmer Smart Monitoring App for data collection. The initial sample target was : 140 households, including the ones covered in the initial CCAFS Baseline (HBS). A total of 279 individuals were sampled: 93 adult females, 75 adult males (age 35 or above) 59 young females and 47 young males (under age of 35). Two adults were surveyed from each household. 5 individuals had unrecorded birth years.To download the documents, please contact: Bonilla-Findji Osana Email: o.bonilla@cgiar.org<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a><ul> <li type= disc> 2018_LAM_GTM-OLO_Cleaned_Data_M0-M5 <li type= disc> 2018_LAM_GTM-OLO_Calculator_Data <li type= disc> 2018_LAM_GTM-OLO_Additional information </ul> <ol> <li value="1"> 2018_LAM_GTM_OLO_Questionnaire Codified</li> <li value="2">2018_LAM_GTM_OLO_Arbol de Preguntas</li> <li value="3">2018_LAM_GTM_OLO_Glosario practicas ASAC</li> <li value="4">2018_LAM_GTM_OLO_Informed consent</li> <li value="5">2018_LAM_GTM_OLO_Comments on data cleaning</li> <li value="6">Minimum Risk Review Application_ME for IDRC</li> <ul> <li>6.b. IRB Approval Letter_CSA_perf - extension 2019 </ul> <li value="7">2018_LAM_GTM_OLO_Introductory presentation Enumerators training (Spanish)</li> <li value="8"> 2018_LAM_GTM_OLO_CSA Monitoring Results_GeoFarmer links</li> </ol>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.org10568/16426Kristjanson 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.org1. 2018_GTM-OLO_Calculadora Finca.tab2835text/tab-separated-valuesUNF:6:86jWsF3GsWK0IWFRUCetXQ==2. 2018_GTM-OLO_Calculadora Cultivo1.tab2746text/tab-separated-valuesUNF:6:Tkx8rHR1PfsikgQmZjQxFg==2. 2018_GTM-OLO_Calculadora Cultivo2.tab2744text/tab-separated-valuesUNF:6:Kr+/kCDb9jZEULWMitEc6w==2. 2018_GTM-OLO_Calculadora Cultivo3.tab2341text/tab-separated-valuesUNF:6:GHDLIfl19loo0nAjJccucw==2. 2018_GTM-OLO_Calculadora Cultivo4.tab1338text/tab-separated-valuesUNF:6:2VGj13vxFRJZhUDNeNNSSQ==M0_LAM_GTM_OLO_2018_cleaned_anonymized.tab28222text/tab-separated-valuesUNF:6:dNtgYW2kv7MS1ycbJ4P5+Q==M1_LAM_GTM_OLO_2018_cleaned_anonymized.tab28176text/tab-separated-valuesUNF:6:yph+auQh7wkdBxyuQ/gW9A==M2_LAM_GTM_OLO_2018_cleaned_anonymized.tab28138text/tab-separated-valuesUNF:6:AiQQ37a/eGEJfgZhDVzNiw==M3_LAM_GTM_OLO_2018_cleaned_anonymized.tab28036text/tab-separated-valuesUNF:6:65/odHCs2aoEJ09IMwVAEw==M4_LAM_GTM_OLO_2018_cleaned_anonymized.tab28026text/tab-separated-valuesUNF:6:7y+enJnfRa8NqvoLkuQzyA==M5_LAM_GTM_OLO_2018_cleaned_anonymized.tab281102text/tab-separated-valuesUNF:6:sExxugCekIhDlV5tJF60AA==1. 2018_LAM_GTM-OLO_Questionnaire Codified.xlsapplication/vnd.ms-excel2. 2018_LAM_GTM-OLO_CCAFS_Arbol_de_Preguntas_Cuestionario.pdfapplication/pdf3. 2018_LAM_GTM-OLO_ Glosario practicas ASAC.pdfapplication/pdf4. 2018_LAM_GTM-OLO_Consentimiento_Informado.docxapplication/vnd.openxmlformats-officedocument.wordprocessingml.document5. 2018_LAM_GTM-OLO_Comments on data cleaning.xlsapplication/vnd.ms-excel6. Minimum Risk Review Application_ME for IDRC.docapplication/msword6b. IRB Approval Letter_CSA_perf - extension 2019.pdfapplication/pdf7. 2018_LAM_GTM-OLO_Introductory presentation Enumerators training (Spanish).pptxapplication/vnd.openxmlformats-officedocument.presentationml.presentation8. 2018_LAM_GTM_OLO_CSA Monitoring Results_GeoFarmer links.xlsapplication/vnd.ms-excel