Replication Data for: Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies

Version 2.5
Mwongera, Caroline; Shikuku, Kelvin Mashisia; Twyman, Jennifer; Läderach, Peter; Ampaire, Edidah; Van Asten, Piet; Twomlowd, Steve; Winowiecki, Leigh, 2016, "Replication Data for: Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies", https://doi.org/10.7910/DVN/HCFDU8, Harvard Dataverse, V2, UNF:6:jZOAo2/XRDd7jArpYw4goA== [fileUNF]
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Description
Approaches that aim to identify and prioritize locally appropriate climate smart agriculture (CSA) technologies will need to address the context-specific multi-dimensional complexity in agricultural systems. The climate smart agriculture rapid appraisal (CSA-RA) is a mixed method approach that draws on participatory bottom-up, qualitative, and quantitative tools to assess the heterogeneity of local contexts, and prioritize context-specific CSA options. This is an imperative if countries are to respond to the COP21 agreement and meet their intended nationally determined contributions (INDCs). The CSA-RA is designed to assess biophysical including climatic, socio-cultural, economic and technological characteristics at the household, farm and community/regional level. The CSA-RA employs gender-disaggregated methods, including gender differences in perceptions of climate change and its impacts. The CSA-RA combines common participatory rural appraisal (PRA) and rapid rural appraisal (RRA) tools into one methodology, that disaggregates the gender dimension, and includes resource mapping; climate calendars; historical calendars; cropping calendars; organization mapping; transect walks; key informant interviews; farmer interviews; and pairwise ranking matrix. The tool collects qualitative and quantitative data from various stakeholders (farmers, local leaders, researchers, local-level agricultural experts, private sector actors, donor organizations, and policy implementers), allowing expansive analysis, triangulation and validation. Application of the CSA-RA in Tanzania and Uganda reveals heterogeneity across the sites in terms of vulnerability, constraints and CSA priorities among different social groups (gender) and agro-ecological zones. Thus, the CSA-RA allows stakeholders to simultaneously take into account biophysical and socio-economic aspects to target and implement CSA.
Subject Earth and Environmental Sciences; Agricultural Sciences
Keyword Climate-smart agriculture, Agriculture, Prioritization, Context-specific, Participatory approaches, Mixed-method approach, Sex-disaggregated data, Africa, Decision and Policy Analysis - DAPA
Related Publication Mwongera, Caroline; Shikuku, Kelvin M.; Twyman, Jennifer; Läderach, Peter; Ampaire, Edidah; Van Asten, Piet; Twomlowd, Steve; Winowiecki, Leigh A.. 2016. Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies. Agricultural Systems . 12 p.doi: 10.1016/j.agsy.2016.05.009
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2. CSA-RA Gross Margin Analysis Codebook.xls
MS Excel Spreadsheet - 39.5 KB
Published Jul 22, 2016
96 Downloads
MD5: 6e6bc05bcf223c329a81135a428e7433
Codebook for Farmer interviews for Gross margin analysis
Documentation
4. CSARA Gulu Table 5 Codebook.xls
MS Excel Spreadsheet - 10.0 KB
Published Jun 30, 2016
91 Downloads
MD5: c3e3d3ad752221702bcd81316b0716e4
Documentation
6. CSARA SAGCOT Table 6 Codebook.xls
MS Excel Spreadsheet - 32.0 KB
Published Jun 30, 2016
89 Downloads
MD5: df87a6b14e3f505b538215bb6e420e54
Documentation
1. CSA-RA Gross Margin Analysis Data.tab
Tabular Data - 5.5 KB
Published Jul 22, 2016
123 Downloads
73 Variables, 24 Observations UNF:6:I145GJSN6tTRqIpGRImhWw==
Farmer interviews for Gross margin analysis
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3. CSARA Gulu Table 5 Data.tab
Tabular Data - 92.8 KB
Published Jun 30, 2016
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24 Variables, 839 Observations UNF:6:5C/Pnr/ZPsXNg7cCBvAiUg==
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5. CSARA SAGCOT Table 6 Data.tab
Tabular Data - 66.4 KB
Published Jun 30, 2016
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32 Variables, 494 Observations UNF:6:XMyk7tR51K5+WHROF1R6Rg==
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7. CSARA dofile ttests.do
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Published Jun 30, 2016
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MD5: ab0789c30251cc6ac8fa724e5c5ccda9
CSARA STATA do file
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