Record Details

2018- CSA Monitoring: Santa Rita Climate Smart-Village (Honduras)

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title 2018- CSA Monitoring: Santa Rita Climate Smart-Village (Honduras)
 
Identifier https://doi.org/10.7910/DVN/INK5IM
 
Creator Bonilla-Findji, Osana
Eitzinger, Anton
Andrieu, Nadine
Jarvis, Andy
Martínez-Barón, Deissy
Suchini, José Gabriel
 
Publisher Harvard Dataverse
 
Description This dataset contains the files produced in the implementation of the “Integrated Monitoring Framework for Climate-Smart Agriculture” in the Santa Rita Climate Smart Village (Honduras) in April 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, in selected sites).
    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:

  1. Within each CSV community, who adopts which CSA technologies and practices and what are their motivations, enabling/constraining factors?

  2. 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)?

  3. How does CSA perform at farm level, and what synergies and trade-offs exist (whole farm model analysis)?


 
Subject Agricultural Sciences
Earth and Environmental Sciences
Monitoring
Climate Smart Agriculture
Households
Livelihoods
Adaptation
Food Security
Climate Shocks
Latin America and the Caribbean
Decision and Policy Analysis - DAPA
 
Language English
Spanish, Castilian
 
Date 2019-12-10
 
Contributor Ortega, Angelly
 
Type Survey data
Socio-economic Data
Geographic Data
Environmental Data
Capacity Building