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Replication Data for: Climate change adaptation of coffee production in space and time

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

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Title Replication Data for: Climate change adaptation of coffee production in space and time
 
Identifier https://doi.org/10.7910/DVN/TSUPE1
 
Creator Läderach, Peter
Ramirez Villegas, Julian
Navarro Racines, Carlos E.
Zelaya Martinez, Carlos
Martinez Valle, Armando
Jarvis, Andy
 
Publisher Harvard Dataverse
 
Description Coffee is grown in more than 60 tropical countries on over 11 million ha by an estimated 25 million farmers, most of whom are smallholders. Several regional studies demonstrate the climate sensitivity of coffee (Coffea arabica) and the likely impact of climate change on coffee suitability, yield, increased pest and disease pressure and farmers’ livelihoods. The objectives of this paper are (i) to quantify the impact of progressive climate change to grow coffee and to produce high quality coffee in Nicaragua and (ii) to develop an adaptation framework across time and space to guide adaptation planning. We used coffee location and cup quality data from Nicaragua in combination with the Maxent and CaNaSTA crop suitability models, the WorldClim historical data and the CMIP3 global circulation models to predict the likely impact of climate change on coffee suitability and quality. We distinguished four different impact scenarios: Very high (coffee disappears), high (large negative changes), medium (little negative changes) and increase (positive changes) in climate suitability. During the Nicaraguan coffee roundtable, most promising adaptation strategies were identified, which we then used to develop a two-dimensional adaptation framework for coffee in time and space. Our analysis indicates that incremental adaptation may occur over short-term horizons at lower altitudes, whereas the same areas may undergo transformative adaptation in the longer term. At higher elevations incremental adaptation may be needed in the long term. The same principle and framework is applicable across coffee growing regions around the world.
 
Subject Agricultural Sciences
Earth and Environmental Sciences
Climate change
Adaptation
Spatial modelling
Nicaragua
Incremental adaptation
Transformative adaptation
Latin America and the Caribbean
Decision and Policy Analysis - DAPA
 
Language English
 
Contributor Lenis Lopez, Andres
 
Type Geospatial Data
Climate Data