Article thumbnail

Climate change adaptation of coffee production in space and time

By Peter Läderach, Julián Ramírez Villegas, Carlos E. Navarro-Racines, Carlos Zelaya, Armando Isaac Martínez Valle and Andy Jarvis

Abstract

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.Peer Revie

Topics: climate change, coffee, adaptation, simulation models, café, cambio climático, adaptación, modelos de simulación
Publisher: 'Springer Fachmedien Wiesbaden GmbH'
Year: 2016
DOI identifier: 10.1007/s10584-016-1788-9
OAI identifier: oai:cgspace.cgiar.org:10568/77563
Provided by: CGSpace
Journal:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • https://hdl.handle.net/10568/7... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.