Assessing high-impact spots of climate change: spatial yield simulations with decision support system for agrotechnology transfer (DSSAT) model
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Eitzinger, Anton; Läderach, Peter; Rodriguez, Beatriz; Fisher, Myles; Beebe, Stephen; Sonder, Kai; Schmidt, Axel. 2016. Assessing high-impact spots of climate change: spatial yield simulations with decision support system for agrotechnology transfer (DSSAT) model. Mitigation and Adaptation Strategies for Global Change 18 p.
Permanent link to cite or share this item: https://hdl.handle.net/10568/70960
Drybeans (Phaseolus vulgaris L.) are an important subsistence crop in Central America. Future climate change may threaten drybean production and jeopardize smallholder farmers’ food security. We estimated yield changes in drybeans due to changing climate in these countries using downscaled data from global circulation models (GCMs) in El Salvador, Guatemala, Honduras, and Nicaragua. We generated daily weather data, which we used in the Decision Support System for Agrotechnology Transfer (DSSAT) drybean submodel. We compared different cultivars, soils, and fertilizer options in three planting seasons.We analyzed the simulated yields to spatially classify high-impact spots of climate change across the four countries. The results show a corridor of reduced yields from Lake Nicaragua to central Honduras (10–38 % decrease). Yields increased in the Guatemalan highlands, towards the Atlantic coast, and in southern Nicaragua (10–41 % increase). Some farmers will be able to adapt to climate change, but others will have to change crops, which will require external support. Research institutions will need to devise technologies that allow farmers to adapt and provide policy makers with feasible strategies to implement them.
CGIAR Author ORCID iDs
Stephen E Beebehttps://orcid.org/0000-0002-3742-9930