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Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model

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...

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Autores principales: Eitzinger, Anton, Läderach, Peter, Rodriguez, Beatriz, Fisher, Myles, Beebe, Stephen, Sonder, Kai, Schmidt, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054003/
https://www.ncbi.nlm.nih.gov/pubmed/30093820
http://dx.doi.org/10.1007/s11027-015-9696-2
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author Eitzinger, Anton
Läderach, Peter
Rodriguez, Beatriz
Fisher, Myles
Beebe, Stephen
Sonder, Kai
Schmidt, Axel
author_facet Eitzinger, Anton
Läderach, Peter
Rodriguez, Beatriz
Fisher, Myles
Beebe, Stephen
Sonder, Kai
Schmidt, Axel
author_sort Eitzinger, Anton
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11027-015-9696-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-60540032018-08-07 Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model Eitzinger, Anton Läderach, Peter Rodriguez, Beatriz Fisher, Myles Beebe, Stephen Sonder, Kai Schmidt, Axel Mitig Adapt Strateg Glob Chang Original Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11027-015-9696-2) contains supplementary material, which is available to authorized users. Springer Netherlands 2016-02-06 2017 /pmc/articles/PMC6054003/ /pubmed/30093820 http://dx.doi.org/10.1007/s11027-015-9696-2 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Eitzinger, Anton
Läderach, Peter
Rodriguez, Beatriz
Fisher, Myles
Beebe, Stephen
Sonder, Kai
Schmidt, Axel
Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model
title Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model
title_full Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model
title_fullStr Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model
title_full_unstemmed Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model
title_short Assessing high-impact spots of climate change: spatial yield simulations with Decision Support System for Agrotechnology Transfer (DSSAT) model
title_sort assessing high-impact spots of climate change: spatial yield simulations with decision support system for agrotechnology transfer (dssat) model
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054003/
https://www.ncbi.nlm.nih.gov/pubmed/30093820
http://dx.doi.org/10.1007/s11027-015-9696-2
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