10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

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

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references40

          • Record: found
          • Abstract: not found
          • Article: not found

          The Analysis of Spatial Association by Use of Distance Statistics

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Prioritizing climate change adaptation needs for food security in 2030.

            Investments aimed at improving agricultural adaptation to climate change inevitably favor some crops and regions over others. An analysis of climate risks for crops in 12 food-insecure regions was conducted to identify adaptation priorities, based on statistical crop models and climate projections for 2030 from 20 general circulation models. Results indicate South Asia and Southern Africa as two regions that, without sufficient adaptation measures, will likely suffer negative impacts on several crops that are important to large food-insecure human populations. We also find that uncertainties vary widely by crop, and therefore priorities will depend on the risk attitudes of investment institutions.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The DSSAT cropping system model

                Bookmark

                Author and article information

                Contributors
                +57 2 4450000 , a.eitzinger@cgiar.org
                Journal
                Mitig Adapt Strateg Glob Chang
                Mitig Adapt Strateg Glob Chang
                Mitigation and Adaptation Strategies for Global Change
                Springer Netherlands (Dordrecht )
                1381-2386
                1573-1596
                6 February 2016
                6 February 2016
                2017
                : 22
                : 5
                : 743-760
                Affiliations
                [1 ]ISNI 0000 0001 0943 556X, GRID grid.418348.2, CIAT International Center for Tropical Agriculture, ; A.A. 6713 Cali, Colombia
                [2 ]CIAT International Center for Tropical Agriculture, Managua, Nicaragua
                [3 ]ISNI 0000 0001 2289 885X, GRID grid.433436.5, CIMMYT International Maize and Wheat Improvement Center, ; Mexico DF, Mexico
                [4 ]CRS Catholic Relief Services, Lima, Peru
                Article
                9696
                10.1007/s11027-015-9696-2
                6054003
                2b210ccc-033a-468a-aca1-5e4c39f386f7
                © 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.

                History
                : 10 December 2014
                : 16 December 2015
                Categories
                Original Article
                Custom metadata
                © Springer Science+Business Media Dordrecht 2017

                climate change,dssat drybean submodel,high-impact spots,simulation modeling,central america

                Comments

                Comment on this article