Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean

These data correspond to the results of the agroclimatic zones of cocoa for the Central America and the Caribbean regions and per country. The data make reference to the ideal zones for cocoa production in three different periods of time (baseline 1970-2000, 2020 - 2049, 2040 - 2069), which allows u...

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Autores principales: Bunn, Christian, Lundy, Mark M., Castro-Llanos, Fabio Alexander
Formato: Conjunto de datos
Lenguaje:Inglés
Publicado: International Center for Tropical Agriculture 2019
Materias:
Acceso en línea:https://hdl.handle.net/10568/101363
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author Bunn, Christian
Lundy, Mark M.
Castro-Llanos, Fabio Alexander
author_browse Bunn, Christian
Castro-Llanos, Fabio Alexander
Lundy, Mark M.
author_facet Bunn, Christian
Lundy, Mark M.
Castro-Llanos, Fabio Alexander
author_sort Bunn, Christian
collection Repository of Agricultural Research Outputs (CGSpace)
description These data correspond to the results of the agroclimatic zones of cocoa for the Central America and the Caribbean regions and per country. The data make reference to the ideal zones for cocoa production in three different periods of time (baseline 1970-2000, 2020 - 2049, 2040 - 2069), which allows us to know what would be the impact of climate change for the crop, and therefore, establish a first route for prospective planning in the different countries under study and the region. This analysis was done with a machine learning approach: Random Forest model, which took into account climatic variables, such as precipitation, temperature and evapotranspiration. The model was trained with presence data for construction.
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spelling CGSpace1013632025-03-13T09:43:57Z Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean Bunn, Christian Lundy, Mark M. Castro-Llanos, Fabio Alexander climate change cocoa food security agriculture adaptation These data correspond to the results of the agroclimatic zones of cocoa for the Central America and the Caribbean regions and per country. The data make reference to the ideal zones for cocoa production in three different periods of time (baseline 1970-2000, 2020 - 2049, 2040 - 2069), which allows us to know what would be the impact of climate change for the crop, and therefore, establish a first route for prospective planning in the different countries under study and the region. This analysis was done with a machine learning approach: Random Forest model, which took into account climatic variables, such as precipitation, temperature and evapotranspiration. The model was trained with presence data for construction. 2019-05-20 2019-05-23T18:24:54Z 2019-05-23T18:24:54Z Dataset https://hdl.handle.net/10568/101363 en Open Access International Center for Tropical Agriculture Bunn, Christian; Lundy, Mark; Castro-Llanos, Fabio, 2019, "Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean", https://doi.org/10.7910/DVN/QUKZTO, Harvard Dataverse, V2
spellingShingle climate change
cocoa
food security
agriculture
adaptation
Bunn, Christian
Lundy, Mark M.
Castro-Llanos, Fabio Alexander
Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean
title Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean
title_full Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean
title_fullStr Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean
title_full_unstemmed Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean
title_short Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean
title_sort replication data for the impact of climate change on cacao production in central america and the caribbean
topic climate change
cocoa
food security
agriculture
adaptation
url https://hdl.handle.net/10568/101363
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