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Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil

The impacts of global climate change have been a worldwide concern for several research areas, including those dealing with resources essential to human well being, such as agriculture, which directly impact economic activities and food security. Here we evaluate the relative effect of climate (as i...

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Autores principales: Caetano, Jordana Moura, Tessarolo, Geiziane, de Oliveira, Guilherme, Souza, Kelly da Silva e, Diniz-Filho, José Alexandre Felizola, Nabout, João Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5790230/
https://www.ncbi.nlm.nih.gov/pubmed/29381755
http://dx.doi.org/10.1371/journal.pone.0191273
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author Caetano, Jordana Moura
Tessarolo, Geiziane
de Oliveira, Guilherme
Souza, Kelly da Silva e
Diniz-Filho, José Alexandre Felizola
Nabout, João Carlos
author_facet Caetano, Jordana Moura
Tessarolo, Geiziane
de Oliveira, Guilherme
Souza, Kelly da Silva e
Diniz-Filho, José Alexandre Felizola
Nabout, João Carlos
author_sort Caetano, Jordana Moura
collection PubMed
description The impacts of global climate change have been a worldwide concern for several research areas, including those dealing with resources essential to human well being, such as agriculture, which directly impact economic activities and food security. Here we evaluate the relative effect of climate (as indicated by the Ecological Niche Model—ENM) and agricultural technology on actual soybean productivity in Brazilian municipalities and estimate the future geographic distribution of soybeans using a novel statistical approach allowing the evaluation of partial coefficients in a non-stationary (Geographically Weighted Regression; GWR) model. We found that technology was more important than climate in explaining soybean productivity in Brazil. However, some municipalities are more dependent on environmental suitability (mainly in Southern Brazil). The future environmental suitability for soybean cultivation tends to decrease by up 50% in the central region of Brazil. Meanwhile, southern-most Brazil will have more favourable conditions, with an increase of ca. 25% in environmental suitability. Considering that opening new areas for cultivation can degrade environmental quality, we suggest that, in the face of climate change impacts on soybean cultivation, the Brazilian government and producers must invest in breeding programmes and more general ecosystem-based strategies for adaptation to climate change, including the development of varieties tolerant to climate stress, and strategies to increase productivity and reduce costs (social and environmental).
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spelling pubmed-57902302018-02-13 Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil Caetano, Jordana Moura Tessarolo, Geiziane de Oliveira, Guilherme Souza, Kelly da Silva e Diniz-Filho, José Alexandre Felizola Nabout, João Carlos PLoS One Research Article The impacts of global climate change have been a worldwide concern for several research areas, including those dealing with resources essential to human well being, such as agriculture, which directly impact economic activities and food security. Here we evaluate the relative effect of climate (as indicated by the Ecological Niche Model—ENM) and agricultural technology on actual soybean productivity in Brazilian municipalities and estimate the future geographic distribution of soybeans using a novel statistical approach allowing the evaluation of partial coefficients in a non-stationary (Geographically Weighted Regression; GWR) model. We found that technology was more important than climate in explaining soybean productivity in Brazil. However, some municipalities are more dependent on environmental suitability (mainly in Southern Brazil). The future environmental suitability for soybean cultivation tends to decrease by up 50% in the central region of Brazil. Meanwhile, southern-most Brazil will have more favourable conditions, with an increase of ca. 25% in environmental suitability. Considering that opening new areas for cultivation can degrade environmental quality, we suggest that, in the face of climate change impacts on soybean cultivation, the Brazilian government and producers must invest in breeding programmes and more general ecosystem-based strategies for adaptation to climate change, including the development of varieties tolerant to climate stress, and strategies to increase productivity and reduce costs (social and environmental). Public Library of Science 2018-01-30 /pmc/articles/PMC5790230/ /pubmed/29381755 http://dx.doi.org/10.1371/journal.pone.0191273 Text en © 2018 Caetano et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Caetano, Jordana Moura
Tessarolo, Geiziane
de Oliveira, Guilherme
Souza, Kelly da Silva e
Diniz-Filho, José Alexandre Felizola
Nabout, João Carlos
Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil
title Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil
title_full Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil
title_fullStr Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil
title_full_unstemmed Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil
title_short Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil
title_sort geographical patterns in climate and agricultural technology drive soybean productivity in brazil
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5790230/
https://www.ncbi.nlm.nih.gov/pubmed/29381755
http://dx.doi.org/10.1371/journal.pone.0191273
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