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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
08/02/2023 |
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Data da última atualização: |
10/02/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SILVA, L. A. P. da; SOUZA, C. M. P. de; SILVA, C. R. da; BOLFE, E. L.; ROCHA, A. M. |
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Afiliação: |
LUCAS AUGUSTO PEREIRA DA SILVA, UNIVERSIDADE FEDERAL DE UBERLÂNDIA; CRISTIANO MARCELO PEREIRA DE SOUZA, UNIVERSIDADE ESTADUAL DE MONTES CLAROS; CLAUDIONOR RIBEIRO DA SILVA, UNIVERSIDADE FEDERAL DE UBERLÂNDIA; EDSON LUIS BOLFE, CNPTIA, UNIVERSIDADE ESTADUAL DE CAMPINAS; ANDRE MEDEIROS ROCHA, UNIVERSIDADE DE SÃO PAULO. |
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Título: |
Projection of climate change impacts on net primary productivity of the legal Amazon - Brazil. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Caderno de Geografia, v. 33, n. 72, p. 110-130, jan./mar. 2023. |
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DOI: |
10.5752/p.2318-2962.2023v33n.72p.110 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract. The Amazon Rainforest is one of the main carbon sinks (CO2) on Earth. However, recently, owing to anthropogenic activities and climate change, it has lost its stability in CO2 absorption. Therefore, understanding the dynamics of future climate change scenarios is essential. We assessed the influence of future climate change scenarios on NPP (biomass) levels in the Amazon Forest using ML models. The tested models were Bayesian, linear, and random forest models. The current scenario was evaluated using 19 bioclimatic covariates (WorldClim dataset). Future scenarios were based on RCPs 2.6 and 8.5 (based on the MIROC5 and HadGEM2-ES models). Random Forest had the best performance statistics (R² = 0.71 in training and 0.68 in the holdout-test). These climate change scenarios imply an increase in the average NPP for the Amazon forest, especially with the greater intensification in RCP 2.6 (10 and 12 % for the HadGEM2-ES and MIROC5 models, respectively). Forests (evergreen broadleaf forest areas) will have a greater carbon fixation capacity. In general, the Amazon forest will have an increased carbon fixation capacity by the end of the century. |
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Palavras-Chave: |
Amazon Forest; Aprendizado de máquina; Carbon sink; Floresta aleatória; Floresta Amazônica; Machine Learning; Mudanças climáticas; Random Forest; Sumidouro de carbono. |
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Thesaurus Nal: |
Climate change. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1151595/1/AP-Projection-climate-2023.pdf
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Marc: |
LEADER 02097naa a2200301 a 4500
001 2151595
005 2023-02-10
008 2023 bl uuuu u00u1 u #d
024 7 $a10.5752/p.2318-2962.2023v33n.72p.110$2DOI
100 1 $aSILVA, L. A. P. da
245 $aProjection of climate change impacts on net primary productivity of the legal Amazon - Brazil.$h[electronic resource]
260 $c2023
520 $aAbstract. The Amazon Rainforest is one of the main carbon sinks (CO2) on Earth. However, recently, owing to anthropogenic activities and climate change, it has lost its stability in CO2 absorption. Therefore, understanding the dynamics of future climate change scenarios is essential. We assessed the influence of future climate change scenarios on NPP (biomass) levels in the Amazon Forest using ML models. The tested models were Bayesian, linear, and random forest models. The current scenario was evaluated using 19 bioclimatic covariates (WorldClim dataset). Future scenarios were based on RCPs 2.6 and 8.5 (based on the MIROC5 and HadGEM2-ES models). Random Forest had the best performance statistics (R² = 0.71 in training and 0.68 in the holdout-test). These climate change scenarios imply an increase in the average NPP for the Amazon forest, especially with the greater intensification in RCP 2.6 (10 and 12 % for the HadGEM2-ES and MIROC5 models, respectively). Forests (evergreen broadleaf forest areas) will have a greater carbon fixation capacity. In general, the Amazon forest will have an increased carbon fixation capacity by the end of the century.
650 $aClimate change
653 $aAmazon Forest
653 $aAprendizado de máquina
653 $aCarbon sink
653 $aFloresta aleatória
653 $aFloresta Amazônica
653 $aMachine Learning
653 $aMudanças climáticas
653 $aRandom Forest
653 $aSumidouro de carbono
700 1 $aSOUZA, C. M. P. de
700 1 $aSILVA, C. R. da
700 1 $aBOLFE, E. L.
700 1 $aROCHA, A. M.
773 $tCaderno de Geografia$gv. 33, n. 72, p. 110-130, jan./mar. 2023.
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Embrapa Agricultura Digital (CNPTIA) |
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