A data-driven framework for assessing climatic impact drivers in the context of food security

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Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorPennsylvania State University-
Autor(es): dc.contributorNational Center for Monitoring and Early Warning of Natural Disasters (Cemaden)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorKorea University-
Autor(es): dc.creatorBenso, Marcos Roberto-
Autor(es): dc.creatorSilva, Roberto Fray-
Autor(es): dc.creatorChiquito Gesualdo, Gabriela-
Autor(es): dc.creatorSaraiva, Antonio Mauro-
Autor(es): dc.creatorDelbem, Alexandre Cláudio Botazzo-
Autor(es): dc.creatorMarques, Patricia Angélica Alves-
Autor(es): dc.creatorMarengo, José Antonio-
Autor(es): dc.creatorMendiondo, Eduardo Mario-
Data de aceite: dc.date.accessioned2025-08-21T22:35:03Z-
Data de disponibilização: dc.date.available2025-08-21T22:35:03Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2025-04-10-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5194/nhess-25-1387-2025-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/305587-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/305587-
Descrição: dc.descriptionUnderstanding how physical climate-related hazards affect food production requires transforming climate data into relevant information for regional risk assessment. Data-driven methods can bridge this gap; however, more development must be done to create interpretable models, emphasizing regions lacking data availability. The main objective of this article was to evaluate the impact of climate risks on food security. We adopted the climatic impact driver (CID) approach proposed by Working Group I (WGI) in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC). In this study, we applied the CID framework using a random forest model in a bootstrapping experiment to identify the most influential indices driving crop yield losses. We also used SHapley Additive exPlanations (SHAP) with the random forest model for explanatory analysis, enabling us to pinpoint critical thresholds for these indices-thresholds that, when exceeded, significantly increase the probability of impact. Additionally, we investigated the effects of two CID types (heat and cold and wet and dry) represented by categories of climate extreme indices on crop yields, with a particular focus on maize and soybeans in key agricultural municipalities in Brazil. We found that mean precipitation is a highly relevant CID. However, there is a window in which crops are more vulnerable to a precipitation deficit. In many regions of Brazil, for example, soybeans face an increased risk of yield losses when precipitation falls below 100 mm per month in December, January and February - marking the end of the growing season in those areas. Nevertheless, including climate means remains highly relevant and recommended for studying the impact of climate risk on agriculture. Our findings contribute to a growing body of knowledge critical for informed decision-making, policy development and adaptive strategies in response to climate change and its impact on agriculture.-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionSão Carlos School of Engineering University of São Paulo, SP-
Descrição: dc.descriptionInstitute of Advanced Studies University of São Paulo, SP-
Descrição: dc.descriptionLuiz de Queiroz College of Agriculture University of São Paulo, SP-
Descrição: dc.descriptionInstitute of Mathematics and Computer Sciences University of São Paulo, SP-
Descrição: dc.descriptionDepartment of Geosciences Pennsylvania State University-
Descrição: dc.descriptionNational Center for Monitoring and Early Warning of Natural Disasters (Cemaden), SP-
Descrição: dc.descriptionGraduate Program in Natural Disasters São Paulo State University (UNESP) Cemaden, SP-
Descrição: dc.descriptionGraduate School of International Studies Korea University-
Descrição: dc.descriptionGraduate Program in Natural Disasters São Paulo State University (UNESP) Cemaden, SP-
Descrição: dc.descriptionCAPES: 88888.057913/2013-00-
Formato: dc.format1387-1404-
Idioma: dc.languageen-
Relação: dc.relationNatural Hazards and Earth System Sciences-
???dc.source???: dc.sourceScopus-
Título: dc.titleA data-driven framework for assessing climatic impact drivers in the context of food security-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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