Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling

Detalhes bibliográficos
Autor(a) principal: Macedo, Fabrício Lopes
Data de Publicação: 2023
Outros Autores: Ragonezi, Carla, Reis, Fábio, Freitas, José G. R. de, Lopes, David Horta, Aguiar, António Miguel Franquinho, Cravo, Délia, Carvalho, Miguel A. A. Pinheiro de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.13/5463
Resumo: Drosophila suzukii is one of the main pests that attack soft-skinned fruits and cause significant economic damage worldwide. Madeira Island (Portugal) is already affected by this pest. The present work aimed to investigate the potential distribution of D. suzukii on Madeira Island to better understand the limits of its geographical distribution on the island using the Maximum Entropy modeling (MaxEnt). The resultant model provided by MaxEnt was rated as regular discrimination with the area under the curve (AUC, 0.7–0.8). Upon scrutinizing the environmental variables with the greatest impact on the distribution of D. suzukii, altitude emerged as the dominant contributor, with the highest percentage (71.2%). Additionally, elevations ranging from 0 to 500 m were identified as appropriate for the species distribution. With the results of the model, it becomes possible to understand/predict which locations will be most suitable for the establishment of the analyzed pest and could be further applied not only for D. suzukii but also for other species that hold the potential for substantial economic losses in this insular region.
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spelling Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy ModelingHabitat suitabilityMaximum entropyEcological niche modelInformation systemModeling trainingMachine learningDrosophilidae.Escola Superior de Tecnologias e GestãoFaculdade de Ciências da VidaDrosophila suzukii is one of the main pests that attack soft-skinned fruits and cause significant economic damage worldwide. Madeira Island (Portugal) is already affected by this pest. The present work aimed to investigate the potential distribution of D. suzukii on Madeira Island to better understand the limits of its geographical distribution on the island using the Maximum Entropy modeling (MaxEnt). The resultant model provided by MaxEnt was rated as regular discrimination with the area under the curve (AUC, 0.7–0.8). Upon scrutinizing the environmental variables with the greatest impact on the distribution of D. suzukii, altitude emerged as the dominant contributor, with the highest percentage (71.2%). Additionally, elevations ranging from 0 to 500 m were identified as appropriate for the species distribution. With the results of the model, it becomes possible to understand/predict which locations will be most suitable for the establishment of the analyzed pest and could be further applied not only for D. suzukii but also for other species that hold the potential for substantial economic losses in this insular region.MDPIDigitUMaMacedo, Fabrício LopesRagonezi, CarlaReis, FábioFreitas, José G. R. deLopes, David HortaAguiar, António Miguel FranquinhoCravo, DéliaCarvalho, Miguel A. A. Pinheiro de2024-01-08T13:45:11Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.13/5463engMacedo, F.L.; Ragonezi, C.; Reis, F.; de Freitas, J.G.R.; Lopes, D.H.; Aguiar, A.M.F.; Cravo, D.; Carvalho, M.A.A.P.d. Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling. Agriculture 2023, 13, 1764. https://doi.org/10.3390/ agriculture1309176410.3390/agriculture13091764info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-14T07:14:11Zoai:digituma.uma.pt:10400.13/5463Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:44:27.185459Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
title Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
spellingShingle Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
Macedo, Fabrício Lopes
Habitat suitability
Maximum entropy
Ecological niche model
Information system
Modeling training
Machine learning
Drosophilidae
.
Escola Superior de Tecnologias e Gestão
Faculdade de Ciências da Vida
title_short Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
title_full Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
title_fullStr Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
title_full_unstemmed Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
title_sort Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
author Macedo, Fabrício Lopes
author_facet Macedo, Fabrício Lopes
Ragonezi, Carla
Reis, Fábio
Freitas, José G. R. de
Lopes, David Horta
Aguiar, António Miguel Franquinho
Cravo, Délia
Carvalho, Miguel A. A. Pinheiro de
author_role author
author2 Ragonezi, Carla
Reis, Fábio
Freitas, José G. R. de
Lopes, David Horta
Aguiar, António Miguel Franquinho
Cravo, Délia
Carvalho, Miguel A. A. Pinheiro de
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv DigitUMa
dc.contributor.author.fl_str_mv Macedo, Fabrício Lopes
Ragonezi, Carla
Reis, Fábio
Freitas, José G. R. de
Lopes, David Horta
Aguiar, António Miguel Franquinho
Cravo, Délia
Carvalho, Miguel A. A. Pinheiro de
dc.subject.por.fl_str_mv Habitat suitability
Maximum entropy
Ecological niche model
Information system
Modeling training
Machine learning
Drosophilidae
.
Escola Superior de Tecnologias e Gestão
Faculdade de Ciências da Vida
topic Habitat suitability
Maximum entropy
Ecological niche model
Information system
Modeling training
Machine learning
Drosophilidae
.
Escola Superior de Tecnologias e Gestão
Faculdade de Ciências da Vida
description Drosophila suzukii is one of the main pests that attack soft-skinned fruits and cause significant economic damage worldwide. Madeira Island (Portugal) is already affected by this pest. The present work aimed to investigate the potential distribution of D. suzukii on Madeira Island to better understand the limits of its geographical distribution on the island using the Maximum Entropy modeling (MaxEnt). The resultant model provided by MaxEnt was rated as regular discrimination with the area under the curve (AUC, 0.7–0.8). Upon scrutinizing the environmental variables with the greatest impact on the distribution of D. suzukii, altitude emerged as the dominant contributor, with the highest percentage (71.2%). Additionally, elevations ranging from 0 to 500 m were identified as appropriate for the species distribution. With the results of the model, it becomes possible to understand/predict which locations will be most suitable for the establishment of the analyzed pest and could be further applied not only for D. suzukii but also for other species that hold the potential for substantial economic losses in this insular region.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
2024-01-08T13:45:11Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.13/5463
url http://hdl.handle.net/10400.13/5463
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Macedo, F.L.; Ragonezi, C.; Reis, F.; de Freitas, J.G.R.; Lopes, D.H.; Aguiar, A.M.F.; Cravo, D.; Carvalho, M.A.A.P.d. Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling. Agriculture 2023, 13, 1764. https://doi.org/10.3390/ agriculture13091764
10.3390/agriculture13091764
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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