Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , |
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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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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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