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

Fabrício Lopes Macedo, Carla Ragonezi (), Fábio Reis, José G. R. de Freitas, David Horta Lopes, António Miguel Franquinho Aguiar, Délia Cravo and Miguel A. A. Pinheiro de Carvalho
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Fabrício Lopes Macedo: ISOPlexis Centre Sustainable Agriculture and Food Technology, University of Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
Carla Ragonezi: ISOPlexis Centre Sustainable Agriculture and Food Technology, University of Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
Fábio Reis: ISOPlexis Centre Sustainable Agriculture and Food Technology, University of Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
José G. R. de Freitas: ISOPlexis Centre Sustainable Agriculture and Food Technology, University of Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
David Horta Lopes: CE3C-Centre for Ecology, Evolution and Environmental Changes, Universidade dos Açores Rua Capitão João d’Ávila, Pico da Urze, 9700-042 Angra do Heroísmo, Portugal
António Miguel Franquinho Aguiar: Laboratório de Qualidade Agrícola, Direção Regional de Agricultura, Secretaria Regional da Agricultura e Desenvolvimento Rural, Caminho Municipal dos Caboucos, 61, 9135-372 Camacha, Portugal
Délia Cravo: Laboratório de Qualidade Agrícola, Direção Regional de Agricultura, Secretaria Regional da Agricultura e Desenvolvimento Rural, Caminho Municipal dos Caboucos, 61, 9135-372 Camacha, Portugal
Miguel A. A. Pinheiro de Carvalho: ISOPlexis Centre Sustainable Agriculture and Food Technology, University of Madeira, Campus da Penteada, 9020-105 Funchal, Portugal

Agriculture, 2023, vol. 13, issue 9, 1-10

Abstract: 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.

Keywords: habitat suitability; maximum entropy; ecological niche model; information system; modeling training; machine learning; Drosophilidae (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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