Prediction of the Potential Distribution of <i>Drosophila suzukii</i> 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,
Miguel A. A. Pinheiro de Carvalho
Affiliations
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
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.
