Publication
Prediction of the potential distribution of Drosophila suzukii on Madeira Island using the maximum entropy modeling.
| dc.contributor.author | Macedo, Fabrício Lopes De | |
| dc.contributor.author | Ragonezi, Carla | |
| dc.contributor.author | Reis, Fábio | |
| dc.contributor.author | Freitas, José G.R. de | |
| dc.contributor.author | Lopes, David João Horta | |
| dc.contributor.author | AGUIAR, ANTÓNIO | |
| dc.contributor.author | Cravo, Délia | |
| dc.contributor.author | Carvalho, Miguel A. A. Pinheiro | |
| dc.date.accessioned | 2024-01-12T14:34:30Z | |
| dc.date.available | 2024-01-12T14:34:30Z | |
| dc.date.issued | 2023-09-06 | |
| dc.description.abstract | 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. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Macedo, F. L., Ragonezi, C., Reis, F., Freitas, J. G. R., Lopes, D. H., Aguiar, A. M. F., Cravo, D., & Carvalho, M. A. A. P. (2023). Prediction of the potential distribution of Drosophila suzukii on Madeira Island using the maximum entropy modeling. “Agriculture”, 13, 1764. DOI:10.3390/ agriculture13091764 (IF2021 3,408; Q1 Agronomy) | pt_PT |
| dc.identifier.doi | 10.3390/ agriculture13091764 | pt_PT |
| dc.identifier.eissn | 2077-0472 | |
| dc.identifier.uri | http://hdl.handle.net/10400.3/6836 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI | pt_PT |
| dc.relation | M1420-01-0145-FEDER-000011-CASBio | pt_PT |
| dc.relation | INTERREG-MAC2014-2020 | pt_PT |
| dc.relation | MAC2/1.1a/231-CUARENTAGRI | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Habitat | pt_PT |
| dc.subject | Maximum Entropy | pt_PT |
| dc.subject | Ecological Niche Modeling | pt_PT |
| dc.subject | Modeling | pt_PT |
| dc.subject | Machine Learning | pt_PT |
| dc.title | Prediction of the potential distribution of Drosophila suzukii on Madeira Island using the maximum entropy modeling. | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Switzerland | pt_PT |
| oaire.citation.endPage | 10 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | Agriculture | pt_PT |
| oaire.citation.volume | 13 | pt_PT |
| person.familyName | Macedo | |
| person.familyName | Ragonezi Gomes Lopes | |
| person.familyName | Reis | |
| person.familyName | Horta Lopes | |
| person.familyName | FRANQUINHO AGUIAR | |
| person.familyName | Cravo | |
| person.givenName | Fabrício Lopes de | |
| person.givenName | Carla Aparecida | |
| person.givenName | Fábio | |
| person.givenName | David | |
| person.givenName | ANTÓNIO MIGUEL | |
| person.givenName | Délia | |
| person.identifier | 2439118 | |
| person.identifier | https://scholar.google.com/citations?hl=pt-PT&view_op=list_works&gmla=AJsN-F7GtjApviXUzeFpT82dvfKJflJy2nY6p12MrVk23i7IWBwUMmQqdf9If4xQKJqDAKvnPJ-s7qMllFNbC7i9BWdWHX5gg0xDJ8Ej_ZVaKD7ZyN6Sc28&user=aqaaKk8AAAAJ | |
| person.identifier.ciencia-id | BD1F-4778-60D1 | |
| person.identifier.ciencia-id | FC12-D3F0-EF3D | |
| person.identifier.ciencia-id | FB1E-8C78-8F49 | |
| person.identifier.ciencia-id | 4A11-1CA3-AF88 | |
| person.identifier.ciencia-id | 1A12-DBB6-6FB8 | |
| person.identifier.orcid | 0000-0002-8025-6422 | |
| person.identifier.orcid | 0000-0002-1822-5473 | |
| person.identifier.orcid | 0000-0002-7525-1344 | |
| person.identifier.orcid | 0000-0002-3057-5871 | |
| person.identifier.orcid | 0000-0002-9572-2967 | |
| person.identifier.orcid | 0000-0003-1804-9665 | |
| person.identifier.scopus-author-id | 39861432500 | |
| person.identifier.scopus-author-id | 36460033800 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 432bf457-4608-4b05-944e-ec70d53ed730 | |
| relation.isAuthorOfPublication | cedca44a-3f7b-4182-b0b5-be1274c541c3 | |
| relation.isAuthorOfPublication | 58752704-f31a-41d4-a564-0fa394c005d3 | |
| relation.isAuthorOfPublication | b06dd5fc-5dba-46db-abb1-fcd4fd240681 | |
| relation.isAuthorOfPublication | 0f83ce29-0247-45e5-a319-d867a89f82a4 | |
| relation.isAuthorOfPublication | 318b0f39-d33f-4816-b193-b98d09660a4e | |
| relation.isAuthorOfPublication.latestForDiscovery | b06dd5fc-5dba-46db-abb1-fcd4fd240681 |