Predicting potential global and future distributions of the African armyworm (Spodoptera exempta) using species distribution models.
dc.contributor.author | Gómez-Undiano, I | |
dc.contributor.author | Musavi, F | |
dc.contributor.author | Mushobozi, WL | |
dc.contributor.author | David, GM | |
dc.contributor.author | Day, R | |
dc.contributor.author | Early, R | |
dc.contributor.author | Wilson, K | |
dc.date.accessioned | 2022-10-07T08:07:05Z | |
dc.date.issued | 2022-09-28 | |
dc.date.updated | 2022-10-06T15:46:13Z | |
dc.description.abstract | Invasive species have historically been a problem derived from global trade and transport. To aid in the control and management of these species, species distribution models (SDMs) have been used to help predict possible areas of expansion. Our focal organism, the African Armyworm (AAW), has historically been known as an important pest species in Africa, occurring at high larval densities and causing outbreaks that can cause enormous economic damage to staple crops. The goal of this study is to map the AAW's present and potential distribution in three future scenarios for the region, and the potential global distribution if the species were to invade other territories, using 40 years of data on more than 700 larval outbreak reports from Kenya and Tanzania. The present distribution in East Africa coincides with its previously known distribution, as well as other areas of grassland and cropland, which are the host plants for this species. The different future climatic scenarios show broadly similar potential distributions in East Africa to the present day. The predicted global distribution shows areas where the AAW has already been reported, but also shows many potential areas in the Americas where, if transported, environmental conditions are suitable for AAW to thrive and where it could become an invasive species. | en_GB |
dc.description.sponsorship | Biotechnology & Biological Sciences Research Council (BBSRC) | en_GB |
dc.format.extent | 16234- | |
dc.identifier.citation | Vol. 12, No. 1, article 16234 | en_GB |
dc.identifier.doi | https://doi.org/10.1038/s41598-022-19983-y | |
dc.identifier.grantnumber | BB/P023444/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/131139 | |
dc.identifier | ORCID: 0000-0003-4108-5904 (Early, Regan) | |
dc.language.iso | en | en_GB |
dc.publisher | Nature Research | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/36171335 | en_GB |
dc.relation.url | https://datadryad.org/stash/share/t-EgQOweHgcOHQ_paK1ao6PQuRsnjkGCSh63_HD4n00 | en_GB |
dc.relation.url | https://doi.org/10.5061/dryad.sbcc2fr9b | en_GB |
dc.rights | © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | en_GB |
dc.subject | Agroecology | en_GB |
dc.subject | Animal migration | en_GB |
dc.subject | Ecological epidemiology | en_GB |
dc.subject | Ecological modelling | en_GB |
dc.subject | Ecology | en_GB |
dc.subject | Invasive species | en_GB |
dc.title | Predicting potential global and future distributions of the African armyworm (Spodoptera exempta) using species distribution models. | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2022-10-07T08:07:05Z | |
dc.identifier.issn | 2045-2322 | |
exeter.article-number | 16234 | |
exeter.place-of-publication | England | |
dc.description | This is the final version. Available from Nature Research via the DOI in this record. | en_GB |
dc.description | Data availability The datasets generated during and/or analysed during the current study will be available in the DRYAD repository, after the manuscript is accepted [https://datadryad.org/stash/share/t-EgQOweHgcOHQ_paK1ao6PQuRsnjkGCSh63_HD4n00] with DOI number [https://doi.org/10.5061/dryad.sbcc2fr9b]. | en_GB |
dc.identifier.journal | Scientific Reports | en_GB |
dc.relation.ispartof | Sci Rep, 12(1) | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2022-09-07 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2022-09-28 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2022-10-07T08:04:24Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2022-10-07T08:08:01Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2022-09-28 |
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