Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/24042
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dc.contributor.authorCooper-Bohannon, Rachael-
dc.contributor.authorRebelo, Hugo-
dc.contributor.authorJones, Gareth-
dc.contributor.authorCotterill, Fenton-
dc.contributor.authorMonadjem, Ara-
dc.contributor.authorSchoeman, M Corrie-
dc.contributor.authorTaylor, Peter-
dc.contributor.authorPark, Kirsty-
dc.date.accessioned2017-02-02T22:38:07Z-
dc.date.available2017-02-02T22:38:07Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/1893/24042-
dc.description.abstractSpecies distribution models were used to predict bat species richness across southern Africa and drivers of these spatial patterns. We also identified species richness within each biotic zone and the distributions of species considered of high conservation priority. We used this information to highlight conservation priorities for bats in southern Africa (defined here as between the latitudes of 8°S, slightly north of Zambia, to the southern tip of Africa 34°S, an area of approximately 9,781,840 km2). We used Maximum entropy modelling (Maxent) to model habitat suitability for 58 bat species in order to determine the key eco-geographical variables influencing their distributions. The potential distribution of each bat species was affected by different eco-geographic variables but in general, water availability (both temporary and permanent), seasonal precipitation, vegetation and karst (caves/limestone) areas were the most important factors. The highest levels of species richness were found mainly in the eastern dry savanna area and some areas of wet savanna. Of the species considered to be of high priority due to a combination of restricted distributions or niches and/or endemism (7 fruit bats, 23 cave-dwellers, 18 endemic and near-endemic, 14 niche-restricted and 15 range-restricted), nine species were considered to be at most risk. We found that range-restricted species were commonly found in areas with low species richness; therefore, conservation decisions need to take into account not only species richness but also species considered to be particularly vulnerable across the biogeographical area of interest.en_UK
dc.language.isoen-
dc.publisherAssociazione Teriologica Italiana-
dc.relationCooper-Bohannon R, Rebelo H, Jones G, Cotterill F, Monadjem A, Schoeman MC, Taylor P & Park K (2016) Predicting bat distributions and diversity hotspots in Southern Africa, Hystrix, the Italian Journal of Mammalogy, 27 (1).-
dc.rightsCopyright (c) 2016 Hystrix, the Italian Journal of Mammalogy This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.-
dc.subjectChiropteraen_UK
dc.subjectbiogeographical strataen_UK
dc.subjectconservation prioritiesen_UK
dc.subjectMaxenten_UK
dc.subjectspecies distribution modellingen_UK
dc.subjectsouthern Africaen_UK
dc.titlePredicting bat distributions and diversity hotspots in Southern Africaen_UK
dc.typeJournal Articleen_UK
dc.identifier.doihttp://dx.doi.org/10.4404/hystrix-27.1-11722-
dc.citation.jtitleHystrix, the Italian Journal of Mammalogy-
dc.citation.issn0394-1914-
dc.citation.volume27-
dc.citation.issue1-
dc.citation.publicationstatusPublished-
dc.citation.peerreviewedRefereed-
dc.type.statusPublisher version (final published refereed version)-
dc.author.emailk.j.park@stir.ac.uk-
dc.citation.date19/07/2016-
dc.contributor.affiliationUniversity of Stirling-
dc.contributor.affiliationUniversity of Bristol-
dc.contributor.affiliationUniversity of Bristol-
dc.contributor.affiliationUniversity of Stellenbosch, South Africa-
dc.contributor.affiliationUniversity of Pretoria-
dc.contributor.affiliationUniversity of KwaZulu-Natal-
dc.contributor.affiliationUniversity of Venda-
dc.contributor.affiliationBiological and Environmental Sciences-
dc.identifier.isi000386517200007-
Appears in Collections:Biological and Environmental Sciences Journal Articles

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