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dc.contributor.authorFreeman, Benedictus
dc.contributor.authorJiménez-Garcia, Daniel
dc.contributor.authorBarca, Benjamin
dc.contributor.authorGrainger, Matthew
dc.date.accessioned2019-09-06T18:17:53Z
dc.date.available2019-09-06T18:17:53Z
dc.date.issued2019-06-10
dc.identifier.citationTY - JOUR AU - Freeman, Benedictus AU - Jiménez-García, Daniel AU - Barca, Benjamin AU - Grainger, Matthew PY - 2019 DA - 2019/06/10 TI - Using remotely sensed and climate data to predict the current and potential future geographic distribution of a bird at multiple scales: the case of Agelastes meleagrides, a western African forest endemic JO - Avian Research SP - 22 VL - 10 IS - 1 AB - Understanding geographic distributions of species is a crucial step in spatial planning for biodiversity conservation, particularly as regards changes in response to global climate change. This information is especially important for species of global conservation concern that are susceptible to the effects of habitat loss and climate change. In this study, we used ecological niche modeling to assess the current and future geographic distributional potential of White-breasted Guineafowl (Agelastes meleagrides) (Vulnerable) across West Africa. SN - 2053-7166 UR - https://doi.org/10.1186/s40657-019-0160-y DO - 10.1186/s40657-019-0160-y ID - Freeman2019 ER -en_US
dc.identifier.urihttp://hdl.handle.net/1808/29544
dc.descriptionThe data analyzed during the current study are available in the following databases: the Global Biodiversity Information Facility (GBIF; https ://www.gbif.org). Data from surveys in Sapo National Park in Liberia and Gola Rainforest National Park in Sierra Leone are available from the corresponding author on reasonable request. Environmental datasets are available at https ://terra .nasa.gov/data and http://www.worldclim.org.en_US
dc.description.abstractBackground:Understanding geographic distributions of species is a crucial step in spatial planning for biodiversity conservation, particularly as regards changes in response to global climate change. This information is especially important for species of global conservation concern that are susceptible to the effects of habitat loss and climate change. In this study, we used ecological niche modeling to assess the current and future geographic distributional potential of White‑breasted Guineafowl (Agelastes meleagrides) (Vulnerable) across West Africa.Methods:We used primary occurrence data obtained from the Global Biodiversity Information Facility and national parks in Liberia and Sierra Leone, and two independent environmental datasets (Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index at 250 m spatial resolution, and Worldclim climate data at 2.5′ spatial resolution for two representative concentration pathway emissions scenarios and 27 general circulation models for 2050) to build ecological niche models in Maxent.Results:From the projections, White‑breasted Guineafowl showed a broader potential distribution across the region compared to the current IUCN range estimate for the species. Suitable areas were concentrated in the Gola rainforests in northwestern Liberia and southeastern Sierra Leone, the Tai‑Sapo corridor in southeastern Liberia and southwest‑ern Côte d’Ivoire, and the Nimba Mountains in northern Liberia, southeastern Guinea, and northwestern Côte d’Ivoire. Future climate‑driven projections anticipated minimal range shifts in response to climate change.Conclusions:By combining remotely sensed data and climatic data, our results suggest that forest cover, rather than climate is the major driver of the species’ current distribution. Thus, conservation efforts should prioritize forest protec‑tion and mitigation of other anthropogenic threats (e.g. hunting pressure) affecting the species.en_US
dc.description.sponsorshipConservation Internationalen_US
dc.description.sponsorshipGlobal Environment Facility-funded Grant # GEF-5810en_US
dc.publisherBMCen_US
dc.relation.isversionofhttps://avianres.biomedcentral.com/articles/10.1186/s40657-019-0160-yen_US
dc.rightsOpen Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectClimate changeen_US
dc.subjectConservationen_US
dc.subjectConservation planningen_US
dc.subjectEcological niche modelingen_US
dc.subjectSpecies distributionen_US
dc.subjectUpper Guinea Foresten_US
dc.subjectWhite-breasted Guineafowlen_US
dc.titleUsing remotely sensed and climate data to predict the current and potential future geographic distribution of a bird at multiple scales:en_US
dc.title.alternativethe case of Agelastes meleagrides, a western African forest endemicen_US
dc.typeArticleen_US
kusw.kuauthorFreeman, Benedictus
kusw.kudepartmentEcology and Evolutionary Biologyen_US
dc.identifier.doi10.1186/s40657-019-0160-yen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-0895-4952en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Except where otherwise noted, this item's license is described as: Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.