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Vegetation cover restricts habitat suitability predictions of endemic Brazilian Atlantic Forest birds

  • Ecological niche models (ENMs) are often used to investigate how climatic variables from known occurrence records can estimate potential species range distribution. Although climate-based ENMs provide critical baseline information, the inclusion of non-climatic predictors related to vegetation cover might generate more realistic scenarios. This assumption is particularly relevant for species with life-history traits related to forest habitats and sensitive to habitat loss and fragmentation. Here, we developed ENMs for 36 Atlantic Forest endemic birds considering two sets of predictor variables: (i) climatic variables only and (ii) climatic variables combined with the percentage of remaining native vegetation. We hypothesized that the inclusion of native vegetation data would decrease the potential range distribution of forest-dependent species by limiting their occurrence in regions harboring small areas of native vegetation habitats, despite otherwise favorable climatic conditions. We also expected that habitat restriction in theEcological niche models (ENMs) are often used to investigate how climatic variables from known occurrence records can estimate potential species range distribution. Although climate-based ENMs provide critical baseline information, the inclusion of non-climatic predictors related to vegetation cover might generate more realistic scenarios. This assumption is particularly relevant for species with life-history traits related to forest habitats and sensitive to habitat loss and fragmentation. Here, we developed ENMs for 36 Atlantic Forest endemic birds considering two sets of predictor variables: (i) climatic variables only and (ii) climatic variables combined with the percentage of remaining native vegetation. We hypothesized that the inclusion of native vegetation data would decrease the potential range distribution of forest-dependent species by limiting their occurrence in regions harboring small areas of native vegetation habitats, despite otherwise favorable climatic conditions. We also expected that habitat restriction in the climate-vegetation models would be more pronounced for highly forest-dependent birds. The inclusion of vegetation data in the modeling procedures restricted the final distribution ranges of 22 out of 36 modeled species, while the 14 remaining presented an expansion of their ranges. We observed that species with high and medium forest dependency showed higher restriction in range size predictions between predictor sets than species with low forest dependency, which showed no alteration or range expansion. Overall, our results suggest that ENMs based on climatic and landscape variables may be a useful tool for conservationists to better understand the dynamic of bird species distributions in threatened and highly fragmented regions such as the Atlantic Forest hotspot.(c) 2021 Associacao Brasileira de Cie circumflex accent ncia Ecol ogica e Conservacao. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ).show moreshow less

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Author details:Anna Elizabeth de Oliveira-SilvaORCiD, Augusto João PiratelliORCiD, Damaris ZurellORCiDGND, Fernando Rodrigues da SilvaORCiDGND
DOI:https://doi.org/10.1016/j.pecon.2021.09.002
ISSN:2530-0644
Title of parent work (English):Perspectives in Ecology and Conservation
Publisher:Elsevier
Place of publishing:Oxford
Publication type:Article
Language:English
Date of first publication:2021/10/05
Publication year:2021
Release date:2024/01/05
Tag:Conservation; Ecological niche modeling; Forest dependency; Fragmentation; Habitat loss; Landscape; Life-history traits
Volume:20
Issue:1
Number of pages:8
First page:1
Last Page:8
Funding institution:Fundacao de Amparo a Pesquisa do Estado de Sao Paulo [2018/02591-0]; German Science Foundation (DFG) [ZU 361-1/1]
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
Publishing method:Open Access / Gold Open-Access
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License (German):License LogoCC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International
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