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  5. What will remain? predicting the representation in protected areas of suitable habitat for endangered tropical avifauna in Borneo under a combined climate- and land-use change scenario
 
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What will remain? predicting the representation in protected areas of suitable habitat for endangered tropical avifauna in Borneo under a combined climate- and land-use change scenario
File(s)
sustainability-13-02792-v2.pdf (1.55 MB)
Published version
Author(s)
Singh, Minerva
Badcock-Scruton, Jessamine
Collins, C Matilda
Type
Journal Article
Abstract
The responses of threatened tropical avian species to projected climate change and land-use change are important for evaluating the ability of the existing protected areas to provide habitat to these species under future scenarios in biodiversity hotspots. This study uses Maxent, a species distribution model that employs a maximum entropy machine learning approach to map the spatial distributions of habitats suitable for the International Union for Conservation of Nature threatened birds under present and future climate and land-use change in Borneo. We find that the existing protected areas provide very low coverage of the threatened bird species’ suitable habitat areas (95%CI = 9.3–15.4%). Analysis of habitat suitability projections for 18 species of threatened birds suggests that in 2050, under Special Report on Emissions Scenarios A1B and B1, avian species with currently little suitable habitat may gain area but lose in the proportion of this that is protected. Large-ranged species are likely to lose habitat area and this will inflate the proportion of this remaining in protected areas. The present availability of suitable habitat was the most important determinant of future habitat availability under both the scenarios. Threat level, as measured by the International Union for Conservation of Nature and the habitat preferences considered here, Lowland or Lowland–Montane, are poor predictors of the amount of habitat contraction or expansion undergone by the species.
Date Issued
2021-03-01
Date Acceptance
2021-02-24
Citation
Sustainability, 2021, 13 (5), pp.1-14
URI
http://hdl.handle.net/10044/1/103586
URL
https://www.mdpi.com/2071-1050/13/5/2792
DOI
https://www.dx.doi.org/10.3390/su13052792
ISSN
2071-1050
Publisher
MDPI AG
Start Page
1
End Page
14
Journal / Book Title
Sustainability
Volume
13
Issue
5
Copyright Statement
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
License URL
http://creativecommons.org/licenses/by/4.0/
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000628627000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
biodiversity
BIODIVERSITY SCENARIOS
BIRDS
climate change
CONSERVATION
conservation of nature
COVER CHANGE
DISTRIBUTIONS
DIVERSITY
entropy machine learning
Environmental Sciences
Environmental Sciences & Ecology
Environmental Studies
FOREST
GAP ANALYSIS
Green & Sustainable Science & Technology
Life Sciences & Biomedicine
Maxent
Science & Technology
Science & Technology - Other Topics
SHIFTS
SPECIES DISTRIBUTION MODELS
Publication Status
Published
Article Number
ARTN 2792
Date Publish Online
2021-03-05
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