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Maximizing the value of forest restoration for tropical mammals by detecting three-dimensional habitat associations

Deere, Nicolas J., Guillera-Arroita, Gurutzeta, Swinfield, Tom, Milodowski, David T., Coomes, David, Bernard, Henry, Reynolds, Glen, Davies, Zoe G., Struebig, Matthew J. (2020) Maximizing the value of forest restoration for tropical mammals by detecting three-dimensional habitat associations. Proceedings of the National Academy of Sciences of the United States of America, 117 (42). pp. 26254-26262. ISSN 0027-8424. (doi:10.1073/pnas.2001823117) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:82261)

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Abstract

Tropical forest ecosystems are facing unprecedented levels of degradation, severely compromising habitat suitability for wildlife. Despite the fundamental role biodiversity plays in forest regeneration, identifying and prioritising degraded forests for restoration or conservation, based on their wildlife value, remains a significant challenge. Efforts to characterize habitat selection are also weakened by simple classifications of human-modified tropical forests as intact versus degraded, which ignore the influence that three-dimensional forest structure may have on species distributions. Here, we develop a framework to identify conservation and restoration opportunities across logged forests in Borneo. We couple high-resolution airborne Light Detection and Ranging (LiDAR) and camera trap data to characterize the response of a tropical mammal community to changes in three-dimensional forest structure across a degradation gradient. Mammals were most responsive to covariates that accounted explicitly for the vertical and horizontal characteristics of the forest, and actively selected structurally-complex environments comprising tall canopies, increased plant area index throughout the vertical column, and the availability of a greater diversity of niches. We show that mammals are sensitive to structural simplification through disturbance, emphasising the importance of maintaining and enhancing structurally-intact forests. By calculating occurrence thresholds of species in response to forest structural change, we identify areas of degraded forest that would provide maximum benefit for multiple high conservation value species if restored. The study demonstrates the advantages of using LiDAR to map forest structure, rather than relying on overly simplistic classifications of human-modified tropical forests, for prioritising regions for restoration.

Item Type: Article
DOI/Identification number: 10.1073/pnas.2001823117
Uncontrolled keywords: Ecological thresholds; LiDAR; occupancy; prioritization; forest degradation
Subjects: Q Science > QH Natural history > QH541 Ecology
Q Science > QH Natural history > QH75 Conservation (Biology)
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)
Depositing User: Nick Deere
Date Deposited: 28 Jul 2020 14:10 UTC
Last Modified: 03 Mar 2021 15:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/82261 (The current URI for this page, for reference purposes)
Deere, Nicolas J.: https://orcid.org/0000-0003-1299-2126
Davies, Zoe G.: https://orcid.org/0000-0003-0767-1467
Struebig, Matthew J.: https://orcid.org/0000-0003-2058-8502
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