E.J. Parker
Habitat selection of an endangered primate, the samango monkey (Cercopithecus albogularis schwarzi): integrating scales to prioritise habitat for wildlife management
Parker, E.J.; Koyama, N.F.; Hill, R.A.
Abstract
Aim: As habitat loss continues to accelerate with global human population growth, identifying landscape characteristics that influence species occurrence is a key conservation priority in order to prevent global biodiversity loss. In South Africa, the arboreal samango monkey (Cercopithecus albogularis sp.) is threatened due to loss and fragmentation of the indigenous forests it inhabits. The aim of this study was to determine the habitat preferences of the samango monkey at different spatial scales, and to identify key conservation areas to inform management plans for this species. Location: This study was carried out in the western Soutpansberg Mountains, which represents the northernmost population of samango monkeys within South Africa, and the only endangered subspecies (C. a. schwarzi). Methods: We used sequentially collected GPS points from two samango monkey groups followed between 2012 – 2017 to quantify the used and available habitat for this species within the western Soutpansberg Mountains. We developed 2nd (selection of ranging area), 3rd (selection within range) and 4th (feeding site selection) order resource selection functions (RSFs) to identify important habitat features at each scale. Through scale integration, we identified three key conservation areas for samango monkeys across Limpopo Province, South Africa. Results: Habitat productivity was the most important landscape variable predicting probability of use at each order of selection, indicating the dependence of these arboreal primates on tall-canopy indigenous forests. Critical habitat across Limpopo was highly fragmented, meaning complete isolation between subpopulations is likely. Main conclusions: Understanding the habitat characteristics that influence samango monkey distribution across South Africa is crucial for prioritising critical habitat for this species. Our results indicated that large, contiguous patches of tallcanopy indigenous forest are fundamental to samango monkey persistence. As such, protected area expansion of large forest patches and creation of forest corridors are identified as key conservation interventions for this species.
Citation
Parker, E., Koyama, N., & Hill, R. (2021). Habitat selection of an endangered primate, the samango monkey (Cercopithecus albogularis schwarzi): integrating scales to prioritise habitat for wildlife management. Ecology and Evolution, 11(12), 8014-8026. https://doi.org/10.1002/ece3.7631
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 12, 2021 |
Online Publication Date | May 5, 2021 |
Publication Date | Jun 21, 2021 |
Deposit Date | Apr 12, 2021 |
Publicly Available Date | Jul 6, 2021 |
Journal | Ecology and Evolution |
Electronic ISSN | 2045-7758 |
Publisher | Wiley Open Access |
Peer Reviewed | Peer Reviewed |
Volume | 11 |
Issue | 12 |
Pages | 8014-8026 |
DOI | https://doi.org/10.1002/ece3.7631 |
Public URL | https://durham-repository.worktribe.com/output/1249875 |
Files
Published Journal Article
(1.6 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Copyright Statement
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
You might also like
Behavioural compatibility, not fear, best predicts the looking patterns of chacma baboons
(2024)
Journal Article
Keystone individuals – linking predator traits to community ecology
(2024)
Journal Article
Leopard density and determinants of space use in a farming landscape in South Africa
(2024)
Journal Article
Tropical field stations yield high conservation return on investment
(2024)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search