Assumptions about fence permeability influence density estimates for brown hyaenas across South Africa

Williams, K.S.; Williams, S.T.; Welch, R.J.; Marneweck, C.J.; Mann, G.T.; Pitman, R.T.; Whittington-Jones, G.; Balme, G.A.; Parker, D.M.; Hill, R.A.

Abstract

Wildlife population density estimates provide information on the number of individuals in an area and influence conservation management decisions. Thus, accuracy is vital. A dominant feature in many landscapes globally is fencing, yet the implications of fence permeability on density estimation using spatial capture-recapture modelling are seldom considered. We used camera trap data from 15 fenced reserves across South Africa to examine the density of brown hyaenas (Parahyaena brunnea). We estimated density and modelled its relationship with a suite of covariates when fenced reserve boundaries were assumed to be permeable or impermeable to hyaena movements. The best performing models were those that included only the influence of study site on both hyaena density and detection probability, regardless of assumptions of fence permeability. When fences were considered impermeable, densities ranged from 2.55 to 15.06 animals per 100 km2, but when fences were considered permeable, density estimates were on average 9.52 times lower (from 0.17 to 1.59 animals per 100 km2). Fence permeability should therefore be an essential consideration when estimating density, especially since density results can considerably influence wildlife management decisions. In the absence of strong evidence to the contrary, future studies in fenced areas should assume some degree of permeability in order to avoid overestimating population density.

Citation

Williams, K., Williams, S., Welch, R., Marneweck, C., Mann, G., Pitman, R., Whittington-Jones, G., Balme, G., Parker, D., & Hill, R. (2021). Assumptions about fence permeability influence density estimates for brown hyaenas across South Africa. Scientific Reports, 11, Article 620. https://doi.org/10.1038/s41598-020-77188-7

• Journal Article Type: Article
• Acceptance Date: Nov 5, 2020
• Online Publication Date: Jan 12, 2021
• Publication Date: 2021
• Deposit Date: Nov 5, 2020
• Publicly Available Date: Jun 14, 2021
• Journal: Scientific Reports
• Publisher: Nature Research
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Article Number: 620
• DOI: https://doi.org/10.1038/s41598-020-77188-7
• Public URL: https://durham-repository.worktribe.com/output/1257657