Using distance sampling with camera traps to estimate the density of group-living and solitary mountain ungulates
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Throughout the Himalaya, mountain ungulates are threatened by hunting for meat and body parts, habitat loss, and competition with livestock. Accurate population estimates are important for conservation management but most of the available methods to estimate ungulate densities are difficult to implement in mountainous terrain. Here, we tested the efficacy of the recent extension of the point transect method, using camera traps for estimating density of two mountain ungulates: the group-living Himalayan blue sheep or bharal Pseudois nayaur and the solitary Himalayan musk deer Moschus leucogaster. We deployed camera traps in 2017-2018 for the bharal (summer: 21 locations; winter: 25) in the trans-Himalayan region (3,000-5,000 m) and in 2018-2019 for the musk deer (summer: 30 locations; winter: 28) in subalpine habitats (2,500-3,500 m) in the Upper Bhagirathi basin, Uttarakhand, India. Using distance sampling with camera traps, we estimated the bharal population to be 0.51 ± SE 0.1 individuals/km2 (CV = 0.31) in summer and 0.64 ± SE 0.2 individuals/km2 (CV = 0.37) in winter. For musk deer, the estimated density was 0.4 ± SE 0.1 individuals/km2 (CV = 0.34) in summer and 0.1 ± SE 0.05 individuals/km2 (CV = 0.48) in winter. The high variability in these estimates is probably a result of the topography of the landscape and the biology of the species. We discuss the potential application of distance sampling with camera traps to estimate the density of mountain ungulates in remote and rugged terrain, and the limitations of this method.
Pal , R , Bhattacharya , T , Qureshi , Q , Buckland , S T & Sathyakumar , S 2021 , ' Using distance sampling with camera traps to estimate the density of group-living and solitary mountain ungulates ' , Oryx , vol. FirstView . https://doi.org/10.1017/S003060532000071X
Copyright © The Author(s), 2021. Published by Cambridge University Presson behalf of Fauna & Flora International. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.