PAANWARIS PAANSRI
Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University. Blacksburg, Virginia 24061, United States

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Environmental influence on the spatial abundance of tiger prey monitored using camera traps in Thap Lan and Pang Sida National Parks, Thailand BENCHAWAN MEEAMNART; SOMPORN PAKPIAN; JIRASAK KHONGMUEANG; PAKON KAMSUDSANG; PAANWARIS PAANSRI; PRATEEP DUENGKAE; WARONG SUKSAVATE
Biodiversitas Journal of Biological Diversity Vol. 26 No. 3 (2025)
Publisher : Society for Indonesian Biodiversity

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/biodiv/d260350

Abstract

Abstract. Meeamnart B, Pakpian S, Khongmueang J, Kamsudsang P, Paansri P, Duengkae P, Suksavate W. 2025. Environmental influence on the spatial abundance of tiger prey monitored using camera traps in Thap Lan and Pang Sida National Parks, Thailand. Biodiversitas 26: 1500-1511. The decline in prey populations within the Dong Phayayen-Khao Yai Forest Complex (DPKY), Thailand, has likely contributed to the local extinction of tigers, raising urgent concerns about the future of this iconic species in the region. Environmental factors play a crucial role in the fluctuations in prey densities. This study estimated the spatial density of five key tiger prey species (gaur, banteng, sambar deer, muntjac, and wild boar) using the Random Encounter and Staying Time (REST) and Royle-Nichols (RN) occupancy models. The REST model produced density estimates of 1.05±0.35, 0.01±0.11, 0.62±0.79, 1.10±0.49, and 1.46±0.38 individuals/km² for gaur, banteng, sambar deer, muntjac, and wild boar, respectively. The RN model yielded slightly higher estimates: 1.51±1.26, 0.05±0.14, 0.82±0.58, 2.62±1.25, and 3.06±1.74 individuals/km². These findings highlight the significant influence of variables like vegetation cover, proximity to human settlements, elevation, and salt licks on prey abundance and distribution, with muntjac and wild boar consistently showing higher densities than other species. This spatial modeling approach provides a novel framework for predicting animal density, which can inform conservation and management strategies for tiger prey populations in DPKY, thereby aiding in tigers' persistence within these protected areas.