Optimizing camera trap placement for felid density estimation: Comparing trail-based and random deployments

Wild felids are globally threatened, requiring accurate monitoring for adaptive conservation. Camera-trap surveys for individually identifiable felids place cameras on trails and estimate density using spatially explicit capture–recapture (SCR) models. However, unequal individual capture probabilities—individual heterogeneity—can bias density estimates if unaccounted for. We examined how camera placement influences SCR-derived density estimates across 400 km 2 study area in Central Bhutan inhabited by five identifiable felid species ( Panthera tigris, Panthera pardus, Neofelis nebulosa, Pardofelis marmorata, and Prionailurus bengalensis ). We deployed 100 paired cameras on trails and 100 single cameras at random locations. Trail cameras produced a male-biased sex ratio of 1.75 males per female, whereas random cameras yielded a balanced ratio of 1.0. The trail placement missed proportionally more females (30%) than males (8%), while the random placement missed more males (56%) than females (33%). This male-biased detection pattern was consistent across species, particularly for leopard and leopard cat. Density estimates based solely on trail data were, on average, 22% lower than estimates derived from the combined trail + random dataset. We evaluated two approaches to address this sex bias. First, incorporating sex as a covariate in SCR models produced trail-only estimates comparable to those from the combined dataset. Second, we tested a mixed deployment approach (trail and random) using data sub-sampling, which indicated that allocating ∼50% of cameras to random locations provided an effective balance between accuracy and precision. Where sex-specific trail use affects detectability, we recommend mixed designs combining trail and random camera placements, although smaller surveys may still justify trail-only designs.

Authors

Institutions

Publication Details

Journal
Biological Conservation
Published
2026-06-28
DOI
https://doi.org/10.1016/j.biocon.2026.111987
Primary Topic
Robotic Locomotion and Control
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing camera trap placement for felid density estimation: Comparing trail-based and random deployments

Kuenley Tenzin, C. Patfuck Doncaster, Wai‐Ming Wong, Rinjan Shrestha et al.
Biological Conservation
Robotic Locomotion and Control
article

Optimizing camera trap placement for felid density estimation: Comparing trail-based and random deployments

Kuenley Tenzin, C. Patfuck Doncaster, Wai‐Ming Wong, Rinjan Shrestha, Paul Glover‐Kapfer, Oliver R. Wearn, Lon Grassman, Lungten Dorji
article en

Abstract

Wild felids are globally threatened, requiring accurate monitoring for adaptive conservation. Camera-trap surveys for individually identifiable felids place cameras on trails and estimate density using spatially explicit capture–recapture (SCR) models. However, unequal individual capture probabilities—individual heterogeneity—can bias density estimates if unaccounted for. We examined how camera placement influences SCR-derived density estimates across 400 km 2 study area in Central Bhutan inhabited by five identifiable felid species ( Panthera tigris, Panthera pardus, Neofelis nebulosa, Pardofelis marmorata, and Prionailurus bengalensis ). We deployed 100 paired cameras on trails and 100 single cameras at random locations. Trail cameras produced a male-biased sex ratio of 1.75 males per female, whereas random cameras yielded a balanced ratio of 1.0. The trail placement missed proportionally more females (30%) than males (8%), while the random placement missed more males (56%) than females (33%). This male-biased detection pattern was consistent across species, particularly for leopard and leopard cat. Density estimates based solely on trail data were, on average, 22% lower than estimates derived from the combined trail + random dataset. We evaluated two approaches to address this sex bias. First, incorporating sex as a covariate in SCR models produced trail-only estimates comparable to those from the combined dataset. Second, we tested a mixed deployment approach (trail and random) using data sub-sampling, which indicated that allocating ∼50% of cameras to random locations provided an effective balance between accuracy and precision. Where sex-specific trail use affects detectability, we recommend mixed designs combining trail and random camera placements, although smaller surveys may still justify trail-only designs.

Biological ConservationVol. 321
Fauna and Flora International (GB), WWF Colombia (CO), Zoological Society of London (GB), Panthera Corporation (US), Georgian Court University (US), World Wildlife Fund Canada (CA), World Wildlife Fund (US), Ministry of Agriculture and Forests (BT), University of Southampton (GB), Royal University of Bhutan (BT)
Panthera, Zoological Society of London, University of Southampton, WWF International
Climate action
Openalex Percentile: Top 13%
Robotic Locomotion and Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.