Work

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

Year: 2026

Type: article

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.

Source: Biological Conservation

DOI: 10.1016/j.biocon.2026.111987