Estimating species richness with camera traps: modeling the effects of delay period, deployment length, number of sites, and interference imagery

Abstract

Biologists commonly use camera traps for estimating species richness to inform conservation actions, steer land protection, and reveal effects of climate change. Long-term studies using short delay periods (≤1 min) and numerous cameras produce voluminous amounts of redundant imagery. Thus, cameratrapping procedures maximizing richness estimates while minimizing data collection need development. We used imagery of mammals spanning 4 deserts in the United States to model the effects of delay, deployment length (i.e., study duration), number of sampling sites, and interference events on the proportion of known species richness detected (R p ). We also determined the proportion of subsamples containing each species (SR) under different sampling conditions to inform subsequent occupancy estimation. We generated contour plots describing the optimal configuration of sites and deployment length that minimized the image acquisition required to estimate R p = 0.9. The optimal configuration was independent of delay (requiring ~50 sites and 13 months). The shortest delay (10 sec) generated ~8 times more images than the longest (3600 sec) without substantially improving R p and rare species detection. The shortest duration to acquire R p = 0.9 was 10 months but required ~70 sites. The fewest