Can we count you: validating density estimation methods for unmarked wildlife with camera traps

Abstract

Estimating population densities of large wildlife in forests has traditionally relied on either spatial capture-recapture (SCR) for animals that are individually marked, or line transect distance sampling (LTDS) for species observable by researchers. Recent advances have now introduced more general camera trap models that are applicable to a large range of terrestrial medium to large-sized species. However, validation of these unmarked density (UD) models remains scarce due to the lack of available density estimates that can serve as references. We tested the accuracy and precision of three UD models (the random encounter model, camera trap distance sampling, and the time-to-event model) against independent SCR estimates for ocelots and jaguars, and against LTDS estimates for eight unmarked species varying in abundance and ecology. We found that UD model estimates for ocelots were relatively accurate in matching the estimates from SCR, albeit with less precision. Additionally, UD model estimates were similar to LTDS estimates for seven out of eight studied species. Estimates for jaguar were, however, not similar between UD models and SCR, implying that UD models are not useful for rare species. Overall, our findings show that UD models are promising tools for monitoring abundant to relatively rare unmarked species in forests, although SCR remains preferred for marked species. To ultimately aid conservationists in making informed conservation decisions, efforts should be directed towards enhancing the precision of these models as well as their ease of access for non-technical practitioners.