Using space to event modeling to estimate density of multiple species in northeastern Washington

Abstract

AbstractConcurrent monitoring of multiple species with a single study design can be an efficient use of time and financial resources. Using camera traps to estimate density or abundance of multiple species is only possible if the study design captures photographs of all target species in an unbiased manner. We used camera trap data originally collected for a different purpose and applied the Space to Event (STE) model to estimate density of multiple species simultaneously. We had sufficient data to estimate densities of moose (Alces alces), black bear (Ursus americanus), mountain lions (Puma concolor), wolves (Canis lupus), and deer (white‐tailed deer [Odocoileus virginianus] and mule deer [O. hemionus] combined). Our estimated densities were lower than those derived from other methods in the study area, possibly due to the lack of a sampling design specific to STE. However, our estimates were generally comparable to published density estimates from across the species' range. Our approach allowed us to estimate abundance and density for each species with the same effort required to estimate abundance of a single species. Our results suggest that with an appropriate study design, STE could be an effective, efficient, low cost and non‐invasive method for estimating densities of multiple unmarked species using a single camera array.