Cameras or Camus? Comparing Snow Track Surveys and Camera Traps to Estimate Densities of Unmarked Wildlife Populations

Abstract

Population density is a valuable metric used to manage wildlife populations. In the Russian Far East, managers use the Formozov- Malyushev-Pereleshin (FMP) snow tracking method to estimate densities of ungulates for hunting management. The FMP also informs Amur tiger (Panthera tigris altaica) conservation since estimates of prey density and biomass help inform conservation interventions. Yet, climate change and challenges with survey design call into question the reliability of the FMP. Camera traps offer a promising alternative, but they remain unexplored for monitoring tiger prey density. Over three years (2020-2022), we used the FMP and camera-based methods to estimate densities of four prey species of the Amur tiger in the Sikhote- Alin Biosphere Reserve, Russian Far East: wild boar (Sus scrofa), red deer (Cervus canadensis), roe deer (Capreolus pygargus), and sika deer (Cervus nippon). We compared FMP results from snow track survey routes either along trails, or along routes representative of the study area, and estimates derived from camera data using the random encounter model (REM), space-to-event model (STE), and time-to-event model (TTE). We found that density estimates from representative routes were typically lower than routes along trails and indicated different relative densities of prey. Density estimates from camera traps and representative track surveys were generally similar with no significant relative bias, but precision was poor for all methods. Differences between estimates were amplified when converted to prey biomass, particularly with larger, more abundant prey, which poses a challenge for their utility for tiger managers. We conclude camera traps can offer an alternative to snow track surveys when monitoring unmarked prey, but we caution that they require considerably more resources to implement. Tiger managers should be especially cautious when extrapolating density to estimates of prey biomass, and we encourage future research to develop more robust methods for doing so.