A Novel Approach to Estimate the Population of Unmarked Social Animal Using Camera Traps Photo-Captures

Robust population estimation is indispensable for well-informed management and conservation of species. Capture-recapture models provide a robust framework for density estimation of animals with unique identifying features. The challenge is amplified for group-living species lacking identifiable marks where both the number of groups and number of individuals needs to be estimated simultaneously. We developed a model to estimate the population of group-living animals using a hierarchical clustering approach. We used weighted geographical distance and probability of missing an individual from photo-capture sequence to estimate number of groups and individuals in a group. We simulated scenarios with a varying number of capture sequence to test the effect of number of sequences on a detection probability and group-size. We applied the proposed method on a group living, unidentifiable canid, dhole (Cuon alpinus) following a multidisciplinary approach. We examined the average radius estimated from clustering method against home-range radius obtained from GPS-collared individuals. Additionally, we compared population estimates with individuals identified through molecular tools. Simulations showed there was no substantial change in the number of individuals estimated with the number of photo-capture sequences. The efficacy of our model was more than 70% until the ratio of the radii of the pack operating area and pack range centres were less than 0.8. The spatial extent and population estimate derived from clustering model was comparable with GPS telemetry data and individuals identified using molecular methods. Our model would broaden the scope of the applicability of camera trap studies for social species with uniquely unidentifiable individuals. With assumptions like territoriality, independent captures and cohesion of the study species, this model can aid in the monitoring and conservation of rare, endangered species like dholes, which otherwise pose a challenge to managers and conservation practitioners.