Andrea R. Litt, Anna K. Moeller, Kerry A. Gunther, Mark A. Haroldson, Matthew J. Gould, Frank T. van Manen

Estimating population abundance is a fundamental challenge in ecology, yet it is central to assessments of population status and management outcomes. American black (Ursus americanus) and grizzly (U. arctos) bears occur in North America at low densities, are highly mobile, occupy large home ranges, and typically lack individually recognizable markings, all of which complicate efforts to estimate abundance. Camera traps can help address many of these challenges, however, their application has been limited by the requirement for individual identification. Recent analytical advances eliminate this constraint. We applied two modeling approaches—time-to-event (TTE) and space-to-event (STE)—as a novel way to estimate densities of black and grizzly bears across Yellowstone National Park, USA. During July and August 2024, 120 camera traps set at random locations captured 1.4 million motion-triggered and time-lapse photographs, including images of both bear species. Approximately 85% of detections for grizzly bears (n = 77) and black bears (n = 97) were motion-triggered photos. We used telemetry data from Global Positioning System-collared bears (56 grizzly and 12 black bears) to estimate species-specific movement rates and field-based measurements to estimate the viewable area for each camera trap. These additional data are crucial for TTE and STE models in linking the detection process to a density estimate. Camera-based estimation techniques offer significant advantages compared with study designs based on captures or aerial surveys, improving safety for bears and humans, while sampling large areas. Additionally, deploying cameras at random locations creates a dataset that can be used to simultaneously estimate abundance of multiple species and address other ecological questions. Our assessment of these techniques provides detailed guidance towards establishing efficient, camera-based approaches for density estimation and monitoring of bear populations.