Wildlife ecologists throughout the world strive to monitor trends in population abundance to help manage wildlife populations and conserve species at risk. Spatial capture-recapture studies are the gold standard for monitoring density, yet they can be difficult to apply because researchers must be able to distinguish all detected individuals. Spatial mark-resight (SMR) models only require a subset of the population to be marked and identifiable. Recent advances in SMR models with radio-collared animals required a two-staged analysis. We developed a one-stage generalized SMR (gSMR) model that used detection histories of marked and unmarked animals in a single analysis. We used simulations to assess the performance of one- and two-stage gSMR models. We then applied the one-stage gSMR with telemetry and remote camera data to estimate grizzly bear (Ursus arctos) abundance from 2012 to 2023 within the Canadian Rocky Mountains. We estimated abundance trends for the population and reproductive females (females with cubs of the year). Simulations suggest one- and two-stage models performed equally well. One-stage models are more dependable as they use exact likelihoods whereas two-stage models have shorter computation times for large datasets. Both methods had > 95% credible interval coverage and minimal bias. Increasing the number of marked animals increased the accuracy and precision of abundance estimates and > 10 marked animals were required to obtain coefficients of variation < 20% in most scenarios. The grizzly bear population increased slightly (growth rate λ_mean = 1.02) to a 2023 density of 10.4 grizzly bears/1000 km². Reproductive female abundance had high interannual variability and increased to 1.0 bears/1000 km². Population density was highest within protected areas, within high quality habitat and far from paved roads. The density of activity centers declined near paved roads over time. Mechanisms of decline may have included direct mortality and shifting activity centers to avoid human activity. Our study demonstrates the influence of human activity on localized density and importance of protected areas for carnivore conservation. Finally, our study highlights the widespread utility of remote camera and telemetry-based spatial mark-resight models for monitoring spatiotemporal trends in abundance.

The gSMR models combine remote camera detections of marked animals, unmarked animals, and telemetry data to estimate the baseline detection rate, home range scale parameter, and spatially explicit estimates of density. Our study area encompassed 15,483 km² and included Banff, Kootenay, and Yoho Nation Parks and the Ya Ha Tinda ecosystem within the Rocky Mountains of Canada. The remote camera data contains detection histories from 25 marked, radio-collared grizzly bears and detections of unmarked grizzly bears recorded at 625 remote cameras from 2012 to 2021. Telemetry data contains daily global positioning system (GPS) locations from fifteen female and ten male grizzly bears. We provide source code to estimate spatial and temporal trends in grizzly bear density as well as the density of female grizzly bears with cubs of the year. We describe each data set and associated attributes in tbl_DataDescription_2023-11-13.csv.