A novel generalized spatial mark-resight model that accounts for group associations

The number and distribution of animals in space form the basis of many wildlife studies. Yet, reliable estimation of population abundance remains challenging. Generalized spatial mark-resight (gSMR) models are widely applicable abundance estimators that do not require all individuals be uniquely identifiable. Despite their flexibility, gSMR models assume independence in distribution and detections of individuals throughout space. Group-living species that aggregate (i.e. share activity centres) and move cohesively (i.e. share detections) violate these assumptions, limiting the applicability of gSMR models to solitary species with limited home range overlap. We developed a gSMR model that accounts for group associations to estimate spatial abundance. We treated groups as the measurable ‘units’ and included a submodel that uses Poisson processes to estimate group size. We conducted a simulation study to compare our novel group-based gSMR to a gSMR that ignores group associations. We generated data across varying levels of aggregation and cohesion parameters. We then quantified and compared the precision and bias of parameter estimates between the two models. The group-based gSMR model outperformed the individual-based gSMR under all aggregation and cohesion scenarios. Group-based 95% Bayesian Credible Intervals (BCI) overlapped the true value of abundance in 91% of simulations, compared to only 15% of simulations in the individual-based gSMR. Both the group-based and individual-based models became less precise and more biased as aggregation and group size increased. However, the group-based gSMR model was less biased in estimating all parameters when compared to the individual-based gSMR model. We applied our group-based gSMR model to grey wolf (Canis lupus) monitoring data within a Canadian national park complex (Banff, Yoho and Kootenay National Parks, and Ya Ha Tinda). We used 12 years (2012–2023) of remote camera data, along with information from GPS radio-collared wolves (N = 16) to estimate spatiotemporal variation in abundance. Over a 12-year period, wolf abundance averaged 73 (95% BCI = 20–207) individuals, and a density of 6.69 (95% BCI = 1.83–19.0) wolves per 1000 km² within the park complex. Our novel group-based gSMR model extends the applicability of spatial mark-resight to species with group associations.