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 centers)
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 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 10% 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 1,000 km2 within the park complex. Our novel group-based gSMR model
extends the applicability of spatial mark-resight to species with group
associations.