Wildlife populations can be unmarked, meaning individuals lack visually distinguishing features for identification; populations may also exhibit non-independent movements, meaning individuals move together. For either unmarked or non-independent individuals, models based on spatial capture-recapture (SCR) approaches estimate abundance, density, and other population parameters critical for monitoring, management, and conservation. However, when individuals are both unmarked and non-independent, few model options exist. One approach has been to apply unmarked models and not address the non-independence despite unquantified impacts of overdispersion on bias, precision, and the ability to make robust ecological inferences. We conducted a simulation study to quantify the impact of non-independence on the performance of spatial count (SC) and spatial partial identity models (SPIM), two SCR-based unmarked modeling approaches, and used the performance of fully marked and independent SCR as a reference. We varied the levels of non-independence (aggregation and cohesion), detection probability, and the number of partial identity covariates used to resolve identities in SPIM estimation. We expected estimates of abundance and sigma (the spatial scale of individual movement) to be increasingly biased and less precise as aggregation and cohesion increased. Results showed that models indeed became less robust to increasing non-independence, especially for abundance, but importantly suggested that only SPIM could be reliably applied under low levels of cohesion when sufficient partial identity covariates are available. SC yielded consistently biased estimates with inflated precision that could not be corrected to nominal levels of coverage. SCR was the most robust across all combinations of aggregation and cohesion, as expected. We therefore advise against the use of SC models for estimating population parameters when individuals are known to be non-independent, caution that SPIM may be used under narrow ecological conditions, and encourage continued investigations into sampling design and methods development for populations of unmarked and non-independent individuals.

Human disturbance directly affects animal populations but indirect effects of disturbance on species behaviors are less well understood. Camera traps provide an opportunity to investigate variation in animal behaviors across gradients of disturbance. We used camera trap data to test predictions about predator-sensitive behavior in three ungulate species (caribou Rangifer tarandus; white-tailed deer, Odocoileus virginianus; moose, Alces alces) across two boreal forest landscapes varying in disturbance. We quantified behavior as the number of camera trap photos per detection event and tested its relationship to predation risk between a landscape with greater industrial disturbance and predator abundance (Algar) and a “control” landscape with lower human and predator activity (Richardson). We also assessed the influence of predation risk and habitat on behavior across camera sites within the disturbed Algar landscape. We predicted that animals in areas with greater predation risk (more wolf activity, less cover) would travel faster and generate fewer photos per event, while animals in areas with less predation risk would linger (rest, forage), generating more photos per event. Consistent with predictions, caribou and moose had more photos per event in the landscape where predation risk was reduced. Within the disturbed landscape, no prey species showed a significant behavioral response to wolf activity, but the number of photos per event decreased for white-tailed deer with increasing line of sight (m) along seismic lines (i.e. decreasing visual cover), consistent with a predator-sensitive response. The presence of juveniles was associated with shorter behavioral events for caribou and moose, suggesting greater predator sensitivity for females with calves. Only moose demonstrated a positive association with vegetation productivity (NDVI), suggesting that for other species influences of forage availability were generally weaker than those from predation risk. Behavioral insights can be gleaned from camera trap surveys and provide information about animal responses to predation risk and the indirect impacts of human disturbances.