Evaluating and integrating spatial capture-recapture models with data of variable individual identifiability

Abstract

Many applications in ecology depend on unbiased and precise estimates of animal population density. Spatial capture recapture models and their variants have become the preferred tool for estimating densities of carnivores. Within the spatial capture-recapture family are variants that require individual identification of all encounters (spatial capture-recapture), individual identification of a subset of a population (spatial mark-resight), or no individual identification (spatial count). In addition, these models can incorporate telemetry data (all models) and the marking process (spatial mark-resight). However, the consistency of results among methods and the relative precision of estimates in a real-world setting are unknown. Consequently, it is unclear how much and what type of data are needed to achieve satisfactory density estimates. We tested a suite of models to estimate population densities of black bears (Ursus americanus), bobcats (Lynx rufus), cougars (Puma concolor), and coyotes (Canis latrans). For each species we genotyped fecal DNA collected with detection dogs. A subset of individuals from each species were affixed with GPS collars bearing unique markings to be resighted by remote cameras set on a 1 km grid. We fit 10 models for each species ranging from those requiring no animals to be individually recognizable to others that necessitate full individual recognition. We then assessed the contribution of incorporating telemetry data to each model and the marking process to the mark-resight model. Finally, we developed an integrated hybrid model that combines camera, physical capture, genetic, and GPS data into a single hierarchical model. Importantly, we find that spatial count models that do not individually identify animals fail in all cases whether or not telemetry data are included. Results improved as models contained more information on individual identity. Models where a subset of individuals were identifiable yielded qualitatively similar results, but can produce quantitatively divergent estimates, suggesting that long-term population monitoring should use a consistent method across years. Incorporation of telemetry data and the marking process can produce more accurate and precise density estimates. Our results can be used to guide future study designs to efficiently estimate carnivore densities for better understanding of population dynamics, predator-prey relationships, and community assemblages.

Abundance estimation of unmarked animals based on camera‐trap data

“…Although it is possible to simulate multiple types of animal movement in virtual landscapes, it is difficult to know which, if any, of the types accurately represent animals moving through real landscapes. Several empirical comparisons of unmarked methods exist and provide insight into the performance of multiple methods in common systems (Doran-Myers 2018;Burgar et al 2018;Ruprecht et al 2020). However, we suggest that further empirical comparisons would be valuable for identifying systems or conditions where abundance estimates from different methods diverge.…”

“…2018; Ruprecht et al. 2020). However, we suggest that further empirical comparisons would be valuable for identifying systems or conditions where abundance estimates from different methods diverge.…”

Games of risk and reward in carnivore communities

“…4e) and in another instance, a GPS-collared cougar killed and consumed a GPS-collared coyote. By observing dead coyotes at 7% of cougar kill sites, and given a cougar density of 2.2 per 100 km 2 in our study area (22), this suggests that approximately 8.4 coyotes are killed per 100 km per year. With a coyote density of 33.9 per 100 km 2 (22), this level of mortality reflects 23.0% (95% CI: 8.4-54.5% when all sources of uncertainty are propagated) of coyotes killed by cougars annually:…”

“…We estimated that each cougar killed approximately 3.8 coyotes annually, though we note previous studies in the region have reported less coyote predation (21,37) so this value may partially be the result of a small sample size. Nonetheless, given a cougar density of 2.2 per 100 km 2 in our study area (22), this suggests that approximately 8.4 coyotes are killed per 100 km 2 per year. With a coyote density of 33.9 per 100 km 2 , this level of mortality reflects 23.0% (95% CI: 8.4-54.5% when all sources of uncertainty are propagated) of coyotes killed by cougars annually.…”

“…At times, the prey items found at cougar kill sites were other carnivores which allowed us to calculate the proportion of cougar kills representing intraguild predation. Combining these data with information on contemporaneously-estimated carnivore densities (22) and cougar kill rates (21) from a recent study in the area allowed us to calculate intraguild predation rates, i.e., the proportion of the co-occurring carnivore population dying annually due to cougar predation. We calculated the intraguild predation rate on species i (P i ) as the number of individuals from species i killed per unit time (K i ) divided by the population density of species i (D i ) where K i is the product of cougar population density (D c ) cougar kill rate (kills/year), R, and proportion of kills corresponding to species i (F i ):…”