Using multiple data types and integrated population models to improve our knowledge of apex predator population dynamics

Abstract

Current management of large carnivores is informed using a variety of parameters, methods, and metrics; however, these data are typically considered independently. Sharing information among data types based on the underlying ecological, and recognizing observation biases, can improve estimation of individual and global parameters. We present a general integrated population model (IPM), specifically designed for brown bears (Ursus arctos), using three common data types for bear (U. spp.) populations: repeated counts, capture–mark–recapture, and litter size. We considered factors affecting ecological and observation processes for these data. We assessed the practicality of this approach on a simulated population and compared estimates from our model to values used for simulation and results from count data only. We then present a practical application of this general approach adapted to the constraints of a case study using historical data available for brown bears on Kodiak Island, Alaska, USA. The IPM provided more accurate and precise estimates than models accounting for repeated count data only, with credible intervals including the true population 94% and 5% of the time, respectively. For the Kodiak population, we estimated annual average litter size (within one year after birth) to vary between 0.45 [95% credible interval: 0.43; 0.55] and 1.59 [1.55; 1.82]. We detected a positive relationship between salmon availability and adult survival, with survival probabilities greater for females than males. Survival probabilities increased from cubs to yearlings to dependent young ≥2 years old and decreased with litter size. Linking multiple information sources based on ecological and observation mechanisms can provide more accurate and precise estimates, to better inform management. IPMs can also reduce data collection efforts by sharing information among agencies and management units. Our approach responds to an increasing need in bear populations’ management and can be readily adapted to other large carnivores.

Using an Integrated Population Model to Evaluate Yellowstone Cutthroat Trout Responses to Management Actions

“…For instance, in many cases fecundity, age, and sex‐ratio data for wildlife populations can be visually observed or collected using nonlethal sampling methods (e.g., Bled et al. ; Abadi et al. ; Eacker et al.…”

Influence of maternal body size, condition, and age on recruitment of four brown bear populations

“…We used logistic regression to assess the influence of indices of body size, body condition, age, and population on the likelihood that an adult female would have offspring ࣙ1 year old with her. We considered the presence of offspring of ࣙ1 year old as a proxy for recruitment because mortality is greatest in the first year of life and the survival of yearlings and subadults approaches that of adult females (Garshelis et al 2005, Bled et al 2017. Correlations between predictors were ࣘ0.7, and we removed individuals with missing values for any measured attribute from the analysis.…”

Integrating data from multiple sources for insights into demographic processes: Simulation studies and proof of concept for hierarchical change-in-ratio models

“…In fact, the motivation for developing integrated population models, as discussed in e.g. [ 47 – 49 ], is to maximize inference from available data. Our work thus clearly benefits from the many previous studies within this field, and the novelty in our work is not so much that we combine data from multiple sources but rather the particular setting and type of data that we use as a basis for our modelling.…”