| Summary: | Woodland caribou (Rangifer tarandus) are classified as threatened in Canada, and the Little Smoky herd in west-central Alberta is at immediate risk of extirpation due in part, to anthropogenic activities such as oil, gas, and forestry that have altered the ecosystem dynamics. Winter season represents an especially challenging time of year for this Holarctic species as it is characterized by a shortage of basic resources and is when most industrial development occurs, to which caribou can perceive as increased predation risk. To investigate the impact of industrial features on caribou, we developed a spatially explicit, agent-based model (ABM) to simulate the underlying behavioral mechanisms caribou are most likely to employ when navigating their landscape in winter. The ABM model is composed of cognitive caribou agents possessing memory and decision-making heuristics that act to optimize tradeoffs between energy acquisition and predator/disturbance avoidance. A set of environmental data layers was used to develop a virtual grid representing the landscape in terms of forage availability, energy content, and predation-risk. The model was calibrated with caribou bio-energetic values from literature sources, and validated using GPS data from thirteen caribou radio-collars deployed over 6 months from 2004 to 2005. Simulations were conducted on alternative caribou habitat-selection strategies by assigning different fitness-maximizing goals to agents. The model outcomes were evaluated using a pattern-oriented modeling approach with actual caribou data. The scenario in which the caribou agent must trade off the mutually competing goals of obtaining its daily energy requirement, conserving reproductive energy, and minimizing predation risk, was found to be the best-fit scenario. Not recognizing industrial features as risk causes simulated caribou to unrealistically reduce their daily and landscape movements; equally, having risk take precedence results in unrealistic energetic deficits and large-scale movement patterns, ...
|
|---|