Evaluating risk effects of industrial features on woodland caribou habitat selection in west central Alberta using agent-based modelling

Abstract

Alberta woodland caribou ( Rangifer tarandus ) are classified as threatened in Canada, and a local population in the west-central region, the Little Smoky herd, is at immediate risk of extirpation due, in part, to anthropogenic activities such as oil, gas, and forestry that have altered the ecosystem dynamics. To investigate these impacts, we have developed a spatially explicit, agent-based model (ABM) to simulate winter habitat selection and use of woodland caribou, and to determine the relative impacts of different industrial features on caribou habitat-selection strategies. The ABM model is composed of cognitive caribou agents possessing memory and decision-making heuristics that act to optimize tradeoffs between energy acquisition and disturbance. A set of environmental data layers was used to develop a virtual grid representing the landscape over which caribou move. This grid contained forage-availability, energy-content, and predation-risk values. The model was calibrated using GPS data from caribou radio collars (n = 13) deployed over six months from 2004 to 2005, representing caribou winter activities. Additional simulations were conducted on caribou habitat-selection strategies by assigning industrial features (i.e., roads, seismic lines, pipelines, well sites, cutblocks and burns) different levels of disturbance depending on their type, age, and density. Differences in disturbance effects between industry features were confirmed by verifying which resultant simulations of caribou movement patterns most closely match actual caribou distributions and other patterns extracted from the GPS data. The results elucidate the degree to which caribou perceive different industry features as disturbance, and the differential energetic costs associated with each, thus offering insight into why caribou are choosing the habitats they use, and consequently, the level and type of industry most likely to affect their bioenergetics and fitness.