Human activities impose both positive and negative effects on wildlife movement, habitat use, perceived predation risk and nutritional condition. There is increasing, global concern that human activities are influencing predator-prey interactions with potential consequences for wildlife communities. Evaluating how human activities alter such interactions can help ecologists develop mitigations, that can help ameliorate adverse effects, and monitor community responses.
We inferred the effects of oil exploration activities on predator-prey relationships in boreal Canada where timber and oil extraction is imposing rapid environmental change. We investigated how prey species alter selection in response to oil exploration, and the subsequent effect on predator-prey interactions in an ecosystem comprised of wolves (Canis lupus), coyotes (C. latrans), lynx (Lynx canadensis), snowshoe hare (Lepus americanus), red squirrels (Tamiasciurus hudsonicus), white-tailed deer (Odocoileus virginanus), moose (Alces alces), and threatened woodland caribou (Rangifer tarandus). Using winter track count data, we estimated resource selection models that considered vegetation, terrain, snow, and oil exploration activities. Using the best fit models we then ascertained how oil exploration influenced the distribution of predators and their respective prey.
Results/Conclusions
Resource selection models indicate that predators and prey altered selection in response to active oil exploration (i.e., seismic lines characterized by packed snow) more so than historical exploration. Our data show that snowshoe hare, deer, and moose avoided active seismic lines. In contrast, wolves, coyotes and lynx all selected active seismic lines. Collectively, our data suggest that predators are motivated by a combination of potential prey encounters and energetic savings, whereas prey are motivated by forage and security.
Our results demonstrate that packed snow associated with active oil exploration influences the cost-benefit choices available to boreal predators and prey. The fact that historical oil exploration did not influence predator-prey interactions in our study suggests that managing people may be more effective than managing the vegetation disturbed by seismic lines. For example, managing the distribution of packed snow relative to prey habitat could provide refuge for prey in any given winter. Extending our inferences with mechanistic data (e.g., nutrition and predation risk) and long-term monitoring data would provide additional insight into the ecological relationships linking predator-prey interactions to human activity, and allow managers to monitor the efficacy of land management strategies.