Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay
Arctic marine mammals are harvested by Indigenous people for subsistence and are socially and culturally important. For ice-dependent species like the polar bear Ursus maritimus, management and conservation require understanding interactions between harvest and sea-ice loss due to climate change. We developed a demographic model to evaluate harvest risk for polar bears in Southern Hudson Bay, Canada, where the annual ice-free season has increased by approximately one month in recent decades. The model was based on the theta-logistic equation and allowed for density-dependent changes (through carrying capacity [K]) and density-independent changes (through population growth rate [r]). Model parameters were estimated using a Bayesian Monte Carlo method that included capture-recapture, aerial survey, and harvest data. Harvest management followed a state-dependent approach under which new estimates of abundance were used to update the harvest level every five years. Under a middle-of-the-road environmental scenario that assumed K and r would decline in proportion to projected sea-ice declines, annual removal of 0.02–0.03 of females resulted in a 0.8 probability of maintaining subpopulation abundance above maximum net productivity level for three polar bear generations (~34 years), our primary criterion for sustainability. Under more pessimistic and optimistic environmental scenarios, comparable female harvest rates were 0.01 and 0.055, respectively. Our coupled modeling-management framework can be used to inform tradeoffs between protection and sustainable use for wildlife populations experiencing habitat loss.
|Incorporating climate change in a harvest risk assessment for polar bears Ursus maritimus in Southern Hudson Bay
|Eric V. Regehr, Markus Dyck, Samuel A. Iverson, David S. Lee, Nicholas J Lunn, Joseph M Northrup, Marie-Claude Richer, Guillaume Szor, Michael C. Runge
|USGS Publications Warehouse
|Eastern Ecological Science Center