Predicting survival, reproduction and abundance of polar bears under climate change

0006-3207/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.biocon.2010.04.004 * Corresponding author at: Centre for Mathemat Mathematical and Statistical Sciences, University of A T6G 2G1. Tel.: +1 780 492 6347; fax: +1 780 492 837 E-mail addresses: [email protected] (P.K. Molná Derocher), [email protected] (G.W. Thiemann), ml Lewis). Polar bear (Ursus maritimus) populations are predicted to be negatively affected by climate warming, but the timeframe and manner in which change to polar bear populations will occur remains unclear. Predictions incorporating climate change effects are necessary for proactive populationmanagement, the setting of optimal harvest quotas, and conservation status decisions. Such predictions are difficult to obtain from historic data directly because past and predicted environmental conditions differ substantially. Here, we explore how models can be used to predict polar bear population responses under climate change. We suggest the development of mechanistic models aimed at predicting reproduction and survival as a function of the environment. Such models can often be developed, parameterized, and tested under current environmental conditions. Model predictions for reproduction and survival under future conditions could then be input into demographic projection models to improve abundance predictions under climate change. We illustrate the approach using two examples. First, using an individual-based dynamic energy budget model, we estimate that 3–6% of adult males inWestern Hudson Baywould die of starvation before the end of a 120 day summer fasting period but 28–48%would die if climate warming increases the fasting period to 180 days. Expected changes in survival are non-linear (sigmoid) as a function of fasting period length. Second, we use an encounter rate model to predict changes in female mating probability under sea ice area declines and declines in mate-searching efficiency due to habitat fragmentation. The model predicts that mating success will decline non-linearly if searching efficiency declines faster than habitat area, and increase non-linearly otherwise. Specifically for the Lancaster Sound population, we predict that female mating success would decline from 99% to 91% if searching efficiency declined twice as fast as sea ice area, and to 72% if searching efficiency declined four times as fast as area. Sea ice is a complex and dynamic habitat that is rapidly changing. Failure to incorporate climate change effects into population projections can result in flawed conservation assessments and management decisions. 2010 Elsevier Ltd. All rights reserved.