Variation in life history and demography across a species' range informs researchers about regional adaptations and affects whether managers can borrow information from other populations in decision‐making. The American black bear (Ursus americanus) is a long‐lived game species whose continued persistence depends on management of harvest and removal of habituated bears that come into conflict with humans. Understanding the demography of black bears guides efforts at management and conservation, yet detailed knowledge of many populations is typically lacking. I performed a hierarchical Bayesian meta‐analysis of black bear demographic studies across the geographic range of the species to explore how vital rates vary across the range, what information they give us about population growth, and whether managers can justify borrowing information from other studies to inform management decisions. Cub, yearling, and adult survival and fecundity varied between eastern and western North America, whereas subadult survival did not show geographic structuring. Adult survival and fecundity appeared to trade off, with higher survival in the western portions of bears' range and higher fecundity in the east. Although adult survival had the highest elasticity, differences in reproduction drove differences in population growth rate. Mean population growth rate was higher in the east (0.99; 95% credible interval [CrI]: 0.96, 1.03) than the west (0.97; 95%CrI: 0.93, 1.01). Despite declining trends in the west, 34% of the distribution of population growth rate was >1, compared to 55% in the east. Further work needs to be done to address the cause of the apparent trade‐off between adult survival and fecundity and explore how the estimated growth rates are likely to affect population status of black bears. Because population growth rates are close to 1 and small deviations could impact whether a population is considered increasing or decreasing, managers need to employ caution in borrowing vital rates from other populations. © 2011 The Wildlife Society.

Recent growth in the wind energy industry has increased concerns about its impacts on wildlife populations. Direct impacts of wind energy include bird and bat collisions with turbines whereas indirect impacts include changes in wildlife habitat and behavior. Although many species may withstand these effects, species that are long-lived with low rates of reproduction, have specialized habitat preferences, or are attracted to turbines may be more prone to declines in population abundance. We developed a prioritization system to identify the avian species most likely to experience population declines from wind facilities based on their current conservation status and their expected risk from turbines. We developed 3 metrics of turbine risk that incorporate data on collision fatalities at wind facilities, population size, life history, species’ distributions relative to turbine locations, number of suitable habitat types, and species’ conservation status. We calculated at least 1 measure of turbine risk for 428 avian species that breed in the United States. We then simulated 100,000 random sets of cutoff criteria (i.e., the metric values used to assign species to different priority categories) for each turbine risk metric and for conservation status. For each set of criteria, we assigned each species a priority score and calculated the average priority score across all sets of criteria. Our prioritization system highlights both species that could potentially experience population decline caused by wind energy and species at low risk of population decline. For instance, several birds of prey, such as the long-eared owl, ferruginous hawk, Swainson’s hawk, and golden eagle, were at relatively high risk of population decline across a wide variety of cutoff values, whereas many passerines were at relatively low risk of decline. This prioritization system is a first step that will help researchers, conservationists, managers, and industry target future study and management activity.

Hundreds of thousands of bats are killed annually by colliding with wind turbines in the U.S., yet little is known about factors causing variation in mortality across wind energy facilities. We conducted a quantitative synthesis of bat collision mortality with wind turbines by reviewing 218 North American studies representing 100 wind energy facilities. This data set, the largest compiled for bats to date, provides further support that collision mortality is greatest for migratory treeroosting species (Hoary Bat [Lasiurus cinereus], Eastern Red Bat [Lasiurus borealis], Silver-haired Bat [Lasionycteris noctivagans]) and from July to October.