Executive SummaryWind energy is a rapidly growing and relatively clean source of renewable energy, which can ultimately meet growing demands for electricity in the US (Manville 2005). Despite the large potential for wind energy production in the US (AWEA 2009) and the minimal carbon emissions that occur from producing this power, the proliferation of wind energy has some drawbacks, including land disturbance caused by the installation of a wind facility, potential decline in aesthetics of a landscape, difficulty in attaining public acceptance, and threats to aerial and terrestrial wildlife (Kunz et al. 2007a;Kuvlesky et al. 2007). Wind project facilities pose two possible hazards to wildlife: the potential for mortality (i.e., collisions with wind turbines and associated power lines) and the potential for habitat effects (Kuvlesky et al. 2007). While both collisions and habitat effects can impact wildlife, this study examined collision hazards only; other studies currently being funded by the US Department of Energy (DOE) are examining habitat displacement effects.Most previous studies on collision impacts at wind facilities have taken place at the site-specific level and have only examined small-scale influences on mortality. In this study, we examine landscape-level influences using a hierarchical spatial model combined with existing datasets and life history knowledge for six bird and three bat species: Horned Lark, Red-eyed Vireo, Mallard, American Avocet, Golden Eagle, Whooping Crane, red bat, silver-haired bat, and hoary bat. These species were modeled in the central United States within Bird Conservation Regions 11, 17, 18, and 19 (NABCI 2012). For the bird species, we modeled bird abundance from existing datasets as a function of habitat variables known to be preferred by each species to develop a relative abundance prediction for each species. For bats, there are no existing abundance datasets so we identified preferred habitat in the landscape for each species and assumed that greater amounts of preferred habitat would equate to greater abundance of bats. The abundance predictions for bird and bats were modeled with additional exposure factors known to influence collisions such as visibility, wind, temperature, precipitation, topography, and behavior to form a final mapped output of predicted collision risk within the study region. Separate collision models were derived for each season given differences in habitat and behavior across seasons; season-specific models were combined to form a cumulative model representing collision risk throughout the year. To evaluate our collision predictions, we reviewed published mortality studies from wind farms in our study region and collected data on reported mortality of our focal species to compare to our modeled predictions. Because of the uncertainty with the degree to which abundance and exposure factors influence collision risk, we performed a sensitivity analysis evaluating model performance of 6 different scenarios where habitat and exposure factors were w...