The U.S. Geological Survey has developed a methodology to assess the impacts of wind energy development on wildlife; it is a probabilistic, quantitative assessment methodology that can communicate to decision makers and the public the magnitude of these effects on species populations. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology is intended to assess species at the national scale and is fundamentally different from existing methods focusing on impacts at individual facilities.
Publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics, and generic population models are used to generate both a ranked list of species based on relative risk as well as quantitative measures of the magnitude of the effect on species' population trend and size. Three metrics are combined to determine direct and indirect relative risk to populations. A generic population model is used to estimate the expected change in population trend and includes additive mortality from collisions with wind turbines. Lastly, the methodology uses observed fatalities and an estimate of potential biological removal to assess the risk of a decline in population size. Data for six bird species have been processed through the entire methodology as a test case, and the results are presented in this report.
Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable. These assumptions are presented in the report and should be carefully considered when using output from the methodology. In addition, this methodology can be used to recommend species for more intensive demographic modeling or highlight those species that may not require any additional protection because effects of wind energy development on their populations are projected to be small.
- Digital Object Identifier: 10.3133/sir20155066
- Source: USGS Publications Warehouse (indexId: sir20155066)