Normandeau Rolls Out Wind-Wildlife Collision-Risk Model

NAW Staff, Wednesday 06 February 2013 - 12:04:07

Normandeau Associates Inc. says it has developed a spatial avian- and bat-collision-risk model for wind resource areas in the central U.S.

Wildlife managers, government agencies and wind energy developers can use this tool to conduct large-scale pre-construction studies and assist with federal and state regulatory compliance, the company says. Normandeau created and tested this empirical collision-risk model during a two-and-a-half year project funded by the U.S. Department of Energy.

"The collision-risk model was based on identifying each species' preferred habitat and other environmental conditions that would increase exposure to wind turbines, such as weather and topography in the landscape," explains Dr. Greg Forcey, Normandeau project manager and senior ecologist.

Potentially risky behaviors (e.g., migratory or mating display flights) are factored into the model, creating a spatiotemporal prediction of when and where particular species would be most at risk from collision.

The study examined landscape-level influences using a hierarchical spatial model, combined with existing data sets and life history knowledge, for six bird and three bat species (horned lark, red-eyed vireo, mallard, American avocet, golden eagle, whooping crane, eastern red bat, hoary bat and silver-haired bat) in the Upper Great Plains region.

Normandeau evaluated the tool's effectiveness by comparing model predictions with available mortality data for four focal species - horned lark, eastern red bat, silver-haired bat and hoary bat. For the three bat species, there was a 90% correlation between existing post-construction mortality data and predicted risk, and for the horned lark there was a 55% correlation, Normandeau says.

"Based on model results, developers can make informed large-scale decisions about wind turbine siting - ensuring the best outcomes for the wind industry, the public and wildlife," Forcey says.

A Web-based interface allows users to identify higher-risk locations for the nine species studied. The tool can be adapted for other species and habitats in different geographic areas if desired.



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