A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos

Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is...

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Main Authors: Leslie New, Emily Bjerre, Brian Millsap, Mark C Otto, Michael C Runge
Format: Article in Journal/Newspaper
Language:unknown
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Online Access:https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130978
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0130978&type=printable
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spelling ftrepec:oai:RePEc:plo:pone00:0130978 2023-05-15T18:49:21+02:00 A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos Leslie New Emily Bjerre Brian Millsap Mark C Otto Michael C Runge https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130978 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0130978&type=printable unknown https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130978 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0130978&type=printable article ftrepec 2020-12-04T13:35:37Z Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6.3). In this case, the increased precision in the fatality prediction lowered the level of authorized take, and thus lowered the required amount of compensatory mitigation. Article in Journal/Newspaper Aquila chrysaetos golden eagle RePEc (Research Papers in Economics)
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6.3). In this case, the increased precision in the fatality prediction lowered the level of authorized take, and thus lowered the required amount of compensatory mitigation.
format Article in Journal/Newspaper
author Leslie New
Emily Bjerre
Brian Millsap
Mark C Otto
Michael C Runge
spellingShingle Leslie New
Emily Bjerre
Brian Millsap
Mark C Otto
Michael C Runge
A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos
author_facet Leslie New
Emily Bjerre
Brian Millsap
Mark C Otto
Michael C Runge
author_sort Leslie New
title A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos
title_short A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos
title_full A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos
title_fullStr A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos
title_full_unstemmed A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos
title_sort collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, aquila chrysaetos
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130978
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0130978&type=printable
genre Aquila chrysaetos
golden eagle
genre_facet Aquila chrysaetos
golden eagle
op_relation https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130978
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0130978&type=printable
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