Predicting Bald Eagle Collision at Wind Energy Facilities
ABSTRACT Bald eagles ( Haliaeetus leucocephalus ) are currently protected in the United States under the Bald and Golden Eagle Protection Act of 1940 and Migratory Bird Treaty Act of 1918. Given these protections and the increasing development of wind energy throughout the United States, it is impor...
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crwiley:10.1002/jwmg.21994 2024-06-02T08:15:58+00:00 Predicting Bald Eagle Collision at Wind Energy Facilities Nasman, Kristen Bay, Kimberly Mattson, Todd Leckband, Jesse Becker, Drew 2021 http://dx.doi.org/10.1002/jwmg.21994 https://onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.21994 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/jwmg.21994 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor The Journal of Wildlife Management volume 85, issue 3, page 520-530 ISSN 0022-541X 1937-2817 journal-article 2021 crwiley https://doi.org/10.1002/jwmg.21994 2024-05-03T11:22:06Z ABSTRACT Bald eagles ( Haliaeetus leucocephalus ) are currently protected in the United States under the Bald and Golden Eagle Protection Act of 1940 and Migratory Bird Treaty Act of 1918. Given these protections and the increasing development of wind energy throughout the United States, it is important for regulators and the wind industry to understand the risk of bald eagle collisions with wind turbines. Prior probability distributions for eagle exposure rates and collision rates have been developed for golden eagles ( Aquila chrysaetos ) by the United States Fish and Wildlife Service (USFWS). Given similar information has not been available for bald eagles, the current recommendation by the USFWS is to use the prior probability distributions developed using data collected on golden eagles to predict take for bald eagles. But some evidence suggests that bald and golden eagles may be at different risk for collision with wind turbines and the prior probability distributions developed for golden eagles may not be appropriate for bald eagles. We developed prior probability distributions using data collected at MidAmerican Energy Company's operating wind energy facilities in Iowa, USA, from December 2014 to March 2017 for bald eagle exposure rates and collision rates. The prior probability distribution for collision rate developed for bald eagles has a lower mean collision rate and less variability relative to that developed for golden eagles. We determined that the prior probability distributions specific to bald eagles from these operating facilities are a better starting point for predicting take for bald eagles at operating wind energy facilities in an agricultural landscape than those developed for golden eagles. © 2021 The Wildlife Society. Article in Journal/Newspaper Aquila chrysaetos golden eagle Wiley Online Library The Journal of Wildlife Management 85 3 520 530 |
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Wiley Online Library |
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crwiley |
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English |
description |
ABSTRACT Bald eagles ( Haliaeetus leucocephalus ) are currently protected in the United States under the Bald and Golden Eagle Protection Act of 1940 and Migratory Bird Treaty Act of 1918. Given these protections and the increasing development of wind energy throughout the United States, it is important for regulators and the wind industry to understand the risk of bald eagle collisions with wind turbines. Prior probability distributions for eagle exposure rates and collision rates have been developed for golden eagles ( Aquila chrysaetos ) by the United States Fish and Wildlife Service (USFWS). Given similar information has not been available for bald eagles, the current recommendation by the USFWS is to use the prior probability distributions developed using data collected on golden eagles to predict take for bald eagles. But some evidence suggests that bald and golden eagles may be at different risk for collision with wind turbines and the prior probability distributions developed for golden eagles may not be appropriate for bald eagles. We developed prior probability distributions using data collected at MidAmerican Energy Company's operating wind energy facilities in Iowa, USA, from December 2014 to March 2017 for bald eagle exposure rates and collision rates. The prior probability distribution for collision rate developed for bald eagles has a lower mean collision rate and less variability relative to that developed for golden eagles. We determined that the prior probability distributions specific to bald eagles from these operating facilities are a better starting point for predicting take for bald eagles at operating wind energy facilities in an agricultural landscape than those developed for golden eagles. © 2021 The Wildlife Society. |
format |
Article in Journal/Newspaper |
author |
Nasman, Kristen Bay, Kimberly Mattson, Todd Leckband, Jesse Becker, Drew |
spellingShingle |
Nasman, Kristen Bay, Kimberly Mattson, Todd Leckband, Jesse Becker, Drew Predicting Bald Eagle Collision at Wind Energy Facilities |
author_facet |
Nasman, Kristen Bay, Kimberly Mattson, Todd Leckband, Jesse Becker, Drew |
author_sort |
Nasman, Kristen |
title |
Predicting Bald Eagle Collision at Wind Energy Facilities |
title_short |
Predicting Bald Eagle Collision at Wind Energy Facilities |
title_full |
Predicting Bald Eagle Collision at Wind Energy Facilities |
title_fullStr |
Predicting Bald Eagle Collision at Wind Energy Facilities |
title_full_unstemmed |
Predicting Bald Eagle Collision at Wind Energy Facilities |
title_sort |
predicting bald eagle collision at wind energy facilities |
publisher |
Wiley |
publishDate |
2021 |
url |
http://dx.doi.org/10.1002/jwmg.21994 https://onlinelibrary.wiley.com/doi/pdf/10.1002/jwmg.21994 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/jwmg.21994 |
genre |
Aquila chrysaetos golden eagle |
genre_facet |
Aquila chrysaetos golden eagle |
op_source |
The Journal of Wildlife Management volume 85, issue 3, page 520-530 ISSN 0022-541X 1937-2817 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/jwmg.21994 |
container_title |
The Journal of Wildlife Management |
container_volume |
85 |
container_issue |
3 |
container_start_page |
520 |
op_container_end_page |
530 |
_version_ |
1800740292249255936 |