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Win-Win for Wind and Wildlife: A Vision to Facilitate Sustainable Development

Overview of attention for article published in PLOS ONE, April 2011
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Title
Win-Win for Wind and Wildlife: A Vision to Facilitate Sustainable Development
Published in
PLOS ONE, April 2011
DOI 10.1371/journal.pone.0017566
Pubmed ID
Authors

Joseph M. Kiesecker, Jeffrey S. Evans, Joe Fargione, Kevin Doherty, Kerry R. Foresman, Thomas H. Kunz, Dave Naugle, Nathan P. Nibbelink, Neal D. Niemuth

Abstract

Wind energy offers the potential to reduce carbon emissions while increasing energy independence and bolstering economic development. However, wind energy has a larger land footprint per Gigawatt (GW) than most other forms of energy production, making appropriate siting and mitigation particularly important. Species that require large unfragmented habitats and those known to avoid vertical structures are particularly at risk from wind development. Developing energy on disturbed lands rather than placing new developments within large and intact habitats would reduce cumulative impacts to wildlife. The U.S. Department of Energy estimates that it will take 241 GW of terrestrial based wind development on approximately 5 million hectares to reach 20% electricity production for the U.S. by 2030. We estimate there are ∼7,700 GW of potential wind energy available across the U.S., with ∼3,500 GW on disturbed lands. In addition, a disturbance-focused development strategy would avert the development of ∼2.3 million hectares of undisturbed lands while generating the same amount of energy as development based solely on maximizing wind potential. Wind subsidies targeted at favoring low-impact developments and creating avoidance and mitigation requirements that raise the costs for projects impacting sensitive lands could improve public value for both wind energy and biodiversity conservation.

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Mendeley readers

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Geographical breakdown

Country Count As %
United States 10 4%
Portugal 4 2%
United Kingdom 3 1%
Brazil 2 <1%
Ghana 1 <1%
Australia 1 <1%
South Africa 1 <1%
Unknown 241 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 67 25%
Student > Bachelor 38 14%
Student > Ph. D. Student 37 14%
Student > Master 30 11%
Other 27 10%
Other 31 12%
Unknown 33 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 97 37%
Environmental Science 62 24%
Engineering 31 12%
Social Sciences 6 2%
Earth and Planetary Sciences 5 2%
Other 23 9%
Unknown 39 15%