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Landscapes for Energy and Wildlife: Conservation Prioritization for Golden Eagles across Large Spatial Scales

Overview of attention for article published in PLOS ONE, August 2015
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
9 news outlets
blogs
4 blogs
twitter
7 X users

Citations

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21 Dimensions

Readers on

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86 Mendeley
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Title
Landscapes for Energy and Wildlife: Conservation Prioritization for Golden Eagles across Large Spatial Scales
Published in
PLOS ONE, August 2015
DOI 10.1371/journal.pone.0134781
Pubmed ID
Authors

Jason D. Tack, Bradley C. Fedy

Abstract

Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 1%
Unknown 85 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 29%
Student > Master 14 16%
Student > Ph. D. Student 11 13%
Other 7 8%
Student > Bachelor 5 6%
Other 13 15%
Unknown 11 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 49%
Environmental Science 22 26%
Unspecified 1 1%
Chemical Engineering 1 1%
Computer Science 1 1%
Other 3 3%
Unknown 16 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 104. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 January 2016.
All research outputs
#382,159
of 24,394,820 outputs
Outputs from PLOS ONE
#5,450
of 210,420 outputs
Outputs of similar age
#4,496
of 268,987 outputs
Outputs of similar age from PLOS ONE
#128
of 6,141 outputs
Altmetric has tracked 24,394,820 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 210,420 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,987 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 6,141 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.