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Quantitative tools for implementing the new definition of significant portion of the range in the U.S. Endangered Species Act

Overview of attention for article published in Conservation Biology, October 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Quantitative tools for implementing the new definition of significant portion of the range in the U.S. Endangered Species Act
Published in
Conservation Biology, October 2017
DOI 10.1111/cobi.12963
Pubmed ID
Authors

Julia E. Earl, Sam Nicol, Ruscena Wiederholt, Jay E. Diffendorfer, Darius Semmens, D. T. Tyler Flockhart, Brady J. Mattsson, Gary McCracken, D. Ryan Norris, Wayne E. Thogmartin, Laura López‐Hoffman

Abstract

In July 2014, the U.S. Fish and Wildlife Service and National Marine Fisheries Service announced a new policy interpretation for the Endangered Species Act. According to the Act, a species must be listed as threatened or endangered if it is determined to be threatened or endangered in a significant portion of its range. The 1973 law does not define "significant portion of its range," leading to concerns that interpretations of "significant" by federal agencies and the courts could be inconsistent. The 2014 policy seeks to provide consistency by establishing that a portion of the range should be considered significant if the associated individuals' "removal would cause the entire species to become endangered or threatened." Here, we review quantitative techniques to assess whether a portion of a species' range is significant according to the new guidance. Our assessments are based on the "3R" criteria - Redundancy (i.e., buffering from catastrophe), Resiliency (i.e., ability to withstand stochasticity), and Representation (i.e., ability to evolve) - that the Fish and Wildlife Service uses to determine if a species merits listing. We identify data needs for each quantitative technique and indicate which methods might be implemented given the data limitations typical of rare species. We also identify proxies that may be used with limited data. To assess potential data availability, we evaluate seven example species by assessing the data in their Species Status Assessments, which document all the information used during a listing decision. Our evaluation suggests that resiliency assessments will likely be most constrained by limited data. While we reviewed quantitative techniques for the US Endangered Species Act, other countries have legislation requiring identification of significant areas that could benefit from this research. This article is protected by copyright. All rights reserved.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 29%
Student > Ph. D. Student 13 19%
Student > Master 9 13%
Professor 4 6%
Other 4 6%
Other 7 10%
Unknown 11 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 49%
Environmental Science 15 22%
Biochemistry, Genetics and Molecular Biology 2 3%
Nursing and Health Professions 1 1%
Economics, Econometrics and Finance 1 1%
Other 2 3%
Unknown 14 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 20 January 2018.
All research outputs
#5,102,819
of 24,932,492 outputs
Outputs from Conservation Biology
#1,980
of 4,017 outputs
Outputs of similar age
#84,624
of 334,998 outputs
Outputs of similar age from Conservation Biology
#29
of 40 outputs
Altmetric has tracked 24,932,492 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,017 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.0. This one has gotten more attention than average, scoring higher than 50% 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 334,998 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.