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Confronting Uncertainty in Wildlife Management: Performance of Grizzly Bear Management

Overview of attention for article published in PLoS ONE, November 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
18 news outlets
blogs
3 blogs
twitter
83 tweeters
facebook
8 Facebook pages
googleplus
3 Google+ users

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
78 Mendeley
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Title
Confronting Uncertainty in Wildlife Management: Performance of Grizzly Bear Management
Published in
PLoS ONE, November 2013
DOI 10.1371/journal.pone.0078041
Pubmed ID
Authors

Kyle A. Artelle, Sean C. Anderson, Andrew B. Cooper, Paul C. Paquet, John D. Reynolds, Chris T. Darimont

Abstract

Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone--discrepancy between expected and realized mortality levels--led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty.

Twitter Demographics

The data shown below were collected from the profiles of 83 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 3%
United Kingdom 1 1%
France 1 1%
Unknown 74 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 18%
Student > Ph. D. Student 14 18%
Researcher 14 18%
Student > Bachelor 8 10%
Unspecified 6 8%
Other 22 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 49%
Environmental Science 19 24%
Unspecified 11 14%
Medicine and Dentistry 3 4%
Social Sciences 2 3%
Other 5 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 230. 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 16 August 2018.
All research outputs
#48,212
of 12,498,674 outputs
Outputs from PLoS ONE
#1,069
of 136,976 outputs
Outputs of similar age
#703
of 179,099 outputs
Outputs of similar age from PLoS ONE
#36
of 4,169 outputs
Altmetric has tracked 12,498,674 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 136,976 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done particularly well, scoring higher than 99% 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 179,099 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 99% of its contemporaries.
We're also able to compare this research output to 4,169 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 99% of its contemporaries.