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When to stop managing or surveying cryptic threatened species

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, September 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
2 blogs
twitter
4 X users
wikipedia
3 Wikipedia pages
reddit
1 Redditor

Citations

dimensions_citation
156 Dimensions

Readers on

mendeley
448 Mendeley
citeulike
2 CiteULike
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1 Connotea
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Title
When to stop managing or surveying cryptic threatened species
Published in
Proceedings of the National Academy of Sciences of the United States of America, September 2008
DOI 10.1073/pnas.0805265105
Pubmed ID
Authors

Iadine Chadès, Eve McDonald-Madden, Michael A. McCarthy, Brendan Wintle, Matthew Linkie, Hugh P. Possingham

Abstract

Threatened species become increasingly difficult to detect as their populations decline. Managers of such cryptic threatened species face several dilemmas: if they are not sure the species is present, should they continue to manage for that species or invest the limited resources in surveying? We find optimal solutions to this problem using a Partially Observable Markov Decision Process and rules of thumb derived from an analytical approximation. We discover that managing a protected area for a cryptic threatened species can be optimal even if we are not sure the species is present. The more threatened and valuable the species is, relative to the costs of management, the more likely we are to manage this species without determining its continued persistence by using surveys. If a species remains unseen, our belief in the persistence of the species declines to a point where the optimal strategy is to shift resources from saving the species to surveying for it. Finally, when surveys lead to a sufficiently low belief that the species is extant, we surrender resources to other conservation actions. We illustrate our findings with a case study using parameters based on the critically endangered Sumatran tiger (Panthera tigris sumatrae), and we generate rules of thumb on how to allocate conservation effort for any cryptic species. Using Partially Observable Markov Decision Processes in conservation science, we determine the conditions under which it is better to abandon management for that species because our belief that it continues to exist is too low.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 448 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 3%
Brazil 5 1%
United Kingdom 3 <1%
India 3 <1%
Netherlands 2 <1%
Spain 2 <1%
Australia 2 <1%
South Africa 2 <1%
Germany 1 <1%
Other 17 4%
Unknown 397 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 131 29%
Student > Ph. D. Student 76 17%
Student > Master 58 13%
Other 31 7%
Student > Bachelor 27 6%
Other 81 18%
Unknown 44 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 208 46%
Environmental Science 127 28%
Earth and Planetary Sciences 10 2%
Computer Science 9 2%
Engineering 8 2%
Other 27 6%
Unknown 59 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 28 April 2022.
All research outputs
#1,693,466
of 24,625,114 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#22,071
of 101,438 outputs
Outputs of similar age
#3,639
of 80,991 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#98
of 708 outputs
Altmetric has tracked 24,625,114 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 101,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.8. This one has done well, scoring higher than 78% 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 80,991 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 95% of its contemporaries.
We're also able to compare this research output to 708 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.