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Evaluating noninvasive genetic sampling techniques to estimate large carnivore abundance

Overview of attention for article published in Molecular Ecology Resources, March 2015
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144 Mendeley
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Article details
Title
Evaluating noninvasive genetic sampling techniques to estimate large carnivore abundance
Published in
Molecular Ecology Resources, March 2015
DOI 10.1111/1755-0998.12390
Pubmed ID
Authors
Abstract

Monitoring large carnivores is difficult because of intrinsically low densities and can be dangerous if physical capture is required. Noninvasive genetic sampling (NGS) is a safe and cost-effective alternative to physical capture. We evaluated the utility of two NGS methods (scat detection dogs and hair sampling) to obtain genetic samples for abundance estimation of coyotes, black bears, and Canada lynx in three areas of Newfoundland, Canada. We calculated abundance estimates using program CAPWIRE, compared sampling costs, and the cost/sample for each method relative to species and study site, and performed simulations to determine the sampling intensity necessary to achieve abundance estimates with coefficients of variation (CV) of <10%. Scat sampling was effective for both coyotes and bears and hair snags effectively sampled bears in two out of three study sites. Rub pads were ineffective in sampling coyotes and lynx. The precision of abundance estimates was dependent upon the number of captures/individual, which was higher for scat. Our simulations suggested that ~3.4 captures/individual will result in a <10% CV for abundance estimates when populations are small (23-39), but fewer captures/individual may be sufficient for larger populations. We found scat sampling was more cost-effective for sampling multiple species, but suggest that hair sampling may be less expensive at study sites with limited road access for bears. Given the dependence of sampling scheme on species and study site, the optimal sampling scheme is likely to be study-specific warranting pilot studies in most circumstances. This article is protected by copyright. All rights reserved.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 144 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 1%
France 2 1%
Unknown 140 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 32 22%
Student > Master 27 19%
Student > Ph. D. Student 23 16%
Student > Bachelor 12 8%
Student > Doctoral Student 5 3%
Other 16 11%
Unknown 29 20%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 72 50%
Environmental Science 20 14%
Biochemistry, Genetics and Molecular Biology 8 6%
Engineering 3 2%
Veterinary Science and Veterinary Medicine 1 <1%
Other 5 3%
Unknown 35 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 September 2015.
All research outputs
#17,727,296
of 30,050,033 outputs
Outputs from Molecular Ecology Resources
#1,317
of 2,017 outputs
Outputs of similar age
#140,308
of 278,178 outputs
Outputs of similar age from Molecular Ecology Resources
#26
of 38 outputs
Altmetric has tracked 30,050,033 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,017 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 278,178 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.