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Trap Configuration and Spacing Influences Parameter Estimates in Spatial Capture-Recapture Models

Overview of attention for article published in PLoS ONE, February 2014
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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3 tweeters

Citations

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78 Dimensions

Readers on

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256 Mendeley
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1 CiteULike
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Title
Trap Configuration and Spacing Influences Parameter Estimates in Spatial Capture-Recapture Models
Published in
PLoS ONE, February 2014
DOI 10.1371/journal.pone.0088025
Pubmed ID
Authors

Catherine C. Sun, Angela K. Fuller, J. Andrew Royle

Abstract

An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 256 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Australia 2 <1%
India 2 <1%
New Zealand 1 <1%
Mexico 1 <1%
Japan 1 <1%
Austria 1 <1%
Unknown 242 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 60 23%
Student > Ph. D. Student 53 21%
Researcher 50 20%
Student > Bachelor 21 8%
Student > Doctoral Student 14 5%
Other 46 18%
Unknown 12 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 148 58%
Environmental Science 62 24%
Earth and Planetary Sciences 5 2%
Mathematics 4 2%
Biochemistry, Genetics and Molecular Biology 4 2%
Other 10 4%
Unknown 23 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 March 2014.
All research outputs
#7,399,034
of 12,826,608 outputs
Outputs from PLoS ONE
#71,467
of 139,134 outputs
Outputs of similar age
#106,160
of 241,696 outputs
Outputs of similar age from PLoS ONE
#3,749
of 8,349 outputs
Altmetric has tracked 12,826,608 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 139,134 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.8. This one is in the 44th percentile – i.e., 44% 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 241,696 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 53% of its contemporaries.
We're also able to compare this research output to 8,349 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.