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Homogenization of Large-Scale Movement Models in Ecology

Overview of attention for article published in Bulletin of Mathematical Biology, January 2011
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Title
Homogenization of Large-Scale Movement Models in Ecology
Published in
Bulletin of Mathematical Biology, January 2011
DOI 10.1007/s11538-010-9612-6
Pubmed ID
Authors

Martha J. Garlick, James A. Powell, Mevin B. Hooten, Leslie R. McFarlane

Abstract

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Germany 2 3%
Canada 2 3%
Brazil 1 2%
Finland 1 2%
Unknown 54 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 30%
Student > Ph. D. Student 12 19%
Professor > Associate Professor 6 10%
Student > Master 6 10%
Student > Postgraduate 5 8%
Other 10 16%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 49%
Environmental Science 8 13%
Mathematics 7 11%
Medicine and Dentistry 3 5%
Computer Science 3 5%
Other 4 6%
Unknown 7 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 November 2011.
All research outputs
#15,234,609
of 22,651,245 outputs
Outputs from Bulletin of Mathematical Biology
#720
of 1,094 outputs
Outputs of similar age
#140,016
of 180,239 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#6
of 9 outputs
Altmetric has tracked 22,651,245 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,094 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 22nd percentile – i.e., 22% 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 180,239 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.