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Analytic steady-state space use patterns and rapid computations in mechanistic home range analysis

Overview of attention for article published in Journal of Mathematical Biology, December 2007
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Title
Analytic steady-state space use patterns and rapid computations in mechanistic home range analysis
Published in
Journal of Mathematical Biology, December 2007
DOI 10.1007/s00285-007-0149-8
Pubmed ID
Authors

Alex H. Barnett, Paul R. Moorcroft

Abstract

Mechanistic home range models are important tools in modeling animal dynamics in spatially complex environments. We introduce a class of stochastic models for animal movement in a habitat of varying preference. Such models interpolate between spatially implicit resource selection analysis (RSA) and advection-diffusion models, possessing these two models as limiting cases. We find a closed-form solution for the steady-state (equilibrium) probability distribution u using a factorization of the redistribution operator into symmetric and diagonal parts. How space use is controlled by the habitat preference function w depends on the characteristic width of the animals' redistribution kernel: when the redistribution kernel is wide relative to variation in w, u proportional, variant w, whereas when it is narrow relative to variation in w, u proportional, variant w (2). In addition, we analyze the behavior at discontinuities in w which occur at habitat type boundaries, and simulate the dynamics of space use given two-dimensional prey-availability data, exploring the effect of the redistribution kernel width. Our factorization allows such numerical simulations to be done extremely fast; we expect this to aid the computationally intensive task of model parameter fitting and inverse modeling.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 4%
United States 2 2%
Bulgaria 1 1%
Germany 1 1%
Canada 1 1%
United Kingdom 1 1%
Unknown 85 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 32%
Student > Ph. D. Student 20 21%
Student > Master 10 11%
Student > Bachelor 7 7%
Professor > Associate Professor 6 6%
Other 14 15%
Unknown 8 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 52 55%
Environmental Science 19 20%
Engineering 3 3%
Computer Science 2 2%
Earth and Planetary Sciences 2 2%
Other 6 6%
Unknown 11 12%
Attention Score in Context

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 13 November 2020.
All research outputs
#14,196,917
of 22,757,090 outputs
Outputs from Journal of Mathematical Biology
#281
of 655 outputs
Outputs of similar age
#129,229
of 155,786 outputs
Outputs of similar age from Journal of Mathematical Biology
#2
of 3 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 655 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 53% of its peers.
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