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How Landscape Heterogeneity Frames Optimal Diffusivity in Searching Processes

Overview of attention for article published in PLoS Computational Biology, November 2011
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Title
How Landscape Heterogeneity Frames Optimal Diffusivity in Searching Processes
Published in
PLoS Computational Biology, November 2011
DOI 10.1371/journal.pcbi.1002233
Pubmed ID
Authors

E. P. Raposo, F. Bartumeus, M. G. E. da Luz, P. J. Ribeiro-Neto, T. A. Souza, G. M. Viswanathan

Abstract

Theoretical and empirical investigations of search strategies typically have failed to distinguish the distinct roles played by density versus patchiness of resources. It is well known that motility and diffusivity of organisms often increase in environments with low density of resources, but thus far there has been little progress in understanding the specific role of landscape heterogeneity and disorder on random, non-oriented motility. Here we address the general question of how the landscape heterogeneity affects the efficiency of encounter interactions under global constant density of scarce resources. We unveil the key mechanism coupling the landscape structure with optimal search diffusivity. In particular, our main result leads to an empirically testable prediction: enhanced diffusivity (including superdiffusive searches), with shift in the diffusion exponent, favors the success of target encounters in heterogeneous landscapes.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
Portugal 2 4%
United States 1 2%
New Zealand 1 2%
Unknown 48 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 26%
Researcher 10 19%
Student > Master 7 13%
Professor > Associate Professor 5 9%
Professor 5 9%
Other 6 11%
Unknown 7 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 30%
Physics and Astronomy 10 19%
Environmental Science 6 11%
Engineering 5 9%
Mathematics 2 4%
Other 7 13%
Unknown 8 15%