Literature DB >> 17824427

How many animals really do the Lévy walk?

Simon Benhamou1.   

Abstract

Lévy walks (LW) are superdiffusive and scale-free random walks that have recently emerged as a new conceptual tool for modeling animal search paths. They have been claimed to be more efficient than the "classical" random walks, and they also seem able to account for the actual search patterns of various species. This suggests that many animals may move using a LW process. LW patterns look like the actual search patterns displayed by animals foraging in a patchy environment, where extensive and intensive searching modes alternate, and which can be generated by a mixture of classical random walks. In this context, even elementary composite Brownian walks are more efficient than LW but may be confounded with them because they present apparent move-length-heavy tail distributions and superdiffusivity. The move-length "survival" distribution (i.e., the cumulative number of moves greater than any given threshold) appears to be a better means to highlight a LW pattern. Even once such a pattern has been clearly identified, it remains to determine how it was actually generated, because a LW pattern is not necessarily produced by a LW process but may emerge from the way the animal interacted with the environment structure through more classical movement processes. In any case, emergent movement patterns should not be confused with the processes that gave rise to them.

Mesh:

Year:  2007        PMID: 17824427     DOI: 10.1890/06-1769.1

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  93 in total

1.  Predicting oscillatory dynamics in the movement of territorial animals.

Authors:  L Giuggioli; J R Potts; S Harris
Journal:  J R Soc Interface       Date:  2012-01-19       Impact factor: 4.118

2.  Brownian motion or Lévy walk? Stepping towards an extended statistical mechanics for animal locomotion.

Authors:  Arild O Gautestad
Journal:  J R Soc Interface       Date:  2012-03-28       Impact factor: 4.118

3.  Evolutionary optimality in stochastic search problems.

Authors:  Mark D Preston; Jonathan W Pitchford; A Jamie Wood
Journal:  J R Soc Interface       Date:  2010-03-24       Impact factor: 4.118

4.  Environmental context explains Lévy and Brownian movement patterns of marine predators.

Authors:  Nicolas E Humphries; Nuno Queiroz; Jennifer R M Dyer; Nicolas G Pade; Michael K Musyl; Kurt M Schaefer; Daniel W Fuller; Juerg M Brunnschweiler; Thomas K Doyle; Jonathan D R Houghton; Graeme C Hays; Catherine S Jones; Leslie R Noble; Victoria J Wearmouth; Emily J Southall; David W Sims
Journal:  Nature       Date:  2010-06-09       Impact factor: 49.962

Review 5.  Stochastic modelling of animal movement.

Authors:  Peter E Smouse; Stefano Focardi; Paul R Moorcroft; John G Kie; James D Forester; Juan M Morales
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-07-27       Impact factor: 6.237

6.  Sensing and decision-making in random search.

Authors:  Andrew M Hein; Scott A McKinley
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-09       Impact factor: 11.205

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Authors:  Janelle Szary; Rick Dale; Christopher T Kello; Theo Rhodes
Journal:  Cogn Process       Date:  2015-08-28

8.  Scaling law in free walking of mice in circular open fields of various diameters.

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Journal:  J Biol Phys       Date:  2016-01-18       Impact factor: 1.365

9.  A framework for analyzing the robustness of movement models to variable step discretization.

Authors:  Ulrike E Schlägel; Mark A Lewis
Journal:  J Math Biol       Date:  2016-02-06       Impact factor: 2.259

Review 10.  Exploration versus exploitation in space, mind, and society.

Authors:  Thomas T Hills; Peter M Todd; David Lazer; A David Redish; Iain D Couzin
Journal:  Trends Cogn Sci       Date:  2014-12-03       Impact factor: 20.229

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