Literature DB >> 17960243

Revisiting Lévy flight search patterns of wandering albatrosses, bumblebees and deer.

Andrew M Edwards1, Richard A Phillips, Nicholas W Watkins, Mervyn P Freeman, Eugene J Murphy, Vsevolod Afanasyev, Sergey V Buldyrev, M G E da Luz, E P Raposo, H Eugene Stanley, Gandhimohan M Viswanathan.   

Abstract

The study of animal foraging behaviour is of practical ecological importance, and exemplifies the wider scientific problem of optimizing search strategies. Lévy flights are random walks, the step lengths of which come from probability distributions with heavy power-law tails, such that clusters of short steps are connected by rare long steps. Lévy flights display fractal properties, have no typical scale, and occur in physical and chemical systems. An attempt to demonstrate their existence in a natural biological system presented evidence that wandering albatrosses perform Lévy flights when searching for prey on the ocean surface. This well known finding was followed by similar inferences about the search strategies of deer and bumblebees. These pioneering studies have triggered much theoretical work in physics (for example, refs 11, 12), as well as empirical ecological analyses regarding reindeer, microzooplankton, grey seals, spider monkeys and fishing boats. Here we analyse a new, high-resolution data set of wandering albatross flights, and find no evidence for Lévy flight behaviour. Instead we find that flight times are gamma distributed, with an exponential decay for the longest flights. We re-analyse the original albatross data using additional information, and conclude that the extremely long flights, essential for demonstrating Lévy flight behaviour, were spurious. Furthermore, we propose a widely applicable method to test for power-law distributions using likelihood and Akaike weights. We apply this to the four original deer and bumblebee data sets, finding that none exhibits evidence of Lévy flights, and that the original graphical approach is insufficient. Such a graphical approach has been adopted to conclude Lévy flight movement for other organisms, and to propose Lévy flight analysis as a potential real-time ecosystem monitoring tool. Our results question the strength of the empirical evidence for biological Lévy flights.

Entities:  

Mesh:

Year:  2007        PMID: 17960243     DOI: 10.1038/nature06199

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  187 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.  Fitness-maximizing foragers can use information about patch quality to decide how to search for and within patches: optimal Levy walk searching patterns from optimal foraging theory.

Authors:  A M Reynolds
Journal:  J R Soc Interface       Date:  2012-01-18       Impact factor: 4.118

3.  Foraging success of biological Lévy flights recorded in situ.

Authors:  Nicolas E Humphries; Henri Weimerskirch; Nuno Queiroz; Emily J Southall; David W Sims
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-23       Impact factor: 11.205

4.  Stochastic coordination of multiple actuators reduces latency and improves chemotactic response in bacteria.

Authors:  Michael W Sneddon; William Pontius; Thierry Emonet
Journal:  Proc Natl Acad Sci U S A       Date:  2011-12-27       Impact factor: 11.205

5.  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

6.  A framework for understanding the architecture of collective movements using pairwise analyses of animal movement data.

Authors:  Leo Polansky; George Wittemyer
Journal:  J R Soc Interface       Date:  2010-09-08       Impact factor: 4.118

7.  Parallel adaptation: one or many waves of advance of an advantageous allele?

Authors:  Peter Ralph; Graham Coop
Journal:  Genetics       Date:  2010-07-26       Impact factor: 4.562

8.  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

9.  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

10.  Mechanistic analysis of the search behaviour of Caenorhabditis elegans.

Authors:  Liliana C M Salvador; Frederic Bartumeus; Simon A Levin; William S Ryu
Journal:  J R Soc Interface       Date:  2014-01-15       Impact factor: 4.118

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.