Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.

Recent theoretical developments had laid down the proper mathematical means to understand how the structural complexity of search patterns may improve foraging efficiency. Under information-deprived scenarios and specific landscape configurations, Lévy walks and flights are known to lead to high sea...

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Main Authors: Frederic Bartumeus, Ernesto P Raposo, Gandhimohan M Viswanathan, Marcos G E da Luz
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4162546?pdf=render
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spelling doaj-38f43d51b79d46fb8d20467ee964592d2020-11-25T02:47:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0199e10637310.1371/journal.pone.0106373Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.Frederic BartumeusErnesto P RaposoGandhimohan M ViswanathanMarcos G E da LuzRecent theoretical developments had laid down the proper mathematical means to understand how the structural complexity of search patterns may improve foraging efficiency. Under information-deprived scenarios and specific landscape configurations, Lévy walks and flights are known to lead to high search efficiencies. Based on a one-dimensional comparative analysis we show a mechanism by which, at random, a searcher can optimize the encounter with close and distant targets. The mechanism consists of combining an optimal diffusivity (optimally enhanced diffusion) with a minimal diffusion constant. In such a way the search dynamics adequately balances the tension between finding close and distant targets, while, at the same time, shifts the optimal balance towards relatively larger close-to-distant target encounter ratios. We find that introducing a multiscale set of reorientations ensures both a thorough local space exploration without oversampling and a fast spreading dynamics at the large scale. Lévy reorientation patterns account for these properties but other reorientation strategies providing similar statistical signatures can mimic or achieve comparable efficiencies. Hence, the present work unveils general mechanisms underlying efficient random search, beyond the Lévy model. Our results suggest that animals could tune key statistical movement properties (e.g. enhanced diffusivity, minimal diffusion constant) to cope with the very general problem of balancing out intensive and extensive random searching. We believe that theoretical developments to mechanistically understand stochastic search strategies, such as the one here proposed, are crucial to develop an empirically verifiable and comprehensive animal foraging theory.http://europepmc.org/articles/PMC4162546?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Frederic Bartumeus
Ernesto P Raposo
Gandhimohan M Viswanathan
Marcos G E da Luz
spellingShingle Frederic Bartumeus
Ernesto P Raposo
Gandhimohan M Viswanathan
Marcos G E da Luz
Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
PLoS ONE
author_facet Frederic Bartumeus
Ernesto P Raposo
Gandhimohan M Viswanathan
Marcos G E da Luz
author_sort Frederic Bartumeus
title Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
title_short Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
title_full Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
title_fullStr Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
title_full_unstemmed Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
title_sort stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description Recent theoretical developments had laid down the proper mathematical means to understand how the structural complexity of search patterns may improve foraging efficiency. Under information-deprived scenarios and specific landscape configurations, Lévy walks and flights are known to lead to high search efficiencies. Based on a one-dimensional comparative analysis we show a mechanism by which, at random, a searcher can optimize the encounter with close and distant targets. The mechanism consists of combining an optimal diffusivity (optimally enhanced diffusion) with a minimal diffusion constant. In such a way the search dynamics adequately balances the tension between finding close and distant targets, while, at the same time, shifts the optimal balance towards relatively larger close-to-distant target encounter ratios. We find that introducing a multiscale set of reorientations ensures both a thorough local space exploration without oversampling and a fast spreading dynamics at the large scale. Lévy reorientation patterns account for these properties but other reorientation strategies providing similar statistical signatures can mimic or achieve comparable efficiencies. Hence, the present work unveils general mechanisms underlying efficient random search, beyond the Lévy model. Our results suggest that animals could tune key statistical movement properties (e.g. enhanced diffusivity, minimal diffusion constant) to cope with the very general problem of balancing out intensive and extensive random searching. We believe that theoretical developments to mechanistically understand stochastic search strategies, such as the one here proposed, are crucial to develop an empirically verifiable and comprehensive animal foraging theory.
url http://europepmc.org/articles/PMC4162546?pdf=render
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