Stochastic optimal foraging : tuning intensive and extensive dynamics in random searches
Bartumeus, Frederic (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Raposo, Ernesto P. (Universidade Federal de Pernambuco. Departamento de Fisica)
Viswanathan, Gandhimohan M. (Universidade do Estado do Rio Grande do Norte (Brasil). Departamento de Física Teórica e Experimental)
Luz, Marcos G. E. da (Universidade Federal do Paraná. Departamento de Física)

Fecha:	2014
Resumen:	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.
Ayudas:	Ministerio de Ciencia e Innovación BFU-2010-22337
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Publicado en:	PloS one, Vol. 9, issue 9 (Set. 2014) , e106373, ISSN 1932-6203

DOI: 10.1371/journal.pone.0106373
PMID: 25216191

11 p, 1.1 MB

El registro aparece en las colecciones:
Documentos de investigación > Documentos de los grupos de investigación de la UAB > Centros y grupos de investigación (producción científica) > Ciencias > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Artículos > Artículos de investigación
Artículos > Artículos publicados