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Inferring topology from dynamics in spatial networks


Gilarranz, Luis J; Hastings, Alan; Bascompte, Jordi (2015). Inferring topology from dynamics in spatial networks. Theoretical Ecology, 8(1):15-21.

Abstract

We examine the dynamics of oscillating populations in habitats described as networks of connected patches where the connections are not regular. This system would be typically analysed focusing either on the population dynamics, or measuring dispersal directly or indirectly. We focus on the question of the degree to which the dynamical patterns, as reflected in synchrony, reveal the underlying dispersal pathways. This would represent a bridge between two major spatial approaches: topological and dynamical. We show how local populations can be synchronized even if there is no direct dispersal route between them, while the stepping-stone populations are not synchronized. This leads to the surprising result that the topological structure of the underlying network is not reflected simply in patterns of synchrony across space in population dynamics. This shows that, with our current tools, the complex relationship between the underlying dispersal patterns and population dynamics prevent us from determining network structure through the observation of population dynamics.

Abstract

We examine the dynamics of oscillating populations in habitats described as networks of connected patches where the connections are not regular. This system would be typically analysed focusing either on the population dynamics, or measuring dispersal directly or indirectly. We focus on the question of the degree to which the dynamical patterns, as reflected in synchrony, reveal the underlying dispersal pathways. This would represent a bridge between two major spatial approaches: topological and dynamical. We show how local populations can be synchronized even if there is no direct dispersal route between them, while the stepping-stone populations are not synchronized. This leads to the surprising result that the topological structure of the underlying network is not reflected simply in patterns of synchrony across space in population dynamics. This shows that, with our current tools, the complex relationship between the underlying dispersal patterns and population dynamics prevent us from determining network structure through the observation of population dynamics.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:February 2015
Deposited On:05 Feb 2016 14:09
Last Modified:08 Dec 2017 18:03
Publisher:Springer
ISSN:1874-1738
Additional Information:The final publication is available at Springer via http://dx.doi.org/10.1007/s12080-014-0231-y
Publisher DOI:https://doi.org/10.1007/s12080-014-0231-y

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