Discrete and continuous time simulations of spatial ecological processes predict different final population sizes and interspecific competition outcomes

Mancy, R., Prosser, P. and Rogers, S. (2013) Discrete and continuous time simulations of spatial ecological processes predict different final population sizes and interspecific competition outcomes. Ecological Modelling, 259, pp. 50-61. (doi:10.1016/j.ecolmodel.2013.03.013)

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Abstract

Cellular automata (CAs) are commonly used to simulate spatial processes in ecology. Although appropriate for modelling events that occur at discrete time points, they are also routinely used to model biological processes that take place continuously. We report on a study comparing predictions of discrete time CA models to those of their continuous time counterpart. Specifically, we investigate how the decision to model time discretely or continuously affects predictions regarding long-run population sizes, the probability of extinction and interspecific competition. We show effects on predicted ecological outcomes, finding quantitative differences in all cases and in the case of interspecific competition, additional qualitative differences in predictions regarding species dominance. Our findings demonstrate that qualitative conclusions drawn from spatial simulations can be critically dependent on the decision to model time discretely or continuously. Contrary to our expectations, simulating in continuous time did not incur a heavy computational penalty. We also raise ecological questions on the relative benefits of reproductive strategies that take place in discrete and continuous time.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Rogers, Dr Simon and Mancy, Dr Rebecca and Prosser, Dr Patrick
Authors: Mancy, R., Prosser, P., and Rogers, S.
College/School:College of Science and Engineering > School of Computing Science
College of Social Sciences > School of Education > Interdisciplinary Science Education Technologies and Learning
Journal Name:Ecological Modelling
Publisher:Elsevier
ISSN:0304-3800
Published Online:22 April 2013
Copyright Holders:Copyright © 2013 Elsevier B.V.
First Published:First published in Ecological Modelling 259:51-61
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
554791EPSRC Doctoral Training Grant 2010-14Mary Beth KneafseyEngineering & Physical Sciences Research Council (EPSRC)EP/P505534/1VICE PRINCIPAL RESEARCH & ENTERPRISE
554792EPSRC Doctoral Training Grant 2010-14Mary Beth KneafseyEngineering & Physical Sciences Research Council (EPSRC)EP/P505534/1VICE PRINCIPAL RESEARCH & ENTERPRISE
554793EPSRC Doctoral Training Grant 2010-14Mary Beth KneafseyEngineering & Physical Sciences Research Council (EPSRC)EP/P505534/1VICE PRINCIPAL RESEARCH & ENTERPRISE