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Agent-based modelling of clonal plant propagation across space: Recapturing fairy rings, power laws and other phenomena

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Title: Agent-based modelling of clonal plant propagation across space: Recapturing fairy rings, power laws and other phenomena
Author: Wong, Sanders; Anand, Madhur; Bauch, Chris T.
Abstract: Many plants reproduce clonally through vegetative extensions. This results in a patch of clones connected through a network of stems (spacers), with some nontrivial spatial pattern. Here, we build on previous work to develop general growth rules that dictate how individual clones under local density-dependent conditions add vegetative extensions, giving rise to emergent population-level spatial patterns. A population subject to these growth rules is simulated in MATLAB as a stochastic individual-based model. The dependence of network architecture on various individual level growth parameters is explored. The growth rules are able to replicate real-world phenomena such as central die-back with regeneration, 'fairy rings', and branch entrapment. A shorter spacer length results in higher population density (which may confer resistance to invasion in real populations), while longer spacer length allows exploiting the field more quickly. The number of daughter branches per mother branch follows a power law distribution for certain parameters values, as is observed in some naturally occurring clonal species.
URI: http://hdl.handle.net/10214/14333
Date: 2010
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder: Copyright 2011 Elsevier B.V. All rights reserved.
Citation: Wong, Sanders, Anand, Madhur, and Bauch, Chris T. (2011). Agent-based modelling of clonal plant propagation across space: Recapturing fairy rings, power laws and other phenomena. Ecologist Informatics. 6(2): 127-135. March 2011.https://doi.org/10.1016/j.ecoinf.2010.11.004


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Attribution-NonCommercial-NoDerivatives 4.0 International Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International