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A cellular automaton approach to spatial and temporal plant population dynamics

A cellular automaton approach to spatial and temporal plant population dynamics
A cellular automaton approach to spatial and temporal plant population dynamics

This thesis examines how prolonged coexistence can be maintained in a grassland plant assemblage with a particular emphasis on spatial arrangement of individuals. Thus a multispecies cellular automation model is used which is explicitly spatial, individual-based and its dynamics are determined by local interactions. We test the various methods of model implementation and find that they can have a significant effect on the population dynamics, but these effects are local in nature and do not alter the final outcome. Having established our model we find that it exhibits the competitive exclusion principle in that a monoculture is always reached. We then impose different disturbance regimes on the system by varying the amount and the sizes of the individual patches and find that the model exhibits behaviour consistent with the 'intermediate disturbance hypothesis'. By introducing another variable of the disturbance regime we find that the behaviour of the system as a whole becomes much more complicated and that the resultant diversity of the system indicates a very strong link between characteristics of the disturbance regime and the inter-relationships of the life-history strategies of the various species. We also produce 3 non-spatial models, comparing results with those of the cellular automata and find that the spatial nature of the latter makes a great difference. Thus we examine how the spatial arrangements of individuals in an undisturbed homogeneous system could prolong coexistence. We find that same-species aggregation is a natural consequence of the modular growth of plants and that it can slow down the extinction of a species by lowering the interface length with a dominant invader.

University of Southampton
Bulling, Mark Trevor
Bulling, Mark Trevor

Bulling, Mark Trevor (1999) A cellular automaton approach to spatial and temporal plant population dynamics. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

This thesis examines how prolonged coexistence can be maintained in a grassland plant assemblage with a particular emphasis on spatial arrangement of individuals. Thus a multispecies cellular automation model is used which is explicitly spatial, individual-based and its dynamics are determined by local interactions. We test the various methods of model implementation and find that they can have a significant effect on the population dynamics, but these effects are local in nature and do not alter the final outcome. Having established our model we find that it exhibits the competitive exclusion principle in that a monoculture is always reached. We then impose different disturbance regimes on the system by varying the amount and the sizes of the individual patches and find that the model exhibits behaviour consistent with the 'intermediate disturbance hypothesis'. By introducing another variable of the disturbance regime we find that the behaviour of the system as a whole becomes much more complicated and that the resultant diversity of the system indicates a very strong link between characteristics of the disturbance regime and the inter-relationships of the life-history strategies of the various species. We also produce 3 non-spatial models, comparing results with those of the cellular automata and find that the spatial nature of the latter makes a great difference. Thus we examine how the spatial arrangements of individuals in an undisturbed homogeneous system could prolong coexistence. We find that same-species aggregation is a natural consequence of the modular growth of plants and that it can slow down the extinction of a species by lowering the interface length with a dominant invader.

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Published date: 1999

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Local EPrints ID: 464109
URI: http://eprints.soton.ac.uk/id/eprint/464109
PURE UUID: 6eccbaa4-5fcc-41b6-a42a-5a53f5bd3321

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Date deposited: 04 Jul 2022 21:18
Last modified: 04 Jul 2022 21:18

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Contributors

Author: Mark Trevor Bulling

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