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Eco-evolutionary dynamics on deformable fitness landscapes

Eco-evolutionary dynamics on deformable fitness landscapes
Eco-evolutionary dynamics on deformable fitness landscapes
Conventional approaches to modelling ecological dynamics often do not include evolutionary changes in the genetic makeup of component species and, conversely, conventional approaches to modelling evolutionary changes in the genetic makeup of a population often do not include ecological dynamics. But recently there has been considerable interest in understanding the interaction of evolutionary and ecological dynamics as coupled processes. However, in the context of complex multi-species ecosytems, especially where ecological and evolutionary timescales are similar, it is difficult to identify general organising principles that help us understand the structure and behaviour of complex ecosystems. Here we introduce a simple abstraction of coevolutionary interactions in a multi-species ecosystem.We model non-trophic ecological interactions based on a continuous but low-dimensional trait/niche space, where the location of each species in trait space affects the overlap of its resource utilisation with that of other species. The local depletion of available resources creates, in effect, a deformable fitness landscape that governs how the evolution of one species affects the selective pressures on other species. This enables us to study the coevolution of ecological interactions in an intuitive and easily visualisable manner.We observe that this model can exhibit either of the two behaviouralmodes discussed in the literature; namely, evolutionary stasis or Red Queen dynamics, i.e., continued evolutionary change.We find that which of these modes is observed depends on the lag or latency between the movement of a species in trait space and its effect on available resources. Specifically, if ecological change is nearly instantaneous compared to evolutionary change, stasis results; but conversely, if evolutionary timescales are closer to ecological timescales, such that resource depletion is not instantaneous on evolutionary timescales, then Red Queen dynamics result. We also observe that in the stasis mode, the overall utilisation of resources by the ecosystem is relatively efficient, with diverse species utilising different niches, whereas in the Red Queen mode the organisation of the ecosystem is such that species tend to clump together competing for overlapping resources. These models thereby suggest some basic conditions that influence the organisation of inter-species interactions and the balance of individual and collective adaptation in ecosystems, and likewise they also suggest factors that might be useful in engineering artificial coevolution.
6
339-368
Springer
Watson, Richard
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Ebner, Marc
628c2826-7b15-4e8e-9656-f4edf6395845
Richter, Hendrik
Engelbrecht, Andries
Watson, Richard
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Ebner, Marc
628c2826-7b15-4e8e-9656-f4edf6395845
Richter, Hendrik
Engelbrecht, Andries

Watson, Richard and Ebner, Marc (2013) Eco-evolutionary dynamics on deformable fitness landscapes. In, Richter, Hendrik and Engelbrecht, Andries (eds.) Recent Advances in the Theory and Application of Fitness Landscapes. (Emergence, Complexity and Computation, , (doi:10.1007/978-3-642-41888-4), 6) Berlin, DE. Springer, pp. 339-368. (doi:10.1007/978-3-642-41888-4).

Record type: Book Section

Abstract

Conventional approaches to modelling ecological dynamics often do not include evolutionary changes in the genetic makeup of component species and, conversely, conventional approaches to modelling evolutionary changes in the genetic makeup of a population often do not include ecological dynamics. But recently there has been considerable interest in understanding the interaction of evolutionary and ecological dynamics as coupled processes. However, in the context of complex multi-species ecosytems, especially where ecological and evolutionary timescales are similar, it is difficult to identify general organising principles that help us understand the structure and behaviour of complex ecosystems. Here we introduce a simple abstraction of coevolutionary interactions in a multi-species ecosystem.We model non-trophic ecological interactions based on a continuous but low-dimensional trait/niche space, where the location of each species in trait space affects the overlap of its resource utilisation with that of other species. The local depletion of available resources creates, in effect, a deformable fitness landscape that governs how the evolution of one species affects the selective pressures on other species. This enables us to study the coevolution of ecological interactions in an intuitive and easily visualisable manner.We observe that this model can exhibit either of the two behaviouralmodes discussed in the literature; namely, evolutionary stasis or Red Queen dynamics, i.e., continued evolutionary change.We find that which of these modes is observed depends on the lag or latency between the movement of a species in trait space and its effect on available resources. Specifically, if ecological change is nearly instantaneous compared to evolutionary change, stasis results; but conversely, if evolutionary timescales are closer to ecological timescales, such that resource depletion is not instantaneous on evolutionary timescales, then Red Queen dynamics result. We also observe that in the stasis mode, the overall utilisation of resources by the ecosystem is relatively efficient, with diverse species utilising different niches, whereas in the Red Queen mode the organisation of the ecosystem is such that species tend to clump together competing for overlapping resources. These models thereby suggest some basic conditions that influence the organisation of inter-species interactions and the balance of individual and collective adaptation in ecosystems, and likewise they also suggest factors that might be useful in engineering artificial coevolution.

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Published date: 2013
Organisations: Agents, Interactions & Complexity, Centre for Biological Sciences

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Local EPrints ID: 393318
URI: http://eprints.soton.ac.uk/id/eprint/393318
PURE UUID: 770a39ee-63f7-4959-a6ac-3858a4f30e9b

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Date deposited: 27 Apr 2016 11:36
Last modified: 16 Apr 2020 16:33

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Author: Richard Watson
Author: Marc Ebner
Editor: Hendrik Richter
Editor: Andries Engelbrecht

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