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An Agent-Based Modelling Approach to Biological Invasion by Macroalgae in European Coastal Environments

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Proceedings of ECCS 2014

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

Introductions of species to new continents and oceans by human activities cause fundamental and irreversible changes to natural communities and ecosystems worldwide, resulting in systematic homogenization of biota at regional and global scales and substantial changes in ecosystem functioning. Seaweeds are major primary producers in coastal areas, and large-scale substitution of dominant native seaweeds with non-native species can consequently alter coastal productivity and food web structure, and therefore impact ecosystem services. In this study, an agent-based modelling approach is taken, in association with data already gathered by the host institution from field studies, ecological experiments and molecular work, to study the impact of the Asian kelp seaweed Undaria pinnatifida, introduced to Europe in the 1970s, on native biodiversity under variable climatic conditions. Our model framework can be used to explicitly represent complex spatial and temporal patterns of invasion in order to be able to predict quantitatively the impact of these factors on the invasion dynamics of U. pinnatifida. This would be a useful tool for making accurate risk assessments of invasion potential under different environmental conditions and for choosing optimal management strategies in order to minimise future control costs.

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Acknowledgments

This research is supported by an Irish Research Council ELEVATE international career development fellowship co-funded by Marie Curie Actions (European Unions Seventh Framework Programme).

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Correspondence to James T. Murphy .

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Murphy, J.T., Johnson, M.P., Viard, F. (2016). An Agent-Based Modelling Approach to Biological Invasion by Macroalgae in European Coastal Environments. In: Battiston, S., De Pellegrini, F., Caldarelli, G., Merelli, E. (eds) Proceedings of ECCS 2014. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-29228-1_10

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