Algorithmic systems ecology: Experiments on multiple interaction types and patches

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Abstract

Dynamic behavior in ecosystems can emerge as a result of multiple interactions of different types as well as movements of the ecosystem species between different patches. The extinction behaviors in ecosystem models, which can result from the small species numbers, bring stochasticity to the foreground as they are often not observable in deterministic representations. To this end, we demonstrate an integrated approach to ecosystem modeling from an algorithmic systems biology point of view. We use a modeling interface, called LIME, which allows us to give biologically intuitive models of a plant-pollinator system's descriptions with varying interaction types and patches. Our models, written in a narrative style, are automatically translated into stochastic programming languages. The discrete stochastic nature of the models brings about the possibility to analyze the models with respect to their simulations as well as various graph representations. Our analysis provides an assessment of the functional dynamics of ecosystems with respect to the influence of various interaction patterns and patch links. © Springer-Verlag Berlin Heidelberg 2014.

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APA

Kahramanoǧullari, O., Lynch, J. F., & Priami, C. (2014). Algorithmic systems ecology: Experiments on multiple interaction types and patches. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7991 LNCS, pp. 154–171). Springer Verlag. https://doi.org/10.1007/978-3-642-54338-8_13

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