Simulating Eco-evolutionary Processes in an Obligate Pollination Model with a Genetic Algorithm
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Norbury, John
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Abstract
Pollination interactions are common, and their maintenance is critical for many food crops upon which human populations depend. Pollination is a mutualism interaction; together with predation and competition, mutualism makes up the triumvirate of fundamental interactions that control population dynamics. Here we examine pollination interactions (nectar reward for gamete transport service) using a simple heuristic model similar to the Lotka–Volterra models that have underpinned our understanding of predation and competition so effectively since the 1920s. We use a genetic algorithm to simulate the eco-evolutionary interactions of the plant and pollinator populations and examine the distributions of the parameter values and zero isoclines to infer the relative ubiquity of the various eco-evolutionary outcomes possible in the model. Our results suggest that trade-offs between costs and benefits for the pollinator may be a key component of obligate pollination systems in achieving adaptive success creating and stably occupying mutualist niches.
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Bulletin of Mathematical Biology
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© 2018 Springer. This is an electronic version of an article published in Bulletin of Mathematical Biology, AOV. Bulletin of Mathematical Biology is available online at: http://link.springer.com/ with the open URL of your article.
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Mathematical sciences
Biological sciences