Food webs and the principle of evolutionary adaptation

TL;DR

This paper introduces an optimization algorithm for food web models based on evolutionary principles, demonstrating that simple food chains can evolve into more complex and stable food webs with increased total biomass.

Contribution

It presents a novel computational method using linear programming to optimize food web structures based on ecological fitness and total biomass.

Findings

Food chains can be significantly optimized for biomass.

Food chains tend to evolve into more complex webs under optimization.

Simple food webs are evolutionarily unstable and tend to diversify.

Abstract

A principle of evolutionary adaptation is applied to the Lotka--Volterra models, in particular to the food webs. We present a relatively simple computational algorithm of optimization with respect to a given criterion. This algorithm boils down to a sequence of easy to solve linear programming problems. As a criterion for the optimization we use the total weighted population size of the given community and an ecological fitness, which is an analogue of the potential energy in physics. We show by computational experiments that it is almost always possible to substantially increase the total weighed population size for an especially simple food web -- food chain; we also show that food chains are evolutionary unstable under the given optimization criteria and, if allowed, evolve into more complicated structures of food webs.