Simple MaxEnt Models for Food Web Degree Distributions
Richard J. Williams

TL;DR
This paper introduces MaxEnt models to explain food web degree distributions, providing a null hypothesis for their most probable form and analyzing deviations to understand ecological pressures.
Contribution
It presents the first mechanistic MaxEnt-based models for food web degree distributions and compares them with observed data across multiple webs.
Findings
MaxEnt models fit resource distributions in many food webs
Consumer distributions are more narrowly distributed than MaxEnt predictions
Deviations suggest ecological pressures favoring specialization or generalism
Abstract
Degree distributions have been widely used to characterize biological networks including food webs, and play a vital role in recent models of food web structure. While food webs degree distributions have been suggested to follow various functional forms, to date there has been no mechanistic or statistical explanation for these forms. Here I introduce models for the degree distributions of food webs based on the principle of maximum entropy (MaxEnt) constrained by the number of species, number of links and the number of top or basal species. The MaxEnt predictions are compared to observed distributions in 51 food webs. The distributions of the number of consumers and resources in 23 (45%) and 35 (69%) of the food webs respectively are not significantly different at a 95% confidence level from the MaxEnt distribution. While the resource distributions of niche model webs are…
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Taxonomy
TopicsPlant and animal studies · Evolutionary Game Theory and Cooperation · Evolution and Genetic Dynamics
