Foraging biology predicts food web complexity

Abstract

Food webs, the networks of feeding links between species, are central to our understanding of ecosystem structure, stability, and function. One of the key aspects of food web structure is complexity, or connectance, the number of links expressed as a proportion of the total possible number of links. Connectance (complexity) is linked to the stability of webs and is a key parameter in recent models of other aspects of web structure. However, there is still no fundamental biological explanation for connectance in food webs. Here, we propose that constraints on diet breadth, driven by optimal foraging, provide such an explanation. We show that a simple diet breadth model predicts highly constrained values of connectance as an emergent consequence of individual foraging behavior. When combined with features of real food web data, such as taxonomic and trophic aggregation and cumulative sampling of diets, the model predicts well the levels of connectance and scaling of connectance with species richness, seen in real food webs. This result is a previously undescribed synthesis of foraging theory and food web theory, in which network properties emerge from the behavior of individuals and, as such, provides a mechanistic explanation of connectance currently lacking in food web models