Emergence of food webs with a multi-trophic hierarchical structure driven by nonlinear trait-matching.

Food webs are a central subject in community ecology, because consumption supports the flow of matter through the system, which is at the base of many of its functions. Identifying the mechanisms that are at the origin of food web structure is useful, e.g., for restoration purposes. We investigated the extent to which trait-matching, which contributes to defining the strength of trophic interactions, can cause the emergence of food webs with a non-trivial, multi-trophic, hierarchical structure. We compared for that purpose the structural properties of food webs simulated by four food web model variants, depending whether trait-matching was linear or nonlinear and whether population dynamics and evolution were accounted for (dynamical model) or not (static model). Nonlinear trait-matching can restrict interactions in phenotypic space so as to obtain localized interactions (i.e., each species interact with a small subset of species), which is a key element for food web formation. In the static case, nonlinear trait-matching allowed for the emergence of food webs, at a relatively low connectance as with random graphs. In the dynamical case, nonlinear trait-matching combined with population dynamics and evolution allowed for the formation of groups of phenotypically close species, resulting in food webs with a multi-trophic, hierarchical structure.