title: Examining the potential effects of species aggregation on the network structure of food webs.
abstract: One of the key measures that have been used to describe the topological properties of complex networks is the "degree distribution", which is a measure that describes the frequency distribution of number of links per node. Food webs are complex ecological networks that describe the trophic relationships among species in a community, and the topological properties of empirical food webs, including degree distributions, have been examined previously. Previously, the "niche model" has been shown to accurately predict degree distributions of empirical food webs, however, the niche model-generated food webs were referenced against empirical food webs that had their species grouped together based on their taxonomic and/or trophic relationships (aggregated food webs). Here, we explore the effects of species aggregation on the ability of the niche model to predict the total- (sum of prey and predator links per node), in- (number of predator links per node), and out- (number of prey links per node) degree distributions of empirical food webs by examining two food webs that can be aggregated at different levels of resolution. The results showed that (1) the cumulative total- and out-degree distributions were consistent with the niche model predictions when the species were aggregated, (2) when the species were disaggregated (i.e., higher resolution), there were mixed conclusions with regards to the niche model's ability to predict total- and out-degree distributions, (3) the model's ability to predict the in-degree distributions of the two food webs was generally inadequate. Although it has been argued that universal functional form based on the niche model could describe the degree distribution patterns of empirical food webs, we believe there are some limitations to the model's ability to accurately predict the structural properties of food webs.
authors.affiliation: Département de Géographie, Complex Systems Laboratory, Université de Montréal, Montréal, QC, Canada. ken.arii@mail.mcgill.ca
authors.forename: Ken
authors.initials: K
authors.lastname: Arii
authors.forename: Raphaëlle
authors.initials: R
authors.lastname: Derome
authors.forename: Lael
authors.initials: L
authors.lastname: Parrott
mesh_terms: D000818:Animals; D020387:Food Chain; D008954:Models, Biological; D011157:Population Dynamics