Network Analysis Reveals Contrasting Effects of Intraspecific Competition on Individual vs. Population Diets

Abstract

Optimal foraging theory predicts that individuals should become more opportunistic when intraspecific competition is high and preferred resources are scarce. This density-dependent diet shift should result in increased diet breadth for individuals as they add previously unused prey to their repertoire. As a result, the niche breadth of the population as a whole should increase. In a recent study, R. Svanbäck and D. I. Bolnick confirmed that intraspecific competition led to increased population diet breadth in threespine stickleback (Gasterosteus aculeatus). However, individual diet breadth did not expand as resource levels declined. Here, we present a new method based on complex network theory that moves beyond a simple measure of diet breadth, and we use the method to reexamine the stickleback experiment. This method reveals that the population as a whole added new types of prey as stickleback density was increased. However, whereas foraging theory predicts that niche expansion is achieved by individuals accepting new prey in addition to previously preferred prey, we found that a subset of individuals ceased to use their previously preferred prey, even though other members of their population continued to specialize on the original prey types. As a result, populations were subdivided into groups of ecologically similar individuals, with diet variation among groups reflecting phenotype-dependent changes in foraging behavior as prey density declined. These results are consistent with foraging theory if we assume that quantitative trait variation among consumers affects prey preferences, and if cognitive constraints prevent individuals from continuing to use their formerly preferred prey while adding new prey.

Ecomorphology and use of food resources: inter- and intraspecific relationships of fish fauna associated with macrophyte stands

“…It is assumed that small-sized fish species are strongly correlated to variations in microhabitat structure (Dibble & Pelicice, 2010) and some species of small fish spend their whole life in macrophyte stands, which may affect fish morphology. Thus, morphological variations may be related to adaptive responses to different environmental selection pressures (Araújo et al, 2008) and may result in morphological convergence of phylogenetically distant species or morphological divergence of phylogenetically closely related species (Peres-Neto, 1999).…”

Interindividual variations in fruit preferences of the yellow-shouldered bat Sturnira lilium (Chiroptera: Phyllostomidae) in a cafeteria experiment

“…An individual whose niche is substantially narrower than the population's niche, due to factors that are not related to sex, age, size, or morphotype, is an individual specialist (Bolnick et al 2003). Evidences of individual specialization have been found in populations of several animals, such as mollusks (West 1986), birds (Smith 1990), otters (Estes et al 2003), and fish (Araújo et al 2008). Direct and indirect evidence of interindividual variations in foraging, roosting, and diet has been also obtained in populations of insectivorous bats (Cryan et al 2012), bird-eating bats (Fortuna et al 2009), and fishing bats (Barclay 1985).…”

Métricas de análise de redes sociais e sua aplicação em redes de interação biológicas: metodologia de aplicação e estudos de caso.

“…More details about the parameters used in the Dieta program can be seen in its manual, available in the supplementary section of [1]. The output file generated by Dieta corresponds to a binary matrix representing the interactions with strong connections, i.e., interactions whose values were greater than or equal to the network average (w-clique).…”

“…The Dieta 25 program [1] allows analyzing individual specialization and identifying cohesive subgroups (w-cliques) in weighted networks; it is based on the complex network theory. It is used in combination with Ucinet 26 [7] -a software that has incorporated a range of SNA metrics, such as cohesive subgroups and measure of centrality [6].…”

“…The last metric applied was the w-clique that allows identifying the cohesive subgroups (clusters) in the network structure; it is composed of a set of vertices (nodes) that are connected to each other by strong interactions, i.e., the weights of which are higher than the average network weight [1]. This metric is an alternative approach to the clique 23 metric, because it takes into account the interaction abundance (weighted matrices) to identify the network clusters.…”