RInSp: anrpackage for the analysis of individual specialization in resource use

Most empirical and theoretical studies of resource use and population dynamics treat conspecific individuals as ecologically equivalent. This simplification is only justified if interindividual niche variation is rare, weak, or has a trivial effect on ecological processes. This article reviews the incidence, degree, causes, and implications of individual-level niche variation to challenge these simplifications. Evidence for individual specialization is available for 93 species distributed across a broad range of taxonomic groups. Although few studies have quantified the degree to which individuals are specialized relative to their population, between-individual variation can sometimes comprise the majority of the population's niche width. The degree of individual specialization varies widely among species and among populations, reflecting a diverse array of physiological, behavioral, and ecological mechanisms that can generate intrapopulation variation. Finally, individual specialization has potentially important ecological, evolutionary, and conservation implications. Theory suggests that niche variation facilitates frequency-dependent interactions that can profoundly affect the population's stability, the amount of intraspecific competition, fitness-function shapes, and the population's capacity to diversify and speciate rapidly. Our collection of case studies suggests that individual specialization is a widespread but underappreciated phenomenon that poses many important but unanswered questions.

Networked structures arise in a wide array of different contexts such as technological and transportation infrastructures, social phenomena, and biological systems. These highly interconnected systems have recently been the focus of a great deal of attention that has uncovered and characterized their topological complexity. Along with a complex topological structure, real networks display a large heterogeneity in the capacity and intensity of the connections. These features, however, have mainly not been considered in past studies where links are usually represented as binary states, i.e. either present or absent. Here, we study the scientific collaboration network and the world-wide air-transportation network, which are representative examples of social and large infrastructure systems, respectively. In both cases it is possible to assign to each edge of the graph a weight proportional to the intensity or capacity of the connections among the various elements of the network. We define new appropriate metrics combining weighted and topological observables that enable us to characterize the complex statistical properties and heterogeneity of the actual strength of edges and vertices. This information allows us to investigate for the first time the correlations among weighted quantities and the underlying topological structure of the network. These results provide a better description of the hierarchies and organizational principles at the basis of the architecture of weighted networks.