Food-web structure and network theory: The role of connectance and size.
Networks from a wide range of physical, biological, and social systems have been recently described as "small-world" and "scale-free." However, studies disagree whether ecological networks called food webs possess the characteristic path lengths, clustering coefficients, and degree distributions required for membership in these classes of networks. Our analysis suggests that the disagreements are based on selective use of relatively few food webs, as well as analytical decisions that obscure important variability in the data. We analyze a broad range of 16 high-quality food webs, with 25-172 nodes, from a variety of aquatic and terrestrial ecosystems. Food webs generally have much higher complexity, measured as connectance (the fraction of all possible links that are realized in a network), and much smaller size than other networks studied, which have important implications for network topology. Our results resolve prior conflicts by demonstrating that although some food webs have small-world and scale-free structure, most do not if they exceed a relatively low level of connectance. Although food-web degree distributions do not display a universal functional form, observed distributions are systematically related to network connectance and size. Also, although food webs often lack small-world structure because of low clustering, we identify a continuum of real-world networks including food webs whose ratios of observed to random clustering coefficients increase as a power-law function of network size over 7 orders of magnitude. Although food webs are generally not small-world, scale-free networks, food-web topology is consistent with patterns found within those classes of networks.
Dunne
Jennifer A
JA
Romberg Tiburon Center, San Francisco State University, 3152 Paradise Drive, Tiburon, CA 94920, USA. jdunne@sfsu.edu
Williams
Richard J
RJ
Martinez
Neo D
ND
D004463:Ecology; D017753:Ecosystem; D005247:Feeding Behavior; D020387:Food Chain; D008962:Models, Theoretical; D013045:Species Specificity; D013223:Statistics as Topic