Cantor et al. 2017, Fig. 2

Nestedness in biological networks

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. Nested structures have been primarily assessed in ecological networks formed by two non-overlapping sets of elements. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Cantor et al. 2017 compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization, from gene and protein interactions to entire food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. Together with our analyses, we published an R package called unodf, which is available on the BitBucket repository.

Species are not ecologically equivalent and the extent to which nestedness is observed in terms of functional trait composition of assemblages still remains poorly known. Bender et al. 2017 assessed the levels of taxonomical vs functional nestedness of reef fish assemblages at the global scale using an extensive database on the functional traits and the distributions of 6316 tropical reef fish species across 169 sites. Functional nestedness was considerably more common than taxonomic nestedness, and generally associated with geographical isolation, where nested subsets are gradually more isolated from surrounding reef areas and from the center of biodiversity.

Publications

(2017). Isolation drives taxonomic and functional nestedness in tropical reef fish faunas. Ecography, 40: 425–435. doi: 10.1111/ecog.02293.

Preprint PDF Project

(2017). Nestedness across biological scales. PLOS One, 12: e0171691. doi: 10.1371/journal.pone.0171691.

Preprint PDF Code Dataset Project