Nestedness across biological scales.
Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, 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. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks.
Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada.
Mauricio
http://orcid.org/0000-0002-0019-5106
M
Cantor
Departamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Mathias M
MM
Pires
Departamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.|Departamento de Física da Matéria Condensada, Universidade Estadual de Campinas, Campinas, São Paulo, Brazil.
Flavia M D
FM
Marquitti
Departamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Rafael L G
RL
Raimundo
Departamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.|Biology Department, Tropical Conservation Biology and Environmental Science, University of Hawai'i at Hilo, Hilo, Hawaii, United States of America.
Esther
E
Sebastián-González
Departamento de Biologia Celular e do Desenvolvimento, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Patricia P
PP
Coltri
División de Antropologia, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina.|Consejo Nacional de Inverstigaciones Cientificas y Tecnicas, Buenos Aires, Argentina.
S Ivan
SI
Perez
Centre for Geometric Biology, School of Biological Sciences, Monash University, Clayton, Victoria, Australia.
Diego R
http://orcid.org/0000-0002-4568-2362
DR
Barneche
Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brazil.
Débora Y C
DY
Brandt
Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brazil.
Kelly
K
Nunes
Departamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
Fábio G
FG
Daura-Jorge
Departamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
Sergio R
SR
Floeter
Departamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Paulo R
PR
Guimarães
D000818:Animals; D001686:Biological Phenomena; D006801:Humans; D008954:Models, Biological; D016571:Neural Networks, Computer