Evidence map›Paper›PMID 28166284›Full record

ArticlePloS one2017

Nestedness across biological scales.

Mauricio Cantor, Mathias M Pires, Flavia M D Marquitti, Rafael L G Raimundo, Esther Sebastián-González, Patricia P Coltri, S Ivan Perez, Diego R Barneche, Débora Y C Brandt, Kelly Nunes and 3 more

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  17. Review
  18. Hierarchically embedded interaction networks represent a missing link in the study of behavioral and community ecology.Behavioral ecology : official journal of the International Society for Behavioral Ecology
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Mauricio CantorDepartment of Biology, Dalhousie University, Halifax, Nova Scotia, Canada.ORCID http://orcid.org/0000-0002-0019-5106
Mathias M PiresDepartamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Flavia M D MarquittiDepartamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Rafael L G RaimundoDepartamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Esther Sebastián-GonzálezDepartamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Patricia P ColtriDepartamento de Biologia Celular e do Desenvolvimento, Universidade de São Paulo, São Paulo, São Paulo, Brazil.
S Ivan PerezDivisión de Antropologia, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina.
Diego R BarnecheCentre for Geometric Biology, School of Biological Sciences, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0000-0002-4568-2362
Débora Y C BrandtDepartamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brazil.
Kelly NunesDepartamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brazil.
Fábio G Daura-JorgeDepartamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
Sergio R FloeterDepartamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
Paulo R GuimarãesDepartamento de Ecologia, Universidade de São Paulo, São Paulo, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Biological PhenomenaModels, BiologicalNeural Networks, ComputerAnimalsHumans

Identifiers

PMID28166284
PMCPMC5293200

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.