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Degree heterogeneity and stability of ecological networks.
Yan, Gang; Martinez, Neo D; Liu, Yang-Yu.
Afiliação
  • Yan G; School of Physics Science and Engineering, Tongji University, Shanghai 200092, People's Republic of China.
  • Martinez ND; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA.
  • Liu YY; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA yyl@channing.harvard.edu.
J R Soc Interface ; 14(131)2017 06.
Article em En | MEDLINE | ID: mdl-28637917
ABSTRACT
A classic measure of ecological stability describes the tendency of a community to return to equilibrium after small perturbations. While many advances show how the network architecture of these communities severely constrains such tendencies, one of the most fundamental properties of network structure, i.e. degree heterogeneity-the variability of the number of links associated with each species, deserves further study. Here we show that the effects of degree heterogeneity on stability vary with different types of interspecific interactions. Degree heterogeneity consistently destabilizes ecological networks with both competitive and mutualistic interactions, while its effects on networks of predator-prey interactions such as food webs depend on prey contiguity, i.e. the extent to which the species consume an unbroken sequence of prey in community niche space. Increasing degree heterogeneity tends to stabilize food webs except those with the highest prey contiguity. These findings help explain why food webs are highly but not completely interval and, more broadly, deepen our understanding of the stability of complex ecological networks.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Comportamento Predatório / Cadeia Alimentar / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Comportamento Predatório / Cadeia Alimentar / Modelos Biológicos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2017 Tipo de documento: Article