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A new model explaining the origin of different topologies in interaction networks
Author(s) -
Pinheiro Rafael B. P.,
Felix Gabriel M. F.,
Dormann Carsten F.,
Mello Marco A. R.
Publication year - 2019
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1002/ecy.2796
Subject(s) - nestedness , network topology , modularity (biology) , generalist and specialist species , modular design , computer science , ecological network , topology (electrical circuits) , selection (genetic algorithm) , homogeneous , resource (disambiguation) , heterogeneous network , interaction network , distributed computing , simple (philosophy) , ecology , biology , mathematics , evolutionary biology , ecosystem , artificial intelligence , biodiversity , statistical physics , computer network , physics , habitat , wireless , wireless network , combinatorics , gene , philosophy , operating system , telecommunications , biochemistry , epistemology
Abstract Nestedness and modularity have been recurrently observed in species interaction networks. Some studies argue that those topologies result from selection against unstable networks, and others propose that they likely emerge from processes driving the interactions between pairs of species. Here we present a model that simulates the evolution of consumer species using resource species following simple rules derived from the integrative hypothesis of specialization ( IHS ). Without any selection on stability, our model reproduced all commonly observed network topologies. Our simulations demonstrate that resource heterogeneity drives network topology. On the one hand, systems containing only homogeneous resources form generalized nested networks, in which generalist consumers have higher performance on each resource than specialists. On the other hand, heterogeneous systems tend to have a compound topology: modular with internally nested modules, in which generalists that divide their interactions between modules have low performance. Our results demonstrate that all real‐world topologies likely emerge through processes driving interactions between pairs of species. Additionally, our simulations suggest that networks containing similar species differ from heterogeneous networks and that modules may not present the topology of entire networks.