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Social networks in changing environments
Author(s) -
Alexander D. M. Wilson,
Stefan Krause,
Indar W. Ramnarine,
Karoline K. Borner,
Romain J. G. Clément,
Ralf H. J. M. Kurvers,
Jens Krause
Publication year - 2015
Publication title -
behavioral ecology and sociobiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.203
H-Index - 120
eISSN - 1432-0762
pISSN - 0340-5443
DOI - 10.1007/s00265-015-1973-2
Subject(s) - guppy , animal ecology , robustness (evolution) , social network (sociolinguistics) , social dynamics , biology , dynamic network analysis , population , social network analysis , social system , poecilia , ecology , computer science , sociology , fish <actinopterygii> , fishery , artificial intelligence , biochemistry , demography , world wide web , social media , gene , computer network
Social network analysis (SNA) has become a widespread tool for the study of animal social organisation. However despite this broad applicability, SNA is currently limited by both an overly strong focus on pattern analysis as well as a lack of dynamic interaction models. Here, we use a dynamic modelling approach that can capture the responses of social networks to changing environments. Using the guppy, Poecilia reticulata, we identified the general properties of the social dynamics underlying fish social networks and found that they are highly robust to differences in population density and habitat changes. Movement simulations showed that this robustness could buffer changes in transmission processes over a surprisingly large density range. These simulation results suggest that the ability of social systems to self-stabilise could have important implications for the spread of infectious diseases and information. In contrast to habitat manipulations, social manipulations (e.g. change of sex ratios) produced strong, but short-lived, changes in network dynamics. Lastly, we discuss how the evolution of the observed social dynamics might be linked to predator attack strategies. We argue that guppy social networks are an emergent property of social dynamics resulting from predator–prey co-evolution. Our study highlights the need to develop dynamic models of social networks in connection with an evolutionary framework

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