Dynamic social networks in guppies (Poecilia reticulata)

被引:44
作者
Wilson, Alexander D. M. [1 ,7 ]
Krause, Stefan [2 ]
James, Richard [3 ]
Croft, Darren P. [4 ]
Ramnarine, Indar W. [5 ]
Borner, Karoline K. [1 ]
Clement, Romain J. G. [1 ]
Krause, Jens [1 ,6 ]
机构
[1] Leibniz Inst Freshwater Ecol & Inland Fisheries, Dept Biol & Ecol Fishes, D-12587 Berlin, Germany
[2] Lubeck Univ Appl Sci, Dept Elect Engn & Comp Sci, Lubeck, Germany
[3] Univ Bath, Dept Phys, Bath BA2 7AY, Avon, England
[4] Univ Exeter, Ctr Res Anim Behav, Coll Life & Environm Sci, Washington Singer Labs, Exeter EX4 4QG, Devon, England
[5] Univ W Indies, Dept Life Sci, St Augustine, Trinidad Tobago
[6] Humboldt Univ, Fac Life Sci, D-10099 Berlin, Germany
[7] Carleton Univ, Dept Biol, Ottawa, ON K1S 5B6, Canada
关键词
Social network analysis; Behaviour type; Fission-fusion dynamics; MARKOV-CHAINS; BEHAVIOR;
D O I
10.1007/s00265-014-1704-0
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
One of the main challenges in the study of social networks in vertebrates is to close the gap between group patterns and dynamics. Usually scan samples or transect data are recorded to provide information about social patterns of animals, but these techniques themselves do not shed much light on the underlying dynamics of such groups. Here we show an approach which captures the fission-fusion dynamics of a fish population in the wild and demonstrates how the gap between pattern and dynamics may be closed. Our analysis revealed that guppies have complex association patterns that are characterised by close strong connections between individuals of similar behavioural type. Intriguingly, the preference for particular social partners is not expressed in the length of associations but in their frequency. Finally, we show that the observed association preferences could have important consequences for transmission processes in animal social networks, thus moving the emphasis of network research from descriptive mechanistic studies to functional and predictive ones.
引用
收藏
页码:915 / 925
页数:11
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