Record |
Author |
Sundaresan, S.R.; Fischhoff, I.R.; Dushoff, J.; Rubenstein, D.I. |
Title |
Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager |
Type |
Journal Article |
Year |
2007 |
Publication |
Oecologia |
Abbreviated Journal |
Oecologia |
Volume ![sorted by Volume (numeric) field, descending order (down)](img/sort_desc.gif) |
151 |
Issue |
1 |
Pages |
140-149 |
Keywords |
Analysis of Variance; Animals; Behavior, Animal/*physiology; *Environment; Equidae/*physiology; Female; India; Kenya; Male; *Models, Theoretical; *Social Behavior; *Social Environment |
Abstract |
For species in which group membership frequently changes, it has been a challenge to characterize variation in individual interactions and social structure. Quantifying this variation is necessary to test hypotheses about ecological determinants of social patterns and to make predictions about how group dynamics affect the development of cooperative relationships and transmission processes. Network models have recently become popular for analyzing individual contacts within a population context. We use network metrics to compare populations of Grevy's zebra (Equus grevyi) and onagers (Equus hemionus khur). These closely related equids, previously described as having the same social system, inhabit environments differing in the distribution of food, water, and predators. Grevy's zebra and onagers are one example of many sets of coarsely similar fission-fusion species and populations, observed elsewhere in other ungulates, primates, and cetaceans. Our analysis of the population association networks reveals contrasts consistent with their distinctive environments. Grevy's zebra individuals are more selective in their association choices. Grevy's zebra form stable cliques, while onager associations are more fluid. We find evidence that females associate assortatively by reproductive state in Grevy's zebra but not in onagers. The current approach demonstrates the utility of network metrics for identifying fine-grained variation among individuals and populations in association patterns. From our analysis, we can make testable predictions about behavioral mechanisms underlying social structure and its effects on transmission processes. |
Address |
Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA. ssundare@princeton.edu |
Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0029-8549 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
PMID:16964497 |
Approved |
no |
Call Number |
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Serial |
1863 |
Permanent link to this record |