Social network analysis and valid Markov chain Monte Carlo tests of null models

Krause, Stefan; Mattner, Lutz; James, Richard; Guttridge, Tristan L.; Corcoran, M J; Gruber, Samuel H.; Krause, Jens

doi:10.1007/s00265-009-0746-1

Cited by 31 publications

(25 citation statements)

References 18 publications

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“…whale sharks, Rhincodon typus, Rhincodontidae: Arzoumanian et al 2005; eagle rays, Aetobatus narinari, Myliobatidae: Krause et al 2009b). whale sharks, Rhincodon typus, Rhincodontidae: Arzoumanian et al 2005; eagle rays, Aetobatus narinari, Myliobatidae: Krause et al 2009b).…”

Section: Marking and Data Collection Techniquesmentioning

confidence: 99%

“…Most of the work which has been carried out on social networks in fish was carried out on individuals from the same local area or pool that were familiar with each other (e.g. Exceptions are the work on adjacent guppy pools where some individuals crossed between pools and on eagle rays and blacktip reef sharks (Carcharhinus melanopterus, Carcharhinidae) roaming around islands Krause et al 2009b;Mourier et al 2012). However, this means that work on fish has largely missed out on a topic of particular interest in the social network literature, namely how different communities are inter- Figure 2 A social network of a guppy (Poecilia reticulata, Poeciliidae) population in Trinidad (redrawn from Croft et al 2008).…”

Section: Familiarity and Site Fidelitymentioning

confidence: 99%

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Social networks in elasmobranchs and teleost fishes

2013

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Over the last decade, there has been an exponential increase in studies using social network analysis to describe the structure of animal societies. In this synthesis, we examine the contribution of social network analysis towards developing our understanding of the social organization of elasmobranchs and teleost fishes. We review and discuss the current state of knowledge of the mechanisms and functions underpinning social network structure in fishes with particular emphasis on cooperation, familiarity, site fidelity, population structure and the welfare of captive populations. We also discuss important methodological issues (e.g. how to identify and mark fish) and highlight new developments in this area of research and their implications for the study of fish behaviour. Finally, we outline promising future research areas for the application of social network analysis to teleost fishes and elasmobranchs.

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Section: Marking and Data Collection Techniquesmentioning

confidence: 99%

Section: Familiarity and Site Fidelitymentioning

confidence: 99%

Social networks in elasmobranchs and teleost fishes

2013

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“…For the relatedness analysis, we counted the number of related (full and half siblings) pairs in each group and then computed the sum of the maximum numbers. All 4 test statistics were then calculated 10 8 -1 times using a Markov Chain Monte Carlo (MCMC) randomisation approach (see Krause et al 2008 for details) providing expected frequency distributions for each test statistic. p-values were obtained by comparing the test statistic expected values with the observed ones.…”

Section: Methodsmentioning

confidence: 99%

Assortative interactions and leadership in a free-ranging population of juvenile lemon shark Negaprion brevirostris

Guttridge¹,

Gruber²,

DiBattista³

et al. 2011

Mar. Ecol. Prog. Ser.

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For marine predators there is a paucity of studies on social behaviour, and even fewer studies have quantified interactions between individuals. In the present study, we looked at the social structure and leadership of free-ranging juvenile lemon shark Negaprion brevirostris in a known aggregation site, Bimini, the Bahamas. Observations of these sharks were made from towers placed in a mangrove inlet, where clear, shallow, protected waters made it possible to record group compositions of externally colour-code tagged wild juvenile lemon sharks. Thirty-eight different individual sharks were observed to use the area over a 2 yr period. Results show repeated social interactions suggestive of active partner preference. In addition, we found that group structure was mostly explained by body length, and possibly by preference for relatives but not by sex. Finally, we observed that some sharks led more groups than others and that those lead individuals were usually larger than those following them. This study quantifies the social structure of a free-ranging shark population and provides novel insights into the social behaviour of juvenile sharks.

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“…Because this approach may be biased (Krause et al 2009), as an alternative, we tested the hypothesis of a random social pattern for this Guiana dolphin population using the null model NM2. Note that our randomization constrained the same features of the original data as would a conventional algorithm (see Bejder et al 1998).…”

Section: Association Patternsmentioning

confidence: 99%