Hypothesis testing in animal social networks

Croft, Darren P.; Madden, Joah R.; Franks, Daniel W.; James, Richard

doi:10.1016/j.tree.2011.05.012

Cited by 353 publications

(345 citation statements)

References 49 publications

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“…This form of network randomization is rather rare in behavioural sciences [79], and ours is the first study that has used this stringent condition in the nullmodels of dominance networks. In the near future, we would like to investigate the procedure of randomization that preserves a predetermined hierarchy in a network.…”

Section: Discussionmentioning

confidence: 99%

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Nandi

Annagiri

Bhattacharya

2014

J. R. Soc. Interface.

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Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.

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Section: Discussionmentioning

confidence: 99%

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Nandi

Annagiri

Bhattacharya

2014

J. R. Soc. Interface.

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“…Third, proximity logging may yield yet unknown sources of bias and/or error (false-positive joint detections and tag-induced behavioural changes), although we did not experience these problems with our data and study species. Finally, while improved data collection techniques will advance our understanding of complex social systems, increased data quantity and quality alone do not negate other analytical challenges (nonindependence, data filtering and management; see the electronic supplementary material) and the importance of using null models for testing network hypotheses [9].…”

Section: Discussionmentioning

confidence: 99%

Proximity data-loggers increase the quantity and quality of social network data

Ryder

Horton

Tillaart³

et al. 2012

Biol. Lett.

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Social network analysis is an ideal quantitative tool for advancing our understanding of complex social behaviour. However, this approach is often limited by the challenges of accurately characterizing social structure and measuring network heterogeneity. Technological advances have facilitated the study of social networks, but to date, all such work has focused on large vertebrates. Here, we provide proof of concept for using proximity data-logging to quantify the frequency of social interactions, construct weighted networks and characterize variation in the social behaviour of a lek-breeding bird, the wire-tailed manakin, Pipra filicauda. Our results highlight how this approach can ameliorate the challenges of social network data collection and analysis by concurrently improving data quality and quantity.

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“…degree and weighted degree). Given that network data are not independent [48], we used flock replicates within each habitat type and included flock identity as a random effect and habitat as a fixed effect to explain variation in degree and weighted degree. To compare across networks in different habitats, we accounted for the number of possible species interactions and sampling time using a log (n or t) offset [49] where n represents the number of possible interspecific associations within the network (n 2 1, number of nodes) and t represents sampling time.…”

Section: (C) Network and Statistical Analysesmentioning

confidence: 99%

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia

et al. 2014

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Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forestdependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

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Hypothesis testing in animal social networks

Cited by 353 publications

References 49 publications

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Proximity data-loggers increase the quantity and quality of social network data

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia

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