Disentangling social networks from spatiotemporal dynamics: the temporal structure of a dolphin society

Cantor, Maurício; Wedekin, Leonardo L.; Guimarães, Paulo R.; Daura‐Jorge, Fábio G.; Rossi‐Santos, Marcos R.; Simões‐Lopes, Paulo C.

doi:10.1016/j.anbehav.2012.06.019

Cited by 84 publications

(76 citation statements)

References 56 publications

(88 reference statements)

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“…Alternatively, changes within one year may integrate into a stable social structure across years. This is consistent with suggestions by Cantor et al (2012) that the spatiotemporal scale is important to identify social processes.…”

Section: Effect On Long-term Social Differentiationsupporting

confidence: 80%

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Environment modulates population social structure: experimental evidence from replicated social networks of wild lizards

et al. 2016

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Social structure is a fundamental component of a population that drives ecological and evolutionary processes ranging from parasite transmission to sexual selection. Nevertheless, we have much to learn about factors that explain variation in social structure. We used advances in biologging and social network analysis to experimentally test how the local habitat, and specifically habitat complexity, modulates social structure at different levels in wild populations. Sleepy lizards, Tiliqua rugosa, establish nonrandom social networks that are characterized by avoidance of some neighbours and frequent interactions with one opposite-sex individual. Using synchronous GPS locations of all adult lizards, we constructed social networks based on spatial proximity of individuals. We increased habitat structural complexity in two study populations by adding 100 short fences across the landscape. We then compared the resulting movement behaviour and social structure between these populations and two unmanipulated populations. Social connectivity (network density) and social stability, measured at weekly intervals, were greater in populations with increased habitat structural complexity. The level of agonistic interaction (quantified as scale damage) was also higher, indicating a fitness cost of greater social connectivity. However, some network parameters were unaffected by increased complexity, including disassortative mixing by sex, and at the individual level, social differentiation among associates (coefficient of variation of edge weights) and maximal interaction frequencies (maximal edge weight). This suggests divergent effects of changed ecological conditions on individual association behaviour compared to the resulting social structure of the population. Our results contrast with those from studies of more gregarious species, in which higher structural complexity in the environment relaxed the social connectivity. This shows that the response to altered ecological conditions can differ fundamentally between species or between populations, and we suggest that it depends on their tendency for gregarious behaviour.

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Section: Effect On Long-term Social Differentiationsupporting

confidence: 80%

“…At the population level, social structures are increasingly recognized as heterogeneous and dynamic, both in space and time and across contexts (Cantor et al, 2012). Our understanding of the ecological variables that drive those heterogeneities is still limited.…”

Section: Effect On Long-term Social Differentiationmentioning

confidence: 99%

Environment modulates population social structure: experimental evidence from replicated social networks of wild lizards

et al. 2016

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“…the citation network used in the example above), a few animal social systems are likely to provide exceptions, especially when a small number of individuals move between cohesive social groups. Therefore, investigating similar questions about 'partial networks' in more highly structured social systems, such as those found in primates (Lehmann & Dunbar, 2009) and dolphins (Cantor et al, 2012;Connor et al, 2001;Lusseau, 2003) would be especially beneficial.…”

Section: Applications and Further Workmentioning

confidence: 98%

The consequences of unidentifiable individuals for the analysis of an animal social network

et al. 2015

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“…While most studies of social networks in animal behavior have focused on describing static network structures there is an increasing interest in studying how social networks change over time and what determines the stability of social networks (Wittemyer et al 2005; Flack et al 2006; Hansen et al 2009; Ansmann et al 2012; Blonder et al 2012; Cantor et al 2012; Foster et al 2012; Brent et al 2013; Gero et al 2013; Hobson et al 2013; Boogert et al 2014; Pinter Wollman et al 2014; Wilson et al 2014). Indeed, inferring changes in social network structures has the potential to provide crucial insights into how social dynamics change over time, for instance, in response to seasonal changes (Wittemyer et al 2005 ; Henzi et al 2009; Brent et al 2013) or in response to disturbances such as the removal of important individuals (Flack et al 2006; Barrett et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Social network dynamics: the importance of distinguishing between heterogeneous and homogeneous changes

Franz

Alberts

2015

Behav Ecol Sociobiol

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Summary Social network analysis is increasingly applied to understand the evolution of animal sociality. Identifying ecological and evolutionary drivers of complex social structures requires inferring how social networks change over time. In most observational studies, sampling errors may affect the apparent network structures.Here, we argue that existing approaches tend not to control sufficiently for some types of sampling errors when social networks change over time. Specifically, we argue that two different types of changes may occur in social networks, heterogeneous and homogeneous changes, and that understanding network dynamics requires distinguishing between these two different types of changes, which are not mutually exclusive. Heterogeneous changes occur if relationships change differentially, e.g. if some relationships are terminated but others remain intact. Homogeneous changes occur if all relationships are proportionally affected in the same way, e.g. if grooming rates decline similarly across all dyads. Homogeneous declines in the strength of relationships can strongly reduce the probability of observing weak relationships, producing the appearance of heterogeneous network changes. Using simulations, we confirm that failing to differentiate homogeneous and heterogeneous changes can potentially lead to false conclusions about network dynamics. We also show that bootstrap tests fail to distinguish between homogeneous and heterogeneous changes. As a solution to this problem we show that an appropriate randomization test can infer whether heterogeneous changes occurred. Finally, we illustrate the utility of using the randomization test by performing an example analysis using an empirical data set on wild baboons.

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Disentangling social networks from spatiotemporal dynamics: the temporal structure of a dolphin society

Cited by 84 publications

References 56 publications

Environment modulates population social structure: experimental evidence from replicated social networks of wild lizards

Environment modulates population social structure: experimental evidence from replicated social networks of wild lizards

The consequences of unidentifiable individuals for the analysis of an animal social network

Social network dynamics: the importance of distinguishing between heterogeneous and homogeneous changes

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