Environmental effects on social interaction networks and male reproductive behaviour in guppies, Poecilia reticulata

Edenbrow, Mat; Darden, Safi K.; Ramnarine, Indar W.; Evans, Jonathan P.; James, Richard; Croft, Darren P.

doi:10.1016/j.anbehav.2010.11.026

Cited by 38 publications

(31 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the same time social differentiation at the individual level was unaffected by structural complexity, with similar levels of heterogeneous interaction frequencies and sexdisassortative mixing in both treatments. Our results contrast with those from more gregarious species, in which higher structural complexity relaxed the social connectedness (Edenbrow et al, 2011;Orpwood et al, 2008;Webster et al, 2013). We suggest that the response to altered ecological conditions can fundamentally vary among species and among populations within species, depending on their tendency for gregarious behaviour.…”

Section: Effect On Long-term Social Differentiationcontrasting

confidence: 56%

“…This affects social interaction patterns among conspecifics. Habitat structural complexity might also affect social structure, if it has reached a level that reduces efficient movement or the detection of attractive conspecific cues, so that individuals may contact each other less frequently, reducing social network connectivity (Edenbrow et al, 2011;Orpwood, Magurran, Armstrong, & Griffiths, 2008;Webster et al, 2013). However, increased habitat complexity might also increase social connectivity by reducing the number of paths available and funnelling movements along particular pathways, or by inhibiting the spread and detection of conspecific cues that animals might use to avoid conspecifics.…”

mentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2016

View full text Add to dashboard Cite

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.

show abstract

Section: Effect On Long-term Social Differentiationcontrasting

confidence: 56%

mentioning

confidence: 99%

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

et al. 2016

View full text Add to dashboard Cite

show abstract

“…The effects of environmental structural complexity on social network dynamics have been explored in several studies, including investigations centring on free-ranging ungulates Sundaresan et al 2007), and in fishes in the laboratory (Orpwood et al 2008;Edenbrow et al 2011). Together these studies report that the structure of the environment, acting in concert with factors including demography, phenotype, and predation pressure can play an important role in influencing social network properties such as subgroup size, stability, and fidelity, and patterns of courtship interactions.…”

Section: Introductionmentioning

confidence: 99%

“…Subgroup size and network density are related, since the size of the subgroups determines the number of pairwise interactions observed. Finally, we calculated network differentiation, essentially a measure of the evenness of the distribution of the total pairwise interactions between individuals within an association matrix (Edenbrow 2011), derived from the coefficient of variation (standard deviation of observed interactions per pair for the group/mean number of interactions per pair for the group). A lower network differentiation score is indicative of lower variation in the extent to which individuals associate with one another.…”

Section: Network Metrics and Statistical Analysismentioning

confidence: 99%

Environmental Complexity Influences Association Network Structure and Network-Based Diffusion of Foraging Information in Fish Shoals

Webster

Atton²,

Hoppitt³

et al. 2013

The American Naturalist

View full text Add to dashboard Cite

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. abstract: Socially transmitted information can significantly affect the ways in which animals interact with their environments. We used network-based diffusion analysis, a novel and powerful tool for exploring information transmission, to model the rate at which sticklebacks (Gasterosteus aculeatus) discovered prey patches, comparing shoals foraging in open and structured environments. We found that for groups in the open environment, individuals tended to recruit to both the prey patch and empty comparison patches at similar times, suggesting that patch discovery was not greatly affected by direct social transmission. In contrast, in structured environments we found strong evidence that information about prey patch location was socially transmitted and moreover that the pathway of information transmission followed the shoals' association network structures. Our findings highlight the importance of considering habitat structure when investigating the diffusion of information through populations and imply that association networks take on greater ecological significance in structured than open environments.

show abstract

“…Flack et al, 2005; McCowan et al, 2008; Beisner et al, 2011a,b; McCowan et al, 2011), behavioral ecology (e.g. Lusseau, 2003; Croft et al, 2004; Edenbrow et al, 2011) and epidemiology (e.g. Corner et al, 2003; Otterstatter and Thomson, 2007).…”

Section: An Introduction To the Social Network Approachmentioning

confidence: 99%

How can social network analysis contribute to social behavior research in applied ethology?

Makagon

McCowan

Mench

2012

Applied Animal Behaviour Science

116

View full text Add to dashboard Cite

Social network analysis is increasingly used by behavioral ecologists and primatologists to describe the patterns and quality of interactions among individuals. We provide an overview of this methodology, with examples illustrating how it can be used to study social behavior in applied contexts. Like most kinds of social interaction analyses, social network analysis provides information about direct relationships (e.g. dominant–subordinate relationships). However, it also generates a more global model of social organization that determines how individual patterns of social interaction relate to individual and group characteristics. A particular strength of this approach is that it provides standardized mathematical methods for calculating metrics of sociality across levels of social organization, from the population and group levels to the individual level. At the group level these metrics can be used to track changes in social network structures over time, evaluate the effect of the environment on social network structure, or compare social structures across groups, populations or species. At the individual level, the metrics allow quantification of the heterogeneity of social experience within groups and identification of individuals who may play especially important roles in maintaining social stability or information flow throughout the network.

show abstract

Environmental effects on social interaction networks and male reproductive behaviour in guppies, Poecilia reticulata

Cited by 38 publications

References 70 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

Environmental Complexity Influences Association Network Structure and Network-Based Diffusion of Foraging Information in Fish Shoals

How can social network analysis contribute to social behavior research in applied ethology?

Contact Info

Product

Resources

About