Social network correlates of food availability in an endangered population of killer whales, Orcinus orca

Foster, Emma; Franks, Daniel W.; Morrell, Lesley J.; Balcomb, Ken C.; Parsons, Kim M.; Ginneken, Astrid van; Croft, Darren P.

doi:10.1016/j.anbehav.2011.12.021

Cited by 136 publications

(103 citation statements)

References 65 publications

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“…Our understanding of the ecological variables that drive those heterogeneities is still limited. Local food abundance (Foster et al, 2012) can affect social structure. For example killer whales, Orcinus orca, form a more interconnected social network when food is abundant (Foster et al, 2012).…”

Section: Effect On Long-term Social Differentiationmentioning

confidence: 99%

“…Local food abundance (Foster et al, 2012) can affect social structure. For example killer whales, Orcinus orca, form a more interconnected social network when food is abundant (Foster et al, 2012). Other ecological factors that can influence social structure include predation pressure (Kelley, Morrell, Inskip, Krause, & Croft, 2011), habitat disturbance (Lattanzio & Miles, 2014) and habitat The GLMM formula in R was lmer(ScaleDamage~Treatment þ SameSex þ Sex þ (1jSite)).…”

Section: Effect On Long-term Social Differentiationmentioning

confidence: 99%

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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 Differentiationmentioning

confidence: 99%

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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“…For example, ecologists interested in animal behavior and social structure have mapped the interactions among individuals of a population (Croft et al, 2004;Foster et al, 2012;Wey et al, 2008). At the community level, Ings et al (2009) identify three broad types of ecological networks: food webs, mutualistic networks, and host-parasitoid networks.…”

Section: Introductionmentioning

confidence: 99%

The rise of Network Ecology: Maps of the topic diversity and scientific collaboration

Borrett

Moody

Edelmann

2014

Ecological Modelling

107

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Network ecologists investigate the structure, function, and evolution of ecological systems using network models and analyses. For example, network techniques have been used to study community interactions (i.e., food-webs, mutualisms), gene flow across landscapes, and the sociality of individuals in populations. The work presented here uses a bibliographic and network approach to (1) document the rise of Network Ecology, (2) identify the diversity of topics addressed in the field, and (3) map the structure of scientific collaboration among contributing scientists. Our aim is to provide a broad overview of this emergent field that highlights its diversity and to provide a foundation for future advances. To do this, we searched the ISI Web of Science database for ecology publications between 1900 and 2012 using the search terms for research areas of Environmental Sciences & Ecology and Evolutionary Biology and the topic tag ecology. From these records we identified the Network Ecology publications using the topic terms network, graph theory, and web while controlling for the usage of misleading phrases. The resulting corpus entailed 29,513 publications between 1936 and 2012. We find that Network Ecology spans across more than 1,500 sources with core ecological journals being among the top 20 most frequent outlets. We document the rapid rise in Network Ecology publications per year reaching a magnitude of over 5% of the ecological publications in 2012. Drawing topical information from the publication record content (titles, abstracts, keywords) and collaboration information from author listing, our analysis highlights the diversity and clustering of topics addressed within Network Ecology and reveals the highly collaborative approach of scientists publishing in this field. We conclude that Network Ecology is a large and rapidly growing area of ecology partly because the relational tools it rests upon are broadly useful for ecology, which is fundamentally a relational science. We expect continued growth and development of this research field.

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“…There is increasing evidence showing that decoding the structure of such a social network is an effective approach for unravelling the underlying processes organizing an animal society (e.g. Lusseau 2003;Croft et al 2008;Foster et al 2012;Mourier et al 2012;Daura-Jorge et al 2012).…”

mentioning

confidence: 99%

“…Wiszniewski et al 2009), or local ecological conditions (e.g. Foster et al 2012). However, social matrices include more than social affinities or ecological factors (e.g.…”

mentioning

confidence: 99%

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

et al. 2012

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Social network correlates of food availability in an endangered population of killer whales, Orcinus orca

Abstract: Social network correlates of food availability in an endangered Social network correlates of food availability in an endangered population of killer whales, Social network correlates of food availability in an endangered population of killer whales, Orcinus orca

Cited by 136 publications

References 65 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 rise of Network Ecology: Maps of the topic diversity and scientific collaboration

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

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