Dolphins online social network - A social network of bottlenose dolphins. The dataset contains a list of all of links, where a link represents frequent associations between dolphins.

Undirected social network of frequent associations between 62 dolphins in a community living off Doubtful Sound, New Zealand, as compiled by Lusseau et al. (2003), and made available by Mark Newman (http://www-personal.umich.edu/~mejn/netdata/).

Lusseau, D., Schneider, K., Boisseau, O. J., Haase, P., Slooten, E., & Dawson, S. M. (2003). The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations - Can geographic isolation explain this unique trait? Behavioral Ecology and Sociobiology, 54, 396-405. DOI: 10.1007/s00265-003-0651-y

Animal Social Networks

Animal Networks - Four networks: an overall network that does not take behaviour into account, and the socialize network, the travel network and the forage network that correspond to their respective behaviours.

Standardized network metrics for each calf (n = 67). (DOCX)

Ranging behaviour and temporal patterns of individuals are known to be fundamental sources of variation in social networks. Spatiotemporal dynamics can both provide and inhibit opportunities for individuals to associate, and should therefore be considered in social analysis. This study investigated the social structure of a Lahille’s bottlenose dolphin (Tursiops truncatus gephyreus) population, which shows different spatiotemporal patterns of use and gregariousness between individuals. For this we constructed an initial social network using association indices corrected for gregariousness and then uncovered affiliations from this social network using generalized affiliation indices. The association-based social network strongly supported that this dolphin population consists of four social units highly correlated to spatiotemporal use patterns. Excluding the effects of gregariousness and spatiotemporal patterns, the affiliation-based social network suggested an additional two social units. Although the affiliation-based social units shared a large part of their core areas, space and/or time use by individuals of the different units were generally distinct. Four of the units were strongly associated with both estuarine and shallow coastal areas, while the other two units were restricted to shallow coastal waters to the south (SC) and north of the estuary (NC), respectively. Interactions between individuals of different social units also occurred, but dolphins from the NC were relatively more isolated and mainly connected to SC dolphins. From a conservation management perspective, it is recommended that information about the dolphin social units should be incorporated in modelling intra-population dynamics and viability, as well as for investigating patterns of gene flow among them.

Two text files containing data and one .R file with R code. These files are sufficient to recreate the analysis found in the manuscript "Dolphin social phenotypes vary in response to food availability but not the North Atlantic Oscillation index", published in Proceedings of the Royal Society B: Biological Sciences in October 2023 and corrected in October 2024 (see below).In brief, the data are based on regular observations of bottlenose dolphins (Tursiops truncatus) off the north east coast of Scotland between 1990 and 2021 inclusive. Regular observations of dolphins co-occurring in groups allowed us to infer social associations and to build social networks. We built social networks for each month and each year there were sufficient observations. From each network we calculated three social network measures (strength, weighted clustering coefficient, and closeness) and we then analyses how these traits vary at both the yearly and monthly scale in response to variation in the North Atlantic Oscillation index and to salmon abundance (data obtained from other sources). We upload the dataset both before filtering (suffix "raw", including individuals of unknown sex and with only a few observations per year/month) and the dataset after filtering which is used for the analyses in the paper.The correction revolves around the calculation of the social network measure "closeness" using the R package igraph. We determined that this function treats the interaction strengths between individuals as distances or costs, where higher values mean more distant/less well-connected. This interpretation of interaction strengths is opposite to how they are interpreted for most other social network metrics, where higher values indicate closer and more well-connected individuals. The consequences are that the closeness values we analysed in the original version of the article are incorrect, and so the results and conclusions around closeness are erroneous. We then re-calculated closeness using a different R package, tnet, which treats interaction strengths in the manner expected i.e., higher values mean closer together, and re-ran all analyses involving closeness. See the supporting documentation of the paper for a description of the changes to the results in full."Dol Soc by Env Yearly data tC.txt" is the data frame for the yearly scale analysis, with network metrics per individual per year and environmental variables per year. Columns are:dol_name - the unique ID of the dolphinyear - the year of observationsex - sex of the dolphin, 1 = male, 2 = femaleyear_nao - the north atlantic oscillation index record for that yearyear_fish - the yearly salmon abudance measureindiv_str - the individual's strength in that yearindiv_cc - the individual's weighted lcustering coefficient in that yearindiv_close - the individual's closeness in that year"Dol Soc by Env Monthly data tC.txt" is the data frame for the monthly scale analysis, with network metrics per individual per month and environmental variables per month. Columns are:dol_name - the unique ID of the dolphinyear - the year of observationmonth - the month of observation, coded numerically i.e., April = 4sex - sex of the dolphin, 1 = male, 2 = femalemonth_year_nao - the north atlantic oscillation index record for that monthmonth_year_fish - the monthly salmon abundance measureindiv_str - the individual's strength in that monthindiv_cc - the individual's weighted clustering coefficient in that monthindiv_close - the individual's closeness in that month"Dol Soc by Env Monthly data tC raw.txt" and "Dol Soc by Env Yearly data tC raw.txt" are the above datasets but prior to filtering (see R code)."Fisher & Cheney code Dol Soc by Env tC.R" is the R code file to recreate the analyses found in the manuscript (a series of mixed-effect models). We used R version 4.3.1 for the analysis. Note requires loading the packages "glmmTMB" (version 1.1.7) and "car" (version 3.1-2) so they must be installed first. Additionally, you will need to save the following R script: https://github.com/hschielzeth/RandomSlopeR2/blob/master/condR.R and refer to it with the source() command to enable the calculation of conditional repeatabilities.

Datasets used in paper "An Efficient Semi-supervised Community Detection Framework in Social Networks"

Identifying foraging variation within a population and assessing its relationship with social structure is essential to increase knowledge about the evolution of social systems. Here, we investigated individual foraging variation in bottlenose dolphins and its potential influence on their social organization. We used generalized affiliation indices and applied social network analysis to data collected over 4 consecutive years of research in a coastal area subject to significant use and pressure by humans. Our findings revealed variation in foraging behavior among individual bottlenose dolphins, which in turn shapes their social organization. Our results indicated that individuals that frequently foraged within human-altered areas (i.e., shellfish farms) exhibited weaker Strength, Reach, and Affinity compared to others. These bottlenose dolphins profit from a reliable and easily located food source which may increase their energy intake and inter-individual competition. In contrast, indi...

Collection of the R Scripts used to perform the analyses used in the study

Effect of number of sightings on social network measures for estuarine-resident common bottlenose dolphins (Tursiops truncatus) in North Carolina.

Behavioural differences among social groups can arise from differing ecological conditions, genetic predispositions and/or social learning. In the past, social learning has typically been inferred as responsible for the spread of behaviour by the exclusion of ecological and genetic factors. This 'method of exclusion' was used to infer that 'sponging', a foraging behaviour involving tool use in the bottlenose dolphin (Tursiops aduncus) population in Shark Bay, Western Australia, was socially transmitted. However, previous studies were limited in that they never fully accounted for alternative factors, and that social learning, ecology and genetics are not mutually exclusive in causing behavioural variation. Here, we quantified the importance of social learning on the diffusion of sponging, for the first time explicitly accounting for ecological and genetic factors, using a multi-network version of 'network-based diffusion analysis' (NBDA). Our results provide compelling support for previous findings that sponging is vertically socially transmitted from mother to (primarily female) offspring. This research illustrates the utility of social network analysis in elucidating the explanatory mechanisms behind the transmission of behaviour in wild animal populations.

Social relationships represent an adaptive behavioural strategy that can provide fitness benefits to individuals. Within mammalian societies, delphinids are known to form diverse grouping patterns and show a variety of social systems. However, how ecological and intrinsic factors have shaped the evolution of such diverse societies is still not well understood. In this study we used photo-identification data and biopsy samples collected between March 2013 and October 2015 in Coffin Bay, a heterogeneous environment in South Australia, to investigate the social structure of southern Australian bottlenose dolphins (Tursiops cf. australis). Based on data from 657 groups of dolphins we used generalized affiliation indices, and applied social network and modularity methods to study affiliation patterns among individuals and investigate the potential presence of social communities within the population. In addition, we investigated genetic relatedness and kinship relationships within and between the communities identified. Modularity analysis revealed that the Coffin Bay population is structured into two similar sized, mixed-sex communities which differed in ranging patterns, affiliation levels and network metrics. Lagged association rates also indicated that non-random affiliations persisted over the study period. The genetic analyses suggested that there was higher relatedness, and a higher proportion of inferred full-sibs and half-sibs, within than between communities. We propose that differences in environmental conditions between the bays and kinship relationships are important factors contributing to the delineation and maintenance of this social structure.

Individually identified dolphins within and between sessions of a capture-mark-recapture survey of estuarine-resident bottlenose dolphins (Tursiops truncatus) in southern North Carolina.

Data used to produce the nodes in publication figure 4 and 7 - Figure 4: Social network (half-weight indices) of individual common bottlenose dolphins of known sex from Walvis Bay, Namibia during the study period (2015-2019). Figure 7: Social network (generalised affiliation indices) of individual common bottlenose dolphins of known sex from Walvis Bay, Namibia during the study period (2015-2019).

Social behavior is an important driver of infection dynamics, though identifying the social interactions that foster infectious disease transmission is challenging. Here we examine how social behavior impacts disease transmission in Indo-Pacific bottlenose dolphins (Tursiops aduncus) using an easily identifiable skin disease and social network data. We analyzed tattoo skin disease (TSD) lesions based on photographs collected as part of a 34-year longitudinal study in relation to the sociality of T. aduncus using three metrics (degree, time spent socializing, and time in groups) and network structure, using the k-test. We show that calves with TSD in the second year of life associated more with TSD-positive individuals in the first year of life compared with calves that did not have TSD. Additionally, the network k-test showed that the social network links are epidemiologically relevant for transmission. However, degree, time spent in groups, and time spent socializing were not significantly different between infected and uninfected groups. Our findings indicate that association with infected individuals is predictive of an individual’s risk for TSD and that the social association network can serve as a proxy for studying the epidemiology of skin diseases in bottlenose dolphins.

Methods Data was collected in Monkey Mia, Western Australia from boat based observations. Data presented here as been limited in accordance with the linked publication and identifiers have been removed.

This data supports the research conducted in the following paper - Submitted to Animal BehaviourHomophily drives use of a risky shallow-water environment by common bottlenose dolphins (Tursiops truncatus) in NamibiaSocial mammals often associate with similar individuals, a tendency known as homophily. Homophily drives social structure in populations and provides fitness benefits by improving inter-individual cooperation and decreasing the cognitive effort required to evaluate collaborators. We investigated the factors (age class, sex, habitat preference, local space use overlap and stranding history) influencing the use of a high-risk tidal environment by a resident population of common bottlenose dolphins (Tursiops truncatus) from Walvis Bay, Namibia. We combined photographic mark-recapture with social network analysis and applied multiple regression quadratic assignment procedures to investigate homophily in this population. Bottlenose dolphins of the same age class, sex and habitat preference were more strongly associated, and the core of this population's social network was comprised of lagoon users (individuals regularly using both the Walvis Bay lagoon and bay habitats). Although males and subadults (of both sexes) were the most frequent users of this habitat, females with dependent calves also regularly utilised this habitat. Additionally, the majority of previously stranded dolphins (71%) were still observed using the lagoon habitat, despite having experienced the risks of potentially life-threatening stranding events. We suggest that the use of this potentially risky, but resource rich habitat may be socially learned, however the mode of transmission of this behaviour (vertically or horizontally) has yet to be investigated. Specialised foraging strategies such as this are often the first step towards separation of a population into behaviourally segregated communities, which may lead to fine-scale genetic differentiation over time.

Understanding individual interactions within a community or population provides valuable insight into its social system, ecology and, ultimately, resilience against external stimuli. Here, we used photo-identification data, generalised affiliation indices and social network analyses to investigate dyadic relationships, assortative interactions and social clustering in the Australian humpback dolphin (Sousa sahulensis). Boat-based surveys were conducted between May 2013 and October 2015 around the North West Cape, Western Australia. Our results indicated a fission-fusion society, characterised by non-random dyadic relationships. Assortative interactions were identified both within and between sexes, and were higher amongst members of the same sex, indicating same-sex preferred affiliations and sexual segregation. Assortative interactions by geographic locations were also identified, but with no evidence of distinct social communities or clusters, or affiliations based on residency patter...

Chi square pair-wise comparison of the proportion of permanently marked individuals for social networks A-E.

Interactions between mammalian social groups are generally antagonistic as individuals in groups cooperate to defend resources from non-members. Members of the family Delphinidae inhabit a three-dimensional habitat where resource defense is usually impractical. Here, we describe a long-term partial fusion of two communities of Atlantic spotted dolphins (Stenella frontalis). The northern community, studied for 30 years, immigrated 160 km to the range of the southern community, observed for 20 years. Both communities featured fission-fusion grouping patterns, strongest associations between adult males, and frequent affiliative contact between individuals. For the five-year period following the immigration, we found members of all age classes and both sexes in mixed groups, but there was a strong bias toward finding immigrant males in mixed groups. Some association levels between males, and males and females, from different communities were as high as the highest within-community associations. Affiliative contacts indicate that these individuals were forming bonds, likely for future mating opportunities. The mixing of two separate social groups with new bond formation is rare in terrestrial mammal groups. Such mixing between spotted dolphin groups suggests that adaptations to respond aggressively to 'outsiders' is diminished in this species and possibly other ecologically similar dolphins.