Vulnerability of a killer whale social network to disease outbreaks

Spatial roost networks and resource selection of female wild turkeys

Wildlife demography is influenced by behavioural decisions, with sleep being a crucial avian behaviour. Avian species use roost sites to minimize thermoregulation costs, predation risk and enhance foraging efficiency. Sleep locations are often reused, forming networks within the home range. Our study, focusing on female eastern wild turkeys (Meleagris gallopavo silvestris) during the reproductive season, used social network analysis to quantify both roost site selection and network structure. We identified roost networks which were composed of a small percentage of hub roost sites connecting satellite roosts. Hub roosts were characterized by greater values of betweenness (β = 0.62, s.e. = 0.02), closeness (β = 0.59, s.e. = 0.03) and eigenvalue centrality (β = 1.15, s.e. = 0.05), indicating their importance as connectors and proximity to the network's functional centre. The probability of a roost being a hub increased significantly with greater eigenvalue centrality. Female wild turkeys consistently chose roost sites at lower elevations and with greater topographical ruggedness. Hub roost probability was higher near secondary roads and further from water. Our research highlights well-organized roost site networks around hub roosts, emphasizing the importance of further investigations into how these networks influence conspecific interactions, reproduction and resource utilization in wild turkeys.

Spatial networks differ when food supply changes: Foraging strategy of Egyptian fruit bats

Animals are faced with a range of ecological constraints that shape their behavioural decisions. Habitat features that affect resource abundance will also have an impact, especially as regards spatial distribution, which will in turn affect associations between the animals. Here we utilised a network approach, using spatial and genetic data, to describe patterns in use of space (foraging sites) by free-ranging Egyptian fruit bats (Rousettus aegyptiacus) at the Dakhla Oasis in Egypt. We observed a decrease in home range size during spring, when food availability was lowest, which was reflected by differences in space sharing networks. Our data showed that when food was abundant, space sharing networks were less connected and more related individuals shared more foraging sites. In comparison, when food was scarce the bats had few possibilities to decide where and with whom to forage. Overall, both networks had high mean degree, suggesting communal knowledge of predictable food distribution.

Sociality and tattoo skin disease among bottlenose dolphins in Shark Bay, Australia

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.

Role of sociality in the response of killer whales to an additive mortality event

In highly social top predators, group living is an ecological strategy that enhances individual fitness, primarily through increased foraging success. Additive mortality events across multiple social groups in populations may affect the social structure, and therefore the fitness, of surviving individuals. This hypothesis was examined in a killer whale (Orcinus orca) population that experienced a 7-y period of severe additive mortality due to lethal interactions with illegal fishing vessels. Using both social and demographic analyses conducted on a unique long-term dataset encompassing periods before, during, and after this event, results indicated a decrease in both the number and the mean strength of associations of surviving individuals during the additive mortality period. A positive significant correlation between association strength and apparent survival suggested that the fitness of surviving individuals was impacted by the additive mortality event. After this event, individuals responded to the loss of relatives in their social groups by associating with a greater number of other social groups, likely to maintain a functional group size that maximized their foraging success. However, these associations were loose; individuals did not reassociate in highly stable social groups, and their survival remained low years after the mortality event. These findings demonstrate how the disruption of social structure in killer whales may lead to prolonged negative effects of demographic stress beyond an additive mortality event. More importantly, this study shows that sociality has a key role in the resilience of populations to human-induced mortality; this has major implications for the conservation of highly social and long-lived species.

Role of social behaviour in the epidemiology of lobomycosis-like disease (LLD) in estuarine common bottlenose dolphins from Ecuador

Lobomycosis-like disease (LLD) is a chronic granulomatous skin disorder that affects Delphinidae worldwide. LLD has been observed in common bottlenose dolphins Tursiops truncatus from the Gulf of Guayaquil, Ecuador, since 1990. Although exogenous factors such as salinity and pollution may play a role in the pathogenesis of this disease in estuarine and coastal dolphin communities, we hypothesized that demography and social behaviour may also influence its epidemiology. To address this issue, the role of social behaviour in the distribution and prevalence of LLD was assessed through hierarchical cluster analysis and spatial distribution analysis in 7 dolphin communities inhabiting the inner estuary. Individuals with LLD lesions were observed in 5 of the 7 dolphin communities, with 13 of the 163 (8%) animals being positive, all adults. Among 8 dolphins of known sex, LLD affected mostly males (86%), who usually were found in pairs. Prevalence was low to moderate (5.1-13%) in dolphin communities where low-rank males had LLD. Conversely, it was high (44.4%, n = 9) in a small community where a high-rank male was infected. LLD affected both dolphins in 2 of the 4 male pairs for which large time series data were available, suggesting horizontal transmission due to contact. Thus, association with LLD-positive males seems to be an important risk factor for infections. Additionally, low-rank males had larger home ranges than high-rank males, indicating that low-status LLD-affected dolphins are likely responsible for the geographic dissemination of the disease in this population.

Advances from the nexus of animal behaviour and pathogen transmission: new directions and opportunities using contact networks

Contact network models have enabled significant advances in understanding the influence of behaviour on parasite and pathogen transmission. They are an important tool that links variation in individual behaviour, to epidemiological consequences at the population level. Here, in our introduction to this special issue, we highlight the importance of applying network approaches to disease ecological and epidemiological questions, and how this has provided a much deeper understanding of these research areas. Recent advances in tracking host behaviour (bio-logging: e.g., GPS tracking, barcoding) and tracking pathogens (high-resolution sequencing), as well as methodological advances (multi-layer networks, computational techniques) started producing exciting new insights into disease transmission through contact networks. We discuss some of the exciting directions that the field is taking, some of the challenges, and importantly the opportunities that lie ahead. For instance, we suggest to integrate multiple transmission pathways, multiple pathogens, and in some systems, multiple host species, into the next generation of network models. Corresponding opportunities exist in utilising molecular techniques, such as high-resolution sequencing, to establish causality in network connectivity and disease outcomes. Such novel developments and the continued integration of network tools offers a more complete understanding of pathogen transmission processes, their underlying mechanisms and their evolutionary consequences.

The risk of disease to great apes: simulating disease spread in orang-utan (Pongo pygmaeus wurmbii) and chimpanzee (Pan troglodytes schweinfurthii) association networks

All great ape species are endangered, and infectious diseases are thought to pose a particular threat to their survival. As great ape species vary substantially in social organisation and gregariousness, there are likely to be differences in susceptibility to disease types and spread. Understanding the relation between social variables and disease is therefore crucial for implementing effective conservation measures. Here, we simulate the transmission of a range of diseases in a population of orang-utans in Sabangau Forest (Central Kalimantan) and a community of chimpanzees in Budongo Forest (Uganda), by systematically varying transmission likelihood and probability of subsequent recovery. Both species have fission-fusion social systems, but differ considerably in their level of gregariousness. We used long-term behavioural data to create networks of association patterns on which the spread of different diseases was simulated. We found that chimpanzees were generally far more susceptible to the spread of diseases than orang-utans. When simulating different diseases that varied widely in their probability of transmission and recovery, it was found that the chimpanzee community was widely and strongly affected, while in orang-utans even highly infectious diseases had limited spread. Furthermore, when comparing the observed association network with a mean-field network (equal contact probability between group members), we found no major difference in simulated disease spread, suggesting that patterns of social bonding in orang-utans are not an important determinant of susceptibility to disease. In chimpanzees, the predicted size of the epidemic was smaller on the actual association network than on the mean-field network, indicating that patterns of social bonding have important effects on susceptibility to disease. We conclude that social networks are a potentially powerful tool to model the risk of disease transmission in great apes, and that chimpanzees are particularly threatened by infectious disease outbreaks as a result of their social structure.

Social structure of a semi-free ranging group of mandrills (Mandrillus sphinx): a social network analysis

The difficulty involved in following mandrills in the wild means that very little is known about social structure in this species. Most studies initially considered mandrill groups to be an aggregation of one-male/multifemale units, with males occupying central positions in a structure similar to those observed in the majority of baboon species. However, a recent study hypothesized that mandrills form stable groups with only two or three permanent males, and that females occupy more central positions than males within these groups. We used social network analysis methods to examine how a semi-free ranging group of 19 mandrills is structured. We recorded all dyads of individuals that were in contact as a measure of association. The betweenness and the eigenvector centrality for each individual were calculated and correlated to kinship, age and dominance. Finally, we performed a resilience analysis by simulating the removal of individuals displaying the highest betweenness and eigenvector centrality values. We found that related dyads were more frequently associated than unrelated dyads. Moreover, our results showed that the cumulative distribution of individual betweenness and eigenvector centrality followed a power function, which is characteristic of scale-free networks. This property showed that some group members, mostly females, occupied a highly central position. Finally, the resilience analysis showed that the removal of the two most central females split the network into small subgroups and increased the network diameter. Critically, this study confirms that females appear to occupy more central positions than males in mandrill groups. Consequently, these females appear to be crucial for group cohesion and probably play a pivotal role in this species.

Networks and the ecology of parasite transmission: A framework for wildlife parasitology

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Animal behaviour can generate heterogeneities in parasite transmission.

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Network models represent these heterogeneities as links (edges) among hosts (nodes).

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Variety of lifecycles and transmission methods can be represented using networks.

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Framework for exploring a range of ecological questions about parasite transmission.

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Challenges remain in their application to wildlife parasitology.

Social network analysis has recently emerged as a popular tool for understanding disease transmission in host populations. Although social networks have most extensively been applied to modelling the transmission of diseases through human populations, more recently the method has been applied to wildlife populations. The majority of examples from wildlife involve modelling the transmission of contagious microbes (mainly viruses and bacteria), normally in context of understanding wildlife disease epidemics. However, a growing number of studies have used networks to explore the ecology of parasite transmission in wildlife populations for a range of endemic parasites representing a diversity of life cycles and transmission methods. This review addresses the application of network models in representing the transmission of parasites with more complex life cycles, and illustrates the way in which this approach can be used to answer ecological questions about the transmission of parasites in wildlife populations.

The interplay between social networks and culture: theoretically and among whales and dolphins

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour.

Identifying the starting point of a spreading process in complex networks

When dealing with the dissemination of epidemics, one important question that can be asked is the location where the contamination began. In this paper, we analyze three spreading schemes and propose and validate an effective methodology for the identification of the source nodes. The method is based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness, and eigenvector centrality. We show that the source node tends to have the highest measurement values. The potential of the methodology is illustrated with respect to three theoretical complex network models as well as a real-world network, the email network of the University Rovira i Virgili.

Network models: an underutilized tool in wildlife epidemiology?

Although the approach of contact network epidemiology has been increasing in popularity for studying transmission of infectious diseases in human populations, it has generally been an underutilized approach for investigating disease outbreaks in wildlife populations. In this paper we explore the differences between the type of data that can be collected on human and wildlife populations, provide an update on recent advances that have been made in wildlife epidemiology by using a network approach, and discuss why networks might have been underutilized and why networks could and should be used more in the future. We conclude with ideas for future directions and a call for field biologists and network modelers to engage in more cross-disciplinary collaboration.

Wildlife diseases: from individuals to ecosystems

1. We review our ecological understanding of wildlife infectious diseases from the individual host to the ecosystem scale, highlighting where conceptual thinking lacks verification, discussing difficulties and challenges, and offering potential future research directions. 2. New molecular approaches hold potential to increase our understanding of parasite interactions within hosts. Also, advances in our knowledge of immune systems makes immunological parameters viable measures of parasite exposure, and useful tools for improving our understanding of causal mechanisms. 3. Studies of transmission dynamics have revealed the importance of heterogeneity in host behaviour and physiology, and of contact processes operating at different spatial and temporal scales. An important future challenge is to determine the key transmission mechanisms maintaining the persistence of different types of diseases in the wild. 4. Regulation of host populations is too complex to consider parasite effects in isolation from other factors. One solution is to seek a unified understanding of the conditions under which (and the ecological rules determining when) population scale impacts of parasites can occur. 5. Good evidence now shows that both direct effects of parasites, and trait mediated indirect effects, frequently mediate the success of invasive species and their impacts on recipient communities. A wider exploration of these effects is now needed. 6. At the ecosystem scale, research is needed to characterize the circumstances and conditions under which both fluxes in parasite biomass, and trait mediated effects, are significant in ecosystem processes, and to demonstrate that parasites do indeed increase 'ecosystem health'. 7. There is a general need for more empirical testing of predictions and subsequent development of theory in the classic research cycle. Experimental field studies, meta-analyses, the collection and analysis of long-term data sets, and data constrained modelling, will all be key to advancing our understanding. 8. Finally, we are only now beginning to understand the importance of cross-scale interactions associated with parasitism. Such interactions may offer key insights into bigger picture questions such as when and how different regulatory factors are important, when disease can cause species extinctions, and what characteristics are indicative of functionally resilient ecosystems.

Disease spread in small-size directed networks: epidemic threshold, correlation between links to and from nodes, and clustering

Network epidemiology has mainly focused on large-scale complex networks. It is unclear whether findings of these investigations also apply to networks of small size. This knowledge gap is of relevance for many biological applications, including meta-communities, plant-pollinator interactions and the spread of the oomycete pathogen Phytophthora ramorum in networks of plant nurseries. Moreover, many small-size biological networks are inherently asymmetrical and thus cannot be realistically modelled with undirected networks. We modelled disease spread and establishment in directed networks of 100 and 500 nodes at four levels of connectance in six network structures (local, small-world, random, one-way, uncorrelated, and two-way scale-free networks). The model was based on the probability of infection persistence in a node and of infection transmission between connected nodes. Regardless of the size of the network, the epidemic threshold did not depend on the starting node of infection but was negatively related to the correlation coefficient between in- and out-degree for all structures, unless networks were sparsely connected. In this case clustering played a significant role. For small-size scale-free directed networks to have a lower epidemic threshold than other network structures, there needs to be a positive correlation between number of links to and from nodes. When this correlation is negative (one-way scale-free networks), the epidemic threshold for small-size networks can be higher than in non-scale-free networks. Clustering does not necessarily have an influence on the epidemic threshold if connectance is kept constant. Analyses of the influence of the clustering on the epidemic threshold in directed networks can also be spurious if they do not consider simultaneously the effect of the correlation coefficient between in- and out-degree.

Cross-reactivity between immunoglobulin G antibodies of whales and dolphins correlates with evolutionary distance

Growing morphological and molecular evidence indicates that the porpoises, dolphins, and whales evolved within the even-toed ungulates, formerly known as Artiodactyla. These animals are now grouped in the Cetartiodactyla. We evaluated the antigenic similarity of the immunoglobulin G (IgG) molecules of 15 cetacean species and the domestic cow. The similarity was scored using three distinct antibodies raised against bottlenose dolphin (Tursiops truncatus) IgG in a Western blot, an indirect enzyme-linked immunosorbent assay (ELISA), and a competitive ELISA format. A score was generated for the genetic distance between each species and T. truncatus using the cytochrome b sequence. Each antibody displayed a distinct pattern of reactivity with the IgG antibodies of the various species. The monoclonal antibody (MAb) specific for the gamma heavy chain of T. truncatus was reactive with all monodontids, delphinids, and phocoenids. The light-chain-specific MAb reacted with IgG of delphinoid and phocoenid species and one of the two mysticete species tested. The polyclonal antibody was broadly cross-reactive across all cetaceans and the domestic cow. Using the MAb specific for the gamma heavy chain, the degree of IgG cross-reactivity ranged from less than 17% for the mysticetes to 106% for killer whale Orcinus orca. The IgG in beaked whale and baleen whale sera was significantly less cross-reactive with bottlenose dolphin IgG than sera from other toothed whales. A strong negative correlation was demonstrated between antigenic cross-reactivity of IgG molecules and the genetic distance of their hosts. The data generated will be useful for the development of clinical serodiagnostics in diverse cetacean species.