Dynamic social networks in guppies (Poecilia reticulata)

Social competence improves the performance of biomimetic robots leading live fish

Collective motion is commonly modeled with static interaction rules between agents. Substantial empirical evidence indicates, however, that animals may adapt their interaction rules depending on a variety of factors and social contexts. Here, we hypothesized that leadership performance is linked to the leader's responsiveness to the follower's actions and we predicted that a leader is followed longer if it adapts to the follower's avoidance movements. We tested this prediction with live guppies that interacted with a biomimetic robotic fish programmed to act as a 'socially competent' leader. Fish that were avoiding the robot were approached more carefully in future approaches. In two separate experiments we then asked how the leadership performance of the socially competent robot leader differed to that of a robot leader that either approached all fish in the same, non-responsive, way or one that did change its approach behavior randomly, irrespective of the fish's actions. We found that (1) behavioral variability itself appears attractive and that socially competent robots are better leaders which (2) require fewer approach attempts to (3) elicit longer average following behavior than non-competent agents. This work provides evidence that social responsiveness to avoidance reactions plays a role in the social dynamics of guppies. We showcase how social responsiveness can be modeled and tested directly embedded in a living animal model using adaptive, interactive robots.

Social learning mechanisms shape transmission pathways through replicate local social networks of wild birds

The emergence and spread of novel behaviours via social learning can lead to rapid population-level changes whereby the social connections between individuals shape information flow. However, behaviours can spread via different mechanisms and little is known about how information flow depends on the underlying learning rule individuals employ. Here, comparing four different learning mechanisms, we simulated behavioural spread on replicate empirical social networks of wild great tits and explored the relationship between individual sociality and the order of behavioural acquisition. Our results reveal that, for learning rules dependent on the sum and strength of social connections to informed individuals, social connectivity was related to the order of acquisition, with individuals with increased social connectivity and reduced social clustering adopting new behaviours faster. However, when behavioural adoption depends on the ratio of an individuals' social connections to informed versus uninformed individuals, social connectivity was not related to the order of acquisition. Finally, we show how specific learning mechanisms may limit behavioural spread within networks. These findings have important implications for understanding whether and how behaviours are likely to spread across social systems, the relationship between individuals' sociality and behavioural acquisition, and therefore for the costs and benefits of sociality.

Emergent social structure is typically not associated with survival in a facultatively social mammal

For social animals, group social structure has important consequences for disease and information spread. While prior studies showed individual connectedness within a group has fitness consequences, less is known about the fitness consequences of group social structure for the individuals who comprise the group. Using a long-term dataset on a wild population of facultatively social yellow-bellied marmots (Marmota flaviventer), we showed social structure had largely no relationship with survival, suggesting consequences of individual social phenotypes may not scale to the group social phenotype. An observed relationship for winter survival suggests a potentially contrasting direction of selection between the group and previous research on the individual level; less social individuals, but individuals in more social groups experience greater winter survival. This work provides valuable insights into evolutionary implications across social phenotypic scales.

Group composition of individual personalities alters social network structure in experimental populations of forked fungus beetles

Social network structure is a critical group character that mediates the flow of information, pathogens and resources among individuals in a population, yet little is known about what shapes social structures. In this study, we experimentally tested whether social network structure depends on the personalities of individual group members. Replicate groups of forked fungus beetles (Bolitotherus cornutus) were engineered to include only members previously assessed as either more social or less social. We found that individuals expressed consistent personalities across social contexts, exhibiting repeatable numbers of interactions and numbers of partners. Groups composed of more social individuals formed networks with higher interaction rates, higher tie density, higher global clustering and shorter average shortest paths than those composed of less social individuals. We highlight group composition of personalities as a source of variance in group traits and a potential mechanism by which networks could evolve.

Exploratory decisions of Trinidadian guppies when uncertain about predation risk

Animals can reduce their uncertainty of predation risk by gathering new information via exploration behaviour. However, a decision to explore may also be costly due to increased predator exposure. Here, we found contextual effects of predation risk on the exploratory activity of Trinidadian guppies Poecilia reticulata in a novel environment. First, guppies were exposed to a 3-day period of either high or low background predation risk in the form of repeated exposure to either injured conspecific cues (i.e. alarm cues) or control water, respectively. A day later, guppies were moved into a testing arena with limited visual information due to structural barriers and were then presented with an acute chemical stimulus, either alarm cues (a known and reliable indicator of risk), a novel odour (an ambiguous cue), or control water. In the presence of control water, guppies from high and low background risk showed a similar willingness to explore the arena. However, high-risk individuals significantly reduced their spatial evenness, although not their movement latency, in the presence of both the alarm and novel cues. When these high-risk individuals were a member of a shoal, they became willing to explore the environment more evenly in the presence of alarm cues while remaining cautious toward the novel cue, indicating an effect of the greater uncertainty associated with the novel cue. In contrast, low-risk guppies showed a willingness to explore the arena regardless of acute threat or social context. Such contextual effects of background risk and social context highlight the complexity of exploratory decisions when uncertain.

Social selection is density dependent but makes little contribution to total selection in New Zealand giraffe weevils

Social selection occurs when traits of interaction partners influence an individual's fitness and can alter total selection strength. However, we have little idea of what factors influence social selection's strength. Further, social selection only contributes to overall selection when there is phenotypic assortment, but simultaneous estimates of social selection and phenotypic assortment are rare. Here, we estimated social selection on body size in a wild population of New Zealand giraffe weevils (Lasiorhynchus barbicornis). We measured phenotypic assortment by body size and tested whether social selection varied with sex ratio, density and interacted with the body size of the focal individual. Social selection was limited and unaffected by sex ratio or the size of the focal individual. However, at high densities social selection was negative for both sexes, consistent with size-based competitive interactions for access to mates. Phenotypic assortment was always close to zero, indicating negative social selection at high densities will not impede the evolution of larger body sizes. Despite its predicted importance, social selection may only influence evolutionary change in specific contexts, leaving direct selection to drive evolutionary change.

Personality composition determines social learning pathways within shoaling fish

In shaping how individuals explore their environment and interact with others, personality may mediate both individual and social learning. Yet increasing evidence indicates that personality expression is contingent on social context, suggesting that group personality composition may be key in determining how individuals learn about their environment. Here, we used recovery latency following simulated predator attacks to identify Trinidadian guppies (Poecilia reticulata) that acted in a consistently bold or shy manner. We then employed network-based diffusion analysis to track the spread of a novel foraging behaviour through groups containing different proportions of bold and shy fish. Informed associates promoted learning to a greater extent in bold individuals, but only within groups composed predominately of bold fish. As the proportion of shy fish within groups increased, bold individuals instead emerged as especially effective demonstrators that facilitated learning in others. Individuals were also more likely to learn overall within shy-dominated groups than in bold-dominated ones. We demonstrate that whether and how individuals learn is conditional on group personality composition, indicating that selection may favour traits enabling individuals to better match their behavioural phenotype to their social environment.

Sender and receiver experience alters the response of fish to disturbance cues

Predation is a pervasive selection pressure, shaping morphological, physiological, and behavioral phenotypes of prey species. Recent studies have begun to examine how the effects of individual experience with predation risk shapes the use of publicly available risk assessment cues. Here, we investigated the effects of prior predation risk experience on disturbance cue production and use by Trinidadian guppies Poecilia reticulata under laboratory conditions. In our first experiment, we demonstrate that the response of guppies from a high predation population (Lopinot River) was dependent upon the source of disturbance cue senders (high vs. low predation populations). However, guppies collected from a low predation site (Upper Aripo River) exhibited similar responses to disturbance cues, regardless of the sender population. In our second experiment, we used laboratory strain guppies exposed to high versus low background risk conditions. Our results show an analogous response patterns as shown for our first experiment. Guppies exposed to high background risk conditions exhibited stronger responses to the disturbance cues collected from senders exposed to high (vs. low) risk conditions and guppies exposed to low risk conditions were not influenced by sender experience. Combined, our results suggest that experience with background predation risk significantly impacts both the production of and response to disturbance cues in guppies.

An interaction mechanism for the maintenance of fission-fusion dynamics under different individual densities

Animals often show high consistency in their social organisation despite facing changing environmental conditions. Especially in shoaling fish, fission-fusion dynamics that describe for which periods individuals are solitary or social have been found to remain unaltered even when density changed. This compensatory ability is assumed to be an adaptation towards constant predation pressure, but the mechanism through which individuals can actively compensate for density changes is yet unknown. The aim of the current study is to identify behavioural patterns that enable this active compensation. We compared the fission-fusion dynamics of two populations of the live-bearing Atlantic molly (Poecilia mexicana) that live in adjacent habitats with very different predator regimes: cave mollies that inhabit a low-predation environment inside a sulfidic cave with a low density of predatory water bugs (Belostoma sp.), and mollies that live directly outside the cave (henceforth called "surface" mollies) in a high-predation environment. We analysed their fission-fusion dynamics under two different fish densities of 12 and 6 fish per 0.36 m2. As expected, surface mollies spent more time being social than cave mollies, and this difference in social time was a result of surface mollies being less likely to discontinue social contact (once they had a social partner) and being more likely to resume social contact (once alone) than cave mollies. Interestingly, surface mollies were also less likely to switch among social partners than cave mollies. A random walk simulation predicted each population to show reduced social encounters in the low density treatment. While cave mollies largely followed this prediction, surface mollies maintained their interaction probabilities even at low density. Surface mollies achieved this by a reduction in the size of a convex polygon formed by the group as density decreased. This may allow them to largely maintain their fission-fusion dynamics while still being able to visit large parts of the available area as a group. A slight reduction (21%) in the area visited at low densities was also observed but insufficient to explain how the fish maintained their fission-fusion dynamics. Finally, we discuss potential movement rules that could account for the reduction of polygon size and test their performance.

Hierarchically embedded interaction networks represent a missing link in the study of behavioral and community ecology

Because genes and phenotypes are embedded within individuals, and individuals within populations, interactions within one level of biological organization are inherently linked to interactors at others. Here, we expand the network paradigm to consider that nodes can be embedded within other nodes, and connections (edges) between nodes at one level of organization form "bridges" for connections between nodes embedded within them. Such hierarchically embedded networks highlight two central properties of biological systems: 1) processes occurring across multiple levels of organization shape connections among biological units at any given level of organization and 2) ecological effects occurring at a given level of organization can propagate up or down to additional levels. Explicitly considering the embedded structure of evolutionary and ecological networks can capture otherwise hidden feedbacks and generate new insights into key biological phenomena, ultimately promoting a broader understanding of interactions in evolutionary theory.

Females facilitate male food patch discovery in a wild fish population

Responding to the information provided by others is an important foraging strategy in many species. Through social foraging, individuals can more efficiently find unpredictable resources and thereby increase their foraging success. When individuals are more socially responsive to particular phenotypes than others, however, the advantage they obtain from foraging socially is likely to depend on the phenotype composition of the social environment. We tested this hypothesis by performing experimental manipulations of guppy, Poecilia reticulata, sex compositions in the wild. Males found fewer novel food patches in the absence of females than in mixed-sex compositions, while female patch discovery did not differ regardless of the presence or absence of males. We argue that these results were driven by sex-dependent mechanisms of social association: Markov chain-based fission-fusion modelling revealed that less social individuals found fewer patches and that males reduced sociality when females were absent. In contrast, females were similarly social with or without males. Our findings highlight the relevance of considering how individual- and population-level traits interact in shaping the advantages of social foraging in the wild.

The use of multilayer network analysis in animal behaviour

Network analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as multilayer network analysis, has advanced the study of multifaceted networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour through connected 'layers' of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer network analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.

Social network properties predict chronic aggression in commercial pig systems

Post-mixing aggression in pigs is a harmful and costly behaviour which negatively impacts both animal welfare and farm efficiency. There is vast unexplained variation in the amount of acute and chronic aggression that dyadic behaviours do not fully explain. This study hypothesised that certain pen-level network properties may improve prediction of lesion outcomes due to the incorporation of indirect social interactions that are not captured by dyadic traits. Utilising current SNA theory, we investigate whether pen-level network properties affect the number of aggression-related injuries at 24 hours and 3 weeks post-mixing (24hr-PM and 3wk-PM). Furthermore we compare the predictive value of network properties to conventional dyadic traits. A total of 78 pens were video recorded for 24hr post-mixing. Each aggressive interaction that occurred during this time period was used to construct the pen-level networks. The relationships between network properties at 24hr and the pen level injuries at 24hr-PM and 3wk-PM were analysed using mixed models and verified using permutation tests. The results revealed that network properties at 24hr could predict long term aggression (3wk-PM) better than dyadic traits. Specifically, large clique formation in the first 24hr-PM predicted fewer injuries at 3wk-PM and high betweenness centralisation at 24hr-PM predicted increased rates of injury at 3wk-PM. This study demonstrates that network properties present during the first 24hr-PM have predictive value for chronic aggression, and have potential to allow identification and intervention for at risk groups.

The Tagging Procedure of Visible Implant Elastomers Influences Zebrafish Individual and Social Behavior

One commonly used method to preserve individual identity in the study of social behavior of zebrafish is through silicone-based visible implant elastomers (VIEs), which represent a safe and durable tagging procedure. While the effects of VIE tagging on welfare and general health have been addressed in detail, whether this procedure influences social behavior remains unclear. In this study, we compared individual and group behaviors exhibited by shoals composed of three individuals: two nontagged and one (focal subject) that was either nontagged (control condition) or sham-, purple-, blue-, or yellow tagged. Traditional behavioral parameters of activity, shoaling, and schooling (speed, polarization, and interindividual distances), along with an information-theoretic measure of social interaction (transfer entropy), were used to study the effect of tagging. Our findings indicate that tagging procedure per se significantly increased individual speed of the tagged subjects and of the group. The tagging procedure also altered the level of interaction between individuals, measured by transfer entropy. Conversely, tagging procedure did not influence shoaling and schooling tendencies. These findings suggest that VIE tagging may elicit some level of stress, which may affect some behavioral responses more than others. We recommend use of alternative methods such as multitracking systems when possible.

Using a robotic fish to investigate individual differences in social responsiveness in the guppy

Responding towards the actions of others is one of the most important behavioural traits whenever animals of the same species interact. Mutual influences among interacting individuals may modulate the social responsiveness seen and thus make it often difficult to study the level and individual variation in responsiveness. Here, open-loop biomimetic robots that provide standardized, non-interactive social cues can be a useful tool. These robots are not affected by the live animal's actions but are assumed to still represent valuable and biologically relevant social cues. As this assumption is crucial for the use of biomimetic robots in behavioural studies, we hypothesized (i) that meaningful social interactions can be assumed if live animals maintain individual differences in responsiveness when interacting with both a biomimetic robot and a live partner. Furthermore, to study the level of individual variation in social responsiveness, we hypothesized (ii) that individual differences should be maintained over the course of multiple tests with the robot. We investigated the response of live guppies (Poecilia reticulata) when allowed to interact either with a biomimetic open-loop-controlled fish robot-'Robofish'-or with a live companion. Furthermore, we investigated the responses of live guppies when tested three times with Robofish. We found that responses of live guppies towards Robofish were weaker compared with those of a live companion, most likely as a result of the non-interactive open-loop behaviour of Robofish. Guppies, however, were consistent in their individual responses between a live companion and Robofish, and similar individual differences in response towards Robofish were maintained over repeated testing even though habituation to the test environment was detectable. Biomimetic robots like Robofish are therefore a useful tool for the study of social responsiveness in guppies and possibly other small fish species.

Fear of predation shapes social network structure and the acquisition of foraging information in guppy shoals

Spatio-temporal variation in predation risk is predicted to select for plastic anti-predator responses, which may in turn impact the fine-scale social structure of prey groups and processes mediated by that structure. To test these predictions, we manipulated the ambient predation risk experienced by Trinidadian guppy (Poecilia reticulata) groups before quantifying their social networks and recording individual latencies to approach and solve a novel foraging task. High-risk conditions drove the formation of social networks that were more strongly assorted by body size than those exposed to low ambient risk and promoted longer durations of contact between preferred partners. Additionally, high background predation risk reduced the probability individuals would approach and solve a novel foraging task. Network-based diffusion analysis revealed that while social transmission of the task solution from knowledgeable to naive individuals occurred at a higher rate within low-risk groups, individuals in high-risk groups were particularly likely to investigate the task while shoaling with preferred social partners. Taken together, our results suggest that the structure and functional importance of prey social networks may partly depend on local predation pressure. Furthermore, by influencing individuals' access to information, fear of predation may impact decision-making in a potentially wide array of behavioural contexts.

Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases.

Analysing animal social network dynamics: the potential of stochastic actor-oriented models

Animals are embedded in dynamically changing networks of relationships with conspecifics. These dynamic networks are fundamental aspects of their environment, creating selection on behaviours and other traits. However, most social network‐based approaches in ecology are constrained to considering networks as static, despite several calls for such analyses to become more dynamic.

There are a number of statistical analyses developed in the social sciences that are increasingly being applied to animal networks, of which stochastic actor‐oriented models (SAOMs) are a principal example. SAOMs are a class of individual‐based models designed to model transitions in networks between discrete time points, as influenced by network structure and covariates. It is not clear, however, how useful such techniques are to ecologists, and whether they are suited to animal social networks.

We review the recent applications of SAOMs to animal networks, outlining findings and assessing the strengths and weaknesses of SAOMs when applied to animal rather than human networks. We go on to highlight the types of ecological and evolutionary processes that SAOMs can be used to study.

SAOMs can include effects and covariates for individuals, dyads and populations, which can be constant or variable. This allows for the examination of a wide range of questions of interest to ecologists. However, high‐resolution data are required, meaning SAOMs will not be useable in all study systems. It remains unclear how robust SAOMs are to missing data and uncertainty around social relationships.

Ultimately, we encourage the careful application of SAOMs in appropriate systems, with dynamic network analyses likely to prove highly informative. Researchers can then extend the basic method to tackle a range of existing questions in ecology and explore novel lines of questioning.

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

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.

Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.

Seasonal patterns of mixed species groups in large East African mammals

Mixed mammal species groups are common in East African savannah ecosystems. Yet, it is largely unknown if co-occurrences of large mammals result from random processes or social preferences and if interspecific associations are consistent across ecosystems and seasons. Because species may exchange important information and services, understanding patterns and drivers of heterospecific interactions is crucial for advancing animal and community ecology. We recorded 5403 single and multi-species clusters in the Serengeti-Ngorongoro and Tarangire-Manyara ecosystems during dry and wet seasons and used social network analyses to detect patterns of species associations. We found statistically significant associations between multiple species and association patterns differed spatially and seasonally. Consistently, wildebeest and zebras preferred being associated with other species, whereas carnivores, African elephants, Maasai giraffes and Kirk's dik-diks avoided being in mixed groups. During the dry season, we found that the betweenness (a measure of importance in the flow of information or disease) of species did not differ from a random expectation based on species abundance. In contrast, in the wet season, we found that these patterns were not simply explained by variations in abundances, suggesting that heterospecific associations were actively formed. These seasonal differences in observed patterns suggest that interspecific associations may be driven by resource overlap when resources are limited and by resource partitioning or anti-predator advantages when resources are abundant. We discuss potential mechanisms that could drive seasonal variation in the cost-benefit tradeoffs that underpin the formation of mixed-species groups.