There is growing empirical evidence that animal movement patterns depend on population density. We investigate travelling wave solutions in reaction-diffusion models of animal range expansion in the case that population diffusion is density-dependent. We find that the speed of the selected wave depends critically on the strength of diffusion at low density. For sufficiently large low-density diffusion, the wave propagates at a speed predicted by a simple linear analysis. For small or zero low-density diffusion, the linear analysis is not sufficient, but a variational approach yields exact or approximate expressions for the speed and shape of population fronts.

Stable social groups usually consist of families. However, recent studies have revealed higher level social structure, with interactions between family groups across different levels of social organization in multiple species. The explanations for why this apparently paradoxical behaviour arises appear to be varied and remain untested. Here, we use automated radio-tagging data from over 1000 wasps from 93 nests and social network analyses of over 30 000 nest visitation records to describe and explain interactions across levels of social organization in the eusocial paper wasp Polistes canadensis . We detected three levels of social organization (nest, aggregation and community) which exchange ‘drifter’ individuals within and between levels. The highest level (community) may be influenced by the patchiness of high-quality nesting habitats in which these insects exist. Networks of drifter movements were explained by the distance between nests, the group size of donor nests and the worker-to-brood ratios on donor and recipient nests. These findings provide some explanation for the multi-level social interactions, which may otherwise seem paradoxical. Fitness benefits across multiple levels of social organization should be considered when trying to understand animal societies.

Cooperation among non-kin is well documented in humans and widespread in non-human animals, but explaining the occurrence of cooperation in the absence of inclusive fitness benefits has proven a significant challenge. Current theoretical explanations converge on a single point: cooperators can prevail when they cluster in social space. However, we know very little about the real-world mechanisms that drive such clustering, particularly in systems where cognitive limitations make it unlikely that mechanisms such as score keeping and reputation are at play. Here, we show that Trinidadian guppies (Poecilia reticulata) use a ‘walk away’ strategy, a simple social heuristic by which assortment by cooperativeness can come about among mobile agents. Guppies cooperate during predator inspection and we found that when experiencing defection in this context, individuals prefer to move to a new social environment, despite having no prior information about this new social group. Our results provide evidence in non-human animals that individuals use a simple social partner updating strategy in response to defection, supporting theoretical work applying heuristics to understanding the proximate mechanisms underpinning the evolution of cooperation among non-kin.

Abstract Social monogamy has evolved multiple times and is particularly common in birds. However, it is not well understood why some species live in long‐lasting monogamous partnerships while others change mates between breeding attempts. Here, we investigate mate fidelity in a sequential polygamous shorebird, the snowy plover (Charadrius nivosus), a species in which both males and females may have several breeding attempts within a breeding season with the same or different mates. Using 6 years of data from a well‐monitored population in Bahía de Ceuta, Mexico, we investigated predictors and fitness implications of mate fidelity both within and between years. We show that in order to maximize reproductive success within a season, individuals divorce after successful nesting and re‐mate with the same partner after nest failure. Therefore, divorced plovers, counterintuitively, achieve higher reproductive success than individuals that retain their mate. We also show that different mating decisions between sexes predict different breeding dispersal patterns. Taken together, our findings imply that divorce is an adaptive strategy to improve reproductive success in a stochastic environment. Understanding mate fidelity is important for the evolution of monogamy and polygamy, and these mating behaviors have implications for reproductive success and population productivity.

Analysis of ecological networks is a valuable approach to understanding the vulnerability of systems to disturbance. The tolerance of ecological networks to coextinctions, resulting from sequences of primary extinctions (here termed "knockout extinction models", in contrast with other dynamic approaches), is a widely used tool for modeling network "robustness". Currently, there is an emphasis to increase biological realism in these models, but less attention has been given to the effect of model choices and network structure on robustness measures. Here, we present a suite of knockout extinction models for bipartite ecological networks (specifically plant-pollinator networks) that can all be analyzed on the same terms, enabling us to test the effects of extinction rules, interaction weights, and network structure on robustness. We include two simple ecologically plausible models of propagating extinctions, one new and one adapted from existing models. All models can be used with weighted or binary interaction data. We found that the choice of extinction rules impacts robustness; our two propagating models produce opposing effects in all tests on observed plant-pollinator networks. Adding weights to the interactions tends to amplify the opposing effects and increase the variation in robustness. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity of nodes (specifically, the skewness of the plant degree distribution) in the network. Our analysis therefore reveals the mechanisms and fundamental network properties that drive observed trends in robustness.

Cooperation among non-kin constitutes a conundrum for evolutionary biology. Theory suggests that non-kin cooperation can evolve if individuals differ consistently in their cooperative phenotypes and assort socially by these, such that cooperative individuals interact predominantly with one another. However, our knowledge of the role of cooperative phenotypes in the social structuring of real-world animal populations is minimal. In this study, we investigated cooperative phenotypes and their link to social structure in wild Trinidadian guppies ( Poecilia reticulata ). We first investigated whether wild guppies are repeatable in their individual levels of cooperativeness (i.e. have cooperative phenotypes) and found evidence for this in seven out of eight populations, a result which was mostly driven by females. We then examined the social network structure of one of these populations where the expected fitness impact of cooperative contexts is relatively high, and found assortment by cooperativeness, but not by genetic relatedness. By contrast, and in accordance with our expectations, we did not find assortment by cooperativeness in a population where the expected fitness impact of cooperative contexts is lower. Our results provide empirical support for current theory and suggest that assortment by cooperativeness is important for the evolution and persistence of non-kin cooperation in real-world populations.

This is a pre-copyedited, author-produced PDF of an article accepted for 1 publication in Proceedings of the Royal Society of London, Series B: 2 Biological Sciences following peer review. The version of record Morrell, 3 LJ, Ruxton, GD & James, R. (2011) The temporal selfish herd: predation 4 risk while aggregations form Proceedings of the Royal Society of London 5 Series B 278: 605-612.” is available online at: 6 dx.doi.org/10.1098/rspb.2010.1605 7

The early social environment can influence the health and behaviour of animals, with effects lasting into adulthood. In Europe, around 60% of dairy calves are reared individually during their first eight weeks of life, while others may be housed in pairs or small groups. This study assessed the effects of varying degrees of social contact on weaning stress, health and production during pen rearing, and on the social networks that calves later formed when grouped. Forty female Holstein-Friesian calves were allocated to one of three treatments: individually housed (I, n = 8), pair-housed from day five (P5, n = 8 pairs), and pair-housed from day 28 (P28, n = 8 pairs). From day 48, calves were weaned by gradual reduction of milk over three days, and vocalisations were recorded as a measure of stress for three days before, during and after weaning. Health and production (growth rate and concentrate intakes) were not affected by treatment during the weaning period or over the whole study. Vocalisations were highest post-weaning, and were significantly higher in I calves than pair-reared calves. Furthermore, P28 calves vocalised significantly more than P5 calves. The social network of calves was measured for one month after all calves were grouped in a barn, using association data from spatial proximity loggers. We tested for week-week stability, social differentiation and assortment in the calf network. Additionally, we tested for treatment differences in: coefficient of variation (CV) in association strength, percentage of time spent with ex-penmate (P5 and P28 calves only) and weighted degree centrality (the sum of the strength of an individual's associations). The network was relatively stable from weeks one to four and was significantly differentiated, with individuals assorting based on prior familiarity. P5 calves had significantly higher CV in association strength than I calves in week one (indicating more heterogeneous social associations) but there were no significant treatment differences in week four. The mean percentage of time that individuals spent with their ex-penmate after regrouping decreased from weeks 1-4, though treatment did not affect this. There were also no significant differences in weighted degree centrality between calves in each rearing treatment. These results suggest that early pair-rearing can allow calves the stress buffering benefits of social support (and that this is more effective when calves are paired earlier) without compromising health or production, and sheds light on the early development of social behaviour in cattle.

A species-wide study shows that the Hawaiian crow Corvus hawaiiensis is a highly proficient tool user, creating opportunities for comparative studies with tool-using New Caledonian crows and other corvids. Birds in the crow family are renowned for their cognitive abilities. The New Caledonian crow Corvus moneduloides is well known for its ability to make and use foraging tools. Christian Rutz et al. show that it is not some lone outlier—it is now joined by another species from the Pacific, the Hawaiian crow Corvus hawaiiensis, better known by its indigenous Hawaiian name 'Alalā. These birds naturally develop tool-using skills when young, and proficient tool use is a species-wide capacity. The authors can say this with confidence as the 'Alalā is extinct in the wild, and they were able to test 104 of the 109 surviving members of the species at the time, all in captivity. The research suggests that the technological skills of tropical crows might be fostered by rather unusual ecological circumstances found on remote islands, such as reduced competition for embedded prey and low predation risk. The discovery of a second tool-using crow species opens up exciting opportunities for comparative studies on animal tool use. Only a handful of bird species are known to use foraging tools in the wild1. Amongst them, the New Caledonian crow (Corvus moneduloides) stands out with its sophisticated tool-making skills2,3. Despite considerable speculation, the evolutionary origins of this species’ remarkable tool behaviour remain largely unknown, not least because no naturally tool-using congeners have yet been identified that would enable informative comparisons4. Here we show that another tropical corvid, the ‘Alalā (C. hawaiiensis; Hawaiian crow), is a highly dexterous tool user. Although the ‘Alalā became extinct in the wild in the early 2000s, and currently survives only in captivity5, at least two lines of evidence suggest that tool use is part of the species’ natural behavioural repertoire: juveniles develop functional tool use without training, or social input from adults; and proficient tool use is a species-wide capacity. ‘Alalā and New Caledonian crows evolved in similar environments on remote tropical islands, yet are only distantly related6, suggesting that their technical abilities arose convergently. This supports the idea that avian foraging tool use is facilitated by ecological conditions typical of islands, such as reduced competition for embedded prey and low predation risk4,7. Our discovery creates exciting opportunities for comparative research on multiple tool-using and non-tool-using corvid species. Such work will in turn pave the way for replicated cross-taxonomic comparisons with the primate lineage, enabling valuable insights into the evolutionary origins of tool-using behaviour.

Social relationships have been shown to significantly impact individual and group success in wild animal populations, but are largely ignored in farm animal management. There are substantial gaps in our knowledge of how farm animals respond to their social environment, which varies greatly between farms but is commonly unstable due to regrouping. Fundamental to addressing these gaps is an understanding of the social network structure resulting from the patterning of relationships between individuals in a group. Here, we investigated the social structure of a group of 110 lactating dairy cows during four one-month periods. Spatial proximity loggers collected data on associations between cows, allowing us to construct social networks. First we demonstrate that proximity loggers can be used to measure relationships between cows; proximity data was significantly positively correlated to affiliative interactions but had no relationship with agonistic interactions. We measured group-level patterns by testing for community structure, centralisation and repeatability of network structure over time. We explored individual-level patterns by measuring social differentiation (heterogeneity of social associations) and assortment of cows in the network by lactation number, breed, gregariousness and milk production. There was no evidence that cows were subdivided into social communities; individuals belonged to a single cluster and networks showed significant centralisation. Repeatability of the social network was low, which may have consequences for animal welfare. Individuals formed differentiated social relationships and there was evidence of positive assortment by traits; cows associated more with conspecifics of similar lactation number in all study periods. There was also positive assortment by breed, gregariousness and milk production in some study periods. There is growing interest in the farming industry in the impact of social factors on production and welfare; this study takes an important step towards understanding social dynamics. (C) 2015 Elsevier B.V. All rights reserved.

This chapter is designed as a largely non-technical introduction to some of the terms, such as edge, adjacency matrix, centrality, betweenness, and degree, that are used in later chapters of this book to quantify the structure and dynamics of animal social networks. The chapter first discusses the basics of networks and measuring network structure, including node-based measures of structure and network-level measures of structure. Then, the topic of clusters or communities is covered. Finally, the chapter outlines model networks and network models.

With increasing interest in animal social networks, field biologists have started exploring the use of advanced tracking technologies for mapping social encounters in free-ranging subjects. Proximity logging, which involves the use of animal-borne tags with the capacity for two-way communication, has attracted particular attention in recent years. While the basic rationale of proximity logging is straightforward, systems generate very large datasets which pose considerable challenges in terms of processing and visualisation. Technical aspects of data handling are crucial for the success of proximity-logging studies, yet are only rarely reported in full detail. Here, we describe the procedures we employed for mining the data generated by a recent deployment of a novel proximity-logging system, “Encounternet”, to study social-network dynamics in tool-using New Caledonian crows.

Summary In the analysis of animal social networks, a common challenge has been distinguishing affiliations – active preferences of pairs of individuals to interact or associate with one another – from other, structural, causes of association or interaction. Such structural factors can include patterns of use of the habitat in time and space, gregariousness and differential association rates among age/sex classes. In an approach with similarities to the multiple regression quadratic assignment procedures test, we suggest calculating generalized affiliation indices as the residuals from a regression of the measures of association or interaction on structural predictor variables, such as gregariousness and spatiotemporal overlap. If the original data are association indices or counts of interactions, then generalized linear models with binomial or Poisson error structures, respectively, can be used in place of linear regression. Anscombe or deviance residuals can be used to assess the significance of particular affiliation indices. Generalized affiliation indices can be used as the weights of links in a social network representation. They can then be portrayed in network diagrams or cluster diagrams and used to calculate network statistics, to delineate communities by maximizing modularity and to test for overall affiliation using data‐stream permutation tests. We evaluate the effectiveness of such generalized affiliation indices using simulated and real association data, finding that the method removes much of the effect of structural variables on association patterns, revealing real affiliations. While the approach is very promising, it is limited by the extent to which the input predictor variables represent important structural factors.

Growing interest in the structure and dynamics of animal social networks has stimulated efforts to develop automated tracking technologies that can reliably record encounters in free-ranging subjects. A particularly promising approach is the use of animal-attached 'proximity loggers', which collect data on the incidence, duration and proximity of spatial associations through inter-logger radio communication. While proximity logging is based on a straightforward physical principle - the attenuation of propagating radio waves with distance - calibrating systems for field deployment is challenging, since most study species roam across complex, heterogeneous environments.In this study, we calibrated a recently developed digital proximity-logging system ('Encounternet') for deployment on a wild population of New Caledonian crows Corvus moneduloides. Our principal objective was to establish a quantitative model that enables robust post hoc estimation of logger-to-logger (and, hence, crow-to-crow) distances from logger-recorded signal-strength values. To achieve an accurate description of the radio communication between crow-borne loggers, we conducted a calibration exercise that combines theoretical analyses, field experiments, statistical modelling, behavioural observations, and computer simulations.We show that, using signal-strength information only, it is possible to assign crow encounters reliably to predefined distance classes, enabling powerful analyses of social dynamics. For example, raw data sets from field-deployed loggers can be filtered at the analysis stage to include predominantly encounters where crows would have come to within a few metres of each other, and could therefore have socially learned new behaviours through direct observation. One of the main challenges for improving data classification further is the fact that crows - like most other study species - associate across a wide variety of habitats and behavioural contexts, with different signal-attenuation properties.Our study demonstrates that well-calibrated proximity-logging systems can be used to chart social associations of free-ranging animals over a range of biologically meaningful distances. At the same time, however, it highlights that considerable efforts are required to conduct study-specific system calibrations that adequately account for the biological and technological complexities of field deployments. Although we report results from a particular case study, the basic rationale of our multi-step calibration exercise applies to many other tracking systems and study species.

Social-network dynamics have profound consequences for biological processes such as information flow, but are notoriously difficult to measure in the wild. We used novel transceiver technology to chart association patterns across 19 days in a wild population of the New Caledonian crow-a tool-using species that may socially learn, and culturally accumulate, tool-related information. To examine the causes and consequences of changing network topology, we manipulated the environmental availability of the crows' preferred tool-extracted prey, and simulated, in silico, the diffusion of information across field-recorded time-ordered networks. Here we show that network structure responds quickly to environmental change and that novel information can potentially spread rapidly within multi-family communities, especially when tool-use opportunities are plentiful. At the same time, we report surprisingly limited social contact between neighbouring crow communities. Such scale dependence in information-flow dynamics is likely to influence the evolution and maintenance of material cultures.

Understanding habitat selection and assessing habitat quality have an important role in habitat management and prioritisation of areas for protection. However, interpretations of habitat selection and habitat quality can be confounded by social effects such as conspecific attraction. Using 7 years' data from a well monitored Great Bustard Otis tarda population in Central Europe, we investigated the roles of human disturbance and social cues in display site selection of male Great Bustards Otis tarda. The spatial distribution of displaying males was best predicted by human disturbance. In addition, the number of males attending display sites was strongly correlated to the number of females present and not with disturbance. This suggests that abundance could be a misleading metric for habitat quality in social species. Our results highlight the roles of disturbance and social cues in male habitat choice, and suggest that social factors need to be taken into consideration for management of endangered populations.

One of the main challenges in the study of social networks in vertebrates is to close the gap between group patterns and dynamics. Usually scan samples or transect data are recorded to provide information about social patterns of animals, but these techniques themselves do not shed much light on the underlying dynamics of such groups. Here we show an approach which captures the fission-fusion dynamics of a fish population in the wild and demonstrates how the gap between pattern and dynamics may be closed. Our analysis revealed that guppies have complex association patterns that are characterised by close strong connections between individuals of similar behavioural type. Intriguingly, the preference for particular social partners is not expressed in the length of associations but in their frequency. Finally, we show that the observed association preferences could have important consequences for transmission processes in animal social networks, thus moving the emphasis of network research from descriptive mechanistic studies to functional and predictive ones.

The scientific study of networks — computer, social, and biological — has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This book provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It provides an overview of the power of the network approach which is useful for understanding patterns and process in animal populations. It also outlines how current methodological constraints and challenges can be overcome.