Search

The genetic structure of animal populations has considerable behavioural, ecological and evolutionary implications and may arise from various demographic traits. Here, we use observational field data and molecular genetics to determine the genetic structure of an invasive population of monk parakeets, Myiopsitta monachus, at a range of spatial scales, and investigate the demographic processes that generate the observed structure. Monk parakeets construct large nests that can house several pairs occupying separate chambers; these nests are often aggregated within nesting trees. We determined patterns of relatedness within compound nests, within nesting trees and between trees. Spatial autocorrelation analyses of pairwise genetic relatedness revealed fine-scale genetic structure with relatives of both sexes spatially clustered within, but not beyond, nesting trees. In addition, males were more related to males sharing their compound nests than to other males occupying the same nesting tree. By contrast, males and females within compound nests were not significantly more closely related than elsewhere in the same tree, and we found no evidence for inbreeding. Adults showed high breeding site fidelity between years despite considerable disturbance of nest sites. Natal dispersal was female-biased, but dispersal distances were relatively short with some natal philopatry observed in both sexes. Sibling coalitions, typically of males, were observed amongst both philopatric and dispersing birds. Our results show significant clustering of kin within compound nests and nesting trees resulting from limited and coordinated natal dispersal, with subsequent breeding site fidelity. The resulting genetic structure has implications for social behaviour in this unusual parrot species.

The extended female postreproductive life span found in humans and some toothed whales remains an evolutionary puzzle. Theory predicts demographic patterns resulting in increased female relatedness with age (kinship dynamics) can select for a prolonged postreproductive life span due to the combined costs of intergenerational reproductive conflict and benefits of late‐life helping. Here, we test this prediction using >40 years of longitudinal demographic data from the sympatric yet genetically distinct killer whale ecotypes: resident and Bigg's killer whales. The female relatedness with age is predicted to increase in both ecotypes, but with a less steep increase in Bigg's due to their different social structure. Here, we show that there is a significant postreproductive life span in both ecotypes with >30% of adult female years being lived as postreproductive, supporting the general prediction that an increase in local relatedness with age predisposes the evolution of a postreproductive life span. Differences in the magnitude of kinship dynamics however did not influence the timing or duration of the postreproductive life span with females in both ecotypes terminating reproduction before their mid‐40s followed by an expected postreproductive period of about 20 years. Our results highlight the important role of kinship dynamics in the evolution of a long postreproductive life span in long‐lived mammals, while further implying that the timing of menopause may be a robust trait that is persistent despite substantial variation in demographic patterns among populations., The rare life history trait of a long postreproductive period in females have been linked to demographic patterns leading to an increased relatedness to the local group with age (kinship dynamics). Here, we show that two killer whale ecotypes that are genetically distinct and exhibit different demographic patterns as well as different strengths of expected kinship dynamics have evolved a long postreproductive period in females, supporting the prediction that an increased female local relatedness with age predisposes for the evolution of this life history trait. Moreover, this results indicates that the onset of the postreproductive period may be robust to substantial variation in demographic patterns among populations.

Abstract In studies of social behaviour, social bonds are usually inferred from rates of interaction or association. This approach has revealed many important insights into the proximate formation and ultimate function of animal social structures. However, it remains challenging to compare social structure between systems or time-points because extrinsic factors, such as sampling methodology, can also influence the observed rate of association. As a consequence of these methodological challenges, it is difficult to analyse how patterns of social association change with demographic processes, such as the death of key social partners. Here we develop and illustrate the use of binomial mixture models to quantitatively compare patterns of social association between networks. We then use this method to investigate how patterns of social preferences in killer whales respond to demographic change. Resident killer whales are bisexually philopatric, and both sexes stay in close association with their mother in adulthood. We show that mothers and daughters show reduced social association after the birth of the daughter’s first offspring, but not after the birth of an offspring to the mother. We also show that whales whose mother is dead associate more with their opposite sex siblings and with their grandmother than whales whose mother is alive. Our work demonstrates the utility of using mixture models to compare social preferences between networks and between species. We also highlight other potential uses of this method such as to identify strong social bonds in animal populations. Significance statement Comparing patters of social associations between systems, or between the same systems at different times, is challenging due to the confounding effects of sampling and methodological differences. Here we present a method to allow social associations to be robustly classified and then compared between networks using binomial mixture models. We illustrate this method by showing how killer whales change their patterns of social association in response to the birth of calves and the death of their mother. We show that after the birth of her calf, females associate less with their mother. We also show that whales’ whose mother is dead associate more with their opposite sex siblings and grandmothers than whales’ whose mother is alive. This clearly demonstrates how this method can be used to examine fine scale temporal processes in animal social systems.

Most ant colonies live in a single nest (monodomy) or a group of nests (polydomy). However, the length of time for which nests are inhabited varies significantly between different species. Although colonies of some species frequently move nest sites, in others, colonies inhabit the same nest or group of nests for many years. Similarly, in some species foraging and resource-sharing trails are highly dynamic, while in other species trails are used for years. Wood ants are a group of keystone species that inhabit many northern hemisphere woodlands, where they are important predators of invertebrates and indirectly act as herbivores through the farming of aphids. Wood ant colonies exhibit both monodomy and polydomy, and can inhabit nests for many years. Trails in wood ant colonies are also thought to be relatively stable. However, information about colony dynamics is mostly anecdotal as, until now, no longitudinal datasets have been collected. In this study, we collected data from ten polydomous wood ant colonies annually for 8 years and a subset of four colonies 16 times over 2 years. We found that most polydomous wood ant nests are abandoned in the first 2 years after being constructed and are more likely to be abandoned in the latter part of the active season. However, the rate of nest abandonment decreases after 2 years and is lower in larger nests. We also found that wood ant trails are relatively static within an active season and become more static later in the season as trails become established.

Significance Why humans and some species of whales go through menopause remains an evolutionary puzzle. In humans, postreproductive females gain genetic benefits by helping family members—particularly increasing their number of surviving grandoffspring. The extent to which these grandmother benefits are important in the evolution of menopause in whales remains unclear. Here, we test the grandmother effect in resident killer whales, where females can live for decades after their last reproductive event. We show that grandmothers increase the survival of their grandoffspring, and these effects are greatest when grandmothers are no longer reproducing. These findings can help explain why killer whales have evolved the longest postreproductive life span of all nonhuman animals., Understanding why females of some mammalian species cease ovulation prior to the end of life is a long-standing interdisciplinary and evolutionary challenge. In humans and some species of toothed whales, females can live for decades after stopping reproduction. This unusual life history trait is thought to have evolved, in part, due to the inclusive fitness benefits that postreproductive females gain by helping kin. In humans, grandmothers gain inclusive fitness benefits by increasing their number of surviving grandoffspring, referred to as the grandmother effect. Among toothed whales, the grandmother effect has not been rigorously tested. Here, we test for the grandmother effect in killer whales, by quantifying grandoffspring survival with living or recently deceased reproductive and postreproductive grandmothers, and show that postreproductive grandmothers provide significant survival benefits to their grandoffspring above that provided by reproductive grandmothers. This provides evidence of the grandmother effect in a nonhuman menopausal species. By stopping reproduction, grandmothers avoid reproductive conflict with their daughters, and offer increased benefits to their grandoffspring. The benefits postreproductive grandmothers provide to their grandoffspring are shown to be most important in difficult times where the salmon abundance is low to moderate. The postreproductive grandmother effect we report, together with the known costs of late-life reproduction in killer whales, can help explain the long postreproductive life spans of resident killer whales.

Understanding how individual behavior shapes the structure and ecology of populations is key to species conservation and management. Like many elasmobranchs, manta rays are highly mobile and wide-ranging species threatened by anthropogenic impacts. In shallow water environments, these pelagic rays often form groups and perform several apparently socially mediated behaviors. Group structures may result from active choices of individual rays to interact or passive processes. Social behavior is known to affect spatial ecology in other elasmobranchs, but this is the first study providing quantitative evidence for structured social relationships in manta rays. To construct social networks, we collected data from more than 500 groups of reef manta rays (Mobula alfredi) over 5 years in the Raja Ampat Regency of West Papua. We used generalized affiliation indices to isolate social preferences from non-social associations, the first study on elasmobranchs to use this method. Longer lasting social preferences were detected mostly between female rays. We detected assortment of social relations by phenotype and variation in social strategies, with the overall social network divided into two main communities. Overall network structure was characteristic of a dynamic fission-fusion society, with differentiated relationships linked to strong fidelity to cleaning station sites. Our results suggest that fine-scale conservation measures will be useful in protecting social groups of M. alfredi in their natural habitats and that a more complete understanding of the social nature of manta rays will help predict population responses to anthropogenic pressures, such as increasing disturbance from dive tourism. In social animals, relationships between individuals have important implications for species conservation. Like many other sharks and rays, manta rays are threatened species, and little is known about their natural behavior or how their populations are structured. This study provides evidence of social structure in a wild, free-ranging population of reef manta rays. We show for the first time that individual manta rays have preferred relationships with others that are maintained over time, and structured societies. This study extends our knowledge of elasmobranch ecology and population structuring. Results suggest that understanding social relationships in manta rays will be important in protecting populations from human impacts and developing sustainable, localized conservation and management initiatives.

The dynamics of wildlife populations often depend heavily on interspecific interactions and understanding the underlying principles can be an important step in designing conservation strategies. Behavioural ecological studies can here provide useful insights into the structure and function of communities and their likely response to environmental changes. In this study of the Masai Mara herbivore community, we use a social network approach to investigate social affinities between species and how these change over the year in response to seasonal changes in ecological conditions. We find that even though social networks were correlated across different ecological conditions, for half the species dyads in the community, the strength of social affinities responded to changes in rainfall and/or the presence of migratory wildebeest. Several species consequentially adopted more or less central positions in the network depending on the ecological conditions. The findings point out interspecific social links that are likely to be attenuated or strengthened as a consequence of human-induced environmental changes and therefore call for particular attention from conservation managers. The eco-evolutionary ramifications of the perturbations of social affinities still require further study. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

Animal social structure is shaped by environmental conditions, such as food availability. This is important as conditions are likely to change in the future and changes to social structure can have cascading ecological effects. Wood ants are a useful taxon for the study of the relationship between social structure and environmental conditions, as some populations form large nest networks and they are ecologically dominant in many northern hemisphere woodlands. Nest networks are formed when a colony inhabits more than one nest, known as polydomy. Polydomous colonies are composed of distinct sub-colonies that inhabit spatially distinct nests and that share resources with each other. In this study, we performed a controlled experiment on 10 polydomous wood ant (Formica lugubris) colonies to test how changing the resource environment affects the social structure of a polydomous colony. We took network maps of all colonies for 5 years before the experiment to assess how the networks changes under natural conditions. After this period, we prevented ants from accessing an important food source for a year in five colonies and left the other five colonies undisturbed. We found that preventing access to an important food source causes polydomous wood ant colony networks to fragment into smaller components and begin foraging on previously unused food sources. These changes were not associated with a reduction in the growth of populations inhabiting individual nests (sub-colonies), foundation of new nests or survival, when compared with control colonies. Colony splitting likely occurred as the availability of food in each nest changed causing sub-colonies to change their inter-nest connections. Consequently, our results demonstrate that polydomous colonies can adjust to environmental changes by altering their social network.

[Robeck et al. (2015)][1] claim that reproductive and actuarial senescence is common in mammalian species and therefore not an unexpected finding in killer whales. However, in most mammals, reproductive and somatic senescence are aligned, and reproduction gradually declines with age. In contrast, there is a substantial evidence that reproductive senescence is unusually accelerated relative to somatic senescence in resident killer whales, resulting in a prolonged postreproductive lifespan. We demonstrate that a postreproductive lifespan is a key component of resident killer whale life history, and is robust to reasonable error in age estimates. [1]: #ref-32

A challenge faced by individuals and groups of many species is determining how resources and activities should be spatially distributed: centralized or decentralized. This distribution problem is hard to understand due to the many costs and benefits of each strategy in different settings. Ant colonies are faced by this problem and demonstrate two solutions: 1) centralizing resources in a single nest (monodomy) and 2) decentralizing by spreading resources across many nests (polydomy). Despite the possibilities for using this system to study the centralization/decentralization problem, the trade-offs associated with using either polydomy or monodomy are poorly understood due to a lack of empirical data and cohesive theory. Here, we present a dynamic network model of a population of ant nests which is based on observations of a facultatively polydomous ant species (Formica lugubris). We use the model to test several key hypotheses for costs and benefits of polydomy and monodomy and show that decentralization is advantageous when resource acquisition costs are high, nest size is limited, resources are clustered, and there is a risk of nest destruction, but centralization prevails when resource availability fluctuates and nest size is limited. Our model explains the phylogenetic and ecological diversity of polydomous ants, demonstrates several trade-offs of decentralization and centralization, and provides testable predictions for empirical work on ants and in other systems., Centralization and decentralization of resources in ant colonies have several costs and benefits. We use a dynamic network model of a population of ant nests to demonstrate that there are several important costs and benefits of centralization and decentralization, which explains the phylogenetic and ecological diversity of methods for distribution of resources across ant species.

We propose a method for examining and measuring the complexity of animal social networks that are characterized using association indices. The method focusses on the diversity of types of dyadic relationship within the social network. Binomial mixture models cluster dyadic relationships into relationship types, and variation in the preponderance and strength of these relationship types can be used to estimate association complexity using Shannon’s information index. We use simulated data to test the method and find that models chosen using integrated complete likelihood give estimates of complexity that closely reflect the true complexity of social systems, but these estimates can be downwardly biased by low-intensity sampling and upwardly biased by extreme overdispersion within components. We also illustrate the use of the method on two real datasets. The method could be extended for use on interaction rate data using Poisson mixture models or on multidimensional relationship data using multivariate mixture models. Animals from many species interact socially with multiple individuals, and these interactions form a social network. Pairs of individuals have social relationships that differ in their strength and type. This social complexity has long interested behavioural biologists, particularly in the context of social cognition. Measuring social complexity, however, presents challenges. We propose a new method for measuring the complexity of animal social networks. Our approach is based on quantifying variation in the strengths of social connections (measured using association indices) which we use to classify different types of pairwise relationships. We, then, use the number, strength and prevalence of these different types of relationships to measure association complexity. Our approach can be used to compare association complexity between populations and/or species. We provide code that researchers can use with their own datasets.

The emergence of novel diseases represents a major hurdle for the recovery of endangered populations, and in some cases may even present the threat of extinction. In recent years, epizootics of infectious diseases have emerged as a major threat to marine mammal populations, particularly group-living odontocetes. However, little research has explored the potential consequences of novel pathogens in endangered cetacean populations. Here, we present the first study predicting the spread of infectious disease over the social network of an entire free-ranging cetacean population, the southern resident killer whale community (SRKW). Utilizing 5 years of detailed data on close contacts between individuals, we build a fine-scale social network describing potential transmission pathways in this population. We then simulate the spread of cetacean morbillivirus (CeMV) over this network. Our analysis suggests that the SRKW population is highly vulnerable to CeMV. The majority of simulations resulted in unusual mortality events (UMEs), with mortality rates predicted to be at least twice the recorded maximum annual mortality. We find only limited evidence that this population's social structure inhibits disease spread. Vaccination is not likely to be an efficient strategy for reducing the likelihood of UMEs, with over 40 vaccinated individuals (>50% of the population) required to reduce the likelihood of UMEs below 5%. This analysis highlights the importance of modelling efforts in designing strategies to mitigate disease, and suggests that populations with strong social preferences and distinct social units may still be highly vulnerable to disease outbreaks.

Warning signals within species, such as the bright colors of chemically defended animals, are usually considered mutualistic, monomorphic traits. Such a view is however increasingly at odds with the growing empirical literature, showing nontrivial levels of signal variation within prey populations. Key to understanding this variation, we argue, could be a recognition that toxicity levels frequently vary within populations because of environmental heterogeneity. Inequalities in defense may undermine mutualistic monomorphic signaling, causing evolutionary antagonism between loci that determine appearance of less well-defended and better defended prey forms within species. In this article, we apply a stochastic model of evolved phenotypic plasticity to the evolution of prey signals. We show that when toxicity levels vary, then antagonistic interactions can lead to evolutionary conflict between alleles at different signaling loci, causing signal evolution, "red queen-like" evolutionary chase, and one or more forms of signaling equilibria. A key prediction is that variation in the way that predators use information about toxicity levels in their attack behaviors profoundly affects the evolutionary characteristics of the prey signaling systems. Environmental variation is known to cause variation in many qualities that organisms signal; our approach may therefore have application to other signaling systems.

Lay Summary Wood ants nests share resources with neighboring nests, not the whole colony. A single ant colony can either live all in one nest, or split into several separate, but communicating, nests. How and why ant colonies do this is unknown. By treating these separated colonies as networks we show that wood ants exchange food locally, with neighboring nests, without a colony-level plan., An important problem facing organisms in a heterogeneous environment is how to redistribute resources to where they are required. This is particularly complex in social insect societies as resources have to be moved both from the environment into the nest and between individuals within the nest. Polydomous ant colonies are split between multiple spatially separated, but socially connected, nests. Whether, and how, resources are redistributed between nests in polydomous colonies is unknown. We analyzed the nest networks of the facultatively polydomous wood ant Formica lugubris. Our results indicate that resource redistribution in polydomous F. lugubris colonies is organized at the local level between neighboring nests and not at the colony level. We found that internest trails connecting nests that differed more in their amount of foraging were stronger than trails between nests with more equal foraging activity. This indicates that resources are being exchanged directly from nests with a foraging excess to nests that require resources. In contrast, we found no significant relationships between nest properties, such as size and amount of foraging, and network measures such as centrality and connectedness. This indicates an absence of a colony-level resource exchange. This is a clear example of a complex behavior emerging as a result of local interactions between parts of a system.

Efficient and robust transportation networks are key to the effectiveness of many natural systems. In polydomous ant colonies, which consist of two or more spatially separated but socially connected nests, resources must be transported between nests. In this study, we analyse the network structure of the inter-nest trails formed by natural polydomous ant colonies. In contrast to previous laboratory studies, the natural colonies in our study do not form minimum spanning tree networks. Instead the networks contain extra connections, suggesting that in natural colonies, robustness may be an important factor in network construction. Spatial analysis shows that nests are randomly distributed within the colony boundary and we find nests are most likely to connect to their nearest neighbours. However, the network structure is not entirely determined by spatial associations. By showing that the networks do not minimise total trail length and are not determined only by spatial associations, the results suggest that the inter-nest networks produced by ant colonies are influenced by previously unconsidered factors. We show that the transportation networks of polydomous ant colonies balance trail costs with the construction of networks that enable efficient transportation of resources. These networks therefore provide excellent examples of effective biological transport networks which may provide insight into the design and management of transportation systems.

Summary Why females of some species cease ovulation prior to the end of their natural lifespan is a long-standing evolutionary puzzle [1–4]. The fitness benefits of post-reproductive helping could in principle select for menopause [1, 2, 5], but the magnitude of these benefits appears insufficient to explain the timing of menopause [6–8]. Recent theory suggests that the cost of inter-generational reproductive conflict between younger and older females of the same social unit is a critical missing term in classical inclusive fitness calculations (the "reproductive conflict hypothesis" [6, 9]). Using a unique long-term dataset on wild resident killer whales, where females can live decades after their final parturition, we provide the first test of this hypothesis in a non-human animal. First, we confirm previous theoretical predictions that local relatedness increases with female age up to the end of reproduction. Second, we construct a new evolutionary model and show that given these kinship dynamics, selection will favor younger females that invest more in competition, and thus have greater reproductive success, than older females (their mothers) when breeding at the same time. Third, we test this prediction using 43 years of individual-based demographic data in resident killer whales and show that when mothers and daughters co-breed, the mortality hazard of calves from older-generation females is 1.7 times that of calves from younger-generation females. Intergenerational conflict combined with the known benefits conveyed to kin by post-reproductive females can explain why killer whales have evolved the longest post-reproductive lifespan of all non-human animals.

For the majority of social species, group composition is dynamic, and individuals are interconnected in a heterogeneous social network. Social network structure has far-reaching implications for the ecology of individuals and populations. However, we have little understanding of how ecological variables shape this structure. We used a long-term data set (1984e2007) to examine the relationship between food availability and social network structure in the endangered southern resident killer whales. During the summer months individuals in this population feed primarily on chinook salmon, Oncorhynchus tshawytscha, which show annual variation in abundance. We tested the hypothesis that temporal variation in chinook salmon will correlate with variation in social network structure. Using a null model that controlled for population demography, group size and sampling effort, we found a significant relationship between the connectivity of the social network and salmon abundance, with a more interconnected social network in years of high salmon abundance. Our results demonstrate that resource availability may be an important determinant of social network structure. Given the central importance of the social network for population processes such as the maintenance of cooperation and the transmission of information and disease, a change in social network structure caused by a change in food availability may have significant ecological and evolutionary consequences. 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

In many group-living animals, leadership by only a fraction of the group members can be important for group navigation. It has been shown that subgroups of informed individuals can steer the remainder of the group without direct communication, resolving conflicts of interest through individual-to-individual interactions. We present a model for the navigation of collectively moving groups that includes preferential interactions between individuals as a way of imposing social network structures, known to be present in many species. We show that effective leadership can occur when leaders do not occupy frontal spatial positions and when navigation tendency is appropriately balanced with social position. Our model also shows that small minorities can dominate movement decisions if they have navigational knowledge combined with influential social network positions. Our findings highlight the mechanistic importance of social networks for the movement decisions of animal groups. We discuss the implications of our research for interpreting empirical observations.

The mechanisms behind the evolution and maintenance of conspicuous visible polymorphisms comprising tens of morphs present a challenge to evolutionary theory. However, for cryptic forms Endler (Evol. Biol., 11, 1978, 319) conjectured that complex backgrounds facilitate polymorphism because in such habitats there are several ways to resemble the resting surface. We use computer simulation to explore the evolution of cryptic morphs on increasingly complex backgrounds under regimes that include selection for crypsis, apostatic predation and dietary wariness. We show that there is a monotonic increase in the number of morphs evolving in a population as the potential number of cryptic morphs increases. The relationship is very weak with selection for crypsis alone, but much stronger with the addition of apostatic selection. In contrast, when dietary wariness is added to the model the plot of number of morphs maintained, as a function of the potential number of cryptic forms available, is minimized at an intermediate number of cryptic forms, i.e. is V-shaped. These counter-intuitive patterns are robust to varying strengths of apostatic selection and different implementations of dietary wariness, and are more pronounced when predator and prey generation lengths are similar.

The theory of collective motion and the study of animal social networks have, each individually, received much attention. Currently, most models of collective motion do not consider social network structure. The implications for considering collective motion and social networks together are likely to be important. Social networks could determine how populations move in, split up into and form separate groups (social networks affecting collective motion). Conversely, collective movement could change the structure of social networks by creating social ties that did not exist previously and maintaining existing ties (collective motion affecting social networks). Thus, there is a need to combine the two areas of research and examine the relationship between network structure and collective motion. Here, we review different modelling approaches that combine social network structures and collective motion. Although many of these models have not been developed with ecology in mind, they present a current context in which a biologically relevant theory can be developed. We argue that future models in ecology should take inspiration from empirical observations and consider different mechanisms of how social preferences could be expressed in collectively moving animal groups.

Ecologists increasingly use network theory to examine animal association patterns. The gambit of the group (GoG) is a simple and useful assumption for accumulating the data necessary for a network analysis. The gambit of the group implies that each animal in a group is associating with every other individual in that group. Sampling is an important issue for networks in wild populations collected assuming GoG. Due to time, effort, and resource constraints and the difficulty of tracking animals, sampled data are usually a subset of the actual network. Ecologists often use association indexes to calculate the frequency of associations between individuals. These indexes are often transformed by applying a filter to produce a binary network. We explore GoG sampling using model networks. We examine assortment at the level of the group by a single dichotomous trait, along with many other network measures, to examine the effect of different sampling regimes, and choice of filter on the accuracy and precision with which measures are estimated. We find strong support for the use of weighted, rather than filtered, network measures and show that different filters have different effects depending on the nature of the sampling. We make several practical recommendations for ecologists planning GoG sampling.

Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network.

Prey that are unprofitable to attack are typically conspicuous in appearance. Conventional theory assumes that these warning signals have evolved in response to predator receiver biases. However, such biases might be a symptom rather than a cause of warning signals. We therefore examine an alternative theory: that conspicuousness evolves in unprofitable prey to avoid confusion with profitable prey. One might wonder why unprofitable prey do not find a cryptic means to be distinct from profitable prey, reducing both their risk of confusion with profitable prey and their rate of detection by predators. Here we present the first coevolutionary model to allow for Batesian mimicry and signals with different levels of detectability. We find that unprofitable prey do indeed evolve ways of distinguishing themselves using cryptic signals, particularly when appearance traits can evolve in multiple dimensions. However, conspicuous warning signals readily evolve in unprofitable prey when there are more ways to look different from the background than to match it. Moreover, the more unprofitable the prey species, the higher its evolved conspicuousness. Our results provide strong support for the argument that unprofitable species evolve conspicuous signals to avoid confusion with profitable prey and indicate that peak shift in conspicuousness-linked traits is a major factor in its establishment.

Theories of the evolution of warning signals are typically expressed using analytic and computational models, most of which attribute aspects of predator psychology as the key factors facilitating the evolution of warning signals. Sherratt provides a novel and promising perspective with a model that considers the coevolution of predator and prey populations, showing how predators may develop a bias towards attacking cryptic prey in preference to conspicuous prey. Here, we replicate the model as an individual-based simulation and find, in accordance with Sherratt, that predators evolve a bias towards attacking cryptic prey. We then use a Monte Carlo simulation to calculate the relative survivorships of cryptic and conspicuous prey and stress that, as it stands, the model does not predict the evolution or stability of warning signals. We extend the model by giving predators continuous attack strategies and by allowing the evolution of prey conspicuousness: results are robust to the first modification but, in all cases, cryptic prey always enjoy a higher survivorship than conspicuous prey. When conspicuousness is allowed to evolve, prey quickly evolve towards crypsis, even when runaway coevolution is enabled. Sherratt's approach is promising, but other aspects of predator psychology, besides their innate response, remain vital to our understanding of warning signals.

Mathematical models of mimicry typically involve artificial prey species with fixed colorations or appearances; this enables a comparison of predation rates to demonstrate the level of protection a mimic might be afforded. Fruitful theoretical results have been produced using this method, but it is also useful to examine the possible evolutionary consequences of mimicry. To that end, we present individual-based evolutionary simulation models where prey colorations are free to evolve. We use the models to examine the effect of Batesian mimics on Muellerian mimics and mimicry rings. Results show that Batesian mimics can potentially incite Muellerian mimicry relationships and encourage mimicry ring convergence.

SECTION I: INTRODUCTION SECTION II: PATTERNS AND PROCESSES SECTION III: TAXONOMIC OVERVIEWS

In socially foraging species resource information can be shared between individuals, increasing foraging success. In ant colonies, nestmate recruitment allows high exploitation rates at known resources however, to maximise foraging efficiency this must be balanced with searching for new resources. Many ant species form colonies inhabiting two or more spatially separated but socially connected nests: this type of organisation is known as polydomy. Polydomous colonies may benefit from increased foraging efficiency by carrying out dispersed-central place foraging. However, decentralisation of the colony may affect recruitment success by limiting interaction between ants based in separate nests. We use an agent-based model which compares the foraging success of monodomous and polydomous colonies in different food environments, incorporating recruitment through pheromone trails and group foraging. In contrast to previous results we show that polydomy is beneficial in some but not all cases. Polydomous colonies discover resources at a higher rate, making them more successful when food is highly dispersed, but their relative success can be lowered by limitations on recruitment success. Monodomous colonies can have higher foraging efficiency than polydomous colonies by exploiting food more rapidly. The results show the importance of interactions between recruitment strategy, colony size, and colony organisation.

Nature is rich with many different examples of the cohesive motion of animals. Previous attempts to model collective motion have primarily focused on group behaviours of identical individuals. In contrast, we put our emphasis on modelling the contributions of different individual-level characteristics within such groups by using stochastic asynchronous updating of individual positions and orientations. Our model predicts that higher updating frequency, which we relate to perceived threat, leads to more synchronized group movement, with speed and nearest-neighbour distributions becoming more uniform. Experiments with three-spined sticklebacks ( Gasterosteus aculeatus ) that were exposed to different threat levels provide strong empirical support for our predictions. Our results suggest that the behaviour of fish (at different states of agitation) can be explained by a single parameter in our model: the updating frequency. We postulate a mechanism for collective behavioural changes in different environment-induced contexts, and explain our findings with reference to confusion and oddity effects.

Visible genetic polymorphism is a common feature of many species. In most cases, the mechanism(s) underlying the maintenance of such variation remain obscure although apostatic selection has often been suggested. Here, we explore individual-based evolutionary models to understand what features of predator-prey relationships may lead to patterns of exuberant polymorphism similar to those observed in the wild. When all morphs are equally visible, the number of evolved morphs increases with the strength of apostatic selection although even with powerful selection the number morphs is still relatively small. The introduction of dietary wariness increases the number of morphs substantially, even when apostatic selection is absent. When one morph is more cryptic the number of evolved morphs is fewer. The cryptic morph reaches high frequency in the population and other morphs are each at lower frequencies. Decreasing the predation intensity enhances the number of evolved morphs in all models. Dietary wariness is a critical factor missing from earlier models and it may provide a general solution to the problem of polymorphisms involving many morphs. Apostatic selection is shown to be neither a necessary, nor a sufficient, requirement for the maintenance of exuberant polymorphisms.

Generalization is at the heart of many aspects of behavioral ecology; for foragers it can be seen as an essential feature of learning about potential prey, because natural populations of prey are unlikely to be perfectly homogenous. Aposematic signals are considered to aid predators in learning to avoid a class of defended prey. Predators do this by generalizing between the appearance of prey they have previously sampled and the appearance of prey they subsequently encounter. Mimicry arises when such generalization occurs between individuals of different species. Our aim here is to explore whether the specific shape of the generalization curve can be expected to be important for theoretical predictions relating to the evolution of aposematism and mimicry. We do this by a reanalysis and development of the models provided in two recent papers. We argue that the shape of the generalization curve, in combination with the nature of genetic and phenotypic variation in prey traits, can have evolutionary significance under certain delineated circumstances. We also demonstrate that the process of gradual evolution of Mullerian mimicry proposed by Fisher is particularly efficient in populations with a rich supply of standing genetic variation in mimetic traits.

The relative sizes of phenotypic mutations contributing to evolutionary change has long been the subject of debate. We describe how mimicry research can shed light on this debate, and frame mimicry studies within the general context of macromutationism and micromutationism, and punctuated versus gradual evolution. Balogh and Leimar [Mullerian mimicry: an examination of Fisher's theory of gradual evolutionary change. Proc. Roy. Soc. Lond. B Biol. Sci. 272, 2269–2275] have recently used a model to readdress the question of whether or not mimicry evolves gradually along a single dimension. We extend their approach, and present the first model to consider the effect of predator generalization along multiple components on the evolution of mimicry. We find that the gradual evolution of mimicry becomes increasingly less likely as the number of signal components increases, unless predators generalize widely over all components. However, we show that the contemporary two-step hypothesis (punctuated evolution followed by gradual refinement) can explain the evolution of Mullerian mimicry under all tested conditions. Thus, although the gradual evolution of mimicry is possible, the two-step hypothesis appears more generally applicable.

Prey that are unprofitable to attack (for example, those containing noxious chemicals) are often conspicuously patterned and move in a slower and more predictable manner than species lacking these defences. Contemporary theories suggest these traits have evolved as warning signals because they can facilitate both associative and discriminative avoidance learning in predators. However, it is unclear why these particular traits and not others have tended to evolve in unprofitable prey. Here we show using a signal detection model that unprofitable prey will evolve conspicuous colours and patterns partly because these characteristics cannot readily evolve in profitable prey without close mimicry. The stability of this signal is maintained through the costs of dishonesty in profitable prey. Indeed, unprofitable prey will sometimes evolve a conspicuous form to reduce mimetic parasitism, even in the unlikely event that this form can be more closely mimicked. This is one of the first mathematical models of the evolution of warning signals to allow for the possibility of mimicry, yet our analyses suggest it may offer a general explanation as to why warning signals take the form that they do. Warning signals and mimicry may therefore be more closely related than is currently supposed.

In a persistent multi-agent system, it should be possible for new agents to benefit from the accumulated learning of more experienced agents. Parallel reasoning can be applied to the case of newborn animals, and thus the biological literature on social learning may aid in the construction of effective multi-agent systems. Biologists have looked at both the functions of social learning and the mechanisms that enable it. Many researchers have focused on the cognitively complex mechanism of imitation; we will also consider a range of simpler mechanisms that could more easily be implemented in robotic or software agents. Research in artificial life shows that complex global phenomena can arise from simple local rules. Similarly, complex information sharing at the system level may result from quite simple individual learning rules. We demonstrate in simulation that simple mechanisms can outperform imitation in a multi-agent system, and that the effectiveness of any social learning strategy will depend on the agents' environment. Our simple mechanisms have obvious advantages in terms of robustness and design costs.

Prolonged life after reproduction is difficult to explain evolutionarily unless it arises as a physiological side effect of increased longevity or it benefits related individuals (i.e., increases inclusive fitness). There is little evidence that postreproductive life spans are adaptive in nonhuman animals. By using multigenerational records for two killer whale (Orcinus orca) populations in which females can live for decades after their final parturition, we show that postreproductive mothers increase the survival of offspring, particularly their older male offspring. This finding may explain why female killer whales have evolved the longest postreproductive life span of all nonhuman animals.

Why females of some species cease ovulation before the end of their natural lifespan is a longstanding evolutionary puzzle. For many species in captivity, post-reproductive life is simply an epiphenomenon of lengthened lifespan. Yet in natural populations of humans as well as some cetaceans and insects, reproductive senescence occurs much faster than somatic aging and females exhibit prolonged post-reproductive lifespans (PRLSs). Determining the mechanisms and functions that underpin PRLSs has proved a significant challenge. Here we bring together both classic and modern hypotheses proposed to explain PRLSs and discuss their application to both human and nonhuman animals. By taking an integrative and broad taxonomic approach we highlight the need to consider multiple interacting explanations for the evolution of PRLSs.

Summary Classic life-history theory predicts that menopause should not occur because there should be no selection for survival after the cessation of reproduction [1]. Yet, human females routinely live 30 years after they have stopped reproducing [2]. Only two other species—killer whales ( Orcinus orca ) and short-finned pilot whales ( Globicephala macrorhynchus ) [3, 4]—have comparable postreproductive lifespans. In theory, menopause can evolve via inclusive fitness benefits [5, 6], but the mechanisms by which postreproductive females help their kin remain enigmatic. One hypothesis is that postreproductive females act as repositories of ecological knowledge and thereby buffer kin against environmental hardships [7, 8]. We provide the first test of this hypothesis using a unique long-term dataset on wild resident killer whales. We show three key results. First, postreproductively aged females lead groups during collective movement in salmon foraging grounds. Second, leadership by postreproductively aged females is especially prominent in difficult years when salmon abundance is low. This finding is critical because salmon abundance drives both mortality and reproductive success in resident killer whales [9, 10]. Third, females are more likely to lead their sons than they are to lead their daughters, supporting predictions of recent models [5] of the evolution of menopause based on kinship dynamics. Our results show that postreproductive females may boost the fitness of kin through the transfer of ecological knowledge. The value gained from the wisdom of elders can help explain why female resident killer whales and humans continue to live long after they have stopped reproducing.