Collective animal navigation and migratory culture: from theoretical models to empirical evidence

Modelling collective navigation via non-local communication

Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals towards a destination, while it has been demonstrated that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesizes navigational cues and perception of other individuals. Crucially, this approach incorporates uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ‘blindspots’, where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the northeast Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.

Certainty and integration of options in animal movement

Physical energy defines the energy landscape and determines the species-specific cost of movement, thus influencing movement decisions. In unpredictable and dynamic environments, observing the locomotion of others increases individual certainty in the distribution of physical energy to increase movement efficiency. Beyond the physical energy landscape, social sampling increases certainty in all ecological landscapes that influence animal movement (including fear and resource landscapes), and individuals use energy to express each of these. We call for the development of an 'optimal movement theory' (OMT) that integrates the multidimensional reality of movement decisions by combining ecological landscapes according to a single expectation of energy cost-benefit, where social sampling provides up-to-date information under uncertain conditions. This mechanistic framework has implications for predicting individual movement patterns and for investigating the emergence of aggregations.

Fish Avoid Visually Noisy Environments Where Prey Targeting Is Reduced

AbstractThe environment contains different forms of ecological noise that can reduce the ability of animals to detect information. Here, we ask whether animals adapt their behavior to either exploit or avoid areas of their environment with increased dynamic visual noise. Three-spined sticklebacks (Gasterosteus aculeatus) were immersed in environments with a simulated form of naturally occurring visual noise-moving light bands that form on underwater substrates caused by the refraction of light through surface waves. We tested whether this form of visual noise affected fish's habitat selection, movements, and prey-targeting behavior. Fish avoided areas of the environment with increased visual noise and achieved this by increasing their activity as a function of the locally perceived noise level. Fish were less likely to respond to virtual prey in environments with increased visual noise, highlighting a potential impact that visual noise has on their perceptual abilities. Fish did not increase or decrease their refuge use in environments with increased visual noise, providing no evidence that visual noise increased either exploratory or risk-aversive behavior. Our results indicate that animals can use simple behavioral strategies to avoid visually noisy environments, thereby mitigating the impacts that these environments appear to have on their perceptual abilities.

Multi-featured collective perception with Evidence Theory: tackling spatial correlations

Collective perception allows sparsely distributed agents to form a global view on a common spatially distributed problem without any direct access to global knowledge and only based on a combination of locally perceived information. However, the evidence gathered from the environment is often subject to spatial correlations and depends on the movements of the agents. The latter is not always easy to control and the main question is how to share and to combine the estimated information to achieve the most precise global estimate in the least possible time. The current article aims at answering this question with the help of evidence theory, also known as Dempster–Shafer theory, applied to the collective perception scenario as a collective decision-making problem. We study eight most common belief combination operators to address the arising conflict between different sources of evidence in a highly dynamic multi-agent setting, driven by modulation of positive feedback. In comparison with existing approaches, such as voter models, the presented framework operates on quantitative belief assignments of the agents based on the observation time of the options according to the agents’ opinions. The evaluated results on an extended benchmark set for multiple options ($$n>2$$ n > 2 ) indicate that the proportional conflict redistribution (PCR) principle allows a collective of small size ($$N=20$$ N = 20 ), occupying $$3.5\%$$ 3.5 % of the surface, to successfully resolve the conflict between clustered areas of features and reach a consensus with almost $$100\%$$ 100 % certainty up to $$n=5$$ n = 5 .

How signaling geometry shapes the efficacy and evolution of animal communication systems

Animal communication is inherently spatial. Both signal transmission and signal reception have spatial biases-involving direction, distance and position-that interact to determine signaling efficacy. Signals, be they visual, acoustic, or chemical, are often highly directional. Likewise, receivers may only be able to detect signals if they arrive from certain directions. Alignment between these directional biases is therefore critical for effective communication, with even slight misalignments disrupting perception of signaled information. In addition, signals often degrade as they travel from signaler to receiver, and environmental conditions that impact transmission can vary over even small spatiotemporal scales. Thus, how animals position themselves during communication is likely to be under strong selection. Despite this, our knowledge regarding the spatial arrangements of signalers and receivers during communication remains surprisingly coarse for most systems. We know even less about how signaler and receiver behaviors contribute to effective signaling alignment over time, or how signals themselves may have evolved to influence and/or respond to these aspects of animal communication. Here, we first describe why researchers should adopt a more explicitly geometric view of animal signaling, including issues of location, direction, and distance. We then describe how environmental and social influences introduce further complexities to the geometry of signaling. We discuss how multimodality offers new challenges and opportunities for signalers and receivers. We conclude with recommendations and future directions made visible by attention to the geometry of signaling.

The burgeoning reach of animal culture

Culture can be defined as all that is learned from others and is repeatedly transmitted in this way, forming traditions that may be inherited by successive generations. This cultural form of inheritance was once thought specific to humans, but research over the past 70 years has instead revealed it to be widespread in nature, permeating the lives of a diversity of animals, including all major classes of vertebrates. Recent studies suggest that culture's reach may extend also to invertebrates-notably, insects. In the present century, the reach of animal culture has been found to extend across many different behavioral domains and to rest on a suite of social learning processes facilitated by a variety of selective biases that enhance the efficiency and adaptiveness of learning. Far-reaching implications, for disciplines from evolutionary biology to anthropology and conservation policies, are increasingly being explored.

Leveraging Social Learning to Enhance Captive Animal Care and Welfare

From ants to zebras, animals are influenced by the behavior of others. At the simplest level, social support can reduce neophobia, increasing animals’ exploration of novel spaces, foods, and other environmental stimuli. Animals can also learn new skills more quickly and more readily after observing others perform them. How then can we apply animals’ proclivity to socially learn to enhance their care and welfare in captive settings? Here, I review the ways in which animals (selectively) use social information, and propose tactics for leveraging that to refine the behavioral management of captive animals: to enhance socialization techniques, enrichment strategies, and training outcomes. It is also important to consider, however, that social learning does not always promote the uniform expression of new behaviors. There are differences in animals’ likelihood to seek out or use socially provided information, driven by characteristics such as species, rank, age, and personality. Additionally, social learning can result in inexact transmission or the transmission of undesirable behaviors. Thus, understanding when, how, and why animals use social information is key to developing effective strategies to improve how we care for animals across settings and, ultimately, enhance captive animal welfare.

Spatial orientation of social caterpillars is influenced by polarized light

Processionary caterpillars of Thaumetopoea pityocampa (in Europe) and Ochrogaster lunifer (in Australia) (Lepidoptera: Notodontidae) form single files of larvae crawling head-to-tail when moving to feeding and pupation sites. We investigated if the processions are guided by polarization vision. The heading orientation of processions could be manipulated with linear polarizing filters held above the leading caterpillar. Exposure to changes in the angle of polarization around the caterpillars resulted in corresponding changes in heading angles. Anatomical analysis indicated specializations for polarization vision of stemma I in both species. Stemma I has a rhabdom with orthogonal and aligned microvilli, and an opaque and rugged surface, which are optimizations for skylight polarization vision, similar to the dorsal rim of adult insects. Stemmata II-VI have a smooth and shiny surface and lobed rhabdoms with non-orthogonal and non-aligned microvilli; they are thus optimized for general vision with minimal polarization sensitivity. Behavioural and anatomical evidence reveal that polarized light cues are important for larval orientation and can be robustly detected with a simple visual system.

Understanding contagion dynamics through microscopic processes in active Brownian particles

Together with the universally recognized SIR model, several approaches have been employed to understand the contagion dynamics of interacting particles. Here, Active Brownian particles (ABP) are introduced to model the contagion dynamics of living agents that perform a horizontal transmission of an infectious disease in space and time. By performing an ensemble average description of the ABP simulations, we statistically describe susceptible, infected, and recovered groups in terms of particle densities, activity, contagious rates, and random recovery times. Our results show that ABP reproduces the time dependence observed in traditional compartmental models such as the Susceptible-Infected-Recovery (SIR) models and allows us to explore the critical densities and the contagious radius that facilitates the virus spread. Furthermore, we derive a first-principles analytical expression for the contagion rate in terms of microscopic parameters, without considering free parameters as the classical SIR-based models. This approach offers a novel alternative to incorporate microscopic processes into analyzing SIR-based models with applications in a wide range of biological systems.

Pattern-induced local symmetry breaking in active-matter systems

The emergence of macroscopic order and patterns is a central paradigm in systems of (self-)propelled agents and a key component in the structuring of many biological systems. The relationships between the ordering process and the underlying microscopic interactions have been extensively explored both experimentally and theoretically. While emerging patterns often show one specific symmetry (e.g., nematic lane patterns or polarized traveling flocks), depending on the symmetry of the alignment interactions patterns with different symmetries can apparently coexist. Indeed, recent experiments with an actomysin motility assay suggest that polar and nematic patterns of actin filaments can interact and dynamically transform into each other. However, theoretical understanding of the mechanism responsible remains elusive. Here, we present a kinetic approach complemented by a hydrodynamic theory for agents with mixed alignment symmetries, which captures the experimentally observed phenomenology and provides a theoretical explanation for the coexistence and interaction of patterns with different symmetries. We show that local, pattern-induced symmetry breaking can account for dynamically coexisting patterns with different symmetries. Specifically, in a regime with moderate densities and a weak polar bias in the alignment interaction, nematic bands show a local symmetry-breaking instability within their high-density core region, which induces the formation of polar waves along the bands. These instabilities eventually result in a self-organized system of nematic bands and polar waves that dynamically transform into each other. Our study reveals a mutual feedback mechanism between pattern formation and local symmetry breaking in active matter that has interesting consequences for structure formation in biological systems.

Pronounced Fidelity and Selection for Average Conditions of Calving Area Suggestive of Spatial Memory in a Highly Migratory Ungulate

A distinguishing characteristic of many migratory animals is their annual return to distinct calving (birthing) areas in the spring, yet the navigational mechanisms employed during migration that result in this pattern are poorly understood. Effective conservation of these species requires reliable delineation of such areas, quantifying the factors that influence their selection, and understanding the underlying mechanisms resulting in use of calving areas. We used barren-ground caribou (Rangifer tarandus granti) as a study species and identified calving sites of the Western Arctic Herd in Alaska using GPS collar data from 2010–2017. We assessed variability in calving areas by comparing spatial delineations across all combinations of years. To understand calving area selection at a landscape scale, we performed a resource selection analysis comparing calving sites to available locations across the herd’s range and incorporated time-varying, remotely sensed metrics of vegetation quality and quantity. We found that whereas calving areas varied from year to year, this annual variation was centered on an area of recurring attraction consistent with previous studies covering the last six decades. Calving sites were characterized by high-quality forage at the average time of calving, but not peak calving that year, and by a narrow range of distinct physiographic factors. Each year, calving sites were located on areas of above-average conditions based on our predictive model. Our findings indicate that the pattern of spring migration for pregnant females was to migrate to areas that consistently provide high-quality forage when averaged across years, and then upon arriving at this calving ground, refine selection using their perception of annually varying conditions that are driven by environmental stochasticity. We suggest that the well-documented and widespread pattern of fidelity to calving grounds by caribou is supportive of a navigational mechanism based on spatial memory at a broad scale to optimize foraging and energy acquisition at a critical life-history stage. The extent to which migrants depend on memory to reach their spring destinations has implications for the adaptability of populations to changing climate and human impacts.

Collective navigation can facilitate passage through human-made barriers by homeward migrating Pacific salmon

The mass migration of animals is one of the great wonders of the natural world. Although there are multiple benefits for individuals migrating in groups, an increasingly recognized benefit is collective navigation, whereby social interactions improve animals’ ability to find their way. Despite substantial evidence from theory and laboratory-based experiments, empirical evidence of collective navigation in nature remains sparse. Here we used a unique large-scale radiotelemetry dataset to analyse the movements of adult Pacific salmon (Oncorhynchus sp.) in the Columbia River Basin, USA. These salmon face substantial migratory challenges approaching, entering and transiting fishways at multiple large-scale hydroelectric mainstem dams. We assess the potential role of collective navigation in overcoming these challenges and show that Chinook salmon (O. tshawytscha), but not sockeye salmon (O. nerka) locate fishways faster and pass in fewer attempts at higher densities, consistent with collective navigation. The magnitude of the density effects were comparable to major established drivers such as water temperature, and model simulations predicted that major fluctuations in population density can have substantial impacts on key quantities including mean passage time and fraction of fish with very long passage times. The magnitude of these effects indicates the importance of incorporating conspecific density and social dynamics into models of the migration process. Density effects on both ability to locate fishways and number of passage attempts have the potential to enrich our understanding of migratory energetics and success of migrating anadromous salmonids. More broadly, our work reveals a potential role of collective navigation, in at least one species, to mitigate the effects of anthropogenic barriers to animals on the move.

Mathematical models for cell migration: a non-local perspective

We provide a review of recent advancements in non-local continuous models for migration, mainly from the perspective of its involvement in embryonal development and cancer invasion. Particular emphasis is placed on spatial non-locality occurring in advection terms, used to characterize a cell's motility bias according to its interactions with other cellular and acellular components in its vicinity (e.g. cell-cell and cell-tissue adhesions, non-local chemotaxis), but we also briefly address spatially non-local source terms. Following a short introduction and description of applications, we give a systematic classification of available PDE models with respect to the type of featured non-localities and review some of the mathematical challenges arising from such models, with a focus on analytical aspects. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.

Rules of collective migration: from the wildebeest to the neural crest

Collective migration, the movement of groups in which individuals affect the behaviour of one another, occurs at practically every scale, from bacteria up to whole species' populations. Universal principles of collective movement can be applied at all levels. In this review, we will describe the rules governing collective motility, with a specific focus on the neural crest, an embryonic stem cell population that undergoes extensive collective migration during development. We will discuss how the underlying principles of individual cell behaviour, and those that emerge from a supracellular scale, can explain collective migration. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.

Comparison of solitary and collective foraging strategies of Caenorhabditis elegans in patchy food distributions

Collective foraging has been shown to benefit organisms in environments where food is patchily distributed, but whether this is true in the case where organisms do not rely on long-range communications to coordinate their collective behaviour has been understudied. To address this question, we use the tractable laboratory model organism Caenorhabditis elegans, where a social strain (npr-1 mutant) and a solitary strain (N2) are available for direct comparison of foraging strategies. We first developed an on-lattice minimal model for comparing collective and solitary foraging strategies, finding that social agents benefit from feeding faster and more efficiently simply owing to group formation. Our laboratory foraging experiments with npr-1 and N2 worm populations, however, show an advantage for solitary N2 in all food distribution environments that we tested. We incorporated additional strain-specific behavioural parameters of npr-1 and N2 worms into our model and computationally identified N2's higher feeding rate to be the key factor underlying its advantage, without which it is possible to recapitulate the advantage of collective foraging in patchy environments. Our work highlights the theoretical advantage of collective foraging owing to group formation alone without long-range interactions and the valuable role of modelling to guide experiments. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.

Challenges of machine learning model validation using correlated behaviour data: Evaluation of cross-validation strategies and accuracy measures

Automated monitoring of the movements and behaviour of animals is a valuable research tool. Recently, machine learning tools were applied to many species to classify units of behaviour. For the monitoring of wild species, collecting enough data for training models might be problematic, thus we examine how machine learning models trained on one species can be applied to another closely related species with similar behavioural conformation. We contrast two ways to calculate accuracies, termed here as overall and threshold accuracy, because the field has yet to define solid standards for reporting and measuring classification performances. We measure 21 dogs and 7 wolves, and find that overall accuracies are between 51 and 60% for classifying 8 behaviours (lay, sit, stand, walk, trot, run, eat, drink) when training and testing data are from the same species and between 41 and 51% when training and testing is cross-species. We show that using data from dogs to predict the behaviour of wolves is feasible. We also show that optimising the model for overall accuracy leads to similar overall and threshold accuracies, while optimizing for threshold accuracy leads to threshold accuracies well above 80%, but yielding very low overall accuracies, often below the chance level. Moreover, we show that the most common method for dividing the data between training and testing data (random selection of test data) overestimates the accuracy of models when applied to data of new specimens. Consequently, we argue that for the most common goals of animal behaviour recognition overall accuracy should be the preferred metric. Considering, that often the goal is to collect movement data without other methods of observation, we argue that training data and testing data should be divided by individual and not randomly.

Sea crossing as a major determinant for the evolution of migratory strategies in soaring birds

IN FOCUS

Santos, C. D., Silva, J. P., Muñoz, A.-R., Onrubia, A., & Wikelski, M. (2020). The gateway to Africa: What determines sea crossing performance of a migratory soaring bird at the strait of Gibraltar? Journal of Animal Ecology, 89, 1317-1328. Migrating birds undertake long journeys which pose several challenges. Water bodies are the most demanding ecological barriers for soaring birds, due to the increase in energy consumption and mortality risk. Through high-resolution GPS, Santos et al. (2020), analysed how the flight performance of 73 black kites crossing the Strait of Gibraltar was affected by external (e.g. weather conditions) and internal factors (individual experience). Kites waited for weaker crosswinds to start the crossing to minimize energy consumption, drift and altitude loss. Moreover, adults were quicker and lost less altitude than juveniles. These processes are likely to occur in all soaring species and have consequences also at a much wider spatial scale. In the Mediterranean region, species- and population-specific migration strategies appear to be influenced by interactions between species' morphology and the distribution of the land masses they traverse.

Collective decision-making by rational agents with differing preferences

Collective decisions can emerge from individual-level interactions between members of a group. These interactions are often seen as social feedback rules, whereby individuals copy the decisions they observe others making, creating a coherent group decision. The benefit of these behavioral rules to the individual agent can be understood as a transfer of information, whereby a focal individual learns about the world by gaining access to the information possessed by others. Previous studies have analyzed this exchange of information by assuming that all agents share common goals. While differences in information and differences in preferences have often been conflated, little is known about how differences between agents' underlying preferences affect the use and efficacy of social information. In this paper, I develop a model of social information use by rational agents with differing preferences, and demonstrate that the resulting collective behavior is strongly dependent on the structure of preference sharing within the group, as well as the quality of information in the environment. In particular, I show that strong social responses are expected by individuals that are habituated to noisy, uncertain environments where private information about the world is relatively weak. Furthermore, by investigating heterogeneous group structures, I demonstrate a potential influence of cryptic minority subgroups that may illuminate the empirical link between personality and leadership.

Consistent sociality but flexible social associations across temporal and spatial foraging contexts in a colonial breeder

When the consequences of sociality differ depending on the state of individual animals and the experienced environment, individuals may benefit from altering their social behaviours in a context-dependent manner. Thus, to fully address the hypotheses about the role of social associations it is imperative to consider the multidimensional nature of sociality by explicitly examining social associations across multiple scales and contexts. We simultaneously recorded > 8000 associations from 85% of breeding individuals from a colony of Australasian gannets (Morus serrator) over a 2-week period, and examined gregariousness across four foraging states using multilayer social network analysis. We found that social associations varied in a context-dependent manner, highlighting that social associations are most prevalent during foraging (local enhancement) and in regions expected to provide clustered resources. We also provide evidence of individual consistency in gregariousness, but flexibility in social associates, demonstrating that individuals can adjust their social behaviours to match experienced conditions.

Modular structure within groups causes information loss but can improve decision accuracy

Many animal groups exhibit signatures of persistent internal modular structure, whereby individuals consistently interact with certain groupmates more than others. In such groups, information relevant to a collective decision may spread unevenly through the group, but how this impacts the quality of the resulting decision is not well understood. Here, we explicitly model modularity within animal groups and examine how it affects the amount of information represented in collective decisions, as well as the accuracy of those decisions. We find that modular structure necessarily causes a loss of information, effectively silencing the input from a fraction of the group. However, the effect of this information loss on collective accuracy depends on the informational environment in which the decision is made. In simple environments, the information loss is detrimental to collective accuracy. By contrast, in complex environments, modularity tends to improve accuracy. This is because small group sizes typically maximize collective accuracy in such environments, and modular structure allows a large group to behave like a smaller group (in terms of its decision-making). These results suggest that in naturalistic environments containing correlated information, large animal groups may be able to exploit modular structure to improve decision accuracy while retaining other benefits of large group size.

This article is part of the theme issue ‘Liquid brains, solid brains: How distributed cognitive architectures process information’.

Decoding collective communications using information theory tools

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

Arboreal route navigation in a Neotropical mammal: energetic implications associated with tree monitoring and landscape attributes

BACKGROUND

Although navigating along a network of routes might constrain animal movement flexibility, it may be an energetically efficient strategy. Routinely using the same route allows for visually monitoring of food resources, which might reduce the cognitive load and as such facilitate the process of movement decision-making. Similarly, locating routes in areas that avoid costly landscape attributes will enhance their overall energy balance. In this study we determined the benefits of route navigation in an energy minimiser arboreal primate, the black howler monkey (Alouatta pigra).

METHODS

We monitored five neighbouring groups of black howler monkeys at Palenque National Park, Mexico from September 2016 through August 2017. We recorded the location of the focal group every 20 m and mapped all travel paths to establish a route network (N = 1528 travel bouts). We constructed linear mixed models to assess the influence of food resource distribution (N = 931 trees) and landscape attributes (slope, elevation and presence of canopy gaps) on the location of routes within a route network.

RESULTS

The number of food trees that fell within the visual detection distance from the route network was higher (mean: 156.1 ± SD 44.9) than randomly simulated locations (mean: 121.9 ± SD 46.4). Similarly, the number of food trees found within the monkey's visual range per meter travelled increased, on overage, 0.35 ± SE 0.04 trees/m with increasing use of the route. In addition, route segments used at least twice were more likely to occur with increasing density of food resources and decreasing presence of canopy gaps. Route segments used at least four times were more likely to occur in elevated areas within the home ranges but only under conditions of reduced visual access to food resources.

CONCLUSIONS

Route navigation emerged as an efficient movement strategy in a group-living arboreal primate. Highly used route segments potentially increased visual access to food resources while avoiding energetically costly landscape features securing foraging success in a tropical rainforest.

Collective Cell Migration: Wisdom of the Crowds Transforms a Negative Cue into a Positive One

The Semaphorin ligands and their Plexin receptors are known to induce cell-cell repulsion. A new study now finds that protrusion collapse, induced by Semaphorin-5C-Plexin-A interactions at the cell-cell contact, promotes planar polarization and collective migration of follicular cells in Drosophila.

Cultural Evolution in Animals

In recent decades, a burgeoning literature has documented the cultural transmission of behavior through social learning in numerous vertebrate and invertebrate species. One meaning of “cultural evolution in animals” refers to these discoveries, and I present an overview of key findings. I then address the other meaning of the term focused on cultural changes within a lineage. Such changes in humans, described as “cumulative cultural evolution,” have been spectacular, but relatively little attention has yet been paid to the topic in nonhuman animals, other than asserting that the process is unique to humans. A variety of evidence including both controlled experiments and field observations has begun to challenge this view, and in some behavioral domains, notably birdsong, cultural evolution has been studied for many years. In this review, I dissect concepts of cultural evolution and cumulative culture and appraise the accumulating evidence bearing on their nature and significance for evolutionary biology at large.

Northward range expansion in spring-staging barnacle geese is a response to climate change and population growth, mediated by individual experience

All long-distance migrants must cope with changing environments, but species differ greatly in how they do so. In some species, individuals might be able to adjust by learning from individual experiences and by copying others. This could greatly speed up the process of adjustment, but evidence from the wild is scarce. Here, we investigated the processes by which a rapidly growing population of barnacle geese (Branta leucopsis) responded to strong environmental changes on spring-staging areas in Norway. One area, Helgeland, has been the traditional site. Since the mid-1990s, an increasing number of geese stage in another area 250 km further north, Vesterålen. We collected data on goose numbers and weather conditions from 1975 to 2017 to explore the extent to which the increase in population size and a warmer climate contributed to this change in staging area use. During the study period, the estimated onset of grass growth advanced on average by 0.54 days/year in each of the two areas. The total production of digestible biomass for barnacle geese during the staging period increased in Vesterålen but remained stable in Helgeland. The goose population has doubled in size during the past 25 years, with most of the growth being accommodated in Vesterålen. The observations suggest that this dramatic increase would not have happened without higher temperatures in Vesterålen. Records of individually marked geese indicate that from the initial years of colonization onwards, especially young geese tended to switch to Vesterålen, thereby predominating in the flocks at Vesterålen. Older birds had a lower probability of switching to Vesterålen, but over the years, the probability increased for all ages. Our findings suggest that barnacle geese integrate socially learned behaviour with adjustments to individual experiences, allowing the population to respond rapidly and accurately to global change.

Experimental investigation of ant traffic under crowded conditions

Efficient transportation is crucial for urban mobility, cell function and the survival of animal groups. From humans driving on the highway, to ants running on a trail, the main challenge faced by all collective systems is how to prevent traffic jams in crowded environments. Here, we show that ants, despite their behavioral simplicity, have managed the tour de force of avoiding the formation of traffic jams at high density. At the macroscopic level, we demonstrated that ant traffic is best described by a two-phase flow function. At low densities there is a clear linear relationship between ant density and the flow, while at large density, the flow remains constant and no congestion occurs. From a microscopic perspective, the individual tracking of ants under varying densities revealed that ants adjust their speed and avoid time consuming interactions at large densities. Our results point to strategies by which ant colonies solve the main challenge of transportation by self-regulating their behavior.

Collective animal migration

Migratory movement is a strategy employed by a broad range of taxa as a response to temporally and spatially varying environmental conditions. Multiple factors can drive animal migration, including movement to hospitable environments when local conditions become unfavourable (such as to reduce nutritional and thermoregulatory stress), movement to find mates and/or breeding sites, and movement to minimise competition, predation, infection or parasitism. Migrating animals can often be seen to move together (Figure 1), sometimes in vast numbers. Despite this, the social aspects of migration have, to date, received very limited attention. Synchronisation of migratory behaviour among organisms, itself, does not imply that migrants utilise social information: synchrony is inevitable if there are relatively short windows of opportunity in which to move, or there exist sudden environmental changes that must be responded to. However, as will be outlined here, there is there is growing evidence that many migratory animals do utilise social cues, and that collective factors could shape migration in a variety of important ways.

Animal learning as a source of developmental bias

As a form of adaptive plasticity that allows organisms to shift their phenotype toward the optimum, learning is inherently a source of developmental bias. Learning may be of particular significance to the evolutionary biology community because it allows animals to generate adaptively biased novel behavior tuned to the environment and, through social learning, to propagate behavioral traits to other individuals, also in an adaptively biased manner. We describe several types of developmental bias manifest in learning, including an adaptive bias, historical bias, origination bias, and transmission bias, stressing that these can influence evolutionary dynamics through generating nonrandom phenotypic variation and/or nonrandom environmental states. Theoretical models and empirical data have established that learning can impose direction on adaptive evolution, affect evolutionary rates (both speeding up and slowing down responses to selection under different conditions) and outcomes, influence the probability of populations reaching global optimum, and affect evolvability. Learning is characterized by highly specific, path-dependent interactions with the (social and physical) environment, often resulting in new phenotypic outcomes. Consequently, learning regularly introduces novelty into phenotype space. These considerations imply that learning may commonly generate plasticity first evolution.

Nocturnal flight-calling behaviour predicts vulnerability to artificial light in migratory birds

Understanding interactions between biota and the built environment is increasingly important as human modification of the landscape expands in extent and intensity. For migratory birds, collisions with lighted structures are a major cause of mortality, but the mechanisms behind these collisions are poorly understood. Using 40 years of collision records of passerine birds, we investigated the importance of species' behavioural ecologies in predicting rates of building collisions during nocturnal migration through Chicago, IL and Cleveland, OH, USA. We found that the use of nocturnal flight calls is an important predictor of collision risk in nocturnally migrating passerine birds. Species that produce flight calls during nocturnal migration tended to collide with buildings more than expected given their local abundance, whereas those that do not use such communication collided much less frequently. Our results suggest that a stronger attraction response to artificial light at night in species that produce flight calls may mediate these differences in collision rates. Nocturnal flight calls probably evolved to facilitate collective decision-making during navigation, but this same social behaviour may now exacerbate vulnerability to a widespread anthropogenic disturbance. Our results also suggest that social behaviour during migration may reflect poorly understood differences in navigational mechanisms across lineages of birds.

Eco-evolutionary dynamics, density-dependent dispersal and collective behaviour: implications for salmon metapopulation robustness

The spatial dispersal of individuals plays an important role in the dynamics of populations, and is central to metapopulation theory. Dispersal provides connections within metapopulations, promoting demographic and evolutionary rescue, but may also introduce maladapted individuals, potentially lowering the fitness of recipient populations through introgression of heritable traits. To explore this dual nature of dispersal, we modify a well-established eco-evolutionary model of two locally adapted populations and their associated mean trait values, to examine recruiting salmon populations that are connected by density-dependent dispersal, consistent with collective migratory behaviour that promotes navigation. When the strength of collective behaviour is weak such that straying is effectively constant, we show that a low level of straying is associated with the highest gains in metapopulation robustness and that high straying serves to erode robustness. Moreover, we find that as the strength of collective behaviour increases, metapopulation robustness is enhanced, but this relationship depends on the rate at which individuals stray. Specifically, strong collective behaviour increases the presence of hidden low-density basins of attraction, which may serve to trap disturbed populations, and this is exacerbated by increased habitat heterogeneity. Taken as a whole, our findings suggest that density-dependent straying and collective migratory behaviour may help metapopulations, such as in salmon, thrive in dynamic landscapes. Given the pervasive eco-evolutionary impacts of dispersal on metapopulations, these findings have important ramifications for the conservation of salmon metapopulations facing both natural and anthropogenic contemporary disturbances.This article is part of the theme issue 'Collective movement ecology'.

Inferring the rules of social interaction in migrating caribou

Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa.

This article is part of the theme issue ‘Collective movement ecology’.

Migration in the Anthropocene: how collective navigation, environmental system and taxonomy shape the vulnerability of migratory species

Recent increases in human disturbance pose significant threats to migratory species using collective movement strategies. Key threats to migrants may differ depending on behavioural traits (e.g. collective navigation), taxonomy and the environmental system (i.e. freshwater, marine or terrestrial) associated with migration. We quantitatively assess how collective navigation, taxonomic membership and environmental system impact species' vulnerability by (i) evaluating population change in migratory and non-migratory bird, mammal and fish species using the Living Planet Database (LPD), (ii) analysing the role of collective navigation and environmental system on migrant extinction risk using International Union for Conservation of Nature (IUCN) classifications and (iii) compiling literature on geographical range change of migratory species. Likelihood of population decrease differed by taxonomic group: migratory birds were more likely to experience annual declines than non-migrants, while mammals displayed the opposite pattern. Within migratory species in IUCN, we observed that collective navigation and environmental system were important predictors of extinction risk for fishes and birds, but not for mammals, which had overall higher extinction risk than other taxa. We found high phylogenetic relatedness among collectively navigating species, which could have obscured its importance in determining extinction risk. Overall, outputs from these analyses can help guide strategic interventions to conserve the most vulnerable migrations.This article is part of the theme issue 'Collective movement ecology'.

Fitness trade-offs of group formation and movement by Thomson's gazelles in the Serengeti ecosystem

Collective behaviours contributing to patterns of group formation and coordinated movement are common across many ecosystems and taxa. Their ubiquity is presumably due to altering interactions between individuals and their predators, resources and physical environment in ways that enhance individual fitness. On the other hand, fitness costs are also often associated with group formation. Modifications to these interactions have the potential to dramatically impact population-level processes, such as trophic interactions or patterns of space use in relation to abiotic environmental variation. In a wide variety of empirical systems and models, collective behaviour has been shown to enhance access to ephemeral patches of resources, reduce the risk of predation and reduce vulnerability to environmental fluctuation. Evolution of collective behaviour should accordingly depend on the advantages of collective behaviour weighed against the costs experienced at the individual level. As an illustrative case study, we consider the potential trade-offs on Malthusian fitness associated with patterns of group formation and movement by migratory Thomson's gazelles in the Serengeti ecosystem.

This article is part of the theme issue ‘Collective movement ecology’.

Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data

While many animal species exhibit strong conspecific interactions, movement analyses of wildlife tracking datasets still largely focus on single individuals. Multi-individual wildlife tracking studies provide new opportunities to explore how individuals move relative to one another, but such datasets are frequently too sparse for the detailed, acceleration-based analytical methods typically employed in collective motion studies. Here, we address the methodological gap between wildlife tracking data and collective motion by developing a general method for quantifying movement correlation from sparsely sampled data. Unlike most existing techniques for studying the non-independence of individual movements with wildlife tracking data, our approach is derived from an analytically tractable stochastic model of correlated movement. Our approach partitions correlation into a deterministic tendency to move in the same direction termed 'drift correlation' and a stochastic component called 'diffusive correlation'. These components suggest the mechanisms that coordinate movements, with drift correlation indicating external influences, and diffusive correlation pointing to social interactions. We use two case studies to highlight the ability of our approach both to quantify correlated movements in tracking data and to suggest the mechanisms that generate the correlation. First, we use an abrupt change in movement correlation to pinpoint the onset of spring migration in barren-ground caribou. Second, we show how spatial proximity mediates intermittently correlated movements among khulans in the Gobi desert. We conclude by discussing the linkages of our approach to the theory of collective motion.This article is part of the theme issue 'Collective movement ecology'.

Synchronization, coordination and collective sensing during thermalling flight of freely migrating white storks

Exploring how flocks of soaring migrants manage to achieve and maintain coordination while exploiting thermal updrafts is important for understanding how collective movements can enhance the sensing of the surrounding environment. Here we examined the structural organization of a group of circling white storks (Ciconia ciconia) throughout their migratory journey from Germany to Spain. We analysed individual high-resolution GPS trajectories of storks during circling events, and evaluated each bird's flight behaviour in relation to its flock members. Within the flock, we identified subgroups that synchronize their movements and coordinate switches in their circling direction within thermals. These switches in direction can be initiated by any individual of the subgroup, irrespective of how advanced its relative vertical position is, and occur at specific horizontal locations within the thermal allowing the storks to remain within the thermal. Using the motion of all flock members, we were able to examine the dynamic variation of airflow within the thermals and to determine the specific environmental conditions surrounding the flock. With an increasing amount of high-resolution GPS tracking, we may soon be able to use these animals as distributed sensors providing us with a new means to obtain a detailed knowledge of our environment.This article is part of the theme issue 'Collective movement ecology'.

From single steps to mass migration: the problem of scale in the movement ecology of the Serengeti wildebeest

A central question in ecology is how to link processes that occur over different scales. The daily interactions of individual organisms ultimately determine community dynamics, population fluctuations and the functioning of entire ecosystems. Observations of these multiscale ecological processes are constrained by various technological, biological or logistical issues, and there are often vast discrepancies between the scale at which observation is possible and the scale of the question of interest. Animal movement is characterized by processes that act over multiple spatial and temporal scales. Second-by-second decisions accumulate to produce annual movement patterns. Individuals influence, and are influenced by, collective movement decisions, which then govern the spatial distribution of populations and the connectivity of meta-populations. While the field of movement ecology is experiencing unprecedented growth in the availability of movement data, there remain challenges in integrating observations with questions of ecological interest. In this article, we present the major challenges of addressing these issues within the context of the Serengeti wildebeest migration, a keystone ecological phenomena that crosses multiple scales of space, time and biological complexity.This article is part of the theme issue 'Collective movement ecology'.

Anatomy of leadership in collective behaviour

Understanding the mechanics behind the coordinated movement of mobile animal groups (collective motion) provides key insights into their biology and ecology, while also yielding algorithms for bio-inspired technologies and autonomous systems. It is becoming increasingly clear that many mobile animal groups are composed of heterogeneous individuals with differential levels and types of influence over group behaviors. The ability to infer this differential influence, or leadership, is critical to understanding group functioning in these collective animal systems. Due to the broad interpretation of leadership, many different measures and mathematical tools are used to describe and infer "leadership," e.g., position, causality, influence, and information flow. But a key question remains: which, if any, of these concepts actually describes leadership? We argue that instead of asserting a single definition or notion of leadership, the complex interaction rules and dynamics typical of a group imply that leadership itself is not merely a binary classification (leader or follower), but rather, a complex combination of many different components. In this paper, we develop an anatomy of leadership, identify several principal components, and provide a general mathematical framework for discussing leadership. With the intricacies of this taxonomy in mind, we present a set of leadership-oriented toy models that should be used as a proving ground for leadership inference methods going forward. We believe this multifaceted approach to leadership will enable a broader understanding of leadership and its inference from data in mobile animal groups and beyond.

Collective movement in ecology: from emerging technologies to conservation and management

Recent advances in technology and quantitative methods have led to the emergence of a new field of study that stands to link insights of researchers from two closely related, but often disconnected disciplines: movement ecology and collective animal behaviour. To date, the field of movement ecology has focused on elucidating the internal and external drivers of animal movement and the influence of movement on broader ecological processes. Typically, tracking and/or remote sensing technology is employed to study individual animals in natural conditions. By contrast, the field of collective behaviour has quantified the significant role social interactions play in the decision-making of animals within groups and, to date, has predominantly relied on controlled laboratory-based studies and theoretical models owing to the constraints of studying interacting animals in the field. This themed issue is intended to formalize the burgeoning field of collective movement ecology which integrates research from both movement ecology and collective behaviour. In this introductory paper, we set the stage for the issue by briefly examining the approaches and current status of research in these areas. Next, we outline the structure of the theme issue and describe the obstacles collective movement researchers face, from data acquisition in the field to analysis and problems of scale, and highlight the key contributions of the assembled papers. We finish by presenting research that links individual and broad-scale ecological and evolutionary processes to collective movement, and finally relate these concepts to emerging challenges for the management and conservation of animals on the move in a world that is increasingly impacted by human activity.This article is part of the theme issue 'Collective movement ecology'.