ABSTRACT
In various animal species conspecifics aggregate at sleeping sites. Such aggregations can act as information centres where individuals acquire up-to-date knowledge about their environment. In some species, communal sleeping sites comprise individuals from multiple groups, where each group maintains stable membership over time. We used GPS tracking to simultaneously record group movement in a population of wild vulturine guineafowl (Acryllium vulturinum) to investigate whether communal sleeping sites can facilitate the transfer of information among individuals across distinct groups. These birds live in large and stable groups that move both together and apart, often forming communal roosts containing up to five groups. We first test whether roosts provide the opportunity for individuals to acquire information from members of other groups by examining the spatial organization at roosts. The GPS data reveal that groups intermix, thereby providing an opportunity for individuals to acquire out-group information. We next conduct a field experiment to test whether naïve groups can locate novel food patches when co-roosting with knowledgeable groups. We find that co-roosting substantially increases the chances for the members of a naïve group to discover a patch known to individuals from other groups at the shared roost. Further, we find that the discovery of food patches by naïve groups subsequently shapes their space use and inter-group associations. We also draw on our long-term tracking to provide examples that demonstrate natural cases where communal roosting has preceded large-scale multi-group collective movements that extend into areas beyond the groups' normal ranges. Our findings support the extension of the information centre hypothesis to communal sleeping sites that consist of distinct social groups.
Subject(s)
Galliformes , Social Behavior , Animals , Galliformes/physiology , Geographic Information Systems , Female , MaleABSTRACT
Deciding where to forage must not only account for variations in habitat quality but also where others might forage. Recent studies have suggested that when individuals remember recent foraging outcomes, negative frequency-dependent learning can allow them to avoid resources exploited by others (indirect competition). This process can drive the emergence of consistent differences in resource use (resource partitioning) at the population level. However, indirect cues of competition can be difficult for individuals to sense. Here, we propose that information pooling through collective decision-making-i.e. collective intelligence-can allow populations of group-living animals to more effectively partition resources relative to populations of solitary animals. We test this hypothesis by simulating (i) individuals preferring to forage where they were recently successful and (ii) cohesive groups that choose one resource using a majority rule. While solitary animals can partially avoid indirect competition through negative frequency-dependent learning, resource partitioning is more likely to emerge in populations of group-living animals. Populations of larger groups also better partition resources than populations of smaller groups, especially in environments with more choices. Our results give insight into the value of long- versus short-term memory, home range sizes and the evolution of specialization, optimal group sizes and territoriality. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.
Subject(s)
Learning , Animals , Social Behavior , Models, Biological , Intelligence , Ecosystem , Competitive Behavior , Decision MakingABSTRACT
Research Highlight: Mistrick, J., Veitch, J. S. M., Kitchen, S. M., Clague, S., Newman, B. C., Hall, R. J., Budischak, S. A., Forbes, K. M., & Craft, M. E. (2024). Effects of food supplementation and helminth removal on space use and spatial overlap in wild rodent populations. Journal of Animal Ecology. http://doi.org/10.1111/1365-2656.14067. The spread of pathogens has been of long-standing interest, even before dramatic outbreaks of avian influenza and the coronavirus pandemic spiked broad public interest. However, the dynamics of pathogen spread in wild populations are complex, with multiple effects shaping where animals go (their space use), population density and, more fundamentally, the resultant patterns of contacts (direct or indirect) among individuals. Thus, experimental studies exploring the dynamics of contact under different sets of conditions are needed. In the current field study, Mistrick et al. (2024) used a multifactorial experimental design, manipulating food availability and individual pathogen infection state in wild bank voles (Clethrionomys glareolus). They found that while food availability, individual traits and seasonality can affect how far individual voles moved, the degree of overlap between individual voles remained largely the same despite a high variation in population density-which itself was affected by food availability. These results highlight how biotic and abiotic factors can shape patterns of space use and balance the level of spatial overlap through multiple pathways.
Subject(s)
Arvicolinae , Animals , Rodent Diseases/epidemiology , Rodent Diseases/parasitology , Rodent Diseases/virology , Prevalence , Animals, Wild , Male , FemaleABSTRACT
To benefit from group living, individuals need to maintain cohesion and coordinate their activities. Effective communication thus becomes critical, facilitating rapid coordination of behaviours and reducing consensus costs when group members have differing needs and information. In many bird and mammal species, collective decisions rely on acoustic signals in some contexts but on movement cues in others. Yet, to date, there is no clear conceptual framework that predicts when decisions should evolve to be based on acoustic signals versus movement cues. Here, we first review how acoustic signals and movement cues are used for coordinating activities. We then outline how information masking, discrimination ability (Weber's Law) and encoding limitations, as well as trade-offs between these, can identify which types of collective behaviours likely rely on acoustic signals or movement cues. Specifically, our framework proposes that behaviours involving the timing of events or expression of specific actions should rely more on acoustic signals, whereas decisions involving complex choices with multiple options (e.g. direction and destination) should generally use movement cues because sounds are more vulnerable to information masking and Weber's Law effects. We then discuss potential future avenues of enquiry, including multimodal communication and collective decision-making by mixed-species animal groups. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamic'.
Subject(s)
Cues , Decision Making , Animals , Birds/physiology , Movement , Animal Communication , Social Behavior , Mammals/physiology , Vocalization, Animal/physiologyABSTRACT
Cooperation may emerge from intrinsic factors such as social structure and extrinsic factors such as environmental conditions. Although these factors might reinforce or counteract each other, their interaction remains unexplored in animal populations. Studies on multilevel societies suggest a link between social structure, environmental conditions and individual investment in cooperative behaviours. These societies exhibit flexible social configurations, with stable groups that overlap and associate hierarchically. Structure can be seasonal, with upper-level units appearing only during specific seasons, and lower-level units persisting year-round. This offers an opportunity to investigate how cooperation relates to social structure and environmental conditions. Here, we study the seasonal multilevel society of superb fairy-wrens (Malurus cyaneus), observing individual responses to experimental playback of conspecific distress calls. Individuals engaged more in helping behaviour and less in aggressive/territorial song during the harsher non-breeding season compared to the breeding season. The increase in cooperation was greater for breeding group members than for members of the same community, the upper social unit, comprised of distinct breeding groups in association. Results suggest that the interaction between social structure and environmental conditions drives the seasonal switch in cooperation, supporting the hypothesis that multilevel societies can emerge to increase cooperation during harsh environmental conditions.
Subject(s)
Passeriformes , Songbirds , Humans , Animals , Songbirds/physiology , Cooperative Behavior , Territoriality , Helping BehaviorABSTRACT
Early-life experiences can drive subsequent variation in social behaviours, but how differences among individuals emerge remains unknown. We combined experimental manipulations with GPS-tracking to investigate the pathways through which developmental conditions affect social network position during the early dispersal of wild red kites (Milvus milvus). Across 211 juveniles from 140 broods, last-hatched chicks-the least competitive-had the fewest number of peer encounters after fledging. However, when food supplemented, they had more encounters than all others. Using 4425 bird-days of GPS data, we revealed that this was driven by differential responses to competition, with less competitive individuals naturally spreading out into marginal areas, and clustering in central foraging areas when food supplemented. Our results suggest that early-life adversities can cause significant natal legacies on individual behaviour beyond independence, with potentially far-reaching consequences on the social and spatial structure of animal populations.
Subject(s)
Birds , Social Behavior , Humans , Animals , FoodABSTRACT
Shared-decision making is beneficial for the maintenance of group-living. However, little is known about whether consensus decision-making follows similar processes across different species. Addressing this question requires robust quantification of how individuals move relative to each other. Here we use high-resolution GPS-tracking of two vulturine guineafowl (Acryllium vulturinum) groups to test the predictions from a classic theoretical model of collective motion. We show that, in both groups, all individuals can successfully initiate directional movements, although males are more likely to be followed than females. When multiple group members initiate simultaneously, follower decisions depend on directional agreement, with followers compromising directions if the difference between them is small or choosing the majority direction if the difference is large. By aligning with model predictions and replicating the findings of a previous field study on olive baboons (Papio anubis), our results suggest that a common process governs collective decision-making in moving animal groups.
Subject(s)
Movement , Humans , Male , Animals , Female , MotionABSTRACT
Research Highlight: Ross, C. T., McElreath, R., & Redhead, D. (2023). Modelling animal network data in R using STRAND. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.14021. One of the most important insights in ecology over the past decade has been that the social connections among animals affect a wide range of ecological and evolutionary processes. However, despite over 20 years of study effort on this topic, generating knowledge from data on social associations and interactions remains fraught with problems. Redhead et al. present an R package-STRAND-that extends the current animal social network analysis toolbox in two ways. First, they provide a simple R interfaces to implement generative network models, which are an alternative to regression approaches that draw inference by simulating the data-generating process. Second, they implement these models in a Bayesian framework, allowing uncertainty in the observation process to be carried through to hypothesis testing. STRAND therefore fills an important gap for hypothesis testing using network data. However, major challenges remain, and while STRAND represents an important advance, generating robust results continues to require careful study design, considerations in terms of statistical methods and a plurality of approaches.
Subject(s)
Biological Evolution , Ecology , Animals , Bayes Theorem , Ecology/methods , Social NetworkingABSTRACT
The structure of animal societies is a key determinant of many ecological and evolutionary processes. Yet, we know relatively little about the factors and mechanisms that underpin detailed social structure. Among other factors, social structure can be influenced by habitat configuration. By shaping animal movement decisions, heterogeneity in habitat features, such as vegetation and the availability of resources, can influence the spatiotemporal distribution of individuals and subsequently key socioecological properties such as the local population size and density. Differences in local population size and density can impact opportunities for social associations and may thus drive substantial variation in local social structure. Here, we investigated spatiotemporal variation in population size at 65 distinct locations in a small songbird, the great tit (Parus major) and its effect on social network structure. We first explored the within-location consistency of population size from weekly samples and whether the observed variation in local population size was predicted by the underlying habitat configuration. Next, we created social networks from the birds' foraging associations at each location for each week and examined if local population size affected social structure. We show that population size is highly repeatable within locations across weeks and years and that some of the observed variation in local population size was predicted by the underlying habitat, with locations closer to the forest edge having on average larger population sizes. Furthermore, we show that local population size affected social structure inferred by four global network metrics. Using simple simulations, we then reveal that much of the observed social structure is shaped by social processes. Across different population sizes, the birds' social structure was largely explained by their preference to forage in flocks. In addition, over and above effects of social foraging, social preferences between birds (i.e. social relationships) shaped certain network features such as the extent of realized social connections. Our findings thus suggest that individual social decisions substantially contribute to shaping certain social network features over and above effects of population size alone.
Subject(s)
Passeriformes , Songbirds , Humans , Animals , Population Density , Social Behavior , Ecosystem , Social StructureABSTRACT
Individuals show consistent between-individual behavioural variation when they interact with conspecifics or heterospecifics. Such patterns might underlie emergent group-specific behavioural patterns and between-group behavioural differences. However, little is known about (i) how social and non-social drivers (external drivers) shape group-level social structures and (ii) whether animal groups show consistent between-group differences in social structure after accounting for external drivers. We used automated tracking to quantify daily social interactions and association networks in 12 colonies of zebra finches (Taeniopygia guttata). We quantified the effects of five external drivers (group size, group composition, ecological factors, physical environments and methodological differences) on daily interaction and association networks and tested whether colonies expressed consistent differences in day-to-day network structure after controlling for these drivers. Overall, we found that external drivers contribute significantly to network structure. However, even after accounting for the contribution of external drivers, there remained significant support for consistent between-group differences in both interaction (repeatability R: up to 0.493) and association (repeatability R: up to 0.736) network structures. Our study demonstrates how group-level differences in social behaviour can be partitioned into different drivers of variation, with consistent contributions from both social and non-social factors.
ABSTRACT
Major climatic changes in conjunction with animal movement may be associated with the spread of parasites and their vectors into new populations, with potentially important consequences for population persistence. Parasites can evolve to adapt to unsuitable ecological conditions and take up refuge within new host species, with consequences for the population growth of the new host species. One parasite species that has likely been increasing its geographic range, and potentially infecting new hosts, is the recently described air sac nematode Serratospiculoides amaculata, in great tits (Parus major) in Slovakia. In this study, we screened wild birds for potential air sac nematode infection in a woodland area of southern Germany. We identified four additional host species: Eurasian nuthatch, great spotted woodpecker, greenfinch and robin. As infection by this group of nematodes can be highly pathogenic, we recommend further investigation into its potential risk to these populations.
ABSTRACT
Multilevel societies are formed when stable groups of individuals spatially overlap and associate preferentially with other groups, producing a hierarchical social structure.1 Once thought to be exclusive to humans and large mammals, these complex societies have recently been described in birds.2,3 However, it remains largely unclear what benefits individuals gain by forming multilevel societies.1 One hypothesis-based on food sharing in hunter-gatherers4-is that multilevel societies facilitate access to a range of cooperative relationships, with individual investment varying across the hierarchical levels of the society. We tested experimentally whether such graded cooperation occurs in the multilevel society of a songbird, the superb fairy-wren (Malurus cyaneus). Specifically, we measured whether responses to playbacks of distress calls-used to recruit help when in extreme danger-varied according to the social level at which the focal individual is connected with the caller. We predicted that anti-predator responses should be highest within breeding groups (the core social unit), intermediate between groups from the same community, and lowest across groups from different communities. Our results confirm that birds exhibit the predicted hierarchical pattern of helping and that, within breeding groups, this pattern is independent of kinship. This pattern of graded helping responses supports the hypothesis that multilevel social structures can sustain stratified cooperative relationships and reveals similarity in cooperation in qualitatively different behaviors-anti-predator behavior and food sharing-in the multilevel societies of songbirds and humans.
Subject(s)
Passeriformes , Songbirds , Humans , Animals , Songbirds/physiology , Cooperative Behavior , Food , Social Behavior , MammalsABSTRACT
How individuals' prior experience and population evolutionary history shape emergent patterns in animal collectives remains a major gap in the study of collective behaviour. One reason for this is that the processes that can shape individual contributions to collective actions can happen over very different timescales from each other and from the collective actions themselves, resulting in mismatched timescales. For example, a preference to move towards a specific patch might arise from phenotype, memory or physiological state. Although providing critical context to collective actions, bridging different timescales remains conceptually and methodologically challenging. Here, we briefly outline some of these challenges, and discuss existing approaches that have already generated insights into the factors shaping individual contributions in animal collectives. We then explore a case study of mismatching timescales-defining relevant group membership-by combining fine-scaled GPS tracking data and daily field census data from a wild population of vulturine guineafowl (Acryllium vulturinum). We show that applying different temporal definitions can produce different assignments of individuals into groups. These assignments can then have consequences when determining individuals' social history, and thus the conclusions we might draw on the impacts of the social environment on collective actions. This article is part of a discussion meeting issue 'Collective behaviour through time'.
Subject(s)
Galliformes , Social Behavior , Animals , Mass Behavior , Social Environment , Longitudinal StudiesABSTRACT
Spatial and social behaviour are fundamental aspects of an animal's biology, and their social and spatial environments are indelibly linked through mutual causes and shared consequences. We define the 'spatial-social interface' as intersection of social and spatial aspects of individuals' phenotypes and environments. Behavioural variation at the spatial-social interface has implications for ecological and evolutionary processes including pathogen transmission, population dynamics, and the evolution of social systems. We link spatial and social processes through a foundation of shared theory, vocabulary, and methods. We provide examples and future directions for the integration of spatial and social behaviour and environments. We introduce key concepts and approaches that either implicitly or explicitly integrate social and spatial processes, for example, graph theory, density-dependent habitat selection, and niche specialization. Finally, we discuss how movement ecology helps link the spatial-social interface. Our review integrates social and spatial behavioural ecology and identifies testable hypotheses at the spatial-social interface.
Subject(s)
Ecology , Ecosystem , Animals , Social Behavior , Spatial Behavior , Phenotype , Biological EvolutionABSTRACT
Interactions between humans and nature have profound consequences, which rarely are mutually beneficial. Further, behavioral and environmental changes can turn human-wildlife cooperative interactions into conflicts, threatening their continued existence. By tracking fine-scale behavioral interactions between artisanal fishers and wild dolphins targeting migratory mullets, we reveal that foraging synchrony is key to benefiting both predators. Dolphins herd mullet schools toward the coast, increasing prey availability within the reach of the net-casting fishers, who gain higher foraging success-but only when matching the casting behavior with the dolphins' foraging cues. In turn, when dolphins approach the fishers' nets closely and cue fishers in, they dive for longer and modify their active foraging echolocation to match the time it takes for nets to sink and close over mullets-but only when fishers respond to their foraging cues appropriately. Using long-term demographic surveys, we show that cooperative foraging generates socioeconomic benefits for net-casting fishers and ca. 13% survival benefits for cooperative dolphins by minimizing spatial overlap with bycatch-prone fisheries. However, recent declines in mullet availability are threatening these short- and long-term benefits by reducing the foraging success of net-casting fishers and increasing the exposure of dolphins to bycatch in the alternative fisheries. Using a numerical model parametrized with our empirical data, we predict that environmental and behavioral changes are pushing this traditional human-dolphin cooperation toward extinction. We propose two possible conservation actions targeting fishers' behavior that could prevent the erosion of this century-old fishery, thereby safeguarding one of the last remaining cases of human-wildlife cooperation.
Subject(s)
Dolphins , Smegmamorpha , Animals , Humans , Conservation of Natural Resources , Symbiosis , Animals, Wild , FisheriesABSTRACT
Observing the behaviour of others is a cheap and effective way of acquiring up-to-date information about the environment. Further, an animal that changes its behaviour in response to acquiring social information effectively propagates that information forwards. Although the rules that govern how individual birds detect and respond to social cues are often very simple, they are able to produce a diverse range of collective actions from which individuals can reap benefits that include predator avoidance and more accurate estimations of the environment. Understanding how and why individual-level rules that favour the emergence of collective behaviour have evolved therefore requires knowledge of the ecological and social contexts in which they are expressed. The breadth of research on social behaviours in birds is an unparalleled window into the ecology of collective behaviour and provides many opportunities to test whether different species overcome different ecological challenges using similar social rules and whether the collective behaviours of birds can act as sensors for the environment.
Subject(s)
Birds , Social Behavior , Animals , Mass Gatherings , Social Environment , KnowledgeABSTRACT
Foraging innovations can give wild animals access to human-derived food sources1. If these innovations spread, they can enable adaptive flexibility2 but also lead to human-wildlife conflicts3. Examples include crop-raiding elephants4 and long-tailed macaques that steal items from people to trade them back for food5. Behavioural responses by humans might act as a further driver on animal innovation2,6, even potentially leading to an inter-species 'innovation arms-race'7, yet this is almost entirely unexplored. Here, we report a potential case in wild, urban-living, sulphur-crested cockatoos (Cacatua galerita; henceforth cockatoos), where the socially-learnt behaviour of opening and raiding of household bins by cockatoos8 is met with increasingly effective and socially-learnt bin-protection measures by human residents.
Subject(s)
Cockatoos , Elephants , Parrots , Animals , Animals, Wild , Humans , ResearchABSTRACT
Parasites can impact the behavior of animals and alter the interplay with ecological factors in their environment. Studying the effects that parasites have on animals thus requires accurate estimates of infections in individuals. However, quantifying parasites can be challenging due to several factors. Laboratory techniques, physiological fluctuations, methodological constraints, and environmental influences can introduce measurement errors, in particular when screening individuals in the wild. These issues are pervasive in ecological studies where it is common to sample study subjects only once. Such factors should be carefully considered when choosing a sampling strategy, yet presently there is little guidance covering the major sources of error. In this study, we estimate the reliability and sensitivity of different sampling practices at detecting two internal parasites-Serratospiculoides amaculata and Isospora sp.-in a model organism, the great tit Parus major. We combine field and captive sampling to assess whether individual parasite infection status and load can be estimated from single field samples, using different laboratory techniques-McMaster and mini-FLOTAC. We test whether they vary in their performance, and quantify how sample processing affects parasite detection rates. We found that single field samples had elevated rates of false negatives. By contrast, samples collected from captivity over 24 h were highly reliable (few false negatives) and accurate (repeatable in the intensity of infection). In terms of methods, we found that the McMaster technique provided more repeatable estimates than the mini-FLOTAC for S. amaculata eggs, and both techniques were largely equally suitable for Isospora oocysts. Our study shows that field samples are likely to be unreliable in accurately detecting the presence of parasites and, in particular, for estimating parasite loads in songbirds. We highlight important considerations for those designing host-parasite studies in captive or wild systems giving guidance that can help select suitable methods, minimize biases, and acknowledge possible limitations.
ABSTRACT
Abstract: Studying the social behaviour of small or cryptic species often relies on constructing networks from sparse point-based observations of individuals (e.g. live trapping data). A common approach assumes that individuals that have been detected sequentially in the same trapping location will also be more likely to have come into indirect and/or direct contact. However, there is very little guidance on how much data are required for making robust networks from such data. In this study, we highlight that sequential trap sharing networks broadly capture shared space use (and, hence, the potential for contact) and that it may be more parsimonious to directly model shared space use. We first use empirical data to show that characteristics of how animals use space can help us to establish new ways to model the potential for individuals to come into contact. We then show that a method that explicitly models individuals' home ranges and subsequent overlap in space among individuals (spatial overlap networks) requires fewer data for inferring observed networks that are more strongly correlated with the true shared space use network (relative to sequential trap sharing networks). Furthermore, we show that shared space use networks based on estimating spatial overlap are also more powerful for detecting biological effects. Finally, we discuss when it is appropriate to make inferences about social interactions from shared space use. Our study confirms the potential for using sparse trapping data from cryptic species to address a range of important questions in ecology and evolution. Significance statement: Characterising animal social networks requires repeated (co-)observations of individuals. Collecting sufficient data to characterise the connections among individuals represents a major challenge when studying cryptic organisms-such as small rodents. This study draws from existing spatial mark-recapture data to inspire an approach that constructs networks by estimating space use overlap (representing the potential for contact). We then use simulations to demonstrate that the method provides consistently higher correlations between inferred (or observed) networks and the true underlying network compared to current approaches and requires fewer observations to reach higher correlations. We further demonstrate that these improvements translate to greater network accuracy and to more power for statistical hypothesis testing. Supplementary Information: The online version contains supplementary material available at 10.1007/s00265-022-03222-5.
ABSTRACT
Permutation tests are widely used to test null hypotheses with animal social network data, but suffer from high rates of type I and II error when the permutations do not properly simulate the intended null hypothesis.Two common types of permutations each have limitations. Pre-network (or datastream) permutations can be used to control 'nuisance effects' like spatial, temporal or sampling biases, but only when the null hypothesis assumes random social structure. Node (or node-label) permutation tests can test null hypotheses that include nonrandom social structure, but only when nuisance effects do not shape the observed network.We demonstrate one possible solution addressing these limitations: using pre-network permutations to adjust the values for each node or edge before conducting a node permutation test. We conduct a range of simulations to estimate error rates caused by confounding effects of social or non-social structure in the raw data.Regressions on simulated datasets suggest that this 'double permutation' approach is less likely to produce elevated error rates relative to using only node permutations, pre-network permutations or node permutations with simple covariates, which all exhibit elevated type I errors under at least one set of simulated conditions. For example, in scenarios where type I error rates from pre-network permutation tests exceed 30%, the error rates from double permutation remain at 5%.The double permutation procedure provides one potential solution to issues arising from elevated type I and type II error rates when testing null hypotheses with social network data. We also discuss alternative approaches that can provide robust inference, including fitting mixed effects models, restricted node permutations, testing multiple null hypotheses and splitting large datasets to generate replicated networks. Finally, we highlight ways that uncertainty can be explicitly considered and carried through the analysis.