In many animal societies, individuals differ consistently in their ability to win agonistic interactions, resulting in dominance hierarchies. These differences arise due to a range of factors that can influence individuals’ abilities to win agonistic interactions, spanning from genetically driven traits through to individuals’ recent interaction history. Yet, despite a century of study since Schjelderup‐Ebbe's seminal paper on social dominance, we still lack a general understanding of how these different factors work together to determine individuals’ positions in hierarchies. Here, we first outline five widely studied factors that can influence interaction outcomes: intrinsic attributes, resource value asymmetry, winner–loser effects, dyadic interaction‐outcome history and third‐party support. A review of the evidence shows that a variety of factors are likely important to interaction outcomes, and thereby individuals’ positions in dominance hierarchies, in diverse species. We propose that such factors are unlikely to determine dominance outcomes independently, but rather form part of feedback loops whereby the outcomes of previous agonistic interactions (e.g. access to food) impact factors that might be important in subsequent interactions (e.g. body condition). We provide a conceptual framework that illustrates the multitude potential routes through which such feedbacks can occur, and how the factors that determine the outcomes of dominance interactions are highly intertwined and thus rarely act independently of one another. Further, we generalise our framework to include multi‐generational feed‐forward mechanisms: how interaction outcomes in one generation can influence the factors determining interaction outcomes in the next generation via a range of parental effects. This general framework describes how interaction outcomes and the factors determining them are linked within generations via feedback loops, and between generations via feed‐forward mechanisms. We then highlight methodological approaches that will facilitate the study of feedback loops and dominance dynamics. Lastly, we discuss how our framework could shape future research, including: how feedbacks generate variation in the factors discussed, and how this might be studied experimentally; how the relative importance of different feedback mechanisms varies across timescales; the role of social structure in modulating the effect of feedbacks on hierarchy structure and stability; and the routes of parental influence on the dominance status of offspring. Ultimately, by considering dominance interactions as part of a dynamic feedback system that also feeds forward into subsequent generations, we will understand better the factors that structure dominance hierarchies in animal groups.
In many animal societies, individuals differ consistently in their ability to win agonistic interactions, resulting in dominance hierarchies. These differences arise due to a range of factors that can influence individuals’ abilities to win agonistic interactions, spanning from genetically driven traits through to individuals’ recent interaction history. Yet, despite a century of study since Schjelderup-Ebbe’s seminal paper on social dominance, we still lack a general understanding of how these different factors work together to determine individuals’ positions in hierarchies. Here, we first outline five widely studied factors that can influence interaction outcomes: intrinsic attributes, resource value asymmetry, winner-loser effects, dyadic interaction-outcome history and third-party support. A review of the evidence shows that whilst different factors have been shown to be important in specific systems, there are few empirical cases where one factor has a definitive effect. We then propose that mixed empirical support for a single factor is likely to arise due to feedback loops, whereby the outcomes of previous agonistic interactions (e.g. access to food) impact factors that might be important in subsequent interactions (e.g. body condition). We provide a conceptual framework which illustrates that there are many potential routes through which feedbacks can occur. Such feedbacks suggest that the factors that determine outcomes of dominance interactions are highly intertwined and are likely to rarely act independently of one-another. Further, we generalise our framework to include multi-generational feed-forward mechanisms and highlight how interaction outcomes in one generation can influence the factors determining interaction outcomes of their offspring via a range of parental effects. This general framework describes how interaction outcomes and the factors determining them are linked within generations via feedback loops, and between generations via feed-forward mechanisms. We then highlight methodological approaches that will facilitate the study of feedback loops and dominance dynamics. Lastly, we discuss how our framework can shape future research, including investigating how feedbacks in dominance hierarchies produce ‘self-organised’ structure, exploring how interaction outcomes are integrated to form dominance hierarchies, and the routes of parental influence on the dominance status of offspring. Ultimately, by considering dominance interactions as part of a dynamic system, that also feeds forward into subsequent generations, we will better understand the factors that structure dominance hierarchies in animal groups.
Animal cultures have now been demonstrated experimentally in diverse taxa from flies to great apes. However, experiments commonly use tasks with unrestricted access to equal pay-offs and innovations seeded by demonstrators who are trained to exhibit strong preferences. Such conditions may not reflect those typically found in nature. For example, the learned preferences of natural innovators may be weaker, while competition for depleting resources can favour switching between strategies and generalizing from past experience. Here we show that in experiments where wild jackdaws ( Corvus monedula ) can freely discover depleting supplies of novel foods, generalization has a powerful effect on learning, allowing individuals to exploit multiple new opportunities through both social and individual learning. Further, in contrast to studies with trained demonstrators, individuals that were first to innovate showed weak preferences. As a consequence, many individuals ate all available novel foods, displaying no strong preference and no group-level culture emerged. Individuals followed a ‘learn from adults’ strategy, but other demographic factors played a minimal role in shaping social transmission. These results demonstrate the importance of generalization in allowing animals to exploit new opportunities and highlight how natural competitive dynamics may impede the formation of culture.
The adjustment of social associations by individuals in response to changes in their social environment is a core principle of influential theories on the evolution of cognition1,2 and cooperation3,4. Selectively adjusting associations with others is thought to allow individuals to maximise short-term rewards from social interactions, thus re-shaping social networks to better favour connections between compatible group members5–8. Crucially, this has yet to be tested in natural populations, where the need to maintain long-term, fitness-enhancing relationships may limit social plasticity9,10. Using a novel social-network-manipulation experiment, we show that wild jackdaws (Corvus monedula) learned to favour social associations with compatible group members (individuals that provided greater returns from social foraging interactions). Consequently, the overall frequency of associations between compatible social partners increased as the experiment progressed. This resulted in clustering of compatible individuals within the social network, but the magnitude of this effect was small, likely due to the preservation of pre-existing long-term relationships. These results provide critical field evidence that learning to adjust social associations is beneficial whilst highlighting trade-offs with the need to maintain valuable long-term relationships. Our findings therefore provide important insights into the cognitive and behavioural basis of social network plasticity and the interplay between individual behaviour and social network structure in natural populations.
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