Pathways to cultural adaptation: the coevolution of cumulative culture and social networks.

Humans have adapted to an immense array of environments by accumulating culturally transmitted knowledge and skills. Adaptive culture can accumulate either via more distinct cultural traits or via improvements of existing cultural traits. The kind of culture that accumulates depends on, and coevolves with, the social structure of societies. Here, we show that the coevolution of learning networks and cumulative culture results in two distinct pathways to cultural adaptation: highly connected populations with high proficiency but low trait diversity vs. sparsely connected populations with low proficiency but higher trait diversity. Importantly, we show there is a conflict between group-level payoffs, which are maximised in highly connected groups that attain high proficiency, and individual level selection, which favours disconnection. This conflict emerges from the interaction of social learning with population structure and causes populations to cycle between the two cultural and network states. The same conflict creates a paradox where increasing innovation rate lowers group payoffs. Finally, we explore how populations navigate these two pathways in environments where payoffs differ among traits and can change over time, showing that high proficiency is favoured when payoffs are stable and vary strongly between traits, while frequent changes in trait payoffs favour more trait diversity. Our results illustrate the complex interplay between networks, learning and the environment, and so inform our understanding of human social evolution.

Not by transmission alone: the role of invention in cultural evolution.

Innovation-the combination of invention and social learning-can empower species to invade new niches via cultural adaptation. Social learning has typically been regarded as the fundamental driver for the emergence of traditions and thus culture. Consequently, invention has been relatively understudied outside the human lineage-despite being the source of new traditions. This neglect leaves basic questions unanswered: what factors promote the creation of new ideas and practices? What affects their spread or loss? We critically review the existing literature, focusing on four levels of investigation: traits (what sorts of behaviours are easiest to invent?), individuals (what factors make some individuals more likely to be inventors?), ecological contexts (what aspects of the environment make invention or transmission more likely?), and populations (what features of relationships and societies promote the rise and spread of new inventions?). We aim to inspire new research by highlighting theoretical and empirical gaps in the study of innovation, focusing primarily on inventions in non-humans. Understanding the role of invention and innovation in the history of life requires a well-developed theoretical framework (which embraces cognitive processes) and a taxonomically broad, cross-species dataset that explicitly investigates inventions and their transmission. We outline such an agenda here. This article is part of the theme issue 'Foundations of cultural evolution'.

Underappreciated features of cultural evolution.

Cultural evolution theory has long been inspired by evolutionary biology. Conceptual analogies between biological and cultural evolution have led to the adoption of a range of formal theoretical approaches from population dynamics and genetics. However, this has resulted in a research programme with a strong focus on cultural transmission. Here, we contrast biological with cultural evolution, and highlight aspects of cultural evolution that have not received sufficient attention previously. We outline possible implications for evolutionary dynamics and argue that not taking them into account will limit our understanding of cultural systems. We propose 12 key questions for future research, among which are calls to improve our understanding of the combinatorial properties of cultural innovation, and the role of development and life history in cultural dynamics. Finally, we discuss how this vibrant research field can make progress by embracing its multidisciplinary nature. This article is part of the theme issue 'Foundations of cultural evolution'.

Capuchin monkey rituals: an interdisciplinary study of form and function.

Many white-faced capuchin monkey dyads in Lomas Barbudal, Costa Rica, practise idiosyncratic interaction sequences that are not part of the species-typical behavioural repertoire. These interactions often include uncomfortable or risky elements. These interactions exhibit the following characteristics commonly featured in definitions of rituals in humans: (i) they involve an unusual intensity of focus on the partner, (ii) the behaviours have no immediate utilitarian purpose, (iii) they sometimes involve 'sacred objects', (iv) the distribution of these behaviours suggests that they are invented and spread via social learning, and (v) many behaviours in these rituals are repurposed from other behavioural domains (e.g. extractive foraging). However, in contrast with some definitions of ritual, capuchin rituals are not overly rigid in their form, nor do the sequences have specific opening and closing actions. In our 9260 h of observation, ritual performance rate was uncorrelated with amount of time dyads spent in proximity but (modestly) associated with higher relationship quality and rate of coalition formation across dyads. Our results suggest that capuchin rituals serve a bond-testing rather than a bond-strengthening function. Ritual interactions are exclusively dyadic, and between-dyad consistency in form is low, casting doubt on the alternative hypothesis that they enhance group-wide solidarity. This article is part of the theme issue 'Ritual renaissance: new insights into the most human of behaviours'.

Evolution of contribution timing in public goods games.

Life-history strategies are a crucial aspect of life, which are complicated in group-living species, where pay-offs additionally depend on others' behaviours. Previous theoretical models of public goods games have generally focused on the amounts individuals contribute to the public good. Yet a much less-studied strategic aspect of public goods games, the timing of contributions, can also have dramatic consequences for individual and collective performance. Here, we develop two stage game theoretical models to explore how the timing of contributions evolves. In the first stage, individuals contribute to a threshold public good based on a performance schedule. The second stage begins once the threshold is met, and the individuals then compete as a function of their performance. We show how contributing rapidly is not necessarily optimal, because delayers can act as 'cheats,' avoiding contributing while reaping the benefits of the public good. However, delaying too long can put the delayers at a disadvantage as they may be ill-equipped to compete. These effects lead to bistability in a single group, and spatial diversity among multiple interacting groups.

Competition for resources can promote the divergence of social learning phenotypes.

Social learning occurs when animals acquire knowledge or skills by observing or interacting with others and is the fundamental building block of culture. Within populations, some individuals use social learning more frequently than others, but why social learning phenotypes differ among individuals is poorly understood. We modelled the evolution of social learning frequency in a system where foragers compete for resources, and there are many different foraging options to learn about. Social learning phenotypes diverged when some options offered much better rewards than others and expected rewards changed moderately quickly over time. When options offered similar rewards or when rewards changed slowly, a single social learning phenotype evolved. This held for fixed and simple conditional social learning rules. Sufficiently complex conditional social learning rules prevented the divergence of social learning phenotypes under all conditions. Our results explain how competition can promote the divergence of social learning phenotypes.

Cultural selection shapes network structure.

Cultural evolution relies on the social transmission of cultural traits along a population's social network. Research indicates that network structure affects information spread and thus the capacity for cumulative culture. However, how network structure itself is driven by population-culture co-evolution remains largely unclear. We use a simple model to investigate how populations negotiate the trade-off between acquiring new skills and getting better at existing skills and how this trade-off shapes social networks. We find unexpected eco-evolutionary feedbacks from culture onto social networks and vice versa. We show that selecting for skill generalists results in sparse networks with diverse skill sets, whereas selecting for skill specialists results in dense networks and a population that specializes on the same few skills on which everyone is an expert. Our model advances our understanding of the complex feedbacks in cultural evolution and demonstrates how individual-level behavior can lead to the emergence of population-level structure.

Reproductive skew affects social information use.

Individuals vary in their propensity to use social learning, the engine of cultural evolution, to acquire information about their environment. The causes of those differences, however, remain largely unclear. Using an agent-based model, we tested the hypothesis that as a result of reproductive skew differences in energetic requirements for reproduction affect the value of social information. We found that social learning is associated with lower variance in yield and is more likely to evolve in risk-averse low-skew populations than in high-skew populations. Reproductive skew may also result in sex differences in social information use, as empirical data suggest that females are often more risk-averse than males. To explore how risk may affect sex differences in learning strategies, we simulated learning in sexually reproducing populations where one sex experiences more reproductive skew than the other. When both sexes compete for the same resources, they tend to adopt extreme strategies: the sex with greater reproductive skew approaches pure individual learning and the other approaches pure social learning. These results provide insight into the conditions that promote individual and species level variation in social learning and so may affect cultural evolution.

Copy-when-uncertain: bumblebees rely on social information when rewards are highly variable.

To understand the relative benefits of social and personal information use in foraging decisions, we developed an agent-based model of social learning that predicts social information should be more adaptive where resources are highly variable and personal information where resources vary little. We tested our predictions with bumblebees and found that foragers relied more on social information when resources were variable than when they were not. We then investigated whether socially salient cues are used preferentially over non-social ones in variable environments. Although bees clearly used social cues in highly variable environments, under the same conditions they did not use non-social cues. These results suggest that bumblebees use a 'copy-when-uncertain' strategy.

Competition for resources can explain patterns of social and individual learning in nature.

In nature, animals often ignore socially available information despite the multiple theoretical benefits of social learning over individual trial-and-error learning. Using information filtered by others is quicker, more efficient and less risky than randomly sampling the environment. To explain the mix of social and individual learning used by animals in nature, most models penalize the quality of socially derived information as either out of date, of poor fidelity or costly to acquire. Competition for limited resources, a fundamental evolutionary force, provides a compelling, yet hitherto overlooked, explanation for the evolution of mixed-learning strategies. We present a novel model of social learning that incorporates competition and demonstrates that (i) social learning is favoured when competition is weak, but (ii) if competition is strong social learning is favoured only when resource quality is highly variable and there is low environmental turnover. The frequency of social learning in our model always evolves until it reduces the mean foraging success of the population. The results of our model are consistent with empirical studies showing that individuals rely less on social information where resources vary little in quality and where there is high within-patch competition. Our model provides a framework for understanding the evolution of social learning, a prerequisite for human cumulative culture.

Clearing pigmented insect cuticle to investigate small insects' organs in situ using confocal laser-scanning microscopy (CLSM).

Various microscopic techniques allow investigating structures from submicron to millimeter range, however, this is only possible if the structures of interest are not covered by pigmented cuticle. Here, we present a protocol that combines clearing of pigmented cuticle while preserving both, hard and soft tissues. The resulting transparent cuticle allows confocal laser-scanning microscopy (CLSM), which yields high-resolution images of e.g. the brain, glands, muscles and fine cuticular structures. Using a fluorescent dye, even single labeled neurons can be visualized and resolved up to an imaging depth of 150 µm through the cleared cuticle. Hydrogen-peroxide, which was used to clear the cuticle, does not preclude immunocytochemical techniques, shown by successful labeling of serotonin-immunoreactive neurons (5HT-ir) in the ants' brain. The 'transparent insect protocol' presented here is especially suited for small arthropods where dissection of organs is very demanding and difficult to achieve. Furthermore, the insect organs are preserved in situ thus allowing a more precise three-dimensional reconstruction of the structures of interest compared to, e.g., dissected or sectioned tissue.