Modelling animal network data in R using STRAND.

There have been recent calls for wider application of generative modelling approaches in applied social network analysis. At present, however, it remains difficult for typical end users-for example, field researchers-to implement generative network models, as there is a dearth of openly available software packages that make application of such models as simple as other, permutation-based approaches. Here, we outline the STRAND R package, which provides a suite of generative models for Bayesian analysis of animal social network data that can be implemented using simple, base R syntax. To facilitate ease of use, we provide a tutorial demonstrating how STRAND can be used to model proportion, count or binary network data using stochastic block models, social relation models or a combination of the two modelling frameworks. STRAND facilitates the application of generative network models to a broad range of data found in the animal social networks literature.

Foraging and the importance of knowledge in Pemba, Tanzania: implications for childhood evolution.

Childhood is a period of life unique to humans. Childhood may have evolved through the need to acquire knowledge and subsistence skills. In an effort to understand the functional significance of childhood, previous research examined increases with age in returns to foraging across food resources. Such increases could be due to changes in knowledge, or other factors such as body size or strength. Here, we attempt to unpack these age-related changes. First, we estimate age-specific foraging returns for two resources. We then develop nonlinear structural equation models to evaluate the relative importance of ecological knowledge, grip strength and height in a population of part-time children foragers on Pemba island, Tanzania. We use anthropometric measures (height, strength, n = 250), estimates of ecological knowledge (n = 93) and behavioural observations for 63 individuals across 370 foraging trips. We find slower increases in foraging returns with age for trap hunting than for shellfish collection. We do not detect any effect of individual knowledge on foraging returns, potentially linked to information sharing within foraging parties. Producing accurate estimates of the distinct contribution of specific traits to an individual's foraging performance constitutes a key step in evaluating different hypotheses for the emergence of childhood.

Machine culture.

The ability of humans to create and disseminate culture is often credited as the single most important factor of our success as a species. In this Perspective, we explore the notion of 'machine culture', culture mediated or generated by machines. We argue that intelligent machines simultaneously transform the cultural evolutionary processes of variation, transmission and selection. Recommender algorithms are altering social learning dynamics. Chatbots are forming a new mode of cultural transmission, serving as cultural models. Furthermore, intelligent machines are evolving as contributors in generating cultural traits-from game strategies and visual art to scientific results. We provide a conceptual framework for studying the present and anticipated future impact of machines on cultural evolution, and present a research agenda for the study of machine culture.

Correction to: 'The natural selection of bad science' (2016) by Paul E. Smaldino and Richard McElreath.

[This corrects the article DOI: 10.1098/rsos.160384.][This corrects the article DOI: 10.1098/rsos.160384.].

Reliable network inference from unreliable data: A tutorial on latent network modeling using STRAND.

Social network analysis provides an important framework for studying the causes, consequences, and structure of social ties. However, standard self-report measures-for example, as collected through the popular "name-generator" method-do not provide an impartial representation of such ties, be they transfers, interactions, or social relationships. At best, they represent perceptions filtered through the cognitive biases of respondents. Individuals may, for example, report transfers that did not really occur, or forget to mention transfers that really did. The propensity to make such reporting inaccuracies is both an individual-level and item-level characteristic-variable across members of any given group. Past research has highlighted that many network-level properties are highly sensitive to such reporting inaccuracies. However, there remains a dearth of easily deployed statistical tools that account for such biases. To address this issue, we provide a latent network model that allows researchers to jointly estimate parameters measuring both reporting biases and a latent, underlying social network. Building upon past research, we conduct several simulation experiments in which network data are subject to various reporting biases, and find that these reporting biases strongly impact fundamental network properties. These impacts are not adequately remedied using the most frequently deployed approaches for network reconstruction in the social sciences (i.e., treating either the union or the intersection of double-sampled data as the true network), but are appropriately resolved through the use of our latent network models. To make implementation of our models easier for end-users, we provide a fully documented R package, STRAND, and include a tutorial illustrating its functionality when applied to empirical food/money sharing data from a rural Colombian population. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Understanding 'it depends' in ecology: a guide to hypothesising, visualising and interpreting statistical interactions.

Ecologists routinely use statistical models to detect and explain interactions among ecological drivers, with a goal to evaluate whether an effect of interest changes in sign or magnitude in different contexts. Two fundamental properties of interactions are often overlooked during the process of hypothesising, visualising and interpreting interactions between drivers: the measurement scale - whether a response is analysed on an additive or multiplicative scale, such as a ratio or logarithmic scale; and the symmetry - whether dependencies are considered in both directions. Overlooking these properties can lead to one or more of three inferential errors: misinterpretation of (i) the detection and magnitude (Type-D error), and (ii) the sign of effect modification (Type-S error); and (iii) misidentification of the underlying processes (Type-A error). We illustrate each of these errors with a broad range of ecological questions applied to empirical and simulated data sets. We demonstrate how meta-analysis, a widely used approach that seeks explicitly to characterise context dependence, is especially prone to all three errors. Based on these insights, we propose guidelines to improve hypothesis generation, testing, visualisation and interpretation of interactions in ecology.

Replication of the natural selection of bad science.

This study reports an independent replication of the findings presented by Smaldino and McElreath (Smaldino, McElreath 2016 R. Soc. Open Sci. 3, 160384 (doi:10.1098/rsos.160384)). The replication was successful with one exception. We find that selection acting on scientist's propensity for replication frequency caused a brief period of exuberant replication not observed in the original paper due to a coding error. This difference does not, however, change the authors' original conclusions. We call for more replication studies for simulations as unique contributions to scientific quality assurance.

Brain structure and function: a multidisciplinary pipeline to study hominoid brain evolution.

To decipher the evolution of the hominoid brain and its functions, it is essential to conduct comparative studies in primates, including our closest living relatives. However, strong ethical concerns preclude in vivo neuroimaging of great apes. We propose a responsible and multidisciplinary alternative approach that links behavior to brain anatomy in non-human primates from diverse ecological backgrounds. The brains of primates observed in the wild or in captivity are extracted and fixed shortly after natural death, and then studied using advanced MRI neuroimaging and histology to reveal macro- and microstructures. By linking detailed neuroanatomy with observed behavior within and across primate species, our approach provides new perspectives on brain evolution. Combined with endocranial brain imprints extracted from computed tomographic scans of the skulls these data provide a framework for decoding evolutionary changes in hominin fossils. This approach is poised to become a key resource for investigating the evolution and functional differentiation of hominoid brains.

The only thing that can stop bad causal inference is good causal inference.

In psychology, causal inference - both the transport from lab estimates to the real world and estimation on the basis of observational data - is often pursued in a casual manner. Underlying assumptions remain unarticulated; potential pitfalls are compiled in post-hoc lists of flaws. The field should move on to coherent frameworks of causal inference and generalizability that have been developed elsewhere.

Expanding the understanding of majority-bias in children's social learning.

Prior experiments with children across seven different societies have indicated U-shaped age patterns in the likelihood of copying majority demonstrations. It is unclear which learning strategies underlie the observed responses that create these patterns. Here we broaden the understanding of children's learning strategies by: (1) exploring social learning patterns among 6-13-year-olds (n = 270) from ethnolinguistically varied communities in Vanuatu; (2) comparing these data with those reported from other societies (n = 629), and (3) re-analysing our and previous data based on a theoretically plausible set of underlying strategies using Bayesian methods. We find higher rates of social learning in children from Vanuatu, a country with high linguistic and cultural diversity. Furthermore, our results provide statistical evidence for modest U-shaped age patterns for a more clearly delineated majority learning strategy across the current and previously investigated societies, suggesting that the developmental mechanisms structuring majority bias are cross-culturally highly recurrent and hence a fundamental feature of early human social learning.

When does selection favor learning from the old? Social learning in age-structured populations.

Culture and demography jointly facilitate flexible human adaptation, yet it still remains unclear how social learning operates in populations with age structure. Here, we present a mathematical model of the evolution of social learning in a population with different age classes. We investigate how demographic processes affect the adaptive value of culture, cultural adaptation and population growth, and identify the conditions that favor learning from older vs. younger individuals. We find that, even with age structure, social learning can evolve without increasing population fitness, i.e., "Rogers' paradox" still holds. However, a process of "demographic filtering", together with cultural transmission, can generate cumulative improvements in adaptation levels. We further show that older age classes have higher proportions of adaptive behavior when the environment is stable and adaptive behavior is hard to acquire but important to survival. Through individual-based simulations comparing temporal and spatial variability in the environment, we find a "copy-the-old"-strategy only evolves when social learning is erroneous and the opposite "copy-the-young"-strategy can function as a compromise between individual and social information use. Our results reveal that age structure substantially changes how culture evolves and provide principled empirical expectations about age-biased social learning and the role of demography in cultural adaptation.

Rates of ecological knowledge learning in Pemba, Tanzania: Implications for childhood evolution.

Humans live in diverse, complex niches where survival and reproduction are conditional on the acquisition of knowledge. Humans also have long childhoods, spending more than a decade before they become net producers. Whether the time needed to learn has been a selective force in the evolution of long human childhood is unclear, because there is little comparative data on the growth of ecological knowledge throughout childhood. We measured ecological knowledge at different ages in Pemba, Zanzibar (Tanzania), interviewing 93 children and teenagers between 4 and 26 years. We developed Bayesian latent-trait models to estimate individual knowledge and its association with age, activities, household family structure and education. In the studied population, children learn during the whole pre-reproductive period, but at varying rates, with the fastest increases in young children. Sex differences appear during middle childhood and are mediated by participation in different activities. In addition to providing a detailed empirical investigation of the relationship between knowledge acquisition and childhood, this study develops and documents computational improvements to the modelling of knowledge development.

The complex life course of mobility: Quantitative description of 300,000 residential moves in 1850-1950 Netherlands.

Mobility is a major mechanism of human adaptation, both in the deep past and in the present. Decades of research in the human evolutionary sciences have elucidated how much, how and when individuals and groups move in response to their ecology. Prior research has focused on small-scale subsistence societies, often in marginal environments and yielding small samples. Yet adaptive movement is commonplace across human societies, providing an opportunity to study human mobility more broadly. We provide a detailed, life-course structured demonstration, describing the residential mobility system of a historical population living between 1850 and 1950 in the industrialising Netherlands. We focus on how moves are patterned over the lifespan, attending to individual variation and stratifying our analyses by gender. We conclude that this population was not stationary: the median total moves in a lifetime were 10, with a wide range of variation and an uneven distribution over the life course. Mobility peaks in early adulthood (age 20-30) in this population, and this peak is consistent in all the studied cohorts, and both genders. Mobile populations in sedentary settlements provide a productive avenue for research on adaptive mobility and its relationship to human life history, and historical databases are useful for addressing evolutionarily motivated questions.

Conformity decreases throughout middle childhood among ni-Vanuatu children: An intracultural comparison.

Multiple studies have shown that children conform to majorities in perceptual judgment tasks against their better knowledge. However, these studies report contradictory results about how conformity develops over age. Here, we study variation in conformity over the course of middle childhood: we examined potential informational and normative motivations underlying conformity, as well as intracultural variability in their age patterns. We measured conformity in both a public and a private setting among 5- to 11-year-olds from eight different communities in Vanuatu (n = 125, 59 boys), a highly diverse society in the South Pacific. We also explored whether selected sociodemographic variables help to explain individual variation in children's conformity. Conformity is lower in both public and private settings the older ni-Vanuatu children are, with conformity in public settings being subject to more developmental and intracultural variation. We infer that normative conformity is more variable than informational conformity. Moreover, we find that children in higher school classes conform less. Our study combines a developmental perspective with an intracultural comparison, and demonstrates that both the publicness of the experimental situation and intracultural variability are important for the understanding of the age patterns of conformity. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Estimating the reproducibility of social learning research published between 1955 and 2018.

Reproducibility is integral to science, but difficult to achieve. Previous research has quantified low rates of data availability and results reproducibility across the biological and behavioural sciences. Here, we surveyed 560 empirical publications, published between 1955 and 2018 in the social learning literature, a research topic that spans animal behaviour, behavioural ecology, cultural evolution and evolutionary psychology. Data were recoverable online or through direct data requests for 30% of this sample. Data recovery declines exponentially with time since publication, halving every 6 years, and up to every 9 years for human experimental data. When data for a publication can be recovered, we estimate a high probability of subsequent data usability (87%), analytical clarity (97%) and agreement of published results with reproduced findings (96%). This corresponds to an overall rate of recovering data and reproducing results of 23%, largely driven by the unavailability or incompleteness of data. We thus outline clear measures to improve the reproducibility of research on the ecology and evolution of social behaviour.

Gendered movement ecology and landscape use in Hadza hunter-gatherers.

Understanding how gendered economic roles structure space use is critical to evolutionary models of foraging behaviour, social organization and cognition. Here, we examine hunter-gatherer spatial behaviour on a very large scale, using GPS devices worn by Hadza foragers to record 2,078 person-days of movement. Theory in movement ecology suggests that the density and mobility of targeted foods should predict spatial behaviour and that strong gender differences should arise in a hunter-gatherer context. As predicted, we find that men walked further per day, explored more land, followed more sinuous paths and were more likely to be alone. These data are consistent with the ecology of male- and female-targeted foods and suggest that male landscape use is more navigationally challenging in this hunter-gatherer context. Comparisons of Hadza space use with space use data available for non-human primates suggest that the sexual division of labour likely co-evolved with increased sex differences in spatial behaviour and landscape use.

Navigating cross-cultural research: methodological and ethical considerations.

The intensifying pace of research based on cross-cultural studies in the social sciences necessitates a discussion of the unique challenges of multi-sited research. Given an increasing demand for social scientists to expand their data collection beyond WEIRD (Western, educated, industrialized, rich and democratic) populations, there is an urgent need for transdisciplinary conversations on the logistical, scientific and ethical considerations inherent to this type of scholarship. As a group of social scientists engaged in cross-cultural research in psychology and anthropology, we hope to guide prospective cross-cultural researchers through some of the complex scientific and ethical challenges involved in such work: (a) study site selection, (b) community involvement and (c) culturally appropriate research methods. We aim to shed light on some of the difficult ethical quandaries of this type of research. Our recommendation emphasizes a community-centred approach, in which the desires of the community regarding research approach and methodology, community involvement, results communication and distribution, and data sharing are held in the highest regard by the researchers. We argue that such considerations are central to scientific rigour and the foundation of the study of human behaviour.

The life history of human foraging: Cross-cultural and individual variation.

Human adaptation depends on the integration of slow life history, complex production skills, and extensive sociality. Refining and testing models of the evolution of human life history and cultural learning benefit from increasingly accurate measurement of knowledge, skills, and rates of production with age. We pursue this goal by inferring hunters' increases and declines of skill from approximately 23,000 hunting records generated by more than 1800 individuals at 40 locations. The data reveal an average age of peak productivity between 30 and 35 years of age, although high skill is maintained throughout much of adulthood. In addition, there is substantial variation both among individuals and sites. Within study sites, variation among individuals depends more on heterogeneity in rates of decline than in rates of increase. This analysis sharpens questions about the coevolution of human life history and cultural adaptation.

The importance of life history and population regulation for the evolution of social learning.

Social learning and life history interact in human adaptation, but nearly all models of the evolution of social learning omit age structure and population regulation. Further progress is hindered by a poor appreciation of how life history affects selection on learning. We discuss why life history and age structure are important for social learning and present an exemplary model of the evolution of social learning in which demographic properties of the population arise endogenously from assumptions about per capita vital rates and different forms of population regulation. We find that, counterintuitively, a stronger reliance on social learning is favoured in organisms characterized by 'fast' life histories with high mortality and fertility rates compared to 'slower' life histories typical of primates. Long lifespans make early investment in learning more profitable and increase the probability that the environment switches within generations. Both effects favour more individual learning. Additionally, under fertility regulation (as opposed to mortality regulation), more juveniles are born shortly after switches in the environment when many adults are not adapted, creating selection for more individual learning. To explain the empirical association between social learning and long life spans and to appreciate the implications for human evolution, we need further modelling frameworks allowing strategic learning and cumulative culture. This article is part of the theme issue 'Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals'.

Dynamic social learning in temporally and spatially variable environments.

Cultural evolution is partly driven by the strategies individuals use to learn behaviour from others. Previous experiments on strategic learning let groups of participants engage in repeated rounds of a learning task and analysed how choices are affected by individual payoffs and the choices of group members. While groups in such experiments are fixed, natural populations are dynamic, characterized by overlapping generations, frequent migrations and different levels of experience. We present a preregistered laboratory experiment with 237 mostly German participants including migration, differences in expertise and both spatial and temporal variation in optimal behaviour. We used simulation and multi-level computational learning models including time-varying parameters to investigate adaptive time dynamics in learning. Confirming theoretical predictions, individuals relied more on (conformist) social learning after spatial compared with temporal changes. After both types of change, they biased decisions towards more experienced group members. While rates of social learning rapidly declined in rounds following migration, individuals remained conformist to group-typical behaviour. These learning dynamics can be explained as adaptive responses to different informational environments. Summarizing, we provide empirical insights and introduce modelling tools that hopefully can be applied to dynamic social learning in other systems.