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. Specifically, how do demographic processes affect the adaptive value of culture, cultural adaptation and population growth and when does selection favor copying the behavior of older vs. younger individuals? Here, we develop and analyze a mathematical model of the evolution of social learning in a population with different age classes. We find that adding age structure alone does not resolve Rogers' paradox, i.e. the finding that social learning can evolve without increasing population fitness. Cultural transmission in combination with demographic filtering, however, can lead to much higher adaptation levels. This is because by increasing proportions of adaptive behavior in older age classes, demographic filtering constitutes an additional adaptive force that social learners can benefit from. Moreover, older age classes tend to have higher proportions of adaptive behavior when the environment is relatively stable and adaptive behavior is hard to acquire but confers large survival advantages. Through individual-based simulations comparing temporal and spatial variability in the environment, we find a ``copy older over younger models''-strategy only evolves readily when social learning is erroneous. The opposite ``copy the younger''-strategy is adaptive when the environment fluctuates frequently but still maintains large proportions of social learners. Our results demonstrate that age structure can substantially alter cultural dynamics and should be addressed in further theoretical and empirical work

Racial disparities in police use of deadly force against unarmed individuals persist after appropriately benchmarking shooting data on violent crime rates

Cesario et al. argue that benchmarking the relative counts of killings by police on relative crime rates, rather than relative population sizes, generates a measure of racial disparity in the use of lethal force that is unbiased by differential crime rates. Their publication, however, lacked any formal derivation showing that their benchmarking methodology has the statistical properties required to establish such a claim. We use the causal model of lethal force by police conditional on relative crime rates implicit in their analyses and prove that their benchmarking methodology does not, in general, remove the bias introduced by crime rate differences. Instead, it creates strong statistical biases that mask true racial disparities, especially in the killing of unarmed noncriminals by police. Reanalysis of their data using formally derived criminality-correcting benchmarks shows that there is strong and statistically reliable evidence of anti-Black racial disparities in the killing of unarmed Americans by police in 2015?2016

A causal framework for cross-cultural generalizability

Behavioral researchers increasingly recognize the need for more diverse samples that capture the breadth of human experience. Current attempts to establish generalizability across populations focus on threats to validity, constraints on generalization, and the accumulation of large, cross-cultural data sets. But for continued progress, we also require a framework that lets us determine which inferences can be drawn and how to make informative cross-cultural comparisons. We describe a generative causal-modeling framework and outline simple graphical criteria to derive analytic strategies and implied generalizations. Using both simulated and real data, we demonstrate how to project and compare estimates across populations and further show how to formally represent measurement equivalence or inequivalence across societies. We conclude with a discussion of how a formal framework for generalizability can assist researchers in designing more informative cross-cultural studies and thus provides a more solid foundation for cumulative and generalizable behavioral research

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

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

High rate of extrapair paternity in a human population demonstrates diversity in human reproductive strategies.

Among nonhuman species, social monogamy is rarely accompanied by complete fidelity. Evolutionary theory predicts that the rate of extrapair paternity (EPP) should vary according to socioecological conditions. In humans, however, geneticists contend that EPP is negligible and relatively invariable. This conclusion is based on a limited set of studies, almost all of which describe European-descent groups. Using a novel, double-blind method designed in collaboration with a community of Himba pastoralists, we find that the rate of EPP in this population is 48%, with 70% of couples having at least one EPP child. Both men and women were very accurate at detecting cases of EPP. These data suggest that the range of variation in EPP across human populations is substantially greater than previously thought. We further show that a high rate of EPP can be accompanied by high paternity confidence, which highlights the importance of disaggregating EPP from the notion of "cuckoldry.

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

Stream Network Geometry and the Spatial Influence of Aquatic Insect Subsidies Across the Contiguous United States

Emergent aquatic insects transport aquatic‐derived resources into terrestrial ecosystems but are rarely studied at landscape or regional scales. Here, we investigate how stream network geometry constrains the spatial influence of aquatic insect subsidies in terrestrial ecosystems. We also explore potential factors (i.e., climate, topography, soils, and vegetation) that could produce variation in stream network geometry and thus change the extent of aquatic insect subsidies from one region to another. The stream signature is the percentage of aquatic insect subsidies traveling a given distance into the terrestrial ecosystem, relative to what comes out of the stream. We use this concept to model the spatial extent (area) and distribution (spatial patterning) of aquatic subsidies in terrestrial ecosystems across the contiguous United States. Our findings suggest that at least 8% of the subsidies measured at the aquatic–terrestrial boundary (i.e., the 8% stream signature) are typically transferred throughout the entire watershed and that variation in this spatial extent is largely influenced by the drainage density of the stream network. Moreover, we found stream signatures from individual stream reaches overlap such that the spatial extent of the 8% stream signature often includes inputs from multiple stream reaches. Landscape‐scale stream network characteristics increased the area of overlapping stream signatures more than reach‐scale channel properties. Finally, we found runoff was an important factor influencing stream network geometry suggesting a potential effect of climate on aquatic‐to‐terrestrial linkages that have been understudied.Financial support was provided by a grant from this National Science Foundation (EF‐1802872) to DCA, and the Adams Family Endowment at the University of Oklahoma provided additional financial support to DAK. Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

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