Problems modelling behavioural variation across Western North American Indian societies

Towner, Mary C.; Grote, Mark N.; Mulder, Monique Borgerhoff

doi:10.1098/rspb.2015.2184

Cited by 5 publications

(3 citation statements)

References 23 publications

(38 reference statements)

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Towner et al [1] question the methods and the theoretical framework of our study of behavioural variation among Native American tribes of Western North America [2]. Here we show that their concerns are unfounded and that our results are robust.

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supporting

confidence: 61%

Cultural history, not ecological environment, is the main determinant of human behaviour

Mathew

Perreault

2016

Proc. R. Soc. B.

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Towner et al. [1] question the methods and the theoretical framework of our study of behavioural variation among Native American tribes of Western North America [2]. Here we show that their concerns are unfounded and that our results are robust. We also clarify the theoretical issues that motivated our paper, and explain why it is critical to disentangle the role of ecology and cultural inheritance in a cultural species like humans.Towner et al. contend that the higher summed absolute value of the cultural -historical betas (i.e. C ) relative to that of ecology (i.e. E) is due to the fact that cultural history has 10 potential predictors and ecology has seven. Their argument is based on the fact that the expectation of the absolute beta of a predictor representing stochastic noise is not zero, but ð2s 2 =pÞ 1=2 (assuming the coefficients are drawn from a Gaussian distribution with mean zero and standard deviation s). This is because the probability density on the negative side of the distribution of beta is shifted to the positive side in the distribution of the absolute beta. Thus, any predictor in a model will contribute to C or E, even when they represent stochastic noise. Towner et al. suggest that the correct measure of the effect size of cultural history and ecology is C À M C ð2s 2 =pÞ 1=2 and E À M E ð2s 2 =pÞ 1=2 , where M C and M E are the number of cultural historical and ecological predictors, respectively.We show here that this correction is not necessary, and neither does it change th results. The model selection approach shields our results from the effect of predictor class size. Predictors that represent stochastic noise will have betas with large standard error relative to their effect size. Such predictors are unlikely to be included in the best model, as the Akaike information criterion (AIC) penalizes models for the number of predictors they contain. As a result, the absolute value of a b coefficient in the best model is a good measure of the true absolute magnitude of the effect of that predictor, even if it does not incorporate explicitly the standard error of the b estimate.However, explicitly incorporating the standard error of the b estimates, as Towner et al. suggest, is a valid alternative to the approach we used. But Towner et al.'s correction is incomplete, because it is only applicable to the worst-case scenario where the predictors represent stochastic noise. Just as the expectation of the absolute beta of a predictor representing stochastic noise is shifted from zero to ð2s 2 =pÞ 1=2 ; the expectation of the absolute effect of a predictor with mean b and standard deviation s iss ffiffiffiffiffiffi 2p p e ððxÀbÞ 2 =2s 2 Þ :Thus, the absolute effect of a predictor, b 0 , is the difference between E(jbj) and the null expectations ffiffiffiffiffiffi 2p p e ÀððxÀbÞ 2 =2s 2 Þ À 2s 2 p 1=2

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supporting

confidence: 61%

Cultural history, not ecological environment, is the main determinant of human behaviour

Mathew

Perreault

2016

Proc. R. Soc. B.

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“…For example, if we assume a priori that for about half of the cultural traits coded in the WNAI one of the variants has been under positive selection, the simulations suggest that we would misclassify about 30% of all traits (50% of the one half of the traits under selection not identified and 10% of the other half of the traits not under selection). [42,83]. In our simulations, the strong effects of horizontal transmission on false inferences about selection may reflect the fact that in this particular sample linguistic and spatial signals are relatively uncorrelated [21].…”

Section: Findings From Our Simulations Of Cultural Macroevolution On mentioning

confidence: 99%

The Potential to Infer the Historical Pattern of Cultural Macroevolution

Lukas¹,

Towner²,

Mulder³

2020

Preprint

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Phylogenetic analyses increasingly take centre-stage in our understanding of the processes shaping patterns of cultural diversity, and cultural evolution over time. Just as biologists explain the origins and maintenance of trait differences among organisms using phylogenetic methods, so anthropologists studying cultural macroevolutionary processes use phylogenetic methods to uncover the history of human populations and the dynamics of culturally transmitted traits. In this paper we revisit concerns with the validity of these methods. Specifically, we use simulations to reveal how properties of the sample (size, missing data), properties of the tree (tree shape), and properties of the traits (rate of change, number of variants, horizontal transmission) might influence the inferences that can be drawn about trait distributions across a given phylogeny, and the power to discern alternative histories. We demonstrate this approach using Western North American Indian dataset societies and show a high rate of Type I and Type II errors contingent on properties of the traits, of the tree shape, and less so of the sample size. While some results may be particular to our simulations, we offer these tools to address some persistent perils in existing cultural macroevolutionary research, and chart outstanding challenges to future work.

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“…Another study of North American toolkit variation found technological richness to be negatively correlated with mean rainfall for driest month, species richness, and aboveground productivity, thereby pointing toward environmental risk as a driver of innovation (Collard et al 2013). Similarly, Mathew and Perrault (2015) found ecology to be a stronger predictor of material culture than cultural phylogeny (although see Towner et al [2016] for a critique of this analysis). Analysis of more contemporary populations shows the same; variation in sea craft design in the Pacific has been found to correlate both to local island environments and to the cultural histories of the people who settled there (Beheim and Bell 2011).…”

Section: Introductionmentioning

confidence: 99%

From Mind to Matter: Patterns of Innovation in the Archaeological Record and the Ecology of Social Learning

Demps,

Herzog,

Clark

2023

Am. Antiq.

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Archaeology and cultural evolution theory both predict that environmental variation and population size drive the likelihood of inventions (via individual learning) and their conversion to population-wide innovations (via social uptake). We use the case study of the adoption of the bow and arrow in the Great Basin to infer how patterns of cultural variation, invention, and innovation affect investment in new technologies over time and the conditions under which we could predict cultural innovation to occur. Using an agent-based simulation to investigate the conditions that manifest in the innovation of technology, we find the following: (1) increasing ecological variation results in a greater reliance on individual learning, even when this decreases average fitness due to the costs of learning; (2) decreasing population size increases variability in the types of learning strategies that individuals use; among smaller populations drift-like processes may contribute to randomization in interpopulation cultural diffusion; (3) increasing the mutation rate affects the variability in learning patterns at different rates of environmental variation; and (4) increasing selection pressure increases the reliance on social learning. We provide an open-source R script for the model and encourage others to use it to test additional hypotheses.

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Problems modelling behavioural variation across Western North American Indian societies

Cited by 5 publications

References 23 publications

Cultural history, not ecological environment, is the main determinant of human behaviour

Cultural history, not ecological environment, is the main determinant of human behaviour

The Potential to Infer the Historical Pattern of Cultural Macroevolution

From Mind to Matter: Patterns of Innovation in the Archaeological Record and the Ecology of Social Learning

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