Human cooperation is highly unusual. We live in large groups composed mostly of non-relatives. Evolutionists have proposed a number of explanations for this pattern, including cultural group selection and extensions of more general processes such as reciprocity, kin selection, and multi-level selection acting on genes. Evolutionary processes are consilient; they affect several different empirical domains, such as patterns of behavior and the proximal drivers of that behavior. In this target article, we sketch the evidence from five domains that bear on the explanatory adequacy of cultural group selection and competing hypotheses to explain human cooperation. Does cultural transmission constitute an inheritance system that can evolve in a Darwinian fashion? Are the norms that underpin institutions among the cultural traits so transmitted? Do we observe sufficient variation at the level of groups of considerable size for group selection to be a plausible process? Do human groups compete, and do success and failure in competition depend upon cultural variation? Do we observe adaptations for cooperation in humans that most plausibly arose by cultural group selection? If the answer to one of these questions is "no," then we must look to other hypotheses. We present evidence, including quantitative evidence, that the answer to all of the questions is "yes" and argue that we must take the cultural group selection hypothesis seriously. If culturally transmitted systems of rules (institutions) that limit individual deviance organize cooperation in human societies, then it is not clear that any extant alternative to cultural group selection can be a complete explanation.Keywords: competition; culture; evolution; group selection; heritable variation; institutions; norms BEHAVIORAL AND BRAIN SCIENCES (2016) KARL FROST is a Ph.D. candidate in Ecology at the University of California, Davis. He researches the cultural evolution of prosociality via religion and ritual practices, using behavioral experiments, gene-culture coevolution models, and field research in Canada looking at environmental activism in the face of the tar sands oil industry and an antagonistic government. He also directs the Body Research Physical Theater and is interested in cross-cultural exchange of theater practice as theater anthropology and arts-science fusion.

A common belief among human life history researchers is that “harsher” environments - i.e., those with higher mortality rates and resource stress - select for “fast” life histories, i.e. earlier reproduction and faster senescence. I show that these “harsh environments, fast life histories” - or HEFLH - hypotheses are poorly supported by evolutionary theory. First, I use a simple model to show that effects of environmental harshness on life history evolution are incredibly diverse. In particular, small changes in basic but poorly understood variables - e.g., whether and how population density affects vital rates - can cause selection to favor very different life histories. Furthermore, I show that almost all life history theory used to justify HEFLH hypotheses is misapplied in the first place. The reason is that HEFLH hypotheses usually treat plastic responses to heterogeneous environmental conditions within a population, whereas the theory used to justify such hypotheses treat genetic responses to environmental changes across an entire population. Counter-intuitively, the predictions of the former do not generally apply to the latter: the optimal response to a harsh environment within a large heterogeneous environment is not necessarily the optimal strategy of a population uniformly inhabiting the same harsh environment. I discuss these theoretical results in light of the current state of empirical research.

The main objective of our target article was to sketch the empirical case for the importance of selection at the level of groups on cultural variation. Such variation is massive in humans, but modest or absent in other species. Group selection processes acting on this variation is a framework for developing explanations of the unusual level of cooperation between non-relatives found in our species. Our case for cultural group selection (CGS) followed Darwin's classic syllogism regarding natural selection: If variation exists at the level of groups, if this variation is heritable, and if it plays a role in the success or failure of competing groups, then selection will operate at the level of groups. We outlined the relevant domains where such evidence can be sought and characterized the main conclusions of work in those domains. Most commentators agree that CGS plays some role in human evolution, although some were considerably more skeptical. Some contributed additional empirical cases. Some raised issues of the scope of CGS explanations versus competing ones.

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Previous models of cultural evolution found that larger populations can better maintain complex technologies because they contain more highly skilled people whom others can imitate. These models, however, do not distinguish the effects of population size from population density or network size; a learner’s social network includes the entire population. Does population size remain important when populations are subdivided and networks are realistically small? I use a mathematical model to show that population size has little effect on equilibrium levels of mean skill under a wide range of conditions. The effects of network size and transmission error rate usually overshadow that of population size. Population size can, however, affect the rate at which a population approaches equilibrium, by increasing the rate at which innovations arise. This effect is small unless innovation is very rare. Population size should predict technological complexity in the real world, then, only if technological evolution is a slow, innovation-limited process. Population density and “connectedness” have similar affects to population size, though density can also affect equilibrium skill. I discuss the results of this analysis in light of the current empirical debate.

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Henrich (2004) argued that larger populations can better maintain complex technologies because they contain more highly skilled people whom others can imitate. His original model, however, did not distinguish the effects of population size from population density or network size; a learner’s social network included the entire population. Does population size remain important when populations are subdivided and networks are realistically small? I use a mathematical model to show that population size has little effect on equilibrium levels of mean skill under a wide range of conditions. The effects of network size and transmission error rate usually overshadow that of population size. Population size can, however, affect the rate at which a population approaches equilibrium, by increasing the rate at which innovations arise. This effect is small unless innovation is very rare. Whether population size predicts technological complexity in the real world, then, depends on whether technological evolution is innovation-limited and short of equilibrium. The effect of population “connectedness,” via migration or trade, is similar. I discuss the results of this analysis in light of the current empirical debate.

Explaining the evolution of human life history traits remains an important challenge for evolutionary anthropologists. Progress is hindered by a poor appreciation of how demographic factors affect the action of natural selection. I review life history theory showing that the quantity maximized by selection depends on whether and how population growth is regulated. I show that the common use of R, a strategy’s expected lifetime number of offspring, as a fitness maximand is only appropriate under a strict set of conditions, which are apparently unappreciated by anthropologists. To concretely show how demography-free life history theory can lead to errors, I reanalyze an influential model of human life history evolution, which investigated the coevolution of a long lifespan and late age of maturity. I show that the model’s conclusions do not hold under simple changes to the implicitly assumed mechanism of density dependence, even when stated assumptions remain unchanged. This analysis suggests that progress in human life history theory requires better understanding of the demography of our ancestors.