One of the major benefits of interdisciplinary research is the chance to swap tools between fields, to save having to reinvent the wheel. The fields of language evolution and evolutionary biology have been swapping tools for centuries to the enrichment of both. Here I will discuss three categories of tool swapping: conceptual tools, where analogies are drawn between hypotheses, patterns or processes, so that one field can take advantage of the path cut through the intellectual jungle by the other; theoretical (...) tools, where the machinery developed to process the data in one field is adapted to be applied to the data of the other; and analytical tools, where common problems encountered in both fields can be solved using useful tricks developed by one or the other. I will argue that conceptual tools borrowed from linguistics contributed to the Darwinian revolution in biology; that theoretical tools of evolutionary change can in some cases be applied to both genetic and linguistic data without having to assume the underlying evolutionary processes are exactly the same; and that there are practical problems that have long been recognised in historical linguistics that may be solved by borrowing some useful analytical tools from evolutionary biology. (shrink)

Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the (...) latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution.Editor's suggested further reading in BioEssaysLinguistic evidence supports date for Homeric epics Abstract. (shrink)

Demography plays a large role in cultural evolution through its effects on the effective rate of innovation. If we assume that useful inventions are rare, then small isolated societies will have low rates of invention. In small populations, complex technology will tend to be lost as a result of random loss or incomplete transmission (the Tasmanian effect). Large populations have more inventors and are more resistant to loss by chance. If human populations can grow freely, then a population-technology-population positive feedback (...) should occur such that human societies reach a stable growth path on which the rate of growth of technology is limited by the rate of invention. This scenario fits the Holocene to a first approximation, but the late Pleistocene is a great puzzle. Large-brained hominins existed in Africa and west Eurasia for perhaps 50,000 years with, at best, slow rates of technical innovation. The most sophisticated societies of the last glacial period appear after 50,000 years ago and were apparently restricted to west and north-central Eurasia and North Africa. These patterns have no simple, commonly accepted explanation. We argue that increased high-frequency climate change around 70,000–50,000 years ago may have tipped the balance between humans and their competitor-predators, such as lions and wolves, in favor of humans. At the same time, technically sophisticated hunters would tend to overharvest their prey. Perhaps the ephemeral appearance of complex tools and symbolic artifacts in Africa after 00,000 years ago resulted from hunting inventions that allowed human populations to expand temporarily before prey overexploitation led to human population and technology collapse. Sustained human populations of moderate size using distinctively advanced Upper Paleolithic artifacts may have existed in west Eurasia because cold, continental northeastern Eurasia–Beringia acted as a protected reserve for prey populations. (shrink)

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. (shrink)

Much human adaptation depends on the gradual accumulation of culturally transmitted knowledge and technology. Recent models of this process predict that large, well-connected populations will have more diverse and complex tool kits than small, isolated populations. While several examples of the loss of technology in small populations are consistent with this prediction, it found no support in two systematic quantitative tests. Both studies were based on data from continental populations in which contact rates were not available, and therefore these studies (...) do not provide a test of the models. Here, we show that in Oceania, around the time of early European contact, islands with small populations had less complicated marine foraging technology. This finding suggests that explanations of existing cultural variation based on optimality models alone are incomplete because demography plays an important role in generating cumulative cultural adaptation. It also indicates that hominin populations with similar cognitive abilities may leave very different archaeological records, a conclusion that has important implications for our understanding of the origin of anatomically modern humans and their evolved psychology. (shrink)