Despite decades of research, the roles of climate and humans in driving the dramatic extinctions of large-bodied mammals during the Late Quaternary remain contentious. We use ancient DNA, species distribution models and the human fossil record to elucidate how climate and humans shaped the demographic history of woolly rhinoceros, woolly mammoth, wild horse, reindeer, bison and musk ox. We show that climate has been a major driver of population change over the past 50,000 years. However, each species responds differently to the effects of climatic shifts, habitat redistribution and human encroachment. Although climate change alone can explain the extinction of some species, such as Eurasian musk ox and woolly rhinoceros, a combination of climatic and anthropogenic effects appears to be responsible for the extinction of others, including Eurasian steppe bison and wild horse. We find no genetic signature or any distinctive range dynamics distinguishing extinct from surviving species, underscoring the challenges associated with predicting future responses of extant mammals to climate and human-mediated habitat change.

Despite a deep Great Basin tradition of incorporating paleoenvironmental change within ecologically oriented analyses of past human lifeways, there has been little attention focused on Holocene variation in artiodactyl abundances and the human hunting strategies dependent upon them. Here, we draw upon recently generated paleontological evidence from Homestead Cave of the Bonneville Basin to document a late Holocene artiodactyl population increase. We then use the prey model of foraging theory to predict late Holocene increases in the hunting of artiodactyls, relative to lagomorphs. That prediction is then tested against several fine-grained archaeological records of hunting behavior in the Bonneville Basin, Hogup Cave and Camels Back Cave, and a variety of more coarse-grained faunal records from throughout the Great Basin. Close fits are found between the deductively derived prediction and the empirical records of hunting behavior: dramatic proportional increases in artiodactyl hunting occurred during the late Holocene. The results have far-reaching implications for our understanding of prehistoric human adaptations in the Great Basin.

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The use of body size as an index of prey rank in zooarchaeology has fostered a widely applied approach to understanding variability in foraging efficiency. This approach has, however, been critiqued—most recently by the suggestion that large prey have high probabilities of failed pursuits. Here, we clarify the logic and history of using body size as a measure of prey rank and summarize empirical data on the body size-return rate relationship. With few exceptions, these data document strong positive relationships between prey size and return rate. We then illustrate, with studies from the Great Basin, the utility of body size-based abundance indices (e.g., the Artiodactyl Index) when used as one component of multidimensional analyses of prehistoric diet breadth. We use foraging theory to derive predictions about Holocene variability in diet breadth and test those predictions using the Artiodactyl Index and over a dozen other archaeological indices. The results indicate close fits between the predictions and the data and thus support the use of body size-based abundance indices as measures of foraging efficiency. These conclusions have implications for reconstructions of Holocene trends in large game hunting in western North America and for zooarchaeological applications of foraging theory in general.

A simple model of political popularity, as recorded by opinion polls of voting intentions, is proposed. We show that, as a consequence of aggregating heterogeneous poll responses under certain assumptions about the evolution of individual opinions, the time series of poll data should exhibit long memory characteristics. In an analysis of the monthly Gallup data on party support in the UK, we con®rm that the series have long memory and further show them to be virtually pure`fractional noise' processes. An explanation of the latter result is offered. We study the role of economic indicators in predicting swings in support, perform event analyses and use our estimates to generate post-sample forecasts to April 1997.