Demography and the Palaeolithic Archaeological Record

Abstract

Demographic change has recently re-emerged as a key explanation for socio-cultural changes documented in the prehistoric archaeological record. While the majority of studies of Pleistocene demography have been conducted by geneticists, the archaeological records of the Palaeolithic should not be ignored as a source of data on past population trends. This paper forms both a comprehensive synthesis and the first critical review of current archaeological research into Palaeolithic demography. Within prevailing archaeological frameworks of dual inheritance theory and human behavioural ecology, I review the ways in which demographic change has been used as an explanatory concept within Palaeolithic archaeology. I identify and discuss three main research areas which have benefitted from a demographic approach to socio-cultural change; 1) technological stasis in the Lower Palaeolithic; 2) the Neanderthal-Homo sapiens transition in Europe, and; 3) the emergence of behavioural modernity. I then address the ways in which palaeodemographic methods have been applied to Palaeolithic data-sets, considering both general methodological concerns and the challenges specific to this time period. Finally, I discuss the ability of ethnographic analogy to aid research into Palaeolithic demography.

Dogs And Mankind: Coevolution on the Move – An Update

“…As for the density estimates, however, a few more words of caution must be inserted here: the remarkable feat (Mazet et al, 2016) of the Li and Durbin landmark study in 2011 (Li & Durbin, 2011), rests on several assumptions that may be questionable, especially in the case of Pleistocene populations of humans at extremely low densities: panmixia, or the spread in a two-dimensional diffusion process, and a comparison of data sets obtained with different methods under varying assumptions from very different populations, even from different species (e.g., Lorenzen et al, 2011). However, the extremely small human population size estimates for Pleistocene Eurasia, as calculated by the "genetic" Ne, and here used as substitute for Nc -the census population size -are well supported by recent estimates based on the archeological evidence from Pleistocene camp sites in Europe (French, 2015;French & Collins, 2015;Maier et al, 2016). The human population, in sharp contrast, numbering all over Eurasia only a few thousand individuals, narrowly had escaped extinction during the Pleistocene bottleneck, remained on a level of ecological insignificance for thousands of years, and started its rise only after the LGM to become the ultimate keystone species and "natural catastrophe" (Schaller, 1991).…”

The empirical case against the ‘demographic turn’ in Palaeolithic archaeology

“…These studies have been repeatedly cited by Palaeolithic archaeologists as evidence that population size affects cultural change [8,16]. In this section, we will show that this is not correct.…”

A demographic perspective on the Middle to Later Stone Age transition from Nasera rockshelter, Tanzania

“…Inferences of Palaeolithic demography from archaeological proxies usually rely on changes in (i) the number of sites in a region for a given time interval, (ii) artefact accumulation rates, (iii) site size or (iv) diet, particularly increased dietary breadth, the inclusion of lower ranked resources, intensified predation pressure and prey extirpation [36]. For East Africa, Blome et al [35] report increases in site frequency beginning approximately 90 ka, but temporally and spatially limited excavations and the rarity of preserved or reported fauna currently severely limit use of analyses of site size or changes in dietary breadth [3,35].…”

“…the density and predictability of key resources), and the proximity and number of other human groups, as a more densely packed landscape reduces mobility options [41]. While an individual forager or group may shift residential mobility seasonally or over longer time periods [41], data from recent and historic foragers [36,37,[41][42][43][44][45][46] suggest that residential mobility is inversely correlated with net primary productivity and the abundance and predictability of key resources. When resources are abundant and predictable, there is little need for a group to incur the energetic costs of high residential mobility, but when sparse, the costs of mobility are outweighed by the increase in returns gained from exploiting the broader landscape.…”