Demographic Studies in Southwestern Prehistory

Abstract

In this Essay, I will focus on inferences about the size of prehistoric populations based on estimates of the quantity of space utilized by those populations. I wish to recognize at the outset that there are many other data bases that have been employed by archaeologists in making inferences about prehistoric demography. While I do not intend to question the validity of alternative data bases for making paleo-demographic inferences, there are reasons why I believe that utilized space is potentially our most significant data base. Let us consider some of the alternatives. (1) Simulation models. Simulation models are powerful tools for gaining insight into the demography of prehistoric populations. Yet, if the implications of such models are to be tested, a means of making direct inferences about the population of prehistoric groups is needed.(2) Burial populations. Burial populations are likely to remain the data base from which the most comprehensive demographic inferences can be made. However, there are many areas of the world in which burial populations are so rare that one cannot count on using this data base. In addition, Cook (1972) and Baker and Sanders (1973) have identified a number of significant limitations on the utility of burial data.

Demography and the Palaeolithic Archaeological Record

“…with certain classes of material culture. This problem of (lack of) chronological precision is one of the primary obstacles within palaeodemography, and means that any demographic data generated is difficult to reconcile with both DIT and HBE frameworks (for attempts to overcome the contemporaneity problem see; Ammerman et al 1976;Grove 2012;Hill 1970;Plog 1975;Schacht 1981).…”

Prehistoric Demography in the Southwest: Migration, Coalescence, and Hohokam Population Decline

“…Using these data we estimate population throughout the Southwest for each 50-year interval. Estimating population from archaeological data is a notoriously difficult task involving numerous assumptions (Abbott and Foster 2003;Kintigh 1985;Nelson et al 1994;Plog 1975;Schacht 1981). While we endeavor to arrive at the most reasonable estimates possible with the information Kayenta/Tusayan Region available, it is important to note that our arguments are not as dependent on a high level of accuracy in determining momentary population as they are on identifying macro-regional demographic trends (e.g., Dean et al 1994;Duff 1998).…”

“…Thus, this percentage probably varied depending on site size and length of occupation. Kintigh (1985:22), citing a range of 50 percent to 80 percent, suggests occupancy rates of 65 percent for sites in the Zuni region, while Plog (1975) uses a figure of 59 percent in the Chevelon and Hay Hollow areas, and Nelson et al (1994) report 75 percent for the Dolores area. While population has typically been estimated using different approaches in the Hohokam region, this range of occupation percentages is consistent with opinion in that area (e.g., Wilcox 1991).…”

Growth and Aggregation at Canyon Creek Ruin: Implications for Evolutionary Change in East-Central Arizona

“…Eighmy 1979) or functionally variable room building (cf. Plog 1975;Schact 1980). Furthermore, households were not simply established through population growth (an implication often derived from logistic models), but more likely through a combination of immigration and natural growth.…”