The past and future of growth rate estimation in demographic temporal frequency analysis: Biodemographic interpretability and the ascendance of dynamic growth models

Abstract

Population growth rate estimators have recently emerged in demographic temporal frequency analysis (dTFA) as further tools to monitor pre-census population dynamics. The information that such estimators supply affords considerable heuristic potential for population-ecological research both because they implicate the environmental, behavioral, and physiological mechanisms that condition population growth, and because they impose much-needed empirical constraints on our efforts to build theory addressing long-run human population dynamics. However, the earnestness with which these estimators have been applied warrants caution. First, several nonidentical measures of population growth are current in both formal demography and dTFA, creating an opportunity for their equivocation. Second, our ability to insightfully interrogate growth estimates for population-ecological information has been checked by a tendency to interpret them in the framework of off-the-shelf parametric growth models ill-suited to long-run population dynamics. This paper evaluates the biodemographic merit of three estimators recently applied in dTFA. It also advocates a transition away from parametric and toward dynamic growth models and introduces an inductive, regression-based approach to the latter. A Monte Carlo simulation study indicates that this inductive approach can successfully recapture information about environmental influences on population growth from archaeological summed probability distributions, less so from kernel density estimates.

Culture Process and the Interpretation of Radiocarbon Data

“…We know from previous research that archaeologists must control for the effects of calibration, over sampling of single features or sites (sampling intensity), under certain circumstances, taphonomic processes, and even must be cognizant of the assumptions of different growth models before inferring population parameters from large 14 C time-series (Surovell et al 2009;Williams 2012;Contreras and Meadows 2014;Brown 2015Brown , 2017. Proper 14 C hygiene limits over-sampling induced bias, and recent research has shown that large sample sizes (1000+ assays) are more robust to the effects of preservation bias (Williams 2012).…”

“…Archaeologists increasingly use large samples of 14 C dates to estimate human population sizes, long-term population growth rates, and other demographic processes (e.g., Pettitt et al 2003;Shennan 2008;Peros et al 2010;Williams 2012Williams , 2013Kelly et al 2013;Shennan et al 2013;Contreras and Meadows 2014;Wang et al 2014;Crema et al 2016;Zahid et al 2016). Making inferences from these data sets about demography, however, is not without challenges (Williams 2012;Downey et al 2014;Attenbrow and Hiscock 2015;Brown 2015Brown , 2017. The issues stem from processes external and internal to prehistoric human populations.…”

Sparse Radiocarbon Data Confound Culture-Climate Links in Late Pre-Columbian Amazonia

“…The two patterns of land use that are advanced for pre-Columbian Amazonia by De Souza et al are contrasted by visually comparing SPDs derived from dates affiliated to "extensive" or "intensive" phases within six regions [1]. Before doing this, however, the paper takes the step of pre-filtering the 14 C dates (n = 337) as sequences of phases, to use the terminology of the OxCal calibration software [9].…”

“…phases within six regions [1]. Before doing this, however, the paper takes the step of pre-filtering the 14 C dates (n = 337) as sequences of phases, to use the terminology of the OxCal calibration software [9]. By modelling the phases as a continuous uniform distribution, this procedure tags certain dates as phase "outliers", ultimately reducing the sample by 11 dates (n = 326).…”

Analysis of Demographic Pressure on Nature

“…Various scientists put forward theories of demographic growth and thought about annually increasing demographic pressure [1][2][3][4][5]. Currently, this problem is becoming more urgent, since the growing demographic pressure can hamper the steady growth of the world economy.…”