Māori Population Growth in Pre-contact New Zealand: Regional Population Dynamics Inferred From Summed Probability Distributions of Radiocarbon Dates

Abstract

Past population dynamics play a key role in integrated models of socio-cultural change in Polynesia. A key aspect of these models is the interplay between food production and population growth. Located on the margins of Polynesia, New Zealand presented considerable challenges to traditional Polynesian food production, many crops were not successfully established and those that were produced greatly reduced yields. However, despite the hurdles to food production and the likely influence on population, little empirical analysis of M aori population has been carried out in New Zealand. Here, we use summed probability distributions of radiocarbon dates (SPDRD) to show clear regional and local variation population dynamics. Specifically, we find population in the optimal horticultural zone follows a logistic pattern of growth, while in the sub-optimal zone both a modified logistic curve, representing slower growth than the north, or a "stepped" pattern are supported. In the non-horticultural south our results concur with previous studies that suggest population rapidly grew and then declined as faunal resources diminished. Finally, our analysis of local-scale growth showed considerable heterogeneity within the horticultural zone and homogeneity in the southern hunting region. This suggests that

Late Glacial and Early Holocene human demographic responses to climatic and environmental change in Atlantic Iberia

“…We consider this approach is more robust against the calibration artefacts ‘false positives’ compared to methods that use a rolled mean SPD, e.g. [ 15 , 16 ]. Kernel density estimate (KDE) models for the data were calculated using the method of McLaughlin [ 17 ], also using one date per site phase, and this method was further developed to allow the calculation of dynamic models of the mean annualized growth rate.…”

“…Kernel density estimate (KDE) models for the data were calculated using the method of McLaughlin [ 17 ], also using one date per site phase, and this method was further developed to allow the calculation of dynamic models of the mean annualized growth rate. Unlike approaches that find the average geometric growth between fixed points in the SPD, such as century-wide ‘bins’ [ 16 ], we derived a fully continuous reading of growth from the radiocarbon data. This was done by numerically differentiating the bootstrapped KDE and expressing it as a time series with a defined confidence envelope.…”

Did pre-Columbian populations of the Amazonian biome reach carrying capacity during the Late Holocene?

“…subsistence type, a given archaeological ceramic style) create spatial groupings that are relevant to specific time slices but potentially entirely irrelevant to prior or later time slices and, hence, to overall palaeodemographic processes at regional scale. To circumvent the need to manually partition RAmazon, we employed spatial permutation testing (Figure 2b, Figure SM.1) under a null assumption of homogeneous growth [38,39]. We proceeded by shuffling date locations in the place of bins.…”

Sedimentary unknowns constrain the current use of frequency analysis of radiocarbon data sets in forming regional models of demographic change

“…A. Brown & Crema, 2019; Crema & Kobayashi, 2020; Hosner et al, 2016; Wright et al, 2020). Indeed, the number of published archaeological studies using SPD analysis of large radiocarbon data sets has increased significantly in the last 15 years (Figure 1; see also data in Carleton & Groucutt, 2019).…”

“…A. Brown & Crema, 2019; Crombe & Robinson, 2014; A. Goldberg et al, 2016; Riris & Arroyo‐Kalin, 2019; Zahid et al, 2016), or (ii) to undertake a correlative study with other archaeological parameters to support the use of SPD analyses (e.g., French & Collins, 2015; Palmisano et al, 2017). What can be missing are the questions that set out to understand and explain the human or natural drivers for change in the archaeological record.…”