Accelerator mass spectrometry radiocarbon (AMS 14C) dating was used for determining the age of wedge ice. It has been found that between 11,270 and 6420 cal BP, or the Greenlandian and Northgrippian stages of the Holocene, ice wedges grew syngenetically in sandy deposits with gravel in the Chara River valley. The variations of δ18O values in the ice wedges are about 8‰, from –25.5‰ to –18.8‰. Based on the stable isotope composition of ice wedges, paleotemperature reconstructions revealed that the mean January temperature was as low as –38°C during the coldest periods of the early half of the Holocene and as high as –28°C during the warmer periods.

Estimation of residence time of groundwater, particularly in regions with inadequate surface waters are very important for formulating sustainable groundwater management policies. We developed a technique for extracting dissolved inorganic carbon (DIC) quantitatively from water for measuring its 14C contents and presented the analytical details here. We also measured stable carbon isotope ratio (δ13C) in soil CO2 and groundwater DIC to correct the groundwater 14C ages. In addition, 14C in soil CO2 were measured for making necessary correction in the initial activity of the recharging water. The corrected 14C contents in the groundwater samples were used to estimate their residence times employing Lumped Parameter Models (LPM), a set of mathematical models to account for the processes that take place during transport from the recharge to the sampling spots. We present a case study focused on the calculation of radiocarbon ages and residence times for a groundwater sample collected from the campus of Physical Research Laboratory in Ahmedabad, Gujarat, India. The study also includes estimations of groundwater residence times using previously measured 14C ages of groundwater samples from Gujarat, India. Various factors controlling the groundwater ages in the LPM and their applicability are discussed.

There is a rich and diverse body of research dedicated to understanding the cultural and biological processes that led to plant domestication and the development of agriculture in both the Old and New Worlds. Work continues to refine and challenge proposed models for the process of plant domestication, the likely centres of origin and subsequent spread of plant crops and agricultural innovations. This research is taking place in the light of new archaeobotanical evidence and the development and application of novel scientific techniques. As such, publications that bring together new lines of research and evidence, and how these inform our current understanding of plant domestication and agriculture, are an important resource for both specialist and non-specialist audiences.

The intensity of changes in the population dynamics of the Early Neolithic (ca. 6250–5300 cal BC) communities in the Central Balkans was addressed by estimating the growth rate values. The Bayesian approach (Crema and Shoda 2021) of estimating intrinsic growth rates by fitting different models of population growth was applied to radiocarbon dates from the Early Neolithic sites in Serbia. We explored two possible episodes of population growth based on the results of the population dynamics reconstruction using the summed calibrated radiocarbon probability distributions (SPD) method. The results have shown that, within the first episode of growth, the intrinsic growth rate mean values are higher than the estimated continental average (between 1% and 2%). The results indicate a sudden and fast rise in population size, possibly due to the influx of the new population settling in the region at the beginning of the Neolithic. Lower values for the second episode could indicate more gradual population growth due to the mechanisms associated with the Neolithic Demographic Transition and the rise in fertility.

Inequality is present in all human societies, but building a robust understanding of how that inequality developed and persisted for centuries requires historical and archaeological data. Identifying the degree of inequality (or disparity) in ancient communities can be addressed through a variety of methods. One method becoming standard practice in archaeology evaluates inequality through quantitative analysis of robust settlement data. In this Compact Special Section, we assess household size as a potential reflection of wealth inequality among Classic period (a.d. 250–900) Maya settlements. First, we generate house-size data from both pedestrian and remotely sensed LiDAR surveys. Then we use those data to calculate Gini coefficients and Lorenz curves, which provide measures of variation. Gini coefficients range from 0 to 1, where 0 reflects perfect equality and 1 indicates perfect inequality, regardless of the actual values in the distribution. Both area (m2) and volume (m3) provide different, complementary metrics to investigate residential size as a metric for wealth inequality among Classic Maya Lowland settlements. Proposed mechanisms that generate inequality include the intergenerational transmission of wealth and differential access to resources; however, addressing these and other pathways for how inequality develops and persists, and how it was maintained in the past provides insight into similar processes of systemic inequality worldwide.

Gini coefficients for residential groups at Coba for roofed surface area, volume of architecture, and houselot space range from 0.423 to 0.551, fitting well within the range of many ancient and modern state-level cities and societies and other Mesoamerican centers. These values are also similar to other large, Classic period, Northern Lowland cities, such as Dzibilchaltun and Chunchucmil. These data do not support the idea that autocratic regimes exhibit greater wealth inequality. We also failed to find a pattern in which inequality grew over the course of the Classic period. The Lorenz curves for Coba and other sites do not indicate any breaks that would allow households to be sorted into wealth classes. Thus, wealth differences were fluid, continuous, and out in the open, giving these settlements the dynamism and attractiveness that helped them grow into some of the largest and most remarkable ancient Maya cities.

The Classic Maya polities of Baking Pot and Lower Dover developed along two dramatically different trajectories. At Baking Pot, the capital and associated apical elite regime grew concomitantly with surrounding populations over a thousand-year period. The smaller polity of Lower Dover, in contrast, formed when a Late Classic political center was established by an emergent apical elite regime amidst several long-established intermediate elite-headed districts. The different trajectories through which these polities formed should have clear implications for residential size variability. We employ the Gini coefficient to measure variability in household volume to compare patterns of residential size differentiation between the two polities. The Gini coefficients, while similar, suggest greater differentiation in residential size at Baking Pot than at Lower Dover, likely related to the centralized control of labor by the ruling elite at Baking Pot. While the Gini coefficient is synonymous with measuring wealth inequalities, we suggest that in the Classic period Belize River Valley, residential size was more reflective of labor control.

Located at the western edge of the Classic Maya heartland, El Peru-Waka' was one of the most densely aggregated urban cores in the Lowlands. With households packed next to each other, it can be difficult to define where one ends and another begins. Nevertheless, survey and excavation data suggest that differences in household provisioning and generational cycling created considerable variation in household wealth across the city. This paper employs household area (m2) and volume (m3) to calculate Gini coefficients for the El Peru-Waka' urban core and immediate hinterlands to quantify household differentiation across the urban landscape. Comparison of the coefficients for the total study area with those for individual urban zones (core, periurban, hinterland) demonstrate that while El Perú-Waka' exhibits high overall household differentiation, this differentiation is considerably muted within a given urban zone. This demonstrates the impact of settlement location on differences in household size and architectural investment.

House size provides a comparative measure of household wealth that enables archaeologists to track global trends in inequality across a range of sedentary societies. Such approaches hold particular promise for Maya archaeology given its long history of settlement pattern research and recent applications of LiDAR to map large areas surrounding ancient Maya cities. Estimating dwelling size, however, is not a trivial exercise. This article addresses potential confounds associated with geometric-based estimates (volume and area) and compares traditional house size-based measures of wealth with other estimates of house size and quality of life indicators. Settlement pattern data from the Upper Usumacinta Confluence Zone, recently collected by the Proyecto Arqueológico Altar de Sacrificios, combined with previously published excavation data provide a robust dataset to evaluate alternative measures of wealth beyond house size.

Survey teams at the El Pilar Archaeological Reserve for Maya Flora and Fauna have mapped 70 percent of its 20 km2 area and revealed the extent of settlement around the city center. Large-scale civic architecture, and the distribution of smaller ceremonial groups and minor centers, reflect the wealth and power of Maya rulers presiding over the largest Classic period city in the upper Belize River area. Previous analyses suggest disparities in wealth at El Pilar were more nuanced than the elite/commoner dichotomy commonly invoked for Classic Maya society. This article works to understand wealth inequality at ancient El Pilar by computing Gini coefficients from areal and volumetric calculations of primary residential units—the class of settlement remains most likely to represent ancient households. Presentation of Gini coefficients and their potential interpretations follows a discussion of settlement classification and residential group labor investment. We conclude by contextualizing these results within prior settlement pattern analyses to explore how disparities in wealth may have been distributed across the physical and social landscape.