In April 2009, a lidar survey flown by the National Center for Airborne Laser Mapping recorded 200 square kilometers of terrain that comprised the Classic Period Maya city of Caracol, Belize. The data revealed a highly manipulated landscape of dense settlement, agricultural terraces, and residential reservoirs. Literature on Maya agriculture has discussed the benefits of terraces in controlling soil erosion, retaining water, and managing the gravitational flow of water; however, until now these benefits have not been quantified or demonstrated on the ground at scale. This research utilizes these lidar data and data derivatives in order to test the degree to which the ancient Maya manipulated their environment and were able to support large-scale populations through their landscape management practices. As such, the research provides evidence supporting the significance of agricultural terraces and their impact on limiting soil erosion, increasing water retention, and permitting flow control over rainfall runoff. This research also highlights the conscious effort by the ancient Maya to manage the hydrology of their terraced landscape.

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization.

The Classic Period Maya (300CEto 900CE) built many of their cities away from standing, flowing, or subterranean water resources. Because of this, scholars have suggested that one key manifestation of ancient Maya ritual and political authority was the control and management of water housed in large central‐site reservoirs, rectilinear excavated features that were lined with stone and coated with plaster or clay to catch and store rainfall runoff. This research assesses those arguments by using remote sensing data to map residential reservoirs—smaller versions of the monumental reservoirs in city centers—from the intensively investigated city of Caracol, Belize. The Caracol Maya were entirely dependent on rainfall and built monumental and residential reservoirs throughout their city. Using a 200‐square kilometer Digital Elevation Model created fromLiDAR(Light Detection and Ranging) data, research uncovered the extent of ancient water capture at Caracol. Analysis of theLiDARdata reveals a conservative count of 1590 reservoirs at Caracol; this is more than 25 times the number of reservoirs identified by traditional ground survey methods. These data demonstrate how the people of Caracol were able to successfully harness the water available in their environment. In addition, the decentralized nature of Caracol's reservoirs suggests that elite power, at least in this ancient city, was not based on control of water resources due to the ubiquity of residential reservoirs throughout the site.WIREs Water2016, 3:885–897. doi: 10.1002/wat2.1171This article is categorized under: Engineering Water > Planning Water Science of Water > Water and Environmental Change Human Water > Water Governance

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.