Diachronic shifts in lithic technological transmission between the eastern Eurasian Steppe and northern China in the Late Pleistocene.

The successful occupation of the eastern Eurasian Steppe in the Late Pleistocene improved cultural connections between western Eurasia and East Asia. We document multiple waves of lithic technological transmission between the eastern Eurasian Steppe and northern China during 50-11 cal. ka BP. These waves are apparent in the sequential appearance of three techno-complexes in northern China: (1) the Mousterian techno-complex, (2) the blade techno-complex mixed with Mousterian elements, (3) and the microlithized blade techno-complex. These lithic techno-complexes were transmitted under different paleoenvironmental conditions along different pathways through the eastern Eurasian Steppe. The Mousterian techno-complex and the blade techno-complex mixed with Mousterian elements were only dispersed in the north and west peripheries of northern China (50-33 cal. ka BP). We argue that these techno-complexes failed to penetrate into the hinterland of northern China because they were not well suited to local geographical conditions. In contrast, the microlithized blade technology which diffused from the eastern Eurasian Steppe was locally modified into a Microblade techno-complex which was highly suited to local environmental conditions, and proliferated across the hinterland of northern China (28/27-11 cal. ka BP). The subsequent spread of microblade technology over vast regions of Mongolia and Siberia indicates that the Pleistocene inhabitants of northern China not only adopted and modified technologies from their neighbors in the Eurasian Steppe, but these modified variants were subsequently transmitted back into the Eurasian Steppe. These episodes of technological transmission indicate complicated patterns of population dispersal and technological interaction across northern China and the eastern Eurasian Steppe.

Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale.

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.