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The archaeological assemblage recovered from the Middle Stone Age (MSA) levels in Blombos Cave, South Africa, is central to our understanding of the development of early modern humans. Here, we demonstrate that the cultural and technological innovations inferred from the Blombos Cave MSA record also correlate with significant shifts in site use and occupational intensity. Through a comprehensive geoarchaeological investigation of three MSA occupation phases, we identified distinct diachronic trends in the frequency of visits and the modes of occupation. During the earliest phases (ca. 88–82 ka), humans inhabited the cave for more extended periods, but cave visits were not frequent. During the later phases (ca. 77–72 ka), the cave was more regularly visited but for shorter periods each time. We argue that these changes in local occupational intensity, which also coincide with shifts in vegetation, sea levels, and subsistence, can best be explained by broader changes in hunter-gatherer mobility strategies and occupation patterns. Fundamental changes in regional settlement dynamics during Marine Oxygen Isotope Stages 5b-4 would have significantly affected the nature and frequency of social interaction within and between prehistoric populations living in the southern Cape, a scenario that ultimately may explain some of the social and technological advances that occurred there during this time frame.
Life in the terrestrial and marine subsurface has adapted and evolved mechanisms to survive under extremes of energy limitation, temperature, pressure, radiation, and/or water availability. New developments in nucleic acid sequencing, high-pressure biochemistry, and high-pressure biophysics have expanded our understanding of the mechanisms used by deep life. This chapter synthesizes these new developments and highlights remaining gaps in understanding.
All scientific disciplines prize predictive success. Conventional statistical analyses, however, treat prediction as secondary, instead focusing on modeling and hence estimation, testing, and detailed physical interpretation, tackling these tasks before the predictive adequacy of a model is established. This book outlines a fully predictive approach to statistical problems based on studying predictors; the approach does not require predictors correspond to a model although this important special case is included in the general approach. Throughout, the point is to examine predictive performance before considering conventional inference. These ideas are traced through five traditional subfields of statistics, helping readers to refocus and adopt a directly predictive outlook. The book also considers prediction via contemporary 'black box' techniques and emerging data types and methodologies where conventional modeling is so difficult that good prediction is the main criterion available for evaluating the performance of a statistical method. Well-documented open-source R code in a Github repository allows readers to replicate examples and apply techniques to other investigations.