Clovis Blade Technology at the Topper Site (38AL23): Assessing Lithic Attribute Variation and Regional Patterns of Technological Organization

This monograph, by Douglas A. Sain, is based on his master’s thesis research on the organization of Clovis blade technology. This second monograph of the Occasional Papers series of the Southeastern Paleoamerican Survey closely follows the first in terms of the meticulousness of the study, and the new information it provides about the Topper Site. Detailed studies of Clovis material are eagerly sought by Paleoindian archaeologists, enthusiasts, and particularly by lithic analysts. Sain provides a well-rounded literature review for these groups, and an innovative approach to identifying technological blades. The “mixed assemblage” problem resulting when multiple lithic technologies were used at a single site is one with which lithic analysts continue to struggle. With a quarry site such as Topper and the wide variety of core forms and tools recovered, a nuanced and consistent approach to blade identification is a necessity if one wants to consider broader questions of technological organization. Recognizing variability in the end-product of blade manufacture and the relative importance of some characteristics over others, Sain weights six attributes from three to one and through detailed study of individual detached pieces produces a score. With a maximum value of 12, those with a score of seven or higher are considered a blade. This provides a consistent, replicable procedure for separating blades from blade-like flakes, and using these data in the consideration of Clovis lifeways. The small percentage of blades at Topper with modification, when coupled with a consideration of assemblages in the local and broader region, provide evidence that blades were part of a curated technology and toolkit, a transportable and reliable product that could be maintained as people moved across the landscape. This work provides a specific reconstruction of Clovis technological organization in the Savannah River Valley, and should inspire broader considerations of blade technology elsewhere in the Americas.https://scholarcommons.sc.edu/archanth_occasional_paleoam_papers/1001/thumbnail.jp

Climate Change, Coral Reef Ecosystems, and Management Options for Marine Protected Areas

Marine protected areas (MPAs) provide place-based management of marine ecosystems through various degrees and types of protective actions. Habitats such as coral reefs are especially susceptible to degradation resulting from climate change, as evidenced by mass bleaching events over the past two decades. Marine ecosystems are being altered by direct effects of climate change including ocean warming, ocean acidification, rising sea level, changing circulation patterns, increasing severity of storms, and changing freshwater influxes. As impacts of climate change strengthen they may exacerbate effects of existing stressors and require new or modified management approaches; MPA networks are generally accepted as an improvement over individual MPAs to address multiple threats to the marine environment. While MPA networks are considered a potentially effective management approach for conserving marine biodiversity, they should be established in conjunction with other management strategies, such as fisheries regulations and reductions of nutrients and other forms of land-based pollution. Information about interactions between climate change and more “traditional” stressors is limited. MPA managers are faced with high levels of uncertainty about likely outcomes of management actions because climate change impacts have strong interactions with existing stressors, such as land-based sources of pollution, overfishing and destructive fishing practices, invasive species, and diseases. Management options include ameliorating existing stressors, protecting potentially resilient areas, developing networks of MPAs, and integrating climate change into MPA planning, management, and evaluation

Population and Environmental Correlates of Maize Yields in Mesoamerica: a Test of Boserup’s Hypothesis in the Milpa

Using a sample of 40 sources reporting milpa and mucuna-intercropped maize yields in Mesoamerica, we test Boserup’s (1965) prediction that fallow is reduced as a result of growing population density. We further examine direct and indirect effects of population density on yield. We find only mixed support for Boserupian intensification. Fallow periods decrease slightly with increasing population density in this sample, but the relationship is weak. Controlling for other covariates, fallow-unadjusted maize yields first rise then fall with population density. Fallow-adjusted maize yields peak at 390 kg/ha/yr for low population densities (8 persons / km2) and decline to around 280 kg/ha/yr for the highest population densities observed in our dataset. Fallow practices do not appear to mediate the relationship between population density and yield. The multi-level modeling methods we adopt allow for data clustering, accurate estimates of group-level variation, and they generate conditional predictions, all features essential to the comparative study of prehistoric and contemporary agricultural yields

Statistical science: contributions to the Administration\u27s research priority on climate change

Data are fundamental to all of science. Data enhance scientific theories and their statistical analysis suggests new avenues of research and data collection. Climate science is no exception. Earth\u27s climate system is complex, involving the interaction of many different kinds of physical processes and many different time scales. Thus this area of science has a critical dependence on the examination of all relevant data and the application of statistics for its interpretation. Climate datasets are increasing in number, size, and complexity and challenge traditional methods of data analysis. Satellite remote sensing campaigns, automated weather monitoring networks, and climate-model experiments have contributed to a data explosion that provides a wealth of new information but can overwhelm standard approaches. Developing new statistical approaches is an essential part of understanding climate and its impact on society in the presence of uncertainty. Experience has shown that rapid progress can be made when big data is used with statistics to derive new technologies. Crucial to this success are new statistical methods that recognize uncertainties in the measurements and the scientific processes but are also tailored to the unique scientific questions being studied