Measurements of Archaeobotanical Diversity and Richness Using Combined Macrobotanical and Microbotanical Data: Methodological and Theoretical Considerations

Summary

This is an abstract from the "SAA 2023: Individual Abstracts" session, at the 88th annual meeting of the Society for American Archaeology.

Recent computational advances in the accessibility of robust statistical techniques used to estimate the biological richness and diversity of ecological communities using observational data provide a strong foundation for archaeological assessments of botanical richness and diversity using archaeobotanical data. While there is broad consensus amongst paleoethnobotanists that assessments of past botanical diversity must include macrobotanical and microbotanical data, there is less agreement regarding appropriate methods for integrating these distinctive lines of evidence due to divergent taphonomies. First, we outline some of the theoretical and methodological considerations necessary to link archaeobotanical data and human behavior. Then, our analyses focus on botanical assemblages recovered from three single-component Ancestral Puebloan sites located in what is now northern Arizona (USA) dating between AD 250 and 550, inhabited by highly mobile yet intensive maize (Zea mays) farmers that used a wide range of foraged and cultivated plant foods alongside domesticated plant foods. We utilize incidence-based (presence/absence) sample-derived rarefaction to compare the richness and diversity of composite macrobotanical/microbotanical assemblages at scales ranging from context-specific to contemporaneous site-wide assemblages. We also introduce the application of coverage-based rarefaction to archaeobotanical data as a technique for standardizing assemblages not only by sampling effort but also by “sample completeness.”

This Resource is Part of the Following Collections

• SAA 2023: Individual Abstracts   •
• Society for American Archaeology 88th Annual Meeting, Portland, OR (2023)

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Record Identifiers

Abstract Id(s): 37225.0