Reconstructing Utah’s Indigenous Maize Farming Niche
Author(s): Ishmael Medina; Brian Codding; Kenneth Vernon; Jerry Spangler
Year: 2024
Summary
This is an abstract from the "SAA 2024: Individual Abstracts" session, at the 89th annual meeting of the Society for American Archaeology.
Maize (Zea mays) was one of the most widespread domesticated plants in the Americas before European colonization. Despite its widespread distribution, explaining how and why ancient maize farming spread into Utah remains a central research question in Southwest archaeology. To understand how ancient maize spread, we need a comprehensive suitability model for maize agriculture using multiple ecological variables that accurately predict where maize farming was suitable and unsuitable. For this presentation, we have constructed a species distribution model (SDM) for maize, using a novel machine learning approach called Random Forest, to produce a suitability model for Indigenous maize agriculture in Utah (ca. 3200 - 500 BP). Furthermore, this research builds on ecological theory recently applied to archaeological data by utilizing the Ideal Free Distribution (IFD) model to explain the changes in behavior and settlement patterns observed in the archaeological record. Comparing locations best suited for maize agriculture, determined by the SDM, with well-dated Indigenous maize farming sites will test the predictions of the IFD model and help explain Indigenous maize farmer settlement patterns throughout the northwestern limit of maize agriculture.
Cite this Record
Reconstructing Utah’s Indigenous Maize Farming Niche. Ishmael Medina, Brian Codding, Kenneth Vernon, Jerry Spangler. Presented at The 89th Annual Meeting of the Society for American Archaeology. 2024 ( tDAR id: 499621)
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Keywords
General
Digital Archaeology: Simulation and Modeling
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Farming
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Formative
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IFD
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Machine Learning
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Maize
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Quantitative and Spatial Analysis
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Random
Geographic Keywords
North America: Northern Southwest U.S.
Spatial Coverage
min long: -123.97; min lat: 37.996 ; max long: -101.997; max lat: 46.134 ;
Record Identifiers
Abstract Id(s): 39667.0