The study of ancient Maya intensive, intra-site agricultural systems, such as kitchen gardens, has gained new interest in recent years as a valuable way of interpreting numerous aspects of the ancient Maya's daily life (e.g. subsistence and settlement patterns, population growth, diet and nutrition, gender roles). However, while contemporary Maya kitchen gardens can often be easily identified and studied by cultural anthropologists and archaeologists, ancient kitchen gardens are usually much harder to identify by traditional archaeological techniques because of their lack of architectural structures and other identifying features. To compensate for this limitation, various forms of chemical testing (primarily phosphate analysis) are being used to positively identify kitchen gardens and other specific anthropogenically modified spaces that are invisible to standard archaeological techniques. The archaeological community trusts these methods to be a reliable way of testing soils in archaeological sites for specific agricultural features, even though there has been little research conducted to conclusively prove this assertion. In response to this lack of research, this thesis investigates the viability of phosphate analysis and other chemical tests through a comprehensive literary review of previous and current research and an analysis of the data presented within it. While soil phosphate analysis has been used in past and current research to identify general agricultural features with great success, the chemical signatures produced from this method only give vague information about the soil and what was done to it, making soil Phosphate analysis unreliable to definitively discern specific agricultural areas, such as kitchen gardens, from general agricultural areas.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-2453 |
| Date | 01 January 2015 |
| Creators | Foster, Cheryl |
| Publisher | University of Central Florida |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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