GSA 2020 Connects Online

Paper No. 57-2
Presentation Time: 10:20 AM

SOIL CARBON STORAGE IN THE MAYA LOWLANDS: DISTURBANCE, FLUX AND RECOVERY IN THE TROPICAL EARLY ANTHROPOCENE


LUZZADDER-BEACH, Sheryl, Department of Geography and the Environment, The University of Texas at Austin, 305 E. 23rd St. A3100, RLP 3.306, Austin, TX 78712, BEACH, Timothy P., Department of Geography and the Environment, University of Texas at Austin, RLP Bldg. Rm. 3.306, A3100, 305 E. 23rd Street, Austin, TX 78712, DUNNING, Nicholas P., Department of Geography, University of Cincinnati, Cincinnati, OH 45221-0131, COOK, Duncan, Australian Catholic University, Virginia, QLD 4034, Australia, KRAUSE, Samantha M., Department of Geography, Texas State University, San Marcos, TX 78666 and DOYLE, Colin, Geography and the Environment, University of Texas at Austin, CLA Bldg. Rm. 3.306, A3100, 305 E. 23rd Street, Austin, TX 78712

Studying the soils of the Maya Lowlands in conjunction with archaeological exploration provides a long view lens into tropical soil and atmospheric carbon cycle dynamics. This paper will test the hypothesis that soil carbon persistence differs in time, space and between geomorphic and archaeological settings. This paper will use dated soil carbon isotopic results from multiple geoarchaeological investigations we have conducted in Guatemala, Belize and Mexico, to generate and compare rates of soil carbon storage, flux, and persistence in the Maya Lowlands. These results will be relevant for better quantifying variables for modeling anthropogenic inputs to climate change during and after the Early Anthropocene, based on human land disturbance activities for agriculture such as terracing and ditched field agriculture. It is expected that rates of change and recovery will vary based on geomorphic and paleoecological settings, and on post disturbance recovery. These rates should be taken into account in modeling atmospheric CO2 inputs attributed to ancient human land disturbance, use, conservation, and abandonment, and can give insight into modeling modern and future anthropogenic impacts.