264-8 Spatio-Temporal Interactions Between Soil Carbon and Nutrient Cycles In the Lower Suwannee River Basin.

Poster Number 222

See more from this Division: S05 Pedology
See more from this Session: Spatial Predictions In Soils, Crops and Agro/Forest/Urban/Wetland Ecosystems: III (Includes Graduate Student Competition)
Tuesday, October 18, 2011
Henry Gonzalez Convention Center, Hall C
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Pasicha Chaikaew1, Sabine Grunwald1, David B. Myers2, Nicholas B. Comerford3 and Willie G. Harris4, (1)Soil and Water Science, University of Florida, Gainesville, FL
(2)Cropping Systems and Water Quality Research, USDA-ARS, Columbia, MO
(3)University of Florida, Quincy, FL
(4)University of Florida, Gainesville, FL
Climate change and human activities have profound impacts on carbon and nutrient cycling at global, regional, and local scales but our understanding how ecosystem and anthropogenic forcings are interlinked with soil carbon under nutrient constraints and/or enrichment is still limited. There are research needs to assess carbon sequestration and nutrient regulation ecosystem services which have profound impacts on carbon and nutrient cycling. Our objectives were to (i) quantify historic and current spatial patterns of soil organic carbon (SOC) stocks; (ii) assess spatially-explicit relationships between SOC and environmental factors (soils, climate, biota, topography, and parent material), and (iii) investigate spatially-explicit relationships between SOC and soil nutrients. We collected 138 soil samples (0-20 cm) in 2009 within the Lower Suwannee River Basin, Florida (19,665 km2). Historic SOC was derived from the Florida Soil Characterization Database (1965-1996) and Soil Data Mart (NRCS). Total carbon (TC) was determined by combustion using a carbon analyzer. Inorganic carbon (IC) was derived by phosphoric acid extraction at 200˚C. SOC was derived by subtracting IC from TC and carbon stocks were derived using measured bulk densities. The total nitrogen (TN) and total phosphorus (TP) were derived by gas combustion analysis and ICP methods, respectively. A suite of environmental GIS and remote sensing data was compiled to characterize soil, climate, vegetation, land use, topography, and parent material. Environmental variables were used to develop models to predict SOC and nutrients across the basin using regression trees, ensemble regression trees, and partial least squares regression and evaluate them using cross-validation. Results suggest that SOC change induced by external environmental factors is proportionally larger in nutrient enriched ecosystems than in nutrient limited ones.
See more from this Division: S05 Pedology
See more from this Session: Spatial Predictions In Soils, Crops and Agro/Forest/Urban/Wetland Ecosystems: III (Includes Graduate Student Competition)