Characterizing the Spatial Pattern of Soil Carbon and Nitrogen Pools in the Turkey Lakes Watershed: A Comparison of Regression Techniques

There is considerable spatial heterogeneity in organic carbon (C), total nitrogen (N), and potentially mineralizable nitrogen (PMN) pools in the soils of the Turkey Lakes Watershed. We hypothesized that topography regulates the spatial pattern of these pools through a combination of static factors (slope, aspect and elevation), which influence radiation, temperature andmoisture conditions, and dynamic factors (catenary position,profile and planar curvature), which influence the transport ofmaterials downslope. We used multiple linear regression (MLR)and tree regression (TR) models as exploratory techniques todetermine if there was a topographic basis for the spatialpattern of the C, N and PMN pools. The MLR and TR modelspredicted similar integrated totals (i.e., within 5% of eachother) but dissimilar spatial patterns of the pools. For thecombined litter, fibric and hemic layer, the MLR models explaineda significant portion of the variance (R² = 0.38, 0.23 and0.28 for C, N and PMN, respectively), however, the residuals werelarge and biased (the smallest contents were over-predicted andthe largest contents were under-predicted). The TR models (9-branch), in contrast, explained a greater portion of the variance (R² = 0.75, 0.67 and 0.62 for C, N and PMN, respectively) and the residuals were smaller and unbiased. Based on our sampling strategy, the models suggested that static factors were most important in predicting the spatial pattern of the nutrient pools. However, a nested sampling strategy that included scales where both static (among hillslopes) and dynamic (within hillslope) factors result in a systematic variation in soil nutrient pools may have improvedthe predictive ability of the models.