Taxonomic Implications of Geographic Modeling of Soil Moisture: Applying the Newhall Simulation Model to Broad Regions Using the Parameter-Elevation Regressions On Independent Slopes Model (PRISM) Data Set.

Parameter-elevation-Regressions-on-Independent-Slopes-Model (PRISM) dataset were used as input into an automated Java program of the Newhall Simulation Model (NSM) in order to model soil moisture and temperature regimes in major land resource are (MLRA) 147 and 140 in Pennsylvania, New York, Maryland and West Virginia. While moisture and temperature regimes were nearly uniformly mesic-udic, a great deal of variability was found in simulations of biological activity windows, such as the number of days per year that the soil was above 5 degrees (C) and moist. Moving from static taxonomic systems in which broad classifications are the norm to dynamic predictive taxonomy, in which specific predictions for a given set of soil-climate-environmental features are given is possible with sophisticated simulations such as NSM and should be a long-term goal for soil taxonomy.