Pedoecological Mapping to Improve Land Management Decision-Making Using Ecological Site Descriptions.

Conventional soil maps (CSM) like the USDA-NRCS Soil Survey Geographic (SSURGO) database have been used for land management since their inception in the early 20th century. Spatial disaggregation of CSM using digital soil mapping (DSM) methods can help scale soil surveys to field-scale management schema like Ecological Site Descriptions (ESD). ESD integrate information on soil, vegetation, climate, habitat, ecosystem services, and land management by grouping areas with soils of similar ecological potential. To further utilize these resources, mapping should integrate both ESD and disaggregated CSM into pedoecological maps (PEM). ESD use state and transition models (STM) to illustrate and attribute the different potential reference biological communities (mainly vegetation descriptions) and also degraded states that result from both natural and human disturbance. Each of these states has an associated set of vegetation production amounts and dynamic soil property measures (e.g. O horizon thickness, aggregate stability) that distinguish them from other states within the same ecological site. If these states can be integrated with DSM and disaggregation techniques, it can greatly increase our ability to target specific areas for management. We present a PEM example using a spatial model of spodic soil property expression to disaggregate soil map units for correlation to ESD, and then using forest inventory data to superimpose the vegetative state as interpreted from the ESD-STM. We demonstrate this as a case study of the Spodic Shale Upland Conifer Forest Ecological Site in the Monongahela National Forest, West Virginia, USA.