GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 71-5
Presentation Time: 9:00 AM-5:30 PM


STOLL, Emily J., Earth and Planetary Science, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21234, COOK, Rachel L., Department of Forestry and Environmental Resources, North Carolina State University, 2800 Faucette Dr., Raleigh, NC 27607; Forest Productivity Cooperative, Raleigh, NC 27607 and AUSTIN, Robert, Soil Science, North Carolina State University, Raleigh, NC 27695,

Soils are classified to communicate characteristics that indicate appropriate management techniques. However, the widely accepted NRCS Soil Survey classification system is not tailored specifically to forest management. For example, geology is not included in the NRCS soils classification, but since tree roots extend deeper into the soil than crops’, bedrock can be a significant factor affecting forest growth and response to fertilization. A new classification system, constructed by the Forest Productivity Cooperative (FPC), provides a more comprehensive assessment of factors known to influence forest response to management practices. This project constructed and combined a spatially explicit map of the FPC soil properties codes from SSURGO soil data, geology, and major land resource areas to create the foundation for a decision support tool for forest managers.

The classification system was mapped for the states on the United States southeast seaboard. In this area, bedrock geology is important in the mountain and piedmont regions, but is less important in the coastal plain due to depths up to 10 km, which is far beyond the reach of tree roots. More important for the coastal plain than bedrock are the marine deposits that formed terraces throughout the late Quaternary. Thus, bedrock is mapped for the mountain and piedmont regions and the terraces are mapped as the geology layer for the coastal plain.

To maximize user interaction, a web platform allows users to click on an area of interest. It then identifies FPC codes within a stand and presents the user with management techniques recommended for optimum growth, such as fertilizer application or site preparation. This classification system allows for later incorporation of landscape scale nutrient response experiments onto the map to improve forest productivity and sustainable management through spatially tailored recommendations.