Soil Carbon Variability and Change Detection in the Forest Inventory Analysis Database of the United States

Tuesday, 16 December 2014
An-Min Wu1, Edward A Nater1, Brent J Dalzell1 and Charles Hobart Perry2, (1)University of Minnesota - Twin Cities, Saint Paul, MN, United States, (2)USDA Forest Service, Vallejo, CA, United States
The USDA Forest Service’s Forest Inventory Analysis (FIA) program is a national effort assessing current forest resources to ensure sustainable management practices, to assist planning activities, and to report critical status and trends. For example, estimates of carbon stocks and stock change in FIA are reported as the official United States submission to the United Nations Framework Convention on Climate Change. While the main effort in FIA has been focused on aboveground biomass, soil is a critical component of this system. FIA sampled forest soils in the early 2000s and has remeasurement now underway. However, soil sampling is repeated on a 10-year interval (or longer), and it is uncertain what magnitude of changes in soil organic carbon (SOC) may be detectable with the current sampling protocol. We aim to identify the sensitivity and variability of SOC in the FIA database, and to determine the amount of SOC change that can be detected with the current sampling scheme. For this analysis, we attempt to answer the following questions:

1) What is the sensitivity (power) of SOC data in the current FIA database?

2) How does the minimum detectable change in forest SOC respond to changes in sampling intervals and/or sample point density?

Soil samples in the FIA database represent 0-10 cm and 10-20 cm depth increments with a 10-year sampling interval. We are investigating the variability of SOC and its change over time for composite soil data in each FIA region (Pacific Northwest, Interior West, Northern, and Southern). To guide future sampling efforts, we are employing statistical power analysis to examine the minimum detectable change in SOC storage. We are also investigating the sensitivity of SOC storage changes under various scenarios of sample size and/or sample frequency. This research will inform the design of future FIA soil sampling schemes and improve the information available to international policy makers, university and industry partners, and the public.