A modeling framework for the estimation soil organic matter carbon in forests of the United States
Soil organic carbon (SOC) is the largest terrestrial carbon (C) sink and management of this pool is a critical component of global efforts to mitigate atmospheric C concentrations. Soil organic carbon also affects essential biological, chemical, and physical soil functions such as nutrient cycling, water retention, and soil structure. Much of the SOC on earth is found in forest ecosystems and is thought to be relatively stable. However, there is growing evidence that SOC may be sensitive to global change effects, particularly in the northern circumpolar region where an estimated 50 percent of the global SOC is stored. In the United States (US), SOC in forests is monitored by the national forest inventory (NFI) conducted by the Forest Inventory and Analysis (FIA) program within the US Department of Agriculture, Forest Service. The FIA program currently uses SOC predictions based on SSURGO/STATSGO data to populate the NFI. Most estimates of SOC in forests from the SSURGO/STATSGO data are based primarily upon expert opinion and lack systematic field observations. The FIA program has been consistently measuring soil attributes as part of the NFI since 2001 and has amassed an extensive inventory of SOC in forests in the conterminous US and coastal Alaska. Here we present, for the first time, estimates of soil organic carbon (SOC) density (Mg∙ha-1) obtained from the NFI of the US and describe the modeling framework used to compile estimates for United Nations Framework Convention on Climate Change reporting.
Initial comparisons between the NFI estimates (to a depth of 20 cm) and country-specific (CS) predictions (to a depth of 100 cm) of SOC density suggest that the CS predictions, while generally larger, will result in underestimates of SOC across all regions and forest types given the large difference in depth between the estimates. This is particularly the case in the Western US where NFI estimates are more than 76 percent larger (29.35±17.47 Mg ha -1) than CS predictions. Given the preliminary results, it is likely that the US has been underestimating the contribution of SOC in the Nation’s forest C budget. Next steps will be to expand the NFI estimates to a depth of 30 cm to align with Intergovernmental Panel on Climate Change guidance and 100 cm for direct comparison with the current CS predictions. The NFI estimates and auxiliary information will then be used to develop a new model to predict SOC for all regions and forest types in the US.