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Title: Extrapolating existing soil organic carbon data to estimate soil organic carbon stocks below 20 cm

Author: Wu, An-Min; Fissore, Cinzia; Perry, Charles H.; Wu, An-Min; Dalzell, Brent; Wilson, Barry T.;

Date: 2015

Source: In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8–10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 163-165.

Publication Series: General Technical Report (GTR)

   Note: This article is part of a larger document. View the larger document

Description: Estimates of forest soil organic carbon stocks across the US are currently developed from expert opinion in STATSGO/SSURGO and linked to forest type. The results are reported to the US EPA as the official United States submission to the UN Framework Convention on Climate Change. Beginning in 2015, however, estimates of soil organic carbon (SOC) stocks will be based on SOC data from soil cores collected in the field (0-10 and 10-20 cm depth). In addition, the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance suggests these estimates extend to at least 30 cm for all forested lands. This study reports the results of that extrapolation effort. Data for this effort were obtained from the International Soil Carbon Network (ISCN) database, from analyses of more than 500 150 cm deep cores collected from forested sites across the Upper Midwest, and from cores taken at several US Forest Service Experimental Forests. SOC contents were adjusted to 0-10, 10-20, and 20-50 cm depth increments by a weighted average estimation technique if needed. Multiple linear regression modeling was used to predict the percent SOC of the 20 to 50 cm depth layer from the percent SOC of the 0-10 and 10-20 cm depth layers. Additional covariates included climatic data, latitude and longitude. Preliminary analyses show a best fit prediction R2 > 0.6 for all data.

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Citation:


Nater, Edward A.; Fissore, Cinzia; Perry, Charles H.; Wu, An-Min; Dalzell, Brent; Wilson, Barry T. 2015. Extrapolating existing soil organic carbon data to estimate soil organic carbon stocks below 20 cm. In: Stanton, Sharon M.; Christensen, Glenn A., comps. 2015. Pushing boundaries: new directions in inventory techniques and applications: Forest Inventory and Analysis (FIA) symposium 2015. 2015 December 8–10; Portland, Oregon. Gen. Tech. Rep. PNW-GTR-931. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 163-165.

 


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