Method Comparison for Forest Soil Carbon and Nitrogen Estimates in the Delaware River Basin. Issue 1 (30th December 2015)

• Record Type: Journal Article
• Authors: Xu, B.; Pan, Y.; Johnson, A.H.; Plante, A.F.
• Is Part Of: Soil Science Society of America Journal. Volume 80:Issue 1(2016)
• Page Start: 227
• Page End: 237
• Publication Date: 2015-12-30
• Subjects: Soils -- United States -- Periodicals; Soil science -- Periodicals; Periodicals; 631.4973
• DOI: 10.2136/sssaj2015.04.0167
• Languages: English
• ISSNs: 0361-5995

Abstract

Abstract : Core Ideas: Soil cores and quantitative pits each have their limitations in forest soils. Bulk density, coarse fragment, and C concentration variations are method dependent. Compensating errors may mask uncertainty in regional estimates of soil C and N. The accuracy of forest soil C and N estimates is hampered by forest soils that are rocky, inaccessible, and spatially heterogeneous. A composite coring technique is the standard method used in Forest Inventory and Analysis, but its accuracy has been questioned. Quantitative soil pits provide direct measurement of rock content and soil mass from a larger, more representative volume. In this study, the two sampling methods were used to estimate soil C and N stocks in forested plots in the Delaware River Basin. Mean stocks in the whole soil profile (organic and mineral layers, 0–40 cm, using pits) were 76.6 Mg C ha −1 and 4.45 Mg N ha −1 . In the surface mineral layer (0–20 cm), lower bulk density (BD), lower coarse fragment content (CF), and greater C concentration (%C) were measured using the core method compared with the pit method. However, because the three variables are not independent and can be counterbalancing, soil C stocks did not differ between sampling methods. Spatial variation in C stocks was mainly driven by the variance of %C and BD in both methods, while the relative contribution of CF was greater in the soil pit method. Our results suggest that the physical problems associated with the core method and the ability of the core method to capture spatial variation in soil C and N stocks are questionable compared with quantitative soil pits. While variability and covariance among the contributing variables resulted in similar stock estimates from both sampling methods, they might accumulate greater uncertainty in spatial extrapolation to regional estimates of forest soil C and N stocks.