Rapid, non-destructive carbon analysis of forest soils using neutron-induced gamma-ray spectroscopy


Forest soils are pivotal to understanding global carbon (C) cycling and evaluating policies for mitigating global change. However, they are very difficult to monitor because of the heterogeneity of soil characteristics, the difficulty of representative sampling, and the slow time scale of response to environmental change. Here we demonstrate that use of gamma-ray spectroscopy facilitates in situ non-destructive analysis of C and other elements in forest soils. In this approach the element-specific gamma-rays are induced by fast and thermal neutrons interacting with the nuclei of the elements present in the soil. Background gamma-rays emanating from naturally occurring radionuclides in the forest are recorded as well. We applied this approach in a mature northern hardwood forest on glacial till soils at the Bartlett Experimental Forest in New Hampshire, USA. The inelastic neutron scattering (INS) system yielded strong signals in gamma-ray counts/h, from C and other elements present in the soil matrix that included silicon, oxygen, hydrogen, iron, aluminum, manganese and potassium. The INS sensitivity for carbon was 20.656 counts h−1 kg−1 C m−2 based on current net C gamma-ray counts and the data for the O horizon and mineral soil to a depth of 30 cm obtained from a nearby quantitative soil pit (7.35 kg C m−2). We estimate the minimum detectable change to be ∼0.34 kg C m−2, which is ∼5% of the current soil C content, and the minimum detectable limit to be ∼0.23 kg C m−2. Eight % reproducibility from 11 measurements was limited, in part, by the large variability in the system counting geometry due to the uneven forest microtopography. The INS approach has the potential to revolutionize belowground monitoring of C and other elements, because the possibility of detecting a 5% change in forest soils has not been possible with destructive sampling methods.


Earth Systems Research Center

Publication Date


Journal Title

Forest Ecology and Management



Digital Object Identifier (DOI)


Document Type



Copyright © 2010, Elsevier