Quantifying the allocation of soil organic carbon to biologically significant fractions

Abstract

Soil organic carbon (OC) exists as a diverse mixture of organic materials with different susceptibilities to biological decomposition. Computer simulation models constructed to predict the dynamics of soil OC have dealt with this diversity using a series of conceptual pools differentiated from one another by the magnitude of their respective decomposition rate constants. Research has now shown that the conceptual pools can be replaced by measureable fractions of soil OC separated on the basis of physical and chemical properties. In this study, an automated protocol for allocating soil OC to coarse (>50 µm) and fine (≤50 µm) fractions was assessed. Automating the size fractionation process was shown to reduce operator dependence and variability between replicate analyses. Solid-state 13C nuclear magnetic resonance spectroscopy was used to quantify the content of biologically resistant poly-aryl carbon in the coarse and fine size fractions. Cross-polarisation analyses were completed for coarse and fine fractions of 312 soils, and direct polarisation analyses were completed for 38 representative fractions. Direct polarisation analyses indicated that the resistant poly-aryl carbon was under-represented in the cross-polarisation analyses, on average, by a factor of ~2. Combining this under-representation with a spectral analysis process allowed the proportion of coarse- and fine-fraction OC existing as resistant poly-aryl C to be defined. The content of resistant OC was calculated as the sum of that found in the coarse and fine fractions. Contents of particulate and humus OC were calculated after subtracting the resistant OC from the coarse and fine fractions, respectively. Across the 312 soils analysed, substantial variations in the contents of humus, particulate, and resistant carbon were noted, with respective average values of 9.4, 4.0, and 4.5 g fraction C/kg soil obtained. When expressed as a proportion of the OC present in each soil, the humus, particulate, and resistant OC accounted for 56, 19, and 26%, respectively. The nuclear magnetic resonance analyses also indicated that the use of a 50-µm sieve to differentiate particulate (>50 µm) from humus (≤50 µm) forms of OC provided an effective separation based on extents of decomposition. The procedures developed in this study provided a means to differentiate three biologically significant forms of soil OC based on size, extent of decomposition, and chemical composition (poly-aryl content).

Greater soil carbon stocks and faster turnover rates with increasing agricultural productivity

“…The HF procedure resulted in an average C loss of 17.4 %. Operating conditions were identical to those reported in Baldock et al (2013a). In order to quantify absolute differences in chemical composition, data were reported by normalizing the recorded signal intensity by the amount of observable C, determined following the conventions of Smernik and Oades (2000), in the analyzed sample.…”

“…Mid-infrared spectroscopy in combination with partial least-squares regression (MIR-PLSR) was used to estimate the distribution of OC into three biologically meaningful pools, the particulate (POC), humus (HOC), and resistant (ROC) organic carbon fractions (Baldock et al, 2013a, b), using the Unscrambler X software package (CAMO Software, Oslo, Norway). Prediction statistics (Hotelling's T square and Mahalanobis distance) suggested that this soil type was well represented in the calibration set of Baldock et al (2013b).…”

Post-wildfire Erosion in Mountainous Terrain Leads to Rapid and Major Redistribution of Soil Organic Carbon

“…Spectra were compared to a glycine standard for observability. For these NMR analyses, 10-20,000 scans were collected per sample, and the collected spectra were integrated into eight regions: 0-45 ppm (Alkyl), [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60] For the samples from erosional sites, the Soil Carbon Research Program (SCaRP) MIR-PLSR model was used to predict three organic C fractions within the soil samples: resistant organic carbon (ROC, particles that are chemically similar to charcoal, or PyC), particulate organic carbon (POC, particles 50-2,000 µm excluding PyC), and humic organic carbon (HOC, particles <50 µm excluding PyC) (Baldock et al, 2014). This model has proven to be a reliable and time-effective method for predicting soil fractions and has been demonstrated a reasonable predictor across different land uses and vegetation types in and out of Australia (Baldock et al, 2013b;Ahmed et al, 2017;Jauss et al, 2017).…”

Sediment and carbon deposition vary among vegetation assemblages in a coastal salt marsh

“…Residue samples were treated with 2 % hydrofluoric acid (HF) according to the method of Skjemstad et al (1994) to remove paramagnetic materials and concentrate organic C for 13 C NMR analyses. Cross-polarisation 13 C NMR spectra were acquired using a 200 MHz Avance spectrometer (Bruker Corporation, Billerica, MA, USA) following the instrument specifications, experimental procedures and spectral processing outlined by Baldock et al (2013b). …”