Jeff Baldock

Role of the soil matrix and minerals in protecting natural organic materials against biological attack

Natural organic materials in soils consist of a complex mixture of different biochemicals exhibiting numerous morphologies and stages of biological oxidation. A continuum of decomposability exists based on chemical structure; however, this continuum can be altered by interactions with minerals within matrices capable of stabilising potentially labile organic matter against biological oxidation. Protection is not considered to equate to a permanent and complete removal of organic C from decomposition, but rather to a reduced decomposition rate relative to similar unprotected materials. The stabilisation of organic materials in soils by the soil matrix is a function of the chemical nature of the soil mineral fraction and the presence of multivalent cations, the presence of mineral surfaces capable of adsorbing organic materials, and the architecture of the soil matrix. The degree and amount of protection offered by each mechanism depends on the chemical and physical properties of the mineral matrix and the morphology and chemical structure of the organic matter. Each mineral matrix will have a unique and finite capacity to stabilise organic matter. Quantifying the protective capacity of a soil requires a careful consideration of all mechanisms of protection and the implications of experimental procedures.

The effects of vegetation and burning on the chemical composition of soil organic matter in a volcanic ash soil as shown by 13C NMR spectroscopy. I. Whole soil and humic acid fraction

Soil samples were collected from the surface mineral horizon (Ah horizon) of four adjacent soils (sites I, II, III, IV) and one remote soil (site V) derived from volcanic ash in Japan. The four adjacent sites were managed as Miscanthus sinensis grassland for several hundred years by the use of annual burning to prevent the regrowth of native forest species. At site I, annual burning was still being practiced when soil samples were collected; however, at sites II, III and IV annual burning to maintain grassland vegetation ceased about 20–30, 40–50 and more than 100 years ago, respectively, and the sites were left to return to forest. At site V, a mature, broad-leaf, deciduous forest established by natural regeneration existed. The influence of annual burning and vegetative cover on the chemistry of the organic materials contained in the whole soil, the < 53 μm soil fraction, the residues remaining after photo-oxidation of the < 53 μm soil fraction, and the humic acid fraction present at each of the five sites was examined using solid-state 13C NMR. On site I, where grasses were still burned annually, SOM and humic acid fraction contained a greater proportion of aromatic and carbonyl carbons compared to the other sites. Alkyl carbon made a relatively small (19%) contribution to the composition of SOM on site I. When grassland was invaded by forest, the chemical nature of the SOM and humic acid fraction changed. The greatest changes occurred during the first 20–30 years, after which changes in the chemistry of SOM and humic acid fraction were of a smaller magnitude. The changes in SOM chemistry included a decrease in aromatic and an increase in alkyl carbon contents, indicating that SOM produced under forest was richer in alkyl carbon than that produced under grasses managed with annual burning. The SOM at the remote site, under deciduous forest (site V), was highly aliphatic in nature with alkyl carbon contributing 35% of the total soil carbon. Application of a proton-spin relaxation editing (PSRE) procedure to the SOM of each site indicated heterogeneity within the SOM structures, and subspectra of carbon associated with slower- and faster-relaxing protons were derived. Subspectra of the slowly-relaxing fractions from sites I, II and III were similar and resembled spectra of partly decomposed plant materials. The fast-relaxing subspectrum from site I contained a strong central resonance at 130 ppm and a small peak at 176 ppm, and was very similar to spectra obtained for charcoal and charred residues. The fast relaxing fractions from other sites included less aromatic carbon and had some O-alkyl materials. The Bloch decay spectrum of SOM from site I showed more aromatic and carbonyl carbons than the CP/MAS spectrum and highlighted an important limitation of the CP/MAS technique when it is applied to SOM containing charcoals or charred plant residues.

Microbial utilisation Of biochar-derived carbon

Whilst largely considered an inert material, biochar has been documented to contain a small yet significant fraction of microbially available labile organic carbon (C). Biochar addition to soil has also been reported to alter soil microbial community structure, and to both stimulate and retard the decomposition of native soil organic matter (SOM). We conducted a short-term incubation experiment using two (13)C-labelled biochars produced from wheat or eucalypt shoots, which were incorporated in an aridic arenosol to examine the fate of the labile fraction of biochar-C through the microbial community. This was achieved using compound specific isotopic analysis (CSIA) of phospholipid fatty acids (PLFAs). A proportion of the biologically-available fraction of both biochars was rapidly (within three days) utilised by gram positive bacteria. There was a sharp peak in CO2 evolution shortly after biochar addition, resulting from rapid turnover of labile C components in biochars and through positive priming of native SOM. Our results demonstrate that this CO2 evolution was at least partially microbially mediated, and that biochar application to soil can cause significant and rapid changes in the soil microbial community; likely due to addition of labile C and increases in soil pH.

Concepts in modelling N2O emissions from land use

Modelling nitrous oxide (N2O) emissions from soil is challenging because multiple biological processes are involved that each respond differently to various environmental and soil factors. Soil water content, organic carbon, temperature and pH are often used in models that predict N2O emissions, yet for each of these factors there are concepts that are not fully understood. Though a ubiquitous measure of soil water for models, the application of functions based on water filled pore space across soils that vary in bulk density is not ideal. Diffusion of gases and solutes in soil are controlled by the volume fractions of air and water present. Across soils with different bulk densities, both of these terms vary at constant water filled pore space. Soil organic carbon influences N2O emissions in two ways: as a source of energy for denitrifiers and also by driving biological oxygen demand and the creation of anaerobic zones in the soil. Soil temperature influences N2O emissions through its effect on the activity of microorganisms and enzymes. A variety of temperature response functions have been proposed. The preferred response function should contain a temperature optimum that can be varied in response to climatic conditions to account for microbial adaptation. Soil pH can have direct and indirect influences on rates and product ratios of nitrification and denitrification. The concepts of pH optima and microbial adaptation need to be considered in modelling. Methodological issues such as microsite versus bulk soil measurements and apportioning N2O fluxes to the various N transformation processes remain an impediment to characterising the influence of pH and other factors on N2O emissions. Quantifying the response of N2O emissions to individual factors using regression analysis requires all other factors to be controlled experimentally. Boundary line analysis provides a way of defining the response to a single input variable where other influencing variables are not controlled. Such analyses can aid in the definition of the shape and magnitude of response functions to be incorporated into process simulation models. Process/mechanistic simulation models offer a greater transferability than empirical models but careful consideration of temporal and spatial scale and the availability of data to run these models is critical in developing model structure.

The effects of vegetation and burning on the chemical composition of soil organic matter of a volcanic ash soil as shown by 13C NMR spectroscopy. II. Density fractions

Soil samples from the surface mineral horizons (Ah) of two adjacent sites (sites I and III) and one remote site (site V), derived from volcanic ash in Japan, were collected and separated into fractions with densities 2.0 Mg m−3. The terms free and occluded were used to indicate density fractions in which organic materials weakly associated with soil mineral particles resided external to or within soil aggregates, respectively. The studied sites were under different vegetative covers and had different burning histories. Sites I and III were managed as grassland for several hundred years by the use of annual burning to prevent the regrowth of native forest. At site I, annual burning of Japanese pampa grass (Miscanthus sinensis) was still occurring. However at site III vegetation burning was stopped more than 100 years ago and the site was left to return to forest. At site V a mature, broad leaf deciduous forest maintained by natural regeneration existed. Solid state 13C CP/MAS, Bloch decay, and proton-spin relaxation editing (PSRE) NMR were applied to various density fractions to study the effect of vegetative cover and burning on the chemical composition of soil organic matter (SOM) associated with different density separates. The components of SOM contained in density fractions were also studied using light microscopy. The 13C CP/MAS NMR spectra obtained for the fractions < 1.0 free and < 1.6 free density fractions from sites I and III were similar to spectra of plant material and litter. However, at site V these fractions had more alkyl and less O-alkyl carbon than the corresponding fractions from sites I and III, indicating an influence of vegetative cover and/or extent of decomposition of plant material on the chemistry of SOM contained in these fractions. Using light microscopy, the < 1.0 Mg m−3 free and < 1.6 Mg m−3 free fractions were observed to be dominated by large, undecomposed root and shoot fragments and included charcoal and charred plant residues. The chemistry of the 1.8–2.0 Mg m−3 fractions was comparable to that of the < 1.6 Mg m−3 free fractions. The fractions < 1.6 Mg m−3 occluded and 1.6–1.8 Mg m−3, however, had considerably less O-alkyl and more aromatic carbon contents than the free light fractions. The aromatic carbon in these fractions was suggested to originate in part from charcoal and charred plant residues resulting from burning. Lignin and its decomposition products were also another source of aromatic carbon for these fractions. Application of Bloch decay NMR to the fractions 1.6–1.8 Mg m−3, confirmed the presence of a source of aromatic carbon containing few protons similar to charcoal in all three sites studied and showed that the aromatic carbon content of the fractions were underestimated by the CP/MAS method. PSRE NMR separated the fractions 1.6–1.8 Mg m−3 into two components and subspectra for these components in site I resembled spectra of slightly decomposed plant residues and charcoal.

Demineralization of marine and freshwater sediments for CP/MAS 13C NMR analysis

Abstract A method was developed to demineralize sediment trap material and marine sediments containing labile organic matter (OM), in preparation for cross polarization and magic angle spinning (CP/MAS) solid-state 13C NMR analysis. Carbonate and silicate minerals were dissolved with HCl and a mixture of dilute HCl/HF, respectively. Demineralization kinetics were assessed for a range of freshwater and marine sediments, as well as pure mineral and organic samples. For samples with a very low organic carbon (OC) concentration (

Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change.

We can effectively monitor soil condition—and develop sound policies to offset the emissions of greenhouse gases—only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C in the soil of Australia. We assembled and harmonized data from several sources to produce the most comprehensive set of data on the current stock of organic C in soil of the continent. Using them, we have produced a fine spatial resolution baseline map of organic C at the continental scale. We describe how we made it by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of stock were predicted at the nodes of a 3-arc-sec (approximately 90 m) grid and mapped together with their uncertainties. We then calculated baselines of soil organic C storage over the whole of Australia, its states and territories, and regions that define bioclimatic zones, vegetation classes and land use. The average amount of organic C in Australian topsoil is estimated to be 29.7 t ha−1 with 95% confidence limits of 22.6 and 37.9 t ha−1. The total stock of organic C in the 0–30 cm layer of soil for the continent is 24.97 Gt with 95% confidence limits of 19.04 and 31.83 Gt. This represents approximately 3.5% of the total stock in the upper 30 cm of soil worldwide. Australia occupies 5.2% of the global land area, so the total organic C stock of Australian soil makes an important contribution to the global carbon cycle, and it provides a significant potential for sequestration. As the most reliable approximation of the stock of organic C in Australian soil in 2010, our estimates have important applications. They could support Australias National Carbon Accounting System, help guide the formulation of policy around carbon offset schemes, improve Australias carbon balances, serve to direct future sampling for inventory, guide the design of monitoring networks and provide a benchmark against which to assess the impact of changes in land cover, land management and climate on the stock of C in Australia. In this way, these estimates would help us to develop strategies to adapt and mitigate the effects of climate change.

Predicting contents of carbon and its component fractions in Australian soils from diffuse reflectance mid-infrared spectra

Quantifying the content and composition of soil carbon in the laboratory is time-consuming, requires specialised equipment and is therefore expensive. Rapid, simple and low-cost accurate methods of analysis are required to support current interests in carbon accounting. This study was completed to develop national and state-based models capable of predicting soil carbon content and composition by coupling diffuse reflectance mid-infrared (MIR) spectra with partial least-squares regression (PLSR) analyses. Total, organic and inorganic carbon contents were determined and MIR spectra acquired for 20 495 soil samples collected from 4526 locations from soil depths to 1 m within Australia’s agricultural regions. However, all subsequent MIR/PLSR models were developed using soils only collected from the 0–10, 10–20 and 20–30 cm depth layers. The extent of grinding applied to air-dried soil samples was found to be an important determinant of the variability in acquired MIR spectra. After standardisation of the grinding time, national MIR/PLSR models were developed using an independent test-set validation approach to predict the square-root transformed contents of total, organic and inorganic carbon and total nitrogen. Laboratory fractionation of soil organic carbon into particulate, humus and resistant forms was completed on 312 soil samples. Reliable national MIR/PLSR models were developed using cross-validation to predict the contents of these soil organic carbon fractions; however, further work is required to enhance the representation of soils with significant contents of inorganic carbon. Regional MIR/PLSR models developed for total, organic and inorganic carbon and total nitrogen contents were found to produce more reliable and accurate predictions than the national models. The MIR/PLSR approach offers a more rapid and more cost effective method, relative to traditional laboratory methods, to derive estimates of the content and composition of soil carbon and total nitrogen content provided that the soils are well represented by the calibration samples used to build the predictive models.

Variability in harvest index of grain crops and potential significance for carbon accounting: examples from Australian agriculture

Abstract For grain crops, harvest index (HI) is the ratio of harvested grain to total shoot dry matter, and this can be used as a measure of reproductive efficiency. The index can also be used to estimate crop carbon (C) balances by applying it to grain yield statistics to determine total shoot dry matter and then calculating crop residues as the difference between shoot C and grain C. Such an approach is widely used in C-accounting systems. Such a C-accounting practice is sensitive to changes in HI. In Australia, measured variations in HI are large enough to alter C balance calculations for some crops. Much of this variation results from the diverse range of climates and soils, which are a feature of the Australian cereal cropping region. Factors that influence crop HI include the energy and protein content of seeds, long-term breeding achievements, and extreme (either hot or cold) temperatures during crop reproductive development. Crop husbandry can also influence HI, especially delayed sowing, which shortens the length of the vegetative phase and increases HI. For wheat, and perhaps some other C3 cereals, excess nitrogen can enhance the allocation of photosynthate to structural carbon, which cannot be mobilized to grain later, resulting in a decrease in HI. Evidence for the balance between pre and postanthesis water use of field-grown crops having a significant influence on crop HI is equivocal. A dataset containing more than 3000 estimates of HI in Australia has been assembled and used to summarize observed HI variations for each of the principal field crops grown in Australia. There remains a need for more reliable field HI data to be used in C-accounting systems and to aid the development of models to simulate likely regional and seasonal differences in HI for C-accounting purposes.

Quantifying the allocation of soil organic carbon to biologically significant fractions

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).