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Soil carbon (C) models are important tools for understanding soil C balance and projecting C stocks in terrestrial ecosystems, particularly under global change. The initialization and/or parameterization of soil C models can vary among studies even when the same model and data set are used, causing potential uncertainties in projections. Although a few studies have assessed such uncertainties, it is yet unclear what these uncertainties are correlated with and how they change across varying environmental and management conditions. Here, applying a process-based biogeochemical model to 90 individual field experiments (ranging from 5 to 82 years of experimental duration) across the Australian cereal-growing regions, we demonstrated that well-designed optimization procedures enabled the model to accurately simulate changes in measured C stocks, but did not guarantee convergent forward projections (100 years). Major causes of the projection uncertainty were due to insufficient understanding of how microbial processes and soil C pool change to modulate C turnover. For a given site, the uncertainty significantly increased with the magnitude of future C input and years of the projection. Across sites, the uncertainty correlated positively with temperature but negatively with rainfall. On average, a 331 % uncertainty in projected C sequestration ability can be inferred in Australian agricultural soils. This uncertainty would increase further if projections were made for future warming and drying conditions. Future improvement in soil C modelling should focus on how the microbial community and its C use efficiency change in response to environmental changes, and better conceptualization of heterogeneous soil C pools and the C transformation among those pools. [ABSTRACT FROM AUTHOR]

The benefits of sequestering carbon are many, including improved crop productivity, reductions in greenhouse gases, and financial gains through the sale of carbon credits. Achieving better understanding of the sequestration process has motivated many deterministic models of soil carbon dynamics, but none of these models address uncertainty in a comprehensive manner. Uncertainty arises in many ways-around the model inputs, parameters, and dynamics, and subsequently model predictions. In this paper, these uncertainties are addressed in concert by incorporating a physical-statistical model for carbon dynamics within a Bayesian hierarchical modelling framework. This comprehensive approach to accounting for uncertainty in soil carbon modelling has not been attempted previously. This paper demonstrates proof-of-concept based on a one-pool model and identifies requirements for extension to multi-pool carbon modelling. Our model is based on the soil carbon dynamics in Tarlee, South Australia. We specify the model conditionally through its parameters, soil carbon input and decay processes and observations of those processes. We use a particle marginal Metropolis-Hastings approach specified using the LibBi modelling language. We highlight how samples from the posterior distribution can be used to summarise our knowledge about model parameters, to estimate the probabilities of sequestering carbon and to forecast changes in carbon stocks under crop rotations not represented explicitly in the original field trials. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract Clay dispersion in soil results in structural instability and management problems. The aim of this study was to determine whether or not the easily dispersed colloidal materials differ in [...]

Measurement of dispersible clay is important for the diagnosis of structural stability problems in soil. However, clay dispersibility is known to change with water content and time. The purpose of the present study was to determine how incubation of sodic soil under different water content regimes influences clay dispersibility. Two topsoils (depth 0-0.1 m), one sodic [exchangeable sodium percentage (ESP) 9.7] and the other non-sodic (ESP 3.8), were collected from an experimental pasture at Kyabram, Victoria, and 2 soils, a sodic topsoil (depth 0-0.1 m, ESP 6.9) and the corresponding subsoil (depth 0.2-0.3 m, ESP 25.7), were collected from a cropped field at Two Wells, South Australia. The soils were incubated for 264 days in a split-plot design. The main treatments were soil type and incubation water content: continuously air-dry, continuously wet (-50 kPa), or with wet/dry cycles. The subtreatment was water content at analysis: air dry or wet (-50 kPa). Clay dispersion was greater when measured on wet soils than dry soils, irrespective of water contents during the prior incubation. Electrical conductivity increased, and sodium adsorption ratio (SAR), pH, and organic carbon content decreased as a function of the time for which the soils were wet. In the Kyabram soils that were wet when analysed, easily dispersible clay content increased with SAR. Decreases in moderately dispersible clay under the wetting/drying regime were not related to electrolyte composition, and were attributed to particle rearrangement and cementation. The decreases in clay dispersibility with time occurred despite net losses of carbohydrate and aliphatic materials. An implication of the work is that the decomposition of soil organic matter, even in the absence of fresh additions, may reduce clay dispersion in sodic soils by altering electrolyte concentration and composition. Additional keywords: sodium adsorption ratio, organic matter, pH, water content., Introduction The tendency of clay to disperse is an important property of soil, and it has been suggested that values of dispersible clay should be collected routinely for assessing the [...]

Carbon dioxide emissions and the mass loss of peat incubated in situ were measured in peat soils in the Australian Alps. The carbon chemistry of incubated peats was characterized using 13C nuclear magnetic resonance (NMR). In situ decomposition decreased as a function of increasing alkyl carbon content of the initial organic matter, providing direct evidence of the oft-cited link between substrate quality and decomposition rates. More mass loss occurred in the bog peat samples than in the dried peat samples. However, at the peat surface, the amount of CO2 emitted was not significantly different between bog peat and dried peat. Carbon inputs, and therefore the sink or source status, of these peats are yet to be quantified. [ABSTRACT FROM AUTHOR]

Symbiotic dinitrogen (N2) fixation of crop and pasture legumes is a critical component of agricultural systems, but its measurement is expensive and labour intensive. Simple models which can provide approximations based on crop or pasture dry matter production would be useful for agrononomists and those interested in regional nitrogen (N) cycle fluxes. We investigate meta analysis of published data on legume shoot dry matter production, shoot %N and legume %N fixed (%Ndfa) and look for relationships among these, as a possible way of providing useful approximations of N2 fixation. We restricted our analysis to Australian studies where we have ready access to the primary data and where cultivars, management and climate are more constrained compared to a universal dataset. Regression analysis between shoot dry matter and amounts of shoot N2 fixed were strong for all crop and pasture legumes with significant differences in slope and intercept values being obtained between pastures and crops, and between chickpea ( Cicer arietinium) and all other crop and pasture legumes. Annual pasture legumes showed the strongest linear relationship between N2 fixation and shoot dry matter and had the greatest slope (20.2–24.3 kg N2 fixed/t), compared to 18.7 kg N2 fixed/t for the perennial pasture legume lucerne (alfalfa, Medicago sativa), and between 10.7 to 23.0 kg N2/t for crop legumes, depending upon species. It was recognised that the use of such shoot-based relationships would underestimate the total amounts of N2 fixed since the contributions of fixed N present in, or derived from, roots and nodules are not included. Furthermore there needs to be careful consideration of the validity of an intercept term, which might reflect suppression of N2 fixation at low dry matter and high soil mineral N availability, or possibly the use of non-linear regression. For chickpea crops grown in north-eastern Australia, multiple regression indicated that N2 fixation was much more closely correlated with %Ndfa than dry matter production. Evidence presented also indicated that %Ndfa of other crops and lucerne in this region may similarly be influenced by soil mineral N. The regression approach presented provides a statistical basis to approximate N2 fixation in the first instance. This work highlights some of the dangers of fitting single regressions to aggregated datasets and using these to approximate symbiotic N2 fixation. The analysis indicates that where pasture legumes are grown in mixtures with non-legumes, and driven to high dependence on N2 fixation, simple linear regressions may be quite useful, provided that possible differences between species are investigated as the slopes of the regressions between these can be quite different. For crop legumes, where low dependence on N2 fixation can occur at higher mineral N availability, there is a need to carefully consider the intercept term, obtain estimates of mineral N availability, and/or resort to non-linear models. The gross generalisations presented in scatter plots cannot be reliably applied any more specifically, even within the datasets from which they were generated, and in some cases even within legume species between regions. They cannot substitute for direct measurement where any certainty is required under a particular set of defined conditions. [ABSTRACT FROM AUTHOR]

Australia's tidal marshes have suffered significant losses but their recently recognised importance in CO2 sequestration is creating opportunities for their protection and restoration. We compiled all available data on soil organic carbon (OC) storage in Australia's tidal marshes (323 cores). OC stocks in the surface 1 m averaged 165.41 (SE 6.96) Mg OC ha−1 (range 14-963 Mg OC ha−1). The mean OC accumulation rate was 0.55 ± 0.02 Mg OC ha−1 yr−1. Geomorphology was the most important predictor of OC stocks, with fluvial sites having twice the stock of OC as seaward sites. Australia's 1.4 million hectares of tidal marshes contain an estimated 212 million tonnes of OC in the surface 1 m, with a potential CO2-equivalent value of $USD7.19 billion. Annual sequestration is 0.75 Tg OC yr−1, with a CO2-equivalent value of $USD28.02 million per annum. This study provides the most comprehensive estimates of tidal marsh blue carbon in Australia, and illustrates their importance in climate change mitigation and adaptation, acting as CO2 sinks and buffering the impacts of rising sea level. We outline potential further development of carbon offset schemes to restore the sequestration capacity and other ecosystem services provided by Australia tidal marshes. [ABSTRACT FROM AUTHOR]