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Nontidal wetlands are estimated to contribute significantly to the soil carbon pool across the globe. However, our understanding of the occurrence and variability of carbon storage between wetland types and across regions represents a major impediment to the ability of nations to include wetlands in greenhouse gas inventories and carbon offset initiatives. We performed a large-scale survey of nontidal wetland soil carbon stocks and accretion rates from the state of Victoria in south-eastern Australia-a region spanning 237,000 km 2 and containing >35,000 temperate, alpine, and semi-arid wetlands. From an analysis of >1,600 samples across 103 wetlands, we found that alpine wetlands had the highest carbon stocks (290 ± 180 Mg C org ha -1 ), while permanent open freshwater wetlands and saline wetlands had the lowest carbon stocks (110 ± 120 and 60 ± 50 Mg C org ha -1 , respectively). Permanent open freshwater sites sequestered on average three times more carbon per year over the last century than shallow freshwater marshes (2.50 ± 0.44 and 0.79 ± 0.45 Mg C org ha -1  year -1 , respectively). Using this data, we estimate that wetlands in Victoria have a soil carbon stock in the upper 1 m of 68 million tons of C org , with an annual soil carbon sequestration rate of 3 million tons of CO 2 eq. year -1 -equivalent to the annual emissions of about 3% of the state's population. Since European settlement (~1834), drainage and loss of 260,530 ha of wetlands may have released between 20 and 75 million tons CO 2 equivalents (based on 27%-90% of soil carbon converted to CO 2 ). Overall, we show that despite substantial spatial variability within wetland types, some wetland types differ in their carbon stocks and sequestration rates. The duration of water inundation, plant community composition, and allochthonous carbon inputs likely play an important role in influencing variation in carbon storage., (© 2018 John Wiley & Sons Ltd.)

Understanding soil organic carbon (SOC) sequestration is important to develop strategies to increase the SOC stock and, thereby, offset some of the increases in atmospheric carbon dioxide. Although the capacity of soils to store SOC in a stable form is commonly attributed to the fine (clay + fine silt) fraction, the properties of the fine fraction that determine the SOC stabilization capacity are poorly known. The aim of this study was to develop an improved model to estimate the SOC stabilization capacity of Allophanic (Andisols) and non-Allophanic topsoils (0-15 cm) and, as a case study, to apply the model to predict the sequestration potential of pastoral soils across New Zealand. A quantile (90th) regression model, based on the specific surface area and extractable aluminium (pyrophosphate) content of soils, provided the best prediction of the upper limit of fine fraction carbon (FFC) (i.e. the stabilization capacity), but with different coefficients for Allophanic and non-Allophanic soils. The carbon (C) saturation deficit was estimated as the difference between the stabilization capacity of individual soils and their current C concentration. For long-term pastures, the mean saturation deficit of Allophanic soils (20.3 mg C g -1 ) was greater than that of non-Allophanic soils (16.3 mg C g -1 ). The saturation deficit of cropped soils was 1.14-1.89 times that of pasture soils. The sequestration potential of pasture soils ranged from 10 t C ha -1 (Ultic soils) to 42 t C ha -1 (Melanic soils). Although meeting the estimated national soil C sequestration potential (124 Mt C) is unrealistic, improved management practices targeted to those soils with the greatest sequestration potential could contribute significantly to off-setting New Zealand's greenhouse gas emissions. As the first national-scale estimate of SOC sequestration potential that encompasses both Allophanic and non-Allophanic soils, this serves as an informative case study for the international community., (© 2017 John Wiley & Sons Ltd.)

Subsoils contain large amounts of organic carbon which is generally believed to be highly stable when compared with surface soils. We investigated subsurface organic carbon storage and dynamics by analysing organic carbon concentrations, fractions and isotopic values in 78 samples from 12 sites under different land-uses and climates in eastern Australia. Despite radiocarbon ages of several millennia in subsoils, contrasting native systems with agriculturally managed systems revealed that subsurface organic carbon is reactive on decadal timeframes to land-use change, which leads to large losses of young carbon down the entire soil profile. Our results indicate that organic carbon storage in soils is input driven down the whole profile, challenging the concept of subsoils as a repository of stable organic carbon., (© 2016 John Wiley & Sons Ltd.)

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]