Jeffrey A. Baldock

A statistical framework we call CQUESST (Carbon Quantification and Uncertainty from Evolutionary Soil STochastics), which models carbon sequestration and cycling in soils, is applied to a long-running agricultural experiment that controls for crop type, tillage, and season. The experiment, known as the Millenium Tillage Trial (MTT), ran on 42 field-plots for 10 years from 2000–2010; here CQUESST is used to model soil carbon dynamically in six pools, in each of the 42 agricultural plots, and on a monthly time step for a decade. We show how CQUESST can be used to estimate soil-carbon cycling rates under different treatments. Our methods provide much-needed statistical tools for quantitatively inferring the effectiveness of different experimental treatments on soil-carbon sequestration. The decade-long data are of multiple observation types, and these interacting time series are ingested into a fully Bayesian model that has a dynamic stochastic model of multiple pools of soil carbon at its core. CQUESST’s stochastic model is motivated by the deterministic RothC soil-carbon model based on nonlinear difference equations. We demonstrate how CQUESST can estimate soil-carbon fluxes for different experimental treatments while acknowledging uncertainties in soil-carbon dynamics, in physical parameters, and in observations. An important outcome of our modeling is the inference of cropping-specific decay rates, with evidence suggesting that soil carbon decay-rates vary as a function of land management practices. CQUESST is implemented efficiently in the probabilistic programming language Stan using its MapReduce parallelization, and it scales well for large numbers of field-plots, using software libraries that allow for computation to be shared over multiple nodes of high-performance computing clusters.

The allocation of soil organic carbon (SOC) to its component fractions can indicate the vulnerability of organic carbon stocks to change. The impact of vetiver on the composition and distribution of SOC can provide a complete assessment of its potential to sequester carbon in soil.Purpose: This study quantified the distribution and impact of SOC under vetiver and the allocation of SOC to particulate (POC), humus (HOC) and resistant (ROC) fractions differentiated based on particle size and chemical composition under vetiver grass compared with other plant types.Methods: Carbon fractions were measured on soil samples collected from Australia and Ethiopia to a depth of 1.0 m under three plant communities (vetiver, coffee, and Australian native pastures). We used the MIR/PLSR spectra to estimate SOC fractions based on fractionated, and NMR measured values.Results: The stocks of SOC fractions indicated significant differences in the proportion of labile POC to HOC across sites and vegetation types. The dominant carbon fraction was HOC (71%) for all vegetation types. The average carbon sequestration rate under vetiver for OC was − 2.64 to + 7.69 Mg C ha^− 1 yr^− 1, while for the POC, HOC and ROC was 0.04 to + 1.17, -3.36 to + 4.64 and − 0.35 to + 1.51 Mg C ha^− 1 yr^− 1, respectively.Conclusion: Growing vetiver and undisturbed native pastures has on average a high accumulation rate of a more stable carbon (HOC) which is less vulnerable to change, and change was largely driven by the HOC fraction. We, therefore, recommend the use and promotion of perennial tropical grasses like vetiver and similar grasses and undisturbed native pastures as potential options to facilitate soil carbon sequestration.

Context: Defining soil organic carbon (SOC) ‘potential’ storage, underpins the economic feasibility of carbon sequestration; however, ‘potential’ storage is not quantifiable using historical and current empirical data. We propose a framework to define ‘attainable’ SOC storage that varies with soil properties, environmental conditions and management practices. Aims: Within the soil fine fraction, we quantified additional storage capacity of the fine fraction SOC attainable deficit (FFSOC_Attainable_Def) by the difference between attainable (FFSOC_Attainable) and actual fine fraction SOC. Methods: Using three analyses, we developed a framework to: (1) estimate the FFSOC_Attainable_Def of the fine fraction of Australian agricultural soils within broad mean annual precipitation ranges and soil depth classes; (2) establish rapid prediction capability for the FFSOC_Attainable_Def using infrared/partial least square regression modelling; and (3) generate spatial FFSOC_Attainable_Def estimates for agricultural regions with ensemble Random Forest modelling. Key results: Global analyses of FFSOC_Attainable_Def do not consider key environmental drivers of carbon inflows and outflows nor soil depth. Separate analyses of soils derived from different combinations of precipitation and soil depth need to include variations in environmental conditions and soil properties to accurately define FFSOC_Attainable and FFSOC_Attainable_Def within the fine fraction. Spatially estimated FFSOC_Attainable_Def stocks revealed an opportunity to increase current fine fraction SOC stock by 3.47 GT (0–0.10 m depth) and 3.24 GT (0.10–0.30 m depth). Conclusions: Our findings suggests that FFSOC_Attainable_Def is dynamic, not static. Caution is needed when interpreting the results from this analysis. Implications: Deriving estimates of FFSOC_Attainable_Def will reduce risks in decision making on carbon farming in national policies.

Plant roots are primary factors to contribute to surface and deep soil carbon sequestration (SCS). Perennial grasses like vetiver produce large and deep root system and are likely to contribute significantly to soil carbon. However, we have limited knowledge on how root and shoot decomposition differ and their contribution to SCS. This study examined biomass production and relative decomposition of vetiver which was grown under glasshouse conditions. Subsequently the biomass incubated for 206 days, and the gas analysed using ANCA-GSL. The results confirmed large shoot and root production potential of 161 and 107 Mg ha⁻¹ (fresh) and 67.7 and 52.5 Mg ha⁻¹ (dry) biomass, respectively with 1:1.43 (fresh) and 1:1.25 (dry) production ratio. Vetiver roots decomposed more rapidly in the clay soil (p < 0.001) compared with the shoots, which could be attributed to the lower C:N ratio of roots than the shoots. The large root biomass produced does indeed contribute more to the soil carbon accumulation and the faster root decomposition is crucial in releasing the carbon in the root exudates and would also speed up its contribution to stable SOM. Hence, planting vetiver and similar tropical perennial grasses on degraded and less fertile soils could be a good strategy to rehabilitate degraded soils and for SCS.

The ratio of isotopes of carbon (¹³C:¹²C or δ¹³C) and nitrogen (¹⁵N:¹⁴N or δ¹⁵N) are common indicators of the flow and storage of organic matter in coastal wetland research. Effective use of these indicators requires quantification and understanding of: (1) the variability of isotope signatures of potential organic matter source materials; and (2) the influence of organic matter decomposition on isotopic signatures. While it is well-established that organic matter characteristics change during the decomposition process, there has been little direct quantification of any concurrent shifts in isotope signatures for coastal detritus. In this study, we addressed this by quantifying: (1) shifts in sample composition using solid-state ¹³C Nuclear Magnetic Resonance (NMR) spectroscopy; and (2) shifts in δ¹³C and δ¹⁵N signatures of coastal plant tissues from field litterbag experiments. We observed significant shifts in ¹³C NMR spectra across the course of deployment for all four plant tissues assessed (leaves of mangrove Avicennia marina; branchlets of supratidal tree Casuarina glauca; leaf wrack and roots/rhizomes of the seagrass Zostera muelleri), driven largely by the preferential loss of labile constituents and concentration of more resistant macromolecules, such as lignin and leaf waxes. While there were shifts in isotope ratios for all species, these varied in direction and magnitude among species, tissue type and isotopes. This included δ¹³C enrichments of up to 3.1‰ and 2.4‰ in leaves of A. marina, and branchlets of C. glauca, respectively, but δ¹³C depletions of up to 4.0‰ for Z. muelleri. Shifts in δ¹⁵N varied among species and tissue types, with few clear temporal patterns. Partial least squares regression analyses showed that some tissue isotope signatures can be reliably predicted on the basis of sample composition (¹³C NMR spectra), however, multiple inter- and intra-species variations preclude a simple explanation of isotopic signature shifts on the basis of plant-material molecular shifts alone. Further, we cannot preclude the potential influence of microbe-associated organic matter on sample composition or isotopic signatures. Our findings emphasise the importance of considering decomposition effects on stable isotope signatures in blue carbon ecosystems. Isotope approaches will remain a valuable tool in coastal ecosystem research, but require robust experimental approaches (including appropriate use of decomposed end-members or fractionation correction factors; quantification of microbial organic matter) and quantification of decomposition dynamics for specific plant tissues and environmental settings.

Coastal wetlands are carbon and nutrient sinks that capture large amounts of atmospheric CO2 and runoff of nutrients. ‘Blue carbon’ refers to carbon stored within resident vegetation (e.g. mangroves, tidal marshes and seagrasses) and soil of coastal wetlands. This study aimed to quantify the impact of vegetation type on soil carbon stocks (organic and inorganic) and nitrogen in the surface soils (0–10 cm) of mangroves and tidal marsh habitats within nine temperate coastal blue carbon wetlands in South Australia. Results showed differences in surface soil organic carbon stocks (18.4 Mg OC ha–1 for mangroves; 17.6 Mg OC ha–1 for tidal marshes), inorganic carbon (31.9 Mg IC ha–1 for mangroves; 35.1 Mg IC ha–1 for tidal marshes), and total nitrogen (1.8 Mg TN ha–1 for both) were not consistently driven by vegetation type. However, mangrove soils at two sites (Clinton and Port Augusta) and tidal marsh soils at one site (Torrens Island) had larger soil organic carbon (SOC) stocks. These results highlighted site-specific differences in blue carbon stocks between the vegetation types and spatial variability within sites. Further, differences in spatial distribution of SOC within sites corresponded with variations in soil bulk density (BD). Results highlighted a link between SOC and BD in blue carbon soils. Understanding the drivers of carbon and nitrogen storage across different blue carbon environments and capturing its spatial variability will help improve predictions of the contribution these ecosystems to climate change mitigation.

The stock of organic carbon contained within a soil represents the balance between inputs and losses. Inputs are defined by the ability of vegetation to capture and retain carbon dioxide, effects that management practices have on the proportion of captured carbon that is added to soil and the application organic amendments. The proportion of organic amendment carbon retained is defined by its rate of mineralisation. In this study, the rate of carbon mineralisation from 85 different potential soil organic amendments (composts, manures, plant residues and biosolids) was quantified under controlled environmental conditions over a 547 day incubation period. The composition of each organic amendment was quantified using nuclear magnetic resonance and mid- and near-infrared spectroscopies. Cumulative mineralisation of organic carbon from the amendments was fitted to a two-pool exponential model. Multivariate chemometric algorithms were derived to allow the size of the fast and slow cycling pools of carbon to be predicted from the acquired spectroscopic data. However, the fast and slow decomposition rate constants could not be predicted suggesting that prediction of the residence time of organic amendment carbon in soil would likely require additional information related to soil type, environmental conditions, and management practices in use at the site of application.