Zhongkui Luo

Potential soil organic carbon stock and its uncertainty under various cropping systems in Australian cropland

The diversity of cropping systems and its variation could lead to great uncertainty in the estimation of soil organic carbon (SOC) stock across time and space. Using the pre-validated Agricultural Production Systems Simulator, we simulated the long-term (1022 years) SOC dynamics in the top 0.3 m of soil at 613 reference sites under 59 representative cropping systems across Australia’s cereal-growing regions. The point simulation results were upscaled to the entire cereal-growing region using a Monte Carlo approach to quantify the spatial pattern of SOC stock and its uncertainty caused by cropping system and environment. The predicted potential SOC stocks at equilibrium state ranged from 10 to 140 t ha–1, with the majority in a range 30–70 t ha–1, averaged across all the representative cropping systems. Cropping system accounted for ~10% of the total variance in predicted SOC stocks. The type of cropping system that determined the carbon input into soil had significant effects on SOC sequestration potential. On average, the potential SOC stock in the top 0.3 m of soil was 30, 50 and 60 t ha–1 under low-, medium- and high-input cropping systems in terms of carbon input, corresponding to –2, 18 and 26 t ha–1 of SOC change. Across the entire region, the Monte Carlo simulations showed that the potential SOC stock was 51 t ha–1, with a 95% confidence interval ranging from 38 to 64 t ha–1 under the identified representative cropping systems. Overall, predicted SOC stock could increase by 0.99 Pg in Australian cropland under the identified representative cropping systems with optimal management. Uncertainty varied depending on cropping system, climate and soil conditions. Detailed information on cropping system and soil and climate characteristics is needed to obtain reliable estimates of potential SOC stock at regional scale, particularly in cooler and/or wetter regions.

Using systems modelling to explore the potential for root exudates to increase phosphorus use efficiency in cereal crops

Enhanced citrate release from crop roots has been one of the recent breeding targets for increased phosphorus (P) use efficiency (PUE), due to the potential of root citrate to solubilise soil P. However, it is unclear about the level of citrate efflux required to significantly impact on crop PUE in different soils. This paper presents a modelling approach to assess the field level impact of root exudates on crop PUE. The farming systems model, APSIM, was modified to include the effect of root citrate efflux on P availability in soil, crop P uptake and growth. With parameters derived from literature, the model was used to simulate the long-term impact of root citrate across soil and climatic conditions. Preliminary results showed contrasting long-term and short-term impacts due to either the accumulated effect of solubilisation or the depletion of soil P reserve. The major impact of enhanced citrate efflux is to increase the efficiency of applied P. The enhanced model enables simulations of a wide range of combinations of Genotype by Environment by Management (GxExM) scenarios, to address knowledge gaps, and to assist in design of field testing for validating the performance of new wheat varieties across environments. Highlights? Citrate release from plant roots can solubilize phosphorus (P) bonded in soil. ? It is unclear how much citrate is required to significantly impact on crop P use efficiency (PUE). ? A modelling approach is developed to assess impact of citrate efflux on crop PUE. ? It enables to explore short and long-term impact of citrate efflux on crop PUE. ? Results show major impact of enhanced citrate efflux is to increase the PUE of applied P.

Fresh carbon input differentially impacts soil carbon decomposition across natural and managed systems

The amount of fresh carbon input into soil is experiencing substantial changes under global change. It is unclear what will be the consequences of such input changes on native soil carbon decomposition across ecosystems. By synthesizing data from 143 experimental comparisons, we show that, on average, fresh carbon input stimulates soil carbon decomposition by 14%. The response was lower in forest soils (1%) compared with soils from other ecosystems (> 24%), and higher following inputs of plant residue-like substrates (31%) compared to root exudate-like substrates (9%). The responses decrease with the baseline soil carbon decomposition rate under no additional carbon input, but increase with the fresh carbon input rate. The rates of these changes vary significantly across ecosystems and with the carbon substrates being added. These findings can be applied to provide robust estimates of soil carbon balance across ecosystems under changing aboveground and belowground inputs as consequence of climate and land management changes.

Critical carbon input to maintain current soil organic carbon stocks in global wheat systems.

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha−1 yr−1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Contrasting Effects of Agricultural Management on Soil Organic Carbon Balance in Different Agricultural Regions of China

Improving management of soil organic carbon (SOC) has been considered as a substantial mitigation strategy to climate change. Management such as stubble retention (SR), conservation tillage (ZT), and fertilization are recommended for both promoting production and accumulating SOC. However, whether such management practices can cause net increase in SOC or just a slow-down of SOC decline largely depends on the current status of SOC for a given region. This paper synthesized the available SOC data in the croplands of China, and analysed the change of SOC in the top 20 cm soil as a result of management change. The results showed that, on average, SOC increased by 18.3% through SR, by 9.1% through ZT, and by 12.4%, 36.9% and 41.5% through application of inorganic (IF), organic (OF) and combined inorganic and organic fertilizers (IOF), respectively, compared to those under stubble removal, conventional tillage and no fertilization. Under SR, ZT, IF, OF and IOF, SOC increased by 16.0%, 10.2%, 8.2%, 32.2% and 41.3%, respectively, at the end of the trials compared with the initial values at the start of the trials. Our analysis also showed that in Northeast and Northwest China, SOC in agricultural soils is still decreasing due to cultivation. In North and South China, however, SOC appears to have reached a new equilibrium of low SOC state after a long cultivation history, and soils have greater potential to sequester C. Our analysis highlights the need of taking account of the baseline status to assess the net soil C balance over time and space.

Modelling the dynamic physical protection of soil organic carbon: Insights into carbon predictions and explanation of the priming effect

The role and significance of physically protected soil organic carbon (SOC) in regulating SOC dynamics remains unclear. Here, we developed a simple theoretical model (DP model) considering dynamic physical protection to simulate the dynamics of protected (Cp ) and unprotected SOC (Cu ), and compared the modelling results with a conventional two-pool (fast vs. slow) model considering chemical recalcitrance. The two models were first constrained using extensive SOC data collected from soils with and without fresh carbon (C) inputs under incubation conditions, and then applied to project SOC dynamics and explore mechanisms underpinning the priming effect (PE). Overall, both models explained more than 99% of the variances in observed SOC dynamics. The DP model predicted that Cp accounted for the majority of total SOC. As decomposition proceeds, the proportion of Cp reached >90% and kept relatively constant. Although the similar performance of the two models in simulating observed total SOC dynamics, their predictions of future SOC dynamics were divergent, challenging the predictions of widely used pool-based models. The DP model also suggested alternative mechanisms underpinning the priming of SOC decomposition by fresh C inputs. The two-pool model suggested that the PE was caused by the stimulated decomposition rates, especially for the slow recalcitrant pool, while the DP model suggested that the PE might be the combined consequence of stimulated Cu decomposition, the liberation of Cp to decomposition and the inhibition of the protection of unprotected SOC. The model-data integration provided a new explanation for the PE, highlighting the importance of liberation of initially physically protected SOC to decomposition by new C inputs. Our model-data integration demonstrated the importance of simulating physical protection processes for reliable SOC predictions, and provided new insights into mechanistic understanding of the priming effect.

Confidence in soil carbon predictions undermined by the uncertainties in observations and model parameterisation

Soil carbon (C) responds quickly and feedbacks significantly to environmental changes such as climate warming and agricultural management. Soil C modelling is the only reasonable approach available for predicting soil C dynamics under future conditions of environmental changes, and soil C models are usually constrained by the average of observations. However, model constraining is sensitive to the observed data, and the consequence of using observed averages on C predictions has rarely been studied. Using long-term soil organic C datasets from an agricultural field experiment, we constrained a process-based model using the average of observations or by taking into account the variation in observations to predict soil C dynamics. We found that uncertainties in soil C predictions were masked if ignoring the uncertainties in observations (i.e., using the average of observations to constrain model), if uncertainties in model parameterisation were not explicitly quantified. However, if uncertainties in model parameterisation had been considered, further considering uncertainties in observations had negligible effect on uncertainties in SOC predictions. The results suggest that uncertainties induced by model parameterisation are larger than that induced by observations. Precise observations representing the real spatial pattern of SOC at the studied domain, and model structure improvement and constrained space of parameters will benefit reducing uncertainties in soil C predictions. The results also highlight some areas on which future C model development and software implementations should focus to reliably infer soil C dynamics. We simulate observed soil carbon dynamics using different calibration strategies.Different model initialisation and/or parameterisation cause divergent predictions.Ignoring uncertainty in observations results in biased predictions.Robust prediction needs accurate observations and constrained parameter space.

Effects of temperature, soil substrate, and microbial community on carbon mineralization across three climatically contrasting forest sites

Abstract How biotic and abiotic factors influence soil carbon (C) mineralization rate (R S) has recently emerged as one of the focal interests in ecological studies. To determine the relative effects of temperature, soil substrate and microbial community on R s, we conducted a laboratory experiment involving reciprocal microbial inoculations of three zonal forest soils, and measured R S over a 61‐day period at three temperatures (5, 15, and 25°C). Results show that both R s and the cumulative emission of C (R cum), normalized to per unit soil organic C (SOC), were significantly affected by incubation temperature, soil substrate, microbial inoculum treatment, and their interactions (p < .05). Overall, the incubation temperature had the strongest effect on the R S; at given temperatures, soil substrate, microbial inoculum treatment, and their interaction all significantly affected both R s (p < .001) and R cum (p ≤ .01), but the effect of soil substrate was much stronger than others. There was no consistent pattern of thermal adaptation in microbial decomposition of SOC in the reciprocal inoculations. Moreover, when different sources of microbial inocula were introduced to the same soil substrate, the microbial community structure converged with incubation without altering the overall soil enzyme activities; when different types of soil substrate were inoculated with the same sources of microbial inocula, both the microbial community structure and soil enzyme activities diverged. Overall, temperature plays a predominant role in affecting R s and R cum, while soil substrate determines the mineralizable SOC under given conditions. The role of microbial community in driving SOC mineralization is weaker than that of climate and soil substrate, because soil microbial community is both affected, and adapts to, climatic factors and soil matrix.