Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models

The AMG model coupled with Rock-Eval® analysis accurately predicts cropland soil organic carbon dynamics in the Tuojiang River Basin, Southwest China

Accurate soil organic carbon models are key to understand the mechanisms governing carbon sequestration in soil and to help develop targeted management strategies to carbon budget. The accuracy and reliability of soil organic carbon (SOC) models remains strongly limited by incorrect initialization of the conceptual kinetic pools and lack of stringent model evaluation using time-series datasets. Notably, due to legacy effects of management and land use change, the traditional spin-up approach for initial allocation of SOC among kinetic pools can bring substantial uncertainties in predicting the evolution of SOC stocks. The AMG model can fulfill these conditions as it is a parsimonious yet accurate SOC model using widely-available input data. In this study, we first evaluated the performance of AMGv2 before and after optimizing the potential mineralization rate (k0) of SOC stock following a leave-one-site-out cross-validation based on 24 long-term field experiments (LTEs) in the Southwest of China. Then, we used Rock-Eval® thermal analysis results as input variables in the PARTYSOC machine learning model to estimate the initial stable SOC fraction (CS/C0) for the 14 LTEs where soil samples were available. The results showed that initializing the CS/C0 ratio using PARTYSOC combined with the optimized k0 further improved the accuracy of model simulations (R2 = 0.87, RMSE = 0.25, d = 0.90). Combining average measured CS/C0 and k0 optimization across all 24 LTEs also improved the model predictive capability by 25% compared to using default parameterization, thus suggesting promising avenue for upscaling model applications at the regional level where only a few measurement data on SOC stability can be available. In conclusion, the new version of the AMG model developed in the Tuojiang River Basin context exhibits excellent performance. This result paves the way for further calibration and validation of the AMG model in a wider set of contexts, with the potential to significantly improve confidence in SOC predictions in croplands over regional scales.

Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations

The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.

Soil Organic Carbon Dynamics in Response to Tillage Practices in the Steppe Zone of Southern Russia

Soil organic carbon (SOC) content is a vital indicator for soil health. The use of moldboard (traditional) plowing for many years had led to a prominent decline in the SOC and soil organic matter (SOM) in Southern Russia. Application of no-tillage (NT) is a sustainable alternative to conventional tillage (CT) as it offers an advantage for SOC store. The aim of the study was to assess soil organic carbon dynamics in response to tillage practices in the steppe zone of Southern Russia. The conservation of SOC under different tillage systems (CT and NT) was evaluated in comparison with the soils of the virgin soils (VS) in three different regions of the steppe zone of the Lower Don region (Southern of the European part of Russia). The SOC content under the conditions of CT was significantly lower than that in the VS and demonstrated an inclining trend when using NT technology. We estimate that the transition to NT over an area of 5.5 million hectares will lead to a significant reduction of carbon emissions into the atmosphere (by ~39 × 109 g C/year), thereby SOC deposition will be (~5.1 × 1012 g C) and high economic advantages will be reaped (with cost savings of up to 27%) in the Rostov region of Russia.