Reducing the uncertainty in estimating soil microbial-derived carbon storage.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and plays a crucial role in mitigating climate change and enhancing soil productivity. Microbial-derived carbon (MDC) is the main component of the persistent SOC pool. However, current formulas used to estimate the proportional contribution of MDC are plagued by uncertainties due to limited sample sizes and the neglect of bacterial group composition effects. Here, we compiled the comprehensive global dataset and employed machine learning approaches to refine our quantitative understanding of MDC contributions to total carbon storage. Our efforts resulted in a reduction in the relative standard errors in prevailing estimations by an average of 71% and minimized the effect of global variations in bacterial group compositions on estimating MDC. Our estimation indicates that MDC contributes approximately 758 Pg, representing approximately 40% of the global soil carbon stock. Our study updated the formulas of MDC estimation with improving the accuracy and preserving simplicity and practicality. Given the unique biochemistry and functioning of the MDC pool, our study has direct implications for modeling efforts and predicting the land-atmosphere carbon balance under current and future climate scenarios.

Intrinsic microbial temperature sensitivity and soil organic carbon decomposition in response to climate change.

Soil microbes are essential for regulating carbon stocks under climate change. However, the uncertainty surrounding how microbial temperature responses control carbon losses under warming conditions highlights a significant gap in our climate change models. To address this issue, we conducted a fine-scale analysis of soil organic carbon composition under different temperature gradients and characterized the corresponding microbial growth and physiology across various paddy soils spanning 4000 km in China. Our results showed that warming altered the composition of organic matter, resulting in a reduction in carbohydrates of approximately 0.026% to 0.030% from humid subtropical regions to humid continental regions. These changes were attributed to a decrease in the proportion of cold-preferring bacteria, leading to significant soil carbon losses. Our findings suggest that intrinsic microbial temperature sensitivity plays a crucial role in determining the rate of soil organic carbon decomposition, providing insights into the temperature limitations faced by microbial activities and their impact on soil carbon-climate feedback.

Warming Leads to Changes in Soil Organic Carbon Molecules Due to Decreased Mineral Protection.

Climate change affects the content and composition of soil organic carbon (SOC). However, warming-induced changes in the SOC compounds remain unknown. Using nuclear magnetic resonance spectroscopy, molecular mixing models, and Fourier transform ion cyclotron resonance mass spectrometry, we analyzed the variations and relationships in molecular compounds in Mollisol with 10-56 g C kg-1 soil-1 by translocating soils under six climate regimes. We found that increased temperature and precipitation were negatively correlated with carbohydrate versus lipid and lignin versus protein. The former was consistent across soils with varying SOC contents, but the latter decreased as the SOC content increased. The carbohydrate-lipid correlations were related to dithionite-citrate-extractable Fe, while the lignin-protein correlations were linked to changes in moisture and pyrophosphate-extractable Fe/Al. Our findings indicate that the reduction in the mineral protection of SOC is associated with molecular alterations in SOC under warming conditions.

Drivers of microbially and plant-derived carbon in topsoil and subsoil.

Plant- and microbially derived carbon (C) are the two major sources of soil organic matter (SOM), and their ratio impacts SOM composition, accumulation, stability, and turnover. The contributions of and the key factors defining the plant and microbial C in SOM along the soil profile are not well known. By leveraging nuclear magnetic resonance spectroscopy and biomarker analysis, we analyzed the plant and microbial C in three soil types using regional-scale sampling and combined these results with a meta-analysis. Topsoil (0-40 cm) was rich in carbohydrates and lignin (38%-50%), whereas subsoil (40-100 cm) contained more proteins and lipids (26%-60%). The proportion of plant C increases, while microbial C decreases with SOM content. The decrease rate of the ratio of the microbially derived C to plant-derived C (CM:P ) with SOM content was 23%-30% faster in the topsoil than in the subsoil in the regional study and meta-analysis. The topsoil had high potential to stabilize plant-derived C through intensive microbial transformations and microbial necromass formation. Plant C input and mean annual soil temperature were the main factors defining CM:P in topsoil, whereas the fungi-to-bacteria ratio and clay content were the main factors influencing subsoil CM:P . Combining a regional study and meta-analysis, we highlighted the contribution of plant litter to microbial necromass to organic matter up to 1-m soil depth and elucidated the main factors regulating their long-term preservation.

[Algorithms of multiband remote sensing for coastal red tide waters].

The spectral characteristics of the coastal waters in East China Sea was studied using in situ measurements, and the multiband algorithms of remote sensing for bloom waters was discussed and developed. Examples of red tide detection using the algorithms in the East China Sea were presented. The results showed that the algorithms could provide information about the location and the area coverage of the red tide events.