ABSTRACT
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.
Subject(s)
Carbon , Soil Microbiology , Soil , Carbon/metabolism , Carbon/analysis , Soil/chemistry , Uncertainty , Climate Change , Ecosystem , Bacteria/metabolism , Carbon Sequestration , Machine Learning , Carbon CycleABSTRACT
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.
Subject(s)
Carbon , Climate Change , Soil Microbiology , Soil , Temperature , Soil/chemistry , Carbon/analysis , Carbon/metabolism , China , Bacteria/metabolism , Bacteria/growth & developmentABSTRACT
Fertilizer reduction and efficiency improvement is an important basis for ensuring the safety of the agricultural ecological environment. Microorganisms are the key driving force for regulating the soil nitrogen and phosphorus cycle. Studying the nitrogen and phosphorus transformation function of rhizosphere microorganisms can provide a microbiological regulation approach for further improving the use efficiency of soil nitrogen and phosphorus. Based on the field micro-plot experiments of three typical farmland soils(phaeozem, cambisol, and acrisol), metagenomic sequencing technology was used to study the differences in functional genes and regulatory factors of maize rhizosphere microorganisms during soil nitrogen and phosphorus transformation. The results showed that the functional diversity of maize rhizosphere microorganisms was affected by soil type. The functional diversity of rhizosphere microorganisms in phaeozem and cambisol was mainly affected by water content and nutrient content, and that in acrisol was affected by total phosphorus(TP) and available phosphorus(AP). For soil nitrogen transformation, the gene abundance of related enzymes in the pathway of nitrogen transformation was the highest in the urease gene(ureC) and glucose dehydrogenase gene(gdh), which were 7.25×10-5-12.88×10-5 and 4.47×10-5-7.49×10-5, respectively. The total abundance of assimilatory nitrate reduction functional genes in acrisol was higher than that in phaeozem and cambisol, and the total abundance of functional genes related to other processes was the highest in cambisol. The abundance of functional genes encoding enzymes related to nitrogen metabolism was mainly driven by soil bacterial richness, total potassium(TK), and TP. For soil phosphorus transformation, the number of alkaline phosphatase genes(phoD) catalyzing organic phosphorus mineralization was 1093, and the number of acid phosphatase genes(PHO) was 42. The abundance of phoD was two orders of magnitude higher than that of PHO. In addition, fertilization had no significant effect on the abundance of phoD and PHO in the same soil type. Random forest analysis showed that the abundances of phoD and PHO were significantly affected by soil moisture, organic matter(OM), and total nitrogen(TN), but AP content had the greatest impact on PHO abundance. These results clarified the nitrogen and phosphorus transformation characteristics of maize rhizosphere microorganisms at the functional genomic level and enriched the molecular biological mechanism of the microbial nitrogen and phosphorus transformation function.