Journal
FRONTIERS IN MICROBIOLOGY
Volume 14, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2023.1105723
Keywords
climate change; carbon cycle; soil microbial activity; microbial decomposition model; soil respiration (CO2)
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Soil microorganisms are important indicators for evaluating soil health and their role in carbon-climate feedback is vital. This study conducted an observational experiment in the Ziwuling Mountains, Loess Plateau, China, and found that soil respiration rate is significantly correlated with temperature and moisture, indicating that temperature increase leads to soil carbon loss. The study also revealed the crucial factors affecting soil microbial activity and provided valuable scientific implications for constructing microbial decomposition models to predict soil microbial activity under climate change in the future.
Soil microorganisms are critical biological indicators for evaluating soil health and play a vital role in carbon (C)-climate feedback. In recent years, the accuracy of models in terms of predicting soil C pools has been improved by considering the involvement of microbes in the decomposition process in ecosystem models, but the parameter values of these models have been assumed by researchers without combining observed data with the models and without calibrating the microbial decomposition models. Here, we conducted an observational experiment from April 2021 to July 2022 in the Ziwuling Mountains, Loess Plateau, China, to explore the main influencing factors of soil respiration (R-S) and determine which parameters can be incorporated into microbial decomposition models. The results showed that the R-S rate is significantly correlated with soil temperature (T-S) and moisture (M-S), indicating that T-S increases soil C loss. We attributed the non-significant correlation between R-S and soil microbial biomass carbon (MBC) to variations in microbial use efficiency, which mitigated ecosystem C loss by reducing the ability of microorganisms to decompose organic resources at high temperatures. The structural equation modeling (SEM) results demonstrated that T-S, microbial biomass, and enzyme activity are crucial factors affecting soil microbial activity. Our study revealed the relations between T-S, microbial biomass, enzyme activity, and R-S, which had important scientific implications for constructing microbial decomposition models that predict soil microbial activity under climate change in the future. To better understand the relationship between soil dynamics and C emissions, it will be necessary to incorporate climate data as well as R-S and microbial parameters into microbial decomposition models, which will be important for soil conservation and reducing soil C loss in the Loess Plateau.
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