Unique genes carried by abundant species enhance CH4 emissions during the growing season at the Tibetan Plateau

CH4 emission rates followed an increased pattern during the growing season at Tibetan Plateau.•Unique genes carried by abundant species were positively correlated with CH4 emission rates.•Climate factors influenced CH4 emission rates by regulating microbial community and their genes.Microorganisms play pivotal roles in soil methane(CH4)emissions and their functional genes are origins of a key mechanism for soil CH4-cycling.However,understanding of the roles of specific genes(e.g.,unique or shared genes carried by species)underlying CH4-cycling remains elusive.Here,we measured CH4 emission rates and investigated variations in microbial community and the abundance of genes carried by species during the growing season in alpine meadow on the Tibetan Plateau.We discovered that CH4 emission rates increased from 394.4,745.9,and 1092.7µg CH4 m−2 h−1,in April,June,and August,respectively,and had a positive correlation with unique genes carried by abundant species during the growing season.Moreover,we found that unique genes carried by abundant species involved in methanogenesis processes have a higher abundance than methanotrophic processes.Further analysis indicated that climate factors(i.e.,mean monthly temperature(MMT)and mean monthly precipitation(MMP))influenced microbial community and their functional genes,and therefore affected the CH4 emission rates.Overall,the present study provides a novel insight into the variation of soil CH4 emissions from a functional gene perspective,highlighting the important roles of unique genes carried by abundant species in CH4 emissions in the Tibetan Plateau under seasonal variation.

A novel terbium metal-organic framework for luminescence sensing of pyridine:Synthesis,structure,selectivity,sensitivity and recyclability

One novel two-dimensional(2D)terbium-based framework[Tb(L2-)(Ac)(DMA)]n(1)(H2 L=4’-(3,5-dicarboxyphenyl)-4,2’:6’,4"-terpyridine)was successfully isolated and structurally characterized.The structural analysis reveals that two Tb3+ions in 1 are bridged by twoη1:η1:μ2 carboxylates from L2-to form a binuclear unit,which is further linked by L2-to generate a 2D layer with kgd topology.Moreover,1 displays excellent thermostability and extensive solvent stability.Luminescent measurements reveal that 1 can be used as a recyclable luminescent probe for detecting pyridine with the lowest detection lim it of 0.12 vol%,and the luminescent mechanism is also discussed.

Modeling methane dynamics in three wetlands in Northeastern China by using the CLM-Microbe model

Wetlands account for up to 70%of the natural source of methane(CH_(4))in terrestrial ecosystems on a global scale.Soil microbes are the ultimate producers and biological consumers of CH_(4)in wetlands.Therefore,simulating microbial mechanisms of CH_(4)production and consumptionwould improve the predictability of CH_(4)flux in wetland ecosystems.In this study,we applied a microbial-explicit model,the CLM-Microbe,to simulate CH_(4)flux in three major natural wetlands in northeastern China.The CLM-Microbe model was able to capture the seasonal variation of gross primary productivity(GPP),dissolved organic carbon(DOC),and CH_(4)flux.The CLM-Microbe model explained more than 40%of the variation in GPP and CH_(4)flux across sites.Marsh wetlands had higher CH_(4)flux than mountain peatlands.Ebullition dominated the CH_(4)transport pathway in all three wetlands.The methanogenesis dominates while methanotroph makes a minor contribution to the CH_(4)flux,making all wetlands a CH_(4)source.Sensitivity analysis indicated that microbial growth and death rates are the key factors governing CH_(4)emission and vegetation physiological properties(flnr)and maintenance respiration predominate GPP variation.Explicitly simulating microbial processes allows genomic information to be incorporated,laying a foundation for better predicting CH_(4)dynamics under the changing environment.

人为管理措施诱导土壤微生物磷与土壤微生物碳氮内稳态解耦的代谢证据

微生物化学计量学理论能够预测微生物对碳(C)、氮(N)、磷(P)的同化作用具有比例耦合性。这种耦合性被量化为稳态值,用于计算内稳性系数(H)。C、N、P的H值协变量表明,微生物对C、N、P的同化作用是耦合的。因此,在本文中我们利用全球数据集研究微生物C、N、P的H值在不同生物群落中的时空动态变化。研究结果表明,土地利用和人为管理措施导致P与C、N的代谢在时间和空间上解耦,并且我们利用结构方程模型(SEM)分析结果表明,土壤因子主导P的微生物动态平衡,而土壤元素含量则主导C和N的微生物动态平衡。利用机器学习算法得出的微生物P与微生物C和N的对比因子也证实了这一结果。总的来说,我们的研究强调了在营养循环中人为管理措施对微生物角色转变具有重要的影响。