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  • Title: The regional variation of denitrification phenotypes under anoxic incubation with soils from eight forested catchments in different climate zones of China.
    Author: Cui J, Zhu J, Wang Z, Mulder J, Wang B, Zhang X.
    Journal: Sci Total Environ; 2018 Feb 15; 615():319-329. PubMed ID: 28982081.
    Abstract:
    Denitrification characteristics of forest soils from eight headwater catchments in China were investigated in this study, along a climatic gradient from the tropics in the South to the temperate zones. Within each catchment, different landscape positions along hydrological flow paths were also considered, including well-drained soils on hill slopes and poorly drained soils in groundwater discharge zones. The results showed that instantaneous denitrification rates were much greater in soils from the northern sites than those from the southern sites (with the average of 110.0 and 25.4nmolNg-1drysoilh.-1, respectively). Large potentials for nitrous oxide (N2O) loss (evaluated as maximum N2O accumulation before it was reduced to dinitrogen (N2)) were observed in the six tropical and subtropical catchments, particularly in soils with high carbon (C) and nitrogen (N). Meanwhile high N2O/(N2O+N2) stoichiometries were displayed in soils from these southern sites. Within catchments, soils from the groundwater discharge zones showed greater potential denitrification rates but smaller N2O/(N2O+N2) ratios in comparison with those on the hill slopes, implying large N removal potentials of soils from the groundwater discharge zones. Furthermore, our findings suggest soil pH is the key controller for the potential denitrification rates and the N2O/(N2O+N2) stoichiometries. Soil pH, C and N availability affect the potential for N2O loss synergistically. Our findings not only pinpoint the denitrification phenotypes of soils along the climatic gradient, but also confirm the small-scale variations within catchments which reflect the in situ habitat of the denitrifiers. These indicate the importance of discrimination related to different landscape positions when modeling N2O emissions and N removals from regional N loading.
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