Abstract

Sea level rise–induced salinization is projected to influence the decomposition of soil carbon (C) in tidal wetlands. Despite evidence showing that microbial metabolism can determine the fate of soil C decomposition, the response of microbial metabolism to salinization in tidal wetlands remains largely unknown. Microbial metabolism is impacted by the microbial metabolic limitation and carbon use efficiency (CUE), which can provide mechanistic insights into soil C decomposition. Here, we measured microbial metabolic limitation, microbial CUE, and extracellular enzyme activities along an estuarine salinity gradient ranging from freshwater (0.1 ± 0.1 mg g−1) to oligohaline (2.1 ± 0.5 mg g−1) in a tidal wetland. Overall, microorganisms were limited by phosphorus (P) in the tidal wetlands, where salinization increased microbial P limitation by 34%. The enhanced microbial P limitation was attributed to increases in soil C:P and belowground biomass, as well as decreases in root C:P with increasing salinity. Microbial CUE decreased from 0.38 to 0.33 as salinity increased, while microbial P limitation was negatively correlated with microbial CUE, representing the trade-off between the two. Furthermore, microbial P limitation was positively associated with C-, nitrogen (N)-, and P-acquiring extracellular enzyme activities, while all these enzyme activities were negatively correlated with microbial CUE. These results illustrate that to balance microbial P limitation with salinization, microorganisms transfer more energy from the microbial CUE to extracellular enzyme production, and this was the mechanism underlying the trade-off. Microorganisms were also limited by C in the tidal wetlands. However, as the increasing belowground biomass alleviated microbial C limitation with salinization, no relationship was observed between microbial C limitation and CUE. Future C and nutrient models aimed to simulate tidal wetland ecosystem responses to salinization will benefit from the inclusion of trade-off between microbial CUE and microbial P limitation for more accurate prediction.

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