Abstract
Recent developments of enzyme-based decomposition models highlight the importance of enzyme kinetics with warming, but most modeling exercises are based on studies with a step-wise warming. This approach may mask the effect of temperature in controlling in-situ activities as in most ecosystems the rate of warming is more gradual than these step warming studies. We conducted an experiment to test the effects of contrasting warming rates on the kinetics of carbon (C), nitrogen (N), and phosphorus (P) degradation enzymes in subtropical peat soils. We also wanted to evaluate if the stoichiometry of enzyme kinetics shifts under contrasting warming rates and if so, how does it relate to the stoichiometry in microbial biomass. Contrasting warming rates altered microbial biomass stoichiometry leading to differing patterns of microbial demand for C vs. nutrient (N and P) and enzyme expression following the optimum foraging strategy. Activity (higher Vmax) and efficiency (lower Km) of C acquisition enzymes were greater in the step treatment; however, expressions of nutrient (N and P) acquiring enzymes were enhanced in the ramp treatment at the end of the experiment. In the step treatment, there was a typical pattern of an initial peak in the Vmax and drop in the Km for all enzyme groups followed by later adjustments. On the other hand, a consistent increase in Vmax and decline in Km of all enzyme groups were observed in the ramp treatment. These changes were sufficient to alter microbial identity (as indicated by enzyme Km and biomass stoichiometry) with two apparently different endpoints under contrasting warming rates. This observation resembles the concept of alternate stable states and highlights a need for improved representation of warming effects on enzymes in decomposition models. Using peat soils of Florida Everglades, here we have demonstrated that contrasting warming rates can influence the dynamics of microbial and enzymatic kinetics. Hence, we suggest that future laboratory and field warming studies could consider our approach to accurately represent microbial and enzymatic kinetics in biogeochemical models.
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