It remains unclear how warming will affect resource flows during soil organic matter (SOM) decomposition, in part due to uncertainty in how exoenzymes produced by microbes and roots will function. Rising temperatures can enhance the activity of most exoenzymes, but soil pH can impose limitations on their catalytic efficiency. The effects of temperature and pH on enzyme activity are often examined in environmental samples, but purified enzyme kinetics reveal fundamental attributes of enzymes’ intrinsic temperature responses and how relative release of decay‐liberated resources (their flow ratios) can change with environmental conditions. In this paper, we illuminate the principle that fundamental, biochemical limitations on SOM release of C, N, and P during decay, and differential exoenzymes’ responses to the environment, can exert biosphere‐scale significance on the stoichiometry of bioavailable soil resources. To that end, we combined previously published intrinsic temperature sensitivities of two hydrolytic enzymes that release C and N during decay with a novel data set characterizing the kinetics of a P‐releasing enzyme (acid phosphatase) across an ecologically relevant pH gradient. We use these data to estimate potential change in the flow ratios derived from these three enzymes’ activities (C:N, C:P, and N:P) at the global scale by the end of the century, based on temperature projections and soil pH distribution. Our results highlight how the temperature sensitivity of these hydrolytic enzymes and the influence of pH on that sensitivity can govern the relative availability of bioavailable resources derived from these enzymes. The work illuminates the utility of weaving well‐defined kinetic constraints of microbes’ exoenzymes into models that incorporate changing SOM inputs and composition, nutrient availability, and microbial functioning into their efforts to project terrestrial ecosystem functioning in a changing climate.
Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme‐mediated soil inorganic N processes in the Microbial‐ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C‐N fluxes, microbial C:N ratios, and functional gene abundances from a 12‐year CO2 × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO2fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C‐N‐associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO2concentration. Our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem‐level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.
more » « less- NSF-PAR ID:
- 10363062
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 28
- Issue:
- 5
- ISSN:
- 1354-1013
- Page Range / eLocation ID:
- p. 1935-1950
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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