Abstract
Soil carbon (C) and nitrogen (N) cycles and their complex responses to hydro-climatic forcing have gained increasing attention. While the temperature effects have been intensively studied, soil moisture response functions (SMRFs) are not well documented for various microbial and enzymatic processes due to the difficulties in directly measuring and differentiating the moisture effects on various processes. Here we extended our C-only Microbial-ENzyme Decomposition (MEND) model to the C-N coupled MEND model with flexible element stoichiometry. Our model calibration showed good agreement between simulated and observed C:N ratios in soil organic matter and microbial biomass, as well as the ammonium and nitrate concentrations. We show that the selection of SMRFs for specific biogeochemical processes could result in significant differences in model simulated microbial and C-N processes. In particular, it is essential to account for the soil moisture effects on microbial dormancy and resuscitation, as the changes in microbial physiology under favorable or stressful conditions will exert strong controls on soil C and N dynamics. We also advocate the utilization of dynamic (time-variant) data (e.g., litter input, N deposition, soil temperature and moisture), instead of time-invariant data, to drive model simulations and analyses. Dynamic forcing data (particularly dynamic soil moisture) better represent the real-world climate and environmental conditions, which could facilitate more realistic modeling and understanding of soil C and nutrient cycling in a changing world.
| Original language | English |
|---|---|
| Article number | 124777 |
| Journal | Journal of Hydrology |
| Volume | 585 |
| DOIs | |
| State | Published - Jun 2020 |
Funding
This study was supported by the U.S. Department of Energy , Office of Science, Genomic Science Program under Award Number DE-SC0004730 , DE-SC001057 , DE-SC0004601 , DE-SC0014079 , DE-SC0016247 , and DE-SC0010715 , and the Office of the Vice President for Research at the University of Oklahoma . This work was also supported by the U.S. Department of Energy (DOE) Office of Biological and Environmental Research through the Terrestrial Ecosystem Science Scientific Focus Area at Oak Ridge National Laboratory (ORNL). W.H. and G.Z. were supported by the National Natural Science Foundation of China (Grant Numbers 31670487 , 41430529 , and 31600353 ). We thank Drs. Tianfeng Han, Xiaodong Liu, Deqiang Zhang and Qianmei Zhang for conducting field experiments and data collection. ORNL is managed by the University of Tennessee - Battelle , LLC, under contract DE- AC05-00OR22725 with the U.S. DOE . Model code and data are accessible upon request at https://[email protected]/wanggangsheng/menddhs.git. This study was supported by the U.S. Department of Energy, Office of Science, Genomic Science Program under Award Number DE-SC0004730, DE-SC001057, DE-SC0004601, DE-SC0014079, DE-SC0016247, and DE-SC0010715, and the Office of the Vice President for Research at the University of Oklahoma. This work was also supported by the U.S. Department of Energy (DOE) Office of Biological and Environmental Research through the Terrestrial Ecosystem Science Scientific Focus Area at Oak Ridge National Laboratory (ORNL). W.H. and G.Z. were supported by the National Natural Science Foundation of China (Grant Numbers 31670487, 41430529, and 31600353). We thank Drs. Tianfeng Han, Xiaodong Liu, Deqiang Zhang and Qianmei Zhang for conducting field experiments and data collection. ORNL is managed by the University of Tennessee-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. DOE. Model code and data are accessible upon request at https://[email protected]/wanggangsheng/menddhs.git.
Keywords
- Dynamic data
- Microbial dormancy
- Microbial modeling
- Soil carbon and nitrogen
- Soil microbe
- Soil moisture