Evaluation and Improvement of the Microbial Enzyme Decomposition (MEND) Model Against Multiple Incubation Experiments

Siyang Jian, Tennessee State University


This dissertation contains one incubation study and two modeling studies to represent the attempt of improving the accuracy of the MEND model simulations and soil organic carbon projections under environmental change. First a comprehensive literature review was conducted to demonstrate the current progress and knowledge gaps in the research field of soil microbial modeling. This laid out a strong foundation for the necessity of conducting the current study. In the soil incubation study, a 180-day experiment was conducted to examine the main and interactive effects of temperature and nitrogen (N) fertilization on soil heterotrophic respiration, exoenzyme activities and microbial dynamics in a switchgrass cropland. The results showed no interaction, but significantly individual effect on soil respiration. And the effects of temperature and N fertilization are mediated by microbial changes in growth efficiency and stimulated exoenzyme kinetics, respectively. In the first modeling study, microbial parameters in the MEND model were optimized using the short- and long-term incubation datasets (from Oak Ridge National Laboratory) to assess how incubation duration affects model parameterization and long-term projection. This study found parameters derived from the short-term datasets were larger than their long-term counterparts. Model projection using the long-term dataset derived parameters was more consistent with field observations. Therefore, multi-year datasets can achieve more reasonable parameterization of key microbial processes and subsequently boost the accuracy and confidence of long-term soil carbon projections. In the second modeling study, to seek best-fit microbial parameters for various treatments, soil and ecosystem types, microbial parameters in the MEND were calibrated using either single-case calibration or multiple-case calibration by grouping cases according to substrate treatments, soil type and ecosystems. This modeling study showed that microbially-relevant parameters are sensitive to different soils and treatments, and require site-specific calibration. Future experimental studies should increase microbial observation availability while modeling studies should seek to establish relationship between parameter estimates and soil properties.

Subject Area


Recommended Citation

Siyang Jian, "Evaluation and Improvement of the Microbial Enzyme Decomposition (MEND) Model Against Multiple Incubation Experiments" (2020). ETD Collection for Tennessee State University. Paper AAI28027085.