EVALUATION AND DEVELOPMENT OF ECOSYSTEM MODELS TO UNDERSTAND CARBON AND HYDROLOGICAL PROCESSES
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Belowground processes play a critical role in regulating terrestrial ecosystem functioning by controlling the dynamics of carbon and water cycles. This dissertation focuses on improving our understanding of belowground processes by evaluating microbial-mediated soil carbon dynamics and hydraulic redistribution (HR) in terrestrial ecosystem models. In the first part, I reviewed over 70 microbial models to assess how microbial processes are represented in soil organic carbon (SOC) models. The review identified four commonly incorporated processes, microbial-mediated decomposition, mineral interaction, necromass recycling, and microbial dormancy dynamics. This study revealed that majority of microbial models simulate only one or two microbial processes. Notably, nonlinear kinetics (e.g., Michaelis-Menten) are widely used, and the traditional understanding of SOC persistence due to its inherent chemical property has shifted toward organo-mineral protection. In the second part, I integrated HR into the Terrestrial ECOsystem (TECO) model and applied Bayesian data assimilation to optimize model parameters using multi-year soil moisture data from a semi-arid piñon-juniper woodland. Results showed that HR improved soil moisture predictions, especially in the top 30 cm during dry spells, and that HR dynamics varied with precipitation patterns and drought duration. In the third part, I evaluated the impact of HR on ecosystem water and carbon fluxes at two contrasting sites such as a semi-arid woodland (US-MPJ) and a seasonally wet alpine meadow, by calibrating default and HR-enabled TECO models using multi-depth soil moisture and net ecosystem exchange (NEE) data. The modeling study revealed that incorporating HR improved the simulation of evapotranspiration and carbon uptake at the alpine site due to increased transpiration and gross primary production particularly during growing seasons. However, a limited impact of HR was observed at US-MPJ site. Overall, the results of this dissertation highlight the current state of microbial models in representing microbial processes and underscore the importance of incorporating HR into an ecosystem model, particularly in ecosystems with varying hydroclimatic conditions, to enhance predictions of ecosystem functioning.