Chapter 3: What level of model complexity is needed to accurately predict carbon cycling responses to disturbance?: A coupled field-model experiment
O1: Determine whether added model complexity improves the accuracy of predictions for C cycling response to a phloem-disrupting disturbance, using woody biomass increment, LAI, and NPP as common benchmarks.
Compare model performance across disturbance severities, and
Across two different disturbance types (top-down, bottom-up)
O2: Analyze a simple ecosystem model’s sensitivity to disturbance-sensitive parameter values (LAI, stomatal slope, quantum yield, Vcmax) and determine whether site-specific functional trait distributions improve model performance over PFT-derived defaults.
Chapter 3: What level of model complexity is needed to accurately predict carbon cycling responses to disturbance?: A coupled field-model experiment
O1: Determine whether added model complexity improves the accuracy of predictions for C cycling response to a phloem-disrupting disturbance, using woody biomass increment, LAI, and NPP as common benchmarks.
O2: Analyze a simple ecosystem model’s sensitivity to disturbance-sensitive parameter values (LAI, stomatal slope, quantum yield, Vcmax) and determine whether site-specific functional trait distributions improve model performance over PFT-derived defaults.