Mechanistic representations of biogeochemical processes in ecosystem
models are rapidly advancing, requiring advancements in model evaluation
approaches. Here we quantify multiple aspects of model functional
performance to evaluate improved process representations in ecosystem
models. We compare semi-empirical stomatal models with hydraulic
constraints against more mechanistic representations of stomatal and
hydraulic functioning at a semi-arid pine site using a suite of metrics
and analytical tools. We find that models generally perform similarly
under unstressed conditions, but performance diverges under atmospheric
and soil drought. The more empirical models better capture synergistic
information flows between soil water potential and vapor pressure
deficit to transpiration, while the more mechanistic models are overly
deterministic. Additionally, both multilayer canopy and big-leaf models
were unable to capture the magnitude of canopy temperature divergence
from air temperature. Lastly, modeled stable carbon isotope
fractionation differed under canopy water stress which illustrates the
value of carbon isotopes in helping to characterize ecosystem function
and elucidate differences attributable to model structure. This study
demonstrates the value of merging underutilized observational data
streams with emerging analytical tools to characterize ecosystem
function and discriminate among model process representations.