Leaf gas exchange measurement for steady-state stomatal conductance model calibration

This dataset supports a methodological investigation into leaf gas
exchange measurement protocols for calibrating steady-state stomatal
conductance models. The repository contains 24 data files comprising both
field measurements and 3D biophysical model simulations. Field
measurements include steady-state gas exchange data collected with a LICOR
LI-6800 infrared gas analyzer (IRGA) and non-steady-state survey
measurements collected with a LICOR LI-600 leaf porometer across three
plant species: cowpea (Vigna unguiculata), eastern redbud (Cercis
canadensis), and walnut (Juglans regia). Measured variables include
stomatal conductance, photosynthetic rate, transpiration, leaf
temperature, vapor pressure deficit, and photosynthetic photon flux
density under varying light intensities and environmental conditions.
Complementary simulated data were generated using leaf-resolving
biophysical models to quantify measurement discrepancies across different
stomatal time constants (τ = 900-9000s), spatial sampling strategies
(single leaves vs. canopy surveys), and temporal protocols (diurnal
cycles, steady-state vs. non-steady-state measurements). The dataset
includes light response curves, vapor pressure deficit response curves,
diurnal simulations, and statistical power analyses examining sample size
requirements for parameter recovery. These data quantify leaf-to-leaf
physiological variability (>3-fold under identical conditions),
systematic errors introduced by stomatal kinetics in parameter
calibration, and instrument-specific trade-offs between IRGAs and
porometers. This dataset provides essential benchmarks for developing
efficient gas exchange measurement protocols and assessing the reliability
of stomatal model parameter estimates in crop and land surface modeling
applications.