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

Abstract

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.