Journal of Advances in Modeling Earth Systems (Jan 2023)

Parameterizing Vegetation Traits With a Process‐Based Ecohydrological Model and Xylem Water Isotopic Observations

  • K. Li,
  • S. Kuppel,
  • J. Knighton

DOI
https://doi.org/10.1029/2022MS003263
Journal volume & issue
Vol. 15, no. 1
pp. n/a – n/a

Abstract

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Abstract Knowledge of plant hydraulic traits is critical for simulating terrestrial water storage, ecosystem water use, and tree responses to drought. The isotopic composition of tree xylem water (δXYLEM) has proven to be useful for understanding rooting strategies and for tracing terrestrial water flowpaths. Despite the broad collection of δXYLEM observations, few studies have estimated other plant traits from these data. We demonstrate the sensitivity of process‐based isotope‐enabled ecohydrological model (EcH2O‐iso) simulations of rooting depth distributions (KROOT), maximum stomatal conductance (gsMAX), optimal growth temperatures (TOPT), canopy light interception (KBEERS), stomatal sensitivity to vapor pressure deficits (gs‐VPD), and tree water storage capacity (TreeV) to δXYLEM observations. We sampled the δXYLEM of 30 Eastern hemlock (Tsuga canadensis) trees across 7 months, spanning a range of topographic positions and diameters. We calibrated the model 30 times with δXYLEM from each sampled tree. Calibrated values for gsMAX, KBEERS, and KROOT were validated with independent datasets of latent heat flux, canopy light interception, and xylem observations from independent hemlock stands. The calibrated values of several vegetation traits were significantly correlated with the diameters and topographic positions of the trees sampled in the field. These results indicate that δXYLEM reflects the characteristics and locations of the individual trees that are sampled, and therefore care must be taken in upscaling calibrated or measured plant traits for individual trees to larger horizontal scales. This research demonstrates that isotope‐enabled hydrological‐, land surface‐, and Earth systems‐models can leverage widely available water isotopic data to accurately estimate plant hydraulic traits.

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