Evaluation of method to model stomatal conductance and its use to assess biomass increase in poplar trees

Stomatal conductance (gₛ) is the main limiting factor for photosynthesis and is sensitive to plant water status. Accurately assessing the behavior of gₛ under water deficit stress is essential to model plants carbon and water flux, which govern vegetation biomass production and dynamics. However, direct measurement of gₛ with gas exchange analyzer can be time-consuming and laborious, especially under field conditions, thus constraining the data availability for validating the modeling outcome. This difficulty can be solved if measurement of gₛ is automated. Here, we report on dynamics of gₛ and the maximum (gₛₘₐₓ) of Populus tomentosa, derived from automatically recorded meteorological variables and sap flux density (Jₛ) and turgor pressure sensors outputs (Z) measured in three P. tomentosa trees from a short-rotation plantation subjected to different water stress levels along a whole growing season. The simulated gₛₘₐₓ was related to aboveground (ABM) and underground biomass (UBM) increase by leaf area. Jₛ and Z were continuously measured using sap flow and ZIM sensors. Our results showed that the sensitivity of Jₛ to air vapor deficit (D) (i.e. Jₛ/D) correlated well with gₛ, and the sensitivity of Z to D (i.e. dZ/dD) was well coupled with gₛₘₐₓ. In addition, the ABM increase was linearly aligned with simulated gₛₘₐₓ multiplied by leaf area (LA) (R² > 0.7). Also, increment in UBM was significantly correlated with simulated gₛₘₐₓ * LA across all observed trees, being the best described by a logistic function (R² > 0.7). We conclude that gₛ can be well simulated through automatic monitoring of Jₛ and Z for different meteorological and soil water content conditions. Moreover, the simulated gₛₘₐₓ was also closely related to biomass production both above and underground, which opens the possibility for using it to manage irrigation in smart agriculture and forestry in the future.