Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

Abstract

Abstract. Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ε, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf : sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.

Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

“…Gap-filled multivariate trait datasets may increase the robustness of syntheses of plant form and function and trait-driven modelling approaches (Yang et al, 2015). We also show that spatially distributed layers of environmental information may improve trait mapping, increasing spatial resolution and/or sample size in trait-driven ecosystem process models (Christoffersen et al, 2016).…”

Gap-filling a spatially-explicit plant trait database: comparing imputation methods and different levels of ecological information

“…Siefert et al 2015), the synthesis of plant form and function (Díaz et al 2016) or the development of trait-driven modelling approaches (Yang et al 2015). We also show that spatially-distributed layers of ecological information for trait imputation, as shown here for MICE, can thus be used to obtain trait maps to inform trait-driven ecosystem process models (Christoffersen et al 2016). …”

Plant Hydraulic Trait Covariation: A Global Meta-Analysis to Reduce Degrees of Freedom in Trait-Based Hydrologic Models

“…Such PHMs are being rapidly adopted into dynamic vegetation and land-surface modeling (LSM) platforms in an effort to improve the simulation of forest function, in terms of carbon and water exchange and their combined influence on expectations of plant growth and mortality [44][45][46]. With the incorporation of PHMs, one need only know a given species' hydraulic strategy as dictated by fundamental hydraulic traits, to create simulations of vegetation water use and carbon uptake in the presence of given atmospheric and soil conditions [47].…”

“…Process-based modeling of water transport through the soil-plant-atmosphere continuum has advanced significantly within the last few years, with the development of new PHMs and their ongoing incorporation into LSMs as replacements for the traditional empirical methods to predict transpiration by calculating stomatal conductance [42,44,45,48]. These models simulate the transport of water in the soil-plant-atmosphere continuum as flow through a porous media, using the Darcy or Richards equations for saturated or unsaturated flow, respectively, and restrict stomatal conductance on the basis of leaf and branch water potentials.…”

“…These models simulate the transport of water in the soil-plant-atmosphere continuum as flow through a porous media, using the Darcy or Richards equations for saturated or unsaturated flow, respectively, and restrict stomatal conductance on the basis of leaf and branch water potentials. Most existing PHMs use a formulation based on Darcy's law which assumes that the transfer of plant-water between the soil and the atmosphere is controlled by vegetation hydraulic conductivity and the hydraulic potential gradient between the soil and the plant [44,49,50]. The most basic class of plant hydraulics models largely ignores factors affecting dynamic changes to xylem capacitance and conductance while focusing instead on total vegetative resistance to water flow [51].…”