Stomata close to maximize transpiration

Current modeling of plant hydraulics under water stress often relies on complex, high-order differential equations that describe the catastrophic failure of the xylem. While these models capture the physics of cavitation, they frequently struggle with numerical stability and upscaling in coupled soil-vegetation-atmosphere simulations, and their high parameterization demands complicate data assimilation from emerging hydraulic observations.

In this study, we propose that plant stomatal regulation effectively acts as a "system damper" that trades a linear loss in transpiration flux for the avoidance of exponential hydraulic collapse. This regulatory strategy can be captured with simplified models that are more amenable to integration with diverse hydraulic observations, from in situ water potential measurements to satellite-derived vegetation water content (VWC).

We investigate the transition from a plant-limited hydraulic regime to a soil-limited one, demonstrating that the "Hydraulic Cliff", the point where the loss of soil and xylem conductivity (K) outpaces the pressure gradient, is not a static property but a dynamic bottleneck that shifts as the soil dries. By applying elementary mathematics to the energy and mass balance, we show that stomatal closure follows a regulatory logic that prevents the leaf water potential (Ψ_l) from entering the "runaway" zone where demand exponentially exceeds supply.

Our "Dynamic Hydraulic Cliff" framework reveals that the plant's strategy is to decouple the leaf's energy budget (and its associated exponential temperature-driven demand) from the supply decay of the rhizosphere. This approach maintains system stability while being directly linkable to observable quantities: stomatal conductance controls transpiration linearly, while Ψ_l remains within measurable bounds that can be monitored via sap flow, pressure chambers, or inferred from microwave-based VWC retrievals.

We demonstrate that this parsimonious formulation provides a robust pathway for assimilating multi-scale hydraulic observations into land surface and ecohydrological models without the computational burden and parameter uncertainty of solving complex hydraulic PDEs. The framework enables improved representation of plant responses to drought while facilitating the integration of emerging observational products (VWC, water potential proxies) into operational monitoring systems.

We conclude that "linear" stomatal regulation is an evolutionarily optimal response to the multi-exponential risks inherent in the soil-plant-atmosphere continuum, and that recognizing this principle can bridge the gap between detailed hydraulic theory and practical large-scale prediction of transpiration under future climate extremes.