Ecosystem Water-Saving Timescale Varies Spatially With Typical Drydown Length

Stomatal optimization theory is a commonly used framework for modeling how plants regulate transpiration in response to the environment. Most stomatal optimization models assume that plants instantaneously optimize a reward function such as carbon gain. However, plants are expected to optimize over longer timescales given the rapid environmental variability they encounter. There are currently no observational constraints on these timescales. Here, a new stomatal model is developed and is used to analyze the timescales over which stomatal closure is optimized. The proposed model assumes plants maximize carbon gain subject to the constraint that they cannot draw down soil moisture below a critical value. The reward is integrated over time, after being weighted by a discount factor that represents the timescale (tau) that a plant considers when optimizing stomatal conductance to save water. The model is simple enough to be analytically solvable, which allows the value of tau to be inferred from observations of stomatal behavior under known environmental conditions. The model is fitted to eddy covariance data in a range of ecosystems, finding the value of tau that best predicts the dynamics of evapotranspiration at each site. Across 82 sites, the climate metrics with the strongest correlation to tau are measures of the average number of dry days between rainfall events. Values of tau are similar in magnitude to the longest such dry period encountered in an average year. The results here shed light on which climate characteristics shape spatial variations in ecosystem-level water use strategy. Plants can open and close their stomata (pores in their leaves) in response to environmental conditions. A commonly used theory called stomatal optimality models this process with a cost-benefit calculation balancing between the gain of photosynthesis and the risk of losing water, both of which increase as stomata open. However, those models typically operate at each instant in time separately, rather than a more realistic treatment where costs and benefits accumulate over time. We extended stomatal optimality theory to explicitly account for the timescale over which plants control stomatal opening to save water, so that this timescale can be estimated from data. We found that the water-saving timescale varies between locations from a week to several months, and is adapted to local climate conditions. Specifically, ecosystems save water for longer in places with longer typical dry periods between rainstorms. Future models of ecosystem function could account for this variability to better predict plant responses to drought. A model is proposed in which optimal stomatal conductance depends on the timescale of optimization Water-saving timescale (tau) was estimated at the ecosystem level from eddy-covariance data Across 82 sites, estimated values of tau vary from a week to several months, and are correlated with the typical time between rainy days