Optimal plant water‐use strategies under stochastic rainfall

Abstract

Plant hydraulic traits have been conjectured to be coordinated, thereby providing plants with a balanced hydraulic system that protects them from cavitation while allowing an efficient transport of water necessary for photosynthesis. In particular, observations suggest correlations between the water potentials at which xylem cavitation impairs water movement and the one at stomatal closure, and between maximum xylem and stomatal conductances, begging the question as to whether such coordination emerges as an optimal water-use strategy under unpredictable rainfall. Here mean transpiration <E> is used as a proxy for long-term plant fitness and its variations as a function of the water potentials at 50% loss of stem conductivity due to cavitation and at 90% stomatal closure are explored. It is shown that coordination between these hydraulic traits is necessary to maximize <E>, with rainfall patterns altering the optimal range of trait values. In contrast, coordination between ecosystem-level conductances appears not necessary to maximize <E>. The optimal trait ranges are wider under drier than under mesic conditions, suggesting that in semiarid systems different water use strategies may be equally successful. Comparison with observations across species from a range of ecosystems confirms model predictions, indicating that the coordinated functioning of plant organs might indeed emerge from an optimal response to rainfall variability.

Dynamic interactions of ecohydrological and biogeochemical processes in water‐limited systems

“…Abiotic effects encompass deep percolation and evaporation, as well as atmospheric conditions setting the rate of potential ET (i.e., the maximum rate of soil moisture decline). The biotic effects are primarily controlled by the shape of the Tmoisture curves, which depend on a suite of vegetation traits (Vico and Porporato 2008, Egea et al 2011, Manzoni et al 2014b). Therefore these curves should be interpreted as emerging properties of the internal dynamics in the plant-soil system, affected by plant functional traits and type (grasses, trees, shrubs), and by species adaptations.…”

“…These trait-based, short-term models have been used to explore how different plant features determine emerging properties such as the transpiration-soil moisture and photosynthesissoil moisture relations at the daily time scale (Daly et al 2004a, b, Egea et al 2011, Manzoni et al 2014b. By linking aggregate parameters such as the moisture levels at incipient stomatal closure and at wilting, and the transpiration rate under well-watered conditions, to specific traits, these models bridge the gap between processbased representations and eco-hydrological models based on those aggregate parameters (e.g., Laio et al 2001.…”

“…For example, to our knowledge there are no process-based models explicitly accounting for recovery of photosynthetic capacity after a drought event, whereas some models address the recovery of xylem function (Vesala et al 2003), but not the carryover effects sometimes occurring over several years (Anderegg et al 2013). At longer time scales, changes in traits due to species selection can be described through optimality approaches that explore a range of possible phenotypes and select the trait combinations that allow maximum fitness (Schwinning and Ehleringer 2001, Everard et al 2010, Manzoni et al 2014b. Plant mortality following drought events is particularly complicated to describe, since it results from multiple exogenous and endogenous factors, which only some recent works are attempting to disentangle (Parolari et al 2014).…”

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

“…Manzoni, et al [16] further demonstrated differences in K max , a, Ψ 50 , and normalized maximum transpiration rate with biome and growth form, similarly to Figure S8. A more complex mathematical framework revealed coordination between stomatal closure and Ψ 50 to reduce the risk of embolism while maintaining transpiration [67,68]. A number of smaller-scale, biome or growth form specific studies (e.g., [12,40,[69][70][71]) have revealed a number of more specific relationships.…”

Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

“…Estimates of ecohydrological parameters are relevant to a large range of applications for which the stochastic soil water 10 balance framework has been used and adapted, including: the effects of climate, soil and vegetation on soil moisture dynamics (Laio et al, 2001a;Rodrigues-Iturbe et al, 2001;Porporato et al, 2004), ecohydrological factors driving spatial and structural characteristics of vegetation (Caylor et al, 2005;Manfreda et al, 2017), soil salinization dynamics (Suweis et al, 2010), biological soil crusts (Whitney et al, 2017), vegetation stress, optimum plant water use strategies and plant hydraulic failure (Laio et al, 2001b;Manzoni et al 2014;Feng et al, 2017), vertical root distributions (Laio et al, 2006), plant 15 pathogen risk (Thomspon et al, 2013), streamflow persistence in seasonally dry landscapes (Dralle et al, 2016), and soil water balance partitioning (Good et al, 2014 ; http://rdcu.be/yqW7). A survey of close to 400 echoydrology publications found that 40% relied heavily on simulation, rarely integrated empirical measurements, and were almost never coupled with experimental studies, suggesting a critical need to combine modeling and empirical approaches in echohydrology (King and Caylor, 2011).…”