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Abstract Leaf surface conductance to water vapor and CO2 across the epidermis (gleaf) strongly determines the rates of gas exchange. Thus, clarifying the drivers of gleaf has important implications for resolving the mechanisms of photosynthetic productivity and leaf and plant responses and tolerance to drought. It is well recognized that gleaf is a function of the conductances of the stomata (gs) and of the epidermis + cuticle (gec). Yet, controversies have arisen around the relative roles of stomatal density (d) and size (s), fractional stomatal opening (α; aperture relative to maximum), and gec in determining gleaf. Resolving the importance of these drivers is critical across the range of leaf surface conductances, from strong stomatal closure under drought (gleaf,min), to typical opening for photosynthesis (gleaf,op), to maximum achievable opening (gleaf,max). We derived equations and analyzed a compiled database of published and measured data for approximately 200 species and genotypes. On average, within and across species, higher gleaf,min was determined 10 times more strongly by α and gec than by d and negligibly by s; higher gleaf,op was determined approximately equally by α (47%) and by stomatal anatomy (45% by d and 8% by s), and negligibly by gec; and higher gleaf,max was determined entirely by d. These findings clarify how diversity in stomatal functioning arises from multiple structural and physiological causes with importance shifting with context. The rising importance of d relative to α, from gleaf,min to gleaf,op, enables even species with low gleaf,min, which can retain leaves through drought, to possess high d and thereby achieve rapid gas exchange in periods of high water availability. 

Understanding how environmental adaptations mediate plant and ecosystem responses becomes increasingly important under accelerating global environmental change. Multi-stemmed trees, for example, differ in form and function from single-stemmed trees and may possess physiological advantages that allow for persistence during stressful climatic events such as extended drought. Following the worst drought in Hawaii in a century, we examined patterns of stem abundance and turnover in a Hawaiian lowland dry forest (LDF) and a montane wet forest (MWF) to investigate how multi-stemmed trees might influence site persistence, and how stem abundance and turnover relate to key functional traits. We found stem abundance and multi-stemmed trees to be an important component for climate resilience within the LDF. The LDF had higher relative abundance of multi-stemmed trees, stem abundance, and mean stem abundance compared to a reference MWF. Within the LDF, multi-stemmed trees had higher relative stem abundance (i.e., percent composition of stems to the total number of stems in the LDF) and higher estimated aboveground carbon than single-stemmed trees. Stem abundance varied among species and tree size classes. Stem turnover (i.e., change in stem abundance between five-year censuses) varied among species and tree size classes and species mean stem turnover was correlated with mean species stem abundance per tree. At the plot level, stem abundance per tree is also a predictor of survival, though mortality did not differ between multiple- and single-stemmed trees. Lastly, species with higher mean stem abundance per tree tended to have traits associated with a higher light-saturated photosynthetic rate, suggesting greater productivity in periods with higher water supply. Identifying the traits that allow species and forest communities to persist in dry environments or respond to disturbance is useful for forecasting ecological climate resilience or potential for restoration in tropical dry forests. 

Abstract Intra‐specific trait variation (ITV) plays a role in processes at a wide range of scales from organs to ecosystems across climate gradients. Yet, ITV remains rarely quantified for many ecophysiological traits typically assessed for species means, such as pressure volume (PV) curve parameters including osmotic potential at full turgor and modulus of elasticity, which are important in plant water relations. We defined a baseline “reference ITV” (ITV_ref) as the variation among fully exposed, mature sun leaves of replicate individuals of a given species grown in similar, well‐watered conditions, representing the conservative sampling design commonly used for species‐level ecophysiological traits. We hypothesized that PV parameters would show low ITV_refrelative to other leaf morphological traits, and that their intraspecific relationships would be similar to those previously established across species and proposed to arise from biophysical constraints. In a database of novel and published PV curves and additional leaf structural traits for 50 diverse species, we found low ITV_reffor PV parameters relative to other morphological traits, and strong intraspecific relationships among PV traits. Simulation modeling showed that conservative ITV_refenables the use of species‐mean PV parameters for scaling up from spectroscopic measurements of leaf water content to enable sensing of leaf water potential. 

Abstract Improved estimation of climate niches is critical, given climate change. Plant adaptation to climate depends on their physiological traits and their distributions, yet traits are rarely used to inform the estimation of species climate niches, and the power of a trait‐based approach has been controversial, given the many ecological factors and methodological issues that may result in decoupling of species' traits from their native climate.For 107 species across six ecosystems of California, we tested the hypothesis that mechanistic leaf and wood traits can robustly predict the mean of diverse species' climate distributions, when combining methodological improvements from previous studies, including standard trait measurements and sampling plants growing together at few sites. Further, we introduce an approach to quantify species' trait‐climate mismatch.We demonstrate a strong power to predict species mean climate from traits. As hypothesized, the prediction of species mean climate is stronger (and mismatch lower) when traits are sampled for individuals closer to species' mean climates.Improved resolution of species' climate niches based on mechanistic traits can importantly inform conservation of vulnerable species under the threat of climatic shifts in upcoming decades. Read the freePlain Language Summaryfor this article on the Journal blog.