Climate and stomatal traits drive covariation in nighttime stomatal conductance and daytime gas exchange rates in a widespread C₄ grass

Abstract

Nighttime stomatal conductance (g sn) varies among plant functional types and species, but factors shaping the evolution of g sn remain unclear. Examinations of intraspecific variation in g sn as a function of climate and co-varying leaf traits may provide new insight into the evolution of g sn and its adaptive significance. We grew 11 genotypes of Panicum virgatum (switchgrass) representing differing home-climates in a common garden experiment and measured nighttime and daytime leaf gas exchange, as well as stomatal density (SD) and size during early-, mid-, and late-summer. We used piecewise structural equation modelling to determine direct and indirect relationships between home-climate, gas exchange, and stomatal traits. We found no direct relationship between home-climate and g sn. However, genotypes from hotter climates possessed higher SD, which resulted in higher g sn. Across genotypes, higher g sn was associated with higher daytime stomatal conductance and net photosynthesis. Our results indicate that higher g sn may arise in genotypes from hotter climates via increased SD. High SD may provide benefits to genotypes from hotter climates through enhanced daytime transpirational cooling or by permitting maximal gas exchange when conditions are suitable. These results highlight the role of climate and trait coordination in shaping genetic differentiation in g sn .

Dark respiration explains nocturnal stomatal conductance in rice regardless of drought and nutrient stress

“…A similar result was reported for C 4 switchgrass under lightsaturated PPFD (Chieppa et al, 2021). To our knowledge, the upper limit of PPFD at which g sn influences A and g sd is 1000 µmol m −2 s −1 , based on measurements in wheat (McAusland et al, 2021).…”

“…To determine how abiotic stress affects the stomatal size and density, and whether stomatal anatomy can explain the hypothesised stress‐induced g sn variation, we applied clear nail polish (Chieppa et al, 2021; McAusland et al, 2021) to both the abaxial and adaxial surfaces of marked leaves (three to six per treatment) on DOY 229 in 2021 following the same measurement protocol described in Section 2.2. The dried membrane under the polish was later peeled off using clear tape and mounted on an optical microscope (Axioskop2, Axiocam 506 Colour; Zeiss) for data collection.…”

“…To determine how abiotic stress affects the stomatal size and density, and whether stomatal anatomy can explain the hypothesised stressinduced g sn variation, we applied clear nail polish (Chieppa et al, 2021;McAusland et al, 2021) to both the abaxial and adaxial surfaces of U test (n < 20). To determine whether two groups of samples were from the same populations, we used the nonparametric Epps-Singleton test (Epps & Singleton, 1986).…”

Overexpression of PagSTOMAGEN, a Positive Regulator of Stomatal Density, Promotes Vegetative Growth in Poplar

“…The enhanced photosynthetic rate was caused by increased stomatal conductance and intercellular carbon dioxide concentration in STO-OE plants ( Figure 5 A–C). This indicates that increased stomatal density enhanced the photosynthetic rate by regulating the diffusion process of CO 2 gas [ 26 , 57 , 58 ], which is consistent with Arabidopsis .…”

Testing the limits of plant drought stress and subsequent recovery in four provenances of a widely distributed subtropical tree species

“…The response of g s to increasing Ψ xylem was fitted with a 'sigmoidal' model using the 'fitcond' function, wherein the Ψ xylem at 80% stomatal closure (Ψ gs80 ) was estimated.To determine the direct and indirect relationships among traits related to hydraulic and gas exchange recovery, we conducted piecewise structural equation modelling (pSEM) to synthesize the results with the 'psem' function in piecewiseSEM package in R(Lefcheck 2015). Linear mixed models are independent in each path in the model and pSEM requires smaller datasets than standard SEM approaches(Chieppa et al, 2020). We hypothesized thatthe antecedent xylem water potential (Ψ xylem drought) would affect the antecedent PLC (PLC drought) and recovery xylem water potential (Ψ xylem recovery), which both can affect PLC recovery.…”