Monitoring plant water status via static uniaxial compression of the leaf lamina.

Turgor pressure is an essential, but difficult to measure indicator of plant water status. Turgor has been quantified by localized compression of cells or tissues, but a simple method to perform these measurements is lacking. We hypothesized that changes in leaf turgidity can be monitored by uniaxially compressing the leaf lamina and measuring the mechanical stress under a constrained thickness (stress relaxation) and that changes in leaf water content can be monitored by measuring the leaf thickness under constant mechanical stress. Using a simple, custom-built leaf squeeze-flow rheometer, we performed different compression tests on leaves from 13 plant species. The mechanical stress measured during stress relaxation was correlated with leaf bulk turgor pressure (R2 > 0.95) and thus with balancing pressure (R2 > 0.94); the leaf thickness measured under constant mechanical stress was correlated with relative water content (R2 > 0.74). The coefficients of these relationships were related to the leaf bulk osmotic pressure at the turgor-loss point. An idealized average-cell model suggests that, under isothermal conditions, the stationary bulk modulus during compression is largely determined by the bulk osmotic pressure. Our study presents an inexpensive, accessible and automatable method to monitor plant water status noninvasively.

Leaf trait variation is similar among genotypes of Eucalyptus camaldulensis from differing climates and arises in plastic responses to the seasons rather than water availability.

We used a widely distributed tree Eucalyptus camaldulensis subsp. camaldulensis to partition intraspecific variation in leaf functional traits to genotypic variation and phenotypic plasticity. We examined if genotypic variation is related to the climate of genotype provenance and whether phenotypic plasticity maintains performance in a changing environment. Ten genotypes from different climates were grown in a common garden under watering treatments reproducing the wettest and driest edges of the subspecies' distribution. We measured functional traits reflecting leaf metabolism and associated with growth (respiration rate, nitrogen and phosphorus concentrations, and leaf mass per area) and performance proxies (aboveground biomass and growth rate) each season over a year. Genotypic variation contributed substantially to the variation in aboveground biomass but much less in growth rate and leaf traits. Phenotypic plasticity was a large source of the variation in leaf traits and performance proxies and was greater among sampling dates than between watering treatments. The variation in leaf traits was weakly correlated to performance proxies, and both were unrelated to the climate of genotype provenance. Intraspecific variation in leaf traits arises similarly among genotypes in response to seasonal environmental variation, instead of long-term water availability or climate of genotype provenance.

Shoot surface water uptake enables leaf hydraulic recovery in Avicennia marina.

The significance of shoot surface water uptake (SSWU) has been debated, and it would depend on the range of conditions under which it occurs. We hypothesized that the decline of leaf hydraulic conductance (Kleaf ) in response to dehydration may be recovered through SSWU, and that the hydraulic conductance to SSWU (Ksurf ) declines with dehydration. We quantified effects of leaf dehydration on Ksurf and effects of SSWU on recovery of Kleaf in dehydrated leaves of Avicennia marina. SSWU led to overnight recovery of Kleaf , with recovery retracing the same path as loss of Kleaf in response to dehydration. SSWU declined with dehydration. By contrast, Ksurf declined with rehydration time but not with dehydration. Our results showed a role of SSWU in the recovery of leaf hydraulic conductance and revealed that SSWU is sensitive to leaf hydration status. The prevalence of SSWU in vegetation suggests an important role for atmospheric water sources in maintenance of leaf hydraulic function, with implications for plant responses to changing environments.

Predicting dark respiration rates of wheat leaves from hyperspectral reflectance.

Greater availability of leaf dark respiration (Rdark ) data could facilitate breeding efforts to raise crop yield and improve global carbon cycle modelling. However, the availability of Rdark data is limited because it is cumbersome, time consuming, or destructive to measure. We report a non-destructive and high-throughput method of estimating Rdark from leaf hyperspectral reflectance data that was derived from leaf Rdark measured by a destructive high-throughput oxygen consumption technique. We generated a large dataset of leaf Rdark for wheat (1380 samples) from 90 genotypes, multiple growth stages, and growth conditions to generate models for Rdark . Leaf Rdark (per unit leaf area, fresh mass, dry mass or nitrogen, N) varied 7- to 15-fold among individual plants, whereas traits known to scale with Rdark , leaf N, and leaf mass per area (LMA) only varied twofold to fivefold. Our models predicted leaf Rdark , N, and LMA with r2 values of 0.50-0.63, 0.91, and 0.75, respectively, and relative bias of 17-18% for Rdark and 7-12% for N and LMA. Our results suggest that hyperspectral model prediction of wheat leaf Rdark is largely independent of leaf N and LMA. Potential drivers of hyperspectral signatures of Rdark are discussed.