The increasing frequency and intensity of heat waves caused significant damages to urban woody species, and the different leaf structures between evergreen and deciduous species may be closely related to leaf heat tolerance. However, whether the different leaf structural traits of evergreen and deciduous plants contribute to their different responses under heat waves is still unclear.

During the record-breaking and long-lasting 2022 summer heat waves in China, we investigated the relationships between leaf thermal indices and leaf structural traits of 36 urban woody species in four cities along the Yangtze River.

We found that all the four thermal indices were significantly but weakly related with leaf damage status. The critical temperature that causes the initial 15% damage to photosystem II (Tcrit) may serve as a sensitive measure of heat tolerance. Evergreen species suffered less leaf damage during the heat waves and exhibited higher leaf heat tolerance, thicker leaves than deciduous species. Tcrit was significantly correlated with leaf mass per area, leaf thickness and thickness of spongy tissue.

Synthesis: Urban woody species with high Tcrit, leaf mass per area, and leaf thickness tend to be more tolerant to heat stress. This study provides insights for predicting leaf heat tolerance of urban woody plants in subtropical China and their physiological and ecological responses to severe heat waves.

Quantify leaf damage status (LDR, Fv/Fm)：

(1) Leaf damage ratio (LDR). To quantify physical leaf tissue damage caused by heat waves, we visually assessed and recorded the percentage of damaged leaves in the entire plant canopy as LDR following Esperon-Rodriguez et al. (2021). Specifically, burned areas on the leaf surface associated with a color change from green to light brown with dark brown margins were considered as leaf damage. Two fixed people scored the LDR of each tree, and if their results were similar (within 10% difference), the average value was taken. If the results differed greatly, a third evaluator was asked to provide more information to achieve a more accurate value. We evaluated five replicates per species, and the final average was taken to represent the LDR.

(2) The maximum quantum efficiency (Fv/Fm) of the leaf photosystem II. We sampled 3-5 individuals per species, collected over twenty leaves for each individual (totally 60-100 leaves per species), and brought them to the laboratory. After a 2h 25℃ dark treatment of the leaf samples, we measured Fv/Fm of the leaf photosystem II with PAM 2500 fluorometer (Walz, Effeltrich, Germany).

Measure leaf photosynthetic heat tolerance (Tcrit, T50, TSM):

We set up nine water baths to measure leaf heat tolerance, the control bath was set at 26°C and the experimental water baths were set at 36, 41, 46, 50, 52, 54, 56 and 60°C, respectively. Leaf samples were kept in the dark for at least two hours in plastic bags with moist paper tissues. For each species, leaves were cut into many 4 cm² pieces and 6-8 pieces were placed into a sealed plastic bag (nine plastic bags for nine temperature gradients) in water bath for 15 minutes, followed by 24 hours of dark adaptation. Fv/Fm was recorded to detect leaf irreversible damage caused by temperature treatments. Tcrit and T50 of each species were derived using a Weibull function fitted to Fv/Fm versus treatment temperature using the R package fitplc (Drake et al., 2018), showing the critical temperature (Tcrit) that causes the initial damage (15%) and the temperature (T50) that causes 50% damage to photosystem II.

To determine the thermal safety margin (TSM), we measured the maximum leaf temperature (Tleafmax) of each species (3-5 individuals) during 12:00-14:00 (Marchin et al., 2022) in the same day in each city with an infrared thermal camera (FLIR, America). We tried our best to ensure that leaf temperatures of fully sun-exposed leaves are comparable across species in each city within a short period, as reported in previous studies (Blasini et al., 2022; Lin et al., 2017). Moreover, the maximum leaf temperature recorded for each species in each city on a given day can be measured accurately to calculate TSM. TSM is the difference between T50 or Tcrit and Tleafmax (i.e., TSMcrit = Tcrit - Tleafmax), following the method described by Kitudom (2022). This metric provides a good prediction of leaf heat vulnerability, with the threshold of leaf temperature reached when Tleafmax equals Tcrit or T50.

Measure leaf morphological traits (LA, LMA):

For each species (3-5 replicates), twenty leaves from each replicate were scanned using a flatbed scanner (HP Deskjet 1050). Leaf area (LA, cm²) was analyzed using ImageJ (National Institutes of Health, Bethesda, USA) based on the scanned image. Then leaves were dried (65 °C for 72h) and their masses were determined. Leaf mass per area (LMA, g/cm²) was calculated by the ratio of leaf dry weight to leaf area.

Measure leaf anatomical traits (LT, Tup, Tlow, Tp, Ts, P/S, GCL, SD, SPI)

We made cross sections of leaves using the freehand sectioning method. We measured leaf thickness (LT, µm) and thickness of upper and lower epidermis (Tup, Tlow), palisade mesophyll (Tp), and spongy mesophyll (Ts). All cross sections were photographed with a microscope (YS100, Nikon, Tokyo, Japan) at 40× magnification, and analyzed by Image J software. Three images were captured from each of four leaves per species.

To measure the stomatal traits, epidermal peels from both leaf surfaces of four leaves per species were used to determine stomatal traits (guard cell length (GCL), stomatal pore length (SL) and stomatal density (SD). We used a layer of transparent nail polish to fix the stomata of the leaves. The nail polish layer was then glued to a piece of transparent tape cut into 1.0 cm × 1.0 cm and flattened on a microscope slide before being covered with a coverslip for imaging. All images were captured using a microscope (YS100, Nikon, Tokyo, Japan), and analyzed using Image J software. Three images of epidermal peels were captured from each of four leaves per species. At 400× magnification, we scored guard cell length (GCL, µm) and stomatal pore length (SL, µm). At 100× magnification, we counted stomata in a 0.25 mm² field of view to determine stomatal density (SD, mm^-2), calculating stomatal pore index (SPI = SD×SL²).

Reference:

Blasini, D. E., Koepke, D. F., Bush, S. E., Allan, G. J., Gehring, C. A., Whitham, T. G., Day, T. A., & Hultine, K. R. (2022). Tradeoffs between leaf cooling and hydraulic safety in a dominant arid land riparian tree species. Plant Cell and Environment, 45(6), 1664–1681. https://doi.org/10.1111/pce.14292

Drake, J. E., Tjoelker, M. G., Vårhammar, A., Medlyn, B. E., Reich, P. B., Leigh, A., Pfautsch, S., Blackman, C. J., López, R., Aspinwall, M. J., Crous, K. Y., Duursma, R. A., Kumarathunge, D., De Kauwe, M. G., Jiang, M., Nicotra, A. B., Tissue, D. T., Choat, B., Atkin, O. K., & Barton, C. V. M. (2018). Trees tolerate an extreme heatwave via sustained transpirational cooling and increased leaf thermal tolerance. Global Change Biology, 24(6), 2390–2402. https://doi.org/10.1111/gcb.14037

Esperon-Rodriguez, M., Power, S. A., Tjoelker, M. G., Marchin, R. M., & Rymer, P. D. (2021). Contrasting heat tolerance of urban trees to extreme temperatures during heatwaves. Urban Forestry & Urban Greening, 66, 127387. https://doi.org/10.1016/j.ufug.2021.127387

Kitudom, N., Fauset, S., Zhou, Y., Fan, Z., Li, M., He, M., Zhang, S., Xu, K., & Lin, H. (2022). Thermal safety margins of plant leaves across biomes under a heatwave. Science of The Total Environment, 806, 150416. https://doi.org/10.1016/j.scitotenv.2021.150416

Lin, H., Chen, Y., Zhang, H., Fu, P., & Fan, Z. (2017). Stronger cooling effects of transpiration and leaf physical traits of plants from a hot dry habitat than from a hot wet habitat. Functional Ecology, 31(12), 2202–2211. https://doi.org/10.1111/1365-2435.12923

Marchin, R. M., Backes, D., Ossola, A., Leishman, M. R., Tjoelker, M. G., & Ellsworth, D. S. (2022). Extreme heat increases stomatal conductance and drought-induced mortality risk in vulnerable plant species. Global Change Biology, 28(3), 1133–1146. https://doi.org/10.1111/gcb.15976