Photosynthetic responses to leaf surface wetness in tropical and semiarid savannah trees with varying leaf traits

Abstract:

Literature postulates that photosynthesis rates are inhibited while leaves are wet. Yet, measurements of photosynthesis during wet conditions are challenging to obtain due to equipment limitations and extreme complexity of canopy-atmosphere interactions in forested environments. Thus, the objective of this study was to evaluate the responses of seven tropical and three semi-arid savannah tree species to simulated leaf wetness and test the hypotheses that (1) leaf wetness reduces photosynthetic rates (A_s) and (2) leaf traits explain different responses among species. The two sites were a tropical rainforest in northern Costa Rica with ~4200 mm annual rainfall and a semiarid savannah in central Texas with ~1100 mm. Five sun-exposed leaf replicates from each species were subjected to gas exchange measurements under dry and wet leaf conditions. Relationships between A_s with leaf-to-air temperature difference (ΔT), vapor pressure deficit (VPD), and leaf temperature (T_leaf) were evaluated using simple and multiple linear regression analyses. We found that responses varied greatly among species, but all plants maintained a baseline of activity under wet leaf conditions, suggesting that abaxial leaf A_s was a significant percentage of total leaf A_s. For Costa Rican species, Senna alata had an immediate 31% reduction in A_s, while Zamia skinneri, had a 7% increase in A_s. All oak species showed decline immediately after wetting. After 1 minute, Quercus macrocarpa showed a 28% increase and Quercus stellata a 14% decrease. This variability between species suggests that leaf traits (trichome occurrence, water repellency, vein distribution, size and leaf angle variation) may be critical for optimizing photosynthesis under wet conditions. ΔT was the strongest secondary influence on A_s under wet conditions for both plant types, especially on drought-tolerant species, showing that subtle microclimate alterations can strongly affect physiological processes. Although vegetation-atmosphere interactions are complex, leaf-level data such as that presented here are vital for accurate modeling of growth in tropical environments.