Investigating Dew Deposition on Leaves: Effects on Leaf Water Content, CO2, and Remote Sensing Characterization

摘要

Dew deposition occurs in ecosystems worldwide, even in the driest deserts and in times of drought. Although some species absorb dew water directly via foliar up- take, a ubiquitous effect of dew on plant water balance is the interference of dew droplets with the leaf energy balance, which increases leaf albedo and emissivity and decreases leaf temperature through dew evaporation. Dew deposition frequency and amount are expected to be affected by changing environmental conditions, with un- known consequences for plant water stress and ecosystem carbon, water, and energy fluxes. In this dissertation, I seek to quantify the effect of dew deposition on leaves as well as the spatial extent of dew deposition, to provide an estimate of the effects of dew on water and carbon exchanges between vegetation and the atmosphere. In Chapter 2, I present a new protocol using a Picarro induction module coupled to a cavity ringdown spectrometer to obtain maps of the leaf water isotopes 18O and 2H. The technique is applied to Colocasia esculenta leaves, and I find that these leaves present a unique pattern of intra-leaf water isotopes with a strong radial enrichment and little longitudinal enrichment. In Chapter 3, I use the new method presented in Chapter 2 to study the effects of dew deposition on the water isotopes and water potential of C. esculenta. I discover that dew does not penetrate inside the leaves, but does impact their transpiration rate, helping them maintain a higher water potential. To better understand these results, I develop a dew deposition and leaf water, energy, and carbon balance model presented in Chapter 4. The model is compared to leaf wetness sensor data from the Blue Oak Ranch Reserve in California, and I find that dew deposition usually decreases both transpiration and carbon uptake. I conclude this dissertation by investigating the spatial extent of dew deposition events, which is currently largely unknown, by modeling the effects of dew droplets on leaves in active microwave remote sensing data.