<p>Terrestrial ecosystems, occupying more than 25% of the Earth's surface, can serve as</p><p>`biological valves' in regulating the anthropogenic emissions of atmospheric aerosol</p><p>particles and greenhouse gases (GHGs) as responses to their surrounding environments.</p><p>While the signicance of quantifying the exchange rates of GHGs and atmospheric</p><p>aerosol particles between the terrestrial biosphere and the atmosphere is</p><p>hardly questioned in many scientic elds, the progress in improving model predictability,</p><p>data interpretation or the combination of the two remains impeded by</p><p>the lack of precise framework elucidating their dynamic transport processes over a</p><p>wide range of spatiotemporal scales. The diculty in developing prognostic modeling</p><p>tools to quantify the source or sink strength of these atmospheric substances</p><p>can be further magnied by the fact that the climate system is also sensitive to the</p><p>feedback from terrestrial ecosystems forming the so-called `feedback cycle'. Hence,</p><p>the emergent need is to reduce uncertainties when assessing this complex and dynamic</p><p>feedback cycle that is necessary to support the decisions of mitigation and</p><p>adaptation policies associated with human activities (e.g., anthropogenic emission</p><p>controls and land use managements) under current and future climate regimes.</p><p>With the goal to improve the predictions for the biosphere-atmosphere exchange</p><p>of biologically active gases and atmospheric aerosol particles, the main focus of this</p><p>dissertation is on revising and up-scaling the biotic and abiotic transport processes</p><p>from leaf to canopy scales. The validity of previous modeling studies in determining</p><p>iv</p><p>the exchange rate of gases and particles is evaluated with detailed descriptions of their</p><p>limitations. Mechanistic-based modeling approaches along with empirical studies</p><p>across dierent scales are employed to rene the mathematical descriptions of surface</p><p>conductance responsible for gas and particle exchanges as commonly adopted by all</p><p>operational models. Specically, how variation in horizontal leaf area density within</p><p>the vegetated medium, leaf size and leaf microroughness impact the aerodynamic attributes</p><p>and thereby the ultrane particle collection eciency at the leaf/branch scale</p><p>is explored using wind tunnel experiments with interpretations by a porous media</p><p>model and a scaling analysis. A multi-layered and size-resolved second-order closure</p><p>model combined with particle </p><p>uxes and concentration measurements within and</p><p>above a forest is used to explore the particle transport processes within the canopy</p><p>sub-layer and the partitioning of particle deposition onto canopy medium and forest</p><p>oor. For gases, a modeling framework accounting for the leaf-level boundary layer</p><p>eects on the stomatal pathway for gas exchange is proposed and combined with sap</p><p>ux measurements in a wind tunnel to assess how leaf-level transpiration varies with</p><p>increasing wind speed. How exogenous environmental conditions and endogenous</p><p>soil-root-stem-leaf hydraulic and eco-physiological properties impact the above- and</p><p>below-ground water dynamics in the soil-plant system and shape plant responses</p><p>to droughts is assessed by a porous media model that accommodates the transient</p><p>water </p><p>ow within the plant vascular system and is coupled with the aforementioned</p><p>leaf-level gas exchange model and soil-root interaction model. It should be noted</p><p>that tackling all aspects of potential issues causing uncertainties in forecasting the</p><p>feedback cycle between terrestrial ecosystem and the climate is unrealistic in a single</p><p>dissertation but further research questions and opportunities based on the foundation</p><p>derived from this dissertation are also brie</p><p>y discussed.</p> / Dissertation
| Identifer | oai:union.ndltd.org:DUKE/oai:dukespace.lib.duke.edu:10161/12846 |
| Date | January 2016 |
| Creators | Huang, Cheng-Wei |
| Contributors | Katul, Gabriel G |
| Source Sets | Duke University |
| Detected Language | English |
| Type | Dissertation |
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