Hydrologic Controls on Vegetation: from Leaf to Landscape
Topography, vegetation, nutrient dynamics, soil features and hydroclimatic forcing are inherently coupled, with feedbacks occurring over a wide range of temporal and spatial scales. Vegetation growth may be limited by soil moisture, nutrient or solar radiation availability, and in turn influences both soil moisture and nutrient balances at a point. These dynamics are further complicated in a complex terrain, through a series of spatial interactions. A number of experiments has characterized the feedbacks between soil moisture and vegetation dynamics, but a theoretical framework linking short-term leaf-level to interannual plot-scale dynamics has not been fully developed yet. Such theory is needed for optimal management of water resources in natural ecosystems and for agricultural, municipal and industrial uses. Also, it complements the current knowledge on ecosystem response to the predicted climate change.
In this dissertation, the response of vegetation dynamics to unpredictable environmental fluctuations at multiple space-time scales is explored in a modeling framework from sub-daily to interannual time scales. At the hourly time scale, a simultaneous analysis of photosynthesis, transpiration and soil moisture dynamics is carried out to explore the impact of water stress on different photosynthesis processes at the leaf level, and the overall plant activity. Daily soil moisture and vegetation dynamics are then scaled up to the growing season using a stochastic model accounting for daily to interannual hydroclimatic variability. Such stochastic framework is employed to explore the impact of rainfall patterns and different irrigation schemes on crop productivity, along with their implications in terms of sustainability and profitability. To scale up from point to landscape, a probabilistic representation of local landscape features (i.e., slope and aspect) is developed, and applied to assess the effects of topography on solar radiation. Finally, a minimalistic ecosystem model, including soil moisture, vegetation and nutrient dynamics at the year time scale, is outlined; when coupled to the proposed probabilistic topographic description, the latter model can serve to assess the relevance of spatial interactions and to single out the main biophysical controls responsible for ecohydrological variability at the landscape scale.
DepartmentCivil and Environmental Engineering
Agriculture, Plant Culture
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