Collaborative Proposal: Impact of stochastic soil moisture dynamics on vegetation water stress and nutrient cycling

0236621D‘Odorico在干旱和半干旱生态系统中，蒸散、光合作用和净碳同化速率与土壤水分有很强的相关性。有限的土壤水分条件导致植被进入水分胁迫状态，如果持续下去，就会导致植物失去膨胀性、枯萎和死亡。土壤水分也影响氮素循环，因为分解、矿化、硝化、反硝化、根系吸收和淋溶过程直接或间接依赖于土壤水分条件。根区有效氮素的数量反过来又影响植被过程。因此，通过土壤水平衡，水循环对陆地生态系统起着重要的控制作用，特别是在干旱和半干旱环境中，蒸发蒸腾、养分矿化和养分吸收的速度受到土壤水分可获得性的强烈限制。尽管人们了解了许多将水分胁迫和氮循环与土壤水分条件联系起来的生理和生物地球化学机制，但仍然缺乏一个基于过程的定量框架，用于分析和预测水文过程可能如何影响陆地生态系统。这类框架对于加强了解气候变化对陆地植物群落和生态系统的影响至关重要。通过建立土壤水分平衡的日时间尺度的随机力学模型，建立了土壤水分与土壤水分的相关性，并将这种相关性表示为气候、土壤和植被特征的函数。对于这个项目，我们计划使用这个框架来研究水文条件对土壤氮素收支的影响。特别是，我们将审查干旱和半干旱生态系统中氮和碳循环的数据，并在较短的(每日到每周)时间尺度上审查数据，并确定可能(和合理的)简化植物-养分关系。为模拟土壤水分(和温度)动态驱动的土壤氮素含量波动提供一个概念性框架。该框架将基于机械生物物理模型、基于过程的氮循环分析和随机土壤水分平衡。该模型将用于分析季节和年际降水波动对干旱和半干旱生态系统氮素收支的影响。这一框架的发展将指明在测试和验证干旱和半干旱生态系统的高分辨率生物地球化学模型时所需的数据类型。一些数据将在当地的现场(弗吉尼亚大学拥有和运营的布兰迪实验农场)收集。然而，收集更广泛(和更适当)的数据将不会由这个项目提供资金，但将成为未来研究的一部分，我们希望在本实验结束时向NSF提出建议

0236621D'OdoricoIn arid and semiarid ecosystems there is a strong dependence of the rates of evapotranspiration, photosynthesis, and net carbon assimilation on the soil water content. Conditions of limited soil water availability lead vegetation into a state of water stress, which, if prolonged, is responsible for loss of turgidity, wilting and death of plants. Soil water content also affects nitrogen cycling, due to the direct or indirect dependence of the processes of decomposition, mineralization, nitrification, denitrification, root uptake, and leaching on the soil moisture conditions. The quantity of available nitrogen in the root zone in turn affects vegetation processes. Thus, through the soil water balance, the hydrological cycle exerts a significant control on terrestrial ecosystems, in particular in arid and semiarid environments, where the rates of evapotranspiration, nutrient mineralization and nutrient uptake are strongly limited by soil water availability. Even though many physiological and biogeochemical mechanisms relating water stress and the nitrogen cycle to soil moisture conditions are understood, a quantitative process-based framework for the analysis and prediction of how hydrologic processes may impact terrestrial ecosystems is still lacking. This type of framework is crucial to the enhancement of the understanding of the effect of climate variability on terrestrial plant communities and ecosystems. Through a stochastic mechanistic model of the soil water balance at the daily time scale we have related hydrologic processes (including evapotranspiration and the intermittent stochastic character of precipitation) to soil water content and expressed this dependence as a function of the characteristics of climate, soil, and vegetation. For this project, we plan to use this framework to investigate the impact of hydrologic conditions on the soil nitrogen budget. In particular we will: Review data on the nitrogen and carbon cycles in arid and semiarid ecosystems and at a short (daily-to-weekly) time scale and identify possible (and sensible) simplifications of the plant-nutrient relationships. Develop a conceptual framework for the modeling of the fluctuations in soil nitrogen content driven by soil moisture (and temperature) dynamics. This framework will be based on mechanistic biophysical models, on a process-based analysis of the nitrogen cycle, and on a stochastic soil water balance.The model will be used to analyze the impact of seasonal and interannual fluctuations in precipitation on the nitrogen budget of arid and semiarid ecosystems. The development of this framework will indicate the type of data that is needed in the testing and validation of high-resolution biogeochemical models in arid and semi-arid ecosystems. Some data will be collected at a local field site (Blandy Experiment Farm owned and operated by the University of Virginia). However, the collection of more extensive (and more appropriate) data will not be funded by this project but will be part of future research which we wish to propose to NSF at the end of this ex