Climatic Controls on Snow-Vegetation Interactions Across an Elevational Gradient

海拔梯度上雪与植被相互作用的气候控制

• 批准号: 1141764
• 负责人: Noah Molotch
• 金额: $ 25.66万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1141764&HistoricalAwards=false
• 关键词: Climatic; Controls; Snow; Vegetation; Interactions

In the higher elevations of the western U.S., seasonal snow accumulation provides the primary source of water input to the terrestrial ecosystem. Recent changes in climate and vegetation cover (e.g. fire suppression, beetle infestation, fire) have potentially large, yet unrealized implications for water availability and ecosystem health. Forest structure has profound effects on snow accumulation and snowmelt via interception, attenuation of solar radiation, and other processes. We currently lack the mechanistic understanding needed to address the impacts of annual, decadal and long-term forest dynamics on snowmelt dynamics and water resources. This project targets this knowledge gap via an integrated observing and modeling approach focused on rates of snow accumulation and snowmelt in open versus sub-canopy conditions across an elevational gradient. Distributed hydrologic instrument clusters spanning an elevational gradient in the Colorado Front Range will be used to explore interactions between snow and vegetation, and improve predictions of snow-vegetation interactions associated with climate and vegetation change. Detailed analyses of canopy radiative transfer using hemispherical photography will be used to explain observed differences in snowpack dynamics and to develop robust forcings for detailed snowmelt simulations. The distributed instrument clusters represent the first comprehensive network of co-located snow, soil, and vegetation water use measurements spanning a continental elevational gradient. The combination of the measurements with new modeling capabilities will enable new understanding of ecohydrological feedbacks and have the potential to fundamentally change our ability to predict ecosystem response to climate change. The mountain snowpack is the primary water source for 60 million people in the Western U.S. and one billion people globally. Recent changes in climate and vegetation cover (e.g. fire suppression, beetle infestation, fire) have potentially large, yet unrealized implications for snowmelt and water sustainability. Patterns of snow accumulation and snowmelt are highly variable in mountainous regions, varying with topography, climate, and vegetation. In mountain forests, the ecological impacts of potential changes in snowmelt and water availability are poorly known. The proposed research targets this knowledge gap using measurements of snow depth and other water-related variables in different types of mountain forests. The measurements will be used to improve models that estimate solar radiation and snowmelt, providing the tools needed to predict ecosystem response to changes in climate or land cover. In this regard, the project will improve understanding of the linkages between snowpack processes and land cover changes. The mountain snowpack is one of the most sensitive hydrologic states to changes in climate. Hence, the improved characterization of snowmelt will broadly address societal vulnerabilities to climate change. The new levels of understanding achieved in this research should have dramatic impacts on the research of others and the conceptual model by which snow covered forested systems are studied. For example, many biogeochemical and ecosystem models have parameterizations which represent the processes studied here. Hence the proposed work will broadly extend to collaborators working at the Niwot Ridge Long Term Ecological Research site and other highland systems. Further, the distribution of snowmelt in these systems dominates water inputs and therefore exerts a strong control on the rate of soil erosion and mineral weathering, affording collaborations with the earth surface and geomorphology communities via NSF?s Boulder Creek Critical Zone Observatory (CZO) network ? with implications for cross-CZO research. Data from this project will be made available to these communities through multiple portals providing a direct link to these other activities. Another important impact of the proposed research will be the educational opportunities.

在美国西部高海拔地区，季节性积雪为陆地生态系统提供了主要的水源。最近气候和植被覆盖的变化（如灭火、甲虫侵扰、火灾）对水的可用性和生态系统健康可能产生巨大但尚未实现的影响。森林结构通过拦截、衰减太阳辐射等过程对积雪和融雪具有深远的影响。我们目前缺乏解决年度、年代际和长期森林动态对融雪动态和水资源的影响所需的机制理解。该项目通过综合观测和建模方法，专注于在海拔梯度上开放与亚冠条件下的积雪积累和融雪率，以弥补这一知识差距。分布在科罗拉多前山脉海拔梯度上的水文仪器集群将用于探索雪与植被之间的相互作用，并改进与气候和植被变化相关的雪-植被相互作用的预测。利用半球面摄影技术对冠层辐射传输进行详细分析，将用于解释观测到的积雪动力学差异，并为详细的融雪模拟开发强有力的强迫。分布式仪器集群代表了第一个跨越大陆海拔梯度的位于同一地点的雪、土壤和植被水分利用测量的综合网络。测量与新的建模能力的结合将使我们对生态水文反馈有新的认识，并有可能从根本上改变我们预测生态系统对气候变化的反应的能力。山区积雪是美国西部6000万人和全球10亿人的主要水源。最近气候和植被覆盖的变化（如灭火、甲虫侵扰、火灾）可能对融雪和水的可持续性产生巨大但尚未实现的影响。在山区，积雪和融雪的模式变化很大，随地形、气候和植被而变化。在山地森林中，人们对融雪和水供应的潜在变化所产生的生态影响知之甚少。拟议的研究通过测量不同类型山林的雪深和其他与水有关的变量来解决这一知识差距。这些测量结果将用于改进估算太阳辐射和融雪的模型，为预测生态系统对气候或土地覆盖变化的反应提供所需的工具。在这方面，该项目将增进对积雪过程与土地覆盖变化之间联系的了解。山地积雪是对气候变化最敏感的水文状态之一。因此，对融雪特征的改进将广泛地解决社会对气候变化的脆弱性。在这项研究中取得的新的认识水平应该对其他研究和研究雪覆盖森林系统的概念模型产生重大影响。例如，许多生物地球化学和生态系统模型都具有代表本文研究过程的参数化。因此，拟议的工作将广泛扩展到在尼沃特岭长期生态研究站和其他高地系统工作的合作者。此外，这些系统中融雪的分布支配着水的输入，因此对土壤侵蚀和矿物风化的速度施加了强有力的控制，通过NSF？博尔德溪临界区天文台（CZO）网络？对跨czo研究的启示这个项目的数据将通过多个门户提供给这些社区，这些门户提供了与这些其他活动的直接联系。拟议研究的另一个重要影响将是教育机会。