Collaborative Research: MRA: MACRO-Sheds: Comparative Ecosystem Biogeochemistry at Continental Scales

这项研究将使任何能上网的人都能比较美国数百条河流的流量和化学成分，并探索它们的流域。该项目将把来自许多独立研究项目的数据集合并到一个有吸引力的网站上，使这些数据可用。这将使科学家和学生更容易提出有关整个大陆的水质和河流流动模式的问题。研究人员将利用这些数据来研究哪种类型的流域最能保留养分，从几十年的酸雨中恢复得最快，侵蚀率最高，对洪水和干旱最不敏感。我们从研究许多流域和溪流中吸取的经验教训将有助于更有效地管理我国的水和森林资源。在过去十年中，流域生态系统科学的大部分文献都集中在获取流域内空间异质性的更精细细节上。这种精细尺度的焦点已经确定了单个流域的许多特性，但并没有帮助我们发展关于流域动力学的一般理论。大多数流域生态系统研究仍然相当狭隘，包括对单个或成对流域的详细研究，或对多个流域的一小组属性的调查。宏观系统流域科学，或寻找描述跨流域功能能力和行为的一般原则，一直受到限制。缺乏大规模关注的一个主要原因是数据访问和跨站点集成的挑战。我们的目标是创建一个综合数据集，将所有美国流域生态系统研究合并到一个共同的平台（MacroSheds），并在宏观尺度流域生态系统科学的艺术和实践中培养新一代流域生态系统科学家。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This research will enable anyone with internet access to compare the flow and the chemistry of hundreds of streams throughout the United States and to explore their watersheds. The project will combine data sets from many separate research projects into an attractive Web site that makes the data available. This will make it easy for scientists and students to ask questions about water quality and river flow patterns across the continent. Researchers will use these data to study what types of watersheds are best at retaining nutrients, are recovering most rapidly from decades of acid rain, have the highest erosion rates, and have flow patterns that are least sensitive to floods and droughts. The lessons we learn from studying many watersheds and streams will contribute to more effective management of our nation's water and forest resources.Much of the literature of watershed ecosystem science over the last decade has focused on gaining ever finer detail of spatial heterogeneity within watersheds. This fine-scale focus has identified many idiosyncrasies of individual watersheds but has not helped us develop general theories about watershed dynamics. Most watershed ecosystem studies remain rather parochial, involving detailed studies of individual or paired watersheds, or surveys of a small set of attributes across multiple watersheds. Macrosystem watershed science, or the search for general principles that describe the functional capacity and behavior across watersheds, has been limited. A major reason for this lack of large-scale focus is the challenge of data access and integration across sites. Our goal in this proposal is to create a synthetic dataset that merges all US watershed ecosystem studies into a common platform (MacroSheds) and to enable and train a new generation of watershed ecosystem scientists in the art and practice of macroscale watershed ecosystem science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.