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

这项研究将使任何可以上网的人都能比较美国数百条溪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联合收割机数据集合并到一个有吸引力的网站上，使数据可以获得。这将使科学家和学生更容易提出有关整个非洲大陆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什么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学到的教训将有助于更有效地管理我们国家的水和森林资源。在过去的十年里，流域生态系统科学的许多文献都集中在获得流域内空间异质性的更精细的细节。这种精细尺度的重点已经确定了个别流域的许多特质，但并没有帮助我们发展关于流域动态的一般理论。大多数流域生态系统研究仍然是相当狭隘的，涉及个别或成对流域的详细研究，或跨多个流域的一小部分属性的调查。宏观系统流域科学，或寻找一般原则，描述跨流域的功能能力和行为，一直是有限的。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。我们在这个提案中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中（MacroSheds）该奖项反映了NSF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进行评估，被认为值得支持的搜索.

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.