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

Duke University, Durham NC

Investigators

Abstract

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.