COLLABORATIVE RESEARCH: Defining Stream Biomes to Better Understand and Forecast Stream Ecosystem Change

Project: Research project

Project Details


OVERVIEW: Defining stream biomes to better understand and forecast stream ecosystem change PI, E.S. Bernhardt (Duke); coPIs M.J. Cohen (UFL); N.B. Grimm (ASU); R.O. Hall (UWY); J.B. Heffernan; A.M. Helton (U Conn); W.H. McDowell (UNH); B.L. McGlynn (Duke); E.H. Stanley (UWI) and senior personnel J. Read (USGS) Is there such a thing as a ?stream biome?? Most maps or lists of biomes would suggest that flowing waters are either not important enough to deserve a category or are so similar to one another that all streams can be lumped into a single category. From an ecosystem perspective the first conclusion is untenable because we now know that inland waters play critical roles in global carbon (C) and nitrogen (N) cycling. The second conclusion ignores the physical diversity of lotic waters as well as their tendency to be far more temporally dynamic than terrestrial systems. The River Continuum Concept (Vannote 1980) made a first attempt to categorically define annual stream ecosystem behavior (GPP, R and GPP:R) based on network position. Yet the productivity gradient that Vannote et al. 1980 attributed to river size can not be universally applied to rivers in all terrestrial biomes (Minshall et al. 1983). Nor can stream biomes simply be mapped to terrestrial biomes, because for the majority of lotic ecosystems the direct effects of climate drivers on ecosystem energetics are insignificant compared to the effects of disturbance and streamside vegetation. Ultimately the phenology of stream ecosystem energetics will be a function of energy supply (light and fixed terrestrial carbon) and fixed carbon removal (via hydrologic disturbance). Watershed structure determines the route and rate at which water enters stream channels while watershed vegetation determines the magnitude and timing of fixed carbon inputs and the degree and temporal patterning of light availability. Intellectual Merit : INTELLECTUAL MERIT: This research effort will increase our measurements of annual metabolism by nearly two orders of magnitude. At the present time there exist only two streams for which annual metabolic rates have been calculated using continuous dissolved oxygen measurements. By the conclusion of this project 55 years of metabolism data will have been generated for a total of 35 streams, and the project PIs will have acquired (via leveraged funds) metabolism data for at least 150 additional streams. Metabolism metrics from these 185 streams will be used to build the first hierarchical classification of stream ecosystem functional phenology. This stream biome delineation will facilitate estimation of stream metabolic rates at timescales of days to years for spatial scales from reaches to river networks. Simulation models will be developed from first principles and refined with empirical data specific to each biome. These models will allow ecologists to forecast the likely changes in metabolic rates in response to likely climate and land use change scenarios. Broader Impacts : BROADER IMPACTS: This project team intends to set a new bar for data transparency through the work of this proposal. The data management plan has been designed in collaboration with informatics staff of the USGS Center for Integrated Data Analytics and will be carried out in close cooperation with USGS. USGS has agreed to host and help develop a public data repository, modeling, and data visualization platform specifically designed to collate long-term or high-resolution metabolism and dissolved oxygen datasets for streams. All of the raw data generated from this research effort will be made publicly available immediately after collection. By building, refining and activating a community data platform this research program will change the way individual streams are studied and will facilitate and encourage near instantaneous cross-site synthesis. In addition to capacity building, this project will directly support at least 7 graduate students and 7 postdoctoral associates over the funding period. This project will be conducted in collaboration with a wide variety of institutional partners, including USGS, NEON, NCASI, and the Karuk Tribe who have already committed to provide high quality monitoring data in anticipation of the value added data derivatives that our data platform can provide.
Effective start/end date9/15/158/31/22


  • NSF: Directorate for Biological Sciences (BIO): $547,569.00


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