Submitted by Dan Isaak
Hi Everyone, I’m writing with regards to a new national project we have underway that stream techno-geeks might be interested in. We call it “The National Stream Internet Project.” It’s prompted by the fact that accurate, high resolution information to describe the status and trends of water quality and aquatic biotas does not exist for the approximately 2.5 million kilometers of streams and rivers across the United States. It’s not that we don’t have huge amounts of data that could be tapped for such an endeavor; it’s just that the tools to derive useful information from these big data datasets have only been developed recently. The Stream Internet is a vision for how all the parts could be brought together to create an analytical infrastructure for data on stream networks that can be applied consistently anywhere in the country to create new information at low cost. The project is funded by the U.S. Fish & Wildlife Service’s Landscape Conservation Cooperatives program to develop that national infrastructure. When complete, the project will facilitate convenient application of sophisticated spatial statistical models designed specifically for data measured on stream networks (spatial models are described at the SSN/STARS website: http://www.fs.fed.us/rm/boise/AWAE/projects/SpatialStreamNetworks.shtml). The spatial network models can be applied to databases characterized by clustered locations, which provides a strong incentive to develop comprehensive, interagency databases from existing water quality and biological surveys collected by state, federal, tribal, university, and private resource organizations. The spatial network models outperform traditional statistical techniques and enable predictions at ungaged/unmonitored sites, which facilitates development of high-resolution status maps for full river networks (to see a regional application of Stream Internet technologies, visit the NorWeST website: http://www.fs.fed.us/rm/boise/AWAE/projects/NorWeST.html). An additional key component of the Stream Internet is the NHDPlus national digital stream hydrology layer, which provides a geospatial database of all stream reaches and many reach descriptors across the U.S. (Cooter et al. 2010; Wang et al. 2011). With training in stream network statistics and geospatial database development, users anywhere could begin to use these free software and data tools anywhere to develop a wide array of new information about streams and rivers. As the quality and quantity of information improves, the hope is that resource managers will be able to more effectively manage and conserved aquatic resources, or design new studies and monitoring networks that improve our understanding of these systems over time. Key references and additional resources for this project are provided below.
Additional resources
AWAE Science Briefings: National Stream InterNet
The National Stream InterNet Proposal
Cooter, W., J. Rineer, and B. Bergenroth. 2010. A nationally consistent NHDPlus framework for identifying interstate waters: Implications for integrated assessments and interjurisdictional TMDLs. Environmental Management 46:510-524.
Isaak, D., E. Peterson, J. Ver Hoef, S. Wenger, J. Falke, C. Torgersen, et al. 2014. Applications of spatial statistical network models to stream data. Wiley Interdisciplinary Reviews – Water 1:277-294.
Isaak, D., E. Peterson, D. Nagel, J. Ver Hoef, and J. Kershner. 2014. The national stream internet project: An analytical framework for creating new information from old stream data. Federal Caucus meeting for National Fish Habitat Action Plan team members. Washington DC, January 29.
Peterson, E., J. Ver Hoef, D. Isaak, J. Falke, M. Fortin, et al. 2013. Modelling dendritic ecological networks in space: An integrated network perspective. Ecology Letters 16:707-719.
SSN/STARS: Tools for Spatial Statistical Modeling on Stream Networks. Webpage: www.fs.fed.us/rm/boise/AWAE/projects/SpatialStreamNetworks.shtml.
Ver Hoef, J., E. Peterson, D. Clifford, and R. Shah. 2014. SSN: An R package for spatial statistical modeling on stream networks. Journal of Statistical Software 56(3):1-45.
Wang, L., D. Infante, P. Esselman, A. Cooper, D. Wu, et al. 2011. A hierarchical spatial frame-work and database for the national river fish habitat condition assessment. Fisheries 36:436-449.
Tagged Under: data management