REFERENCES

• Arnold J. G., Moriasi D. N., Gassman P. W., and Abbaspour K. C.. 2012. SWAT: model use, calibration, and validation. Transactions of the ASABE 55: 1491–1508.
   Web of Science ®Google Scholar
• Beniston M., Diaz H. F., and Bradley R. S.. 1997. Climate change at high elevation sites: an overview. Climatic Change 36: 233–251.
   Web of Science ®Google Scholar
• Brenden T. O., Wang L., and Seelbach P. W.. 2008. A river valley segment classification of Michigan streams based on fish and physical attributes. Transactions of the American Fisheries Society 137: 1621–1636.
   Web of Science ®Google Scholar
• Cao Y., Hawkins C. P., Olson J., and Kosterman M.. 2007. Modeling natural environmental gradients improves the accuracy and precision of diatom-based indicators. Journal of the North American Benthological Society 26: 566–585.
   Web of Science ®Google Scholar
• Demars B. O. L., Manson J. R., Ólafsson J. S., Gíslason G. M., Gudmundsdóttir R., Woodward G., Reiss J., Pichler D. E., Rasmussen J. J., and Friberg N.. 2011. Temperature and the metabolic balance of streams. Freshwater Biology 56: 1106–1121.
   Web of Science ®Google Scholar
• Esselman P. E., Infante D. M., Wang L., Wu D., Cooper A. R., and Taylor W. W.. 2011. An index of cumulative disturbance to river fish habitats of the conterminous United States from landscape anthoropogenic activities. Ecological Restoration 29: 133–151.
   Google Scholar
• Falcone J. A., Carlisle D. M., Wolock D. M., and Meador M. R.. 2010. GAGES: a stream gage database for evaluating natural and altered flow conditions in the conterminous United States. Ecology 91:621.
   Google Scholar
• Fish Habitat, Climate and Landuse Change (FHCLC). 2011. Forecasting the impact of climate and land-use change on fish habitat at multiple spatial scales. Available: fishhabclimate.org/. (October 2012).
   Google Scholar
• Flebbe P. A., Roghair L. D., and Bruggink J. L.. 2006. Spatial modeling to project southern Appalachian Trout distribution in a warmer climate. Transactions of the American Fisheries Society 135: 1371–1382.
   Web of Science ®Google Scholar
• Frissell C. A., Liss W. J., Warren C. E., and Hurley M. D.. 1986. A hierarchical framework for stream habitat classification-viewing streams in a watershed context. Environmental Management 10: 199–214.
   Web of Science ®Google Scholar
• Gardner B., Sullivan P. J., and Lembo A. J.. 2003. Predicting stream temperatures: geostatistical model comparison using alternative distance metrics. Canadian Journal of Fisheries and Aquatic Sciences 60: 344–351.
   Web of Science ®Google Scholar
• Herlihy A. T., Paulsen S. G., Van Sickle J., Stoddard J. L., Hawkins C. P., and Yuan L. L.. 2008. Striving for consistency in a national assessment: the challenges of applying a REFERENCE condition approach at a continental scale. Journal of the North American Benthological Society 27: 860–877.
   Web of Science ®Google Scholar
• Homer C., Dewitz J., Fry J., and Coan M.. 2007. Completion of the 2001 National Land Cover Database for the conterminous United States. Photogrammetric Engineering and Remote Sensing 73: 337–341.
   Web of Science ®Google Scholar
• Isaak D. J. 2011. Stream temperature monitoring and modeling: recent advances and new tools for managers. Available: http://www.fs.fed.us/rm/pubs_other/rmrs_2011_isaak_d002.pdf. (October 2012).
   Google Scholar
• Isaak D. J., and Hubert W. A.. 2001. A hypothesis about factors that affect maximum summer stream temperatures across montane landscapes. Journal of the American Water Resources Association 37: 351–366.
   Web of Science ®Google Scholar
• Johnson S. L. 2004. Factors influencing stream temperatures in small streams: substrate effects and a shading experiment. Canadian Journal of Fisheries and Aquatic Sciences 61: 913–923.
   Web of Science ®Google Scholar
• Jowett I. G., and Duncan M. J.. 1990. Flow variability in New Zealand rivers and its relationship to in-stream habitat and biota. New Zealand Journal of Marine and Freshwater Research 24: 305–317.
   Web of Science ®Google Scholar
• Keleher C. J., and Rahel F. J.. 1996. Thermal limits to salmonid distributions in the Rocky Mountain region and potential habitat loss due to global warming: a geographic information system (GIS) approach. Transactions of the American Fisheries Society 125: 1–13.
   Web of Science ®Google Scholar
• Kitchell J. F., Stewart D. J., and Weininger D.. 1977. Applications of a bioenergetics model to Yellow Perch (Perca flavescens) and Walleye (Stizostedion vitreum vitreum). Journal of the Fisheries Research Board of Canada 34: 1922–1935.
   Web of Science ®Google Scholar
• Leopold L. B., Wolman M. G., and Miller J. P.. 1964. Fluvial processes in geomorphology. W.H. Freeman and Company, San Francisco, California.
   Google Scholar
• Magnuson J. J., Crowder L. B., and Medvick P. A.. 1979. Temperature as an ecological resource. American Zoologist 19: 331–343.
   Google Scholar
• Martin R. W., and Petty J. T.. 2009. Local stream temperature and drainage network topology interact to influence the distribution of Smallmouth Bass and Brook Trout in a central Appalachian watershed. Journal of Freshwater Ecology 24: 497–508.
   Web of Science ®Google Scholar
• McManamay R. A., Orth D. J., Dolloff C. A., and Frimpong E. A.. 2011. Regional frameworks applied to hydrology: can landscape-based frameworks capture the hydrologic variability? River Research and Applications 28: 1325–1339.
   Web of Science ®Google Scholar
• Mohseni O., Stefan H. G., and Erickson T. R.. 1998. A nonlinear regression model for weekly stream temperatures. Water Resources Research 34: 2685–2692.
   Web of Science ®Google Scholar
• Morris A., Donovan J., and Strager M.. 2009. Geospatial analysis of climatic and geomorphic interactions influencing stream discharge, Appalachian Mountains, USA. Environmental Modeling and Assessment 14: 73–84.
   Web of Science ®Google Scholar
• National Hydrologic Warning Council. 2006. Benefits of USGS streamgaging program: users and uses of USGS streamflow gages. Available: http://documents.clubexpress.com/documents.ashx?key=pk%2fwnyBWQ7Cq%2fNhuIVq8xjkvWLh2p4E%2bNvRuLBgfWMP2AE5%2b7v35WiK6Vawr10Gb. (May 2012).
   Google Scholar
• Olden J. D., and Poff N. L.. 2005. Long-term trends of native and non-native fish faunas in the American Southwest. Animal Biodiversity and Conservation 28: 75–89.
   Google Scholar
• Paul M. J., and Meyer J. L.. 2001. Streams in the urban landscape. Annual Review of Ecology and Systematics 32: 333–365.
   Google Scholar
• Peterson E. E., Theobald D. M., and Ver Hoef J. M.. 2007. Geostatistical modelling on stream networks: developing valid covariance matrices based on hydrologic distance and stream flow. Freshwater Biology 52: 267–279.
   Web of Science ®Google Scholar
• Poff N. L., and Allan J. D.. 1995. Functional organization of stream fish assemblages in relation to hydrological variability. Ecology 76: 606–627.
   Web of Science ®Google Scholar
• Poff N. L., Allan J. D., Bain M. B., Karr J. R., Prestegaard K. L., Richter B. D., Sparks R. E., and Stromberg J. C.. 1997. The natural flow regime: a paradigm for river conservation and restoration. BioScience 47: 769–784.
   Web of Science ®Google Scholar
• Poff N. L., Bledsoe B. P., and Cuhaciyan C. O.. 2006. Hydrologic variation with land use across the conterminous United States: geomorphic and ecological consequences for stream ecosystems. Geomorphology 79: 264–285.
   Web of Science ®Google Scholar
• Poole G. C., and Berman C. H.. 2001. An ecological perspective on in-stream temperature: Natural heat dynamics and mechanisms of human-caused thermal degradation. Environmental Management 27: 787–802.
   PubMed Web of Science ®Google Scholar
• R Development Core Team. 2012. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
   Google Scholar
• Tockner K., Malard F., and Ward J. V.. 2000. An extension of the flood pulse concept. Hydrological Processes 14: 2861–2883.
   Web of Science ®Google Scholar
• Tsang Y.-P., Felton G. K., Moglen G. E., and Paul M.. 2011. Region of influence method improves macroinvertebrate predictive models in Maryland. Ecological Modelling 222: 3473–3485.
   Web of Science ®Google Scholar
• U.S. Environmental Protection Agency (USEPA). 2010. Environmental Monitoring & Assessment Program. Available: http://www.epa.gov/emap/. (March 2013).
   Google Scholar
• U.S. Environmental Protection Agency and U.S. Geological Survey. 2005. National hydrography dataset plus version 1.0, NHDPlusV1. Available: tems.com/nhdplus/. (March 2010).
   Google Scholar
• U.S. Geological Survey (USGS). 2006. National Elevation Dataset. Available: http://ned.usgs.gov/. (March 2010).
   Google Scholar
• Vogel R., Wilson I., and Daly C.. 1999. Regional regression models of annual streamflow for the United States. Journal of Irrigation and Drainage Engineering 125: 148–157.
   Web of Science ®Google Scholar
• Wagner T., Soraano P. A., Cheruvelil K. S., Renwick W. H., Webster K. E., Vaux P., and Abbitt R. J. F.. 2008. Quantifying sample biases of inland lake sampling programs in relation to lake surface area and land use/cover. Environmental Monitoring and Assessment 141: 131–147.
   PubMed Web of Science ®Google Scholar
• Wehrly K. E., Brenden T. O., and Wang L. Z.. 2009. A comparison of statistical approaches for predicting stream temperatures across heterogeneous landscapes. Journal of the American Water Resources Association 45: 986–997.
   Web of Science ®Google Scholar