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Diversity of Natural Thermal Regimes

Water temperature variability graphs.

Figure from Steel et al. 2012, Ecospheres 3: 104

Natural riverine thermal regimes are extremely diverse.
Water temperatures fluctuate over days, months, and seasons.
These complex patterns shift from headwaters to the mouth and
across side-channels and mainstem habitats. Humans affect
these natural thermal regimes not just by increasing
the mean temperature but by shifting the variability of
thermal regimes. Some dams, for example, have significantly
reduced thermal variability (Steel et al. 2007).

Ashley Steel
Colin Sowder, Statistics, University of Washington
Brian Beckman, Don Larson, Tim Beechie, and Aimee Fullerton, NOAA Northwest Fisheries Science Center
Christian Torgersen, USGS Cascadia Research Station
Erin Peterson, CSIRO, Australia
Abby Tillotson, Fisheries, University of Washington and NOAA Northwest Fisheries Science Center

Research Description:

To explore the importance of complexity in river thermal regimes, we are leading or collaborating
on a series of projects.

Link to YouTube video on stream temperature variability.

  • Using an 8-year time series of water temperature data collected every 30 minutes across multiple side channels of a
    relatively undisturbed floodplain, we are quantifying both the spatial and temporal complexity in natural floodplain thermal
    regimes and identifying a suite of water-temperature metrics to capture the key elements of river thermal regime that are
    biologically important for salmonids.
  • We conducted experiments on early life stages of Chinook salmon (Oncorhynchus tshawytscha) that demonstrated the
    potential for significant biological consequences of alterations to the water temperature regime. We estimate that altered
    variance alone (with relatively little change in the daily mean temperature) could lead to a difference in emergence timing
    of nearly a week in streams with winter temperatures averaging 3ºC (Steel et al. 2011, also Science Findings 163). We are
    collaborating on a set of follow-up experiments at NOAA’s NW Fisheries Science Center to identify whether there are
    differences in how populations of the same species, or even families within populations, react to altered thermal regimes.
  • We are participating in a large collaborative group, originally funded by the National Center for Ecological Analysis and
    Synthesis (NCEAS), to explore applications of new statistical models that incorporate the network structure of correlation
    in stream data (Peterson et al. 2013). Applications of these new statistical approaches for management and monitoring
    applications are constantly under development.  A synthesis can be found in Isaak et al. (2014).
  • We have installed a network of water-temperature monitoring stations across the Snoqualmie and Raging Rivers
    outside Seattle, WA, and are exploring the application of network-based models to a wide range of thermal metrics,
    including metrics that describe both mean temperature and variance in temperature, and metrics that describe
    summer temperatures, winter temperatures, and temperatures during critical salmon life stages.


Note: Most PDF files linked in the publications section of this page were not created by the USDA Forest Service, and may not be accessible to screen-reader software. Many publications are open access, and links to the html versions on the journal websites are also provided, where applicable.

Beer, W.N., E.A. Steel. In press. Impacts and implications of temperature variability on Chinook salmon egg development and emergence phenology. Transactions of the American Fisheries Society.

Fullerton, A.H., C.E. Torgersen, J.J. Lawler, E.A. Steel, J.L. Ebersole, S.Y. Lee. In press. Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: effects of scale and climate change. Aquatic Sciences.

Fuhrman, A.E., D.A. Larsen, E.A. Steel, G. Young, B.R. Beckman. 2018. Chinook salmon emergence phenotypes: describing the relationships between temperature, emergence timing, and condition factor in a reaction norm framework. Ecology of Freshwater Fish 27(1): 350-362. Link to DOI: 10.1111/eff.12351.

Marsha, A., E.A. Steel, A.H. Fullerton, C. Sowder. 2018. Monitoring riverine thermal regimes across stream networks: Insights into spatial sampling designs from the Snoqualmie River, WA. Ecological Indicators 84: 11-26. Link to https://doi.org/10.1016/j.ecolind.2017.08.028.

Steel, E.A., T.J. Beechie, C.E. Torgersen, A.H. Fullerton. 2017. Envisioning, quantifying, and managing thermal regimes on river networks. BioScience 67: 506-522. Link to DOI: https://doi.org/10.1093/biosci/bix047.

Steel, E.A., C. Sowder, E. Peterson. 2016. Spatial and temporal variation of water temperature regimes on the Snoqualmie River network. Journal of the American Water Resources Association 52: 769-787.

Fullerton, A.H., C.E. Torgersen, J.J. Lawler, R.N. Faux, E.A. Steel, T.J. Beechie, J.L. Ebersole, S.G. Leibowitz. 2015. Rethinking the longitudinal stream temperature paradigm: region-wide comparison of thermal infrared imagery reveals unexpected complexity of river temperatures. Hydrological Processes 29: 4719-4737.

Oliver, M. 2014. Stream temperature variability: why it matters to salmon. Science Findings 163. Portland, OR: US Department of Agriculture, Forest Service, Pacific Northwest Research Station. 6 p. Research by Ashley Steel (USFS PNW), Brian Beckman, Keith Denton, Aimee Fullerton, Don Larson,and Abby Tillotson (NOAA Fisheries Science Center).

Isaak, D.J., E.E. Peterson, J.M. Ver Hoef, S.J. Wenger, J.A. Falke, C.E. Torgersen, C. Sowder, E.A. Steel, M.-J. Fortin, C.E. Jordan, A.S. Ruesch, N. Som, and P. Monestiez. 2014. Applications of spatial statistical network models to stream data. WIRES – Water 1(3): 277-294.

Peterson, E.E, J.M. Ver Hoef, D.J. Isaak, J.A. Falke, M.-J. Fortin, C.E. Jordan, K. McNyset, P. Monestiez, A.S. Reusch, A. Sengupta, N. Som, E.A. Steel, D.M. Theobald, C.E. Torgersen, and S.J. Wenger. 2013. Modelling dendritic ecological networks in space: an integrated network perspective. Ecology Letters 16:707-719.

Sowder, C., and E.A. Steel. 2012. A note on the collection and cleaning of water temperature data. Water 4: 597-606. Available at http://www.mdpi.com/2073-4441/4/3/597 (Open Access)

Steel, E.A., A. Tillotson, D.A. Larsen, A.H. Fullerton, K.P. Denton, and B.R. Beckman. 2012. Beyond the mean: The role of variability in predicting ecological impacts of stream temperature. Ecosphere 3: 104

Steel, E.A., and I.A. Lange. 2007. Alteration of water temperature regimes at multiple scales: Effects of multi-purpose dams in the Willamette River basin. River Research and Applications 23:351-359.