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E. Ashley Steel

Ashley Steel

Statistician / Quantitative Ecologist
Pacific Northwest Research Station
Seattle, WA

Contact via email
Phone: (206)-732-7823
Fax: (206)-732-7801

Curriculum Vitae (89 KB)

Statement of Research:

I apply quantitative tools to study rivers and watersheds. My research has focused on (1) harnessing landscape-scale data to predict in-river conditions; (2) quantification and modeling of complex water temperature regimes; and (3) sensitivity analyses to support the best use of modeled data. I also enjoy collaborations that link ideas and tools developed in aquatic ecology to research on trees, wildlife, fire, and people.

Projects & Activities:

Danube River

Danube River, photo by Ashley Steel

Riverine Landscapes
Natural conditions and human actions with a watershed drive the distribution
of habitats and animals within that watershed. For example, the percentage of
particular geologies with a watershed, road density within the watershed, or
the quantity and spatial location of urbanized areas all contribute to conditions
in streams and rivers within that same watershed. Identifying and quantifying
these relationships is a relatively new and rapidly developing approach to
riverine ecology. Read more.





water temperature variability graphs

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

Water Temperature: Quantifying Complex Thermal Regimes
and Biological Implications on Thermal Variability

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. Read more.

Link to YouTube video on stream temperature variability.







water temperature variability graphs

Results of a Monte Carlo sensitivity analysis of the Ecosystem Diagnosis and Treatment (EDT) model of salmon habitat. See Steel et al. 2009 (Fisheries) and McElhany et al. 2010

Best Use of Modeled Data: Incorporating Uncertainty
in Natural Resource Decision-making

One of the greatest possible contributions of the statistical and quantitative
sciences is to provide guidance on how to incorporate uncertainty in natural
resource decision-making. Projects include model sensitivity analyses that
explain how best to apply modeled data in a management setting.
Read more.









two teachers participating in workshop on the scientific process

Teachers from across the state participating in an all-day workshop on the process of scientific research at the Washington State Science and Engineering Fair. The workshop has been taught every year for the past four years by Ashley Steel and Kathryn Kelsey. In this photo, teachers are collecting quantitative observations about tree seedlings. Seedlings provided by Connie Harrington (USFS PNW Research Station, Olympia, WA).

Scientific and Statistical Thinking
Science is not a series of facts but a process for drawing
conclusions by making structured observations. Scientific and
statistical skills are essential not only for scientists but for
teachers, community organizers, environmental decision-
makers and other citizens. These are the ultimate consumers
of the graphs, inferences, models, and scientific reports produced
through scientific research. Yet, the proportion of the U.S.
population with adequate training in math and science to be able to
evaluate and understand the products of scientific research is
so low as to cause considerable national concern.
Read more.

Selected Publications:


Steel, E.A., A. Muldoon, R.L. Flitcroft, J.C. Firman, K.J. Anlauf-Dunn, K.M. Burnett, R.J. Danehy. 2016. Current landscapes and legacies of land-use past: Understanding the distribution of juvenile coho salmon (Oncorhynchus kisutch) and their habitats along the Oregon Coast, USA. Canadian Journal of Fisheries and Aquatic Sciences Early View.

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.

Zald, H.S.J., T.A. Spies, R. Seidl, R.J. Pabst, K.A. Olsen, E.A. Steel. 2016. Complex mountain terrain and disturbance history drive variation in forest aboveground live carbon density in the western Oregon Cascades, USA. Forest Ecology and Management 366:193-207.


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.


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.

Meznarich, P. 2014. Back to the future: assessing accuracy and sensitivityof a forest growth model. Science Findings 165. Portland, OR: US Department of Agriculture, Forest Service, Pacific Northwest Research Station. 6 p. Research by Susan Hummel (USFS PNW), Maureen Kennedy (Univ. WA), and Ashley Steel (USFS PNW) and others.

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).


Hummel, S., M. Kennedy, and E.A. Steel. 2013. Assessing forest vegetation and fire simulation model performance after the Cold Springs wildfire, Washington, USA. Forest Ecology and Management 287:40-52.

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.

Steel, E.A., M.C. Kennedy, P.G. Cunningham, and J.S. Stanovick. 2013. Applied statistics in ecology: common pitfalls and simple solutions. Ecosphere 4:115. Available at http://www.esajournals.org/doi/abs/10.1890/ES13-00160.1


O’Callaghan, J. with E.A. Steel and K.M. Burnett. February 2012. Thinking Big: Linking Rivers to Landscapes. PNW Research Station Science Findings. Available at http://www.fs.fed.us/pnw/sciencef/scifi139.pdf

Seidl, R., T.A. Spies, W. Rammer, E.A. Steel, R.J. Pabst, and K. Olsen. 2012. Multi-scale drivers of spatial variation in old-growth forest carbon density disentangled with Lidar and an individual-based landscape model. Ecosystems 15:1321-1335.

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

Steel, E.A., D.W. Jensen, K.M. Burnett, K. Christiansen, J.C. Firman B.E. Feist, K. Anlauf, and D.P. Larsen. 2012. Landscape characteristics and coho salmon (Oncorhynchus kisutch) distributions: explaining abundance versus occupancy. Canadian Journal of Fisheries and Aquatic Sciences 69:457-468.

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. Ecospheres 3: 104. Available at http://www.esajournals.org/doi/pdf/10.1890/ES12-00255.1


Anlauf, K.J., D.W. Jensen, E.A. Steel, K.M. Burnett, K. Christiansen, J.C. Firman, B.E. Feist, and D.P. Larsen. 2011. Explaining spatial variability in stream habitats using both natural and management-influenced landscape predictors. Aquatic Conservation: Marine and Freshwater Ecosystems 21:704-714.

Firman, J.C., E.A. Steel, D.W. Jensen, K.M. Burnett, K. Christiansen B.E. Feist, and D.P. Larsen. 2011. Landscape models of coho salmon (Oncorhynchus kisutch) distribution in western Oregon: implications for management associated with spatial extent. Transactions of the American Fisheries Society 140:440-455.

Fullerton, A.H., S.T. Lindley, G.R. Pess, B.E. Feist, E.A. Steel, and P. McElhany. 2011. Human influence on the spatial structure of threatened Pacific salmon metapopulations. Conservation Biology 25(5):932-944.

Lucero, Y., E.A. Steel, K.M. Burnett, K. Christiansen. 2011. Untangling human development and natural gradients: Implications of underlying correlation structure for linking landscapes and riverine ecosystems. River Systems 19(3):207-224.


Feist, B.E., E.A. Steel, D.W. Jensen and D.N.D Sather. 2010. Does the scale of our observational window affect our conclusions about correlations between endangered salmon populations and their habitat? Landscape Ecology 25(5):727–743.

Fullerton, A.H., K.M. Burnett, E.A. Steel, R.L. Flitcroft, B.E. Feist, C.E. Torgersen, D.J. Miller, B.L. Sanderson. 2010. Hydrological connectivity for riverine fish: measurement challenges and research opportunities. Freshwater Biology, 55:2215-2237.

Fullerton, A.H., D. Jensen, E.A. Steel, D. Miller, and P. McElhany. 2010. How certain are salmon recovery forecasts? A watershed-scale sensitivity analysis. Environmental Modeling and Assessment 15(1):13-26.

Fullerton, A.H., A. Steel, Y. Caras, and I. Lange. 2010. Effects of spatial pattern and economic uncertainties on freshwater habitat restoration planning: a simulation exercise. Restoration Ecology 18(S2):354-369.

McElhany, P., E.A. Steel, D. Jensen, K. Avery, N. Yoder, C. Busack and B. Thompson. 2010. Dealing with uncertainty in ecosystem models: lessons from a complex salmon model. Ecological Applications 20:465-482.

Steel, E.A., R.M. Hughes, A.H. Fullerton, S. Schmutz, J.A. Young, M. Fukushima, S. Muhar, M. Poppe, B.E. Feist, and C. Trautwein. 2010. Are we meeting the challenges of landscape-scale riverine research? A review. Living Reviews in Landscape Research 4. Available at http://landscaperesearch.livingreviews.org/Articles/lrlr-2010-1/


Fullerton, A., E.A. Steel, Y. Caras, M. Sheer, P. Olson, and J. Kaje. 2009. Putting watershed restoration in context: alternative future scenarios influence management outcomes. Ecological Applications 19:218-235.

Jensen, D.W., E.A. Steel, A.H. Fullerton, and G.R. Pess. 2009. Impact of fine sediment on egg-to-fry survival of Pacific salmon: a meta-analysis of published studies. Reviews in Fisheries Biology 17(3):348-359.

McElhany, P., E.A. Steel, D. Jensen, and K.A. Avery. 2009. Uncertainty in a complex habitat model. Pages 339-356 in E.E. Knudsen and J.H. Michael Jr., editors. Pacific salmon environmental and life history models: advancing science for sustainable salmon in the future. American Fisheries Society, Symposium 71, Bethesda, Maryland.

Sanderson, B.L., C.D. Tran, H. Coe, V. Pelekis, E.A. Steel, W.L. Reichert. 2009. Non-lethal sampling of fish caudal fins yields valuable stable isotope data for threatened and endangered fishes. Transactions of the American Fisheries Society, 138:1166-1177.

Steel, E. Ashley. 2009. Is science really a verb? Educating through scientific thinking. Bulletin of the American Meteorological Society. April: 442-443.

Steel, E.A., T.J. Beechie, M.H. Ruckleshaus, A.H. Fullerton, P. McElhany, and P. Roni. 2009. Mind the gap: Uncertainty and model communication between managers and scientists. Pages 357-372 in E.E. Knudsen and J.H. Michael Jr., editors. Pacific salmon environmental and life history models: advancing science for sustainable salmon in the future. American Fisheries Society, Symposium 71, Bethesda, Maryland.

Steel, E.A., P. McElhany, N.J. Yoder, M.D. Purser, K. Malone, B.E. Thompsen, K.A. Avery, D. Jensen, G. Blair, C. Busack, M.D. Bowen, J. Hubble, T. Kantz, L. Mobrand. 2009. Making the best use of modeled data: Multiple approaches to sensitivity analysis. Fisheries 34 (July):330-339.


Angilletta, M.J. Jr., E.A. Steel, K.K. Bartz, J.G. Kingsolver, M.D. Scheuerell, B.R. Beckman, L.G. Crozier. 2008. Big dams and salmon evolution: changes in thermal regimes and their potential evolutionary consequences. Evolutionary Applications 1:286-289.

Courbois, J., S. Katz, C. Jordan, M. Rub, E.A. Steel, R.F. Thurow, and D.J. Isaak. 2008. Sampling strategies for chinook-salmon spawning populations. Canadian Journal of Fisheries and Aquatic Sciences 65:1814-1830.

E.A. Steel, A.H. Fullerton, Y. Caras, M.B. Sheer, P. Olson, D.W. Jensen, J. Burke, M. Maher, and P. Mcelhany. 2008. A spatially explicit decision support system for watershed-scale management of salmon . Ecology and Society 13(2): 50. [online] URL: http://www.ecologyandsociety.org/vol13/iss2/art50/


Fukushima, M., S. Kameyama, M. Kaneko, K. Nakao, and E.A. Steel. 2007. Modelling the effects of dams on freshwater fish distributions in Hokkaido, Japan. Freshwater Biology 52:1511-1524.

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.


Sheer, M.B. and E.A. Steel. 2006. Lost watersheds: barriers, aquatic habitat connectivity, and species persistence in the Willamette and Lower Columbia basins. Transactions of the American Fisheries Society 135:1654-1669.


Greene, C.M., G.R. Pess, E. Beamer, E.A. Steel, and D.W. Jensen. 2005. Effects of environmental conditions during stream, estuary, and ocean residency on Chinook salmon return rates in the Skagit River, WA. Transactions of the American Fisheries Society 134:1562-1581.

Maher, M., M.B. Sheer, E.A. Steel, and P. McElhany. 2005. Atlas of Salmon and Steelhead Habitat in the Oregon Lower Columbia and Willamette Basins. Northwest Fisheries Science Center, NOAA, 2725 Montlake Blvd East, Seattle, WA 98112.

Roni, P., M. Liermann, C.E. Jordan, and E.A. Steel. 2005. Steps for designing a monitoring and evaluation program for aquatic restoration. In P. Roni (editor), Monitoring stream and watershed restoration, American Fisheries Society, Bethesda, MD., pp 13-34.


Liermann, M., E.A. Steel, M. Rosing, and P.Guttorp. 2004. Random denominators and the analysis of ratio data. Journal of Environmental and Ecological Statistics 11:55-71.

Steel, E.A., B.E. Feist, D. Jensen, G.R. Pess, M. Sheer, J. Brauner, and R.E. Bilby. 2004. Landscape models to understand steelhead (Oncorhynchus mykiss) distribution and help prioritize barrier removals in the Willamette basin, OR, U.S.A. Canadian Journal of Fisheries and Aquatic Sciences 61:999-1011.

Steel, E.A., K.A. Kelsey, J. Morita. 2004. The Truth about Science: A middle school curriculum teaching the scientific method. Journal for Environmental and Ecological Statistics 11:21-29.


Beechie, T. J., E.A. Steel, P. Roni, and E. Quimby (editors). 2003. Ecosystem recovery planning for listed salmon: An integrated assessment approach for salmon habitat. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-58, 183 p.

Feist, B.E., E.A. Steel, G.R. Pess, and R.E. Bilby. 2003. The influence of scale on salmon habitat restoration priorities. Animal Conservation 6:271-282.

Roni, P., M. Liermann, and E.A. Steel. 2003. Monitoring and evaluating fish responses to instream restoration. In D.R. Montgomery, S. Bolton, D. B. Booth, and L. Wall (editors), Restoration of Puget Sound Rivers, University of Washington Press, Seattle, WA, pp 318-339.

Steel, E.A., L. Johnston, B.E. Feist, G. Pess, R.E. Bilby, D. Jensen, T. Beechie, and J. Myers. 2003. Pacific salmon recovery planning and the Salmonid Watershed Analysis Model (SWAM): a broad-scale tool for assisting in the development of habitat recovery plans. Endangered Species Update 20(1):1-32.

Steel, E.A., M.C. Liermann, P. McElhany, N.L. Scholz, A.C. Cullen. 2003. Uncertainty in habitat recovery planning. . In Beechie, T. J., P. Roni, and E.A. Steel (Editors). Ecosystem Recovery Planning for Listed Salmon: Assessment Approaches for Salmon Habitat, NOAA Tech. Memo. NMFS-NWFSC-58, pgs 74-89.

Steel, E.A., W.H. Richards, and K.A. Kelsey. 2003. Wood and wildlife: Benefits of river wood to terrestrial and aquatic vertebrates? American Fisheries Society Symposium 37: 235-247.


Pess, G.R., D.R. Montgomery, R.E. Bilby, E.A. Steel, B.E. Feist, and H.M. Greenberg. 2002. Correlation of landscape characteristics and land use on coho salmon (Oncorhynchus kisutch) abundance, Snohomish River, Washington State, USA. Canadian Journal of Aquatic and Fisheries Science. 59:613-623.

Steel, E.A., and S. Neuhauser. 2002. A comparison of methods for measuring water clarity. Journal of the North American Benthological Society, 21: 326-335.


Steel, E.A., P. Guttorp, J.J. Anderson, and D.C. Caccia. 2001. Modeling juvenile salmon migration using a simple Markov chain. Journal of Agricultural, Biological, and Environmental Statistics 6: 80-88.


Steel, E.A., R.J. Naiman, and S. D. West. 1999. Use of woody debris piles by birds and small mammals in a riparian corridor. Northwest Science 73:19-26.

Steel, E.A. 1999. Effects of temperature and water clarity on juvenile hatchery chinook salmon migration patterns. In R.Sakrison and P. Sturtevant (Editors). Watershed Management to Protect Declining Species. American Water Resources Association, Middleburg, VA, TPS-99-4, 561 pp.

Naiman, R.J., T.J. Beechie, L.E. Benda, D.R. Berg, P.A. Bisson, L.H. MacDonald, M.D. O'Connor, P.L. Olsen and E.A. Steel. 1993. Fundamental elements of ecologically healthy watersheds in the Pacific Northwest coastal ecoregion. In R.J. Naiman and J.R. Sedell, editors. New Perspectives for Watershed Management. Springer-Verlag, New York.