Landscape models to understand steelhead (Oncorhynchus mykiss) distribution and help prioritize barrier removals in the Willamette basin, Oregon, USA

We use linear mixed models to predict winter steelhead (Oncorhynchus mykiss) redd density from geology, land use, and climate variables in the Willamette River basin, Oregon. Landscape variables included in the set of best models were alluvium, hillslope < 6%, landslide-derived geology, young (<40 years) forest, shrub vegetation, agricultural land use, and mafic volcanic geology. Our approach enables us to model the temporal correlation between annual redd counts at the same site while extracting patterns of relative redd density across sites that are consistent even among years with varying strengths of steelhead returns. We use our model to predict redd density (redds per kilometre) upstream of 111 probable migration barriers as well as the 95% confidence interval around the redd density prediction and the total number of potential redds behind each barrier. Using a metric that incorporates uncertainty, we identified high-priority barriers that might have been overlooked using only stream length or mean...

[1]  N. LeRoy Poff,et al.  Landscape Filters and Species Traits: Towards Mechanistic Understanding and Prediction in Stream Ecology , 1997, Journal of the North American Benthological Society.

[2]  E. George Robison,et al.  Oregon Department of Forestry Storm Impacts and Landslides of 1996: Final Report , 1999 .

[3]  W. W. Muir,et al.  Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1980 .

[4]  J. Gill.  Hierarchical Linear Models , 2005 .

[5]  G. Pess,et al.  A Review of Stream Restoration Techniques and a Hierarchical Strategy for Prioritizing Restoration in Pacific Northwest Watersheds , 2002 .

[6]  A. Hossain,et al.  A comparative study on detection of influential observations in linear regression , 1991 .

[7]  M. Wiley,et al.  Distributions of Stream Fishes and their Relationship to Stream Size and Hydrology in Michigan's Lower Peninsula , 2002 .

[8]  Stephen P. Rice,et al.  Tributaries, sediment sources, and the longitudinal organisation of macroinvertebrate fauna along river systems , 2001 .

[9]  James R. Anderson,et al.  A land use and land cover classification system for use with remote sensor data , 1976 .

[10]  James D. Hall,et al.  Rock Type and Channel Gradient Structure Salmonid Populations in the Oregon Coast Range , 2003 .

[11]  G. Pess,et al.  The influence of scale on salmon habitat restoration priorities , 2003 .

[12]  Milo C Bell,et al.  Fisheries Handbook of Engineering Requirements and Biological Criteria , 1990 .

[13]  R. Cook.  Detection of influential observation in linear regression , 2000 .

[14]  A. Huryn,et al.  Multi-scale determinants of secondary production in Atlantic salmon (Salmo salar) streams , 1998 .

[15]  M. Wiley,et al.  Influence of Tributary Spatial Position on the Structure of Warmwater Fish Communities , 1992 .

[16]  David A. Belsley,et al.  Regression Analysis and its Application: A Data-Oriented Approach.@@@Applied Linear Regression.@@@Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1981 .

[17]  L. Benda,et al.  Morphology and Evolution of Salmonid Habitats in a Recently Deglaciated River Basin, Washington State, USA , 1992 .

[18]  L. Holtby.  Effects of Logging on Stream Temperatures in Carnation Creek British Columbia, and Associated Impacts on the Coho Salmon (Oncorhynchus kisutch) , 1988 .

[19]  Christopher J. Murray,et al.  Suitability criteria analyzed at the spatial scale of redd clusters improved estimates of fall chinook salmon (Oncorhynchus tshawytscha) spawning habitat use in the Hanford Reach, Columbia River , 2000 .

[20]  L. K. Croft,et al.  Interior Columbia Basin ecosystem management project , 1997 .

[21]  G. Helfman,et al.  Stream biodiversity: the ghost of land use past. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[22]  D. Montgomery,et al.  Channel type and salmonid spawning distribution and abundance , 1999 .

[23]  Danny C. Lee,et al.  Modeling relationships between landscape-level attributes and snorkel counts of chinook salmon and steelhead parr in Idaho , 2000 .

[24]  R. Littell.  SAS System for Mixed Models , 1996 .

[25]  Carl Richards,et al.  Landscape-scale influences on stream habitats and biota , 1996 .

[26]  T. C. Bjornn.  Habitat requirements of salmonids in streams , 1991 .

[27]  C. Daly,et al.  A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain , 1994 .

[28]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[29]  M. L. Murphy,et al.  Vaired Effects of Clear-cut Logging on Predators and Their Habitat in Small Streams of the Cascade Mountains, Oregon , 1981 .

[30]  David R. Bustard,et al.  Aspects of the Winter Ecology of Juvenile Coho Salmon (Oncorhynchus kisutch) and Steelhead Trout (Salmo gairdneri) , 1975 .

[31]  Kapil Aggarwala,et al.  Of Spatial Data , 2006 .

[32]  A. Marshall,et al.  Naturally Spawning Hatchery Steelhead Contribute to Smolt Production but Experience Low Reproductive Success , 2003 .

[33]  Chuck Hollingworth,et al.  Strategies for Restoring River Ecosystems: Sources of Variability and Uncertainty in Natural and Managed Systems , 2005 .

[34]  R. Lunetta,et al.  GIS-based evaluation of salmon habitat in the Pacific Northwest , 1997 .

[35]  D. Montgomery,et al.  Landscape characteristics, land use, and coho salmon (Oncorhynchus kisutch) abundance, Snohomish River, Wash., U.S.A. , 2002 .

[36]  Williams,et al.  Watershed Assessment Techniques and the Success of Aquatic Restoration Activities , 2003 .