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File Size: 290 MB

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Fish Data Analysis Tools (FDAT) Version 2. 2020

(Version: Version 2. 2020)

Data Categories Fish distribution
Water temperature
Fish community structure/diversity
Dates of Data 1999 TO 2019
Data Set Status Complete
Data Set Update Schedule None
Date Data Set Published on StreamNet Data Store 05-29-2020
Project Name & Number BPA, 2017-002-00
Purpose of Data Set Conceptual visualization to extrapolate general fish use and density based on fish data by population for John Day and Snake River Chinook and Steelhead.
Summary / Abstract The Bonneville Power Administration and partner agencies have made significant investments in 126 monitoring juvenile anadromous fish populations within the Columbia River Basin in previous decades. 127 Thousands of reach surveys have been conducted to determine local densities of Chinook salmon and 128 steelhead. Because multiple agencies collect these data for different purposes, fish survey sites are spread 129 widely within and among basins, and some sites are resampled annually to describe temporal trends. 130 Aggregation of these surveys into a large database provides a considerable resource, which among many 131 possible uses, can be used with Spatial Statistical Network (SSN) models to develop new information 132 about patterns in juvenile densities and covariates that affect those patterns. In Phase 1 of the Analysis of 133 Spatial Stream Networks for Salmonids project (BPA contract #77234), we tested the application of SSN 134 models to juvenile Chinook salmon and steelhead trout density surveys from the Grande Ronde and 135 Wallowa River basins in northeastern Oregon (project area: 10,642 km2). Results from the Phase 1 136 analysis were sufficiently promising that Phase 2 was implemented to expand the approach to a larger 137 geographic area that included the John Day and Imnaha river basins of Oregon, as well as all streams 138 accessible to anadromous fish in Idaho (project area: 90,822 km2). Large datasets of juvenile fish surveys 139 for Chinook salmon (n = 6,757) and steelhead (n = 7,436) were aggregated from CRITFC, ODFW, IDFG, 140 USFS, CHaMP, and BioMark for the period of 2000–2018. These data were fit with SSN models and 28 141 covariates were assessed, which included representations of summer temperatures, flow characteristics, 142 channel type, riparian conditions, land-use, land-cover, geology, invasive species, and inter-annual 143 variation in juvenile densities. The final model for Chinook salmon juvenile densities included 144 statistically significant relationships for seven covariates (reach slope, mean summer flow, mean August 145 stream temperature, baseflow index, riparian canopy density, brook trout density, and inter-annual 146 variation in juvenile densities) and explained 57% of the variation in densities at the survey sites across a 147 potential habitat network of 9,064 km. The final model for steelhead accounted for 48% of the variation 148 in densities at the survey sites across a larger potential habitat network of 18,064 km. The steelhead 149 model included six of the same seven covariates as the Chinook salmon model (watershed conifer 150 coverage replaced baseflow index) but response curves indicated different density-habitat relationships 151 between the two species. Chinook salmon densities were highest in medium sized streams and rivers with 152 low reach slopes, cool temperatures, higher brook trout densities, and intermediate levels of riparian 153 canopy cover and baseflow values. Steelhead densities were highest in small streams with higher slopes, 154 warmer temperatures, low brook trout densities, higher proportions of watershed conifer coverage, and 155 intermediate levels of riparian canopy density. The final models were used to create 24 scenarios of 156 juvenile densities throughout the potential habitat networks, which included a baseline composite scenario 157 of average juvenile densities for 2000-2018 (Scenario 1), annual density scenarios from 2000 through 158 2018 (Scenarios 2–20), standard errors of the density predictions (Scenario 21), and three future density 159 scenarios associated with increases in mean August stream temperature of 1°C, 2°C, and 3°C (Scenarios 160 22–24). The scenarios have many potential applications, a few of which are illustrated by calculating 161 population estimates of juvenile Chinook salmon and steelhead by designated population areas and by 162 assessing the sensitivity of juvenile densities to a 2°C increase in August temperatures. The observation 163 datasets of juvenile densities, as well as the predicted density scenarios, were formatted and delivered 164 with this report as ArcGIS shapefiles to facilitate further applications. A companion report done under 165 BPA contract #81134 addresses additional work elements and explores options for open-source and 166 cloud-based spatial data processing, modeling, and visualization of data and results associated with the 167 Analysis of Spatial Stream Networks for Salmonids project.
Broad Biological Groups Fish, Salmon, Temperature
Taxa Chinook salmon Oncorhynchus tshawytscha (Walbaum, 1792)
Steelhead Oncorhynchus mykiss (Walbaum, 1792)
Location John Day, Grande Ronde, Salmon and Clearwater subbasins
NPCC Subbasins (2001 Subbasins) Blue Mountain: Grande Ronde
Mountain Snake: Salmon
Mountain Snake: Clearwater
Columbia Plateau: John Day
Hatcheries none
Dams none
Keywords FDAT, Carrying capacity, density, Chinook. Steelhead, distribution, density
Lead Person and Organization That Created the Data Set Dan J. Isaak 1, USDA Forest Service, Boise, ID
Other Participating Organizations Dan J. Isaak1, Erin E. Peterson2, Jay M. Ver Hoef3, David Nagel1, Sherry Wollrab1, Gwynne Chandler1, Dona Horan1, and Sharon Parkes-Payne1 1USDA Forest Service, Boise, ID 2Queensland University of Technology, Brisbane, QLD, Australia 3NOAA, Seattle, WA
Contact Person for Questions About the Data Name:  Russell Scranton
Position:  Biologist
Organization:  Bonneville Power Administration
Address:  905 NE Lloyd Blvd
Portland, OR  97232
Phone:  503-230-4412
Broad Category of Methods Spatial Stream Network (SSN) block-krige estimation for salmonid abundance v2
Data Collection Methods Electrofishing, and snorkeling
File Formats GIS
Data structure description See data set files.
URL where updated data may be available NA
Some data sets are intrinsically linked to software, tools, models, or statistical procedures, and must be used in association in order to be of value. If this applies to this data set then the following information will apply:
Relationship between the data set and the software, model, etc. GIS Software, R program
Where the software, tools, models, etc. can be obtained if they are not included with the data download. open source tools
Contact person for questions about the software, tools, models, etc. Name:  

Papers, reports, and presentations that were done under this project. Dan J. Isaak1, Erin E. Peterson2, Jay M. Ver Hoef3, David Nagel1, Sherry Wollrab1, Gwynne Chandler1, Dona Horan1, and Sharon Parkes-Payne1 1USDA Forest Service, Boise, ID 2Queensland University of Technology, Brisbane, QLD, Australia 3NOAA, Seattle, WA, Analysis of Spatial Stream Networks for Salmonids Fish Data Analysis Tool, Phase 2 Report: 2020
Restrictions or legal prerequisites for accessing and using this data set. none

File Size: 290 MB