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The StreamNet Data Store is a searchable archive of data sets related to fish and other aquatic resources that are not of the specific data types included in the main StreamNet database. These data sets come from many different sources and are provided for download in their original formats. To add your own data set to the Data Store, use our Data Publishing Service.
StreamNet did not participate in creation of most of these data sets, and we are not able to answer questions about those we did not help develop. For questions about the data sets available from this page, please contact the originator of the particular data set.
To search the Data Store, enter key words, project numbers, species, methods, etc. into the search box below and click "Search".
Analysis of Spatial Stream Networks for Salmonids
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| Data Categories
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Chinook salmon juvenile density estimates
Steelhead juvenile density estimates
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| Dates of Data
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1989 TO 2022
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| Data Set Status
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Complete
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| Data Set Update Schedule
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None planned
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| Date Data Set Published on StreamNet Data Store
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01-08-2025
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| Project Name & Number
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2017-002-00
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| Purpose of Data Set
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Technical services to develop linear networks for salmon densities using spacial statistics and GIS stream networks. Work will be conducted by the US Forest Service Rocky Mountain Research division(s) NorWeST team with NOAA and Queensland University.
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| Summary / Abstract
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These geospatial data were generated by the USDA Forest Service, Rocky Mountain Research Station, Boise Aquatic Sciences Lab, in association with the Analysis of Spatial Stream Networks for Salmonids project that was funded by the Bonneville Power Administration. These data represent modeled Chinook salmon and steelhead juvenile density estimates for the period 1989-2022. The data extent comprises portions of Oregon and Washington, excluding the John Day and Grande Ronde watersheds. Reach density estimates were predicted from geospatial covariates of stream habitat using spatial statistical network (SSN) models, fit to sampling datasets of juvenile fish surveys for Chinook salmon (n = 4,750) and steelhead (n = 12,796). The steelhead dataset was divided into two domains, coastal and interior, with 7,867 and 4,929 samples respectively.
The final model for Chinook salmon juvenile densities included statistically significant relationships for four covariates (reach slope, August stream temperature, mean summer flow, and the average annual density of juvenile Chinook salmon at observation sites) and explained 66% of the variation in fish densities at the survey sites across a potential habitat network of 14,815 km. The final model for the coastal steelhead domain accounted for 50% of the variation in densities at the survey sites across a potential habitat network of 36,697 km. The final model for the interior steelhead domain accounted for 74% of the variation in densities at the survey sites across a potential habitat network of 10,395 km. The steelhead models included similar covariates as the Chinook salmon model but were slightly more complex (percent riparian canopy cover, reach slope, mean August stream temperature, mean summer
flow, percent watershed conifers, and the average annual density of juvenile steelhead at observation sites), and response curves indicated different density-habitat relationships for Chinook salmon and steelhead.
The final models were used to create 39 scenarios of juvenile densities throughout the potential habitat networks, which included a baseline composite scenario representing average juvenile densities for 2000-2018 (S1), annual density scenarios from 1989 through 2022 (S2-S35), standard errors of the density predictions (S36), and three future density scenarios associated with increases in mean August stream temperature of 1°C, 2°C, and 3°C (S37-S39).
Supplemental Information
The ArcGIS shapefiles in this dataset are comprised of feature classes for two species (Chinook salmon and steelhead) and three themes (fish density observation data, model predicted fish densities at 1000 m prediction points for 39 scenarios, and model predicted fish densities for 1000 m streamline segments for 39 scenarios).
Observation point shapefiles are named:
FDAT_Phase3_Chinook_ObservationPoints.shp
FDAT_Phase3_SteelheadCoastal_ObservationPoints.shp
FDAT_Phase3_SteelheadInterior_ObservationPoints.shp
Prediction point shapefiles are named:
FDAT_Phase3_Chinook_PredictionPoints_DensityResults.shp
FDAT_Phase3_SteelheadCoastal_PredictionPoints_DensityResults.shp
FDAT_Phase3_SteelheadInterior_PredictionPoints_DensityResults.shp
Prediction segment shapefiles are named:
FDAT _Phase3_Chinook_StreamSegments_DensityResults.shp
FDAT _Phase3_SteelheadCoastal_StreamSegments_DensityResults.shp
FDAT _Phase3_SteelheadInterior_StreamSegments_DensityResults.shp
The GIS framework for these products is the 1:100,000 scale medium resolution NHDPlus Version 2 dataset.
https://www.epa.gov/waterdata/get-nhdplus-national-hydrography-dataset-plus-data
The NHDPlus was edited to remove braids, diversions, and other non-dendritic features and incorporated into the National Stream Internet (NSI) dataset. https://www.fs.usda.gov/rm/boise/AWAE/projects/NationalStreamInternet.html
Chinook and steelhead range extents were determined from the SteamNet fish dataset for the Pacific Northwest.
https://www.streamnet.org/
Both fish species ranges were extracted from the NSI to generate the Chinook salmon and steelhead streamline shapefiles. The streamlines were segmented into 1000 m
reaches for modeling purposes. A midpoint was generated for each 1000 m segment and juvenile fish densities were predicted at these midpoints. Densities are attributed to both the prediction points and the streamline shapefiles. A 1:1 relationship exists between features in these point and line shapefiles.
The observation point shapefiles represent the midpoint of instream fish survey reaches. Where surveys were conducted during multiple years at the same location, point features are spatially coincident in the shapefile, with the number of overlapping points representing the number of sample years.
Fish density estimates in the attribute tables are represented by fields named with the prefixes S1-S39. Other fields in the shapefiles represent internal codes, NHDPlus attributes, and modeling covariates.
Citations for works referenced in the attributes metadata below:
Hill, R.A., Weber, M.H., Leibowitz, S.G., Olsen, A.R., and Thornbrugh, D.J. 2016. The stream-catchment (StreamCat) dataset: a database of watershed metrics for the conterminous United States. Journal of the American Water Resources Association 52: 120–128.
Isaak, D., Wenger, S., Peterson, E., Ver Hoef, J., Nagel, D., Luce, C., Hostetler, S., Dunham, J., Roper, B., Wollrab, S., Chandler, G., Horan, D., and Parkes-Payne, S. 2017. The NorWeST summer stream temperature model and scenarios for the western U.S.: A crowd-sourced database and new geospatial tools foster a user community and predict broad climate warming of rivers and streams. Water Resources Research, 53: 9181-9205.
Wenger, S.J., C.H. Luce, A.F. Hamlet, D.J. Isaak, and H.M Neville. 2010. Macroscale hydrologic modeling of ecologically relevant flow metrics. Water Resources Research. 46: W09513.
Wolock, D.M. 2003. “Base-flow index grid for the conterminous United States (Open File Rep. 03–263).” Lawrence, KS: U.S. Geological Survey.
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| Broad Biological Groups
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Fishes
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| Taxa
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Chinook salmon Oncorhynchus tshawytscha (Walbaum, 1792)
Steelhead Oncorhynchus mykiss (Walbaum, 1792)
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| Location
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The Phase 3 project area for Chinook salmon and steelhead included all drainages in Oregon and Washington west of the Cascades, as well as those drainages in the interior Columbia River basin that were not modeled in Phase 2 (Figures 1 and 2). This area encompasses 263,000 km2 and is drained by numerous major rivers including the Willamette, Chehalis, Deschutes, Umatilla, and Yakima among others.
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| NPCC Subbasins (2001 Subbasins)
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Basinwide
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| Hatcheries
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NA
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| Dams
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NA
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| Keywords
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Chinook, steelhead, juvenile, density
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| Lead Person and Organization That Created the Data Set
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US Forest Service (USFS)
Daniel Isaak
David Nagel
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| Other Participating Organizations
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Funding provided by Bonneville Power Administration
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| Contact Person for Questions About the Data
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Name: David Nagel
Position:
Organization: USDA Forest Service RMRS
Address: 322 E Front Street, Suite 401
Boise,
ID 83702
USA
Phone: 208-373-4397
email: david.nagel@usda.gov
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| Broad Category of Methods
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GIS modeling
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| Data Collection Methods
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Electrofishing and snorkel field surveys
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| File Formats
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ArcGIS, ArcGIS Pro, QGIS, etc.
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| Data structure description
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Attributes for observation shapefiles
FDAT_Phase3_Chinook_ObservationPoints.shp
FDAT_Phase3_SteelheadCoastal_ObservationPoints.shp
FDAT_Phase3_SteelheadInterior_ObservationPoints.shp
OBSPRED_ID – A unique ID number assigned to each observation instance.
PERMA_FID – A unique ID number assigned to each observation location. Only one PERMA_FID ID is assigned to each fish density observation location.
SITE_ID – An ID assigned by the agency collecting the fish density observation data.
SampleYear – Year observation data was collected.
SOURCE – The collection agency of the fish density observation data.
SOURCENAME – Name of the individual responsible for sampling.
Method – Sampling method.
ChCount or OMCount – Number of individuals within sampling reach.
SNAPPED_X – X coordinate location of the observation site snapped to the streamline network in the native Albers projection of the observation shapefile.
SNAPPED_Y – Y coordinate location of the observation site snapped to the streamline network in the native Albers projection of the observation shapefile.
SiteLength – Sampling reach length.
Mean_Width – Mean stream width at sampling reach where available.
Mean_Depth – Mean depth at sampling reach where available.
Area_ha – 2D area of the water surface within the sampling reach (units ha).
Area_m2 - 2D area of the water surface within the sampling reach (units m2).
Volume_m3 – 3D volume of water column within sampling reach (units m3)
COMID – A unique ID assigned to each stream reach in the NHDPlusV2 coding system.
GNIS_NAME – Stream name where the fish density observation data was collected.
FTYPE – A feature type assigned to each stream reach in the NHDPlusV2 coding system.
WATERBODY – Binary code for waterbodies such as lakes and reservoirs. 1 = waterbody 0 = stream or river
FCODE – A feature code assigned to each stream reach in the NHDPlusV2 coding system.
CUMDRAINAG – Total drainage area at the observation location as determined by the NHDPlusV2 coding system. Units: square km.
CANOPY - Tree canopy density along stream reaches based on classification of remote sensing imagery. Percent canopy derived from the National Land Cover Database 2011 USFS Tree Canopy Cartographic layer averaged over 1 km stream reaches.
SLOPE – Slope of stream reaches, provides a measure of physical habitat structure and channel type. Dataset is value added attribute developed in conjunction with NHDPlusV2.
BFI – Base flow index. (Wolock, 2003)
S1_93_11 – Mean August stream temperature from 1993-2011 from the NorWeST database. (Isaak et al., 2017)
MS_Hist – Mean summer flow in stream reaches for a historical climate period of 1976-1997. Provides a consistent measure of stream size among reaches in the study area. Flow value dataset developed by Wenger et al. (2010) for NHDPlus reaches.
W95_Hist – The number of days with flows exceeding the 95th percentile during the winter. Provides a measure of hydrologic flashiness that differentiates between stream reaches with snowmelt and rainfall runoff regimes. Flow value dataset developed by Wenger et al. (2010) for NHDPlus reaches.
PctConif11 – Watershed area classified as conifer land cover from remote sensing imagery, 2011. (Hill et al., 2016)
YrAvCHD or YrAvOMD – Average annual linear density of juvenile Chinook salmon or steelhead across all the reaches surveyed during individual years from 2000 through 2018.
YrLogAvCHD or YrLogAvOMD – Log10 +1 transformation of YrAvCHD or YrAvOMD linear density values.
CHD or OMD – Linear density of juvenile Chinook salmon or steelhead counted or estimated to occur within a reach and expressed as the number of fish per 100 meters. Fish less than 150 mm were considered to be juveniles for density calculations.
LogCHD or LogOMD – Log10 +1 transformation of CHD or OMD linear density values.
Attributes for prediction point and stream reach results shapefiles
FDAT_Phase3_Chinook_PredictionPoints_DensityResults.shp
FDAT_Phase3_SteelheadCoastal_PredictionPoints_DensityResults.shp
FDAT_Phase3_SteelheadInterior_PredictionPoints_DensityResults.shp
FDAT _Phase3_Chinook_StreamSegments_DensityResults.shp
FDAT _Phase3_SteelheadCoastal_StreamSegments_DensityResults.shp
FDAT _Phase3_SteelheadInterior_StreamSegments_DensityResults.shp
OBSPRED_ID – A unique ID number assigned to each prediction point and matching stream reach.
CANOPY - Tree canopy density along stream reaches based on classification of remote sensing imagery. Percent canopy derived from the National Land Cover Database 2011 USFS Tree Canopy Cartographic layer averaged over 1 km stream reaches.
SLOPE – Slope of stream reaches, provides a measure of physical habitat structure and channel type. Dataset is value added attribute developed in conjunction with NHDPlusV2.
BFI – Base flow index. (Wolock, 2003)
S1_93_11 – Mean August stream temperature from 1993-2011 from the NorWeST database.
MS_Hist – Mean summer flow in stream reaches for a historical climate period of 1976-1997. Provides a consistent measure of stream size among reaches in the study area. Flow value dataset developed by Wenger et al. (2010) for NHDPlus reaches.
W95_Hist – The number of days with flows exceeding the 95th percentile during the winter. Provides a measure of hydrologic flashiness that differentiates between stream reaches with snowmelt and rainfall runoff regimes. Flow value dataset developed by Wenger et al. (2010) for NHDPlus reaches.
PctConif11 – Watershed area classified as conifer land cover from remote sensing imagery, 2011. (Hill et al., 2016)
GNIS_NAME – Stream name where the fish density observation data was collected.
S1_00_18 – Predicted average juvenile fish density for years 2000-2018. Units: fish/100 m.
S2_1989 – Predicted juvenile fish density for year 1989. Units: fish/100 m.
S3_1990 – Predicted juvenile fish density for year 1990. Units: fish/100 m.
S4_1991 – Predicted juvenile fish density for year 1991. Units: fish/100 m.
S5_1992 – Predicted juvenile fish density for year 1992. Units: fish/100 m.
S6_1993 – Predicted juvenile fish density for year 1993. Units: fish/100 m.
S7_1994 – Predicted juvenile fish density for year 1994. Units: fish/100 m.
S8_1995 – Predicted juvenile fish density for year 1995. Units: fish/100 m.
S9_1996 – Predicted juvenile fish density for year 1996. Units: fish/100 m.
S10_1997 – Predicted juvenile fish density for year 1997. Units: fish/100 m.
S11_1998 – Predicted juvenile fish density for year 1998. Units: fish/100 m.
S12_1999 – Predicted juvenile fish density for year 1999. Units: fish/100 m.
S13_2000 – Predicted juvenile fish density for year 2000. Units: fish/100 m.
S14_2001 – Predicted juvenile fish density for year 2001. Units: fish/100 m.
S15_2002 – Predicted juvenile fish density for year 2002. Units: fish/100 m.
S16_2003 – Predicted juvenile fish density for year 2003. Units: fish/100 m.
S17_2004 – Predicted juvenile fish density for year 2004. Units: fish/100 m.
S18_2005 – Predicted juvenile fish density for year 20005. Units: fish/100 m.
S19_2006 – Predicted juvenile fish density for year 2006. Units: fish/100 m.
S20_2007 – Predicted juvenile fish density for year 2007. Units: fish/100 m.
S21_2008 – Predicted juvenile fish density for year 2008. Units: fish/100 m.
S22_2009 – Predicted juvenile fish density for year 2009. Units: fish/100 m.
S23_2010 – Predicted juvenile fish density for year 2010. Units: fish/100 m.
S24_2011 – Predicted juvenile fish density for year 2011. Units: fish/100 m.
S25_2012 – Predicted juvenile fish density for year 2012. Units: fish/100 m.
S26_2013 – Predicted juvenile fish density for year 2013. Units: fish/100 m.
S27_2014 – Predicted juvenile fish density for year 2014. Units: fish/100 m.
S28_2015 – Predicted juvenile fish density for year 2015. Units: fish/100 m.
S29_2016 – Predicted juvenile fish density for year 2016. Units: fish/100 m.
S30_2017 – Predicted juvenile fish density for year 2017. Units: fish/100 m.
S31_2018 – Predicted juvenile fish density for year 2018. Units: fish/100 m.
S32_2019 – Predicted juvenile fish density for year 2019. Units: fish/100 m.
S33_2020 – Predicted juvenile fish density for year 2020. Units: fish/100 m.
S34_2021 – Predicted juvenile fish density for year 2021. Units: fish/100 m.
S35_2022 – Predicted juvenile fish density for year 2022. Units: fish/100 m.
S36_SEofS1 – Standard error of the predicted density estimates for S1.
S37_1C – Predicted future juvenile fish density assuming a 1 degree Celsius increase in mean August stream temperature. Units: fish/100 m.
S38_2C – Predicted future juvenile fish density assuming a 2 degree Celsius increase in mean August stream temperature. Units: fish/100 m.
S39_3C – Predicted future juvenile fish density assuming a 3 degree Celsius increase in mean August stream temperature. Units: fish/100 m.
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| URL where updated data may be available
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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:
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| Relationship between the data set and the software, model, etc.
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Standard GIS software can be used to read the shapefiles in the dataset
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| Where the software, tools, models, etc. can be obtained if they are not included with the data download.
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| Contact person for questions about the software, tools, models, etc.
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Name:
Organization:
Address:
,
Phone:
email:
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| Papers, reports, and presentations that were done under this project.
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| Restrictions or legal prerequisites for accessing and using this data set.
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No
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