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Assessment of Habitat Use by Juvenile Chinook Salmon ( Oncorhynchus tshawytscha ) in the Willamette River Basin, 2020–21

Gabriel S. Hansen, Russell W. Perry, Tobias J. Kock, James S. White, Philip V. Haner, John M. Plumb · U.S. Geological Survey

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Prepared in cooperation with the U.S. Army Corps of Engineers

Assessment of Habitat Use by Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, Oregon, 2020–21

Open-File Report 2023–1001

U.S. Department of the Interior U.S. Geological Survey

Cover. The Willamette River near Harrisburg, Oregon. Photograph taken by Tobias Kock, U.S. Geological Survey, May 7, 2019

Assessment of Habitat Use by Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, Oregon, 2020–21 By Gabriel S. Hansen, Russell W. Perry, Tobias J. Kock, James S. White, Philip V. Haner, John M. Plumb, and J. Rose Wallick

Prepared in cooperation with the U.S. Army Corps of Engineers

Open-File Report 2023–1001

U.S. Department of the Interior U.S. Geological Survey

U.S. Geological Survey, Reston, Virginia: 2023

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment—visit https://www.usgs.gov or call 1–888–ASK–USGS. For an overview of USGS information products, including maps, imagery, and publications, visit https://store.usgs.gov/. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner. Suggested citation: Hansen, G.S., Perry, R.W., Kock, T.J., White, J.S., Haner, P.V., Plumb, J.M., and Wallick, J.R., 2023, Assessment of habitat use by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21: U.S. Geological Survey Open-File Report 2023–1001, 20 p., https://doi.org/10.3133/ofr20231001. ISSN 2331-1258 (online)

iii

Acknowledgments We thank the U.S. Army Corps of Engineers for funding this research and extend a special thanks to Rich Piaskowski, Jake MacDonald, and Rachel Laird for their interest and involvement. Several people provided insights and knowledge about the Willamette River including Greg Taylor with U.S. Army Corps of Engineers, Luke Whitman from the Oregon Department of Fish and Wildlife, Brian Bangs with the U.S. Fish and Wildlife Service, and Stan Gregory with Oregon State University. Additionally, we thank U.S. Geological Survey colleagues Brad Liedtke, Laurel Stratton Garvin, Collin Smith, and Jim Peterson for assistance with study design planning, development, implementation, and analysis. Data are not currently available from the funding organization, the U.S. Army Corps of Engineers. Contact the U.S. Army Corps of Engineers for further information.

Contents Acknowledgments��iii Abstract��1 Introduction��1 Methods��2 Study Area��2 Sampling Designs��2 Stratified Sampling Design��2 Targeted Sampling Design��2 River Conditions��4 Data Collection��5 Evaluating Prediction by the Habitat Suitability Criteria��5 Data Analysis and Modeling��5 General Observations on Habitat Use��5 Resource Selection Functions��7 Characterizing Differences in Habitat Assessment Methodology��7 Results��7 River Conditions��7 Sampling Locations��8 Assessment of the Habitat Suitability Criteria��8 General Observations on Habitat Use��9 Logistic Regression Model Results��9 Habitat Suitability Criteria and Resource Selection Function Comparison��17 Discussion��18 References Cited��19

Figures 1. 2.

3. 4. 5.

6. 7.

Map showing reaches where habitat sampling occurred during April–July 2020 and 2021 on the mainstem Willamette River, Santiam River, and McKenzie River��3 Diagrams showing representative hydraulic model prediction and detailed sampling water depth and velocity groups used to proportionally distribute cells for a sampling location at a specific streamflow��4 Image showing example of general habitat designation: main channel, side channel, and alcove��6 Graphs showing mainstem Willamette River streamflow and water temperature for April, June, and July at Harrisburg, Oregon, 2015–21��8 Maps showing sampling locations for reaches on the mainstem Willamette River from Eugene to McCartney, McCartney to Peoria, Peoria to Corvallis, and Corvallis to the Santiam River confluence, 2020 and 2021��10 Maps showing sampling locations on the North Santiam River and McKenzie River in 2021��11 Histograms showing the distribution of data collected for individual habitat variables��12

Monthly plots showing water depth and water velocity measured at each habitat cell during the study��13 9. Model of predicted probabilities of observing juvenile Chinook salmon for velocity at mean depth and depth at mean velocity with confidence intervals by month��15 10. Estimated presence probability from the resource selection function for juvenile Chinook salmon based on water velocity and water depth��16 11. Graphs showing receiver operating characteristic curve with Narrow, Median, and Broad category thresholds for selected models��17

Tables 1. 2. 3.

4. 5. 6.

Depth and velocity groups used to stratify habitat suitability categories��4 Sampling dates, river, mean streamflow, mean river temperature and number of habitat cells by sampling design��9 Number of habitat cells where juvenile Chinook salmon were observed, and not observed in relation to the Median habitat suitability criteria used by the hydraulic habitat model��13 Number of habitat cells by habitat category, month, and juvenile Chinook salmon observation��13 Candidate models characteristics: modeling structure, parameters, AICc, delta AICc, and AUC values and model accuracy for selected models��14 Comparison of habitat suitability criteria and resource selection function classification categories used to estimate habitat suitability for juvenile Chinook salmon��18

Conversion Factors U.S. customary units to International System of Units Multiply

To obtain

Length inch (in.)

25.4

millimeter (mm)

foot (ft)

0.3048

meter (m)

mile (mi)

1.609

kilometer (km)

Area acre

4,047

square meter (m2)

square foot (ft2)

0.09290

square meter (m2)

square mile (mi2)

2.590

square kilometer (km2)

Volume cubic foot (ft3)

0.02832

cubic meter (m3)

Flow rate foot per second (ft/s)

0.3048

meter per second (m/s)

vii

Multiply cubic foot per second (ft3/s)

By 0.02832

To obtain cubic meter per second (m3/s)

International System of Units to U.S. customary units Multiply

To obtain

Length millimeter (mm)

0.03937

inch (in.)

meter (m)

3.281

foot (ft)

kilometer (km)

0.6214

mile (mi)

Area square meter (m2)

0.0002471

acre

square meter (m2)

10.76

square foot (ft2)

square kilometer (km2)

0.3861

square mile (mi2)

cubic meter (m3)

35.31

Volume cubic foot (ft3)

Flow rate meter per second (m/s)

3.281

foot per second (ft/s)

cubic meter per second (m3/s)

35.31

cubic foot per second (ft3/s)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows: °F = (1.8 × °C) + 32. Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows: °C = (°F – 32) / 1.8.

Abbreviations AICc

Akaike Information Criterion

AUC

area under the curve

RSF

resource selection function

rkm

river kilometer

SWIFT

Science of the Willamette Instream Flow Team

USGS

U.S. Geological Survey

Assessment of Habitat Use by Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21 By Gabriel S. Hansen, Russell W. Perry, Tobias J. Kock, James S. White, Philip V. Haner, John M. Plumb, and J. Rose Wallick

Abstract

Introduction

We conducted a field study during 2020–21 to describe habitat use patterns of juvenile Chinook salmon (Oncorhynchus tshawytscha) in the mainstem Willamette, McKenzie, and Santiam Rivers and to evaluate how habitat suitability criteria affected the predictive accuracy of a hydraulic habitat model. Two approaches were used to collect habitat use data: a stratified sampling design was used to ensure that a representative sample of available habitats was included in our sampling; and a targeted sampling design was used to collect additional data in habitat cells where juvenile Chinook salmon were observed. Habitat attributes and fish presence data were collected in habitat cells that were approximately 2 square meters during April, June, and July. A total of 632 cells were sampled during the study and included habitat located in the main channel (373 cells), side channels (228 cells), and in alcoves (31 cells). Juvenile Chinook salmon were observed in 42 percent of the cells located in the main channel, 38 percent of the cells located in side channels, and 7 percent of the cells located in alcoves. We used logistic regression to develop resource selection functions for April, June, and July, which produced probability-based predictions of habitat use for juvenile Chinook salmon based on water velocity and water depth. The resource selection functions revealed a habitat shift by juvenile Chinook salmon to locations with higher water velocities and greater water depths from April to July as juvenile Chinook salmon size increased. The resource selection functions that we developed are an important addition to habitat modeling in the Willamette River basin because they were developed from in-basin data, capture seasonal differences in habitat use, and facilitate probability-based estimates of habitat use for juvenile Chinook salmon. These advancements will improve habitat modeling efforts for juvenile Chinook salmon during spring and summer months within the Willamette River.

Flow management is important for the U.S. Army Corps of Engineers which owns and operates the Willamette Project encompassing 13 dams located on large tributaries to the mainstem Willamette River in western Oregon. Resource managers consider multiple factors when making flow management decisions including considerations protecting and enhancing spring Chinook salmon (hereinafter referred to as Chinook salmon; Oncorhynchus tshawytscha) and winter steelhead (Oncorhynchus mykiss) populations. The species are native to the Willamette River Basin and are listed as threatened under the U.S. Endangered Species Act (National Oceanic and Atmospheric Administration, 2021). Flow management can have important effects on fish populations migrating and rearing downstream of Willamette Project dams by altering available habitat, migration timing and water temperature. Thus, for effective decision-making, it is important to understand how flow releases from Willamette Project dams influence these variables in the Willamette River Basin (R2 Resource Consultant, Inc., 2014; River Design Group, Inc., and HDR, Inc., 2015; Bond and others, 2017; Whitman and others, 2017). The U.S. Geological Survey (USGS) has provided substantial scientific support to managers tasked with flow management decision-making in the Willamette River Basin (Rounds, 2010; Buccola and others, 2016; Peterson and others, 2021; Stratton Garvin and Rounds, 2022), including a recently completed review of existing datasets and studies and an overview of existing research approaches that could be used to improve the understanding of flow-management effects on salmon and steelhead habitat in the basin (Kock and others, 2021). In this review, the authors identified a lack of in-basin habitat use data as a key data gap to be addressed to improve future river flow and habitat modeling (Kock and others, 2021). Additionally, USGS has developed a hydraulic habitat model that predicts habitat availability for Chinook salmon and steelhead in the mainstem Willamette River and primary tributaries (North Santiam and McKenzie Rivers) across a range of streamflow conditions (White and others, 2022). The

2 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21 hydraulic habitat model used water depth and water velocity data across a range of river flow scenarios and habitat suitability criteria to predict habitat availability for juvenile Chinook salmon and steelhead (Peterson and others, 2021; White and others, 2022). Habitat use data for juvenile Chinook salmon and steelhead in the Willamette River Basin were very limited when the model was developed, so a literature review was conducted to establish a range of water depth and velocity values for these fish, based on data collected in other rivers (Peterson and others, 2021; White and others, 2022). Based on this literature review, White and others (2022) developed three sets of habitat suitability criteria (Narrow, Median, Broad) to classify modeled cells as useable. Individual cells with water velocity or water depth values that fell outside of these criteria ranges were classified as unusable. We conducted a study to advance these modeling efforts and fill a key data gap in the Willamette River Basin by collecting in-basin habitat use data for juvenile Chinook salmon. These data allowed us to assess habitat suitability criteria from White and others’ (2022) hydraulic habitat model to predict the presence of juvenile Chinook salmon while also advancing the state-of-knowledge on habitat use in the Willamette River Basin. The data were additionally used to characterize habitat use in three categories based on location in the river: main channel, side channel, and alcove—an area with downstream connection to the main channel that lacks upstream connection to the river as flow decreases. Finally, the data were modeled using logistic regression to create a resource selection function for comparison to the habitat suitability criteria used in the hydraulic habitat model. This comparison allowed us to illustrate differences between habitat definitions derived from literature-based and in-basin suitability criteria. Data collection occurred during spring and early summer 2020 and 2021, and this report summarizes results from those efforts.

Sampling Designs

Methods

Targeted Sampling Design

Study Area Sampling was conducted in the mainstem Willamette River and lower reaches of the North Santiam and McKenzie Rivers. Sampling occurred on the mainstem Willamette River between the mouth of the McKenzie (river kilometer [rkm] 281) and Santiam (rkm 167) Rivers. Data collection on the North Santiam River occurred in the reach between the Jefferson Bridge Float Launch (rkm 6) and the Stayton Bridge County Boat Ramp near Stayton, Oregon (rkm 27). On the McKenzie River, sampling occurred in the reach between the Hendricks Bridge County Park Boat Ramp (rkm 33) and Taylor Landing (rkm 41; fig. 1). Sampling reaches were selected to ensure data were collected in river reaches where hydraulic habitat model (White and others, 2022) predictions were available.

Fish use and habitat data were collected using two approaches. A stratified sampling design was used to ensure that the distribution of available habitat was adequately represented in our sampling and to provide data suitable for validating the performance of the White and others (2022) hydraulic habitat model. Additionally, a targeted sampling design was used to ensure that we collected sufficient habitat data at locations where juvenile Chinook salmon were observed. For both approaches, we collected fish use and habitat data in individual 2 square meters (m2) sites (hereinafter referred to as “cells”).

Stratified Sampling Design To implement the stratified sampling design, we used outputs from the hydraulic model of White and Wallick (2022) to identify and characterize habitat conditions for sampling locations. Prior to each sampling period, we input predicted streamflow into the hydraulic model to predict water depths and velocities predicted at the sampling location (an approximately 1.6 kilometer [km] section of river). We then proportionally distributed 40 cells into 9 water depth and water velocity groups constrained by expected sampling limitations (fig. 2). Cells were assigned equally (20 each) to 2 categories using classifications aligned with the Science of the Willamette Instream Flow Team (SWIFT; DeWeber and Peterson, 2020; Peterson and others, 2022) median criteria for pre-smolt (>60 millimeters [mm]) juvenile Chinook salmon to represent habitat suitability: habitat and non-habitat (table 1). Habitat and non-habitat categories were used to balance data collection of fish use in habitat conditions where fish were expected to be observed and fish use in habitat conditions where fish were not expected to be observed.

A targeted sampling design was used to collect habitat data at cells where juvenile Chinook salmon were observed. For this design, the snorkeler(s) moved slowly downstream while continuously scanning for juvenile Chinook salmon. Shorelines were observed at random where conditions allowed for snorkeler safety, and area was observed to the extent limited by visibility. To increase the potential for observing juvenile Chinook salmon, snorkelers attempted to observe various conditions (for example, depth, velocity, cover) present on the selected section of river. Once juvenile Chinook salmon were observed, downstream movement was discontinued, an approximately 2 m2 cell was visually established, and the fish were observed for approximately (~) 60 seconds to determine number of fish in the cell. Once the number of fish at the cell was recorded, the sampling crew collected the full suite of habitat data for the cell and then resumed a downstream search for more juvenile Chinook salmon—repeating this process for the remainder of the sampling day.

Methods 3

Figure 1. Map showing reaches (pink shading) where habitat sampling occurred during April–July 2020 and 2021 on the mainstem Willamette, Santiam, and McKenzie Rivers.

4 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21

Figure 2. Representative hydraulic model prediction (A) and detailed sampling water depth and velocity groups (B) used to proportionally distribute cells for a sampling location at a specific streamflow. Table 1. Depth and velocity groups used to stratify habitat suitability categories. [Proportion and cell numbers are provided for a sampling location at a specified streamflow to illustrate the distribution of cells by group using the hydraulic model prediction. Water depth in meters, water velocity in meters per second. Abbreviations: >, greater than; rkm, river kilometer; ft3/s, cubic feet per second]

Group

Water depth

Water velocity

Habitat suitability

rkm 252.6–254.2 at 4,500 ft3/s Proportion by habitat group

Number of cells

0.0–0.5

0.00–0.25

Yes

0.300

0.0–0.5

>0.25–0.50

Yes

0.240

>0.5–1.0

0.00–0.25

Yes

0.306

>0.5–1.0

>0.25–0.50

Yes

0.154

0.0–0.5

>0.50–0.75

0.176

0.0–0.5

>0.75–1.00

0.093

>0.5–1.0

>0.50–0.75

0.358

>1.0–1.5

0.00–0.25

0.258

>1.0–1.5

>0.25–0.50

0.115

River Conditions We compared river flow and water temperature conditions during our study to similar periods during 2015–19 using daily mean streamflow and river temperature data from USGS streamgage 14166000 Willamette River at Harrisburg, Oregon, from April 01 to July 31. To characterize seasonal sampling streamflow and river temperature conditions in a river

segment, we used the nearest upstream gage to the sampling locations. Daily mean streamflow and river temperature data were obtained from existing USGS stream gages accessed on the National Water Information System website (USGS, 2021) for the following stream gages: 14166000 Willamette River at Harrisburg, Oregon; 14171600 Willamette River at Corvallis, Oregon (records streamflow only); 14174000 Willamette River at Albany, Oregon; 14183000 North Santiam River at

Methods 5 Mehama, Oregon (records streamflow only); 14183020 North Santiam River below Stout Creek, near Mehama, Oregon (records river temperature only); 14163900 McKenzie River near Walterville, Oregon.

Data Collection We collected information about fish presence and habitat attributes in each cell that was sampled using both the stratified and targeted sampling designs. Fish presence data included the identification and enumeration of all fish species observed in a cell. Juvenile salmonids were categorized into two size classes based on visual estimation by each snorkeler: less than or equal to (≤) 60 mm and greater than (>) 60 mm. To describe habitat conditions, we collected data on several habitat attributes in each cell. The latitude and longitude (measured at the center of the cell) of each cell location was recorded using a global positioning system (Trimble TDC600 handheld with a Trimble Catalyst DA1 antenna). Water depth (in meters) was also measured at the center of the cell using a 1.5 m topset wading rod. Water velocity was measured using a Sontek Flowtracker handheld acoustic doppler velocimeter. Each water velocity measurement consisted of a 40-second (s) average for two velocity components (the x- and y-planes) from which we calculated a magnitude for the total velocity vector, referred to hereinafter as velocity. Cells that were 0.46 m or shallower were sampled at a single depth (approximately 60 percent of the total depth); cells that were deeper than 0.46 m were sampled at 20 percent and 80 percent of the total depth. Multiple velocity measurements for a cell (depths greater than 0.46 m) were averaged to create a single depth averaged velocity for those cells. The Sontek Flowtracker also recorded water temperature (in degrees Celsius [°C]) in each cell. Substrate was characterized as the diameter in millimeters of the dominant substrate material present within the cell. Bed slope (in degrees) was measured perpendicular to the shoreline using a manual slope inclinometer. Distanceto-shore and distance-to-cover measurements were obtained using a laser rangefinder (Bushnell Scout 1000 ARC, Bushnell Outdoor Products)—distance-to-cover measurements were only recorded if cover was located within 10 m of the cell boundary (we assumed that fish could not effectively use cover located more than 10 m away). Cover type was visually estimated and categorically assigned to one of 7 variables: small woody debris (100 mm diameter or less), large woody debris (greater than 100 mm diameter), aquatic vegetation, terrestrial vegetation, boulder, undercut bank, or not available based on the nearest cover available for the cell. All data collection and sampling occurred during daytime hours. For a selected stratified sampling location, sampling occurred over a 2-day period using methods adapted from Pinnix and others (2019). On the first day, we marked the boundaries of approximately 40 cells with large (76 mm diameter) metal washers and measured habitat conditions in each cell. The sites were left undisturbed overnight to allow

fish to reoccupy the cells. Fish use was recorded on day two, when two snorkelers slowly approached opposite sides of the cell boundaries to observe fish that were present within a cell. Snorkelers remained near the cell boundaries ~60-seconds to observe if fish were moving in or out of the cells. Once the observation period was concluded, data collection in that cell was determined to be complete. The boundary markers were retrieved, and observations from the snorkelers were recorded.

Evaluating Prediction by the Habitat Suitability Criteria To assess the performance of the habitat suitability criteria used in the hydraulic habitat model, we compared fish presence at cells predicted as habitat or non-habitat using the SWIFT habitat criteria. All sampled cells were assigned as habitat or non-habitat based on water depth and velocity measured in the cell using the SWIFT Median habitat criteria for juvenile (pre-smolt) Chinook salmon—water velocity from 0 to 0.38 meters/second (m/s) and water depth from 0.05 to 1.07 m. The cells were then visualized using water depth and velocity bivariate plots by month to illustrate patterns of fish habitat use.

Data Analysis and Modeling Data collected using the stratified sampling design and the targeted sampling design were merged and analyzed as a single dataset for analysis. Data from multiple sources (GPS receiver, acoustic doppler velocimeter, and field datasheets) were merged, examined for discrepancies, and reconciled to create a final dataset. Data compilation, proofing, visualization, and analysis were performed using R statistical software (R Core Team, 2021) and additional packages (ggplot2, pROC) were run in RStudio (Robin and others, 2011; Wickham, 2016; RStudio Team, 2021).

General Observations on Habitat Use Habitat cells were assigned to one of three general categories, based on their location in the river, to allow for comparison of fish use between categories. The three geomorphic unit categories were: main channel, which was defined as the river segment containing the primary streamflow; side channel, which were segments of branching streamflow that maintained connection on both the upstream and downstream end of the segment (and could contain multiple braided sections); and alcoves, where areas were disconnected from upstream flow with connection to the main channel or a side channel on the downstream end (fig. 3). Once cells were assigned to the geomorphic units, we created presence/absence tables for each group by sampling month to provide a general overview of habitat use.

6 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21

Figure 3. Example of general habitat designation: main channel (pink dots), side channel (blue dots), and alcove (green dots).

Results 7

Resource Selection Functions We used logistic regression models to develop resource selection functions (RSF) that estimated the probability of fish presence in a given habitat cell for juvenile Chinook salmon in the Willamette River Basin. Logistic regression was performed using generalized linear models and logit link functions with the form of: logit(P) = b + bX + bY +…bn where

P b X Y n

(1)

is the probability of observing Chinook salmon; are fitted parameters; is a variable/interaction of interest; is an additional variable/interaction of interest; and is the nth variable/interaction of interest.

To parameterize our models, we used depth and velocity with their associated quadratic and interaction terms. Quadratic terms were included to represent the expected biological response displaying an optimal value with asymmetrical tails. The interaction of depth and velocity was included under the assumption the response of fish to a given velocity may depend on depth. We established an a priori candidate set of models (including a null model) to compare relative model performance. The logistic regression models were fit to a binary variable indicating whether Chinook salmon were seen (1) or not seen (0). Finally, a separate set of models were fitted for each month (April, June, July) when data collection occurred to account for observed increases in fish size due to growth of a given year-class of juveniles. Developed logistic regression models were evaluated for fit and compared for performance to select the best-fitting model. Model fit was evaluated by estimating c-hat as a measure of overdispersion and performing a Hosmer-Lemeshow Goodness of Fit test using the R package vcdExtra (Friendly, 2021). To compare models, we used second-order Akaike Information Criterion (AICc) and for the receiver operating characteristic curve, area under the curve (AUC). Models were ranked by lowest AICc value, and we selected the most complex model among the set of models that were within 2.0 AICc points of the lowest-AICc model, since models within 2.0 AICc points are considered competing models. This approach ensured that selected models included quadratic or interaction terms over simpler, less biologically plausible models as long as the more complex model was within 2.0 AICc of the lowest AICc model. The mean accuracy of selected models was estimated using k-fold cross validation from 100 iterations. To illustrate the response of the model to depth and velocity, we created combinations of water depth and velocity as inputs to the resource selection function. For each sampling month we sequentially increased either water depth (0–1.5 m, by 0.01 m) or velocity (0–1.5 m/s, by 0.01 m/s), while

setting the alternate parameter constant at the mean value observed during that period. Secondarily, we created a set of possible combinations for water depths (0–1.5 m, by 0.01 m) and velocity (0–1.5 m/s, by 0.01 m/s) for application of the resource selection functions.

Characterizing Differences in Habitat Assessment Methodology To illustrate the difference between the habitat assessment methodologies of the SWIFT habitat suitability criteria and the resource selection function produced in this study, we used receiver operating characteristic curves to select thresholds to produce Narrow, Median, and Broad categories. For example, one could select 0.5 as the threshold for the probability of presence above which a cell would be classified as habitat and below which it would not be considered as suitable habitat. As the probability threshold increases, the error in false classification of habitat is reduced but not all true habitat classification is incorporated. Thus, a higher probability threshold results in a narrow range of values classified as habitat with reduced errors in false classification. A lower probability threshold incorporates a wider range of values classified as habitat but increases the potential for classifying habitat falsely. The Median category probability thresholds were determined as the point on the curve with the greatest distance from the random chance line. Narrow and Broad category thresholds were calculated as the median of either side of the remaining curve bisected by the Median category threshold. We used the Median threshold probabilities to illustrate how the probability threshold selection corresponds to the true positive and true negative classification. These thresholds represent the minimum probability from which to obtain depth and velocity criteria from the resource selection function. The range of the criteria is determined by the minimum and maximum values of depth and velocities for all probabilities in the resource selection function greater than the threshold value.

Results River Conditions Streamflow and water temperature conditions on the mainstem Willamette River during the study were similar to those observed during previous years in April, June, and July (fig. 4). April streamflow ranged from 5,350 to 15,000 cubic feet per second (ft3/s), June streamflow ranged from 5,000 to 9,000 ft3/s, and July streamflow ranged from 4,000 to 5,250 during both 2020 and 2021. During the last half of July, streamflow was relatively high in 2020, and relatively low in 2021 compared to late-July flow during 2015–19 (fig. 4). Water temperatures were also within normal ranges, compared to 2015–19, and increased from approximately 8–12 °C during April to 16–20 °C in July during both years (fig. 4). For river

8 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21

Figure 4. Mainstem Willamette River streamflow and water temperature for April (A, B), June (C, D), and July (E, F) at Harrisburg, Oregon, 2015–21.

segments where sampling was conducted, mean streamflow ranged from 1,120 ft3/s on the McKenzie to 8,550 ft3/s on the mainstem Willamette River and mean river temperature ranged from 10.4 °C on the McKenzie to 19.1 °C on the mainstem Willamette River on dates when sampling occurred (table 2).

Sampling Locations A total of 634 cells were sampled during 2020–21 with 362 cells sampled using the stratified sampling design and 272 cells sampled using the targeted sampling design (table 2). Most cells (473 cells) were located in the mainstem Willamette River and the remaining cells were located in the McKenzie (78 cells) and North Santiam (83 cells) Rivers (table 2; figs. 5, 6). Data collected in these cells provided a broad range of habitat conditions within the three river sections where sampling occurred (fig. 7).

Assessment of the Habitat Suitability Criteria We found that SWIFT habitat criteria provided a reasonable representation of juvenile Chinook salmon habitat use in the Willamette River during April while there were substantial differences between habitat criteria and observed fish use during June and July (fig. 8; table 3). In April, when fish were smallest (predominantly <60 mm), 92 percent of the cells where juvenile Chinook salmon were observed occurred in habitat defined as suitable by SWIFT criteria (table 3). This declined to 66 percent in June and 27 percent in July (fig. 8; table 3), when observed fish size was larger (generally >60 mm). Data in figure 8 show that juvenile Chinook salmon moved into locations with higher water velocities as the study progressed from April to July, whereas water depth was fairly constant in cells occupied by Chinook salmon juveniles throughout the study period.

Results 9 Table 2. Sampling dates, river, mean streamflow, mean river temperature and number of habitat cells by sampling design. [Mean streamflow units are in cubic feet per second, mean temperature is in degrees Celsius]

Mean streamflow

Mean temperature

Stratified cells

Targeted cells

June 02–03, 2020

Sampling date

Willamette

River

8,200

15.8

June 15–17, 2020

Willamette

8,270

13.7

June 29–July 01, 2020

Willamette

5,255

15.7

July 13–15, 2020

Willamette

4,770

16.9

July 21–23, 2020

Willamette

4,950

19.1

April 18–20, 2021

North Santiam

2,300

11.5

April 21–22, 2021

McKenzie

1,120

10.4

April 28–29, 2021

Willamette

5,565

11.8

June 01, 2021

Willamette

5,740

15.7

June 02, 2021

McKenzie

3,320

13.3

June 03, 2021

North Santiam

1,370

18.1

June 07–10, 2021

Willamette

5,095

14.4

General Observations on Habitat Use Juvenile Chinook salmon were frequently observed in habitat cells located on the main channel and side channels during our sampling but were rarely observed in habitat cells located in alcoves. Juvenile Chinook salmon were observed in 39 percent (246 cells) of the habitat cells which were surveyed (table 4). Nearly all fish observed were in habitat cells located on the main channel or side channels: 99 percent of the habitat cells where juvenile Chinook salmon were observed were located in these habitats. Forty-two percent of the 373 habitat cells located in the main channel, 38 percent of the habitat cells (228) located in side channels, and 7 percent of the 31 habitat cells located in alcoves had Chinook salmon present during sampling (table 4).

Logistic Regression Model Results Model selection criteria resulted in models of similar complexity, containing multiple common parameters, and increasing model accuracy from April to July, as measured by AUC. The selected models for April, June, and July each included parameters for depth, velocity, and quadratic terms for depth and velocity. Additionally, the June and July models also included an interaction between depth and velocity. For April, a total of five candidate models had delta AICc values less than 2.0 (table 5). Based on selection criteria previously described, we selected the model with parameters for velocity, depth, and quadratic terms for velocity and depth. This model had a model accuracy estimate of 0.781 and an AUC

value of 0.635. For June, two candidate models had delta AICc values less than 2.0 (table 5). We selected the model that had the same parameters as the April model and included an interaction between velocity and depth. This model had a model accuracy estimate of 0.790 and an AUC value of 0.726 (table 5). For July, the only model that met our criteria had the same parameters as the June model and this model had a model accuracy estimate of 0.854 and an AUC value of 0.837 (table 5). We plotted resource selection functions separately for depth and velocity to illustrate the predicted response to changes in these variables (fig. 9). The maximum predicted probability in April was 0.776 at a velocity of 0.07 m/s and 0.748 at a depth of 0.60 m (fig. 9). In June, the maximum probability was 0.654 when water velocity was at 0.46 m/s velocity and 0.628 when water depth was 0.76 m. Maximum probabilities in July were 0.392 at 0.73 m depth and 0.686 at 0.87 m/s velocity (fig. 9). Because of the higher order terms in the model (for example, interactions), we also plot the resource selection functions for water velocity and water depth to illustrate how the probability of presence depends jointly on both variables (fig. 10). The highest probability of presence in April was predicted to be in habitat cells with water depths of 0.60 m and water velocities of 0.07 m/s. During June, peak presence was predicted in cells where water depth was 0.80 m and water velocity was 0.40 m/s. Finally, in July, peak presence was predicted for habitat cells where water depth was 0.93 m and water velocity was 1.02 m/s (fig. 10).

10 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21

Figure 5. Sampling locations for reaches on the mainstem Willamette River from Eugene to McCartney (A), McCartney to Peoria (B), Peoria to Corvallis (C), and Corvallis to the Santiam (River) Confluence (D), 2020 and 2021. Yellow circles represent cells collected using a stratified sampling design and purple circles represent cells collected during a targeted sampling design.

Results 11

Figure 6. Sampling locations on the North Santiam River (A) and McKenzie River (B) in 2021. Yellow circles represent cells collected using a stratified sampling design and purple circles represent cells collected during a targeted sampling design.

12 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21

Figure 7. Histograms showing distribution of data collected for individual habitat variables. Distance-to-cover data does not include 243 cells where cover was not available within 10 meters of the habitat cell.

Results 13

Figure 8. Monthly plots showing water depth and water velocity measured at each habitat cell during the study. Yellow circles are habitat cells where juvenile Chinook salmon (Oncorhynchus tshawytscha) were observed and purple circles are habitat cells where juvenile Chinook salmon were not observed. The blue box outlines the zone defined as suitable habitat by the Science of the Willamette Instream Flow Team Median criteria. Table 3. Number of habitat cells where juvenile Chinook salmon (Oncorhynchus tshawytscha) were observed, and not observed in relation to the Median habitat suitability criteria used by the hydraulic habitat model. Median criteria

Chinook observed No

Yes

Table 4. Number of habitat cells by habitat category, month, and juvenile Chinook salmon (Oncorhynchus tshawytscha) observation.

Habitat category

Unsuitable

34 16

April No

April Suitable

Habitat cells with juvenile Chinook observation June Yes

July Yes

Yes

Alcove

Main channel

110

Side channel

104

June Suitable

134

Unsuitable

July Suitable

Unsuitable

14 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21 Table 5. Candidate models characteristics: modeling structure, parameters, AICc, delta AICc, and AUC values and model accuracy for selected models. [Abbreviations: V, velocity; D, depth; AICc, second-order Akaike Information Criterion; AUC, area under the receiver operating characteristic curve; --, no data]

Modeling structure

Parameters

AICc

Delta AICc

AUC

Model accuracy

April V

176.06

0.00

V+D+D2

176.63

0.57

V+D+V2+D2

177.00

0.94

0.635

0.781

V+D+V2

177.72

1.65

V+D

177.80

1.74

V+D+V2+D2+VD

178.43

2.37

null

184.52

8.46

186.21

10.14

V+D+V2+D2

318.72

0.00

V+D+V2+D2+VD

318.95

0.23

0.726

0.790

V+D+V2

330.03

11.31

V+D+D2

338.24

19.52

350.02

31.31

null

351.32

32.60

V+D

351.48

32.76

353.26

34.54

-0.854

June

July V+D+V2+D2+VD

201.05

0.00

0.837

V+D+V2+D2

203.08

2.03

V+D+D2

206.08

5.03

V+D+V2

215.29

14.24

220.00

18.95

V+D

221.42

20.37

null

259.59

58.54

261.35

60.30

Results 15

Figure 9. Model predicted probabilities of observing juvenile Chinook salmon (Oncorhynchus tshawytscha; heavy curved lines) for velocity at mean depth and depth at mean velocity with confidence intervals (grey shaded areas) by month. Filled areas represent kernel density estimates of juvenile Chinook salmon observations.

16 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21

Figure 10. Estimated presence probability from the resource selection function (RSF) for juvenile Chinook (Oncorhynchus tshawytscha) salmon based on water velocity and water depth.

Results 17

Habitat Suitability Criteria and Resource Selection Function Comparison Thresholds were established for the resource selection function to compare with the SWIFT habitat suitability criteria categories (Narrow, Median, and Broad) using receiver operating characteristic curves. The probability thresholds above which cells were classified as habitat were 0.73, 0.59, and 0.42 for Narrow, Median, and Broad categories, respectively, for April. At the Median category threshold for April the true positive rate was 0.88 and true negative rate 0.44 (fig. 11). This reflects a high proportion of positive observations correctly classified as positive and slightly less than half of the negative observations correctly classified as negative. The June Narrow, Median, and Broad categories probability thresholds were 0.55, 0.40, and 0.23. The Median threshold in June displayed a lower true positive rate (0.69), but a higher true negative rate (0.68) resulting in slightly better predictive classification as compared with the April model (fig. 11). The July probability thresholds for the Narrow, Median, and Broad categories were 0.44, 0.17, and 0.04. The true positive rate (0.93) and true negative rate (0.65) for the July Median threshold resulted in the best predictive classification observed for the 3 months, further represented by July having the highest AUC (fig. 11). Habitat use limits from the habitat suitability criteria for fry sized salmonids was compared to the April resource selection function values (table 6). For velocity, the resource selection function predicts a 120–180 percent increase in the maximum value for the three classification categories, while minimum velocity criteria values for both the resource selection function and the habitat suitability index was 0.00 m/s. Minimum depth values for the habitat suitability criteria remains constant at 0.05 m while the resource selection function varies from 0.02 to 0.37 m from the Broad to Narrow classification. Maximum depth criteria vary from 0.61 to 1.52 m for the habitat suitability criteria (from the Narrow to Broad classification), but only ranges from 0.83 to 1.18 m for the resource selection function. A greater difference was observed comparing the presmolt values from the habitat suitability criteria with the resource selection function limits for July (table 6). Velocity criteria minimum (0.08–0.47 m/s) and maximum (1.50 m/s) values were greater for all classification groups produced from the resource selection function compared to the habitat suitability index minimum (0 m/s) and maximum (0.91–0.38 m/s) values. Similarly, minimum (0.27–0.54 m) and maximum (1.31–1.50 m) depth criteria values were greater for all classification groups from the resource selection function compared to the habitat suitability criteria minimum (0.05 m) and maximum values (0.69–1.07 m), except the Broad category which puts no upper limit on depth.

Figure 11. Receiver operating characteristic (ROC) curve (bold solid line) with Narrow (left vertical dashed line), Median (vertical solid line), and Broad (right vertical dashed line) category thresholds for selected models. Area under the curve (AUC) is an indication of model performance. For comparison perfect chance (the diagonal dotted line) representing a random flip of a coin has an AUC = 0.5.

18 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21 Table 6. Comparison of habitat suitability criteria and resource selection function classification categories used to estimate habitat suitability for juvenile Chinook salmon (Oncorhynchus tshawytscha), Willamette River Basin, 2020–21. [Abbreviations: m, meters; m/s, meters per second; HSC, habitat suitability criteria; RSF, resource selection function; ≥, greater than equal to]

Habitat metric

HSC Broad

RSF

Median

Narrow

Broad

Median

Narrow

April

Fry Velocity (m/s)

0–0.46

0–0.38

0–0.15

0–0.57

0–0.45

0–0.27

Depth (m)

0.05–1.52

0.05–1.07

0.05–0.61

0.02–1.18

0.16–1.04

0.37–0.83

Velocity (m/s)

0–0.91

0–0.50

0–0.38

0.08–1.50

0.27–1.50

0.47–1.50

Depth (m)

≥0.05

0.05–1.07

0.05–0.69

0.27–1.50

0.40–1.45

0.54–1.31

Pre-smolt

July

Discussion This study used empirical observations of habitat use by juvenile Chinook salmon in the Willamette River Basin to develop resource selection functions useful for hydraulic habitat modeling efforts in the future. Previous studies provided data on habitat use by juvenile Chinook salmon in the Willamette River Basin (Friesen, 2005; Friesen and others, 2007; Whitman and others, 2017), but these studies had limited usefulness for assessing the current hydraulic habitat model. The Friesen (2005) and Friesen and others (2007) study was a rigorous, multi-year effort that focused on the Lower Willamette River, downstream of Willamette Falls, which is not a reach of primary interest for flow management actions in support of juvenile salmonid habitat in the basin. Whitman and others (2017) collected habitat information primarily at gravel bars where seining crews focused collection efforts to tag juvenile Chinook salmon using passiveintegrated-transponders to study migration timing. Our study expanded on these efforts by focusing on river reaches that are of primary interest for flow management to improve habitat for rearing juvenile salmonids, and included sampling a range of habitats within these reaches to better understand the importance of the various habitat types. There are limitations with the data collection methods. Field staff collected habitat data while wading and made fish observations while snorkeling. As a result, we were limited by depth (depths greater than 1.5 were not assessed), water velocity (data primarily collected in areas where velocities were 1 m/s or slower), and water visibility (2 m or less). The presence of snorkelers may also have affected fish behavior, which is a factor that we were unable to assess. Additionally, all data were collected during daylight hours, so the data do not account for diel differences in juvenile Chinook behavior and habitat use. Finally, our sampling occurred on a portion of the mainstem Willamette River and in lower reaches of two tributaries. Habitat conditions differ in areas located outside of sampling reaches, so results from this study may not apply to those areas. Our results represent an addition to the foundation of knowledge for juvenile Chinook

salmon habitat use, while identifying possibilities for additional refinement of habitat relationships to flow within the Willamette River basin. Our sampling included sites located in the main river channel, side channels, and in alcoves, and we found that juvenile Chinook salmon were routinely present in main channel and side channel habitats but were seldom observed in alcoves. Off-channel habitat has been shown to be important for juvenile Chinook salmon (Limm and Marchetti, 2009; Huntsman and Falke, 2019). During our study, we found that juvenile Chinook salmon were only observed in 7 percent of the alcove habitats that we sampled compared to approximately 40 percent of the main channel and side channel habitats. However, alcove sampling comprised a relatively small proportion of our overall effort, and our sampling was limited to April, June, and July. Friesen and others (2007) used radiotelemetry to monitor habitat use by tagged juvenile Chinook salmon in the Lower Willamette River and reported that most of the fish they relocated were present in mainstem, rather than off-channel habitat. Collectively, these results indicate that off-channel habitat usage may be limited for juvenile Chinook salmon in reaches of Willamette River we studied, but additional research will be needed to fully assess this factor and to understand if the use of off-channel habitat varies throughout the year or as flows change. We found that habitat use by juvenile Chinook salmon underwent a seasonal shift that was likely driven by the increasing size of fish over time. The resource selection functions developed from data collected during our study showed that optimum water velocity for juvenile Chinook salmon in April was near 0.1 m/s and increased to nearly 0.9 m/s in July, while optimum depth increased from approximately 0.6 m to 0.7 m during the same period. The resource selection functions also showed that the probability of juvenile Chinook salmon occupying a given habit decreased substantially as velocity and depth departed from these optimum values. These findings are supported by other studies that have shown that juvenile Chinook salmon move farther offshore and into deeper water as they grow during spring and early summer (Everest and Chapman, 1972; Tabor and others, 2011).

References Cited 19 These resource selection functions can be used to improve hydraulic habitat models, particularly in comparison to coarser approaches such as the SWIFT habitat suitability criteria. For example, the hydraulic habitat model classified habitat as suitable, using the SWIFT criteria, if habitat cells had water depth as shallow as 0.05 m. We found that juvenile Chinook salmon were rarely observed in water depth less than 0.25 m, which means that the SWIFT criteria resulted in an overestimation of habitat availability relative to our observations. Additionally, all habitat cells with water velocity and depth attributes that met the SWIFT criteria were designated as suitable habitat, so this approach did not allow for proportional predictions of habitat use based on various water depth and velocity combinations. These observations illustrate the value of using in-basin data to develop resource selection functions with proportional probabilities to optimize predictive hydraulic habitat models.

References Cited Bond, M., Nodine, T., Sorel, M., Beechie, T., Pess, G., Myers, J., and Zabel, R., 2017, Estimates of UWR Chinook and steelhead spawning and rearing capacity above and below Willamette Project dams: Portland, Oregon, U.S. Army Corps of Engineers, Study Code APH-15-04-DET, 77 p. [Also available at https://www.nwp.usace.army.mil/ library/.] Buccola, N.L., Turner, D.F., and Rounds, S.A., 2016, Water temperature effects from simulated dam operations and structures in the Middle Fork Willamette River, western Oregon: U.S. Geological Survey Open-File Report 2016–1159, 39 p., accessed on February 22, 2022, at https://doi.org/10.3133/ofr20161159. DeWeber, J.T., and Peterson, J.T., 2020, Comparing environmental flow implementation options with structured design making—Case study from the Willamette River, Oregon: Journal of the American Water Resources Association, v. 56, no. 4, p. 599–614, accessed January 11, 2022, at https://onli nelibrary.wiley.com/doi/10.1111/1752-1688.12845. Everest, F.H., and Chapman, D.W., 1972, Habitat selection and spatial interaction by juvenile Chinook salmon and steelhead trout in two Idaho streams: Journal of the Fisheries Research Board of Canada, v. 29, no. 1, p. 91–100, accessed January 7, 2022, at https://doi.org/10.1139/f72-012.

Friendly, M., 2021, vcdExtra: 'vcd' extensions and additions: R package version 0.7-5, accessed February 16, 2022, at https://CRAN.R-project.org/package=vcdExtra. Friesen, T.A., 2005, Biology, behavior, and resources of resident and anadromous fish in the lower Willamette River—Final Report to the City of Portland: Oregon Department of Fish and Wildlife, 246 p., accessed June 3, 2022, at http://osu-wams-blogs-uploads.s3.amazonaws.com/ blogs.dir/2943/files/2019/02/WFS-FINAL-REPORT-5-11- 2005.pdf. Friesen, T.A., Vile, J.S., and Pribyl, A.L., 2007, Outmigration of juvenile Chinook salmon in the lower Willamette River, Oregon: Northwest Science, v. 81, no. 3, p. 173–190, accessed June 3, 2022, at https://doi.org/10.3955/0029- 344X-81.3.173. Huntsman, B.M., and Falke, J.A., 2019, Main stem and off-channel habitat use by juvenile Chinook salmon in a sub-Arctic riverscape: Freshwater Biology, v. 64, no. 3, p. 433–446, accessed January 10, 2022, at https://onlinelibrary. wiley.com/doi/full/10.1111/fwb.13232. Kock, T.J., Perry, R.W., Hansen, G.S., White, J., Stratton Garvin, L., and Wallick, J.R., 2021, Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon: U.S. Geological Survey Open-File Report 2021–1114, 24 p., accessed January 11, 2022, at https://doi.org/10.3133/ofr20211114. Limm, M.P., and Marchetti, M.P., 2009, Juvenile Chinook salmon (Oncorhynchus tshawytscha) growth in off-channel and main-channel habitats on the Sacramento River, CA using otolith increments widths: Environmental Biology of Fishes, v. 85, p. 141–151, accessed on January 10, 2022, at https://link.springer.com/article/10.1007/s10641- 009-9473-8. National Oceanic and Atmospheric Administration, 2021, Endangered Species Act threatened and endangered species directory: National Oceanic and Atmospheric Administration, accessed December 9, 2021, at https://www .fisheries.noaa.gov/species-directory/threatened-endangered. Peterson, J. T., Pease, J. E., Whitman, L., White, J., StrattonGarvin, L., Rounds, S., and Wallick, R., 2021, Integrated tools for identifying optimal flow regimes and evaluating alternative minimum flows for recovering at-risk salmonids in a highly managed system: River Research and Applications, v. 38, no. 2, p. 1–16, accessed January 11, 2022, at https://doi.org/10.1002/rra.3903.

20 Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, 2020–21 Pinnix, W.D., Rupert, D., Som, N.A., Petros, P., and De Juilio, K., 2019, The use of small 2-dimensional habitat zones and dual-snorkeler surveys to model the habitat use of juvenile salmonids in the Trinity River, California: Arcata, California, Arcata Fish and Wildlife Office, U.S. Fish and Wildlife Service, Arcata Fisheries Technical Report Number TR 2019-37, 55 p. [Also available at https://www.fws.gov/ sites/default/files/documents/Juvenile_Density_Report_ Final.pdf.] R Core Team, 2021, R: A language and environment for statistical computing: Vienna, Austria, R Foundation for Statistical Computing, accessed February 16, 2022, at https://www.R-project.org/. R2 Resource Consultants, Inc., 2014, Evaluation of habitatflow relationships for Spring Chinook and winter steelhead in the North and South Santiam Rivers, Oregon: Portland, Oregon, U.S. Army Corps of Engineers, 148 p. [Also available at https://www.nwp.usace.army.mil/library/.] River Design Group, Inc., and HDR, Inc., 2015, Evaluation of the relationship between river flow and fish habitat availability in the Middle Fork of the Willamette and McKenzie Rivers: Portland, Oregon, U.S. Army Corps of Engineers, 218 p. [Also available at https://www.nwp.usace.army.mil/ library/.] Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J., and Müller, M., 2011, pROC—An opensource package for R and S+ to analyze and compare ROC curves: BMC Bioinformatics, v. 12, no. 77, 8 p., accessed February 16, 2022, at https://www.biomedcentral.com/ 1471-2105/12/77/. Rounds, S.A., 2010, Thermal effects of dams in the Willamette River basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2010–5153, 64 p., accessed February 22, 2022, at https://pubs.usgs.gov/sir/2010/5153/. RStudio Team, 2021, RStudio—Integrated development environment for R: Boston, Massachusetts, RStudio, PBC, accessed February 16, 2022, at https://www.rstudio.com/.

Stratton Garvin, L.E., and Rounds, S.A., 2022, The thermal landscape of the Willamette River—Patterns and controls on stream temperature and implications for flow management and cold-water salmonids: U.S. Geological Survey Scientific Investigations Report 2022–5035, 43 p. [Also available at https://doi.org/10.3133/sir20225035.] Tabor, R.A., Fresh, K.L., Piaskowski, R.M., Gearns, H.A., and Hayes, D.B., 2011, Habitat use by juvenile Chinook salmon in the nearshore areas of Lake Washington—Effects of depth, lakeshore development, substrate, and vegetation: North American Journal of Fisheries Management, v. 31, no. 4, p. 700–713, accessed June 7, 2022, at https://doi.org/ 10.1080/02755947.2011.611424. U.S. Geological Survey, 2021, USGS water data for the nation: U.S. Geological Survey National Water Information System database, accessed December 16, 2021, at https://doi.org/10.5066/F7P55KJN. White, J.S., Peterson, J.T., Stratton Garvin, L.E., Kock, T.J., and Wallick, J.R., 2022, Assessment of habitat availability for juvenile Chinook salmon (Onchorhynchus tshwawytscha) and steelhead (O. mykiss) in the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5034, 56 p., accessed June 6, 2022, at https://doi.org/10.3133/sir20225034. White, J.S., and Wallick, J.R., 2022, Development of continuous bathymetry and two-dimensional hydraulic models for the Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2022–5025, 67 p., accessed April 18, 2022, at https://doi.org/10.3133/sir20225025. Whitman, L.D., Schroeder, R.K., and Friesen, T.A., 2017, Evaluating migration timing and habitat for juvenile Chinook salmon and winter steelhead in the mainstem Willamette River and major spawning tributaries: Portland, Oregon, U.S. Army Corps of Engineers, 32 p., accessed December 11, 2022, at https://odfw.forestry.oregonstate.edu/ willamettesalmonidrme/sites/default/files/evaluating_ habitat_for_chs_and_sts_final.pdf. Wickham, H., 2016, ggplot2: Elegant graphics for data analysis. Springer-Verlag New York, New York, accessed February 16, 2022, at https://ggplot2.tidyverse.org.

For information about the research in this report, contact Director, Western Fisheries Research Center U.S. Geological Survey 6505 NE 65th Street Seattle, Washington 98115-5016 https://www.usgs.gov/centers/western-fisheries-research-center Manuscript approved on January 9, 2023 Publishing support provided by the U.S. Geological Survey Science Publishing Network, Tacoma Publishing Service Center

Hansen and others—Assessment of Habitat Use by Juvenile Chinook Salmon in the Willamette River Basin, Oregon, 2020–21—OFR 2023–1001

ISSN 2331-1258 (online) https://doi.org/10.3133/ofr20231001

Assessment of Habitat Use by Juvenile Chinook Salmon ( Oncorhynchus tshawytscha ) in the Willamette River Basin, 2020–21

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