Science, Faculty of
Oceans and Fisheries, Institute for the
DSpace
UBCV
Hicks, Delaney
Master of Science - MSc
University of British Columbia
This thesis investigated juvenile freshwater and smolt-to-adult survival (ÏSAS) rates of threatened Upper Willamette River spring-run Chinook salmon (Oncorhynchus tshawytscha) and other spring- and summer-run Chinook salmon stocks across the Columbia River Basin. In Chapter Two, I analyzed Passive Integrated Transponder (PIT) tag data from 143 releases between 2002 and 2016 to estimate ÏSAS and release-smolt survival (ÏRSS) rates for Upper Willamette River spring-run Chinook salmon. I used a Bayesian Cormack-Jolly-Seber model with a minimum design configuration that included two detection locations: one for juvenile smolts before entry to the Columbia River estuary and one for adults on their return to the Willamette River. Sensitivity analysis results found a minimal effect of prior choice on model output results. Estimates of ÏSAS were consistently below the 2% recovery benchmark for the Columbia River Basin. Additionally, ÏRSS through river segments varied across Willamette River sub-basins, with the lowest estimates observed from release locations requiring longer migrations through multiple dams. In Chapter Three, I used published estimates of ÏSAS from the Snake, Middle Columbia, and Upper Columbia River and evaluated survival trends across these and the Willamette River. Common shared year effects revealed interannual variation; however, when separated, trends were not uniform across all regions, albeit with higher uncertainty. Univariate covariate analyses revealed negative associations that did not overlap with zero between ÏSAS estimates and the abundance of pink salmon in the Northeast Pacific Ocean, with adjusted R² values ranging from 0.02 to 0.11 across regions. Additionally, the Pacific Decadal Oscillation and El Niño-Southern Oscillation were linked to reduced survival, while the North Pacific Gyre Oscillation showed positive associations. Although these drivers showed the same associations with survival across all regions, their relative importance differed. Multivariate model covariate analyses explained up to 36% of the observed variation in survival, but found that no singular covariate appeared as a top driver across all regions. These results suggest that accounting for regional differences in response to environmental and ecological stressors may be beneficial for conservation and recovery strategies for spring and summer Chinook salmon populations in the Columbia River system.
Examining release-smolt and smolt-to-adult survival rates of spring Chinook salmon (Oncorhynchus tshawytscha) from the Willamette River by Delaney Hicks B.Sc., Dalhousie University, 2023 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Oceans and Fisheries) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2025 © Delaney Hicks, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Examining release-smolt and smolt-to-adult survival rates of spring Chinook salmon (Oncorhynchus tshawytscha) from the Willamette River submitted by Delaney Hicks in partial fulfillment of the requirements for the degree of Master of Science in Oceans and Fisheries Examining Committee: Dr. Murdoch McAllister, Associate Professor, Institute for the Oceans and Fisheries, UBC Supervisor Dr. Tom Porteus, Independent Contractor, UBC Supervisory Committee Member Dr. Brian Hunt, Associate Professor, Institute for the Oceans and Fisheries, UBC Supervisory Committee Member Dr. Andrew Trites, Professor, Institute for the Oceans and Fisheries, UBC Additional Examiner iii Abstract This thesis investigated juvenile freshwater and smolt-to-adult survival (ÏSAS) rates of threatened Upper Willamette River spring-run Chinook salmon (Oncorhynchus tshawytscha) and other spring- and summer-run Chinook salmon stocks across the Columbia River Basin. In Chapter Two, I analyzed Passive Integrated Transponder (PIT) tag data from 143 releases between 2002 and 2016 to estimate ÏSAS and release-smolt survival (ÏRSS) rates for Upper Willamette River spring-run Chinook salmon. I used a Bayesian Cormack-Jolly-Seber model with a minimum design configuration that included two detection locations: one for juvenile smolts before entry to the Columbia River estuary and one for adults on their return to the Willamette River. Sensitivity analysis results found a minimal effect of prior choice on model output results. Estimates of ÏSAS were consistently below the 2% recovery benchmark for the Columbia River Basin. Additionally, ÏRSS through river segments varied across Willamette River sub-basins, with the lowest estimates observed from release locations requiring longer migrations through multiple dams. In Chapter Three, I used published estimates of ÏSAS from the Snake, Middle Columbia, and Upper Columbia River and evaluated survival trends across these and the Willamette River. Common shared year effects revealed interannual variation; however, when separated, trends were not uniform across all regions, albeit with higher uncertainty. Univariate covariate analyses revealed negative associations that did not overlap with zero between ÏSAS estimates and the abundance of pink salmon in the Northeast Pacific Ocean, with adjusted R2 values ranging from 0.02 to 0.11 across regions. Additionally, the Pacific Decadal Oscillation and El Niño-Southern Oscillation were linked to reduced survival, while the North Pacific Gyre Oscillation showed positive associations. Although these drivers showed the same associations iv with survival across all regions, their relative importance differed. Multivariate model covariate analyses explained up to 36% of the observed variation in survival, but found that no singular covariate appeared as a top driver across all regions. These results suggest that accounting for regional differences in response to environmental and ecological stressors may be beneficial for conservation and recovery strategies for spring and summer Chinook salmon populations in the Columbia River system. v Lay Summary Chinook salmon (Oncorhynchus tshawytscha) are an important species, but many of their populations are struggling to survive. Using tagging data, I estimated survival rates for populations of threatened Upper Willamette River spring-run Chinook salmon and compared their time trends with those for spring and summer run Chinook salmon from other regions of the Columbia River Basin. Results showed that marine survival rates for Upper Willamette River Chinook salmon remain below recovery goals, and freshwater survival rates are lower for release groups that migrate longer distances through multiple dams. I also examined how changing predator abundance and ocean conditions affect marine survival across regions within the Columbia River Basin. While the direction of impact of each factor on marine survival rates was consistent across regions, the extent to which each one affected survival varied, indicating that restoring Chinook salmon abundance may benefit from region-specific strategies. vi Preface This thesis is original, unpublished work conducted by me. I am the sole author and performed the data analysis and interpretation for all chapters. I was not involved in the design of the research program or the collection of the data. All data were obtained from various studies submitted to PTAGIS and the published report by McCann et al. (2024). Generative artificial intelligence (ChatGPT) was used during this thesis to assist with debugging R code. All analyses and data interpretation were developed without the use of generative artificial intelligence. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ................................................................................................................................ xi List of Figures ............................................................................................................................. xiii List of Abbreviations ............................................................................................................... xxiv Acknowledgements .................................................................................................................. xxvi Chapter 1: Introduction ................................................................................................................1 1.1 Life cycle and conservation status of Chinook salmon populations ............................... 1 1.2 The Upper Willamette River ........................................................................................... 3 1.3 Potential causes of declines ............................................................................................ 4 1.4 Thesis overview and objectives ...................................................................................... 7 Chapter 2: Marine and Freshwater Survival Rate Estimates for Upper Willamette River Spring Chinook Salmon ................................................................................................................9 2.1 Introduction ..................................................................................................................... 9 2.2 Methods......................................................................................................................... 12 2.2.1 Study sites ................................................................................................................. 12 2.2.2 PIT-tagged fish.......................................................................................................... 15 2.2.3 CJS model ................................................................................................................. 15 2.2.4 Convergence diagnostics .......................................................................................... 18 viii 2.2.5 Posterior to prior precision ratio cut-off ................................................................... 19 2.2.6 Sensitivity analysis.................................................................................................... 20 2.2.7 Seasonal effect .......................................................................................................... 22 2.2.8 Estuary detections ..................................................................................................... 23 2.2.9 Imputation of missing adult detections ..................................................................... 23 2.3 Results ........................................................................................................................... 25 2.3.1 Assessing prior updates and informative data values for estimated parameters ....... 25 2.3.1.1Examining ratios of posterior to prior precision and IQR values .......................... 25 2.3.1.2Relationship between the posterior correlation coefficient and release group size 28 2.3.2 Base case time series of parameter estimates ........................................................... 32 2.3.3 Sensitivity analysis of the results under different assumptions and input settings ... 45 2.3.3.1Changes to prior mean and precision ..................................................................... 45 2.3.3.2Percent change in posterior means ......................................................................... 53 2.3.3.3Seasonal effect ....................................................................................................... 53 2.3.3.4Estuary detections .................................................................................................. 56 2.3.3.5Imputation of adult detections ............................................................................... 58 2.4 Discussion ..................................................................................................................... 60 2.4.1 Empirically driven posterior estimates ..................................................................... 60 2.4.2 Survival estimate comparisons ................................................................................. 62 2.4.3 Assessing model sensitivity ...................................................................................... 65 2.4.3.1Informative prior changes ...................................................................................... 65 2.4.3.2Seasonal effect on survival .................................................................................... 66 2.4.3.3Inclusion of estuary survival in the model ............................................................. 67 ix 2.4.3.4Effect of closure of Willamette Falls detection site ............................................... 68 2.5 Limitations .................................................................................................................... 69 2.6 Conclusion .................................................................................................................... 70 Chapter 3: Examining Drivers of Chinook Salmon Smolt-to-Adult Survival Rates in the Columbia River Basin..................................................................................................................71 3.1 Introduction ................................................................................................................... 71 3.2 Methods......................................................................................................................... 76 3.2.1 Study Sites ................................................................................................................ 76 3.2.2 Criteria for inclusion of smolt-to-adult survival rate estimates from the Willamette River Basin ........................................................................................................................... 77 3.2.3 Selection of ÏSAS estimates from the Columbia River Basin .................................... 80 3.2.4 Global effects models ............................................................................................... 82 3.2.4.1Shared year effect .................................................................................................. 82 3.2.4.2Hatchery effect ....................................................................................................... 84 3.2.4.3Group and year effect............................................................................................. 85 3.2.5 Covariate compilation ............................................................................................... 85 3.2.6 Covariate lagging ...................................................................................................... 87 3.2.7 Determining top models ............................................................................................ 89 3.3 Results ........................................................................................................................... 92 3.3.1 Effects models ........................................................................................................... 92 3.3.2 Covariate effects in the top models ........................................................................... 97 3.4 Discussion ................................................................................................................... 110 3.4.1 Effects models ......................................................................................................... 110 x 3.4.2 Individual linear models ......................................................................................... 112 3.4.3 Multivariate models ................................................................................................ 116 3.4.4 Evaluating Drivers of Smolt-to-Adult Survival in a Multi-Stock System .............. 117 3.4.5 Limitations .............................................................................................................. 118 3.5 Conclusion .................................................................................................................. 119 Chapter 4: Conclusion ...............................................................................................................121 4.1 Summary of Key Findings .......................................................................................... 121 4.2 Limitations and Future Directions .............................................................................. 123 Bibliography ...............................................................................................................................125 Appendices ..................................................................................................................................139 Appendix A ............................................................................................................................. 139 Appendix B ............................................................................................................................. 140 Appendix C ............................................................................................................................. 170 Appendix D ............................................................................................................................. 201 Appendix E ............................................................................................................................. 226 Appendix F.............................................................................................................................. 228 Appendix G ............................................................................................................................. 232 Appendix H ............................................................................................................................. 257 Appendix I .............................................................................................................................. 258 xi List of Tables Table 2.1 Location of each area marked by river kilometers (RKM) from the Pacific Ocean. .... 13 Table 2.2 The time series and number of release groups within each area (e.g., sub-basin or mainstem reach) examined in this study. ...................................................................................... 17 Table 2.3. Breakdown of the sensitivity analysis scenarios performed for ÏRSS, ÏSAS, and PWFF, showing what was changed for each parameter to determine the mean(CV) and the beta distribution. ................................................................................................................................... 22 Table 2.4. DIC outputs from four release groups with a clear seasonal split in release timing. Model outputs from combined (e.g., no seasonal split accounted for) or spring and winter (e.g., filtered for spring, then for winter, and then added the DIC outputs). ......................................... 55 Table 3.1 Release groups of PIT-tagged juvenile spring Chinook salmon from the Willamette River Basin that are empirically updated and have three or more years of consecutive hatchery or wild release data. Releases entering the ocean as subyearlings are bolded. ................................. 79 Table 3.2. Description of covariates used for analysis. Stage describes what phase of life the covariate is affecting. Covariates were standardized based on the mean and standard deviation (SD) calculated for each covariate's time series. .......................................................................... 86 Table 3.3. List of covariates and life history type they are assigned to, along with the associated lag applied for the covariate analysis. ........................................................................................... 89 Table 3.4. Pairwise R² values for covariates with high correlations. Values represent the strength of linear relationships between selected covariates within each region. ...................................... 91 xii Table 3.5. Top models from the Snake River. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). ........................... 103 Table 3.6. Top models from the Middle Columbia. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). .............. 105 Table 3.7. Top models from the Upper Columbia. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). .............. 107 Table 3.8. Top models from the Willamette River. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). .............. 109 Table 3.9. Direction and frequency of covariate effects from top multivariate model outputs across regions (Snake River, Middle Columbia, Upper Columbia, Willamette). The year range of each region's ÏSAS estimates are shown in the top rows. Values indicate the number of times a covariate appeared, with the sign of the effect shown in parentheses (positive [+], negative [â], or both directions [both])................................................................................................................. 110 xiii List of Figures Figure 2.1 Map of the Willamette River (Oregon, USA) and a portion of the Columbia. Points show where the Willamette connects to the Columbia (red point) and dam locations (orange points) along the river. Downstream is Willamette Falls (purple point), which houses Sullivan Dam Juvenile Bypass Facility (SUJ) and Willamette Falls Adult Fishway (WFF). Highlighted in bold are the four sub-basins, ordered from top to bottom: North Santiam, South Santiam, McKenzie, and Middle Fork, and two reaches of the mainstem river: Middle Willamette and Upper Willamette. ......................................................................................................................... 14 Figure 2.2. Schematic diagram of the Cormack-Jolly-Seber (CJS) model. The model follows a minimum design configuration, with one release site and two detection sites: one for juveniles (PSUJ) and one for adults (PWFF). The model parameters are release-smolt-survival (ÏRSS), smolt-adult-survival (ÏSAS), and probability of detection at the Sullivan Dam bypass facility (PSUJ) and at Willamette Falls (PWFF). Reprinted from Porteus et al., in review. ........................................... 18 Figure 2.3. Posterior density plots of smolt-adult-survival (ÏSAS) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The solid black lines are the prior distributions, and the dashed lines are the ÏSAS distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. .............................................................................................. 29 Figure 2.4. Posterior density plots of release-smolt-survival (ÏRSS) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem xiv river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The solid black lines are the prior distributions, and the dashed lines are the ÏRSS distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. .............................................................................................. 30 Figure 2.5. Posterior density plots of detection probability at SUJ (PSUJ) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The areas are further subdivided by flow level into low, mid, or high, depending on the flow at detection time. The solid black lines are the prior distributions, and the dashed lines are the PSUJ posterior distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. ...................................... 31 Figure 2.6. Posterior density plots of detection probability at WFF (PWFF) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The solid black lines are the prior distributions, and the dashed lines are the PWFF distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. ............................................................. 32 Figure 2.7. ÏSAS for each release group within the McKenzie sub-basin from 2002 to 2015 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The xv dashed line represents the prior mean value (mean = 0.011), while the grey shading indicates the 95% prior credible interval. The pink data points represent the posterior mean estimates with their corresponding 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ............................................................................................................................................. 36 Figure 2.8. ÏRSS for each release group within the McKenzie sub-basin from 2002 to 2015 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. .............................. 37 Figure 2.9. ÏSAS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.011), while the grey shading indicates the 95% prior credible interval. The pink data points represent the posterior mean estimates with their corresponding 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ............................................................................................................................................. 38 xvi Figure 2.10. ÏRSS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. .............................. 39 Figure 2.11. ÏSAS (top panel) and ÏRSS (bottom panel) for the Middle Willamette reach of the mainstem river from 2007 to 2016 under the base case with informative priors. The dashed line represents the prior mean values (mean = 0.399 & mean = 0.011), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ............. 40 Figure 2.12. ÏSAS for each release group within the North Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.011), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ........................................................................................................ 41 Figure 2.13. ÏRSS for each release group within the North Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value xvii (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2 and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ............. 42 Figure 2.14. ÏSAS for each release group within the South Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.011), while the grey shading indicates the 95% prior credible interval. The pink data points represent the posterior mean estimates with their corresponding 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ................................................................... 43 Figure 2.15. ÏRSS for each release group within the South Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ........................................................................................................ 44 Figure 2.16. ÏSAS (top panel) and ÏRSS (bottom panel) for the Upper Willamette reach of the mainstem river from 2004 to 2016 under the base case with informative priors. The dashed line represents the prior mean values (mean = 0.399 & mean = 0.011), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2 and triangles xviii represent ratios between 1.5-2. The minimum and maximum values for each release group are displayed at the bottom left of each panel. ................................................................................... 45 Figure 2.17. Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork sub-basin from 2011 to 2014. ............................................................................................... 48 Figure 2.18. Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and a combination of half-precision and mean. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. ...................................................................................................... 49 Figure 2.19. Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. ................................................................................................................................ 50 xix Figure 2.20. Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. ...................................................................................................... 51 Figure 2.21. Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from the base (0.98) to 0.9, 0.49, and a combined mean and precision of half. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. ........................................................................................................................ 52 Figure 2.22 ÏSAS for each release group with a seasonal split in release timing. Columns are divided by model type from left to right: combined (no seasonal effect), spring (filtering for only spring releases), and winter (filtering for only winter releases). The dashed line represents the prior mean value, with a mean of 0.011. The data points represent the mean estimates with 95% credible intervals (black = posterior estimates, pink = prior values). The point values for each release group's posterior estimates are listed at the bottom left of each panel. ............................ 54 Figure 2.23. ÏRSS for each release group with a seasonal split in release timing. Columns are divided by model type from left to right: combined (no seasonal effect), spring (filtering for only spring releases), and winter (filtering for only winter releases). The dashed line represents the xx prior mean value, with a mean of 0.399. The data points represent the mean estimates with 95% credible intervals (black = posterior estimates, pink = prior values). The point values for each release group's posterior estimates are listed at the bottom left of each panel. ............................ 55 Figure 2.24. ÏSAS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors (pink) and the base case with estuary detections (blue). When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.011), and the data points represent the posterior mean estimates with 95% credible intervals. The minimum and maximum values for each release group are displayed on the left side of each panel, with the top panel representing the estuary and the bottom panel representing the base. .................................................................................................................... 57 Figure 2.25. ÏRSS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors (pink) and the base case with estuary detections (blue). When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.399), and the data points represent the posterior mean estimates with 95% credible intervals. The minimum and maximum values for each release group are displayed on the left side of each panel, with the top panel representing the estuary and the bottom panel representing the base. .................................................................................................................... 58 Figure 2.26. Comparison of ÏSAS estimates from non-imputed (pink) and imputed (green) data sets. Big Cliff Dam Tailrace, Detroit Dam Head of Reservoir, Horse Creek, McKenzie River (RKM 0-56), and McKenzie River (RKM 57-90) release groups are from 2015, and Middle xxi Willamette and Upper Willamette release groups are from 2016. The dashed line represents the prior mean of 0.011. ...................................................................................................................... 59 Figure 2.27. Comparison of ÏRSS estimates from non-imputed (pink) and imputed (blue) data sets. Big Cliff Dam Tailrace, Detroit Dam Head of Reservoir, Horse Creek, McKenzie River (RKM 0-56), and McKenzie River (RKM 57-90) release groups are from 2015, and Middle Willamette and Upper Willamette release groups are from 2016. The dashed line represents the prior mean of 0.399. ...................................................................................................................... 60 Figure 3.1. Map of the Columbia River. Points show dam locations (orange points) along the river. Furthest downstream is Bonneville Dam, which houses the Bonneville Dam Juvenile Bypass Facility (BVJ) and the Bonneville Adult Fishway (BWL). Highlighted in bold are the three sub-basins, ordered from right to left: Snake River, Upper Columbia, and Middle Columbia. Note: Figure 2.1 shows the location of the Willamette River sub-basins and where it joins the Columbia River. ............................................................................................................. 77 Figure 3.2. Combined estimated year effect on log-transformed smolt-to-adult return rates from 2000 to 2022 from the Snake River, Middle Columbia, Upper Columbia, and Willamette. Points represent posterior means of year-specific deviations, and vertical lines indicate 90% credible intervals. The dashed line at zero indicates where there is no year effect. ................................... 92 Figure 3.3. Sensitivity analysis on the combined estimated year effect of log-transformed smolt-to-adult return rates from 2000 to 2022 from the Snake River, Middle Columbia, Upper Columbia, and Willamette. Points represent posterior means of year-specific deviations from the overall mean, and vertical lines indicate 90% credible intervals. Pink indicates estimates from the base prior on the precision, blue represents a lower precision, and green reflects a higher precision. The dashed horizontal line at zero denotes no year effect. .......................................... 93 xxii Figure 3.4. Estimated group-level effects on log-transformed smolt-to-adult return rates for four regions: Middle Columbia, Snake River, Upper Columbia, and Willamette. Points represent posterior means of group-specific deviations from the overall mean, and vertical lines indicate 90% credible intervals. The dashed line at zero represents no group-level deviation. ................. 94 Figure 3.5. Estimated hatchery effect on log-transformed smolt-to-adult return rates. The points represent the posterior means of the hatchery-origin and wild-origin fish, and the vertical lines show the 90% credible intervals. The dashed line at zero represents no difference between hatchery and wild fish. .................................................................................................................. 95 Figure 3.6. Estimated year-specific effects on Chinook salmon's log-transformed smolt-to-adult survival (ÏSAS) for four regions: Middle Columbia River Basin, Snake River, Upper Columbia River Basin, and Willamette River Basin. Points represent the posterior means of the group-by-year interaction terms, and vertical lines denote 90% credible intervals. A dashed horizontal line at zero indicates no year effect. Values above or below zero reflect years when survival was higher or lower than expected after accounting for other covariates in the model. ...................... 96 Figure 3.7. Relationships between smolt-to-adult survival (ÏSAS) of Chinook salmon and 15 standardized covariates across four regions: Middle Columbia, Snake River, Upper Columbia, and Willamette. Each panel displays a scatterplot of ÏSAS estimates versus a single covariate, with fitted linear trend lines colored by region. ............................................................................ 98 Figure 3.8. Estimated effects of environmental and anthropogenic covariates on smolt-to-adult survival (ÏSAS) of Chinook salmon across four regions: Middle Columbia, Snake River, Upper Columbia, and Willamette. Points represent the estimated effect sizes from standardized linear models for each covariate, and horizontal lines show associated 90% credible intervals. xxiii Covariates were standardized prior to modeling to allow direct comparison of effect magnitude. Dashed vertical lines at zero denote no effect. ........................................................................... 100 Figure 3.9. Distribution of coefficient estimates from Snake River top models. Each panel is grouped by covariate, with jittered points on the y-axis representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. ................................................................... 102 Figure 3.10. Distribution of coefficient estimates from Middle Columbia top models. Each panel is grouped by covariate, with jittered points representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. .......................................................................... 104 Figure 3.11. Distribution of coefficient estimates from Upper Columbia top models. Each panel is grouped by covariate, with jittered points representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. .......................................................................... 106 Figure 3.12. Distribution of coefficient estimates from Willamette top models. Each panel is grouped by covariate, with jittered points representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. .......................................................................... 108 xxiv List of Abbreviations BCJS â Bayesian Cormack-Jolly-Seber CSS â Comparative Survival Study CV â Coefficient of Variation DIC â Deviation Information Criteria ENSO â El Nino Southern Oscillation ESU â Evolutionary Significant Unit IQR â Interquartile Range MCMC â Markov Chain Monte Carlo NPGO â North Pacific Gyre Oscillation PDO â Pacific Decadal Oscillation PIT â Passive Integrated Transponder PITAGIS â Pit Tag Information System RKM â River Kilometer RSS â Release-smolt-survival rate SAR â Smolt-adult return SAS â Smolt-adult-survival rate SST â Sea Surface Temperature SUJ - Sullivan Dam Juvenile Bypass facility SAR â Smolt Adult Return rate TWX â Towed Array US â United States UWR â Upper Willamette River xxv WFF â Willamette Falls Adult Fishway WVP â Willamette Valley Project xxvi Acknowledgements I want to thank my supervisors, Murdoch McAllister and Tom Porteus, for their ongoing support and guidance throughout this project. I would also like to thank Brian Hunt for his helpful insights. I want to thank the other members of the SEARUN lab for their ongoing support. I am grateful for the support I received through the Brian Jessop Graduate Award in Freshwater and Diadromous Fisheries and the funding I received from NSERC. Chapter 1: Introduction 1.1 Life cycle and conservation status of Chinook salmon populations Chinook salmon (Oncorhynchus tshawytscha) are one of five species of Pacific salmon found in North America. Chinook salmon are anadromous, meaning they spawn and lay their eggs in freshwater but spend a portion of their lives at sea (Quinn, 2018). The exact timing of this process can vary, but once hatched, salmon fry spend some time in freshwater before migrating to the ocean as sub-yearling smolts (i.e., during their first year of life) or as yearling smolts (i.e., during their second year of life) (Riddell et al., 2018; Schroeder et al., 2016). Before migrating downstream, juveniles undergo a process known as smoltification, which prepares them to transition from freshwater to saltwater (Quinn, 2018). Their bodies become streamlined throughout this process, and their parr marks fade (Quinn, 2018). Internally, their gills develop specialized cells to regulate salt balance, and their kidneys adjust from retaining salt to excreting it (Quinn, 2018). Once smoltification is underway, the juveniles can begin migrating downstream. During this phase, they are exposed to constant risks, and longer migrations are typically associated with increased mortality (Skalski et al., 1998). Downstream survival is estimated as high as 99.8% per kilometer; however, some populations must migrate 700-800 kilometers before reaching the ocean (Bickford & Skalski, 2000; Quinn, 2018). Therefore, the longer a juvenile's travel distance, the less likely they are to survive the entire migration (Bickford & Skalski, 2000). Despite the challenges associated with downstream migration, successfully reaching the ocean is only the beginning of a new suite of challenges. Juveniles that reach the ocean can spend one to five (typically two to four) years growing and feeding in epipelagic, coastal, and offshore areas (Quinn, 2018). The salmon are exposed to 2 slow gyral currents and cold water in open ocean areas; however, within coastal areas, they must navigate the varying effects of geography (e.g., islands, bays, reefs, and points of land) and physiological effects from the water (e.g., warmer water temperature, lower salinity, lower dissolved oxygen, and faster tides; Quinn, 2018). Although many uncertainties exist regarding survival during the marine phase, studies suggest that most mortality occurs in two stages within the first few months after ocean entry (Duffy & Beauchamp, 2011). Mortality during the first 40 days is considered the first stage and is assumed to be mainly predation-based (Duffy & Beauchamp, 2011). Second-stage mortality occurs during the first winter, where growth during the summer determines the chances of survival; a larger size leads to higher survival rates (Duffy & Beauchamp, 2011). Despite most risks occurring during the first few months in the ocean, salmon are also susceptible to other sources of mortality during the rest of their time at sea. In the summer of 1983, El Niño conditions led to warm temperatures and weak upwelling along the coast, resulting in poor growth, delayed mortality, and consequently low adult returns (Quinn, 2018). Another source of mortality, even for adult salmon, is predation risk. A study by Chasco et al. (2017) found that in 2015, pinnipeds and killer whales consumed 31.5 million individual Chinook salmon. Because many salmon populations are reproductively isolated from one another, this predation could comprise a substantial proportion of individual populations, leading to local depletions. Salmon are exposed to numerous risks throughout their marine phase of life, but the risks do not end there, as they encounter additional challenges once they migrate back to freshwater. As salmon return to freshwater, they undergo a series of physiological and biological changes, including reduced feeding, activation of hormones involved in gonadal development, and alterations to their osmoregulatory systems, to prepare for the transition to freshwater and 3 the demands of spawning (Quinn, 2018). These changes are important, as the upstream migration is physically demanding, with many salmon traveling long distances to return to their natal streams. Once they successfully arrive, Chinook salmon reproduce; however, as semelparous fish, males and females expend most of their energy during spawning and eventually die (Quinn, 2018). This life cycle completes their reproductive journey and plays an important ecological role. The salmon carcasses provide essential nutrients, such as phosphorus and nitrogen, to nutrient-poor freshwater ecosystems and surrounding terrestrial areas, making salmon a keystone species (Quinn, 2018). Despite being a keystone species, the number of salmon returning to rivers and streams has declined from historical levels (Beamish, 2022; Brandt et al., 2016; Connors et al., 2020; Schroeder et al., 2016; Welch et al., 2020). Salmon populations are reproductively isolated from one another (Quinn, 2018). Therefore, while certain species may appear to be doing well, this can mask individual populations that have experienced large declines (Quinn, 2018). Although the rate of decline has slowed in recent years, many populations remain at a fraction of their historical levels and show no signs of recovery (Nehlson et al., 1991; Riddell et al., 2018; Quinn, 2018). 1.2 The Upper Willamette River The Upper Willamette River (UWR) is located in Oregon, USA, with its 301 km mainstem lying entirely in northwestern Oregon and joining the Columbia River at river kilometer (RKM) 163 (Schroder et al., 2016; Table 2.1). Historically, passage to the UWR has been challenging due to Willamette Falls, a 15-meter-high basalt ledge located 43 km upstream from where the Willamette joins the Columbia (Schroder et al., 2016; Table 2.1). The Falls were a barrier to most anadromous fish, except spring-run Chinook salmon, winter-run steelhead, and 4 Pacific Lamprey (Schroder et al., 2016). However, in 1968, the construction of fishways alongside the falls improved passage (Gleeson, 1972; Schroder et al., 2016). Despite improved passage at the falls, around the same time (1950s - 1960s), dams were being constructed throughout the UWR for water storage, diversion, and hydropower generation (Brandt et al., 2016; Gleeson, 1972; Keefer et al., 2013; Schroeder et al., 2016). With the construction of the dams, what once was a free-flowing river now contains a series of reservoirs within each sub-basin: McKenzie, Middle Fork, North Santiam, and South Santiam (Gleeson, 1972). The dams have caused alterations in habitat, flow regimes, and water temperature and have inhibited access to 70%-95% of historical spawning grounds (Brandt et al., 2016; Gleeson, 1972; Keefer et al., 2013; Schroeder et al., 2016). Nine out of 13 dams currently in operation throughout the Willamette River are located in areas that hinder the migration of UWR spring Chinook salmon (Nagel, 2017; Peterson et al., 2022; Wallick et al., 2007). Not only do the dams hinder migration, but also, because they are primarily used for flood control, the flow levels in the sub-basins can vary between seasons (Olmsted et al., 2018; Schroeder et al., 2016). This difference in flow may not align with historical levels and, consequently, the natural timing of downstream migrating smolts, which can negatively impact their survival (Beeman et al., 2015). Therefore, the decline in spring Chinook salmon returns and the listing of the UWR population as threatened under the United States Endangered Species Act in 1999 has been partly attributed to the Willamette Valley Project (WVP) dams (Brandt et al., 2016; Keefer et al., 2013; Schroeder et al., 2016). 1.3 Potential causes of declines Beyond the effects of dams, other factors may also have contributed to the decline in UWR spring Chinook salmon returns. Several factors have been hypothesized, including 5 freshwater habitat loss, marine conditions, bycatch in fisheries, predation, hatchery practices, and competition (Duffy & Beauchamp, 2011; Chamberlain et al., 2011; Cunningham et al., 2018; Sobocinski et al., 2021; Wilson et al., 2022). However, due to the complex life histories and long migrations, a combination of factors from freshwater and marine environments are likely constraining population recovery (Sobocinski et al., 2021; Wilson et al., 2022). One factor thought to have a considerable contribution to declining returns is habitat loss and degradation. Nehlson et al. (1991) found that habitat loss and degradation contributed to 91% of the risk of extinction. In the freshwater environment, drastic changes have been made to habitats resulting from mining, logging, agricultural development, and urban development (Schroder et al., 2016; Sobocinski et al., 2021; Quinn, 2018). Sediment and gravel mining alter channel formation, migration, and sediment transport, while logging near riverbanks leads to erosion and changes in flow, reducing habitat suitability (Gregory et al., 2008; Gronsdahl et al., 2019; Guthrie, 2002; Tschaplinski & Pike, 2017; Wilson et al., 2022). Agriculture increases turbidity and alters water properties, whereas urban development raises water temperatures by reducing canopy cover and increasing surface runoff, degrading river hydrology and morphology (Gleeson, 1972; Waite et al., 2008). Although direct habitat alteration is less pronounced in the marine environment, changes in oceanic conditions are thought to contribute to population declines. Naturally occurring marine conditions, such as the Pacific Decadal Oscillation, El Niño/La Niña years, and the North Pacific Ocean Gyre, alter ecosystems and are linked to changes in recruitment productivity and production (Chamberlin et al., 2011; Wilson et al., 2022). Additionally, ocean temperatures affect survival. Warming ocean temperatures are predicted to negatively impact West Coast salmon populations by reducing primary and secondary production, decreasing prey availability 6 and nutritional content, and increasing metabolic requirements (Connors et al., 2022; Cunningham et al., 2018). Fishing also poses threats to survival. Nehlson et al. (1991) found that overfishing contributed to 50% of the risk of extinction in salmon populations. While overfishing of Pacific salmon was a large problem, ESA listings have reduced fishing pressures. However, bycatch and harvest mortality from other targeted fisheries remain a concern. Data from the Bering Sea groundfish fishery revealed that in two seasons from 2010, the British Columbia and West Coast US stocks comprised 3.4% and 40.2% of the bycatch stock composition estimates, respectively (Guthrie et al., 2012). Despite efforts to reduce bycatch, it remains a problem that hinders recovery efforts and continues to threaten vulnerable salmon populations. Biotic interactions, including predation, competition, and hatchery practices, are also thought to play a role in the observed declines. Nehlson et al. (1991) found that biotic factors contributed to 53% of the risk of extinction in salmon populations. Recent attention has focused on increased predation from harbour seals (Phoca vitulina) and Steller sea lions (Eumetopias jubatus) as a driver of the low salmon returns, as it is thought that since they were listed under federal protection in 1970, their populations have recovered to and exceeded pre-harvest levels (Nelson et al., 2019; Wilson et al., 2022). Another potential explanation for the low returns is competition effects between species. Cunningham et al. (2018) found that increased pink salmon (Oncorhynchus gorbuscha) abundance was correlated with the reduced survival of Chinook and sockeye salmon. Recently, there have been high numbers of pink salmon returns. Additionally, although hatcheries have been implemented to enhance salmon survival, there is evidence for density-dependent effects on survival, where the survival of wild salmon is impacted by increased hatchery releases (Cunningham et al., 2018; Courter et al., 2022). 7 1.4 Thesis overview and objectives A combination of freshwater and marine environmental factors likely drives the ongoing low returns of UWR spring Chinook salmon. Addressing this issue is important for managing and conserving this species, but it will require coordinated efforts that consider the interactions among various factors. Numerous efforts have been made to estimate Pacific salmon survival rates; however, insights gained from one area may not apply to another population (Riddell et al., 2018; Quinn, 2018). While relatively little work has been conducted within the UWR compared to other areas of the Columbia River system, Passive Integrated Transponder (PIT) tag studies have been conducted since the early 2000s, providing detailed records of releases and detections. Using data from PIT tag studies, I used a Bayesian Cormack-Jolly-Seber (BCJS) model to obtain estimates of survival rates from release to the Sullivan Dam Juvenile Bypass Facility (SUJ), i.e., release-smolt survival rate (ÏRSS) and of survival rates from SUJ until return at Willamette Falls Adult Fishway (WFF), i.e., smolt-to-adult survival rate (ÏSAS) for different groups of UWR spring Chinook salmon released within each of the tributaries (Middle Fork Willamette, McKenzie, South Santiam, and North Santiam) and mainstem reaches of the Willamette (Upper Willamette, Middle Willamette). ÏRSS represents early-stage survival, while ÏSAS reflects survival through ocean migration and back to adulthood. Along with the Willamette River Basin survival estimates from Chapter Two, in Chapter Three, I expanded the analysis to include Chinook salmon populations from the Snake River, Upper Columbia River, and Middle Columbia River. I evaluated patterns of interannual variability in smolt-to-adult survival rates across these regions and examined the influence of a range of covariates for ecological processes thought to impact survival. This broader comparison 8 provided a basin-wide perspective on smolt-to-adult survival for spring and summer run Chinook salmon to assess whether trends observed in the Willamette River Basin were consistent with those from other parts of the Columbia River. 9 Chapter 2: Marine and Freshwater Survival Rate Estimates for Upper Willamette River Spring Chinook Salmon 2.1 Introduction This chapter's focal study species is the Evolutionary Significant Unit (ESU) of spring Chinook salmon from the UWR (Brandt et al., 2016; Schroeder et al., 2016). Despite being listed as an ESU to aid in improving conservation efforts, the numbers of UWR spring Chinook salmon remain at a fraction of their historical levels and continue to experience high mortality rates (Nehlsen et al., 1991; Wilson et al., 2022). Several factors have been hypothesized to contribute to the increased mortality rates in UWR Chinook salmon populations (Duffy & Beauchamp, 2011; Chamberlain et al., 2011; Cunningham et al., 2018; Sobocinski et al., 2021; Wilson et al., 2022). However, the reduced salmon returns have traditionally been attributed to alterations in freshwater ecosystems, mainly due to the WVP dams (Brandt et al., 2016; Keefer et al., 2013; Schroeder et al., 2016; Welch et al., 2020). The dams present high mortality risks, as fish must pass through high-pressure, high-velocity regulating outlets or hydroelectric turbines, where mortality hazards are presumed high (Brandt et al., 2016; Keefer et al., 2013). Some dams have spillways as an alternative to fish passage through regulating outlets or turbines; however, at high-head dams, these spillways have been found to induce high mortality rates (Brandt et al., 2016). The high mortality rates observed are concerning, as they appear to be preventing the recovery of ESA-listed salmon populations, especially for those that must pass through multiple dams and reservoirs (Olmsted et al., 2018). Despite the high mortality rates associated with dam passage, many uncertainties remain about 10 survival rates during other life stages of UWR spring Chinook salmon. Tagging studies offer a means to address these knowledge gaps. There are a variety of tags that can be used on salmon species to study their migration, ecology, behavior, marine residence, and factors affecting survival (Burnett et al., 2014; Gibbons & Andrews, 2004; Raby et al., 2011; Richard et al., 2014; Roussel et al., 2000; Spares et al., 2012; Vollset et al., 2020). However, PIT tags have increased in popularity in salmonid studies because they do not have a battery and are thus small and long-lasting; instead, they have an internal microchip that transmits a unique ID when the tag passes through an electrical field (Gibbons & Andrews, 2004; Hill et al., 2006; Prentice et al., 1990; Vollset et al., 2020). The electrical field is an array of passive antennas commonly located near hydroelectric facilities and fishways, allowing for detection records without needing physical recapture (Hill et al., 2006). The factors mentioned above make PIT tags useful for researching migratory fish, like salmon, which migrate to the ocean and return to rivers years later to spawn and complete their life cycle (Vollset et al., 2020). However, PIT tags are not perfect because the animals must pass within a certain distance of the antenna (0.3 meters - 1 meter) to be detected (Gibbons & Andrews, 2004; Prentice et al., 1990; Saboret et al., 2021; Zentner et al., 2021; Zydlewski et al., 2006). Passive antennas must be strategically placed along migration routes to increase the chance of detecting the tagged fish at each detection location; this can be problematic in large rivers, limiting their use (Zentner et al., 2021). Additionally, tag size, fish size, fish behavior, water velocity, water discharge, interference from ambient radio frequencies, and changes in water levels or depth can all have negative impacts on detection efficiency (O'Donnell et al., 2010; Saboret et al., 2021; Zydlewski et al., 2006). 11 These difficulties are exacerbated in the UWR due to the limited detection infrastructure (e.g., having only two long-standing detection sites at SUJ and WFF), the river's large size, and the multiple tributaries separated by large dams. Because UWR dams are primarily maintained for flood control, the mean river discharge can vary between seasons and years (Olmsted et al., 2018; Schroeder et al., 2016). The varying discharge can affect the detection of PIT-tagged fish, especially at Willamette Falls, which is the location of SUJ (Olmstead et al., 2018; Schroeder et al., 2016). High flows, for example, can lower the detection efficiency at SUJ, hindering the ability to accurately determine the number of juveniles reaching this location (Porteus et al., in review; Olmsted et al., 2018). However, a Bayesian implementation of the Cormack-Jolly-Seber model, based on the original models by Cormack (1964), Jolly (1965), and Seber (1965), is beneficial for PIT tagging studies due to its ability to account for uncertainty in detection and survival probabilities (Kery & Schaub, 2012). Another advantage of Bayesian statistics is the ability to incorporate relevant prior information, which helps enhance model estimates when data are scarce (Brooks et al., 2000; McCarthy & Masters, 2005). Whereas traditional frequentist methods preclude the incorporation of information obtained outside the study, Bayesian statistics utilize priors to incorporate previous knowledge into the modeling (Brooks et al., 2000; Kéry & Schaub, 2012). With vague priors, Bayesian methods yield similar outputs to traditional frequentist methods; however, informative priors can reduce uncertainty in conclusions (McCarthy & Masters, 2005). Therefore, I used informative priors developed for each parameter in the BCJS model to help improve the estimates (Porteus et al., in review). To better understand the population dynamics of UWR Chinook salmon populations and evaluate the extent to which the available data informs survival rate estimates, this chapter seeks 12 to estimate ÏRSS and ÏSAS for each release group and then address the following questions: (1) Given the relatively sparse PIT tag data from the UWR, what are the relative extents of updates from prior to posterior? (2) What is the central tendency in these updates for a given area and parameter? (3) Of the available data, which release groups show sufficient updating from the prior to be considered empirically driven? (4) What are the ranges of posterior mean estimates for ÏRSS and ÏSAS at a given release location? (5) Do the time series of survival estimates show any trends? Addressing these questions will help identify where survival rates are low, informing management and conservation efforts in freshwater and marine environments. 2.2 Methods 2.2.1 Study sites The US Army Corps of Engineers operates 13 dams throughout the UWR, nine of which (orange points in Figure 2.1) are located in the McKenzie, Middle Fork, North Santiam, and South Santiam sub-basins and hinder the migration of UWR spring Chinook salmon. River kilometers (RKM) mark the sub-basins and dams to determine the specific location of interest within the river (e.g., South Santiam RKM 19.000 â 19.032 represents a 32-kilometer stretch, 19 kilometers from where the South Santiam joins the mainstem; Figure 2.1; Table 2.1). Willamette Falls (purple point in Figure 2.1) is further downstream, where the two detection antenna arrays (Sullivan Dam Juvenile Bypass Facility and Willamette Falls Adult Fishway) are located (Table 2.1). The juvenile bypass facility detects PIT-tagged smolts migrating downstream to the ocean, while the adult fishway detects PIT-tagged adults returning upstream to spawn. 13 Table 2.1 Location of each area marked by river kilometers (RKM) from the Pacific Ocean. Area RKM Description Pacific Ocean 0.000 The mouth of the Columbia River Willamette 163.000 Where the Willamette joins the Columbia Willamette Falls 163.043 Location of Willamette Falls Middle Willamette 163.046 - 163.188 Reach of the mainstem North Santiam 163.174 The mouth of the North Santiam South Santiam 163.174 The mouth of the South Santiam Upper Willamette 163.190 â 163.297 Reach of the mainstem McKenzie 163.282 The mouth of the McKenzie Middle Fork 163.301 The mouth of the Middle Fork 14 Figure 2.1 Map of the Willamette River (Oregon, USA) and a portion of the Columbia. Points show where the Willamette connects to the Columbia (red point) and dam locations (orange points) along the river. Downstream is Willamette Falls (purple point), which houses Sullivan Dam Juvenile Bypass Facility (SUJ) and Willamette Falls Adult Fishway (WFF). Highlighted in bold are the four sub-basins, ordered from top to bottom: North Santiam, South Santiam, McKenzie, and Middle Fork, and two reaches of the mainstem river: Middle Willamette and Upper Willamette. 15 2.2.2 PIT-tagged fish Since the early 2000s, researchers have released groups of sub-yearling or yearling juvenile Chinook salmon fitted with PIT tags above and below dams in the UWR. These have typically been of hatchery origin, but some have also been of natural origin from captures made within the sub-basins (Brandt et al., 2016; Peterson et al., 2022; Schroeder et al., 2016). The compiled data from these studies is available in the PIT Tag Information System (PTAGIS; http://www.ptagis.org/), a central repository for all PIT tag studies conducted in the Columbia River basin. PTAGIS contains detailed records of the number of released fish, release locations, detection locations, and dates of releases and detections. The data used for this project was downloaded from the PTAGIS database in August 2023. 2.2.3 CJS model The analysis used a BCJS model with a minimum design configuration (Figure 2.2; Kéry & Schaub, 2012; Skalski et al., 1998). The BCJS model can estimate interval-specific survival rates of PIT-tagged fish and differentiate between survival rates and detections based on release detection records (Porteus et al., in review; Kéry & Schaub, 2012). As such, the model estimates four parameters: the release-smolt survival rate (ÏRSS), the smolt-to-adult survival rate (ÏSAS), and the probabilities of detection at SUJ (PSUJ) and WFF (PWFF), respectively (Figure 2.2). Juvenile Chinook salmon that pass SUJ are determined to be smolts. The model was run with either vague or informative prior probability distributions on ÏRSS, ÏSAS, and PSUJ; however, all model runs applied a highly informative prior on PWFF, specified by a Beta distribution of Beta(191.1, 3.9), resulting in a mean of 0.98 and a coefficient of variation (CV) of 0.01. The informative prior on PWFF was required because it was the final detection site, enabling differentiation between detection at WFF and survival rate between SUJ 16 and WFF. The PWFF prior was the strongest assumption; however, the detections at this location should not be much lower than 98% as other studies have found that very few returning PIT-tagged fish are undetected at adult fish ladders (Johnson et al., 2016; Welch et al., 2020). Beta(1,1) was the vague prior applied for ÏRSS, ÏSAS, and PSUJ. Informative priors were applied for ÏRSS specified by a Beta distribution of Beta(2.440, 3.665) with a mean of 0.399 and CV of 0.46, and ÏSAS specified by a Beta distribution of Beta(3.193, 277.76), with a mean of 0.0111 and CV of 0.555. The informative prior for detection at SUJ was split by flow level using the average of Willamette Falls' weighted mean discharge (cfs) and detection times. Flow levels were specified by a Beta distribution and categorized as low, Beta(0.672, 2.430), with a mean of 0.216 and CV of 0.939; mid, Beta(0.445, 2.499) with a mean of 0.151 and CV of 1.192; or high, Beta(0.215, 3.914) with a mean of 0.052 and CV of 1.882. For more details on developing the informative priors, see Porteus et al., in review. The model was run for each area (Figure 2.1; Table 2.2), using the vague priors and then the informative priors for 143 release groups under each scenario. Samples from the joint posterior probability distribution were simulated by Markov Chain Monte Carlo (MCMC) integration using JAGS (Plummer, 2003) implemented in R (Posit Team, 2023). The results are referred to as the vague and informative prior base case scenarios when using the priors specified above. Despite the informative priors developed for the model, initial runs indicated that the ÏSAS estimates from the 2015 and 2016 release groups are biased low. The Willamette Falls Adult Fishway monitoring station shut down in April 2019. Therefore, the data on the returns from the 2015 releases includes only age-3 and age-4 fish, and the returns from the 2016 releases include only age-3 fish. Across all areas and years of data, age-3 returns of spring Chinook 17 salmon from the Willamette are infrequent; typically, the returns consist mainly of age-4 and age-5 adults. As a result, the adult return data for the 2015 and 2016 release groups are missing a portion of the returning cohort (i.e., those expected to return in 2020 and 2021) and, therefore, likely cannot accurately capture estimates that describe the survival patterns from these cohorts. Table 2.2 The time series and number of release groups within each area (e.g., sub-basin or mainstem reach) examined in this study. Area Number of Release Groups Years McKenzie 60 2002-2015 Middle Fork 22 2011-2014 Middle Willamette 10 2007-2016 North Santiam 22 2006-2016 South Santiam 16 2006-2016 Upper Willamette 13 2004-2016 18 Figure 2.2. Schematic diagram of the Cormack-Jolly-Seber (CJS) model. The model follows a minimum design configuration, with one release site and two detection sites: one for juveniles (PSUJ) and one for adults (PWFF). The model parameters are release-smolt-survival (ÏRSS), smolt-adult-survival (ÏSAS), and probability of detection at the Sullivan Dam bypass facility (PSUJ) and at Willamette Falls (PWFF). Reprinted from Porteus et al., in review. 2.2.4 Convergence diagnostics Various model outputs (e.g., trace plots of MCMC chains, autocorrelation within MCMC chains, cross-correlations between parameters, and density plots for parameters) were examined to determine convergence. The primary outputs for overall convergence indicators were trace plots and Gelman-Rubin diagnostics. The trace plots were visually examined to determine 19 convergence. The Gelman-Rubin diagnostic outputs were also examined, with a cut-off threshold of 1.1 for the point estimates; any values exceeding this threshold indicated non-convergence. Convergence was achieved for all release groups after 60,000 iterations when running the model with informative priors, using the following settings: thinning every 20th iteration, a burn-in period of 10,000 iterations, and three independent chains. Consequently, the posterior was summarized using 3 Ã (60,000 â 10,000) / 20 for 7,500 samples. However, when running the model with 60,000 iterations using the vague priors, some release groups failed to converge (8 out of 143 total release groups) based on the Gelman-Rubin diagnostic (See Appendix A). However, convergence only occurred after 100,000 iterations (e.g., 3 Ã (100,000 - 10,000)/20 for 13,500 samples), and both runs provided similar estimates. Therefore, the number of iterations was kept at 60,000 for all release groups, as this provided stable summary results. 2.2.5 Posterior to prior precision ratio cut-off Although there is no universal standard for what can be considered empirically driven posterior results, I chose a posterior-to-prior precision ratio of two. A ratio with a value close to or lower than one suggests that there has been minimal update from the prior. However, a ratio of 1.5 represents a 50% increase in precision, and a ratio of two represents a doubling in precision. For this thesis, precision doubling was determined to indicate that the data had added sufficient information. Therefore, posterior-to-prior precision ratios exceeding two were deemed empirically driven posterior results. Additionally, the interquartile range (IQR) of the posterior-to-prior precision ratios was examined to assess the range of updates within an area for a given parameter. A narrow IQR 20 suggests that the ratios are relatively stable, indicating a more uniform increase in precision. Conversely, a wider IQR suggests greater variability in how much the data informs different parameters. 2.2.6 Sensitivity analysis Once the model ran under each release group's vague and informative prior base scenarios, the informative priors were adjusted to assess model sensitivity to the prior assumptions. The mean and precision were adjusted to half and 1.5 times the base scenario for the priors on survival (ÏSAS and ÏRSS), as these align with biologically realistic survival estimates. The base mean was multiplied by 1.5 to calculate the mean changes, and the variance remained unchanged. The adjusted mean values and base variance values were used to calculate new beta distributions, testing the sensitivity to the mean. To calculate the precision changes, the base variance was multiplied by 2 to obtain half the precision and by 0.5 to obtain 1.5 times the precision, while the prior mean values remained unchanged. The adjusted variance values and the base mean values were used to calculate the new beta distributions and test the sensitivity to the precision. The estimates for ÏRSS when halving the prior mean were (mean = 0.199, CV = 0.919), and when increasing the prior mean were (mean = 0.599, CV = 0.306), which determined the beta prior distributions, ÏRSS ~ Beta(0.746, 2.99) and ÏRSS ~Beta(0.366, 2.44), respectively. Similarly, when halving the precision, the values were (mean = 0.399, CV = 0.650), and when increasing the precision were (mean = 0.399, CV = 0.325), giving Beta prior distributions of ÏRSS ~ Beta (1.02, 1.53), and ÏRSS ~ Beta (5.28, 7.93). Alternatively, the estimates for ÏSAS when halving the prior mean were (mean = 0.00568, CV = 1.11) and when increasing it to 1.5 were (mean = 0.0165, CV = 0.370), which resulted in Beta prior distributions of ÏSAS ~ Beta (0.80, 21 139.99) and ÏSAS ~ Beta (7.15, 412.35), respectively. When halving the precision, the values were (mean = 0.011, CV = 0.785), and when increasing the precision, they were (mean = 0.011, CV = 0.392), which determined the beta prior distributions: ÏSAS ~ Beta(1.59, 138.39) and ÏSAS ~ Beta(6.39, 556.51). Additionally, the mean and precision were simultaneously changed to half the base prior; the estimates for ÏRSS were (mean = 0.199, CV = 0.406) with a Beta prior distribution of (0.273, 1.09), while for ÏSAS were (mean = 0.0568, CV = 1.57) with a Beta prior distribution of (0.397, 69.50). The base prior was highly informative for PWFF and assumed almost 100% detection probability. Nonetheless, lower detection probabilities of 0.9 and 0.49 were used to examine model sensitivity. The estimates for PWFF, with a mean of 0.9 (CV = 0.01), resulted in a Beta prior distribution of (956.09, 106.23). When halving the mean, the estimates were (mean = 0.49, CV = 0.020) with a Beta prior distribution of (1224.02, 1273.98). Model sensitivity to the PWFF parameter was also tested when the mean and precision were simultaneously changed to half their original values. The estimates for PWFF were (mean = 0.49, CV = 0.204) with a Beta prior distribution of (11.75, 12.23). The model was then run for each parameter scenario across all 143 release groups to test its sensitivity. For example, when changing ÏRSS to the half-mean Beta prior distribution, ÏSAS and PWFF remained at their base-case prior distributions (Table 2.3). 22 Table 2.3. Breakdown of the sensitivity analysis scenarios performed for ÏRSS, ÏSAS, and PWFF, showing what was changed for each parameter to determine the mean(CV) and the beta distribution. Sensitivity Analysis Parameter Mean Change Precision Change Mean (CV) Beta Distribution Inform Base ÏRSS None None 0.399 (0.46) Beta(2.440, 3.665) Vague Base ÏRSS None None 1(1) Beta(1,1) Half ÏRSS Half None 0.199(0.919) Beta(0.746, 2.99) 1.5 ÏRSS 1.5 X None 0.599(0.306) Beta(0.366, 2.44) Half ÏRSS None Half 0.399(0.650) Beta(1.02, 1.53) 1.5 ÏRSS None 1.5 X 0.399(0.325) Beta(5.28, 7.93) Half & Half ÏRSS Half Half 0.199(0.406) Beta(0.273, 1.09) Inform Base ÏSAS None None 0.011(0.555) Beta(3.193, 277.76) Vague Base ÏSAS None None 1(1) Beta(1,1) Half ÏSAS Half None 0.0057(1.11) Beta(0.80, 139.99) 1.5 ÏSAS 1.5 X None 0.0017(0.37) Beta(7.15, 412.35) Half ÏSAS None Half 0.011(0.785) Beta(1.59, 138.39 1.5 ÏSAS None 1.5 X 0.011(0.392) Beta(6.39, 556.51) Half & Half ÏSAS Half Half 0.0057(1.57) Beta(0.397, 69.50) Inform Base PWFF None None 0.98(0.01) Beta(191.1, 3.9) Half PWFF Half None 0.49(0.02) Beta(1224.02, 1273.98) 0.9 PWFF 0.9 X None 0.9(0.01) Beta(956.09, 106.23) Half & Half PWFF Half Half 0.49(0.204) Beta(11.75, 12.23 2.2.7 Seasonal effect Release groups were defined by location and year. However, some release groups were wild-caught and, therefore, could have been released over several months throughout the year, depending on when they were captured, rather than all being released on a single day (e.g., 23 hatchery releases). Of the groups released throughout the year, three showed a clear pattern, with some releases occurring in the spring, no releases in the summer, and then releases resuming in the fall or winter of that same year. To test for potential survival advantages from releasing fish in either spring or fall/winter, an alternative model was created by splitting the release dates into spring (March, April, May) and fall/winter (September, October, November, December) for these three groups. Then, counting the spring and fall/winter model outputs as additive, the DIC outputs from the original model without seasonal effects (combined) were compared to those from the split model (spring + fall/winter). 2.2.8 Estuary detections During the study period, a towed estuary detection array (TWX) operated seasonally from March to September each year, allowing for the compilation of detection histories from the estuarine environment. Estuary detection was included in the model because the additional detection station provides more data, potentially improving PIT tag survival estimates. The estuary analysis examines whether these extra detections meaningfully improve the estimates. Estuary detection and survival were specified using vague priors of Beta(1,1) to incorporate this data into the BCJS model. The model's m-array was modified, and to account for the extra detection location, the detection histories were redefined (e.g., from 111 to 1111). Then, the modified model was run for the release groups from the Middle Fork sub-basin, serving as a representative example. 2.2.9 Imputation of missing adult detections The Willamette Falls adult fishway monitoring station closed on April 4th, 2019 (PTAGIS, https://www.ptagis.org/Sites/InterrogationSites?code=WFF), so adult detections were not recorded after this date. Across all PIT tag study data, only 0.37% of spring Chinook salmon 24 adults returned to Willamette Falls before April 4th; the peak of the returns occurred in May and June. Therefore, it is unlikely that any returning adults were detected in 2019, meaning that reliable detections occurred only for age-3 and age-4 adults from the 2015 release groups and only for age-3 adults from the 2016 release groups. For 2015 and 2016 release groups with WFF detections before April 2019, the expected detection numbers of age-4 to age-6 returns were imputed using age composition data, allowing for examination of the model's sensitivity to the missing WFF detection data. Imputation was not possible for release groups with zero WFF detections. PIT tag study data from fully returned brood years prior to 2019 were used to determine the average age composition of the adults returning to the Willamette. For North Santiam adults (n = 222), the age-3 to age-6 return rates were 5.0%, 58.1%, 36.9%, and 0%, respectively. For McKenzie adults (n = 170), the age-3 to age-6 return rates were 2.4%, 39.4%, 55.9%, and 2.4%, respectively. For Middle Fork adults (n = 76), the return rates for the age groups 3 to 6 were 14.5%, 76.3%, 9.2%, and 0%, respectively. Too few adults returned from other areas to determine an age composition. Across all adult detections at Willamette Falls, the age-3 to age-6 return rates were 5.6%, 54.3%, 39.3%, and 0.9%, respectively. To impute the number of WFF detections for the 2015 release groups, a predicted age composition was generated using the known numbers of age-3 and age-4 detections with an unknown 'missing' number of age-5 and age-6 detections. An age composition for the 2016 release groups was generated using only the known numbers of age-3 detections. The unknown numbers-at-age were estimated by fitting the predicted age composition to the observed average age composition from the relevant area using minimum sums of squares. 25 2.3 Results The results section is structured as follows: First, I evaluate the extent of posterior updates from the informative priors for each parameter. Second, I report on the time series of the posterior parameter estimates under the base case model settings. In the third section, I report on the sensitivity of the results under different assumptions and input settings. 2.3.1 Assessing prior updates and informative data values for estimated parameters 2.3.1.1 Examining ratios of posterior to prior precision and IQR values Regarding ÏSAS posterior to prior precision, the McKenzie saw the smallest span of updates and the lowest IQR, with ratios ranging from 0.88 to 5.06 and a value of 1.25, respectively (Figure 2.3; Appendix B.1). In contrast, the Middle Fork saw the largest range in updates with ratios spanning from 0.81 to 62.02, this sub-basin also had the highest IQR, with a value of 7.06 (Figure 2.3; Appendix B.1). The Middle Willamette and the North Santiam saw similar ranges in updates for ÏSAS posterior to prior precision ratios spanning from 2.15 to 20.25 and from 1.18 to 20.25, respectively (Figure 2.3; Appendix B.1). The South Santiam and Upper Willamette had similar ranges with ratios ranging from 1.1 to 7.5 and from 1.88 to 6.89, respectively (Figure 2.3; Appendix B.1). Additionally, the relationship between the posterior to prior precision ratio and release group size was examined by linear regression. Regarding ÏSAS, there was a positive relationship between the precision ratio and release group size, resulting in an R2 value of 0.244 (Appendix B.5). The smallest span in ÏRSS posterior to prior precision ratios and lowest IQR value was from the South Santiam, with ratios ranging from 1.11 to 2.69 and a value of 0.37 (Figure 2.4; Appendix B.2). The McKenzie and the Middle Willamette also saw small ranges in updates spanning from 1.09 to 3.66 and from 1.94 to 3.00, respectively (Figure 2.4; Appendix B.2). The 26 Upper Willamette saw a range of ÏRSS posterior to prior precision ratios from 1.77 to 7.52 (Figure 2.4; Appendix B.2). The Middle Fork and North Santiam saw larger ratio ranges from 1.13 to 37.5 and 1.46 to 15.28, respectively (Figure 2.4; Appendix B.2). These two groups also had the highest IQR values of 5.57 and 4.08, respectively (Appendix B.2). Additionally, the relationship between the posterior to prior precision ratio and release group size was examined, in regards to ÏRSS, the positive relationship between the precision ratio and release group size resulted in an R2 value of 0.214 (Appendix B.6). The PSUJ posterior means showed variation from the prior mean and in the range of the amount of updating (Figure 2.5; Appendix B.3; Appendix C.1; Appendix C.4). Within the McKenzie, under the low, mid, and high flows, the PSUJ posterior to prior precision ratios ranged from 1.79 to 11.88, from 1.96 to 67.24, and from 1.19 to 119.05, respectively (Figure 2.5; Appendix B.3). Within the Middle Fork, the ratios ranged from 1.35 to 25.86 under the low flow, from 1.71 to 73.80 under the mid-flow, and from 1.37 to 1071.47 under the high flow (Figure 2.5; Appendix B.3). In the McKenzie, the mid flow group had the highest IQR with a value of 12.72; however, in the Middle Fork, the mid flow group had the lowest IQR value of 11.80 (Appendix B.3). In Middle Willamette, the low flow had the smallest IQR value of 0.13 with ratios ranging from 1.34 to 1.97 whereas the mid flow ratios ranged from 1.18 to 7.04 (Figure 2.5; Appendix B.3). Within the North Santiam, under the low, mid, and high flows, the PSUJ posterior to prior precision ratios ranged from 1.34 to 52.77, from 2.69 to 144.64, and from 0.51 to 21.87, respectively, the high flow had the lowest IQR with a value of 5.34 (Figure 2.5; Appendix B.3). Within South Santiam, the ratios ranged from 1.41 to 93.81 under the low flow and from 1.49 to 2.95 under the mid flow (Figure 2.5; Appendix B.3). In the Upper Willamette, the low flow ratios ranged from 1.35 to 14.73, and the mid flow PSUJ ratios ranged from 1.43 to 27 2.59 (Figure 2.5; Appendix B.3). In the South Santiam and the Upper Willamette, the mid flow groups had the lowest IQR values of 1.06 and 0.58, respectively (Appendix B.3). Additionally, the relationship between the posterior to prior precision ratio and release group size was examined, in regards to PSUJ, the positive relationships between the precision ratio and release group size resulted in R2 values of 0.045, 0.252, and 0.322 for the low, mid, and high flow release groups, respectively (Appendix B.7). Across all areas, the PWFF posterior means remained unchanged from the prior mean (Figure 2.6; Appendix C.1; Appendix C.5). For the PWFF parameter, the data did not add any information to the prior, as indicated by the PWFF posterior to prior precision ratios (Figure 2.6; Appendix B.4). All PWFF ratios had values of one (Appendix B.4). Based on posterior-to-prior precision ratios with values larger than 1.5, out of 143 total release groups, 118 ÏSAS estimates, 113 ÏRSS estimates, and 123 PSUJ estimates are sufficiently updated (Appendix B.1; Appendix B.2; Appendix B.3). However, based on the posterior-to-prior precision ratios for ÏSAS, ÏRSS, and PSUJ, a ratio threshold of two was chosen as the cut-off for empirically driven posterior estimates. Based on this cut-off point, out of 143 total release groups, 100 ÏSAS estimates, 70 ÏRSS estimates, and 107 PSUJ estimates are considered empirically driven posterior estimates (Appendix B.1; Appendix B.2; Appendix B.3). When breaking it down by area, for ÏSAS, that removes 26 release groups from the McKenzie, nine from the Middle Fork, none from the Middle Willamette, two from the North Santiam, five from the South Santiam, and one from the Upper Willamette (Appendix B.1). Regarding ÏRSS, this cut-off removes 43 groups from the McKenzie, eight from the Middle Fork, one from the Middle Willamette, six from the North Santiam, 13 from the South Santiam, and two from the Upper Willamette (Appendix B.2). As for PSUJ, it removes six groups from each area (Appendix B.3). 28 PWFF had a highly informative prior placed on it. Therefore, no cut-off ratio was considered for this parameter, as the ratios were all one (Appendix B.4). The plots in the following results sections include the posterior mean estimates from each release group; however, when reporting on the results, I will only discuss those with ratios of posterior-to-prior precision larger than two. 2.3.1.2 Relationship between the posterior correlation coefficient and release group size R² values were calculated to determine the relationship between the posterior correlation coefficient in parameter estimates and release group size. The strongest relationship with release group size was the correlation between detection probability at SUJ and ÏSAS (R² = 0.83; Appendix E.1). This positive correlation showed a substantial increase from small release group sizes but then leveled out to a mean of 0.75 at release group sizes around 5,000 (Appendix E.1). The second strongest relationship with release group size was the negative correlation between ÏRSS and ÏSAS (R² = 0.75; Appendix E.2). This decreased from close to zero at small release group sizes and leveled to -0.75 at release group sizes larger than 5,000 (Appendix E.2). These R² values were derived from fitted relationships, where an asymptotic model provided the best fit. Both of these strong relationships between the posterior correlation coefficient and release group size indicate that the structure in the data could provide information for estimation on key parameters, including ÏSAS, PSUJ, and ÏRSS, but is best realized at release group sizes around 5,000 and larger (Appendix E.1; Appendix E.2). The posterior correlation coefficients between the other parameters, including PSUJ and PWFF, PSUJ and ÏRSS, PWFF and ÏRSS, and PWFF and ÏSAS, all showed weak correlations with release group size. 29 Figure 2.3. Posterior density plots of smolt-adult-survival (ÏSAS) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The solid black lines are the prior distributions, and the dashed lines are the ÏSAS distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. 30 Figure 2.4. Posterior density plots of release-smolt-survival (ÏRSS) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The solid black lines are the prior distributions, and the dashed lines are the ÏRSS distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. 31 Figure 2.5. Posterior density plots of detection probability at SUJ (PSUJ) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The areas are further subdivided by flow level into low, mid, or high, depending on the flow at detection time. The solid black lines are the prior distributions, and the dashed lines are the PSUJ posterior distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. 32 Figure 2.6. Posterior density plots of detection probability at WFF (PWFF) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. The solid black lines are the prior distributions, and the dashed lines are the PWFF distributions. There is one dashed line per year for easier visual analysis, but with multiple releases per year, the density is calculated across all points from that year. The colours of the lines denote release years, spanning from 2002 to 2016. 2.3.2 Base case time series of parameter estimates Within the McKenzie, ÏSAS posterior means from the McKenzie River (RKM 0-56) release group had a narrow range from 0.0051 (CV = 0.57) to 0.0076 (CV = 0.58; Figure 2.7; Appendix C.2). The North Fork McKenzie River release group also had a narrow range in estimates from 0.0046 (CV = 0.67) to 0.0069 (CV = 0.63; Figure 2.7; Appendix C.2). The McKenzie Hatchery release group exhibited more variation in ÏSAS, with means ranging from 0.0049 (CV = 0.56) to 0.0120 (CV = 0.36; Figure 2.7; Appendix C.2). Similarly, the ÏSAS estimates from the McKenzie River Bypass release group had means ranging from 0.0046 (CV = 33 0.65) to 0.0098 (CV = 0.44; Figure 2.7; Appendix C.2). Regarding ÏRSS, the McKenzie River (RKM 0-56) release group showed means ranging from 0.148 (CV = 0.81) to 0.248 (CV = 0.51; Figure 2.8; Appendix C.3). The McKenzie River Bypass release group had posterior means ranging from 0.208 (CV = 0.46) to 0.314 (CV = 0.36), also showing slight variation in ÏRSS (Figure 2.8; Appendix C.3). Within the McKenzie, release group estimates for ÏSAS, appear to show different trends (Figure 2.7; Appendix C.2). For instance, the McKenzie River (RKM 0-56) release group ÏSAS estimates were 0.0076, 0.0074, and 0.0070 in 2004, 2005, and 2006 respectively (Figure 2.7). However, in the McKenzie Hatchery release group, the ÏSAS estimate in 2004 was 0.0076, but decreased to 0.0056 in 2005 and then increased to 0.0120 in 2006 (Figure 2.7). The Middle Fork Dexter Dam Tailrace release group exhibited low variation in ÏSAS, with posterior means ranging from 0.0017 (CV = 0.57) to 0.0044 (CV = 0.55; Figure 2.9; Appendix C.2). Middle Fork Lookout Point Dam Head of Reservoir showed more variation in ÏSAS, with posterior mean estimates ranging from 0.003 (CV = 0.62) to 0.0072 (CV = 0.40; Figure 2.9; Appendix C.2). Regarding ÏRSS, the Middle Fork Dexter Dam Tailrace release group showed the most variation over the years, with posterior means ranging from 0.043 (CV = 0.72) to 0.301 (CV = 0.42; Figure 2.10; Appendix C.3). Contrastingly, the Middle Fork Lookout Point Dam Head of Reservoir release group showed lower variation in ÏRSS, with means ranging from 0.023 (CV = 1.30) to 0.189 (CV = 0.60; Figure 2.10; Appendix C.3). Within the Middle Fork, the Dexter Dam Tailrace and Lookout Point Dam Head of Reservoir release groups showed a similar time series trend in ÏRSS, however, a similar trend was not observed in ÏSAS (Figure 2.9; Figure 2.10; Appendix C.2; Appendix C.3). 34 Within the mainstem Middle Willamette, ÏSAS estimates were consistently below the prior, with 2016 showing the highest estimate and the most uncertainty (mean = 0.0095, CV = 0.46; Figure 2.11; Appendix C.2). ÏRSS estimates ranged from 0.199 (CV = 0.54) to 0.496 (CV = 0.24; Figure 2.11; Appendix C.3). This area experienced a decrease in ÏSAS and ÏRSS from 2008 to 2010; however, the rest of the time series varied from year to year without observable trends between the two survival parameters (Figure 2.11; Appendix C.2; Appendix C.3). Within the North Santiam, the Big Cliff Dam Tailrace (RKM 19.066) release group exhibited variability in ÏSAS, with consistently low CVs (all below 0.3; Figure 2.12). The Detroit Dam Forebay, Detroit Dam Head of Reservoir (RKM 19.091), and Detroit Dam Head of Reservoir (RKM 19.093) release groups all showed decreasing ÏSAS estimates over the years (Figure 2.12; Appendix C.2). However, each group's final year of data (2016) had the highest CVs: 0.89, 0.41, and 0.91, respectively (Figure 2.12). The North Santiam (RKM 19.000 - 19.030) release group ÏSAS estimates ranged from 0.0045 (CV = 0.63) to 0.0097 (CV = 0.44; Figure 2.12; Appendix C.2). Regarding ÏRSS, the Big Cliff Dam Tailrace (RKM 19.066) release group means ranged from 0.28 to 0.48, with consistently low CVs of 0.25 (Figure 2.13). The Detroit Dam Head of Reservoir (RKM 19.093) release group 2016 estimate had the lowest mean of 0.062, with the highest CV of 1.15 (Figure 2.13; Appendix C.3). The North Santiam (RKM 19.000 - 19.030) release group ÏRSS estimates, ranged from 0.180 (CV = 0.68) to 0.298 (CV = 0.41; Figure 2.13; Appendix C.3). The South Santiam (RKM 19.000 - 19.032) release group had ÏSAS mean estimates ranging from 0.0040 (CV = 0.57) to 0.0086 (CV = 0.51; Figure 2.14; Appendix C.2). Regarding ÏRSS, the mean estimates ranged from 0.134 (CV = 0.84) to 0.262 (CV = 0.50; Figure 2.15; Appendix C.3). 35 ÏSAS in the mainstem Upper Willamette exhibited little variability, particularly from 2010 to 2016, with means during these years ranging from 0.0041 (CV = 0.57) to 0.0051 (CV = 0.54; Figure 2.16; Appendix C.2). In contrast, ÏRSS means ranged from 0.140 (CV = 0.48) to 0.295 (CV = 0.42; Figure 2.16; Appendix C.3). The ÏRSS estimates showed a decreasing trend from 2012 until 2014, however, a similar trend was not observed in the ÏSAS estimates (Figure 2.16; Appendix C.3). Within the North Santiam Detroit, the below-dam release exhibited higher ÏSAS in 2013 (mean = 0.0103) relative to the above-dam release (mean = 0.0076), but in 2014, ÏSAS was lower in the below-dam release (mean = 0.0060) compared to the above-dam release (mean = 0.0073; Figure 2.12; Appendix C.2). Regarding, ÏRSS the estimate was higher for the above-dam release in 2013 (mean = 0.375) compared to the below-dam release (mean = 0.276; Figure 2.13; Appendix C.3). However, in 2014, ÏRSS was lower for the above-dam release (mean = 0.256) compared to the below-dam release, which had a mean estimate of 0.405 (Figure 2.13; Appendix C.3). 36 Figure 2.7. ÏSAS for each release group within the McKenzie sub-basin from 2002 to 2015 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.011), while the grey shading indicates the 95% prior credible interval. The pink data points represent the posterior mean estimates with their corresponding 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 37 Figure 2.8. ÏRSS for each release group within the McKenzie sub-basin from 2002 to 2015 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 38 Figure 2.9. ÏSAS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.011), while the grey shading indicates the 95% prior credible interval. The pink data points represent the posterior mean estimates with their corresponding 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 39 Figure 2.10. ÏRSS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors. When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 40 Figure 2.11. ÏSAS (top panel) and ÏRSS (bottom panel) for the Middle Willamette reach of the mainstem river from 2007 to 2016 under the base case with informative priors. The dashed line represents the prior mean values (mean = 0.399 & mean = 0.011), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 41 Figure 2.12. ÏSAS for each release group within the North Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.011), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 42 Figure 2.13. ÏRSS for each release group within the North Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2 and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 43 Figure 2.14. ÏSAS for each release group within the South Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.011), while the grey shading indicates the 95% prior credible interval. The pink data points represent the posterior mean estimates with their corresponding 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 44 Figure 2.15. ÏRSS for each release group within the South Santiam sub-basin from 2006 to 2016 under the base case with informative priors. The dashed line represents the prior mean value (mean = 0.399), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2, triangles represent ratios between 1.5-2, and squares represent ratios less than 1.5. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 45 Figure 2.16. ÏSAS (top panel) and ÏRSS (bottom panel) for the Upper Willamette reach of the mainstem river from 2004 to 2016 under the base case with informative priors. The dashed line represents the prior mean values (mean = 0.399 & mean = 0.011), the grey shading is the 95% prior credible interval, and the pink data points represent the posterior mean estimates with 95% credible intervals. Circles represent release groups with ratios larger than 2 and triangles represent ratios between 1.5-2. The minimum and maximum values for each release group are displayed at the bottom left of each panel. 2.3.3 Sensitivity analysis of the results under different assumptions and input settings 2.3.3.1 Changes to prior mean and precision Model sensitivity to changes in the prior distributions for ÏRSS, ÏSAS, and detection at PWFF across all areas was examined visually using plots. I used data from the Middle Fork to analyze sensitivity to different assumptions and input settings. The data from Middle Fork are a representative example of the comprehensive dataset. Across the other five areas, the observable trends appear similar to those in the sensitivity analysis from the Middle Fork. For sensitivity plots from the other five areas, please see Appendix D. 46 Some ÏSAS estimates derived from vague priors were larger than those derived from informative priors (Figure 2.17). In some cases, even when the ÏSAS mean was increased by 1.5 times the informative prior, the vague prior estimates remained higher (Figure 2.17). For instance, in the Hills Creek Dam Head of Reservoir release group in 2012, the mean from the 1.5 increase was 0.0117, while the estimate from the vague prior was higher at 0.0599 (Figure 2.17). The sensitivity analysis explored variations in the mean and precision of the priors (Table 2.3). Increasing the ÏSAS prior mean by 1.5 times led to decreased ÏRSS estimates, while halving the ÏSAS prior mean resulted in increased ÏRSS estimates (Figure 2.17). In the Hills Creek Dam Head of Reservoir release group from the year 2012, increasing the ÏSAS prior mean by 1.5 times to 0.0117 (CV = 0.436) resulted in a ÏRSS estimate of 0.0422 (CV = 0.592; Figure 2.17). Conversely, halving the ÏSAS prior mean to 0.0017 (CV = 0.934) increased the ÏRSS estimate to 0.3226 (CV = 0.542; Figure 2.17). Similarly, increasing the ÏRSS prior mean by 1.5 times to 0.2960 (CV = 0.625) caused a decrease in the ÏSAS estimate to 0.0022 (CV = 0.853; Figure 2.19). On the other hand, halving the ÏRSS prior mean to 0.0560 (CV = 0.847) led to an increase in the ÏSAS estimate to 0.0095 (CV = 0.579; Figure 2.19). Precision changes for both ÏSAS and ÏRSS showed less pronounced effects overall than the prior mean changes, although smaller release groups were slightly more sensitive than larger release groups (Figure 2.18; Figure 2.20). This trend was particularly noticeable in the releases at Dexter Dam Tailrace (Figure 2.18; Figure 2.20). In 2011, 5,959 fish were released. In the model, increasing ÏSAS precision by 1.5 times resulted in a mean of 0.0046 (CV = 0.423), compared to the base mean of 0.011, and an ÏRSS estimate of 0.234 (CV = 0.391), compared to the base mean of 0.399 (Figure 2.18). Contrastingly, in 2012, 49,301 fish were released, and increasing the ÏSAS 47 precision by 1.5 times in the model resulted in a mean of 0.0026 (CV = 0.344) and a ÏRSS estimate of 0.143 (CV = 0.299; Figure 2.18). The results were variable when the prior mean and precision were halved simultaneously. For instance, the 2011 Lookout Point Dam Head of Reservoir release group showed relatively consistent results among the sensitivity analysis estimates. Under the base case, the ÏSAS posterior mean was 0.0056. Under the sensitivity analysis, halving both the prior mean and precision together resulted in a posterior mean of 0.0021 (CV = 0.938), compared to 0.0023 (CV = 0.863) when halving the prior mean alone and 0.0038 (CV = 0.758) when halving only the prior precision (Figure 2.17; Figure 2.18). In contrast, results for 2014 showed much greater variability. Under the base case, the posterior mean for ÏSAS was 0.0047. However, after halving both the prior mean and precision together, the posterior mean was 0.000082 (CV = 2.595), compared to 0.00024 (CV = 2.161) when halving the prior mean alone and 0.0013 (CV = 1.475) when halving only the prior precision (Figure 2.17; Figure 2.18). When examining changes in the detection prior probability at WFF, which had a highly informative prior, minimal shifts in posteriors for ÏRSS and ÏSAS were observed under different pWFF prior specifications (Figure 2.21). For instance, in the Lookout Point Dam Forebay release group from 2013, decreasing the PWFF prior mean to 0.9 resulted in a ÏSAS posterior mean of 0.0045 (CV = 0.506) compared to the base posterior mean of 0.0042 and an ÏRSS posterior mean of 0.1988 (CV = 0.529) compared to the base posterior mean of 0.1958 (Figure 2.21). Halving the PWFF prior mean to 0.49 led to a ÏSAS posterior mean of 0.0065 (CV = 0.465) and a ÏRSS posterior mean of 0.2368 (CV = 0.473; Figure 2.21). 48 Figure 2.17. Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork sub-basin from 2011 to 2014. 49 Figure 2.18. Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and a combination of half-precision and mean. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. 50 Figure 2.19. Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. 51 Figure 2.20. Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. 52 Figure 2.21. Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from the base (0.98) to 0.9, 0.49, and a combined mean and precision of half. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis due to the considerable variation in release sizes (ranging from less than 100 to over 30,000). Release groups are from the Middle Fork basin from 2011 to 2014. 53 2.3.3.2 Percent change in posterior means There was no relationship between the percent changes in the posterior estimates with different priors (e.g., half and 1.5 times the base case) and release group size, as indicated by the widespread data points and low R2 values (<0.16). However, the non-zero percent changes indicate that changing the prior mean or precision affects the posterior across all groups. Please refer to Appendix F for the plots. 2.3.3.3 Seasonal effect To test for seasonal effect, the 2008 McKenzie bypass release group was the only one with a posterior-to-prior precision ratio larger than two for both ÏSAS and ÏRSS (Appendix B.1, Appendix B.2). The McKenzie hatchery release group empirically updated for ÏSAS but not ÏRSS and the 2012 McKenzie Bypass release group empirically updated for ÏRSS but not ÏSAS (Appendix B.1, Appendix B.2). However, because of the posterior correlation between ÏSAS and ÏRSS in the model, having one of the two parameters empirically updated should aid in estimating the other (Appendix E.2). Under each scenario, the model without seasonal effects outperformed the alternatives (Table 2.4). For the McKenzie hatchery release group, a DIC difference of 11.9 favored the model without a split for seasonal effects (Table 2.4). Similarly, DIC differences of 14.2 in 2008 and 12.3 in 2012 for the McKenzie River Bypass release groups favored the model without seasonal splits (Table 2.4). Although the posterior credible intervals for ÏSAS and ÏRSS overlapped between the combined model and the split models, there were some differences in the point estimates for each release group (Figure 2.22; Figure 2.23). For the ÏSAS estimates, the 2008 release group showed more variation, with estimates ranging from 0.0069 to 0.013 (Figure 2.22). The 2012 release 54 group showed slight variation, with estimates ranging from 0.013 to 0.015 (Figure 2.22). The 2010 McKenzie Hatchery release group had posterior mean estimates of 0.0086, 0.0088, and 0.010 for the combined, spring, and winter models, respectively (Figure 2.22). Regarding ÏRSS, the 2008 McKenzie Bypass release group showed estimates of 0.36, 0.30, and 0.31 for the combined, spring, and winter models, respectively (Figure 2.23). The 2010 McKenzie Hatchery release group had posterior mean estimates of 0.40 for the combined and winter models and an estimate of 0.38 for the spring model (Figure 2.23). The 2012 McKenzie Bypass release group had the lowest estimate of 0.28 from the combined model and 0.34 and 0.32 for the spring and winter models, respectively (Figure 2.23). Figure 2.22 ÏSAS for each release group with a seasonal split in release timing. Columns are divided by model type from left to right: combined (no seasonal effect), spring (filtering for only spring releases), and winter (filtering for only winter releases). The dashed line represents the prior mean value, with a mean of 0.011. The data points represent the mean estimates with 95% credible intervals (black = posterior estimates, pink = prior values). The point values for each release group's posterior estimates are listed at the bottom left of each panel. 55 Figure 2.23. ÏRSS for each release group with a seasonal split in release timing. Columns are divided by model type from left to right: combined (no seasonal effect), spring (filtering for only spring releases), and winter (filtering for only winter releases). The dashed line represents the prior mean value, with a mean of 0.399. The data points represent the mean estimates with 95% credible intervals (black = posterior estimates, pink = prior values). The point values for each release group's posterior estimates are listed at the bottom left of each panel. Table 2.4. DIC outputs from four release groups with a clear seasonal split in release timing. Model outputs from combined (e.g., no seasonal split accounted for) or spring and winter (e.g., filtered for spring, then for winter, and then added the DIC outputs). Group Year Model DIC McKenzie River Bypass 2008 Combined 18.4 McKenzie River Bypass 2008 Spring & Winter 32.6 McKenzie Hatchery 2010 Combined 17.8 McKenzie Hatchery 2010 Spring & Winter 29.7 McKenzie River Bypass 2012 Combined 21.1 McKenzie River Bypass 2012 Spring & Winter 33.4 56 2.3.3.4 Estuary detections Including estuary detection and survival in the model had minimal impact on the estimates for both ÏRSS and ÏSAS compared to the original model that excluded the estuary detection data (Appendix C.6; Appendix C.7; Figure 2.24; Figure 2.25). There was a larger difference in the ÏSAS point estimates compared to ÏRSS. However, the credible intervals for both parameters showed an overlap between the estuary and base models across all release groups (Figure 2.24; Figure 2.25). In the Lookout Point Head of Reservoir release group, ÏSAS estimates were 0.0042 in 2011, 0.0083 in 2012, 0.0027 in 2013, and 0.0024 in 2014 compared to the base estimates of 0.0056, 0.0072, 0.0030, and 0.0047, respectively (Appendix C.6; Figure 2.24). Regarding ÏRSS, the estimates were 0.134 in 2011, 0.082 in 2012, 0.195 in 2013, and 0.022 in 2014 compared to the base estimates of 0.135, 0.097, 0.189, and 0.023, respectively (Appendix C.7; Figure 2.25). 57 Figure 2.24. ÏSAS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors (pink) and the base case with estuary detections (blue). When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.011), and the data points represent the posterior mean estimates with 95% credible intervals. The minimum and maximum values for each release group are displayed on the left side of each panel, with the top panel representing the estuary and the bottom panel representing the base. 58 Figure 2.25. ÏRSS for each release group within the Middle Fork sub-basin from 2011 to 2014 under the base case with informative priors (pink) and the base case with estuary detections (blue). When multiple releases occur from the same location within the same year, the data point is adjusted by 0.2 years for easier visual analysis. The dashed line represents the prior mean value (mean = 0.399), and the data points represent the posterior mean estimates with 95% credible intervals. The minimum and maximum values for each release group are displayed on the left side of each panel, with the top panel representing the estuary and the bottom panel representing the base. 2.3.3.5 Imputation of adult detections The imputed datasets showed higher ÏRSS and ÏSAS estimates than the non-imputed datasets (Figure 2.26; Figure 2.27). However, all the 2015 release groups showed overlap 59 between the credible intervals (Figure 2.26; Figure 2.27). In contrast, the 2016 releases showed either no or minimal overlap in the credible intervals between the non-imputed and imputed datasets (Figure 2.26; Figure 2.27). The 2016 release group from the Middle Willamette had a non-imputed ÏSAS estimate of 0.0095, but the imputed estimate was 0.038, showing no overlap in the credible intervals (Figure 2.26). Similarly, for ÏRSS, the non-imputed estimate was 0.26, whereas the imputed estimate was 0.76, again showing no overlap in the credible intervals (Figure 2.27). The 2016 release group from the Upper Willamette had a non-imputed ÏSAS estimate of 0.0048, and the estimate for the imputed dataset was 0.013 (Figure 2.26). Additionally, the ÏRSS estimate from the non-imputed dataset was 0.26, whereas the imputed estimate was 0.55 (Figure 2.27). However, there was some overlap in the credible intervals from the 2016 Upper Willamette release group (Figure 2.26; Figure 2.27). Figure 2.26. Comparison of ÏSAS estimates from non-imputed (pink) and imputed (green) data sets. Big Cliff Dam Tailrace, Detroit Dam Head of Reservoir, Horse Creek, McKenzie River (RKM 0-56), and McKenzie River (RKM 57-90) release groups are from 2015, and Middle Willamette and Upper Willamette release groups are from 2016. The dashed line represents the prior mean of 0.011. 60 Figure 2.27. Comparison of ÏRSS estimates from non-imputed (pink) and imputed (blue) data sets. Big Cliff Dam Tailrace, Detroit Dam Head of Reservoir, Horse Creek, McKenzie River (RKM 0-56), and McKenzie River (RKM 57-90) release groups are from 2015, and Middle Willamette and Upper Willamette release groups are from 2016. The dashed line represents the prior mean of 0.399. 2.4 Discussion 2.4.1 Empirically driven posterior estimates Across all areas, most release groups showed empirical updates in parameter estimates. However, some release groups had ÏSAS and ÏRSS posterior-to-prior precision ratios that were not large enough to be considered empirically driven. Regarding ÏSAS, there were 26/60 release groups from the McKenzie with ratios less than two, 9/22 from the Middle Fork, 0/10 from the Middle Willamette, 2/22 from the North Santiam, 5/16 from the South Santiam, and 1/13 from the Upper Willamette (Appendix B.1). Although a ratio of two was chosen as the cut-off, with a more relaxed cut-off ratio of 1.5, then 13/60 release groups from the McKenzie were not considered empirically driven, 6/22 from the Middle Fork, 0/10 from the Middle Willamette, 61 2/22 from the North Santiam, 4/16 from the South Santiam and 0/13 from the Upper Willamette (Appendix B.1). Additionally, there were three release groups that had ÏSAS ratios less than one: the South Fork McKenzie River Tailrace in 2012, the Middle Fork Dexter Dam Tailrace in 2013, and the Middle Fork Hills Creek Tailrace in 2013, which had releases of 42, 150, and 308 fish, respectively (Appendix B.1). The ratios less than one were unexpected however, likely result from the small number of releases from these groups. Regarding ÏRSS 43 groups from the McKenzie cannot be considered empirically driven based on the cut-off of two, eight from the Middle Fork, one from the Middle Willamette, six from the North Santiam, 13 from the South Santiam, and two from the Upper Willamette (Appendix B.2). However, with a cut-off ratio of 1.5, 18 groups from the McKenzie cannot be considered empirically driven, seven from the Middle Fork, none from the Middle Willamette, one from the North Santiam, four from the South Santiam, and none from the Upper Willamette (Appendix B.2). It is important to consider the amount of update in the posteriors as the results show that some groups provide more informative data, leading to more substantial updates. Understanding these differences is crucial for interpreting the reliability of survival estimates across different release groups. With a cut-off ratio of two for PSUJ posterior to prior precision ratios, six release groups from each area were not updated enough to be considered empirically driven (e.g., six groups from each area had ratios less than two). With a cut-off ratio of 1.5 for PSUJ posterior to prior precision ratios, two release groups from the McKenzie were not empirically updated, three from the Middle Fork, five from the Middle Willamette, five from the North Santiam, two from the South Santiam, and three from the Upper Willamette (Appendix B.3). Within North Santiam, the three high-flow releases from 2016 had PSUJ ratios of posterior-to-prior precision lower than one (Figure 2.5; Appendix B.3). One potential explanation is the closure of the WFF detection site in 62 April 2019, which affected the recorded number of adult returns from the 2015 and 2016 release groups. Within North Santiam, no adult detections from the 2016 releases before April 2019 existed. Therefore, the lack of adult returns could lead the model to adjust ÏSAS estimates based on SUJ detections (Appendix E.1). The model assumes that early-stage detection and survival are linked: a lower detection rate at SUJ suggests more fish pass through undetected; conversely, a higher detection probability at SUJ signals that fewer fish may be migrating successfully. When the model assumes that fewer fish are migrating out to sea, based on the SUJ detections, it predicts lower ÏSAS returns, and vice versa (Appendix E.1). This may explain why the data did not update from the prior for the North Santiam 2016 high-flow release groups. The means from the PWFF posterior distributions matched the prior mean across all years and areas, and all ratios of posterior-to-prior precision equaled one (Figure 2.6; Appendix B.4). The ratios of one indicate that the data did not update from the prior likely because of the highly informative prior placed on the PWFF parameter to differentiate between survival and detection rates (Porteus et al., in review; Johnson et al., 2016; Welch et al., 2020). 2.4.2 Survival estimate comparisons Smolt-to-adult returns (SAR) are calculated by multiplying smolt survival during freshwater downstream migration, marine survival, and adult survival during freshwater upstream migration (Welch et al., 2020). However, due to the limited PIT tagging infrastructure in the UWR, the model used for this project cannot account for upstream survival back to the release site, as the UWR lacks detection arrays upstream from WFF (Porteus et al., in review). Therefore, no detection histories existed for adults passing WFF and returning to their respective release points (Porteus et al., in review). As a result, this model can only account for upstream survival to WFF. Therefore, the ÏSAS estimates here likely show higher survival than SAR 63 estimates because a portion of survival is missing from WFF back to the release location, which could include many more kilometers of migration or more dam passage, depending on the release location. In other areas of the Columbia River, the Northwest Power and Conservation Council has adopted a standard rebuilding target for spring Chinook salmon (McCann et al., 2021; Welch et al., 2020). The target has been set at 2-6% for SARs, with a 2% return considered the minimum for potential recovery (McCann et al., 2021; Welch et al., 2020). However, recent estimates put survival under 2% for multiple Snake River and Columbia stocks (CTC, 2021; McCann et al., 2021). These findings are consistent with the outcomes from this study, where no ÏSAS estimates reached the 2% minimum survival goal (Appendix C.2). If 2% SAR is the minimum survival required for the recovery of these populations, the estimates shown here indicate that UWR spring Chinook salmon are not meeting the necessary rates for recovery (McCann et al., 2021; Welch et al., 2020). Several potential factors could influence these low survival rates, which will be explored further in Chapter Three of this thesis. Release-smolt survival rates within different rivers appear more variable. Estimates from the Klamath, Trinity, and Snake Rivers put survival at 0.709, 0.639, and 0.897, respectively (Beeman et al., 2015). Survival from Minto Dam to Portland also fell within this range, with estimates from 0.675 to 0.836 (Beeman et al., 2015). However, estimates have been placed between 0.443 and 0.564 in the Sacramento River, depending on the release date (Beeman et al., 2012). The results for ÏRSS from this study ranged from 0.023 to 0.496 across all areas and, therefore, were more in line with those from the Sacramento River (Appendix C.3). A study conducted by Skalski et al. (1998) for juvenile Chinook salmon in the Snake and Columbia Rivers found that ÏRSS was higher with less distance traveled. The study found that 64 survival was 0.902 for a distance of 31 km (from release to the tailrace of Lower Granite Dam) but was 0.859 for a distance of 60 km (from the tailrace of Lower Granite Dam to the tailrace of Little Goose Dam; Skalski et al., 1998). The results shown here agree with the findings from Skalski et al. (1998) when looking at ÏRSS; the Upper Willamette estimates were typically lower than those from the Middle Willamette, where release groups have less distance to travel before reaching SUJ (Figure 2.1; Figure 2.11; Figure 2.16; Table 2.1). Other studies have found lower survival in areas near dams and lower survival when juvenile salmon must pass multiple dams during migrations (Beeman et al., 2012; Brandt et al., 2016; Keefer et al., 2013). From the results shown here, the area with some of the lowest ÏRSS estimates observed was the Middle Fork sub-basin, especially the above dam release group, Middle Fork Lookout Point Head of Reservoir (Figure 2.9). The Middle Fork sub-basin is the furthest basin from SUJ (Figure 2.1; Table 2.1). Moreover, juvenile Chinook salmon originating above the Lookout Point Reservoir have two Middle Fork dams (Lookout Point and Dexter) to attempt to go through during their downstream migration (Figure 2.1). The combination of having the longest migration distance and multiple dam passages could explain why the model estimated low ÏRSS for these release groups from the Middle Fork. One could expect ÏSAS to be higher but ÏRSS to be lower for above-dam releases compared to below-dam releases. Fish released above dams must migrate through the dam, potentially leading to lower ÏRSS (Beeman et al., 2012; Brandt et al., 2016; Keefer et al., 2013; Skalski et al., 1998). However, fish have better growth opportunities in the above-dam reservoirs. Therefore, they can reach a larger size before entering the ocean. Studies have found that a larger ocean entry size is associated with higher ÏSAS (James et al., 2023; Osterback et al., 2014). Notably, some results obtained here did not match the expectation. Within the North Santiam 65 Detroit, the below-dam release exhibited higher ÏSAS in 2013 relative to the above-dam release (Figure 2.12; Appendix C.2). Regarding ÏRSS, the estimate was higher for the above-dam release compared to the below-dam release (Figure 2.13; Appendix C.3). 2.4.3 Assessing model sensitivity 2.4.3.1 Informative prior changes Informative priors can impact the final model estimates if they are too precise; therefore, checking the model's sensitivity to different prior assumptions is important to ensure it is correctly specified (Depaoli et al., 2020). This study's sensitivity analysis examined changes in survival parameters (ÏRSS and ÏSAS) and adult detection probability (PWFF). Although the model was sensitive to parameter changes, none of the alterations had a strong enough effect to warrant a re-evaluation of the original prior assumptions. However, some outcomes from the sensitivity analysis were worth noting. The model exhibited heightened sensitivity to changes in the mean, compared to changes in precision, suggesting that the estimates are concentrated around the central values of the prior. Additionally, the priors have a greater impact on shaping the estimates for smaller release groups. Smaller groups have fewer data points and inherently provide less information, whereas larger groups have more empirical observations on which the model can rely. As a result, the model relies more on the prior to guide the estimates for groups with smaller release sizes. However, the calculated percent changes with release size showed low R-squared values, suggesting that the number of fish released does not have a strong effect (Appendix F). The model showed a strong negative relationship between the ÏRSS and ÏSAS posterior correlation coefficient and release group size (Appendix E.2). This relationship was evident in the sensitivity analysis, where increasing the prior mean value (e.g., 1.5 x prior mean) of one 66 survival parameter caused lower estimates in the other and decreasing the prior mean value (e.g., by half) of one survival parameter caused higher estimates in the other (Figure 2.17). This negative relationship implies that within the model structure, ÏRSS and ÏSAS are each somewhat constrained by the other. The effects of changing both the mean and precision were mixed, with some years showing consistent estimates while others demonstrated more variable estimates. In particular, the Lookout Point Dam Head of Reservoir release group exhibited stability in the 2011 estimates, whereas the 2014 estimates showed more variability under the same adjustments (Figure 2.19). This suggests that in 2011, the data may be informative enough to reduce model dependency on the prior assumptions. In contrast, the 2014 data show a greater reliance on the prior, indicating that the data were less informative. Regardless of adjustments to the prior mean for PWFF, ÏSAS, and ÏRSS remained essentially unchanged (Figure 2.21). This is a positive outcome, given that the PWFF prior was necessary to differentiate between the survival rate and the detection at WFF. In BCJS models without this prior, these parameters cannot be identified separately (Porteus et al., in review; Kéry & Schaub, 2012). 2.4.3.2 Seasonal effect on survival The results indicate that the model without a seasonal effect outperformed the model incorporating additive seasonal effects (Table 2.4). However, this finding may be influenced by the low number of detections, particularly when filtering for fall/winter or spring releases, which may limit the model's ability to estimate survival rates accurately. Furthermore, the analysis was 67 confined to three release groups within McKenzie, limiting the ability to draw broad conclusions regarding the impact of seasonal release timing on survival. Various factors affect survival, but release timing could be one, especially in the UWR, where flow rates vary between seasons (Olmsted et al., 2018; Schroeder et al., 2016). The UWR dams are mainly operated for flood control, and the flow levels at dams may not align well with the natural timing of downstream migrating juvenile Chinook salmon smolts (Beeman et al., 2015). An active tag study conducted in the Detroit Reservoir found that estimates for reach survival differed between seasons, with spring survival ranging from 0.670 to 0.812 and fall survival ranging from 0.622 to 0.921 (Beeman et al., 2015). A similar trend could occur in the UWR, depending on when groups are released; this could coincide with flow levels that hinder dam passage and survival during migration. However, the three release groups' data showed minimal survival differences between seasons (Figure 2.22; Figure 2.23). Due to the sparseness of the data, my results cannot provide much insight into potential seasonal effects. Therefore, future datasets that include a more comprehensive range of seasonal releases could allow for further, more accurate estimation and would be an interesting area for future research. 2.4.3.3 Inclusion of estuary survival in the model In this study, only the Middle Fork was used as a representative example to assess potential differences in estimates between the models with and without estuary detections (Figure 2.24; Figure 2.25). The results indicated no or minimal changes in survival estimates when estuary detections were added (Figure 2.24; Figure 2.25). Although the absolute differences between the models were slight, the estuary data could still be included in future estimations, as none of the parameter estimates were compromised with the inclusion of the data. 68 One factor potentially contributing to the limited variation observed between the estimates could be the relatively low number of estuary detections overall. The estuary detections are from a towed array that operates from March to September yearly; however, this array has lower overall detections than SUJ. The highest number of detections at SUJ was from the 2012 Middle Fork Dexter Dam Tailrace release group, with 2,747 detections out of 49,301 fish released. In contrast, the same release group had 34 detections from the TWX array. Thirty-four was also the highest number of TWX detections across all release groups. Additional detection infrastructure within the estuary would allow for more accurate and differentiated estimates. Furthermore, informative priors were developed for the other four parameters, but not the estuary parameter. Future efforts could focus on creating informative priors to enhance model performance and precision, particularly where current detection data is limited in the estuary. 2.4.3.4 Effect of closure of Willamette Falls detection site In North Santiam, the final year of data (2016) exhibited unexpectedly low ÏSAS estimates compared to previous years within this sub-basin (Figure 2.12). This is likely a result of the closure of the Willamette Falls adult fishway monitoring station in April 2019 (https://www.ptagis.org/Sites/InterrogationSites?code=WFF). With the station shut down, adult returns for age-4, and age-5 fish from the 2016 release groups were not detected. As a result, the model classified these undetectable returns as 'false' zeros (e.g., non-survivors), even though some adults may have returned after the station ceased operations. Therefore, the data from the 2016 releases included only age-3 jack returns, which, in the UWR, are known to be sporadic and less representative of overall survival trends (Olmsted et al., 2018). Most adult spawner returns in the UWR typically consist of age-4 and age-5 fish (Olmsted et al., 2018). 69 This trend of unusually low 2016 survival estimates did not occur in the Middle and Upper Willamette, likely because they had more adult return data; however, the estimates showed wide credible intervals, reflecting higher uncertainty (Figure 2.11; Figure 2.16). Additionally, the imputed results from the age composition data showed higher survival estimates for the 2016 releases when compared to the non-imputed data, indicating that survival would be higher with the extra detections of age-4 and age-5 fish (Figure 2.26; Figure 2.27). Although no detection data were available to perform an imputation for the North Santiam 2016 releases, a similar trend could be expected, as observed in the Middle and Upper Willamette imputations. If imputation were possible for the North Santiam sub-basin, the results would likely show an increase in the 2016 smolt-to-adult survival estimates from this area compared to the current estimates. 2.5 Limitations Population studies assessing trends in survival rates typically have 30 or more years of data (Mantua & Hare, 2002; Schaller et al., 2014). However, the UWR time series is relatively short, from 2002 to 2016 for releases and extending to 2019 for detections. Additionally, several release groups in this study lack complete time series, with some release locations having multiple-year gaps between records or some locations represented by only one or two years of data. Furthermore, in April 2019, the WFF detection station was shut down, which hindered the ability to accurately model the survival estimates for the 2015 and 2016 release groups. The SUJ detection station was also shut down in September 2018, so in addition to no detection at WFF, there is currently no ability to detect smolts or returning adults at Willamette Falls from recent releases of PIT-tagged fish into different areas of the UWR (Cramer Fish Sciences, 2024). 70 Nevertheless, this study presents a starting point in understanding UWR spring Chinook salmon survival rates. If PIT-tag detection infrastructure in the Willamette improves in the future, this model provides a reasonably robust framework for estimating ÏRSS and ÏSAS under uncertainty. 2.6 Conclusion This chapter examined survival rate estimates for UWR spring Chinook salmon through a Bayesian CJS framework. It provides initial insights into UWR spring Chinook salmon survival and shows areas where population recovery targets remain unmet. ÏSAS estimates were consistently below the 2% minimum SAR target for recovery. Additionally, ÏRSS estimates showed that sub-basins requiring longer migrations through multiple dams exhibited the lowest survival estimates. However, challenges, including monitoring limitations and incomplete time series, highlight the need for additional data and expanded detection infrastructure to better monitor these ESA-listed populations. 71 Chapter 3: Examining Drivers of Chinook Salmon Smolt-to-Adult Survival Rates in the Columbia River Basin 3.1 Introduction Chinook salmon (Oncorhynchus tshawytscha) populations throughout the west coast of North America have experienced substantial declines in productivity in recent years (Welch et al., 2020). These declines have occurred even in regions with relatively pristine freshwater conditions, such as Southeast Alaska and the Canadian Yukon, indicating that factors beyond freshwater habitat degradation contribute to reduced survival (Welch et al., 2020). Such observations challenge the long-standing assumption that anthropogenic impacts in freshwater are the primary drivers of population declines and instead suggest the importance of broader oceanographic processes, even in highly modified systems such as the Columbia River (Welch et al., 2020). Despite this, knowledge of survival during the marine phase remains limited due to the speciesâ extensive migrations, complex life histories, and stock-specific variability in ocean use. The Columbia River provides a valuable setting to examine these uncertainties, as it supports multiple Chinook salmon stocks, including those from the Columbia and the Willamette, which migrate through and interact. The Willamette River joins the Columbia River at river kilometre (RKM) 163; therefore, Chinook salmon originating from the Willamette River Basin must pass through a portion of the Columbia River, including the Columbia River Estuary, before reaching the Pacific Ocean. In doing so, they are exposed to the same environmental conditions as stocks from other regions of the Columbia Basin, suggesting that factors influencing ÏSAS estimates in the Willamette could be similar to those affecting other Columbia River stocks. The Columbia River itself flows more 72 than 2,000 kilometers before emptying into the Pacific Ocean (Stanford et al., 2005). The Columbia is one of the world's most developed rivers, and, similar to the Willamette River Basin, it is a dammed system that provides around 60% of the hydropower for the Pacific Northwest (Rechisky et al., 2013; Stanford et al., 2005; Williams et al., 2005). However, the dams have caused direct and indirect mortality for migrating salmon populations (Rechisky et al., 2013; Stanford et al., 2005; Williams et al., 2005). Concerns about the impacts of the dams were raised before their construction. Upon their completion, research began estimating passage survival for downstream migrating juvenile salmonids, with spring and summer runs of Chinook salmon being of particular concern (Rechisky et al., 2013; Williams et al., 2005). In 1966 and 1967, four dams were in place on the main stem of the Snake River to Bonneville; during this time, survival estimates ranged between 32% and 56% for juvenile Chinook salmon migrating through all four dams (Williams et al., 2005). In the 1970s, eight dams were in place on the mainstem, and survival rate estimates for juvenile Chinook salmon ranged from 10% to 30% (Williams et al., 2005). Due to the concerns surrounding passage survival, many efforts were made to mitigate the impacts of the dams. Structures were built to aid migrations, including juvenile bypass systems and modified spillways, and transportation programs (âtrap-and-haulâ) were implemented (Williams et al., 2005). Despite efforts to enhance downstream survival, several Columbia River Chinook salmon stocks showed no signs of recovery, which eventually led to their listing under the federal Endangered Species Act in 1992 (McCann et al., 2024; Rechisky et al., 2013). Even with their listing, many Columbia River Chinook salmon stocks continue to remain at low levels (McCann et al., 2024; Rechisky et al., 2013). But, the lack of recovery 73 cannot be attributed entirely to the dams, as freshwater survival rates of juvenile Chinook salmon have improved since the implementation of the dam passage programs (McCann et al., 2024). A study conducted by Rechisky et al. (2013) found that Chinook salmon smolts migrating downstream through the eight mainstem dams had survival rates of around 50%. However, smolt-to-adult return rates for many West Coast Chinook salmon populations are typically around 1% (Welch et al., 2020). These low returns likely result from a combination of factors such as ocean conditions (Cunningham et al., 2018; Duffy & Beauchamp, 2011), predator abundance (Sobocinski et al., 2021; Wilson et al., 2022), and hatchery practices (Chamberlain et al., 2011), which impact Chinook salmon throughout their lifecycle. The negative impacts of the hydropower system may worsen the effects of the aforementioned drivers on Chinook salmon returns, particularly during periods of poor ocean conditions (Chamberlin et al., 2011; Connors et al., 2022; Cunningham et al., 2018; Stanford et al., 2005; Williams et al., 2005; Wilson et al., 2022). Ocean conditions can strongly influence Chinook salmon production, and smolts migrating from various regions of the Columbia River Basin, exhibiting the same life history types, all enter the ocean through the mouth of the Columbia River, and are thus likely affected by oceanographic conditions in the same way early in their marine life (Williams et al., 2005). For instance, cold sea surface temperatures (SST) and increased coastal upwelling are associated with improved adult Chinook salmon returns (Rechisky et al., 2013). Conversely, periods of poor ocean conditions, such as a positive phase of the Pacific Decadal Oscillation (PDO), coincide with low ÏSAS estimates (Rechisky et al., 2013; Williams et al., 2005). Understanding how 74 oceanographic conditions impact Chinook salmon is important; however, it is dependent on knowledge of which areas of the ocean they inhabit. While the migration routes of Chinook salmon appear consistent from year to year, a single population can exhibit multiple life history types that undergo different migration routes (Rechisky et al., 2013). In the Columbia River Basin, spring-run Chinook salmon typically spawn in September, and their fry emerge from the gravel by January, marking the beginning of their freshwater rearing phase (Bottom et al., 2008). From there, individuals can follow different developmental pathways. Subyearling Chinook salmon typically migrate and smolt in the spring or early summer, entering the ocean during their first year of life (Bottom et al., 2008). However, some individuals overwinter in natal streams or the estuary and start their ocean migration the following spring as yearlings (Bottom et al., 2008). Subyearling Chinook salmon typically remain along the coastal waters of British Columbia during their first summer before gradually migrating northward (Bottom et al., 2008; Riddell et al., 2018). In contrast, yearling Chinook salmon typically migrate in May after rearing in freshwater for a year and can be found in Alaska during their first summer at sea (Riddell et al., 2018). These differing life history strategies have implications for survival, as yearlings and subyearlings experience different oceanographic conditions during their first year at sea. In addition to juvenile outmigration timing, Chinook salmon are categorized into three main runs: spring, summer, and fall (Riddell et al., 2018). These run types are associated with different life histories: spring- and summer-run Chinook are generally yearling migrants, while fall-run Chinook typically follow a subyearling strategy (Bottom et al., 2008; Riddell et al., 2018). Adult return timing also differs. Spring-run Chinook enter freshwater in early spring, and summer-run Chinook return slightly later (Riddell et al., 75 2018). In contrast, fall-run Chinook enter freshwater later in the year (Riddell et al., 2018). Because fall-run Chinook differ in both juvenile and adult migratory behavior, including them in analyses with spring and summer-run Chinook salmon would introduce additional life history variation that is not directly comparable. Despite the challenges associated with studying salmon survival, much effort has been dedicated to researching the Columbia River Chinook salmon populations (Quinn, 2018). One large-scale effort is the Comparative Survival Study (CSS), which provides data on survival trends for Chinook salmon and steelhead (O. mykiss) originating in the Columbia River Basin (McCann et al., 2024). Similar to the Willamette Basin, the CSS utilizes PIT-tagged fish to estimate survival (McCann et al., 2024). Most PIT tagging of Columbia River Basin salmon occurs at hatcheries, smolt traps, or juvenile bypasses (Fryer et al., 2017). The tagged fish are then released into the system, where PIT tag arrays detect the fish as they migrate (Fryer et al., 2017). Compared to the Willamette River, the Columbia River has a far greater number of detection arrays (McCann et al., 2024). The PIT tag arrays capture passage dates and locations for both juvenile and adult PIT-tagged fish; juvenile detection probabilities can range from 1-90%, while adult detection probabilities are nearly 100% (McCann et al., 2024; Fryer et al., 2017). From the release and detection data, survival probability can be estimated and compared across release groups and sub-basins (McCann et al., 2024). In the previous chapter, I estimated time series of smolt-to-adult survival rates (ÏSAS) for spring-run Chinook salmon from PIT-tag studies conducted in the Upper Willamette River system, which revealed interannual variation. Understanding the drivers of this variation remains challenging because the Willamette time series is relatively short and imprecise. In contrast, 76 more precise estimates are available for spring- and summer-run stocks from other Columbia River regions (McCann et al., 2024). This chapter, therefore, examines the factors associated with variation in ÏSAS across the Willamette, Snake, Middle Columbia, and Upper Columbia regions (McCann et al.,2024). Specifically, I address the following questions: (1) Are there common shared year effects influencing smolt-to-adult survival? (2) Do similar trends in year effects emerge across regions? (3) Are Willamette ÏSAS estimates comparable to those in other regions of the Columbia Basin? (4) Which covariates appear to explain interannual variation in ÏSAS? 3.2 Methods 3.2.1 Study Sites The Columbia River Basin contains multiple large dams that influence the migration of Chinook salmon. Along the mainstem Columbia and Lower Snake rivers, eight dams operated by the U.S. Army Corps of Engineers impede the downstream migration of smolts and the upstream migration of returning adults (Figure 3.1). River kilometers (RKM) are used to indicate specific locations along rivers. The downstream-most structure is Bonneville Dam at RKM 64, which includes two detection facilities: the Bonneville Dam Juvenile Bypass Facility (BVJ) and the Bonneville Adult Fishway (BWL; Figure 3.1). BVJ detects PIT-tagged juveniles migrating toward the ocean, while BWL detects returning adults migrating upstream to their natal spawning grounds. 77 Figure 3.1. Map of the Columbia River. Points show dam locations (orange points) along the river. Furthest downstream is Bonneville Dam, which houses the Bonneville Dam Juvenile Bypass Facility (BVJ) and the Bonneville Adult Fishway (BWL). Highlighted in bold are the three sub-basins, ordered from right to left: Snake River, Upper Columbia, and Middle Columbia. Note: Figure 2.1 shows the location of the Willamette River sub-basins and where it joins the Columbia River. 3.2.2 Criteria for inclusion of smolt-to-adult survival rate estimates from the Willamette River Basin In Chapter Two, I generated ÏSAS estimates for PIT tag study release groups from the Willamette River Basin. As established in the previous chapter, I defined empirically driven posterior results as those with posterior-to-prior precision ratios exceeding two; of the 143 release groups examined, 43 had ratios of two or less and were not considered further. In addition to meeting the cut-off criteria, the release group needed to have at least three consecutive years of data for either hatchery or wild releases. Applying these criteria narrowed 78 the dataset to 57 release groups from the Willamette River Basin (Appendix G.1; Table 3.1). Although this chapter refers broadly to the Willamette River, the ÏSAS estimates are based on release groups located throughout the basin, including both mainstem and tributary sites. Of the release groups from the Willamette River Basin that met the established criteria, there was a mix of subyearling and yearling Chinook salmon releases. Since subyearling and yearling Chinook salmon exhibit distinct migratory behaviors, it is important to differentiate between their life history types (Riddell et al., 2018). However, since subyearling life history types can migrate to the ocean as yearlings, determining the timing of ocean entry is also important. Although there are few juvenile detections beyond the Sullivan Dam juvenile bypass facility at Willamette Falls (SUJ) to determine the exact timing of ocean entry, previous research in the Columbia River has reported on migration and estuary residency times for both life history types. Studies have found that hatchery-origin subyearlings released earlier in the year tend to migrate quickly through the system, with these individuals having short estuarine residency times (Bottom et al., 2008). In contrast, hatchery-origin subyearlings released later in the year are more likely to stay in the estuary throughout the winter and migrate to the ocean the following spring as yearlings (Bottom et al., 2008; Marsh et al., 2007). Based on the previous research available, I assumed that the Willamette River Basin subyearlings released from June until September migrated without prolonged estuarine residency time and reached the ocean as subyearlings, while those released in October and November overwintered in the estuary and migrated onwards the following spring as yearlings (Table 3.1). 79 Table 3.1 Release groups of PIT-tagged juvenile spring Chinook salmon from the Willamette River Basin that are empirically updated and have three or more years of consecutive hatchery or wild release data. Releases entering the ocean as subyearlings are bolded. Year Release Group Type 2002 McKenzie River(RKM 0-56) Wild 2003 McKenzie River(RKM 0-56) Wild 2004 McKenzie River(RKM 0-56) Wild 2005 McKenzie River(RKM 0-56) Wild 2007 McKenzie River(RKM 0-56) Wild 2008 McKenzie River(RKM 0-56) Wild 2009 McKenzie River(RKM 0-56) Wild 2011 McKenzie River(RKM 0-56) Wild 2012 McKenzie River(RKM 0-56) Wild 2013 McKenzie River(RKM 0-56) Wild 2014 McKenzie River(RKM 0-56) Wild 2015 McKenzie River(RKM 0-56) Wild 2004 McKenzie Hatchery Hatchery 2005 McKenzie Hatchery Hatchery 2006 McKenzie Hatchery Hatchery 2008 McKenzie River Bypass Wild 2009 McKenzie River Bypass Wild 2010 McKenzie River Bypass Wild 2011 McKenzie River Bypass Wild 2013 McKenzie River Bypass Wild 2013 McKenzie River Bypass Wild 2014 McKenzie River Bypass Wild 2015 McKenzie River Bypass Wild 2011 Middle Willamette Wild 2012 Middle Willamette Wild 2013 Middle Willamette Wild 2014 Middle Willamette Wild 2012 Big Cliff Dam Tailrace(RKM 19.066) Hatchery 2013 Big Cliff Dam Tailrace(RKM 19.066) Hatchery 2014 Big Cliff Dam Tailrace(RKM 19.066) Hatchery 2012 Detroit Dam Head of Reservoir(RKM 19.091) Hatchery 2013 Detroit Dam Head of Reservoir(RKM 19.091) Hatchery 2014 Detroit Dam Head of Reservoir(RKM 19.091) Hatchery 2014 Detroit Dam Head of Reservoir(RKM 19.093) Hatchery 2015 Detroit Dam Head of Reservoir(RKM 19.093) Hatchery 2016 Detroit Dam Head of Reservoir(RKM 19.093) Hatchery 2007 North Santiam(RKM 19.000-19.030) Wild 2008 North Santiam(RKM 19.000-19.030) Wild 2009 North Santiam(RKM 19.000-19.030) Wild 2010 North Santiam(RKM 19.000-19.030) Wild 2011 North Santiam(RKM 19.000-19.030) Wild 80 2007 South Santiam(RKM 19.000-19.032) Wild 2008 South Santiam(RKM 19.000-19.032) Wild 2009 South Santiam(RKM 19.000-19.032) Wild 2010 South Santiam(RKM 19.000-19.032) Wild 2011 South Santiam(RKM 19.000-19.032) Wild 2012 South Santiam(RKM 19.000-19.032) Wild 2007 Upper Willamette Wild 2008 Upper Willamette Wild 2009 Upper Willamette Wild 2010 Upper Willamette Wild 2011 Upper Willamette Wild 2012 Upper Willamette Wild 2013 Upper Willamette Wild 2014 Upper Willamette Wild 2015 Upper Willamette Wild 2016 Upper Willamette Wild 3.2.3 Selection of ÏSAS estimates from the Columbia River Basin The cut-off criteria I established left a limited number of Willamette River Basin release groups available for further analysis (Appendix G.1). To expand the analysis, I supplemented the dataset with ÏSAS estimates from spring- and summer-run Chinook salmon stocks in other regions of the Columbia River Basin, obtained through the Comparative Survival Study (CSS; McCann et al., 2024). The CSS Annual Report provides survival estimates for wild- and hatchery-origin spring and summer Chinook salmon release groups from the Snake River, Middle Columbia, and Upper Columbia (Appendix G.2; Appendix G.3; Appendix G.4; Figure 3.1; McCann et al., 2024). References to these Columbia River regions include release groups from both mainstem sites and tributaries. The Columbia River Basin contains more PIT-tag detection infrastructure than the Willamette River Basin, allowing for smolt-to-adult return (SAR) estimates from juvenile release location until adult returns to the release location (McCann et al., 2024). In the Willamette River 81 Basin, estimates reflect survival from juvenile detection at Willamette Falls to adult return at the same location, and therefore capture only a portion of the full cycle. As a result, the two estimates are not entirely comparable, as the CSS SAR values include additional freshwater survival components. However, to ensure as much consistency as possible, I used CSS estimates based on adult returns to Bonneville Dam, rather than the release point (McCann et al., 2024). Although the CSS refers to these values as SAR estimates, SARs typically encompass complete freshwater and marine survival, including adult survival upstream of Bonneville Dam (Welch et al., 2020). Therefore, because the estimates do not reflect the complete cycle, and to maintain consistency across regions, I refer to both sets of estimates as ÏSAS. There are further inconsistencies between the two datasets. The CSS primarily focuses on PIT tagging and releasing yearling spring and summer Chinook salmon, whereas subyearlings are typically fall-run Chinook salmon (McCann et al., 2024). In contrast, the Willamette River Basin dataset includes both yearling and subyearling spring Chinook salmon. Determining the ocean entry timing of these releases allowed for the separation of subyearling and yearling migrants within the dataset (Table 3.1). Another difference is that the CSS distinguishes between jack and non-jack returns, whereas the Willamette River Basin dataset does not (McCann et al., 2024). In the Columbia River Basin, many groups had jack return proportions exceeding 20%, while in the Willamette River Basin, jack returns were consistently below 10% across all years. Therefore, I used non-jack CSS estimates to ensure better alignment with the Willamette River Basin data. Incorporating the CSS estimates with those from the Willamette River Basin (n= 48) resulted in 481 release groups, including 108 releases from the Middle Columbia River, 99 from 82 the Upper Columbia River, and 226 from the Snake River (Appendix G.2; Appendix G.3; Appendix G.4). 3.2.4 Global effects models To assess how different factors affect smolt-to-adult returns, I examined whether shared effects could explain the observed variations. I evaluated whether ÏSAS was influenced by (1) shared interannual sources of variation (shared year effect), representing conditions experienced by all groups in a given year; (2) differences among groups (group effect), capturing variation among regions; (3) hatchery versus wild (hatchery effect), representing variation between origin types; or (4) a combination of year and group effects to explore their joint influence on the observed variation. I outline the four models below. I used the same set of priors for the four models below. The prior on µ assumes a broad normal distribution centered at zero. The lognormal prior on observation error variance (Tse) reflects typical smolt-to-adult return rates observed in salmon populations while allowing for moderate uncertainty around the median. These priors were chosen to be weakly informative, allowing flexibility for the data to inform the estimates. 3.2.4.1 Shared year effect Observation Model: log(ÏSASi) ~ N(µ + δy[t], Ïobs) For each release group i = 1, 2,â¦, n, where ÏSASi represents the smolt-to-adult return rate for release group i, μ is the global mean, and δy[t] is the year effect for year t. Year Effect: δy[t] ~ N(0, ÏT), t = 1, 2, â¦., nyears 83 Priors: µ ~ N(0, 0.001) Tse ~ Lognormal(lmse, Ïse) ÏT = 1/Tse2 lmse = log(0.8) Ïse = 1/0.72 Ïobs ~ Gamma(0.001, 0.001) A sensitivity analysis of the year effect model assessed how posterior estimates responded to different assumptions about prior certainty. Three specifications were tested to see how strongly the distribution is concentrated around its mean: 1) the base prior, 2) a higher precision prior, and 3) a lower precision prior. Priors: Base: µ ~ N(0, 0.001) High: µ ~ N(0, 0.01) Low: µ ~ N(0, 0.0001) Group effect Observation Model: log(ÏSASi) ~ N(µ + δg[i], Ïobs) For each release group i = 1, 2,â¦, n, where ÏSASi represents the smolt-to-adult return rate for release group i, μ is the global mean, and δg[i] is the group-level effect for release group i. Group Effect: δg[i] ~ N(0, ÏT), i = 1, 2, â¦., ngroups 84 Priors: µ ~ N(0, 0.001) Tse ~ Lognormal(lmse, Ïse) ÏT = 1/Tse2 lmse = log(0.8) Ïse = 1/0.72 Ïobs ~ Gamma(0.001, 0.001) 3.2.4.2 Hatchery effect Observation Model: log(ÏSASi) ~ N(µ + δtype[i], Ïobs) For each release group i = 1, 2,â¦, n, where ÏSASi represents the smolt-to-adult return rate for release group i, μ is the global mean, and δtype[i] is the effect of hatchery or wild type for release group i. Hatchery Effect: δtype[i] ~ N(0, ÏT), type = 1, 2, â¦., ntypes Priors: µ ~ N(0, 0.001) Tse ~ Lognormal(lmse, Ïse) ÏT = 1/Tse2 lmse = log(0.8) Ïse = 1/0.72 Ïobs ~ Gamma(0.001, 0.001) 85 3.2.4.3 Group and year effect Observation Model: log(ÏSASi) ~ N(µ + δy[i] + ϵg[i] + γy[i], g[i], Ïobs) For each release group i â = 1, 2, â¦., n, where ÏSASi represents the smolt-to-adult return rate for release group i, μ is the global mean, and δy[i] is the year effect for release group i, ϵg[i] is the group effect for release group i, and γy[i],g[i] is the year by group interaction effect. Group Effect: ϵg[i] ~ N(0, ÏT), g = 1, 2, â¦., ngroups Year Effect: δy[t] ~ N(0, ÏT), t = 1, 2, â¦., nyears Year and Group Effect: γy[i],g[i] ~ N(0, ÏT), for all t and g Priors: µ ~ N(0, 0.001) Tse ~ Lognormal(lmse, Ïse) ÏT = 1/Tse2 lmse = log(0.8) Ïse = 1/0.72 Ïobs ~ Gamma(0.001, 0.001) 3.2.5 Covariate compilation I conducted a covariate analysis to better understand the factors contributing to the variability in spring and summer Chinook salmon survival. To inform my analysis, I reviewed the literature on Chinook salmon and selected the most consistently supported covariates across 86 studies (Appendix I.1). These included ocean conditions indices, interaction effects, the number of released hatchery Chinook salmon, and the number of predator species. After identifying the relevant covariates, I compiled time series data for each one (Appendix I.1). The final set of covariates included in the analysis is summarized in Table 3.2. To ensure comparability across covariates and allow for interpretation of covariate effects, I standardized each covariate before analysis. Standardization was performed by calculating the mean and standard deviation for each covariate time series, and then transforming the data: Standardized value = (x â xÌ) / s Where x is the original value, xÌ is the mean, and s is the standard deviation of the covariate (Table 3.2). The standardized covariate time series were then used in the subsequent modeling to assess which covariates may be driving the observed variations. Table 3.2. Description of covariates used for analysis. Stage describes what phase of life the covariate is affecting. Covariates were standardized based on the mean and standard deviation (SD) calculated for each covariate's time series. Covariate Description Stage Mean SD Alaska SST Summer sea surface temperature from the Gulf of Alaska (°C) 1st Ocean Year 11.235 0.916 BC SST Average summer sea surface temperature from Nootka Point and Amphitrite Point (°C) 1st Ocean Year 14.293 0.536 ENSO Winter El Niño Southern Oscillation cycle readings 1st Ocean Year -0.271 0.838 NPGO Winter North Pacific Gyre Oscillation readings 1st Ocean Year -0.055 1.403 PDO Winter Pacific Decadal Oscillation readings 1st Ocean Year -0.561 0.897 48N, 125W Summer upwelling index at 48N, 125W 1st Ocean Year 21.145 6.118 51N, 131W Summer upwelling index at 51N, 131W 1st Ocean Year 11.221 11.183 87 54N, 134W Summer upwelling index at 54N, 134W 1st Ocean Year -8.575 10.781 57N, 137W Summer upwelling index at 57N, 137W 1st Ocean Year -8.275 9.456 Spring Transition date Date of transition from downwelling to upwelling 1st Ocean Year 144.913 27.510 Willamette Hatchery Releases Count of hatchery releases from the Willamette basin Downstream Migration 4664996 522608.100 Middle Columbia Hatchery Releases Count of hatchery releases from the Middle Columbia Downstream Migration 2363669 256967.900 Upper Columbia Hatchery releases Count of hatchery releases from the Upper Columbia Downstream Migration 1745701 330238.300 Snake River Hatchery Releases Count of hatchery releases from the Snake River Downstream Migration 7207801 2802432 Harbour Seals Abundance of BC coast harbour seals 1st Ocean Year 123562.200 12600.610 Pink Salmon Abundance of Pacific pink salmon 1st Ocean Year 48219231 56062779 Sea Lions Abundance of California and Stellar Sea Lions Adult 45440.640 12494.530 Killer Whales Abundance of Northern (G and R Clans) and Southern Resident Killer Whales Adult 197.536 19.776 3.2.6 Covariate lagging For the covariate analysis, I lagged the data based on the migration timing and life history traits of yearling and subyearling Chinook salmon, as reported in the literature, to ensure that environmental conditions aligned with the periods when fish were present and exposed to each covariate. 88 The covariates were assumed to affect one of three life stages of Chinook salmon: 1) downstream smolt migration (below BVJ or SUJ) and ocean entry, 2) first ocean year, and 3) returning adults (Table 3.2). The ÏSAS estimates were calculated based on juvenile migration year; therefore, no lag was applied to covariates affecting downstream migration (Table 3.3). Covariates affecting the first ocean year can be classified into two categories: predation and species interactions, as well as environmental factors. The predation and interaction covariates associated with the first ocean year had no lag applied; however, the environmental covariates had seasonal lags, within the year of outmigration, applied to each one (Table 3.3). The available age composition data show that most returning adults were age-4 (McCann et al., 2024). Thus, covariates affecting the adult stage were lagged by 2 years for yearlings and 3 years for subyearlings (Table 3.3). 89 Table 3.3. List of covariates and life history type they are assigned to, along with the associated lag applied for the covariate analysis. Covariate Life History Lag Alaska SST Yearling Summer after ocean entry BC SST Subyearling Summer after ocean entry ENSO Both Winter before ocean entry NPGO Both Winter before ocean entry PDO Both Winter before ocean entry Upwelling 48N, 125W Subyearling Summer after ocean entry Upwelling 51N, 131W Subyearling Summer after ocean entry Upwelling 54N, 134W Yearling Summer after ocean entry Upwelling 57N, 137W Yearling Summer after ocean entry Spring Transition Date Both Ocean entry Combined Hatchery Releases Subyearling No lag Willamette Hatchery Releases Yearling No lag Middle Columbia Hatchery Releases Yearling No lag Upper Columbia Hatchery releases Yearling No lag Snake River Hatchery Releases Yearling No lag Harbour Seals Both No lag Pink Salmon Both No lag Sea Lions Yearling 2-year lag Sea Lions Subyearling 3-year lag Killer Whales Yearling 2-year lag Killer Whales Subyearling 3-year lag 3.2.7 Determining top models To evaluate the effect of each covariate on smolt-to-adult survival, I fitted separate linear models for each region (e.g., Snake River, Middle Columbia, Upper Columbia, Willamette), using the untransformed proportion ÏSAS estimate as the response variable and each covariate as a predictor (Posit Team, 2023). Models assumed a Gaussian error structure, meaning residuals were normally distributed with constant variance (Posit Team, 2023). Non-linear relationships between covariates and survival were not considered. While evaluating covariates individually 90 provides insight into their potential influence on survival, this approach does not account for interactions or shared variance among predictors. Testing models that include multiple covariates helps identify the most informative combinations of variables. To determine the most parsimonious models explaining variation in smolt-to-adult survival across release groups, I used the âdredgeâ function from the MuMIn package in R (Posit Team, 2023). This process was conducted separately for the Middle Columbia, Upper Columbia, Snake River, and the Willamette. I fit a linear model for each region, with ÏSAS as the response variable and the covariates as predictors. Due to high correlations among specific covariates, I first generated subset models for each region (Table 3.4). The subset models excluded highly correlated covariates (â¥ 50% correlation); for example, where harbour seal and sea lion abundance were highly correlated, only one was included in any given model (Table 3.4). Each subset model was passed to âdredgeâ to generate all possible combinations. To avoid implausible biological interpretations, I excluded models in which the abundance of sea lions, harbour seals, or killer whales had positive effects, as these covariates represent predation and are assumed to affect survival negatively. I also excluded models where pink salmon abundance had positive effects, as this covariate appeared to have strong negative associations in the univariate modeling. However, pink salmon could have a positive indirect effect on juvenile Chinook salmon survival (e.g., reducing Chinook salmon predation). Therefore, constraining this covariate to be negative may limit the interpretability of the multivariate model conclusions regarding the impacts of pink salmon. The top-ranked model based on AIC was selected from the filtered set, and all models within ÎAIC â¤ 2 were retained. The top models from each subset were then compiled. From this combined model set, I again 91 selected the model with the lowest AIC and retained all models within ÎAIC â¤ 2 as the final supported set for each region. From the final supported set of models, I extracted the AIC values, effect sizes, R², and adjusted R² values from the fitted models. Table 3.4. Pairwise R² values for covariates with high correlations. Values represent the strength of linear relationships between selected covariates within each region. Region Covariates R2 Snake River Harbour Seal vs Sea Lion 0.90 Snake River Harbour Seal vs Killer Whale 0.82 Snake River Harbour Seal vs Pink 0.52 Snake River Sea Lion vs NPGO 0.73 Snake River Sea Lion vs Killer Whale 0.74 Snake River Sea Lion vs Pink 0.55 Middle Columbia Harbour Seal vs Sea Lion 0.91 Middle Columbia Harbour Seal vs Killer Whale 0.83 Middle Columbia Harbour Seal vs Pink 0.50 Middle Columbia Sea Lion vs NPGO 0.71 Middle Columbia Sea Lion vs Killer Whale 0.74 Middle Columbia Sea Lion vs Pink 0.51 Upper Columbia Harbour Seal vs Sea Lion 0.91 Upper Columbia Harbour Seal vs Killer Whale 0.81 Upper Columbia Harbour Seal vs Pink 0.50 Upper Columbia Sea Lion vs NPGO 0.80 Upper Columbia Sea Lion vs Killer Whale 0.73 Upper Columbia Sea Lion vs Pink 0.55 Willamette Harbour Seal vs Sea Lion 0.72 Willamette Harbour Seal vs Killer Whale 0.74 Willamette Harbour Seal vs Pink 0.12 Willamette Sea Lion vs NPGO 0.20 Willamette Sea Lion vs Killer Whale 0.56 Willamette Sea Lion vs Pink 0.16 92 3.3 Results 3.3.1 Effects models Modeling the shared year effect across all regions showed substantial variation in certain years of the time series (Figure 3.2). Some autocorrelation was evident, especially during the first half of the time series (Appendix H.1; Figure 3.2). Strong positive year effects, indicating years with above-average ÏSAS, were observed in 2000, 2008, 2009, 2013, and 2020 (Appendix H.1; Figure 3.2). Conversely, strong negative year effects, reflecting below-average survival, occurred in 2005, 2011, 2015, 2016, 2017, 2018, 2019, and 2022 (Appendix H.1; Figure 3.2). The remaining years did not exhibit a strong effect, as the credible intervals overlapped with zero (Figure 3.2). Figure 3.2. Combined estimated year effect on log-transformed smolt-to-adult return rates from 2000 to 2022 from the Snake River, Middle Columbia, Upper Columbia, and Willamette. Points represent posterior means of year-specific deviations, and vertical lines indicate 90% credible intervals. The dashed line at zero indicates where there is no year effect. 93 A sensitivity analysis was conducted using different priors on the precision to assess the influence of prior assumptions on the estimated year effects. Results showed minimal sensitivity to prior precision: year effect estimates were highly consistent across the base, higher precision, and lower precision priors (Figure 3.3). Credible intervals overlapped substantially under all specifications, indicating that the year effect estimates were stable across changes in prior precision specification (Figure 3.3). Figure 3.3. Sensitivity analysis on the combined estimated year effect of log-transformed smolt-to-adult return rates from 2000 to 2022 from the Snake River, Middle Columbia, Upper Columbia, and Willamette. Points represent posterior means of year-specific deviations from the overall mean, and vertical lines indicate 90% credible intervals. Pink indicates estimates from the base prior on the precision, blue represents a lower precision, and green reflects a higher precision. The dashed horizontal line at zero denotes no year effect. Estimated group effects varied across regions; however, the credible intervals all showed overlap with zero and with the other groups (Figure 3.4). The Snake River exhibited a positive group effect, whereas the Middle Columbia, Upper Columbia, and Willamette showed negative effects (Figure 3.4). 94 Figure 3.4. Estimated group-level effects on log-transformed smolt-to-adult return rates for four regions: Middle Columbia, Snake River, Upper Columbia, and Willamette. Points represent posterior means of group-specific deviations from the overall mean, and vertical lines indicate 90% credible intervals. The dashed line at zero represents no group-level deviation. To evaluate the influence of fish origin, effects were estimated for wild and hatchery fish. Wild-origin fish showed a positive effect, while hatchery-origin fish had a negative effect (Figure 3.5). However, the credible intervals were wide and overlapped both with zero and each other, indicating uncertainty (Figure 3.5). 95 Figure 3.5. Estimated hatchery effect on log-transformed smolt-to-adult return rates. The points represent the posterior means of the hatchery-origin and wild-origin fish, and the vertical lines show the 90% credible intervals. The dashed line at zero represents no difference between hatchery and wild fish. While the overall estimated year effects showed strong patterns in several years, separating them by region revealed more variable and uncertain trends (Appendix H.1; Figure 3.6). Year effects generally aligned with each regionâs ÏSAS estimates, but patterns differed among regions (Appendices G.5âG.8). In the Middle Columbia, the effects were mainly positive in the early 2000s but were negative after 2015 (Figure 3.6). Contrastingly, Upper Columbia year effects were generally negative in the early 2000s (Figure 3.6). However, in both regions, the credible intervals overlapped with zero in all years, indicating uncertainty (Figure 3.6). The Snake River exhibited stronger evidence of interannual variability, with 2008 showing a positive effect and 2015 and 2017 showing negative effects, none of which overlapped with zero (Figure 3.6). In the Willamette, 2008 and 2009 showed the lowest year effects; however, all years were associated with high uncertainty (Appendix H.1; Figure 3.6). In contrast, across the Upper 96 Columbia, Middle Columbia, and Snake River, 2008 and 2009 showed above-average estimates (Appendix H.1; Figure 3.6). Figure 3.6. Estimated year-specific effects on Chinook salmon's log-transformed smolt-to-adult survival (ÏSAS) for four regions: Middle Columbia River Basin, Snake River, Upper Columbia River Basin, and Willamette River Basin. Points represent the posterior means of the group-by-year interaction terms, and vertical lines denote 90% credible intervals. A dashed horizontal line at zero indicates no year effect. Values above or below zero reflect years when survival was higher or lower than expected after accounting for other covariates in the model. 97 3.3.2 Covariate effects in the top models Relationships between ÏSAS estimates and individual covariates showed linear relationships consistent across regions, though some regions exhibited steeper slopes (Figure 3.6). Survival was negatively associated with the abundance of sea lions, resident killer whales, and pink salmon across all regions (Figure 3.7). Similarly, oceanographic indices such as the PDO and ENSO phases exhibited negative associations with survival, whereas the NPGO showed a positive association (Figure 3.7). Alaska sea surface temperature and the timing of the spring transition were also negatively related to survival (Figure 3.7). Upwelling indices exhibited generally flat trends, indicating a weak association (Figure 3.7). Hatchery releases varied by region: the Snake River showed a slightly negative trend, the Middle and Upper Columbia regions showed neutral trends, and the Willamette exhibited a positive trend (Figure 3.7). 98 Figure 3.7. Relationships between smolt-to-adult survival (ÏSAS) of Chinook salmon and 15 standardized covariates across four regions: Middle Columbia, Snake River, Upper Columbia, and Willamette. Each panel displays a scatterplot of ÏSAS estimates versus a single covariate, with fitted linear trend lines colored by region. 99 The estimated covariate effects on ÏSAS showed similar directional trends across regions, though effect sizes varied (Figure 3.8). Sea lion, pink salmon, and killer whale abundances were negatively associated with survival in all four regions, with credible intervals excluding zero except in the Upper Columbia (Figure 3.8). PDO conditions also showed negative effects, but overlapped with zero in the Middle Columbia and Willamette (Figure 3.8). ENSO conditions had a negative association with survival, although only the Snake River showed a credible interval that did not overlap with zero (Figure 3.8). NPGO conditions were positively associated with survival in all regions, though this effect overlapped with zero in the Upper Columbia and Willamette (Figure 3.8). Both Alaska sea surface temperature and spring transition timing showed negative associations with survival, but with intervals overlapping zero across regions (Figure 3.8). Both upwelling indices had weak negative effects in the Middle Columbia and Snake River (Figure 3.8). In contrast, the 57°N, 137°W index had a positive effect in the Upper Columbia and Willamette, albeit with credible intervals overlapping zero (Figure 3.8). Hatchery release metrics affecting their respective regions were more variable: Snake River hatchery releases showed a strong negative effect, and the Middle Columbia hatchery releases showed a weak negative effect (Figure 3.8). Contrastingly, the Upper Columbia hatchery releases showed a positive effect, and the Willamette hatchery releases showed no effect (Figure 3.8). 100 Figure 3.8. Estimated effects of environmental and anthropogenic covariates on smolt-to-adult survival (ÏSAS) of Chinook salmon across four regions: Middle Columbia, Snake River, Upper Columbia, and Willamette. Points represent the estimated effect sizes from standardized linear models for each covariate, and horizontal lines show associated 90% credible intervals. Covariates were standardized prior to modeling to allow direct comparison of effect magnitude. Dashed vertical lines at zero denote no effect. 101 For the Snake River, seven models were within 2 AIC units of the top-ranked model; the highest-ranked model, with an AIC of -1379.89 (adj. R2 = 0.357), included harbour seals, ENSO, PDO, spring transition, upwelling at 54°N, 134°W, and hatchery releases (Appendix I.3; Table 3.5). All top models included PDO, ENSO, spring transition, and upwelling index at 54°N, 134°W (Appendix I.3; Table 3.5). Harbour seal abundance appeared in four of the top models, and pink salmon abundance was included in two of the top models (Appendix I.3; Table 3.5). Hatchery releases appeared in seven of the top models (Appendix I.3; Table 3.5). Within the Snake River, the adjusted R2 values ranged from 0.351 to 0.361 across all top models (Appendix I.3). Within the Snake River, coefficient estimates across covariates were generally similar in magnitude, though a few showed slightly stronger associations (Figure 3.9). The Snake River hatchery release covariate exhibited the largest absolute estimates, ranging from -0.00384 to -0.00351 across the three top models (Figure 3.9). PDO and Spring transition also showed consistently high-magnitude effects, with coefficient estimates ranging from -0.00289 to -0.00180 and -0.00314 to -0.00245, respectively (Figure 3.9). 102 Figure 3.9. Distribution of coefficient estimates from Snake River top models. Each panel is grouped by covariate, with jittered points on the y-axis representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. 103 Table 3.5. Top models from the Snake River. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). Model Included Predictors AIC 1 Harbour seal + ENSO + PDO + Spring Transition + Upwelling 54N, 134W + Hatchery Releases -1379.89 2 Harbour seal + ENSO+ PDO + Alaska SST + Spring Transition + Upwelling 54N, 134W + Hatchery Releases -1379.81 3 Harbour seal + ENSO + PDO + Alaska SST + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -1379.16 4 Pink + ENSO + PDO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W -1379.15 5 ENSO + PDO + Spring Transition + Upwelling 54N, 134W + Hatchery Releases -1378.92 6 Pink + ENSO + PDO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -1378.47 7 Harbour seal + ENSO+ PDO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -1378.45 8 ENSO + PDO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -1378.07 Model selection for the Middle Columbia yielded 19 models within 2 AIC of the top-ranked model (Appendix I.4; Table 3.6). The best model included pink salmon abundance and the PDO index (AIC = â496.13, adj. R2 = 0.0717; Appendix I.4; Table 3.6). Pink salmon abundance was the most consistently included predictor, appearing in 15 of the 20 top models (Appendix I.4; Table 3.6). PDO was also frequently retained, as were the upwelling indices at both 54°N, 134°W and 57°N, 137°W (Appendix I.4; Table 3.6). Hatchery releases, spring transition timing, and NPGO appeared less consistently and only in more complex models (Appendix I.4; Table 3.6). Sea lion abundance appeared in just one model (Appendix I.4; Table 3.6). Within the Middle Columbia, the adjusted R² values for the top models were lower compared to those from the Snake River, ranging from 0.0405 to 0.0795 (Appendix I.4). Within the Middle Columbia region, coefficient estimates were generally similar in magnitude across covariates, though a few exhibited relatively stronger associations (Figure 104 3.10). The Upwelling Index at 54°N, 134°W, and the NPGO showed the largest absolute effect sizes, with estimates ranging from -0.0041 to -0.00375 and 0.00298 to 0.0053, respectively. In contrast, the ENSO covariate showed no discernible effect (Figure 3.10). Figure 3.10. Distribution of coefficient estimates from Middle Columbia top models. Each panel is grouped by covariate, with jittered points representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. 105 Table 3.6. Top models from the Middle Columbia. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). Model Included Predictors AIC 1 Pink + PDO -496.13 2 Pink + Upwelling 54N, 134W + Upwelling 57N, 137W -495.20 3 NPGO + Upwelling 54N, 134W + Upwelling 57N, 137W -495.11 4 Pink + NPGO + Upwelling 54N, 134W + Upwelling 57N, 137W -494.95 5 NPGO + PDO -494.93 6 Pink + PDO + Spring Transition -494.79 7 Pink + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -494.78 8 PDO + Spring Transition -494.72 9 Pink -494.63 10 Pink + PDO + Upwelling 54N, 134W -494.59 11 PDO -494.53 12 Sea Lions + PDO -494.53 13 Pink + Upwelling 54N, 134W -494.42 14 Pink + NPGO + PDO -494.37 15 NPGO -494.26 16 Pink + Spring Transition -494.22 17 Pink + PDO + Upwelling 57N, 137W -494.20 18 Pink + PDO + Hatchery Releases -494.20 19 Pink + PDO + Alaska SST -494.17 20 Pink + ENSO + PDO -494.13 For the Upper Columbia, there were nine models within 2 AIC of the top model (Appendix I.5; Table 3.7). The best-performing model, with an AIC of -615.87 (adj. R2 = 0.281), included pink salmon, ENSO conditions, spring transition, both upwelling indices (54°N, 134°W and 57°N, 137°W), and hatchery releases (Appendix I.5; Table 3.7). Pink salmon abundance, both upwelling indices, and hatchery releases were in all top models (Appendix I.5; Table 3.7). ENSO and spring transition timing appeared in nine and six of the top models, respectively (Appendix I.5; Table 3.7). Alaska sea surface temperatures, PDO, and NPGO were included in a smaller number of models (Appendix I.5; Table 3.7). The R2 values for the top models from the Upper Columbia ranged from 0.253 to 0.288 (Appendix I.5). 106 Within the Upper Columbia, coefficient estimates were generally similar in magnitude across covariates (Figure 3.11). The Upwelling Indices at 54°N, 134°W, and at 57°N, 137°W showed the largest absolute effect sizes, with estimates ranging from -0.00544 to -0.00426 and 0.003048 to 0.004319, respectively (Figure 3.11). Figure 3.11. Distribution of coefficient estimates from Upper Columbia top models. Each panel is grouped by covariate, with jittered points representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. 107 Table 3.7. Top models from the Upper Columbia. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). Model Included Predictors AIC 1 Pink + ENSO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -615.87 2 Pink + ENSO + Alaska SST + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -615.72 3 Pink + ENSO+ Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -615.24 4 Pink + ENSO+ Alaska SST + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.92 5 Pink + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.43 6 Pink + NPGO + ENSO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.14 7 Pink + ENSO + PDO + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.14 8 Pink + NPGO + ENSO+ Alaska SST + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.11 9 Pink + NPGO + ENSO+ Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.08 10 Pink + ENSO + PDO + Alaska SST + Spring Transition + Upwelling 54N, 134W + Upwelling 57N, 137W + Hatchery Releases -614.04 In the Willamette River, 19 models were within 2 AIC of the best-performing model (Appendix I.6; Table 3.8). The top model included only pink salmon abundance (AIC = â457.54, adj. R2 = 0.0946), and in total, pink salmon appeared in 7 of the top models (Appendix I.6; Table 3.8). Killer whales appeared in 9 of the top models, and sea lions in 4 (Appendix I.6; Table 3.8). Alaska SST was the environmental covariate that appeared most frequently, occurring in 10 of the top models (Appendix I.6; Table 3.8). Within the Willamette, the R2 values from the top models ranged from 0.0946 to 0.103 (Appendix I.6). Within the Willamette, coefficient estimates varied in magnitude across covariates (Figure 3.12). The sea lion and pink salmon covariates showed the largest absolute effect sizes, 108 with the estimates ranging from -0.00198 to -0.00176 and -0.00203 to -0.00187, respectively (Figure 3.12). Figure 3.12. Distribution of coefficient estimates from Willamette top models. Each panel is grouped by covariate, with jittered points representing individual model estimates for that covariate along the x-axis. The horizontal solid lines represent 90% credible intervals. The vertical dashed line at zero indicates no effect. 109 Table 3.8. Top models from the Willamette River. Models were generated using dredge and filtered to exclude combinations with positive predator coefficients. Models are ranked by AIC, with all listed models falling within 2 AIC units of the top filtered model (Model 1). Model Included Predictors AIC 1 Pink -457.54 2 Killer Whales + Alaska SST -457.20 3 Killer Whales -457.12 4 Killer Whales + Alaska SST + Hatchery Releases -456.97 5 Sea Lions -456.58 6 Sea Lions + NPGO + Alaska SST + Hatchery Releases -456.43 7 Sea Lions + Alaska SST + Hatchery Releases -456.42 8 Killer Whales + Spring Transition -456.40 9 Killer Whales + PDO + Alaska SST -456.30 10 Killer Whales + NPGO + Alaska SST -456.11 11 Pink + Hatchery Releases -455.97 12 Killer Whales + Upwelling 54N, 134W -455.87 13 Pink + Spring Transition -455.73 14 Pink + Upwelling 54N, 134W -455.65 15 Killer Whale + Alaska SST + Spring Transition -455.62 16 Pink + ENSO -455.57 17 Pink + PDO -455.56 18 Sea Lions + NPGO + Alaska SST -455.56 19 Pink + Alaska SST -455.55 20 Killer Whales + NPGO + Alaska SST + Hatchery Releases -455.55 Across regions, several covariates showed relatively consistent associations with survival (Table 3.9). Alaska SST had a negative association in the Snake and Upper Columbia, mixed in the Willamette, and positive in the Middle Columbia (Table 3.9). ENSO showed a positive association in the Snake, Middle Columbia, and Upper Columbia, but a negative association in the Willamette (Table 3.9). PDO was negative in the Snake and Middle Columbia (Table 3.9). Upwelling indices showed opposite patterns depending on location: upwelling at 54°N, 134°W was generally negative, while upwelling at 57°N, 137°W was consistently positive (Table 3.9). Hatchery releases were positively associated with survival in the Middle Columbia and Upper Columbia but tended to be negative elsewhere (Table 3.9). Harbour seal density was only associated with survival in the Snake River, and killer whale abundance was only associated with 110 survival in the Willamette (Table 3.9). Finally, spring transition timing was negative across all regions (Table 3.9). Table 3.9. Direction and frequency of covariate effects from top multivariate model outputs across regions (Snake River, Middle Columbia, Upper Columbia, Willamette). The year range of each region's ÏSAS estimates are shown in the top rows. Values indicate the number of times a covariate appeared, with the sign of the effect shown in parentheses (positive [+], negative [â], or both directions [both]). Snake River (2000-2022) Middle Columbia (2000-2022) Upper Columbia (2000-2022) Willamette (2002-2016) Alaska SST 2/8 [-] 1/20 [+] 4/10 [-] 10/20 [both] ENSO 8/8 [+] 1/20 [-] 9/10 [+] 1/20 [+] NPGO 0/8 5/20 [+] 3/10 [both] 4/20 [-] PDO 8/8 [-] 12/20 [-] 2/10 [both] 2/20 [+] Upwelling 54N, 134W 8/8 [-] 6/20 [-] 10/10 [-] 2/20 [both] Upwelling 57N, 137W 5/8 [+] 5/20 [+] 10/10 [+] 0/20 Hatchery releases 7/8 [-] 2/20 [+] 10/10 [+] 5/20 [-] Harbour Seals 4/8 [-] 0/20 0/10 0/20 Pink 2/8 [-] 14/20 [-] 10/10 [-] 7/20 [-] Sea lions 0/8 1/20 [-] 0/10 4/20 [-] Killer whales 0/8 0/20 0/10 9/20 [-] Spring transition 8/8 [-] 3/20 [-] 6/10 [-] 3/20 [-] 3.4 Discussion 3.4.1 Effects models The global effects models revealed a common, shared year effect influencing the spring- and summer-run Chinook salmon (Oncorhynchus tshawytscha) smolt-adult survival rates in the Columbia River Basin (Figure 3.2). Between 2000 and 2022, 2000 had the highest estimate, while 2017 showed the lowest estimate (Appendix H.1; Figure 3.2). These findings align with those of Berkman et al. (2021), who found that the marine survival of Chinook salmon from the Stikine River and Chilkat River in Southeast Alaska was high in 2000. Several factors may influence interannual variability in salmon survival; however, previous research has identified correlations with large-scale climate indices and local-scale measures of ocean conditions (Hertz 111 et al., 2016). Conditions in 2000 were beneficial for salmon survival, with favorable PDO, NPGO, and ENSO events, an early spring transition date, moderate upwelling at 54°N 134°W, and strong upwelling at 57°N 137°W (Appendix I.2). In contrast, 2017 showed mixed signals, while the PDO and ENSO were neutral, the spring transition, NPGO and both upwelling indices were unfavorable (Appendix I.2). Environmental conditions in 2017 were not uniformly unfavorable for survival; rather other factors likely contributed to the strongly negative estimate that year. However, disaggregating the year effect by river region revealed variability (Appendix G.5-G.8; Appendix H.1; Figure 3.2; Figure 3.6). For instance, the lowest estimates from the Snake River, Middle Columbia, Upper Columbia, and Willamette occurred in 2017, 2022, 2005, and 2009, respectively (Appendix H.1; Figure 3.6). Interestingly, the low estimate from the Willamette was not apparent in the three other regions, which all showed an above-average year effect (Appendix G.5 - G.8; Figure 3.6). This highlights the importance of stock-specific monitoring, as year-to-year variability appears to differ between the regions examined (Figure 3.6). There was a lack of close correspondence between the global common shared year effects and the region-specific year effects. In the global common shared year effect, the highest estimate was in 2000 (Figure 3.2). However, when split by region, only the Middle Columbia had its highest estimate in 2000 (Figure 3.6). In contrast, the highest estimates for the Snake River, Upper Columbia, and Willamette were in 2008, 2008, and 2011, respectively (Figure 3.6). The observed differences in trends could stem from the difference in model structure. While the global model estimates a single shared trend averaged across all regions, the regional model allows year effects to deviate independently between the regions. Additionally, differences in sample size and data quality could contribute to this divergence. 112 3.4.2 Individual linear models The covariate analysis showed strong negative associations between ÏSAS estimates and the abundances of sea lions, pink salmon, and killer whales (Figure 3.8). In the mid-20th century, multiple protections were implemented to recover the Southern Resident and Northern Resident killer whale and pinniped populations (Chasco et al., 2017). However, these protections present trade-offs, as the recovered populations are predators of Chinook salmon (Chasco et al., 2017). For example, the estimated biomass of Chinook salmon consumed by marine mammals in the Salish Sea increased from 6,100 (1975) to 15,200 (2015) metric tons following the implementation of these protections (Chasco et al., 2017). The increase in predator abundance and associated predation pressure likely contributes to the negative associations observed between the predator covariates (e.g., sea lions and killer whales) and Chinook salmon survival. In addition to predation, interactions among salmon species may also reduce the survival of Chinook salmon (Ruggerone & Irvine, 2018). High abundances of pink salmon in the northern North Pacific Ocean have been linked to large-scale shifts in marine food webs, including reduced zooplankton biomass and altered phytoplankton dynamics (Batten et al., 2018; Springer & van Vliet, 2014). These trophic changes can reduce prey availability for other salmon species (Ruggerone et al., 2023). Furthermore, although uncertain, in offshore areas of the northern North Pacific Ocean, there could be some spatial overlap between adult pink salmon and juvenile Chinook salmon abundances (Ruggerone et al., 2023). In these offshore areas, adult pink salmon may outcompete juvenile Chinook salmon (Ruggerone et al., 2023). In years when pink salmon were 40 times more abundant (odd years), Chinook salmon consumed 72% less squid and 44% less fish compared to even years (Ruggerone et al., 2023). Meanwhile, pink salmon consumed 113 32% less squid and 25% less fish (Ruggerone et al., 2023). These findings suggest that pink salmon may outcompete Chinook salmon for high-energy prey when prey availability is limited (Ruggerone et al., 2023). The aforementioned factors could contribute to the negative association between pink salmon abundance and Chinook salmon ÏSAS estimates in this study. However, the strong negative associations should be interpreted with caution, as the spatial overlap between these two species is uncertain. In addition to predation and species interactions, variations in the marine survival of Chinook salmon correspond with ocean conditions. Cold ocean phases are generally more suitable for Chinook salmon, whereas warm phases are associated with reduced survival, often mediated by shifts in ocean productivity (Peterson et al., 2006). The Pacific Decadal Oscillation, which reflects patterns in North Pacific SST, is one such indicator (Peterson et al., 2006). In late 1998, the PDO entered a four-year cold phase, followed by a three-year warm phase (Peterson et al., 2006). The 1998 cool phase coincided with an increase in spring Chinook counts at Bonneville Dam, and in 2000, ÏSAS estimates were their highest levels in the time series, potentially reflecting these favorable conditions (Peterson et al., 2006). However, during the time series, warm or neutral PDO phases predominated, likely contributing to the overall negative association between PDO and ÏSAS observed in the model results (Figure 3.8). Similarly, ENSO exhibits variation between La Niña (cool) and El Niño (warm) phases (Peterson et al., 2006). El Niño events have been associated with lower ÏSAS due to their impacts on ocean temperature and productivity (Peterson et al., 2006). Because either neutral or El Niño conditions characterized most years during the study period, this likely explains the negative association of ÏSAS estimates with ENSO in the modeling results (Figure 3.8). 114 Building on these broader climate patterns, more localized ocean conditions also influenced survival. Alaska SST was negatively associated with ÏSAS for Columbia River Basin spring and summer Chinook salmon stocks, likely due to the persistent marine heatwave in the Gulf of Alaska that resulted in increased water temperatures (Quan et al., 2018). This region has experienced warmer temperatures since 2012, with 2015 and 2016 recording the two warmest SSTs on record (Quan et al., 2018). These elevated temperatures can alter food web structure and reduce prey availability for juvenile salmon during their early marine residence, which can impair growth and increase mortality, contributing to the observed negative association with ÏSAS (Riddell et al., 2018; Quan et al., 2018). Additionally, the timing of the spring transition, a shift from winter downwelling to summer upwelling, was also negatively correlated with ÏSAS (Peterson et al., 2006). Because upwelling drives nutrient-rich waters and primary production, the timing of the spring transition influences ecosystem productivity (Peterson et al., 2006). An earlier transition supports zooplankton production. In recent years, particularly after 2014, the spring transition has tended to occur later. A later phytoplankton bloom can reduce recruitment of key zooplankton species, potentially contributing to the observed negative association with ÏSAS estimates. In contrast to the negative effects of the other covariates, NPGO was one of the few covariates positively associated with ÏSAS in the modeling results for Columbia River Basin spring and summer run Chinook salmon stocks (Figure 3.8). The NPGO reflects changes in ocean circulation and salinity that are linked to nutrient availability and primary production in the California Current and Gulf of Alaska (Di Lorenzo et al., 2008). The positive association suggests that during the time series since 2000, there were years with stronger NPGO signals, which may have supported increased survival (Di Lorenzo et al., 2008). 115 Hatchery programs have been increasingly implemented to supplement declining fish populations, particularly with advances in hatchery propagation (Levin et al., 2001). However, the ecological effects of large-scale hatchery production are complex and can vary depending on several factors (Chilcote et al., 2011; Levin et al., 2001; NMFS, 2022). From a genetic and ecological perspective, hatchery-origin fish may pose risks to wild populations through competition and reduced fitness (Chilcote et al., 2011). However, from a reproductive standpoint, some argue that hatcheries can help support population persistence under certain conditions (Chilcote et al., 2011). Some studies, for example, have found that ÏSAS has been positively associated with the abundance of hatchery salmonid releases, speculating that predation risk may be decreased when juvenile salmonid abundance is higher (Sobockinski et al., 2021; Courter et al., 2022). In the Snake River, I found a strong negative association between hatchery releases and ÏSAS (Figure 3.8). In the Middle Columbia, effects were also negative but overlapped with zero (Figure 3.8). These findings align with some studies, which have shown reduced Chinook salmon survival in years with high hatchery releases, particularly when marine conditions are unfavorable (e.g., Levin et al., 2001). Conversely, hatchery releases in the Upper Columbia were positively associated with ÏSAS, although the confidence intervals overlapped with zero (Figure 3.8). This may reflect improvements in hatchery practices in this region, as the Upper Columbia had the lowest numbers of hatchery releases (NMFS, 2022). It is also possible that, due to their longer migration distance, fish from the Upper Columbia potentially have a larger size at ocean entry (Figure 3.1). Larger smolts may be better equipped to survive and compete in the marine environment, potentially mitigating density-dependent effects (Duffy & Beauchamp, 2011). In the Willamette, hatchery effects appeared neutral, possibly due to the limited number of release groups available for comparison. 116 In this study, I employed univariate modeling to explore relationships between survival rates and hypothesized covariates. While univariate models can help identify possible associations, they are inherently limited. One limitation is their inability to account for covariation among predictors. As a result, univariate models may misleadingly strongly attribute variation in survival to a single factor, when the true variation could result from a combination of drivers. 3.4.3 Multivariate models The model selection results revealed regional differences explaining variation in ÏSAS, as no single covariate appeared in the top models across all regions. This difference is consistent with the idea that behavioral traits, stock-specific migration routes and timing, habitat conditions, or genetic components can lead to salmon populations responding differently to environmental drivers (Crozier & Zabel, 2006). For example, the top models for Chinook salmon originating from the Snake River explained 35.1% to 36.1% of the variation in ÏSAS and consistently included the PDO, ENSO, spring transition, and the upwelling index at 54°N, 134°W (Appendix I.3; Table 3.9). Within the Snake River survival estimates, the PDO and Spring transition covariates showed consistently high-magnitude effects (Figure 3.9). These findings suggest that broad-scale environmental conditions have a strong influence on ÏSAS. In contrast, the top models for Chinook salmon originating from the Upper Columbia explained 25.3% to 28.8% of the variation in ÏSAS and included pink salmon abundance, both upwelling indices, and hatchery releases (Appendix I.5; Table 3.9). Both upwelling indices also showed the largest magnitude in effect sizes (Figure 3.11). These results suggest that localized factors have a stronger influence on survival for the Upper Columbia. The different covariates appearing in the top models 117 between these two regions highlight the importance of considering population-specific responses to environmental and ecological drivers (Table 3.9). By considering all reasonable combinations of covariates, multivariate modeling provides a more robust framework to test alternative hypotheses about the drivers of variation in ÏSAS. This approach enables a more accurate assessment of interactive effects among covariates. Still, limitations remain; if the time series is short relative to the number of predictors, or if important covariates are omitted or poorly measured, models may yield misleading conclusions. 3.4.4 Evaluating Drivers of Smolt-to-Adult Survival in a Multi-Stock System Previous research has shown that evaluating multiple potential drivers across a broad range of stocks can better disentangle complex survival patterns than analyses with narrower stock coverage (Sobocinski et al., 2021). This is especially important in systems like the Columbia River Basin, where environmental conditions, management actions, and life-history traits vary across space and time. Given the limited number of release groups from the Willamette River, I incorporated additional release groups from other regions of the Columbia River Basin to strengthen the analysis and improve the interpretability of the results. Assessing survival across multiple stocks also allowed for a broader examination of how different populations respond to shared drivers. This comparative, multi-stock approach helps identify both widespread and region-specific influences on survival, providing a stronger foundation for understanding population dynamics. 118 3.4.5 Limitations Several limitations should be considered when interpreting the results of this chapter. First, the time series used in the analysis was relatively short, limiting the ability to detect long-term or historical trends. For instance, harbour seal abundance declined throughout the time series, failing to capture the broader historical increase that occurred after their protection (Appendix I.2; Chasco et al., 2017). Consequently, individual linear model predictions showed a mostly positive relationship between harbour seal abundance and ÏSAS estimates, which does not accurately reflect the expected ecological relationship, as they are known predators of juvenile salmonids (Chasco et al., 2017; Figure 3.8). Although harbour seal abundance appeared in four of the top multivariate models from the Snake River, it is possible that this covariate could have been included in models from other regions had the time series captured a period of increasing abundance, as was the case for the sea lion and killer whale covariates (Appendix I.2). Second, the effect of pink salmon abundance was constrained to be negative when filtering the multivariate models. In reality, the effect of pink salmon on Chinook could be positive; for example, high pink salmon abundance may reduce predation pressure. Additionally, while pink salmon emerged as a top covariate in many models, Columbia River Chinook and pink salmon may not have extensive spatial overlap. Greater overlap likely occurs in the Bering Sea with Chinook populations originating from further North; however, this is an area that Columbia River Chinook do not typically inhabit. Consequently, the influence of this covariate should be interpreted with caution as it may overestimate the interaction effects between these two species. 119 Another limitation is that data availability for the Willamette River system was limited relative to other regions. The Willamette had fewer years of available data and fewer release groups, which contributed to greater uncertainty in model estimates and limited the strength of conclusions for this region. Additionally, I was unable to include subyearling releases from the Willamette River Basin due to a lack of sufficient data. After determining which releases would reach the ocean as subyearlings, I was left with nine release groups, which was not enough data to perform further statistical analysis. As a result, this chapter does not assess subyearling life-history types, which are likely to differ from those of yearlings. Finally, although the top models explained some variation, the highest adjusted R² value was 36.1%, indicating that a substantial portion of the observed variations in survival remains unexplained (Appendix I.3). Studying Chinook salmon smolt-to-adult survival is complex, as it is shaped by freshwater, estuarine, and marine processes. Additional factors not included in this analysis likely play important roles in influencing survival. For example, estuary-specific conditions, changes in predation rates from other predators, such as piscivorous birds or salmon sharks, physiological traits, size at entry, or cumulative stressors could further explain variation in ÏSAS (Evans et al., 2016; Weitkamp & Garcia, 2022). 3.5 Conclusion This chapter explored factors affecting Chinook salmon smolt-to-adult survival across the Snake, Middle Columbia, Upper Columbia, and Willamette River systems. Shared year effects revealed changes in certain years; however, regional analyses showed different trends and greater uncertainty between regions. Covariate analyses indicated that sea lions, killer whales, 120 and pink salmon are correlated with lower ÏSAS for spring and summer run Chinook salmon stocks in the Columbia River Basin. Large-scale oceanographic indices, such as the PDO and ENSO, were generally negatively correlated, while the NPGO was positively correlated with ÏSAS. Although the association of ÏSAS with these covariates was consistent across regions, their importance in the top models varied. These findings highlight potential stock-specific responses to a range of covariates affecting Chinook salmon survival. Thus, effective conservation efforts may benefit from identifying drivers and considering how populations from different regions respond to them. 121 Chapter 4: Conclusion 4.1 Summary of Key Findings Despite the implementation of many conservation measures, multiple Chinook salmon populations remain listed as threatened under the US Endangered Species Act, and many of these populations continue to persist at low levels (Nehlson et al., 1991; Riddell et al., 2018). With the lack of recovery, much research on the survival of different populations has been conducted (Duffy & Beauchamp, 2011; Cunningham et al., 2018; Sobocinski et al., 2021; Wilson et al., 2022). However, because Chinook salmon have complex life histories and long migrations, their populations have been hypothesized to be constrained by both freshwater and marine factors (Riddell et al., 2018; Quinn, 2018). Additionally, populations can respond differently to changing conditions and, therefore, insights gained from one region may not be directly transferable to another (Riddell et al., 2018; Quinn, 2018). The goal of this thesis was to estimate survival rates for spring-run Chinook salmon in the relatively data-limited Willamette River system and assess how time trends in them compare with those in other regions of the Columbia River Basin. Chapter Two applied a Bayesian Cormack-Jolly-Seber model to estimate release-smolt survival (ÏRSS) and smolt-to-adult survival (ÏSAS) rates for 143 different Passive Integrated Transponder (PIT) tag release groups of yearling and subyearling Chinook salmon in the Willamette River. The results showed that estimates of ÏSAS consistently fell below the 2% minimum smolt-to-adult return benchmark often referenced for Columbia Basin recovery, indicating that survival rates remain below the management target. The estimates of ÏSAS varied over the years, with most Willamette River release groups showing no indication of consistently 122 strong increasing or decreasing trends. Regarding ÏRSS, estimates varied across sub-basins, with the lowest estimated value at release sites being those associated with the longest migrations through multiple dams. These results suggest that hydrosystem configuration and migration distance may reduce release-smolt survival rates, which could impact overall returns, particularly during years of poor marine conditions, where smolt-to-adult survival rates could be negatively impacted. Chapter Three expanded the analysis by including published ÏSAS estimates for spring- and summer-run Chinook salmon from three other regions in the Columbia Basin (e.g., Snake River, Middle Columbia, Upper Columbia). The results suggested that there was a common shared year effect behind the observed interannual variation. However, further analyses revealed differing trends between the four regions, suggesting that the population groups do not respond uniformly to shared environmental drivers. Covariate analyses identified several factors negatively associated with ÏSAS, including increasing abundances of sea lions, killer whales, and pink salmon, implicating both predation and competition in the marine environment. Oceanographic indices such as Alaska sea surface temperature, spring transition date, upwelling at 54N, 134W, the Pacific Decadal Oscillation, and El Niño Southern Oscillation were generally linked to lower survival rates. In contrast, the North Pacific Gyre Oscillation was positively associated. Although these relationships were consistent in direction across regions, estimates of the relative magnitude of their effects differed between the four regions. No single factor emerged as a dominant driver across all regions, highlighting potential stock-specific responses of Chinook salmon to environmental and ecological stressors. This result is supported by previous research, which has found differences in smolt-to-adult survival rates among Chinook 123 salmon populations (Rechisky et al., 2013; Trudel et al., 2009; Welch et al., 2020). Populations of Chinook salmon appear to have consistent migration patterns across years; however, they may respond differently to ocean conditions (Rechisky, 2013). 4.2 Limitations and Future Directions One limitation of the covariate study is that it focused exclusively on yearling spring- and summer-run Chinook salmon smolts. While this provided consistency for comparisons across the Columbia Basin, it limits applicability to subyearling or fall-run life histories, which follow different migration timing and routes and thus could have different time trends in smolt-to-adult survival rates (Riddell et al., 2018; Quinn, 2018). Another limitation was that the ÏSAS time series were relatively short (e.g., 2000-2022), restricting the ability to detect long-term trends. This was particularly problematic for the harbour seal covariate, as their population increase occurred before the ÏSAS time series from this study began. As a result, the available data only captured a decline in harbour seal abundance. This likely explains why univariate modeling showed a positive association with harbour seal abundance, despite its role as a predation covariate. Additionally, harbour seal predation may have appeared in the Snake River multivariate model simply because it was the most robust dataset. With a longer time series or larger datasets in other regions, harbour seal abundance might have emerged as a more consistent predictor across models. The short time series also contributed to collinearity among covariates. For example, sea lion and harbour seal abundances were highly correlated, preventing their inclusion in the same model and limiting the ability to determine their effects on ÏSAS. Another limitation of this work was that survival rate estimates for many release groups in the Willamette River were imprecise 124 due to small release sizes and sparse detection histories, which reduced the statistical power to detect covariate effects or make strongly informative regional comparisons. While challenges remain, this work contributes to a growing body of research aimed at understanding and addressing the complex drivers of Chinook salmon survival rates in the Willamette and other watersheds within the Columbia River system. 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Area Release group (Year) Parameter Point estimate Upper CI McKenzie RKM 90.008-90.039 (2011) ÏRSS 1.17 1.26 McKenzie North Fork (2009) ÏRSS 1.15 1.40 Middle Fork Dexter Dam Tailrace (2012) ÏRSS 1.12 1.32 Middle Fork Hills Creek Head of Reservoir (2012) ÏRSS 1.14 1.22 North Santiam Big Cliff Tailrace RKM 19.067 (2016) ÏRSS 1.34 2.33 North Santiam Detroit Head of Reservoir RKM 19.093 (2016) ÏRSS 1.16 1.33 South Santiam RKM 19.000 â 19.032 (2006) ÏRSS 1.28 1.97 Upper Willamette Upper Willamette (2007) ÏRSS 1.11 1.18 140 Appendix B B.1 Ratios of posterior to prior precision for each release group for smolt-adult-survival (ÏSAS) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. Ratios of less than 1.5 are bolded, and ratios between 1.5 and two are bolded and in italics. Area Release Group Year Ratio McKenzie Horse Creek 2011 1.53 McKenzie Horse Creek 2012 1.80 McKenzie Horse Creek 2013 1.96 McKenzie Horse Creek 2014 1.03 McKenzie Horse Creek 2015 1.72 McKenzie McKenzie River(RKM 0-56) 2002 2.05 McKenzie McKenzie River(RKM 0-56) 2003 2.15 McKenzie McKenzie River(RKM 0-56) 2004 2.05 McKenzie McKenzie River(RKM 0-56) 2005 2.15 McKenzie McKenzie River(RKM 0-56) 2007 2.15 McKenzie McKenzie River(RKM 0-56) 2008 2.75 McKenzie McKenzie River(RKM 0-56) 2009 2.48 McKenzie McKenzie River(RKM 0-56) 2011 4.72 McKenzie McKenzie River(RKM 0-56) 2012 2.75 McKenzie McKenzie River(RKM 0-56) 2013 2.15 McKenzie McKenzie River(RKM 0-56) 2014 3.24 McKenzie McKenzie River(RKM 0-56) 2015 3.88 McKenzie McKenzie Hatchery 2002 5.06 141 McKenzie McKenzie Hatchery 2003 1.80 McKenzie McKenzie Hatchery 2004 3.06 McKenzie McKenzie Hatchery 2005 4.72 McKenzie McKenzie Hatchery 2006 2.05 McKenzie McKenzie Hatchery 2008 1.18 McKenzie McKenzie Hatchery 2009 2.15 McKenzie McKenzie Hatchery 2010 3.64 McKenzie McKenzie River Bypass 2002 3.64 McKenzie McKenzie River Bypass 2003 1.27 McKenzie McKenzie River Bypass 2004 4.13 McKenzie McKenzie River Bypass 2005 4.13 McKenzie McKenzie River Bypass 2006 1.88 McKenzie McKenzie River Bypass 2007 1.18 McKenzie McKenzie River Bypass 2008 2.15 McKenzie McKenzie River Bypass 2009 2.25 McKenzie McKenzie River Bypass 2010 3.88 McKenzie McKenzie River Bypass 2011 2.61 McKenzie McKenzie River Bypass 2012 1.22 McKenzie McKenzie River Bypass 2013 2.90 McKenzie McKenzie River Bypass 2013 4.72 McKenzie McKenzie River Bypass 2014 3.24 McKenzie McKenzie River Bypass 2015 2.25 142 McKenzie McKenzie River(RKM 57-90) 2010 1.59 McKenzie McKenzie River(RKM 57-90) 2012 1.07 McKenzie McKenzie River(RKM 57-90) 2013 1.80 McKenzie McKenzie River(RKM 57-90) 2014 1.00 McKenzie McKenzie River(RKM 57-90) 2015 1.80 McKenzie North Fork McKenzie River 2009 4.41 McKenzie North Fork McKenzie River 2010 5.06 McKenzie North Fork McKenzie River 2011 2.15 McKenzie North Fork McKenzie River 2012 1.47 McKenzie North Fork McKenzie River 2013 1.36 McKenzie North Fork McKenzie River 2014 1.27 McKenzie North Fork McKenzie River 2015 2.25 McKenzie South Fork McKenzie River 2011 1.72 McKenzie South Fork McKenzie River 2012 1.14 McKenzie South Fork McKenzie River Tailrace 2005 1.96 McKenzie South Fork McKenzie River Tailrace 2006 1.31 McKenzie South Fork McKenzie River Tailrace 2011 1.80 McKenzie South Fork McKenzie River Tailrace 2012 0.88 McKenzie McKenzie River(RKM 90.008-90.039) 2011 1.96 McKenzie McKenzie River(RKM 90.008-90.039) 2012 1.80 Middle Fork Middle Fork Dexter Dam Tailrace 2011 15.50 Middle Fork Middle Fork Dexter Dam Tailrace 2012 62.02 143 Middle Fork Middle Fork Dexter Dam Tailrace 2013 49.00 Middle Fork Middle Fork Dexter Dam Tailrace 2013 0.83 Middle Fork Middle Fork Dexter Dam Tailrace 2014 6.89 Middle Fork Middle Fork Lookout Point Head of Reservoir 2011 3.88 Middle Fork Middle Fork Lookout Point Head of Reservoir 2012 4.72 Middle Fork Middle Fork Lookout Point Head of Reservoir 2013 10.99 Middle Fork Middle Fork Lookout Point Head of Reservoir 2014 2.75 Middle Fork Middle Fork Hills Creek Head of Reservoir 2012 3.06 Middle Fork Middle Fork Hills Creek Head of Reservoir 2013 1.59 Middle Fork Middle Fork Fall Creek Head of Reservoir 2013 1.36 Middle Fork Middle Fork Fall Creek Head of Reservoir 2013 1.96 Middle Fork Middle Fork Fall Creek Head of Reservoir 2014 2.75 Middle Fork Middle Fork Lookout Point Dam Forebay 2013 9.00 Middle Fork Middle Fork Lookout Point Dam Forebay 2013 1.03 Middle Fork Middle Fork Lookout Point Dam Forebay 2014 4.72 Middle Fork Middle Fork Lookout Point Dam Tailrace 2014 20.25 Middle Fork Middle Fork(RKM 23) 2014 1.18 Middle Fork Middle Fork Fall Creek Tailrace 2013 1.59 Middle Fork Middle Fork Fall Creek Tailrace 2014 1.14 Middle Fork Middle Fork Hills Creek Dam Tailrace 2013 0.81 Middle Willamette Middle Willamette 2007 5.06 Middle Willamette Middle Willamette 2008 5.44 144 Middle Willamette Middle Willamette 2009 6.35 Middle Willamette Middle Willamette 2010 20.25 Middle Willamette Middle Willamette 2011 4.41 Middle Willamette Middle Willamette 2012 7.50 Middle Willamette Middle Willamette 2013 5.87 Middle Willamette Middle Willamette 2014 4.72 Middle Willamette Middle Willamette 2015 9.92 Middle Willamette Middle Willamette 2016 2.15 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2012 13.73 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2013 5.44 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2014 13.73 North Santiam Big Cliff Dam Tailrace(RKM 19.067) 2015 4.13 North Santiam Big Cliff Dam Tailrace(RKM 19.067) 2016 20.25 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2012 5.44 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2013 6.89 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2014 4.41 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2014 2.25 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2015 6.35 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2016 6.89 North Santiam Detroit Dam Forebay 2013 3.43 North Santiam Detroit Dam Forebay 2014 6.89 North Santiam Detroit Dam Forebay 2016 7.50 145 North Santiam North Santiam(RKM 19.000-19.030) 2006 1.31 North Santiam North Santiam(RKM 19.000-19.030) 2007 3.24 North Santiam North Santiam(RKM 19.000-19.030) 2008 2.36 North Santiam North Santiam(RKM 19.000-19.030) 2009 5.06 North Santiam North Santiam(RKM 19.000-19.030) 2010 2.15 North Santiam North Santiam(RKM 19.000-19.030) 2011 2.75 North Santiam North Santiam(RKM 19.000-19.030) 2012 1.18 North Santiam North Santiam(RKM 19.000-19.030) 2013 2.36 South Santiam Foster Dam Head of Reservoir 2015 2.90 South Santiam Foster Dam Head of Reservoir 2016 2.36 South Santiam Foster Dam Mid Reservoir 2015 2.61 South Santiam Foster Dam Mid Reservoir 2016 2.48 South Santiam South Santiam(RKM 19.000-19.032) 2006 2.05 South Santiam South Santiam(RKM 19.000-19.032) 2007 2.90 South Santiam South Santiam(RKM 19.000-19.032) 2008 5.44 South Santiam South Santiam(RKM 19.000-19.032) 2009 4.41 South Santiam South Santiam(RKM 19.000-19.032) 2010 3.88 South Santiam South Santiam(RKM 19.000-19.032) 2011 7.50 South Santiam South Santiam(RKM 19.000-19.032) 2012 2.05 South Santiam South Santiam(RKM 19.000-19.032) 2013 1.88 South Santiam South Santiam(RKM 19.035-19.059) 2006 1.31 South Santiam South Santiam(RKM 19.035-19.059) 2007 1.27 146 South Santiam South Santiam(RKM 19.035-19.059) 2008 1.10 South Santiam South Santiam(RKM 19.035-19.059) 2010 1.14 Upper Willamette Upper Willamette 2004 2.36 Upper Willamette Upper Willamette 2005 3.24 Upper Willamette Upper Willamette 2006 1.88 Upper Willamette Upper Willamette 2007 3.06 Upper Willamette Upper Willamette 2008 3.64 Upper Willamette Upper Willamette 2009 6.35 Upper Willamette Upper Willamette 2010 5.44 Upper Willamette Upper Willamette 2011 5.44 Upper Willamette Upper Willamette 2012 6.35 Upper Willamette Upper Willamette 2013 5.06 Upper Willamette Upper Willamette 2014 6.89 Upper Willamette Upper Willamette 2015 5.06 Upper Willamette Upper Willamette 2016 5.06 147 B.2 Ratios of posterior to prior precision for each release group for release-smolt-survival (ÏRSS) for four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. Ratios of less than 1.5 are bolded, and ratios between 1.5 and 2 are bolded and in italics. Area Release Group Year Ratio McKenzie Horse Creek 2011 1.20 McKenzie Horse Creek 2012 1.44 McKenzie Horse Creek 2013 1.48 McKenzie Horse Creek 2014 1.40 McKenzie Horse Creek 2015 1.35 McKenzie McKenzie River(RKM 0-56) 2002 2.47 McKenzie McKenzie River(RKM 0-56) 2003 2.47 McKenzie McKenzie River(RKM 0-56) 2004 1.63 McKenzie McKenzie River(RKM 0-56) 2005 1.54 McKenzie McKenzie River(RKM 0-56) 2007 1.85 McKenzie McKenzie River(RKM 0-56) 2008 1.77 McKenzie McKenzie River(RKM 0-56) 2009 2.09 McKenzie McKenzie River(RKM 0-56) 2011 2.09 McKenzie McKenzie River(RKM 0-56) 2012 1.80 McKenzie McKenzie River(RKM 0-56) 2013 1.91 McKenzie McKenzie River(RKM 0-56) 2014 2.06 McKenzie McKenzie River(RKM 0-56) 2015 2.64 McKenzie McKenzie Hatchery 2002 1.94 McKenzie McKenzie Hatchery 2003 1.35 148 McKenzie McKenzie Hatchery 2004 1.54 McKenzie McKenzie Hatchery 2005 1.75 McKenzie McKenzie Hatchery 2006 1.65 McKenzie McKenzie Hatchery 2008 1.09 McKenzie McKenzie Hatchery 2009 1.58 McKenzie McKenzie Hatchery 2010 1.85 McKenzie McKenzie River Bypass 2002 1.85 McKenzie McKenzie River Bypass 2003 1.48 McKenzie McKenzie River Bypass 2004 2.19 McKenzie McKenzie River Bypass 2005 2.00 McKenzie McKenzie River Bypass 2006 1.80 McKenzie McKenzie River Bypass 2007 3.66 McKenzie McKenzie River Bypass 2008 2.51 McKenzie McKenzie River Bypass 2009 2.09 McKenzie McKenzie River Bypass 2010 2.13 McKenzie McKenzie River Bypass 2011 2.06 McKenzie McKenzie River Bypass 2012 2.55 McKenzie McKenzie River Bypass 2013 2.69 McKenzie McKenzie River Bypass 2013 1.82 McKenzie McKenzie River Bypass 2014 2.06 McKenzie McKenzie River Bypass 2015 1.65 McKenzie McKenzie River(RKM 57-90) 2010 1.30 149 McKenzie McKenzie River(RKM 57-90) 2012 2.00 McKenzie McKenzie River(RKM 57-90) 2013 1.32 McKenzie McKenzie River(RKM 57-90) 2014 1.18 McKenzie McKenzie River(RKM 57-90) 2015 1.75 McKenzie North Fork McKenzie River 2009 1.91 McKenzie North Fork McKenzie River 2010 1.91 McKenzie North Fork McKenzie River 2011 1.54 McKenzie North Fork McKenzie River 2012 1.63 McKenzie North Fork McKenzie River 2013 1.54 McKenzie North Fork McKenzie River 2014 1.67 McKenzie North Fork McKenzie River 2015 1.58 McKenzie South Fork McKenzie River 2011 1.25 McKenzie South Fork McKenzie River 2012 1.11 McKenzie South Fork McKenzie River Tailrace 2005 1.33 McKenzie South Fork McKenzie River Tailrace 2006 1.10 McKenzie South Fork McKenzie River Tailrace 2011 1.56 McKenzie South Fork McKenzie River Tailrace 2012 1.18 McKenzie McKenzie River(RKM 90.008-90.039) 2011 1.46 McKenzie McKenzie River(RKM 90.008-90.039) 2012 1.50 Middle Fork Middle Fork Dexter Dam Tailrace 2011 2.16 Middle Fork Middle Fork Dexter Dam Tailrace 2012 7.30 Middle Fork Middle Fork Dexter Dam Tailrace 2013 5.84 150 Middle Fork Middle Fork Dexter Dam Tailrace 2013 1.21 Middle Fork Middle Fork Dexter Dam Tailrace 2014 35.12 Middle Fork Middle Fork Lookout Point Head of Reservoir 2011 5.27 Middle Fork Middle Fork Lookout Point Head of Reservoir 2012 18.25 Middle Fork Middle Fork Lookout Point Head of Reservoir 2013 2.64 Middle Fork Middle Fork Lookout Point Head of Reservoir 2014 37.50 Middle Fork Middle Fork Hills Creek Head of Reservoir 2012 3.00 Middle Fork Middle Fork Hills Creek Head of Reservoir 2013 30.99 Middle Fork Middle Fork Fall Creek Head of Reservoir 2013 3.74 Middle Fork Middle Fork Fall Creek Head of Reservoir 2013 1.48 Middle Fork Middle Fork Fall Creek Head of Reservoir 2014 1.70 Middle Fork Middle Fork Lookout Point Dam Forebay 2013 2.38 Middle Fork Middle Fork Lookout Point Dam Forebay 2013 3.12 Middle Fork Middle Fork Lookout Point Dam Forebay 2014 1.13 Middle Fork Middle Fork Lookout Point Dam Tailrace 2014 9.69 Middle Fork Middle Fork(RKM 23) 2014 1.18 Middle Fork Middle Fork Fall Creek Tailrace 2013 1.32 Middle Fork Middle Fork Fall Creek Tailrace 2014 1.13 Middle Fork Middle Fork Hills Creek Dam Tailrace 2013 1.33 Middle Willamette Middle Willamette 2007 2.03 Middle Willamette Middle Willamette 2008 2.47 Middle Willamette Middle Willamette 2009 2.00 151 Middle Willamette Middle Willamette 2010 2.03 Middle Willamette Middle Willamette 2011 1.94 Middle Willamette Middle Willamette 2012 2.47 Middle Willamette Middle Willamette 2013 2.89 Middle Willamette Middle Willamette 2014 2.30 Middle Willamette Middle Willamette 2015 3.00 Middle Willamette Middle Willamette 2016 2.89 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2012 2.27 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2013 6.89 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2014 3.18 North Santiam Big Cliff Dam Tailrace(RKM 19.067) 2015 3.82 North Santiam Big Cliff Dam Tailrace(RKM 19.067) 2016 6.00 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2012 6.16 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2013 2.60 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2014 2.84 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2014 1.97 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2015 15.28 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2016 6.69 North Santiam Detroit Dam Forebay 2013 10.03 North Santiam Detroit Dam Forebay 2014 2.34 North Santiam Detroit Dam Forebay 2016 6.33 North Santiam North Santiam(RKM 19.000-19.030) 2006 2.27 152 North Santiam North Santiam(RKM 19.000-19.030) 2007 1.75 North Santiam North Santiam(RKM 19.000-19.030) 2008 1.56 North Santiam North Santiam(RKM 19.000-19.030) 2009 1.97 North Santiam North Santiam(RKM 19.000-19.030) 2010 2.30 North Santiam North Santiam(RKM 19.000-19.030) 2011 3.00 North Santiam North Santiam(RKM 19.000-19.030) 2012 1.46 North Santiam North Santiam(RKM 19.000-19.030) 2013 1.70 South Santiam Foster Dam Head of Reservoir 2015 1.67 South Santiam Foster Dam Head of Reservoir 2016 1.67 South Santiam Foster Dam Mid Reservoir 2015 1.82 South Santiam Foster Dam Mid Reservoir 2016 1.67 South Santiam South Santiam(RKM 19.000-19.032) 2006 2.69 South Santiam South Santiam(RKM 19.000-19.032) 2007 2.51 South Santiam South Santiam(RKM 19.000-19.032) 2008 1.75 South Santiam South Santiam(RKM 19.000-19.032) 2009 2.00 South Santiam South Santiam(RKM 19.000-19.032) 2010 1.67 South Santiam South Santiam(RKM 19.000-19.032) 2011 1.94 South Santiam South Santiam(RKM 19.000-19.032) 2012 1.56 South Santiam South Santiam(RKM 19.000-19.032) 2013 1.58 South Santiam South Santiam(RKM 19.035-19.059) 2006 1.24 South Santiam South Santiam(RKM 19.035-19.059) 2007 1.11 South Santiam South Santiam(RKM 19.035-19.059) 2008 1.13 153 South Santiam South Santiam(RKM 19.035-19.059) 2010 1.18 Upper Willamette Upper Willamette 2004 2.23 Upper Willamette Upper Willamette 2005 2.64 Upper Willamette Upper Willamette 2006 1.94 Upper Willamette Upper Willamette 2007 2.30 Upper Willamette Upper Willamette 2008 3.37 Upper Willamette Upper Willamette 2009 2.38 Upper Willamette Upper Willamette 2010 1.77 Upper Willamette Upper Willamette 2011 3.51 Upper Willamette Upper Willamette 2012 7.52 Upper Willamette Upper Willamette 2013 2.27 Upper Willamette Upper Willamette 2014 2.16 Upper Willamette Upper Willamette 2015 2.19 Upper Willamette Upper Willamette 2016 2.19 154 B.3 Ratios of posterior to prior precision for each release group for probability of detection at SUJ (ÏPSUJ) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. Ratios of less than 1.5 are bolded, and ratios between 1.5 and 2 are bolded and in italics. Area Release Group Flow Year Ratio McKenzie Horse Creek high 2011 57.06 McKenzie Horse Creek mid 2012 16.81 McKenzie Horse Creek mid 2013 33.86 McKenzie Horse Creek low 2014 3.18 McKenzie Horse Creek mid 2015 15.38 McKenzie McKenzie River(RKM 0-56) low 2002 9.22 McKenzie McKenzie River(RKM 0-56) low 2003 5.47 McKenzie McKenzie River(RKM 0-56) mid 2004 19.36 McKenzie McKenzie River(RKM 0-56) high 2005 57.06 McKenzie McKenzie River(RKM 0-56) mid 2007 41.51 McKenzie McKenzie River(RKM 0-56) mid 2008 52.07 McKenzie McKenzie River(RKM 0-56) low 2009 8.44 McKenzie McKenzie River(RKM 0-56) mid 2011 4.61 McKenzie McKenzie River(RKM 0-56) low 2012 11.88 McKenzie McKenzie River(RKM 0-56) low 2013 3.18 McKenzie McKenzie River(RKM 0-56) low 2014 2.92 McKenzie McKenzie River(RKM 0-56) low 2015 3.02 McKenzie McKenzie Hatchery mid 2002 1.96 McKenzie McKenzie Hatchery high 2003 119.05 155 McKenzie McKenzie Hatchery mid 2004 7.47 McKenzie McKenzie Hatchery mid 2005 3.76 McKenzie McKenzie Hatchery high 2006 10.71 McKenzie McKenzie Hatchery mid 2008 6.64 McKenzie McKenzie Hatchery mid 2009 20.34 McKenzie McKenzie Hatchery mid 2010 16.07 McKenzie McKenzie River Bypass mid 2002 5.79 McKenzie McKenzie River Bypass mid 2003 13.02 McKenzie McKenzie River Bypass low 2004 2.24 McKenzie McKenzie River Bypass mid 2005 3.61 McKenzie McKenzie River Bypass mid 2006 33.86 McKenzie McKenzie River Bypass mid 2007 19.36 McKenzie McKenzie River Bypass mid 2008 15.38 McKenzie McKenzie River Bypass mid 2009 6.64 McKenzie McKenzie River Bypass high 2010 3.08 McKenzie McKenzie River Bypass high 2011 4.19 McKenzie McKenzie River Bypass mid 2012 20.34 McKenzie McKenzie River Bypass high 2013 1.27 McKenzie McKenzie River Bypass mid 2013 7.95 McKenzie McKenzie River Bypass high 2014 1.59 McKenzie McKenzie River Bypass low 2015 1.79 McKenzie McKenzie River(RKM 57-90) high 2010 13.23 156 McKenzie McKenzie River(RKM 57-90) mid 2012 7.47 McKenzie McKenzie River(RKM 57-90) high 2013 4.19 McKenzie McKenzie River(RKM 57-90) mid 2014 7.04 McKenzie McKenzie River(RKM 57-90) high 2015 4.02 McKenzie North Fork McKenzie River high 2009 1.76 McKenzie North Fork McKenzie River high 2010 1.19 McKenzie North Fork McKenzie River high 2011 4.76 McKenzie North Fork McKenzie River mid 2012 9.67 McKenzie North Fork McKenzie River high 2013 9.42 McKenzie North Fork McKenzie River low 2014 2.53 McKenzie North Fork McKenzie River high 2015 4.19 McKenzie South Fork McKenzie River high 2011 19.92 McKenzie South Fork McKenzie River mid 2012 4.11 McKenzie South Fork McKenzie River Tailrace high 2005 8.86 McKenzie South Fork McKenzie River Tailrace mid 2006 18.45 McKenzie South Fork McKenzie River Tailrace mid 2011 13.55 McKenzie South Fork McKenzie River Tailrace high 2012 8.86 McKenzie McKenzie River(RKM 90.008-90.039) high 2011 26.71 McKenzie McKenzie River(RKM 90.008-90.039) mid 2012 67.24 Middle Fork Middle Fork Dexter Dam Tailrace low 2011 2.37 Middle Fork Middle Fork Dexter Dam Tailrace low 2012 3.68 Middle Fork Middle Fork Dexter Dam Tailrace low 2013 2.20 157 Middle Fork Middle Fork Dexter Dam Tailrace mid 2013 1.71 Middle Fork Middle Fork Dexter Dam Tailrace low 2014 1.40 Middle Fork Middle Fork Lookout Point Head of Reservoir low 2011 1.72 Middle Fork Middle Fork Lookout Point Head of Reservoir low 2012 16.55 Middle Fork Middle Fork Lookout Point Head of Reservoir low 2013 20.43 Middle Fork Middle Fork Lookout Point Head of Reservoir low 2014 3.83 Middle Fork Middle Fork Hills Creek Head of Reservoir high 2012 1071.47 Middle Fork Middle Fork Hills Creek Head of Reservoir mid 2013 73.80 Middle Fork Middle Fork Fall Creek Head of Reservoir mid 2013 6.11 Middle Fork Middle Fork Fall Creek Head of Reservoir mid 2013 4.61 Middle Fork Middle Fork Fall Creek Head of Reservoir mid 2014 5.09 Middle Fork Middle Fork Lookout Point Dam Forebay low 2013 25.86 Middle Fork Middle Fork Lookout Point Dam Forebay low 2013 1.35 Middle Fork Middle Fork Lookout Point Dam Forebay low 2014 4.06 Middle Fork Middle Fork Lookout Point Dam Tailrace low 2014 13.68 Middle Fork Middle Fork(RKM 23) mid 2014 10.38 Middle Fork Middle Fork Fall Creek Tailrace mid 2013 1.90 Middle Fork Middle Fork Fall Creek Tailrace high 2014 1.37 Middle Fork Middle Fork Hills Creek Dam Tailrace mid 2013 31.78 Willamette Middle Willamette low 2007 1.35 Willamette Middle Willamette mid 2008 7.04 Willamette Middle Willamette mid 2009 6.11 158 Willamette Middle Willamette mid 2010 2.26 Willamette Middle Willamette mid 2011 3.85 Willamette Middle Willamette mid 2012 1.18 Willamette Middle Willamette low 2013 1.38 Willamette Middle Willamette low 2014 1.48 Willamette Middle Willamette low 2015 1.34 Willamette Middle Willamette low 2016 1.97 North Santiam Big Cliff Dam Tailrace(RKM 19.066) low 2012 17.23 North Santiam Big Cliff Dam Tailrace(RKM 19.066) mid 2013 38.70 North Santiam Big Cliff Dam Tailrace(RKM 19.066) low 2014 52.77 North Santiam Big Cliff Dam Tailrace(RKM 19.067) high 2015 21.87 North Santiam Big Cliff Dam Tailrace(RKM 19.067) high 2016 0.51 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) low 2012 10.10 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) mid 2013 81.36 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) mid 2014 112.61 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) mid 2014 100.44 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) mid 2015 22.54 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) high 2016 0.78 North Santiam Detroit Dam Forebay mid 2013 44.64 North Santiam Detroit Dam Forebay mid 2014 144.64 North Santiam Detroit Dam Forebay high 2016 0.78 North Santiam North Santiam(RKM 19.000-19.030) mid 2006 73.80 159 North Santiam North Santiam(RKM 19.000-19.030) low 2007 2.41 North Santiam North Santiam(RKM 19.000-19.030) low 2008 14.19 North Santiam North Santiam(RKM 19.000-19.030) low 2009 1.48 North Santiam North Santiam(RKM 19.000-19.030) mid 2010 2.69 North Santiam North Santiam(RKM 19.000-19.030) low 2011 1.34 North Santiam North Santiam(RKM 19.000-19.030) low 2012 17.23 North Santiam North Santiam(RKM 19.000-19.030) low 2013 1.66 South Santiam Foster Dam Head of Reservoir mid 2015 1.49 South Santiam Foster Dam Head of Reservoir mid 2016 2.95 South Santiam Foster Dam Mid Reservoir low 2015 1.74 South Santiam Foster Dam Mid Reservoir mid 2016 1.79 South Santiam South Santiam(RKM 19.000-19.032) low 2006 45.97 South Santiam South Santiam(RKM 19.000-19.032) low 2007 1.86 South Santiam South Santiam(RKM 19.000-19.032) mid 2008 2.59 South Santiam South Santiam(RKM 19.000-19.032) low 2009 1.41 South Santiam South Santiam(RKM 19.000-19.032) mid 2010 2.74 South Santiam South Santiam(RKM 19.000-19.032) mid 2011 1.73 South Santiam South Santiam(RKM 19.000-19.032) low 2012 8.69 South Santiam South Santiam(RKM 19.000-19.032) low 2013 2.11 South Santiam South Santiam(RKM 19.035-19.059) low 2006 93.81 South Santiam South Santiam(RKM 19.035-19.059) mid 2007 2.90 South Santiam South Santiam(RKM 19.035-19.059) low 2008 2.61 160 South Santiam South Santiam(RKM 19.035-19.059) low 2010 2.05 Willamette Upper Willamette low 2004 2.87 Willamette Upper Willamette low 2005 1.66 Willamette Upper Willamette low 2006 14.73 Willamette Upper Willamette low 2007 1.84 Willamette Upper Willamette low 2008 6.98 Willamette Upper Willamette low 2009 1.35 Willamette Upper Willamette mid 2010 2.59 Willamette Upper Willamette mid 2011 1.43 Willamette Upper Willamette low 2012 1.52 Willamette Upper Willamette low 2013 2.37 Willamette Upper Willamette low 2014 2.14 Willamette Upper Willamette low 2015 1.38 Willamette Upper Willamette low 2016 2.20 161 B.4 Ratios of posterior to prior precision for each release group for probability of detection at WFF (ÏPWFF) for each of the four subbasins (McKenzie, Middle Fork, North Santiam, and South Santiam) and two reaches of the mainstem river (Middle and Upper Willamette) examined from the Willamette River in Oregon, USA. Area Release Group Year Ratio McKenzie Horse Creek 2011 1 McKenzie Horse Creek 2012 1 McKenzie Horse Creek 2013 1 McKenzie Horse Creek 2014 1 McKenzie Horse Creek 2015 1 McKenzie McKenzie River(RKM 0-56) 2002 1 McKenzie McKenzie River(RKM 0-56) 2003 1 McKenzie McKenzie River(RKM 0-56) 2004 1 McKenzie McKenzie River(RKM 0-56) 2005 1 McKenzie McKenzie River(RKM 0-56) 2007 1 McKenzie McKenzie River(RKM 0-56) 2008 1 McKenzie McKenzie River(RKM 0-56) 2009 1 McKenzie McKenzie River(RKM 0-56) 2011 1 McKenzie McKenzie River(RKM 0-56) 2012 1 McKenzie McKenzie River(RKM 0-56) 2013 1 McKenzie McKenzie River(RKM 0-56) 2014 1 McKenzie McKenzie River(RKM 0-56) 2015 1 McKenzie McKenzie Hatchery 2002 1 McKenzie McKenzie Hatchery 2003 1 162 McKenzie McKenzie Hatchery 2004 1 McKenzie McKenzie Hatchery 2005 1 McKenzie McKenzie Hatchery 2006 1 McKenzie McKenzie Hatchery 2008 1 McKenzie McKenzie Hatchery 2009 1 McKenzie McKenzie Hatchery 2010 1 McKenzie McKenzie River Bypass 2002 1 McKenzie McKenzie River Bypass 2003 1 McKenzie McKenzie River Bypass 2004 1 McKenzie McKenzie River Bypass 2005 1 McKenzie McKenzie River Bypass 2006 1 McKenzie McKenzie River Bypass 2007 1 McKenzie McKenzie River Bypass 2008 1 McKenzie McKenzie River Bypass 2009 1 McKenzie McKenzie River Bypass 2010 1 McKenzie McKenzie River Bypass 2011 1 McKenzie McKenzie River Bypass 2012 1 McKenzie McKenzie River Bypass 2013 1 McKenzie McKenzie River Bypass 2013 1 McKenzie McKenzie River Bypass 2014 1 McKenzie McKenzie River Bypass 2015 1 McKenzie McKenzie River(RKM 57-90) 2010 1 163 McKenzie McKenzie River(RKM 57-90) 2012 1 McKenzie McKenzie River(RKM 57-90) 2013 1 McKenzie McKenzie River(RKM 57-90) 2014 1 McKenzie McKenzie River(RKM 57-90) 2015 1 McKenzie North Fork McKenzie River 2009 1 McKenzie North Fork McKenzie River 2010 1 McKenzie North Fork McKenzie River 2011 1 McKenzie North Fork McKenzie River 2012 1 McKenzie North Fork McKenzie River 2013 1 McKenzie North Fork McKenzie River 2014 1 McKenzie North Fork McKenzie River 2015 1 McKenzie South Fork McKenzie River 2011 1 McKenzie South Fork McKenzie River 2012 1 McKenzie South Fork McKenzie River Tailrace 2005 1 McKenzie South Fork McKenzie River Tailrace 2006 1 McKenzie South Fork McKenzie River Tailrace 2011 1 McKenzie South Fork McKenzie River Tailrace 2012 1 McKenzie McKenzie River(RKM 90.008-90.039) 2011 1 McKenzie McKenzie River(RKM 90.008-90.039) 2012 1 Middle Fork Middle Fork Dexter Dam Tailrace 2011 1 Middle Fork Middle Fork Dexter Dam Tailrace 2012 1 Middle Fork Middle Fork Dexter Dam Tailrace 2013 1 164 Middle Fork Middle Fork Dexter Dam Tailrace 2013 1 Middle Fork Middle Fork Dexter Dam Tailrace 2014 1 Middle Fork Middle Fork Lookout Point Head of Reservoir 2011 1 Middle Fork Middle Fork Lookout Point Head of Reservoir 2012 1 Middle Fork Middle Fork Lookout Point Head of Reservoir 2013 1 Middle Fork Middle Fork Lookout Point Head of Reservoir 2014 1 Middle Fork Middle Fork Hills Creek Head of Reservoir 2012 1 Middle Fork Middle Fork Hills Creek Head of Reservoir 2013 1 Middle Fork Middle Fork Fall Creek Head of Reservoir 2013 1 Middle Fork Middle Fork Fall Creek Head of Reservoir 2013 1 Middle Fork Middle Fork Fall Creek Head of Reservoir 2014 1 Middle Fork Middle Fork Lookout Point Dam Forebay 2013 1 Middle Fork Middle Fork Lookout Point Dam Forebay 2013 1 Middle Fork Middle Fork Lookout Point Dam Forebay 2014 1 Middle Fork Middle Fork Lookout Point Dam Tailrace 2014 1 Middle Fork Middle Fork(RKM 23) 2014 1 Middle Fork Middle Fork Fall Creek Tailrace 2013 1 Middle Fork Middle Fork Fall Creek Tailrace 2014 1 Middle Fork Middle Fork Hills Creek Dam Tailrace 2013 1 Willamette Middle Willamette 2007 1 Willamette Middle Willamette 2008 1 Willamette Middle Willamette 2009 1 165 Willamette Middle Willamette 2010 1 Willamette Middle Willamette 2011 1 Willamette Middle Willamette 2012 1 Willamette Middle Willamette 2013 1 Willamette Middle Willamette 2014 1 Willamette Middle Willamette 2015 1 Willamette Middle Willamette 2016 1 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2012 1 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2013 1 North Santiam Big Cliff Dam Tailrace(RKM 19.066) 2014 1 North Santiam Big Cliff Dam Tailrace(RKM 19.067) 2015 1 North Santiam Big Cliff Dam Tailrace(RKM 19.067) 2016 1 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2012 1 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2013 1 North Santiam Detroit Dam Head of Reservoir(RKM 19.091) 2014 1 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2014 1 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2015 1 North Santiam Detroit Dam Head of Reservoir(RKM 19.093) 2016 1 North Santiam Detroit Dam Forebay 2013 1 North Santiam Detroit Dam Forebay 2014 1 North Santiam Detroit Dam Forebay 2016 1 North Santiam North Santiam(RKM 19.000-19.030) 2006 1 166 North Santiam North Santiam(RKM 19.000-19.030) 2007 1 North Santiam North Santiam(RKM 19.000-19.030) 2008 1 North Santiam North Santiam(RKM 19.000-19.030) 2009 1 North Santiam North Santiam(RKM 19.000-19.030) 2010 1 North Santiam North Santiam(RKM 19.000-19.030) 2011 1 North Santiam North Santiam(RKM 19.000-19.030) 2012 1 North Santiam North Santiam(RKM 19.000-19.030) 2013 1 South Santiam Foster Dam Head of Reservoir 2015 1 South Santiam Foster Dam Head of Reservoir 2016 1 South Santiam Foster Dam Mid Reservoir 2015 1 South Santiam Foster Dam Mid Reservoir 2016 1 South Santiam South Santiam(RKM 19.000-19.032) 2006 1 South Santiam South Santiam(RKM 19.000-19.032) 2007 1 South Santiam South Santiam(RKM 19.000-19.032) 2008 1 South Santiam South Santiam(RKM 19.000-19.032) 2009 1 South Santiam South Santiam(RKM 19.000-19.032) 2010 1 South Santiam South Santiam(RKM 19.000-19.032) 2011 1 South Santiam South Santiam(RKM 19.000-19.032) 2012 1 South Santiam South Santiam(RKM 19.000-19.032) 2013 1 South Santiam South Santiam(RKM 19.035-19.059) 2006 1 South Santiam South Santiam(RKM 19.035-19.059) 2007 1 South Santiam South Santiam(RKM 19.035-19.059) 2008 1 167 South Santiam South Santiam(RKM 19.035-19.059) 2010 1 Willamette Upper Willamette 2004 1 Willamette Upper Willamette 2005 1 Willamette Upper Willamette 2006 1 Willamette Upper Willamette 2007 1 Willamette Upper Willamette 2008 1 Willamette Upper Willamette 2009 1 Willamette Upper Willamette 2010 1 Willamette Upper Willamette 2011 1 Willamette Upper Willamette 2012 1 Willamette Upper Willamette 2013 1 Willamette Upper Willamette 2014 1 Willamette Upper Willamette 2015 1 Willamette Upper Willamette 2016 1 168 B.5 Scatterplot of ÏSAS posterior to prior precision ratio for each release group in relation to release group size. Data points are colored by area (McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, Upper Willamette). The solid black line shows the trend between release size and the ratios; the shaded grey area represents the 95% credible interval, and the R2 value is displayed on the bottom right. B.6 Scatterplot of ÏRSS posterior to prior precision ratio for each release group in relation to release group size. Data points are colored by area (McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, Upper Willamette). The solid black line shows the trend between release size and the ratios; the shaded grey area represents the 95% credible interval, and the R2 value is displayed on the bottom right. 169 B.7 Scatterplot of PSUJ posterior to prior precision ratio for each release group in relation to release group size. Panels are separated by flow type, from top to bottom: low flow, mid flow and high flow. Data points are colored by area (McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, Upper Willamette). The solid black line shows the trend between release size and the ratios, and the R2 value is displayed on the bottom right of each panel. 170 Appendix C C.1 Informative prior mean, SD, lower 95% CI, Median, and upper 95% CI for each parameter in the BCJS model. Parameter Mean SD 2.5 Median 97.5 ÏRSS 0.3997 0.1837 0.0897 0.3906 0.7693 ÏSAS 0.0114 0.0063 0.0026 0.0102 0.0268 PSUJ: low flow 0.2167 0.2034 0.0018 0.1492 0.7225 PSUJ: mid flow 0.1513 0.1804 0.0000 0.0804 0.6567 PSUJ: high flow 0.0522 0.0982 0.0000 0.0194 0.3532 PWFF 0.9800 0.0100 0.9564 0.9816 0.9948 171 C.2 ÏSAS posterior mean, SD, lower 95% CI, Median, and upper 95% CI for each release group across all areas. Release Group Year Mean SD 2.5 Median 97.5 Horse Creek 2011 0.0098 0.0051 0.0026 0.0089 0.0224 Horse Creek 2012 0.0098 0.0047 0.0031 0.0090 0.0210 Horse Creek 2013 0.0087 0.0045 0.0025 0.0078 0.0196 Horse Creek 2014 0.0124 0.0062 0.0034 0.0114 0.0270 Horse Creek 2015 0.0088 0.0048 0.0023 0.0079 0.0209 McKenzie River(RKM 0-56) 2002 0.0066 0.0044 0.0012 0.0055 0.0177 McKenzie River(RKM 0-56) 2003 0.0064 0.0043 0.0011 0.0054 0.0173 McKenzie River(RKM 0-56) 2004 0.0076 0.0044 0.0018 0.0067 0.0187 McKenzie River(RKM 0-56) 2005 0.0074 0.0043 0.0019 0.0064 0.0184 McKenzie River(RKM 0-56) 2007 0.0070 0.0043 0.0016 0.0061 0.0177 McKenzie River(RKM 0-56) 2008 0.0069 0.0038 0.0021 0.0060 0.0163 McKenzie River(RKM 0-56) 2009 0.0067 0.0040 0.0017 0.0059 0.0168 McKenzie River(RKM 0-56) 2011 0.0051 0.0029 0.0014 0.0044 0.0123 McKenzie River(RKM 0-56) 2012 0.0072 0.0038 0.0022 0.0064 0.0164 McKenzie River(RKM 0-56) 2013 0.0069 0.0043 0.0013 0.0059 0.0178 McKenzie River(RKM 0-56) 2014 0.0061 0.0035 0.0014 0.0053 0.0151 McKenzie River(RKM 0-56) 2015 0.0052 0.0032 0.0011 0.0045 0.0132 McKenzie Hatchery 2002 0.0049 0.0028 0.0012 0.0044 0.0117 McKenzie Hatchery 2003 0.0091 0.0047 0.0027 0.0081 0.0209 McKenzie Hatchery 2004 0.0076 0.0036 0.0025 0.0069 0.0164 McKenzie Hatchery 2005 0.0056 0.0029 0.0017 0.0051 0.0128 McKenzie Hatchery 2006 0.0120 0.0044 0.0056 0.0113 0.0228 172 McKenzie Hatchery 2008 0.0104 0.0058 0.0023 0.0094 0.0246 McKenzie Hatchery 2009 0.0108 0.0043 0.0045 0.0102 0.0211 McKenzie Hatchery 2010 0.0086 0.0033 0.0037 0.0080 0.0166 McKenzie River Bypass 2002 0.0059 0.0033 0.0016 0.0052 0.0141 McKenzie River Bypass 2003 0.0126 0.0056 0.0043 0.0117 0.0263 McKenzie River Bypass 2004 0.0051 0.0031 0.0012 0.0045 0.0130 McKenzie River Bypass 2005 0.0049 0.0031 0.0011 0.0041 0.0125 McKenzie River Bypass 2006 0.0113 0.0046 0.0047 0.0105 0.0222 McKenzie River Bypass 2007 0.0140 0.0058 0.0054 0.0130 0.0274 McKenzie River Bypass 2008 0.0098 0.0043 0.0037 0.0091 0.0204 McKenzie River Bypass 2009 0.0087 0.0042 0.0027 0.0079 0.0188 McKenzie River Bypass 2010 0.0065 0.0032 0.0022 0.0059 0.0143 McKenzie River Bypass 2011 0.0078 0.0039 0.0025 0.0070 0.0175 McKenzie River Bypass 2012 0.0151 0.0057 0.0064 0.0143 0.0289 McKenzie River Bypass 2013 0.0097 0.0037 0.0043 0.0091 0.0183 McKenzie River Bypass 2013 0.0045 0.0029 0.0010 0.0038 0.0120 McKenzie River Bypass 2014 0.0069 0.0035 0.0021 0.0063 0.0155 McKenzie River Bypass 2015 0.0070 0.0042 0.0014 0.0061 0.0173 McKenzie River(RKM 57-90) 2010 0.0105 0.0050 0.0033 0.0097 0.0222 McKenzie River(RKM 57-90) 2012 0.0139 0.0061 0.0050 0.0130 0.0286 McKenzie River(RKM 57-90) 2013 0.0089 0.0047 0.0023 0.0080 0.0205 McKenzie River(RKM 57-90) 2014 0.0128 0.0063 0.0036 0.0117 0.0276 McKenzie River(RKM 57-90) 2015 0.0099 0.0047 0.0033 0.0090 0.0211 North Fork McKenzie River 2009 0.0046 0.0030 0.0009 0.0038 0.0123 173 North Fork McKenzie River 2010 0.0046 0.0028 0.0010 0.0040 0.0118 North Fork McKenzie River 2011 0.0069 0.0043 0.0013 0.0059 0.0178 North Fork McKenzie River 2012 0.0116 0.0052 0.0042 0.0107 0.0242 North Fork McKenzie River 2013 0.0113 0.0054 0.0037 0.0103 0.0246 North Fork McKenzie River 2014 0.0110 0.0056 0.0030 0.0100 0.0243 North Fork McKenzie River 2015 0.0067 0.0042 0.0013 0.0058 0.0172 South Fork McKenzie River 2011 0.0083 0.0048 0.0018 0.0073 0.0199 South Fork McKenzie River 2012 0.0107 0.0059 0.0023 0.0096 0.0253 South Fork McKenzie River Tailrace 2005 0.0078 0.0045 0.0019 0.0068 0.0190 South Fork McKenzie River Tailrace 2006 0.0107 0.0055 0.0029 0.0097 0.0242 South Fork McKenzie River Tailrace 2011 0.0078 0.0047 0.0016 0.0069 0.0197 South Fork McKenzie River Tailrace 2012 0.0088 0.0067 0.0009 0.0071 0.0257 McKenzie River(RKM 90.008-90.039) 2011 0.0079 0.0045 0.0020 0.0069 0.0192 McKenzie River(RKM 90.008-90.039) 2012 0.0093 0.0047 0.0028 0.0084 0.0212 Middle Fork Dexter Dam Tailrace 2011 0.0029 0.0016 0.0007 0.0025 0.0069 Middle Fork Dexter Dam Tailrace 2012 0.0019 0.0008 0.0007 0.0018 0.0037 Middle Fork Dexter Dam Tailrace 2013 0.0017 0.0009 0.0004 0.0015 0.0040 Middle Fork Dexter Dam Tailrace 2013 0.0141 0.0069 0.0041 0.0130 0.0305 Middle Fork Dexter Dam Tailrace 2014 0.0044 0.0024 0.0010 0.0040 0.0101 Middle Fork Lookout Point Head of Reservoir 2011 0.0056 0.0032 0.0014 0.0050 0.0135 Middle Fork Lookout Point Head of Reservoir 2012 0.0072 0.0029 0.0028 0.0068 0.0139 Middle Fork Lookout Point Head of Reservoir 2013 0.0030 0.0019 0.0008 0.0026 0.0078 Middle Fork Lookout Point Head of Reservoir 2014 0.0047 0.0038 0.0005 0.0038 0.0142 Middle Fork Hills Creek Head of Reservoir 2012 0.0049 0.0036 0.0009 0.0039 0.0144 174 Middle Fork Hills Creek Head of Reservoir 2013 0.0078 0.0050 0.0013 0.0068 0.0203 Middle Fork Fall Creek Head of Reservoir 2013 0.0138 0.0054 0.0057 0.0130 0.0266 Middle Fork Fall Creek Head of Reservoir 2013 0.0083 0.0045 0.0022 0.0075 0.0191 Middle Fork Fall Creek Head of Reservoir 2014 0.0069 0.0038 0.0019 0.0060 0.0165 Middle Fork Lookout Point Dam Forebay 2013 0.0042 0.0021 0.0014 0.0038 0.0094 Middle Fork Lookout Point Dam Forebay 2013 0.0112 0.0062 0.0025 0.0101 0.0262 Middle Fork Lookout Point Dam Forebay 2014 0.0038 0.0029 0.0005 0.0030 0.0111 Middle Fork Lookout Point Dam Tailrace 2014 0.0023 0.0014 0.0007 0.0020 0.0059 Middle Fork(RKM 23) 2014 0.0116 0.0058 0.0033 0.0106 0.0253 Middle Fork Fall Creek Tailrace 2013 0.0090 0.0050 0.0020 0.0080 0.0213 Middle Fork Fall Creek Tailrace 2014 0.0106 0.0059 0.0024 0.0095 0.0252 Middle Fork Hills Creek Dam Tailrace 2013 0.0172 0.0070 0.0063 0.0163 0.0333 Middle Willamette 2007 0.0043 0.0028 0.0008 0.0037 0.0112 Middle Willamette 2008 0.0087 0.0027 0.0045 0.0083 0.0150 Middle Willamette 2009 0.0060 0.0025 0.0025 0.0056 0.0120 Middle Willamette 2010 0.0025 0.0014 0.0007 0.0022 0.0062 Middle Willamette 2011 0.0070 0.0030 0.0027 0.0065 0.0142 Middle Willamette 2012 0.0035 0.0023 0.0006 0.0030 0.0094 Middle Willamette 2013 0.0038 0.0026 0.0007 0.0032 0.0102 Middle Willamette 2014 0.0046 0.0029 0.0009 0.0039 0.0118 Middle Willamette 2015 0.0030 0.0020 0.0005 0.0025 0.0082 Middle Willamette 2016 0.0095 0.0043 0.0031 0.0088 0.0199 Big Cliff Dam Tailrace(RKM 19.066) 2012 0.0057 0.0017 0.0031 0.0055 0.0097 Big Cliff Dam Tailrace(RKM 19.066) 2013 0.0104 0.0027 0.0059 0.0101 0.0164 175 Big Cliff Dam Tailrace(RKM 19.066) 2014 0.0060 0.0017 0.0034 0.0057 0.0099 Big Cliff Dam Tailrace(RKM 19.067) 2015 0.0086 0.0031 0.0038 0.0081 0.0158 Big Cliff Dam Tailrace(RKM 19.067) 2016 0.0016 0.0014 0.0002 0.0012 0.0054 Detroit Dam Head of Reservoir(RKM 19.091) 2012 0.0096 0.0027 0.0052 0.0093 0.0159 Detroit Dam Head of Reservoir(RKM 19.091) 2013 0.0077 0.0024 0.0039 0.0074 0.0131 Detroit Dam Head of Reservoir(RKM 19.091) 2014 0.0073 0.0030 0.0029 0.0067 0.0145 Detroit Dam Head of Reservoir(RKM 19.093) 2014 0.0093 0.0042 0.0036 0.0085 0.0198 Detroit Dam Head of Reservoir(RKM 19.093) 2015 0.0076 0.0025 0.0034 0.0073 0.0134 Detroit Dam Head of Reservoir(RKM 19.093) 2016 0.0027 0.0024 0.0002 0.0019 0.0091 Detroit Dam Forebay 2013 0.0143 0.0034 0.0084 0.0141 0.0216 Detroit Dam Forebay 2014 0.0073 0.0024 0.0037 0.0069 0.0130 Detroit Dam Forebay 2016 0.0026 0.0023 0.0002 0.0020 0.0088 North Santiam(RKM 19.000-19.030) 2006 0.0100 0.0055 0.0026 0.0089 0.0239 North Santiam(RKM 19.000-19.030) 2007 0.0063 0.0035 0.0016 0.0056 0.0153 North Santiam(RKM 19.000-19.030) 2008 0.0090 0.0041 0.0032 0.0082 0.0189 North Santiam(RKM 19.000-19.030) 2009 0.0045 0.0028 0.0009 0.0039 0.0115 North Santiam(RKM 19.000-19.030) 2010 0.0097 0.0043 0.0035 0.0089 0.0200 North Santiam(RKM 19.000-19.030) 2011 0.0068 0.0038 0.0016 0.0061 0.0159 North Santiam(RKM 19.000-19.030) 2012 0.0146 0.0058 0.0059 0.0137 0.0281 North Santiam(RKM 19.000-19.030) 2013 0.0070 0.0041 0.0015 0.0062 0.0170 Foster Dam Head of Reservoir 2015 0.0061 0.0037 0.0012 0.0053 0.0154 Foster Dam Head of Reservoir 2016 0.0067 0.0041 0.0013 0.0058 0.0170 Foster Dam Mid Reservoir 2015 0.0063 0.0039 0.0013 0.0055 0.0161 Foster Dam Mid Reservoir 2016 0.0063 0.0040 0.0013 0.0053 0.0166 176 South Santiam(RKM 19.000-19.032) 2006 0.0065 0.0044 0.0011 0.0055 0.0177 South Santiam(RKM 19.000-19.032) 2007 0.0058 0.0037 0.0011 0.0050 0.0150 South Santiam(RKM 19.000-19.032) 2008 0.0051 0.0027 0.0015 0.0045 0.0118 South Santiam(RKM 19.000-19.032) 2009 0.0047 0.0030 0.0009 0.0041 0.0123 South Santiam(RKM 19.000-19.032) 2010 0.0062 0.0032 0.0018 0.0056 0.0142 South Santiam(RKM 19.000-19.032) 2011 0.0040 0.0023 0.0010 0.0035 0.0097 South Santiam(RKM 19.000-19.032) 2012 0.0086 0.0044 0.0025 0.0077 0.0194 South Santiam(RKM 19.000-19.032) 2013 0.0078 0.0046 0.0016 0.0069 0.0191 South Santiam(RKM 19.035-19.059) 2006 0.0105 0.0055 0.0029 0.0095 0.0239 South Santiam(RKM 19.035-19.059) 2007 0.0102 0.0056 0.0022 0.0091 0.0237 South Santiam(RKM 19.035-19.059) 2008 0.0108 0.0060 0.0025 0.0096 0.0250 South Santiam(RKM 19.035-19.059) 2010 0.0107 0.0059 0.0025 0.0096 0.0247 Upper Willamette 2004 0.0065 0.0041 0.0012 0.0055 0.0171 Upper Willamette 2005 0.0052 0.0035 0.0009 0.0044 0.0140 Upper Willamette 2006 0.0074 0.0046 0.0016 0.0064 0.0189 Upper Willamette 2007 0.0056 0.0036 0.0010 0.0048 0.0146 Upper Willamette 2008 0.0080 0.0033 0.0032 0.0074 0.0157 Upper Willamette 2009 0.0038 0.0025 0.0007 0.0033 0.0099 Upper Willamette 2010 0.0051 0.0027 0.0014 0.0045 0.0119 Upper Willamette 2011 0.0047 0.0027 0.0012 0.0042 0.0112 Upper Willamette 2012 0.0050 0.0025 0.0014 0.0045 0.0110 Upper Willamette 2013 0.0046 0.0028 0.0011 0.0040 0.0116 Upper Willamette 2014 0.0042 0.0024 0.0010 0.0037 0.0100 Upper Willamette 2015 0.0043 0.0028 0.0008 0.0037 0.0115 177 Upper Willamette 2016 0.0048 0.0028 0.0011 0.0042 0.0117 178 C.3 ÏRSS posterior mean, SD, lower 95% CI, Median, and upper 95% CI for each release group across all areas. Release Group Year Mean SD 2.5 Median 97.5 Horse Creek 2011 0.345 0.168 0.080 0.325 0.725 Horse Creek 2012 0.366 0.153 0.126 0.347 0.711 Horse Creek 2013 0.295 0.151 0.078 0.267 0.653 Horse Creek 2014 0.282 0.155 0.065 0.251 0.651 Horse Creek 2015 0.305 0.158 0.076 0.280 0.671 McKenzie River(RKM 0-56) 2002 0.145 0.117 0.016 0.112 0.463 McKenzie River(RKM 0-56) 2003 0.148 0.117 0.021 0.114 0.466 McKenzie River(RKM 0-56) 2004 0.247 0.144 0.052 0.216 0.602 McKenzie River(RKM 0-56) 2005 0.265 0.148 0.060 0.237 0.626 McKenzie River(RKM 0-56) 2007 0.207 0.135 0.038 0.175 0.548 McKenzie River(RKM 0-56) 2008 0.267 0.138 0.080 0.239 0.612 McKenzie River(RKM 0-56) 2009 0.219 0.127 0.057 0.189 0.543 McKenzie River(RKM 0-56) 2011 0.248 0.127 0.079 0.220 0.562 McKenzie River(RKM 0-56) 2012 0.290 0.137 0.096 0.263 0.620 McKenzie River(RKM 0-56) 2013 0.194 0.133 0.036 0.160 0.539 McKenzie River(RKM 0-56) 2014 0.237 0.128 0.072 0.208 0.559 McKenzie River(RKM 0-56) 2015 0.181 0.113 0.049 0.151 0.483 McKenzie Hatchery 2002 0.328 0.132 0.140 0.307 0.645 McKenzie Hatchery 2003 0.331 0.158 0.088 0.309 0.686 McKenzie Hatchery 2004 0.374 0.148 0.145 0.353 0.708 McKenzie Hatchery 2005 0.345 0.139 0.141 0.321 0.672 McKenzie Hatchery 2006 0.481 0.143 0.233 0.471 0.778 179 McKenzie Hatchery 2008 0.335 0.176 0.063 0.314 0.717 McKenzie Hatchery 2009 0.462 0.146 0.213 0.450 0.766 McKenzie Hatchery 2010 0.400 0.135 0.193 0.382 0.715 McKenzie River Bypass 2002 0.272 0.135 0.089 0.244 0.606 McKenzie River Bypass 2003 0.338 0.151 0.109 0.316 0.685 McKenzie River Bypass 2004 0.231 0.124 0.076 0.203 0.541 McKenzie River Bypass 2005 0.226 0.130 0.064 0.194 0.558 McKenzie River Bypass 2006 0.356 0.137 0.147 0.336 0.676 McKenzie River Bypass 2007 0.208 0.096 0.082 0.187 0.452 McKenzie River Bypass 2008 0.261 0.116 0.106 0.238 0.556 McKenzie River Bypass 2009 0.264 0.127 0.095 0.238 0.579 McKenzie River Bypass 2010 0.275 0.126 0.101 0.249 0.598 McKenzie River Bypass 2011 0.266 0.128 0.093 0.241 0.576 McKenzie River Bypass 2012 0.284 0.115 0.120 0.262 0.569 McKenzie River Bypass 2013 0.314 0.112 0.154 0.293 0.585 McKenzie River Bypass 2013 0.242 0.136 0.069 0.208 0.580 McKenzie River Bypass 2014 0.282 0.128 0.107 0.256 0.586 McKenzie River Bypass 2015 0.286 0.143 0.095 0.257 0.633 McKenzie River(RKM 57-90) 2010 0.391 0.161 0.124 0.374 0.734 McKenzie River(RKM 57-90) 2012 0.261 0.130 0.082 0.237 0.580 McKenzie River(RKM 57-90) 2013 0.346 0.160 0.098 0.325 0.699 McKenzie River(RKM 57-90) 2014 0.433 0.169 0.143 0.422 0.780 McKenzie River(RKM 57-90) 2015 0.307 0.139 0.104 0.282 0.631 North Fork McKenzie River 2009 0.212 0.133 0.051 0.177 0.556 180 North Fork McKenzie River 2010 0.250 0.133 0.075 0.222 0.584 North Fork McKenzie River 2011 0.236 0.148 0.044 0.204 0.603 North Fork McKenzie River 2012 0.344 0.144 0.125 0.324 0.677 North Fork McKenzie River 2013 0.306 0.148 0.091 0.280 0.663 North Fork McKenzie River 2014 0.239 0.142 0.056 0.208 0.590 North Fork McKenzie River 2015 0.239 0.146 0.044 0.207 0.596 South Fork McKenzie River 2011 0.284 0.164 0.048 0.256 0.666 South Fork McKenzie River 2012 0.350 0.174 0.076 0.331 0.733 South Fork McKenzie River Tailrace 2005 0.267 0.159 0.042 0.238 0.645 South Fork McKenzie River Tailrace 2006 0.395 0.175 0.107 0.380 0.763 South Fork McKenzie River Tailrace 2011 0.258 0.147 0.055 0.231 0.617 South Fork McKenzie River Tailrace 2012 0.390 0.169 0.112 0.374 0.750 McKenzie River(RKM 90.008-90.039) 2011 0.280 0.152 0.065 0.253 0.638 McKenzie River(RKM 90.008-90.039) 2012 0.316 0.150 0.095 0.292 0.662 Middle Fork Dexter Dam Tailrace 2011 0.301 0.125 0.131 0.273 0.603 Middle Fork Dexter Dam Tailrace 2012 0.182 0.068 0.099 0.166 0.359 Middle Fork Dexter Dam Tailrace 2013 0.138 0.076 0.057 0.115 0.349 Middle Fork Dexter Dam Tailrace 2013 0.392 0.167 0.119 0.374 0.746 Middle Fork Dexter Dam Tailrace 2014 0.043 0.031 0.018 0.035 0.117 Middle Fork Lookout Point Head of Reservoir 2011 0.135 0.080 0.049 0.113 0.351 Middle Fork Lookout Point Head of Reservoir 2012 0.097 0.043 0.044 0.087 0.207 Middle Fork Lookout Point Head of Reservoir 2013 0.189 0.113 0.055 0.159 0.491 Middle Fork Lookout Point Head of Reservoir 2014 0.023 0.030 0.002 0.013 0.112 Middle Fork Hills Creek Head of Reservoir 2012 0.132 0.106 0.025 0.099 0.434 181 Middle Fork Hills Creek Head of Reservoir 2013 0.031 0.033 0.005 0.021 0.121 Middle Fork Fall Creek Head of Reservoir 2013 0.235 0.095 0.107 0.215 0.470 Middle Fork Fall Creek Head of Reservoir 2013 0.316 0.151 0.094 0.292 0.659 Middle Fork Fall Creek Head of Reservoir 2014 0.286 0.141 0.089 0.259 0.624 Middle Fork Lookout Point Dam Tailrace 2014 0.224 0.119 0.071 0.197 0.532 Middle Fork Lookout Point Dam Forebay 2013 0.196 0.104 0.069 0.170 0.460 Middle Fork Lookout Point Dam Forebay 2013 0.404 0.173 0.117 0.388 0.766 Middle Fork Lookout Point Dam Forebay 2014 0.057 0.059 0.010 0.037 0.229 Middle Fork(RKM 23) 2013 0.397 0.169 0.116 0.379 0.759 Middle Fork Fall Creek Tailrace 2013 0.356 0.160 0.112 0.334 0.703 Middle Fork Fall Creek Tailrace 2013 0.402 0.173 0.110 0.390 0.757 Middle Fork Hills Creek Dam Tailrace 2013 0.524 0.159 0.223 0.524 0.830 Middle Willamette 2007 0.272 0.129 0.113 0.240 0.609 Middle Willamette 2008 0.496 0.117 0.299 0.484 0.756 Middle Willamette 2009 0.410 0.130 0.206 0.391 0.703 Middle Willamette 2010 0.321 0.129 0.147 0.295 0.638 Middle Willamette 2011 0.428 0.132 0.218 0.412 0.720 Middle Willamette 2012 0.231 0.117 0.090 0.201 0.526 Middle Willamette 2013 0.199 0.108 0.073 0.169 0.483 Middle Willamette 2014 0.274 0.121 0.115 0.249 0.573 Middle Willamette 2015 0.207 0.106 0.085 0.179 0.488 Middle Willamette 2016 0.260 0.108 0.120 0.236 0.532 Big Cliff Dam Tailrace(RKM 19.066) 2012 0.478 0.122 0.284 0.463 0.746 Big Cliff Dam Tailrace(RKM 19.066) 2013 0.276 0.070 0.170 0.265 0.443 182 Big Cliff Dam Tailrace(RKM 19.066) 2014 0.405 0.103 0.235 0.393 0.640 Big Cliff Dam Tailrace(RKM 19.067) 2015 0.246 0.094 0.118 0.228 0.474 Big Cliff Dam Tailrace(RKM 19.067) 2016 0.082 0.075 0.017 0.057 0.283 Detroit Dam Head of Reservoir(RKM 19.091) 2012 0.293 0.074 0.181 0.282 0.466 Detroit Dam Head of Reservoir(RKM 19.091) 2013 0.375 0.114 0.203 0.359 0.651 Detroit Dam Head of Reservoir(RKM 19.091) 2011 0.256 0.109 0.110 0.235 0.525 Detroit Dam Head of Reservoir(RKM 19.093) 2014 0.303 0.131 0.116 0.279 0.615 Detroit Dam Head of Reservoir(RKM 19.093) 2015 0.126 0.047 0.066 0.115 0.247 Detroit Dam Head of Reservoir(RKM 19.093) 2016 0.062 0.071 0.007 0.036 0.274 Detroit Dam Forebay 2013 0.234 0.058 0.149 0.224 0.371 Detroit Dam Forebay 2014 0.383 0.120 0.200 0.367 0.664 Detroit Dam Forebay 2016 0.058 0.073 0.007 0.032 0.278 North Santiam(RKM 19.000-19.030) 2006 0.180 0.122 0.031 0.150 0.497 North Santiam(RKM 19.000-19.030) 2007 0.310 0.139 0.116 0.284 0.641 North Santiam(RKM 19.000-19.030) 2008 0.379 0.147 0.152 0.358 0.707 North Santiam(RKM 19.000-19.030) 2009 0.306 0.131 0.137 0.277 0.633 North Santiam(RKM 19.000-19.030) 2010 0.298 0.121 0.128 0.275 0.593 North Santiam(RKM 19.000-19.030) 2011 0.199 0.106 0.079 0.169 0.476 North Santiam(RKM 19.000-19.030) 2012 0.414 0.152 0.165 0.398 0.738 North Santiam(RKM 19.000-19.030) 2013 0.345 0.141 0.143 0.319 0.677 Foster Dam Head of Reservoir 2015 2015 0.283 0.142 0.093 0.253 0.634 Foster Dam Head of Reservoir 2016 2016 0.220 0.142 0.043 0.185 0.583 Foster Dam Mid Reservoir 2015 2015 0.265 0.136 0.089 0.235 0.607 Foster Dam Mid Reservoir 2016 2016 0.251 0.142 0.069 0.217 0.614 183 South Santiam(RKM 19.000-19.032) 2006 0.134 0.112 0.013 0.101 0.441 South Santiam(RKM 19.000-19.032) 2007 0.178 0.116 0.046 0.147 0.492 South Santiam(RKM 19.000-19.032) 2008 0.345 0.139 0.144 0.321 0.670 South Santiam(RKM 19.000-19.032) 2009 0.262 0.130 0.099 0.231 0.593 South Santiam(RKM 19.000-19.032) 2010 0.378 0.142 0.162 0.357 0.708 South Santiam(RKM 19.000-19.032) 2011 0.313 0.132 0.133 0.286 0.632 South Santiam(RKM 19.000-19.032) 2012 0.305 0.147 0.094 0.280 0.646 South Santiam(RKM 19.000-19.032) 2013 0.278 0.146 0.079 0.249 0.626 South Santiam(RKM 19.035-19.059) 2006 0.316 0.165 0.068 0.293 0.685 South Santiam(RKM 19.035-19.059) 2007 0.356 0.174 0.087 0.333 0.732 South Santiam(RKM 19.035-19.059) 2008 0.352 0.173 0.084 0.331 0.732 South Santiam(RKM 19.035-19.059) 2010 0.372 0.169 0.105 0.353 0.737 Upper Willamette 2004 0.171 0.123 0.030 0.138 0.504 Upper Willamette 2005 0.161 0.113 0.039 0.130 0.468 Upper Willamette 2006 0.198 0.132 0.035 0.165 0.540 Upper Willamette 2007 0.184 0.121 0.047 0.150 0.509 Upper Willamette 2008 0.263 0.100 0.124 0.243 0.510 Upper Willamette 2009 0.234 0.119 0.094 0.205 0.544 Upper Willamette 2010 0.344 0.138 0.142 0.319 0.674 Upper Willamette 2011 0.188 0.098 0.076 0.162 0.450 Upper Willamette 2012 0.140 0.067 0.067 0.122 0.319 Upper Willamette 2013 0.238 0.122 0.083 0.210 0.544 Upper Willamette 2014 0.295 0.125 0.129 0.269 0.610 Upper Willamette 2015 0.243 0.124 0.095 0.209 0.564 184 Upper Willamette 2016 0.264 0.124 0.100 0.236 0.574 185 C.4 PSUJ posterior mean, SD, lower 95% CI, Median, and upper 95% CI for each release group across all areas. Release Group Year Flow Mean SD 2.5 Median 97.5 Horse Creek 2011 high 0.010 0.013 0.000 0.006 0.041 Horse Creek 2012 mid 0.080 0.044 0.030 0.068 0.197 Horse Creek 2013 mid 0.041 0.031 0.011 0.032 0.122 Horse Creek 2014 low 0.158 0.114 0.036 0.124 0.462 Horse Creek 2015 mid 0.059 0.046 0.014 0.045 0.184 McKenzie River(RKM 0-56) 2002 low 0.058 0.067 0.007 0.036 0.251 McKenzie River(RKM 0-56) 2003 low 0.086 0.087 0.013 0.058 0.344 McKenzie River(RKM 0-56) 2004 mid 0.047 0.041 0.010 0.035 0.157 McKenzie River(RKM 0-56) 2005 high 0.014 0.013 0.003 0.010 0.047 McKenzie River(RKM 0-56) 2007 mid 0.029 0.028 0.005 0.021 0.102 McKenzie River(RKM 0-56) 2008 mid 0.043 0.025 0.014 0.036 0.109 McKenzie River(RKM 0-56) 2009 low 0.107 0.070 0.029 0.087 0.295 McKenzie River(RKM 0-56) 2011 mid 0.154 0.084 0.052 0.134 0.368 McKenzie River(RKM 0-56) 2012 low 0.111 0.059 0.039 0.097 0.270 McKenzie River(RKM 0-56) 2013 low 0.137 0.114 0.028 0.102 0.456 McKenzie River(RKM 0-56) 2014 low 0.209 0.119 0.065 0.182 0.520 McKenzie River(RKM 0-56) 2015 low 0.189 0.117 0.049 0.159 0.493 McKenzie Hatchery 2002 mid 0.314 0.129 0.134 0.289 0.624 McKenzie Hatchery 2003 high 0.009 0.009 0.001 0.006 0.032 McKenzie Hatchery 2004 mid 0.143 0.066 0.062 0.128 0.317 McKenzie Hatchery 2005 mid 0.217 0.093 0.093 0.198 0.445 McKenzie Hatchery 2006 high 0.082 0.030 0.043 0.076 0.156 186 McKenzie Hatchery 2008 mid 0.059 0.070 0.003 0.037 0.255 McKenzie Hatchery 2009 mid 0.103 0.040 0.053 0.095 0.203 McKenzie Hatchery 2010 mid 0.126 0.045 0.062 0.117 0.234 McKenzie River Bypass 2002 mid 0.138 0.075 0.047 0.120 0.334 McKenzie River Bypass 2003 mid 0.085 0.050 0.028 0.072 0.219 McKenzie River Bypass 2004 low 0.256 0.136 0.083 0.222 0.606 McKenzie River Bypass 2005 mid 0.156 0.095 0.045 0.131 0.393 McKenzie River Bypass 2006 mid 0.072 0.031 0.031 0.065 0.150 McKenzie River Bypass 2007 mid 0.087 0.041 0.032 0.079 0.189 McKenzie River Bypass 2008 mid 0.104 0.046 0.040 0.096 0.215 McKenzie River Bypass 2009 mid 0.139 0.070 0.050 0.124 0.318 McKenzie River Bypass 2010 high 0.116 0.056 0.044 0.104 0.259 McKenzie River Bypass 2011 high 0.091 0.048 0.033 0.080 0.211 McKenzie River Bypass 2012 mid 0.094 0.040 0.039 0.086 0.193 McKenzie River Bypass 2013 mid 0.183 0.064 0.086 0.173 0.329 McKenzie River Bypass 2013 high 0.142 0.087 0.043 0.121 0.368 McKenzie River Bypass 2014 high 0.165 0.078 0.063 0.149 0.359 McKenzie River Bypass 2015 low 0.288 0.152 0.097 0.248 0.680 McKenzie River(RKM 57-90) 2010 high 0.041 0.027 0.012 0.034 0.113 McKenzie River(RKM 57-90) 2012 mid 0.110 0.066 0.035 0.094 0.279 McKenzie River(RKM 57-90) 2013 high 0.072 0.048 0.021 0.059 0.205 McKenzie River(RKM 57-90) 2014 mid 0.098 0.068 0.022 0.080 0.282 McKenzie River(RKM 57-90) 2015 high 0.093 0.049 0.034 0.080 0.222 North Fork McKenzie River 2009 high 0.106 0.074 0.026 0.085 0.298 187 North Fork McKenzie River 2010 high 0.155 0.090 0.049 0.132 0.389 North Fork McKenzie River 2011 high 0.048 0.045 0.009 0.034 0.17 North Fork McKenzie River 2012 mid 0.115 0.058 0.045 0.100 0.265 North Fork McKenzie River 2013 high 0.047 0.032 0.013 0.039 0.135 North Fork McKenzie River 2014 low 0.185 0.128 0.045 0.149 0.537 North Fork McKenzie River 2015 high 0.052 0.048 0.010 0.037 0.181 South Fork McKenzie River 2011 high 0.016 0.022 0.000 0.009 0.073 South Fork McKenzie River 2012 mid 0.085 0.089 0.005 0.058 0.341 South Fork McKenzie River Tailrace 2005 high 0.023 0.033 0.002 0.014 0.107 South Fork McKenzie River Tailrace 2006 mid 0.045 0.042 0.006 0.033 0.153 South Fork McKenzie River Tailrace 2011 mid 0.059 0.049 0.014 0.044 0.196 South Fork McKenzie River Tailrace 2012 high 0.043 0.033 0.008 0.033 0.131 McKenzie River(RKM 90.008-90.039) 2011 high 0.020 0.019 0.003 0.014 0.071 McKenzie River(RKM 90.008-90.039) 2012 mid 0.032 0.022 0.009 0.026 0.090 Middle Fork Dexter Dam Tailrace 2011 low 0.329 0.132 0.140 0.310 0.637 Middle Fork Dexter Dam Tailrace 2012 low 0.342 0.106 0.153 0.334 0.564 Middle Fork Dexter Dam Tailrace 2013 low 0.322 0.137 0.102 0.309 0.622 Middle Fork Dexter Dam Tailrace 2013 mid 0.210 0.138 0.041 0.178 0.571 Middle Fork Dexter Dam Tailrace 2014 low 0.411 0.172 0.118 0.395 0.773 Middle Fork Lookout Point Head of Reservoir 2011 low 0.324 0.155 0.094 0.298 0.678 Middle Fork Lookout Point Head of Reservoir 2012 low 0.130 0.050 0.052 0.124 0.245 Middle Fork Lookout Point Head of Reservoir 2013 low 0.075 0.045 0.021 0.065 0.188 Middle Fork Lookout Point Head of Reservoir 2014 low 0.100 0.104 0.008 0.066 0.397 Middle Fork Hills Creek Head of Reservoir 2012 high 0.004 0.003 0.001 0.003 0.013 188 Middle Fork Hills Creek Head of Reservoir 2013 mid 0.024 0.021 0.003 0.019 0.080 Middle Fork Fall Creek Head of Reservoir 2013 mid 0.186 0.073 0.079 0.174 0.354 Middle Fork Fall Creek Head of Reservoir 2013 mid 0.138 0.084 0.046 0.116 0.365 Middle Fork Fall Creek Head of Reservoir 2014 mid 0.137 0.080 0.046 0.116 0.351 Middle Fork Lookout Point Dam Forebay 2013 low 0.081 0.040 0.027 0.074 0.181 Middle Fork Lookout Point Dam Forebay 2013 low 0.253 0.175 0.021 0.218 0.683 Middle Fork Lookout Point Dam Forebay 2014 low 0.132 0.101 0.017 0.104 0.395 Middle Fork Lookout Point Dam Tailrace 2014 low 0.103 0.055 0.033 0.090 0.247 Middle Fork(RKM 23) 2013 mid 0.077 0.056 0.018 0.061 0.237 Middle Fork Fall Creek Tailrace 2013 mid 0.233 0.131 0.080 0.199 0.589 Middle Fork Fall Creek Tailrace 2014 high 0.106 0.084 0.013 0.083 0.332 Middle Fork Hills Creek Dam Tailrace 2013 mid 0.047 0.032 0.009 0.039 0.126 Middle Willamette 2007 low 0.407 0.175 0.149 0.378 0.800 Middle Willamette 2008 mid 0.280 0.068 0.173 0.271 0.438 Middle Willamette 2009 mid 0.219 0.073 0.115 0.207 0.392 Middle Willamette 2010 mid 0.311 0.120 0.134 0.292 0.587 Middle Willamette 2011 mid 0.281 0.092 0.150 0.265 0.498 Middle Willamette 2012 mid 0.362 0.166 0.126 0.334 0.747 Middle Willamette 2013 low 0.362 0.173 0.115 0.333 0.761 Middle Willamette 2014 low 0.398 0.167 0.159 0.368 0.791 Middle Willamette 2015 low 0.408 0.176 0.138 0.384 0.798 Middle Willamette 2016 low 0.381 0.145 0.158 0.361 0.704 Big Cliff Dam Tailrace(RKM 19.066) 2012 low 0.187 0.049 0.111 0.181 0.296 Big Cliff Dam Tailrace(RKM 19.066) 2013 mid 0.116 0.029 0.068 0.113 0.179 189 Big Cliff Dam Tailrace(RKM 19.066) 2014 low 0.108 0.028 0.064 0.104 0.174 Big Cliff Dam Tailrace(RKM 19.067) 2015 high 0.058 0.021 0.026 0.055 0.106 Big Cliff Dam Tailrace(RKM 19.067) 2016 high 0.200 0.137 0.034 0.168 0.546 Detroit Dam Head of Reservoir(RKM 19.091) 2012 low 0.261 0.064 0.154 0.255 0.400 Detroit Dam Head of Reservoir(RKM 19.091) 2013 mid 0.064 0.020 0.034 0.062 0.110 Detroit Dam Head of Reservoir(RKM 19.091) 2014 mid 0.042 0.017 0.017 0.039 0.084 Detroit Dam Head of Reservoir(RKM 19.093) 2014 mid 0.037 0.018 0.015 0.034 0.083 Detroit Dam Head of Reservoir(RKM 19.093) 2015 mid 0.118 0.038 0.053 0.115 0.202 Detroit Dam Head of Reservoir(RKM 19.093) 2016 high 0.123 0.111 0.012 0.089 0.423 Detroit Dam Forebay 2013 mid 0.115 0.027 0.068 0.113 0.171 Detroit Dam Forebay 2014 mid 0.048 0.015 0.025 0.046 0.084 Detroit Dam Forebay 2016 high 0.128 0.111 0.011 0.095 0.421 North Santiam(RKM 19.000-19.030) 2006 mid 0.019 0.021 0.002 0.012 0.075 North Santiam(RKM 19.000-19.030) 2007 low 0.276 0.131 0.104 0.247 0.600 North Santiam(RKM 19.000-19.030) 2008 low 0.120 0.054 0.052 0.108 0.256 North Santiam(RKM 19.000-19.030) 2009 low 0.419 0.167 0.170 0.393 0.785 North Santiam(RKM 19.000-19.030) 2010 mid 0.270 0.110 0.114 0.250 0.536 North Santiam(RKM 19.000-19.030) 2011 low 0.394 0.176 0.130 0.371 0.786 North Santiam(RKM 19.000-19.030) 2012 low 0.104 0.049 0.044 0.093 0.231 North Santiam(RKM 19.000-19.030) 2013 low 0.381 0.158 0.162 0.349 0.758 Foster Dam Head of Reservoir 2015 mid 0.282 0.148 0.095 0.247 0.665 Foster Dam Head of Reservoir 2016 mid 0.129 0.105 0.028 0.096 0.427 Foster Dam Mid Reservoir 2015 low 0.299 0.154 0.099 0.263 0.679 Foster Dam Mid Reservoir 2016 mid 0.221 0.135 0.065 0.184 0.577 190 South Santiam(RKM 19.000-19.032) 2006 low 0.021 0.030 0.001 0.011 0.103 South Santiam(RKM 19.000-19.032) 2007 low 0.235 0.149 0.057 0.195 0.621 South Santiam(RKM 19.000-19.032) 2008 mid 0.266 0.112 0.115 0.243 0.541 South Santiam(RKM 19.000-19.032) 2009 low 0.365 0.171 0.130 0.332 0.771 South Santiam(RKM 19.000-19.032) 2010 mid 0.267 0.109 0.123 0.245 0.536 South Santiam(RKM 19.000-19.032) 2011 mid 0.330 0.137 0.136 0.303 0.657 South Santiam(RKM 19.000-19.032) 2012 low 0.117 0.069 0.039 0.098 0.299 South Santiam(RKM 19.000-19.032) 2013 low 0.234 0.140 0.072 0.197 0.606 South Santiam(RKM 19.035-19.059) 206 low 0.017 0.021 0.001 0.011 0.075 South Santiam(RKM 19.035-19.059) 2007 mid 0.129 0.106 0.022 0.098 0.428 South Santiam(RKM 19.035-19.059) 2008 low 0.162 0.126 0.023 0.126 0.502 South Santiam(RKM 19.035-19.059) 2010 low 0.214 0.142 0.042 0.176 0.589 Upper Willamette 2004 low 0.143 0.120 0.027 0.106 0.482 Upper Willamette 2005 low 0.241 0.158 0.055 0.197 0.660 Upper Willamette 2006 low 0.055 0.053 0.010 0.039 0.194 Upper Willamette 2007 low 0.234 0.150 0.057 0.195 0.631 Upper Willamette 2008 low 0.211 0.077 0.095 0.200 0.394 Upper Willamette 2009 low 0.394 0.175 0.134 0.366 0.783 Upper Willamette 2010 mid 0.265 0.112 0.114 0.243 0.543 Upper Willamette 2011 mid 0.343 0.151 0.116 0.320 0.679 Upper Willamette 2012 low 0.453 0.165 0.165 0.442 0.800 Upper Willamette 2013 low 0.264 0.132 0.090 0.236 0.592 Upper Willamette 2014 low 0.343 0.139 0.140 0.319 0.671 Upper Willamette 2015 low 0.381 0.173 0.129 0.354 0.771 191 Upper Willamette 2016 low 0.297 0.137 0.109 0.270 0.630 192 C.5 PWFF posterior mean, SD, lower 95% CI, Median, and upper 95% CI for each release group across all areas. Release Group Year Mean SD 2.5 Median 97.5 Horse Creek 2011 0.980 0.010 0.956 0.982 0.994 Horse Creek 2012 0.980 0.010 0.956 0.982 0.994 Horse Creek 2013 0.980 0.010 0.956 0.981 0.994 Horse Creek 2014 0.980 0.010 0.957 0.982 0.995 Horse Creek 2015 0.980 0.010 0.956 0.982 0.995 McKenzie River(RKM 0-56) 2002 0.980 0.010 0.956 0.981 0.994 McKenzie River(RKM 0-56) 2003 0.980 0.010 0.956 0.981 0.995 McKenzie River(RKM 0-56) 2004 0.980 0.010 0.956 0.981 0.994 McKenzie River(RKM 0-56) 2005 0.980 0.010 0.956 0.981 0.994 McKenzie River(RKM 0-56) 2007 0.980 0.010 0.957 0.982 0.995 McKenzie River(RKM 0-56) 2008 0.980 0.010 0.957 0.981 0.994 McKenzie River(RKM 0-56) 2009 0.980 0.010 0.956 0.981 0.994 McKenzie River(RKM 0-56) 2011 0.980 0.010 0.955 0.981 0.995 McKenzie River(RKM 0-56) 2012 0.980 0.010 0.956 0.981 0.994 McKenzie River(RKM 0-56) 2013 0.980 0.010 0.955 0.981 0.995 McKenzie River(RKM 0-56) 2014 0.980 0.010 0.956 0.981 0.995 McKenzie River(RKM 0-56) 2015 0.980 0.010 0.956 0.981 0.994 McKenzie Hatchery 2002 0.980 0.010 0.955 0.981 0.994 McKenzie Hatchery 2003 0.980 0.010 0.956 0.982 0.994 McKenzie Hatchery 2004 0.980 0.010 0.956 0.981 0.995 McKenzie Hatchery 2005 0.980 0.010 0.957 0.981 0.994 McKenzie Hatchery 2006 0.980 0.010 0.956 0.981 0.995 193 McKenzie Hatchery 2008 0.980 0.010 0.957 0.982 0.995 McKenzie Hatchery 2009 0.980 0.010 0.957 0.982 0.995 McKenzie Hatchery 2010 0.980 0.010 0.956 0.982 0.995 McKenzie River Bypass 2002 0.980 0.010 0.955 0.981 0.995 McKenzie River Bypass 2003 0.980 0.010 0.956 0.981 0.995 McKenzie River Bypass 2004 0.980 0.010 0.956 0.981 0.995 McKenzie River Bypass 2005 0.980 0.010 0.955 0.981 0.994 McKenzie River Bypass 2006 0.980 0.010 0.957 0.982 0.994 McKenzie River Bypass 2007 0.980 0.010 0.956 0.982 0.995 McKenzie River Bypass 2008 0.980 0.010 0.956 0.982 0.995 McKenzie River Bypass 2009 0.980 0.010 0.956 0.981 0.995 McKenzie River Bypass 2010 0.980 0.010 0.955 0.981 0.995 McKenzie River Bypass 2011 0.980 0.010 0.956 0.981 0.995 McKenzie River Bypass 2012 0.980 0.010 0.956 0.982 0.995 McKenzie River Bypass 2013 0.980 0.010 0.956 0.982 0.995 McKenzie River Bypass 2013 0.980 0.010 0.956 0.982 0.995 McKenzie River Bypass 2014 0.980 0.010 0.956 0.981 0.995 McKenzie River Bypass 2015 0.980 0.010 0.956 0.981 0.995 McKenzie River(RKM 57-90) 2010 0.980 0.010 0.956 0.982 0.995 McKenzie River(RKM 57-90) 2012 0.980 0.010 0.957 0.982 0.995 McKenzie River(RKM 57-90) 2013 0.980 0.010 0.956 0.982 0.995 McKenzie River(RKM 57-90) 2014 0.980 0.010 0.956 0.982 0.995 McKenzie River(RKM 57-90) 2015 0.980 0.010 0.956 0.981 0.994 North Fork McKenzie River 2010 0.980 0.010 0.956 0.981 0.995 194 North Fork McKenzie River 2011 0.980 0.010 0.956 0.982 0.995 North Fork McKenzie River 2011 0.980 0.010 0.956 0.981 0.995 North Fork McKenzie River 2012 0.980 0.010 0.957 0.982 0.995 North Fork McKenzie River 2013 0.980 0.010 0.956 0.982 0.995 North Fork McKenzie River 2014 0.980 0.010 0.956 0.981 0.995 North Fork McKenzie River 2015 0.980 0.010 0.956 0.982 0.994 South Fork McKenzie River 2011 0.980 0.010 0.955 0.982 0.994 South Fork McKenzie River 2012 0.980 0.010 0.956 0.982 0.995 South Fork McKenzie River Tailrace 2005 0.980 0.010 0.956 0.981 0.994 South Fork McKenzie River Tailrace 2006 0.980 0.010 0.957 0.982 0.995 South Fork McKenzie River Tailrace 2011 0.980 0.010 0.957 0.982 0.994 South Fork McKenzie River Tailrace 2012 0.980 0.010 0.957 0.982 0.995 McKenzie River(RKM 90.008-90.039) 2011 0.980 0.010 0.956 0.982 0.995 McKenzie River(RKM 90.008-90.039) 2012 0.980 0.010 0.955 0.981 0.995 Middle Fork Dexter Dam Tailrace 2011 0.980 0.010 0.956 0.981 0.995 Middle Fork Dexter Dam Tailrace 2012 0.980 0.010 0.956 0.981 0.994 Middle Fork Dexter Dam Tailrace 2013 0.980 0.010 0.956 0.981 0.994 Middle Fork Dexter Dam Tailrace 2013 0.980 0.010 0.956 0.982 0.995 Middle Fork Dexter Dam Tailrace 2014 0.980 0.010 0.956 0.981 0.995 Middle Fork Lookout Point Dam Head of Reservoir 2011 0.980 0.010 0.956 0.981 0.994 Middle Fork Lookout Point Dam Head of Reservoir 2012 0.980 0.010 0.956 0.982 0.995 Middle Fork Lookout Point Dam Head of Reservoir 2013 0.980 0.010 0.956 0.981 0.995 Middle Fork Lookout Point Dam Head of Reservoir 2014 0.980 0.010 0.956 0.981 0.994 Middle Fork Hills Creek Dam Head of Reservoir 2012 0.980 0.010 0.956 0.982 0.995 195 Middle Fork Hills Creek Dam Head of Reservoir 2013 0.980 0.010 0.956 0.981 0.994 Middle Fork Fall Creek Head of Reservoir 2013 0.980 0.010 0.957 0.981 0.995 Middle Fork Fall Creek Head of Reservoir 2013 0.980 0.010 0.956 0.982 0.994 Middle Fork Fall Creek Head of Reservoir 2014 0.980 0.010 0.956 0.982 0.995 Middle Fork Lookout Point Dam Forebay 2013 0.980 0.010 0.956 0.981 0.994 Middle Fork Lookout Point Dam Forebay 2013 0.980 0.010 0.956 0.981 0.994 Middle Fork Lookout Point Dam Forebay 2014 0.980 0.010 0.955 0.981 0.994 Middle Fork Lookout Point Dam Tailrace 2014 0.980 0.010 0.956 0.981 0.994 Middle Fork(RKM 23) 2013 0.980 0.010 0.957 0.982 0.995 Middle Fork Fall Creek Tailrace 2013 0.980 0.010 0.956 0.982 0.995 Middle Fork Fall Creek Tailrace 2014 0.980 0.010 0.957 0.982 0.995 Middle Fork Hills Creek Dam Tailrace 2013 0.980 0.010 0.957 0.982 0.995 Middle Willamette 2007 0.980 0.010 0.955 0.982 0.995 Middle Willamette 2008 0.980 0.010 0.956 0.982 0.995 Middle Willamette 2009 0.980 0.010 0.956 0.982 0.995 Middle Willamette 2010 0.980 0.010 0.956 0.981 0.995 Middle Willamette 2011 0.980 0.010 0.957 0.981 0.994 Middle Willamette 2012 0.980 0.010 0.956 0.981 0.995 Middle Willamette 2013 0.980 0.010 0.955 0.981 0.995 Middle Willamette 2014 0.980 0.010 0.956 0.982 0.995 Middle Willamette 2015 0.979 0.010 0.955 0.981 0.995 Middle Willamette 2016 0.980 0.010 0.956 0.982 0.995 Big Cliff Dam Tailrace(RKM 19.066) 2012 0.980 0.010 0.956 0.981 0.994 Big Cliff Dam Tailrace(RKM 19.066) 2013 0.980 0.010 0.957 0.982 0.995 196 Big Cliff Dam Tailrace(RKM 19.066) 2014 0.980 0.010 0.956 0.981 0.995 Big Cliff Dam Tailrace(RKM 19.067) 2015 0.980 0.010 0.955 0.981 0.995 Big Cliff Dam Tailrace(RKM 19.067) 2016 0.980 0.010 0.955 0.981 0.994 Detroit Dam Head of Reservoir(RKM 19.091) 2012 0.980 0.010 0.957 0.981 0.994 Detroit Dam Head of Reservoir(RKM 19.091) 2013 0.980 0.010 0.956 0.982 0.995 Detroit Dam Head of Reservoir(RKM 19.091) 2014 0.980 0.010 0.955 0.981 0.995 Detroit Dam Head of Reservoir(RKM 19.093) 2014 0.980 0.010 0.956 0.982 0.994 Detroit Dam Head of Reservoir(RKM 19.093) 2015 0.980 0.010 0.956 0.981 0.994 Detroit Dam Head of Reservoir(RKM 19.093) 2016 0.980 0.010 0.956 0.981 0.995 Detroit Dam Forebay 2013 0.980 0.010 0.956 0.982 0.995 Detroit Dam Forebay 2014 0.980 0.010 0.956 0.982 0.995 Detroit Dam Forebay 2016 0.980 0.010 0.956 0.981 0.995 North Santiam(RKM 19.000-19.030) 2006 0.980 0.010 0.956 0.982 0.994 North Santiam(RKM 19.000-19.030) 2007 0.980 0.010 0.956 0.982 0.995 North Santiam(RKM 19.000-19.030) 2008 0.980 0.010 0.956 0.982 0.995 North Santiam(RKM 19.000-19.030) 2009 0.980 0.010 0.956 0.981 0.995 North Santiam(RKM 19.000-19.030) 2010 0.980 0.010 0.957 0.981 0.994 North Santiam(RKM 19.000-19.030) 2011 0.980 0.010 0.956 0.981 0.994 North Santiam(RKM 19.000-19.030) 2012 0.980 0.010 0.956 0.982 0.995 North Santiam(RKM 19.000-19.030) 2013 0.980 0.010 0.956 0.981 0.995 Foster Dam Head of Reservoir 2015 0.980 0.010 0.956 0.981 0.995 Foster Dam Head of Reservoir 2016 0.980 0.010 0.955 0.981 0.994 Foster Dam Mid Reservoir 2015 0.980 0.010 0.956 0.981 0.995 Foster Dam Mid Reservoir 2016 0.980 0.010 0.956 0.982 0.994 197 South Santiam(RKM 19.000-19.032) 2006 0.980 0.010 0.956 0.981 0.994 South Santiam(RKM 19.000-19.032) 2007 0.980 0.010 0.955 0.981 0.994 South Santiam(RKM 19.000-19.032) 2008 0.980 0.010 0.956 0.982 0.995 South Santiam(RKM 19.000-19.032) 2009 0.980 0.010 0.956 0.981 0.994 South Santiam(RKM 19.000-19.032) 2010 0.980 0.010 0.956 0.981 0.995 South Santiam(RKM 19.000-19.032) 2011 0.980 0.010 0.956 0.981 0.995 South Santiam(RKM 19.000-19.032) 2012 0.980 0.010 0.955 0.982 0.995 South Santiam(RKM 19.000-19.032) 2013 0.980 0.010 0.956 0.982 0.995 South Santiam(RKM 19.035-19.059) 2006 0.980 0.010 0.955 0.982 0.994 South Santiam(RKM 19.035-19.059) 2007 0.980 0.010 0.957 0.982 0.995 South Santiam(RKM 19.035-19.059) 2008 0.980 0.010 0.956 0.981 0.994 South Santiam(RKM 19.035-19.059) 2010 0.980 0.010 0.956 0.982 0.994 Upper Willamette 2004 0.980 0.010 0.955 0.981 0.995 Upper Willamette 2005 0.980 0.010 0.956 0.982 0.995 Upper Willamette 2006 0.980 0.010 0.956 0.982 0.995 Upper Willamette 2007 0.980 0.010 0.956 0.981 0.995 Upper Willamette 2008 0.980 0.010 0.957 0.981 0.995 Upper Willamette 2009 0.980 0.010 0.957 0.981 0.994 Upper Willamette 2010 0.980 0.010 0.956 0.981 0.994 Upper Willamette 2011 0.980 0.010 0.956 0.981 0.995 Upper Willamette 2012 0.980 0.010 0.955 0.981 0.995 Upper Willamette 2013 0.980 0.010 0.955 0.981 0.995 Upper Willamette 2014 0.980 0.010 0.956 0.982 0.995 Upper Willamette 2015 0.980 0.010 0.956 0.981 0.994 198 Upper Willamette 2016 0.980 0.010 0.956 0.981 0.995 199 C.6 ÏSAS posterior mean, SD, lower 95% CI, Median, and upper 95% CI for each release group from the Middle Fork under the estuary model. Release Group Year Mean SD 2.5 Median 97.5 Middle Fork Dexter Dam Tailrace 2011 0.0021 0.0003 0.0002 0.0019 0.0068 Middle Fork Dexter Dam Tailrace 2012 0.0036 0.0003 0.0008 0.0033 0.0098 Middle Fork Dexter Dam Tailrace 2013 0.0041 0.0005 0.0007 0.0038 0.0119 Middle Fork Dexter Dam Tailrace 2013 0.0094 0.0016 0.0006 0.0092 0.0300 Middle Fork Dexter Dam Tailrace 2014 0.0041 0.0005 0.0005 0.0040 0.0119 Middle Fork Lookout Point Dam Head of Reservoir 2011 0.0042 0.0006 0.0004 0.0039 0.0133 Middle Fork Lookout Point Dam Head of Reservoir 2012 0.0083 0.0002 0.0028 0.0081 0.0167 Middle Fork Lookout Point Dam Head of Reservoir 2013 0.0027 0.0001 0.0005 0.0024 0.0076 Middle Fork Lookout Point Dam Head of Reservoir 2014 0.0024 0.0011 0.0000 0.0018 0.0142 Middle Fork Hills Creek Dam Head of Reservoir 2012 0.0045 0.0002 0.0007 0.0037 0.0141 Middle Fork Hills Creek Dam Head of Reservoir 2013 0.0061 0.0008 0.0005 0.0054 0.0199 Middle Fork Fall Creek Head of Reservoir 2013 0.0127 0.0004 0.0043 0.0123 0.0256 Middle Fork Fall Creek Head of Reservoir 2013 0.0055 0.0011 0.0003 0.0053 0.0191 Middle Fork Fall Creek Head of Reservoir 2014 0.0051 0.0007 0.0005 0.0047 0.0161 Middle Fork Lookout Point Dam Forebay 2013 0.0047 0.0001 0.0014 0.0044 0.0107 Middle Fork Lookout Point Dam Forebay 2013 0.0056 0.0018 0.0001 0.0050 0.0251 Middle Fork Lookout Point Dam Forebay 2014 0.0027 0.0006 0.0001 0.0023 0.0111 Middle Fork Lookout Point Dam Tailrace 2014 0.0022 0.0001 0.0005 0.0020 0.0060 Middle Fork(RKM 23) 2013 0.0077 0.0013 0.0005 0.0073 0.0251 Middle Fork Fall Creek Tailrace 2013 0.0044 0.0015 0.0000 0.0039 0.0210 Middle Fork Fall Creek Tailrace 2014 0.0053 0.0017 0.0001 0.0048 0.0241 Middle Fork Hills Creek Dam Tailrace 2013 0.0139 0.0011 0.0027 0.0138 0.0334 200 C.7 ÏRSS posterior mean, SD, lower 95% CI, Median, and upper 95% CI for each release group from the Middle Fork under the estuary model. Release Group Year Mean SD 2.5 Median 97.5 Middle Fork Dexter Dam Tailrace 2011 0.309 0.128 0.135 0.283 0.623 Middle Fork Dexter Dam Tailrace 2012 0.154 0.030 0.110 0.149 0.227 Middle Fork Dexter Dam Tailrace 2013 0.060 0.012 0.043 0.058 0.091 Middle Fork Dexter Dam Tailrace 2013 0.393 0.169 0.118 0.375 0.752 Middle Fork Dexter Dam Tailrace 2014 0.035 0.018 0.017 0.030 0.081 Middle Fork Lookout Point Dam Head of Reservoir 2011 0.134 0.081 0.050 0.112 0.347 Middle Fork Lookout Point Dam Head of Reservoir 2012 0.082 0.035 0.039 0.073 0.173 Middle Fork Lookout Point Dam Head of Reservoir 2013 0.195 0.119 0.056 0.162 0.520 Middle Fork Lookout Point Dam Head of Reservoir 2014 0.022 0.031 0.002 0.012 0.107 Middle Fork Hills Creek Dam Head of Reservoir 2012 0.132 0.102 0.027 0.102 0.406 Middle Fork Hills Creek Dam Head of Reservoir 2013 0.037 0.039 0.007 0.026 0.139 Middle Fork Fall Creek Head of Reservoir 2013 0.233 0.093 0.107 0.214 0.468 Middle Fork Fall Creek Head of Reservoir 2013 0.319 0.151 0.096 0.296 0.673 Middle Fork Fall Creek Head of Reservoir 2014 0.290 0.142 0.089 0.264 0.636 Middle Fork Lookout Point Dam Forebay 2013 0.161 0.079 0.064 0.141 0.362 Middle Fork Lookout Point Dam Forebay 2013 0.403 0.172 0.114 0.389 0.765 Middle Fork Lookout Point Dam Forebay 2014 0.057 0.057 0.010 0.039 0.212 Middle Fork Lookout Point Dam Tailrace 2014 0.208 0.113 0.073 0.180 0.508 Middle Fork(RKM 23) 2013 0.396 0.170 0.117 0.382 0.756 Middle Fork Fall Creek Tailrace 2013 0.352 0.161 0.113 0.328 0.713 Middle Fork Fall Creek Tailrace 2014 0.403 0.175 0.111 0.385 0.771 Middle Fork Hills Creek Dam Tailrace 2013 0.527 0.160 0.227 0.526 0.831 201 Appendix D D.1 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the McKenzie sub-basin from 2002 to 2015. 202 D.2 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the McKenzie sub-basin from 2002 to 2015. 203 D.3 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the McKenzie sub-basin from 2002 to 2015. 204 D.4 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and a combination of half-precision and mean. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the McKenzie sub-basin from 2002 to 2015. 205 D.5 Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from the base (0.98) to 0.9, 0.49, and the combined mean and precision at half. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the McKenzie sub-basin from 2002 to 2015. 206 D.6 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Middle Willamette from 2007 to 2016. 207 D.7 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Middle Willamette from 2007 to 2016. 208 D.8 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Middle Willamette from 2007 to 2016. 209 D.9 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed, using base ten, for easier visual analysis. Release groups are from the mainstem Middle Willamette from 2007 to 2016. 210 D.10 Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from base (0.98) to 0.9, 0.49, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed, using base ten, for easier visual analysis. Release groups are from the mainstem Middle Willamette from 2007 to 2016. 211 D.11 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the North Santiam sub-basin from 2006 to 2016. 212 D.12 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the North Santiam sub-basin from 2006 to 2016. 213 D.13 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the North Santiam sub-basin from 2006 to 2016. 214 D.14 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and a combination of half-precision and mean. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the North Santiam sub-basin from 2006 to 2016. 215 D.15 Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from the base (0.98) to 0.9, 0.49, and the combined mean and precision at half. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the North Santiam sub-basin from 2006 to 2016. 216 D.16 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the South Santiam sub-basin from 2006 to 2016. 217 D.17 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the South Santiam sub-basin from 2006 to 2016. 218 D.18 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the South Santiam sub-basin from 2006 to 2016. 219 D.19 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and a combination of half-precision and mean. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the South Santiam sub-basin from 2006 to 2016. 220 D.20 Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from the base (0.98) to 0.9, 0.49, and the combined mean and precision at half. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the South Santiam sub-basin from 2006 to 2016. 221 D.21 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS mean was changed from base to half mean, 1.5 times mean, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Upper Willamette from 2004 to 2016. 222 D.22 Sensitivity analysis on vague and informative priors for release-smolt-survival (ÏRSS) and smolt-adult-survival (ÏSAS). ÏRSS precision was changed from base to half-precision, 1.5 times precision, and half mean and precision combined. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Upper Willamette from 2004 to 2016. 223 D.23 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). The ÏSAS mean was changed from base to half mean, 1.5 times the mean, and a combination of half mean and precision. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Upper Willamette from 2004 to 2016. 224 D.24 Sensitivity analysis on vague and informative priors for smolt-adult-survival (ÏSAS) and release-smolt-survival (ÏRSS). ÏSAS precision was changed from base to half-precision, 1.5 times precision, and a combination of half-precision and mean. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Upper Willamette from 2004 to 2016. 225 D.25 Vague and informative prior sensitivity analysis of ÏSAS and ÏRSS on changes to the detection at WFF (PWFF). The mean for WFF detection was changed from the base (0.98) to 0.9, 0.49, and the combined mean and precision at half. Dashed lines represent the prior mean values, and the colours correspond with the different sensitivity changes. Values were log-transformed using a base-10 logarithm for easier visual analysis. Release groups are from the mainstem Upper Willamette from 2004 to 2016. 226 Appendix E E.1 Posterior correlation plot between detection at SUJ (PSUJ) and smolt-adult-survival (ÏSAS), with the posterior correlation coefficient values displayed on the y-axis and release size on the x-axis. Data points are coloured by area (McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, and Upper Willamette). The R-squared, asymptotic equation and the number of data points combined across all six basins are displayed in the bottom right corner. 227 E.2 Posterior correlation plot between ÏSAS and ÏRSS, with posterior correlation values on the y-axis and release size on the x-axis. Data points are coloured by area (McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, and Upper Willamette). The R-squared value, asymptotic equation, and the number of data points combined across all six basins are displayed in the top right corner. 228 Appendix F F.1 Calculated percent change for 1.5 ÏRSS to base mean (left panel) and half ÏRSS to base mean (right panel) relative to release size. Data points are colored by area: McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, and Upper Willamette. The solid black line illustrates the trend between release size and the calculated percentage changes in the estimates; the shaded grey area represents the 95% credible interval, and the R-squared values are displayed at the bottom right of each panel. 229 F.2 Calculated percent change for 1.5 ÏSAS to base mean (left panel) and half ÏSAS to base mean (right panel) relative to release size. Data points are colored by area: McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, and Upper Willamette. The solid black line illustrates the trend between release size and the calculated percentage changes in the estimates; the shaded grey area represents the 95% credible interval, and the R-squared values are displayed at the bottom right of each panel. 230 F.3 Calculated percent change for 1.5 ÏRSS to base precision (left panel) and half ÏRSS to base precision (right panel) relative to release size. Data points are colored by area: McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, and Upper Willamette. The solid black line shows the trend between release size and the calculated percent changes in the estimates; the shaded grey area represents the 95% credible interval, and the R2 values are displayed on the bottom right of each panel. 231 F.4 Calculated percent change for 1.5 ÏSAS to base precision (left panel) and half ÏSAS to base precision (right panel) relative to release size. Data points are colored by area (McKenzie, Middle Fork, Middle Willamette, North Santiam, South Santiam, Upper Willamette). The solid black line shows the trend between release size and the calculated percent changes in the estimates; the shaded grey area represents the 95% credible interval, and the R2 values are displayed on the bottom right of each panel. 232 Appendix G G.1 ÏSAS posterior mean, lower CI, and upper CI for each release group from the Willamette used in the second analysis chapter. Release Group Origin Year Mean Lower CI Upper CI McKenzie River(RKM 0-56) Wild 2002 0.0066 0.0016 0.0151 McKenzie River(RKM 0-56) Wild 2003 0.0064 0.0015 0.0146 McKenzie River(RKM 0-56) Wild 2004 0.0076 0.0023 0.0161 McKenzie River(RKM 0-56) Wild 2005 0.0074 0.0023 0.0157 McKenzie River(RKM 0-56) Wild 2007 0.0070 0.0020 0.0153 McKenzie River(RKM 0-56) Wild 2008 0.0068 0.0025 0.0142 McKenzie River(RKM 0-56) Wild 2009 0.0067 0.0021 0.0143 McKenzie River(RKM 0-56) Wild 2011 0.0051 0.0017 0.0107 McKenzie River(RKM 0-56) Wild 2012 0.0072 0.0026 0.0145 McKenzie River(RKM 0-56) Wild 2013 0.0069 0.0017 0.0152 McKenzie River(RKM 0-56) Wild 2014 0.0061 0.0018 0.0130 McKenzie River(RKM 0-56) Wild 2015 0.0052 0.0014 0.0115 McKenzie Hatchery Hatchery 2004 0.0076 0.0030 0.0145 McKenzie Hatchery Hatchery 2005 0.0056 0.0021 0.0111 McKenzie Hatchery Hatchery 2006 0.0121 0.0063 0.0202 McKenzie River Bypass Wild 2008 0.0098 0.0042 0.0179 McKenzie River Bypass Wild 2009 0.0087 0.0033 0.0165 McKenzie River Bypass Wild 2010 0.0065 0.0026 0.0127 McKenzie River Bypass Wild 2011 0.0078 0.0030 0.0154 233 McKenzie River Bypass Wild 2013 0.0097 0.0048 0.0164 McKenzie River Bypass Wild 2013 0.0045 0.0012 0.0101 McKenzie River Bypass Wild 2014 0.0069 0.0026 0.0134 McKenzie River Bypass Wild 2015 0.0070 0.0019 0.0151 Middle Willamette Wild 2011 0.0070 0.0032 0.0126 Middle Willamette Wild 2012 0.0035 0.0009 0.0080 Middle Willamette Wild 2013 0.0038 0.00086 0.0087 Middle Willamette Wild 2014 0.0046 0.0012 0.0102 Big Cliff Dam Tailrace(RKM 19.066) Hatchery 2012 0.0058 0.0034 0.0089 Big Cliff Dam Tailrace(RKM 19.066) Hatchery 2013 0.0104 0.0064 0.0153 Big Cliff Dam Tailrace(RKM 19.066) Hatchery 2014 0.0060 0.0037 0.0091 Detroit Dam Head of Reservoir(RKM 19.091) Hatchery 2012 0.0096 0.0057 0.0146 Detroit Dam Head of Reservoir(RKM 19.091) Hatchery 2013 0.0077 0.0044 0.0121 Detroit Dam Head of Reservoir(RKM 19.091) Hatchery 2014 0.0073 0.0034 0.0130 Detroit Dam Head of Reservoir(RKM 19.093) Hatchery 2014 0.0093 0.0041 0.0174 Detroit Dam Head of Reservoir(RKM 19.093) Hatchery 2015 0.0076 0.0039 0.0121 Detroit Dam Head of Reservoir(RKM 19.093) Hatchery 2016 0.0027 0.0003 0.0075 North Santiam(RKM 19.000-19.030) Wild 2007 0.0063 0.0020 0.0131 North Santiam(RKM 19.000-19.030) Wild 2008 0.0090 0.0038 0.0167 North Santiam(RKM 19.000-19.030) Wild 2009 0.0045 0.0012 0.0098 North Santiam(RKM 19.000-19.030) Wild 2010 0.0097 0.0040 0.0178 North Santiam(RKM 19.000-19.030) Wild 2011 0.0068 0.0021 0.0140 234 South Santiam(RKM 19.000-19.032) Wild 2007 0.0058 0.0014 0.0130 South Santiam(RKM 19.000-19.032) Wild 2008 0.0051 0.0018 0.0104 South Santiam(RKM 19.000-19.032) Wild 2009 0.0047 0.0012 0.0106 South Santiam(RKM 19.000-19.032) Wild 2010 0.0062 0.0022 0.0122 South Santiam(RKM 19.000-19.032) Wild 2011 0.0040 0.0012 0.0084 South Santiam(RKM 19.000-19.032) Wild 2012 0.0086 0.0030 0.0170 Upper Willamette Wild 2007 0.0056 0.0013 0.0126 Upper Willamette Wild 2008 0.0080 0.0037 0.0141 Upper Willamette Wild 2009 0.0038 0.0010 0.0086 Upper Willamette Wild 2010 0.0051 0.0017 0.0104 Upper Willamette Wild 2011 0.0048 0.0014 0.0099 Upper Willamette Wild 2012 0.0050 0.0017 0.0098 Upper Willamette Wild 2013 0.0046 0.0014 0.0100 Upper Willamette Wild 2014 0.0042 0.0013 0.0088 Upper Willamette Wild 2015 0.0043 0.0011 0.0098 Upper Willamette Wild 2016 0.0048 0.0014 0.0102 G.2 ÏSAS posterior mean, lower CI, and upper CI for each release group from the Snake River. Release Group Origin Year Mean Lower CI Upper CI Catherine Creek Hatchery 2001 0.0039 0.0026 0.0055 Catherine Creek Hatchery 2002 0.0099 0.0074 0.0124 Catherine Creek Hatchery 2003 0.0033 0.0020 0.0047 235 Catherine Creek Hatchery 2004 0.0044 0.0025 0.0063 Catherine Creek Hatchery 2005 0.0052 0.0032 0.0075 Catherine Creek Hatchery 2006 0.0079 0.0058 0.0105 Catherine Creek Hatchery 2007 0.0053 0.0036 0.0071 Catherine Creek Hatchery 2008 0.0273 0.0238 0.0306 Catherine Creek Hatchery 2009 0.0210 0.0179 0.0243 Catherine Creek Hatchery 2010 0.0120 0.0097 0.0146 Catherine Creek Hatchery 2011 0.0064 0.0045 0.0086 Catherine Creek Hatchery 2012 0.0105 0.0083 0.0129 Catherine Creek Hatchery 2013 0.0163 0.0127 0.0203 Catherine Creek Hatchery 2014 0.0060 0.0042 0.0081 Catherine Creek Hatchery 2015 0.0057 0.0037 0.0074 Catherine Creek Hatchery 2016 0.0037 0.0024 0.0050 Catherine Creek Hatchery 2017 0.0032 0.0020 0.0044 Catherine Creek Hatchery 2018 0.0037 0.0023 0.0051 Catherine Creek Hatchery 2019 0.0078 0.0060 0.0095 Catherine Creek Hatchery 2020 0.0072 0.0057 0.0089 Catherine Creek Hatchery 2021 0.0048 0.0036 0.0062 Catherine Creek Hatchery 2022 0.0054 0.0041 0.0067 Clearwater Hatchery 2006 0.0088 0.0078 0.0098 Clearwater Hatchery 2007 0.0043 0.0036 0.0049 Clearwater Hatchery 2008 0.0133 0.0120 0.0148 236 Clearwater Hatchery 2009 0.0102 0.0093 0.0112 Clearwater Hatchery 2010 0.0065 0.0058 0.0073 Clearwater Hatchery 2011 0.0021 0.0017 0.0026 Clearwater Hatchery 2012 0.0069 0.0061 0.0076 Clearwater Hatchery 2013 0.0088 0.0078 0.0096 Clearwater Hatchery 2014 0.0049 0.0042 0.0056 Clearwater Hatchery 2015 0.0042 0.0035 0.0051 Clearwater Hatchery 2016 0.0041 0.0035 0.0047 Clearwater Hatchery 2017 0.0021 0.0017 0.0026 Clearwater Hatchery 2018 0.0014 0.0011 0.0018 Clearwater Hatchery 2019 0.0008 0.0001 0.0011 Clearwater Hatchery 2020 0.0042 0.0036 0.0048 Clearwater Hatchery 2021 0.0045 0.0039 0.0051 Clearwater Hatchery 2022 0.0029 0.0025 0.0034 Dworshak Hatchery 2000 0.0153 0.0141 0.0166 Dworshak Hatchery 2001 0.0044 0.0037 0.0052 Dworshak Hatchery 2002 0.0072 0.0063 0.0083 Dworshak Hatchery 2003 0.0030 0.0025 0.0035 Dworshak Hatchery 2004 0.0053 0.0046 0.0061 Dworshak Hatchery 2005 0.0028 0.0023 0.0034 Dworshak Hatchery 2006 0.0056 0.0050 0.0064 Dworshak Hatchery 2007 0.0048 0.0041 0.0055 237 Dworshak Hatchery 2008 0.0100 0.0091 0.0112 Dworshak Hatchery 2009 0.0053 0.0045 0.0061 Dworshak Hatchery 2010 0.0069 0.0062 0.0077 Dworshak Hatchery 2011 0.0024 0.0019 0.0029 Dworshak Hatchery 2012 0.0066 0.0057 0.0074 Dworshak Hatchery 2013 0.0084 0.0075 0.0093 Dworshak Hatchery 2014 0.0037 0.0031 0.0043 Dworshak Hatchery 2015 0.0014 0.0010 0.0019 Dworshak Hatchery 2016 0.0016 0.0011 0.0020 Dworshak Hatchery 2017 0.0007 0.0004 0.0010 Dworshak Hatchery 2018 0.0016 0.0011 0.0020 Dworshak Hatchery 2019 0.0023 0.0018 0.0029 Dworshak Hatchery 2020 0.0055 0.0047 0.0063 Dworshak Hatchery 2021 0.0037 0.0030 0.0043 Dworshak Hatchery 2022 0.0039 0.0033 0.0046 Rapid River Hatchery 2000 0.0262 0.0245 0.0280 Rapid River Hatchery 2001 0.0138 0.0125 0.0154 Rapid River Hatchery 2002 0.0102 0.0090 0.0114 Rapid River Hatchery 2003 0.0032 0.0027 0.0039 Rapid River Hatchery 2004 0.0043 0.0037 0.0050 Rapid River Hatchery 2005 0.0032 0.0026 0.0038 Rapid River Hatchery 2006 0.0073 0.0064 0.0082 238 Rapid River Hatchery 2007 0.0048 0.0041 0.0055 Rapid River Hatchery 2008 0.0182 0.0169 0.0195 Rapid River Hatchery 2009 0.0144 0.0132 0.0156 Rapid River Hatchery 2010 0.0073 0.0065 0.0082 Rapid River Hatchery 2011 0.0035 0.0029 0.0041 Rapid River Hatchery 2012 0.0113 0.0102 0.0124 Rapid River Hatchery 2013 0.0146 0.0134 0.0158 Rapid River Hatchery 2014 0.0055 0.0048 0.0062 Rapid River Hatchery 2015 0.0027 0.0022 0.0032 Rapid River Hatchery 2016 0.0024 0.0020 0.0029 Rapid River Hatchery 2017 0.0029 0.0023 0.0035 Rapid River Hatchery 2018 0.0027 0.0021 0.0033 Rapid River Hatchery 2019 0.0038 0.0030 0.0046 Rapid River Hatchery 2020 0.0091 0.0080 0.0101 Rapid River Hatchery 2021 0.0039 0.0032 0.0046 Rapid River Hatchery 2022 0.0034 0.0028 0.0039 Sawtooth Hatchery 2007 0.0071 0.0056 0.0088 Sawtooth Hatchery 2008 0.0120 0.0090 0.0145 Sawtooth Hatchery 2009 0.0043 0.0029 0.0058 Sawtooth Hatchery 2010 0.0055 0.0040 0.0072 Sawtooth Hatchery 2011 0.0012 0.0007 0.0019 Sawtooth Hatchery 2012 0.0054 0.0040 0.0070 239 Sawtooth Hatchery 2013 0.0100 0.0083 0.0118 Sawtooth Hatchery 2014 0.0042 0.0031 0.0054 Sawtooth Hatchery 2015 0.0024 0.0016 0.0032 Sawtooth Hatchery 2016 0.00277 0.0019 0.0036 Sawtooth Hatchery 2017 0.0010 0.0005 0.0016 Sawtooth Hatchery 2018 0.0020 0.0013 0.0028 Sawtooth Hatchery 2019 0.0016 0.0009 0.0024 Sawtooth Hatchery 2020 0.0034 0.0024 0.0043 Sawtooth Hatchery 2021 0.0043 0.0033 0.0053 Sawtooth Hatchery 2022 0.0028 0.0020 0.0037 Clearwater River Wild 2006 0.0039 0.0017 0.0063 Clearwater River Wild 2007 0.0104 0.0036 0.0183 Clearwater River Wild 2008 0.0176 0.0116 0.0246 Clearwater River Wild 2009 0.0141 0.0083 0.0200 Clearwater River Wild 2010 0.0105 0.0084 0.0129 Clearwater River Wild 2011 0.0049 0.0020 0.0078 Clearwater River Wild 2012 0.0069 0.0035 0.0111 Clearwater River Wild 2013 0.0073 0.0033 0.0116 Clearwater River Wild 2014 0.0036 0.0000 0.0074 Clearwater River Wild 2015 0.0020 0.0000 0.0057 Clearwater River Wild 2016 0.0013 0.0000 0.0039 Clearwater River Wild 2017 0.0022 0.0000 0.0053 240 Clearwater River Wild 2018 0.0100 0.0042 0.0162 Clearwater River Wild 2019 0.0031 0.0000 0.0072 Clearwater River Wild 2020 0.0139 0.0071 0.0209 Clearwater River Wild 2021 0.0037 0.0000 0.0079 Clearwater River Wild 2022 0.0032 0.0000 0.0077 Grande Ronde Basin Wild 2006 0.0104 0.0077 0.0131 Grande Ronde Basin Wild 2007 0.0149 0.0114 0.0190 Grande Ronde Basin Wild 2008 0.0380 0.0312 0.0445 Grande Ronde Basin Wild 2009 0.0277 0.0223 0.0331 Grande Ronde Basin Wild 2010 0.0081 0.0058 0.0105 Grande Ronde Basin Wild 2011 0.0049 0.0031 0.0072 Grande Ronde Basin Wild 2012 0.0200 0.0159 0.0244 Grande Ronde Basin Wild 2013 0.0192 0.0151 0.0228 Grande Ronde Basin Wild 2014 0.0150 0.0118 0.0189 Grande Ronde Basin Wild 2015 0.0068 0.0031 0.0108 Grande Ronde Basin Wild 2016 0.0069 0.0043 0.0094 Grande Ronde Basin Wild 2017 0.0028 0.0013 0.0044 Grande Ronde Basin Wild 2018 0.0076 0.0051 0.0103 Grande Ronde Basin Wild 2019 0.0122 0.0082 0.0163 Grande Ronde Basin Wild 2020 0.0197 0.0149 0.0250 Grande Ronde Basin Wild 2021 0.0105 0.0070 0.0143 Grande Ronde Basin Wild 2022 0.0122 0.0081 0.0165 241 Imnaha River Wild 2006 0.0069 0.0027 0.0123 Imnaha River Wild 2007 0.0071 0.0050 0.0093 Imnaha River Wild 2008 0.0389 0.0339 0.0439 Imnaha River Wild 2009 0.0244 0.0200 0.0290 Imnaha River Wild 2010 0.0093 0.0070 0.0122 Imnaha River Wild 2011 0.0041 0.0021 0.0063 Imnaha River Wild 2012 0.0113 0.0077 0.0149 Imnaha River Wild 2013 0.0146 0.0111 0.0181 Imnaha River Wild 2014 0.0050 0.0031 0.0069 Imnaha River Wild 2015 0.0048 0.0029 0.0069 Imnaha River Wild 2016 0.0055 0.0026 0.0090 Imnaha River Wild 2017 0.0015 0.0000 0.0036 Imnaha River Wild 2018 0.0044 0.0024 0.0073 Imnaha River Wild 2019 0.0067 0.0029 0.0111 Imnaha River Wild 2020 0.0240 0.0185 0.0298 Imnaha River Wild 2021 0.0051 0.0026 0.0079 Imnaha River Wild 2022 0.0028 0.0010 0.0048 Middle Fork Salmon River Wild 2006 0.0039 0.0000 0.0115 Middle Fork Salmon River Wild 2007 0.0117 0.0028 0.0210 Middle Fork Salmon River Wild 2008 0.0353 0.0296 0.0411 Middle Fork Salmon River Wild 2009 0.0156 0.0116 0.0194 Middle Fork Salmon River Wild 2010 0.0112 0.0080 0.0143 242 Middle Fork Salmon River Wild 2011 0.0041 0.0022 0.0059 Middle Fork Salmon River Wild 2012 0.0135 0.0098 0.0173 Middle Fork Salmon River Wild 2013 0.0176 0.0132 0.0222 Middle Fork Salmon River Wild 2014 0.0056 0.0034 0.0079 Middle Fork Salmon River Wild 2015 0.0008 0.0000 0.0018 Middle Fork Salmon River Wild 2016 0.0049 0.0024 0.0077 Middle Fork Salmon River Wild 2017 0.0013 0.0000 0.0027 Middle Fork Salmon River Wild 2018 0.0028 0.0012 0.0045 Middle Fork Salmon River Wild 2019 0.0092 0.0059 0.0128 Middle Fork Salmon River Wild 2020 0.0148 0.0111 0.0187 Middle Fork Salmon River Wild 2021 0.0111 0.0082 0.0145 Middle Fork Salmon River Wild 2022 0.0074 0.0050 0.0102 Snake River (Above LGR) Wild 2000 0.0259 0.0197 0.0322 Snake River (Above LGR) Wild 2001 0.0186 0.0097 0.0288 Snake River (Above LGR) Wild 2002 0.0114 0.0095 0.0134 Snake River (Above LGR) Wild 2003 0.0035 0.0027 0.0043 Snake River (Above LGR) Wild 2004 0.0068 0.0057 0.0080 Snake River (Above LGR) Wild 2005 0.0029 0.0023 0.0035 Snake River (Above LGR) Wild 2006 0.0084 0.0072 0.0095 Snake River (Above LGR) Wild 2007 0.0116 0.0101 0.0129 Snake River (Above LGR) Wild 2008 0.0358 0.0337 0.0381 Snake River (Above LGR) Wild 2009 0.0193 0.0176 0.0210 243 Snake River (Above LGR) Wild 2010 0.0092 0.0083 0.0102 Snake River (Above LGR) Wild 2011 0.0042 0.0035 0.0049 Snake River (Above LGR) Wild 2012 0.0148 0.0135 0.0163 Snake River (Above LGR) Wild 2013 0.0154 0.0140 0.0170 Snake River (Above LGR) Wild 2014 0.0061 0.0053 0.0070 Snake River (Above LGR) Wild 2015 0.0028 0.0020 0.0036 Snake River (Above LGR) Wild 2016 0.0044 0.0036 0.0052 Snake River (Above LGR) Wild 2017 0.0019 0.0014 0.0024 Snake River (Above LGR) Wild 2018 0.0054 0.0046 0.0063 Snake River (Above LGR) Wild 2019 0.0088 0.0074 0.0102 Snake River (Above LGR) Wild 2020 0.0177 0.0158 0.0195 Snake River (Above LGR) Wild 2021 0.0087 0.0075 0.0100 Snake River (Above LGR) Wild 2022 0.0068 0.0057 0.0080 South Fork Salmon River Wild 2006 0.0094 0.0054 0.0140 South Fork Salmon River Wild 2007 0.0160 0.0114 0.0206 South Fork Salmon River Wild 2008 0.0483 0.0394 0.0575 South Fork Salmon River Wild 2009 0.0185 0.0136 0.0237 South Fork Salmon River Wild 2010 0.0153 0.0103 0.021 South Fork Salmon River Wild 2011 0.0027 0.0009 0.0057 South Fork Salmon River Wild 2012 0.0124 0.0067 0.0186 South Fork Salmon River Wild 2013 0.0148 0.0070 0.0228 South Fork Salmon River Wild 2014 0.0077 0.0019 0.0145 244 South Fork Salmon River Wild 2015 0.0047 0.0000 0.0105 South Fork Salmon River Wild 2016 0.0046 0.0012 0.0082 South Fork Salmon River Wild 2017 0.0014 0.0000 0.0033 South Fork Salmon River Wild 2018 0.0068 0.0033 0.0109 South Fork Salmon River Wild 2019 0.0082 0.0044 0.0122 South Fork Salmon River Wild 2020 0.0239 0.0173 0.0307 South Fork Salmon River Wild 2021 0.0094 0.0059 0.0134 South Fork Salmon River Wild 2022 0.0107 0.0064 0.0146 Upper Salmon River Wild 2006 0.0066 0.0043 0.0090 Upper Salmon River Wild 2007 0.0101 0.0065 0.0139 Upper Salmon River Wild 2008 0.0391 0.0310 0.0472 Upper Salmon River Wild 2009 0.0194 0.0149 0.0248 Upper Salmon River Wild 2010 0.0111 0.0083 0.0137 Upper Salmon River Wild 2011 0.0046 0.0031 0.0062 Upper Salmon River Wild 2012 0.0188 0.0154 0.0225 Upper Salmon River Wild 2013 0.0164 0.0131 0.0202 Upper Salmon River Wild 2014 0.0040 0.0023 0.0058 Upper Salmon River Wild 2015 0.0013 0.0000 0.0027 Upper Salmon River Wild 2016 0.0042 0.0027 0.0058 Upper Salmon River Wild 2017 0.0025 0.0015 0.0038 Upper Salmon River Wild 2018 0.0066 0.0049 0.0085 Upper Salmon River Wild 2019 0.0108 0.0078 0.0139 245 Upper Salmon River Wild 2020 0.0165 0.0131 0.0201 Upper Salmon River Wild 2021 0.0092 0.0070 0.0115 Upper Salmon River Wild 2022 0.0054 0.0035 0.0077 G.3 ÏSAS posterior mean, lower CI, and upper CI for each release group from the Middle Columbia. Release Group Origin Year Mean Lower CI Upper CI Carson Hatchery 2000 0.0285 0.0263 0.0306 Carson Hatchery 2001 0.0149 0.0133 0.0165 Carson Hatchery 2002 0.0101 0.0089 0.0115 Carson Hatchery 2003 0.0023 0.0017 0.0029 Carson Hatchery 2004 0.0062 0.0052 0.0073 Carson Hatchery 2005 0.0030 0.0023 0.0038 Carson Hatchery 2006 0.0042 0.0034 0.0051 Carson Hatchery 2007 0.0056 0.0046 0.0066 Carson Hatchery 2008 0.0148 0.0132 0.0165 Carson Hatchery 2009 0.0142 0.0126 0.0158 Carson Hatchery 2010 0.0075 0.0064 0.0087 Carson Hatchery 2011 0.0033 0.0026 0.0041 Carson Hatchery 2012 0.0054 0.0044 0.0063 Carson Hatchery 2013 0.0105 0.0091 0.0119 Carson Hatchery 2014 0.0056 0.0046 0.0066 Carson Hatchery 2015 0.0038 0.0030 0.0046 246 Carson Hatchery 2016 0.0023 0.0017 0.0030 Carson Hatchery 2017 0.0017 0.0012 0.0024 Carson Hatchery 2018 0.0022 0.0016 0.0029 Carson Hatchery 2019 0.0033 0.0026 0.0041 Carson Hatchery 2020 0.0095 0.0083 0.0110 Carson Hatchery 2021 0.0047 0.0039 0.0058 Carson Hatchery 2022 0.0054 0.0045 0.0065 Cle Elum Hatchery 2000 0.0361 0.0334 0.0391 Cle Elum Hatchery 2001 0.0028 0.0020 0.0037 Cle Elum Hatchery 2002 0.0136 0.0118 0.0154 Cle Elum Hatchery 2003 0.0059 0.0048 0.0071 Cle Elum Hatchery 2004 0.0154 0.0131 0.0178 Cle Elum Hatchery 2005 0.0066 0.0048 0.0084 Cle Elum Hatchery 2006 0.0123 0.0106 0.0143 Cle Elum Hatchery 2007 0.0101 0.0087 0.0116 Cle Elum Hatchery 2008 0.0315 0.0286 0.0343 Cle Elum Hatchery 2009 0.0182 0.0164 0.0200 Cle Elum Hatchery 2010 0.0151 0.0133 0.0171 Cle Elum Hatchery 2011 0.0093 0.0079 0.0108 Cle Elum Hatchery 2012 0.0122 0.0108 0.0137 Cle Elum Hatchery 2013 0.0139 0.0122 0.0159 Cle Elum Hatchery 2014 0.0058 0.0048 0.0070 247 Cle Elum Hatchery 2015 0.0102 0.0086 0.0118 Cle Elum Hatchery 2016 0.0087 0.0074 0.0101 Cle Elum Hatchery 2017 0.0062 0.0049 0.0075 Cle Elum Hatchery 2018 0.0054 0.0043 0.0066 Cle Elum Hatchery 2019 0.0077 0.0062 0.0093 Cle Elum Hatchery 2020 0.0120 0.0097 0.0141 Cle Elum Hatchery 2021 0.0092 0.0069 0.0116 Cle Elum Hatchery 2022 0.0057 0.0038 0.0077 Warm Springs Hatchery 2007 0.0030 0.0024 0.0037 Warm Springs Hatchery 2008 0.0084 0.0074 0.0094 Warm Springs Hatchery 2009 0.0065 0.0056 0.0075 Warm Springs Hatchery 2010 0.0021 0.0015 0.0027 Warm Springs Hatchery 2011 0.0019 0.0013 0.0024 Warm Springs Hatchery 2012 0.0066 0.0056 0.0078 Warm Springs Hatchery 2013 0.0118 0.0103 0.0133 Warm Springs Hatchery 2014 0.0089 0.0077 0.0103 Warm Springs Hatchery 2015 0.0038 0.0030 0.0047 Warm Springs Hatchery 2016 0.0029 0.0022 0.0038 Warm Springs Hatchery 2017 0.0005 0.0002 0.0009 Warm Springs Hatchery 2018 0.0011 0.0007 0.0016 Warm Springs Hatchery 2019 0.0033 0.0025 0.0041 Warm Springs Hatchery 2020 0.0029 0.0023 0.0036 248 Warm Springs Hatchery 2021 0.0053 0.0030 0.0064 Warm Springs Hatchery 2022 0.0003 0.0000 0.0014 John Day River Wild 2000 0.1077 0.0915 0.1233 John Day River Wild 2001 0.0386 0.0329 0.0450 John Day River Wild 2002 0.0378 0.0303 0.0452 John Day River Wild 2003 0.0277 0.0234 0.0322 John Day River Wild 2004 0.0314 0.0246 0.0381 John Day River Wild 2005 0.0185 0.0149 0.0226 John Day River Wild 2006 0.0206 0.0168 0.0249 John Day River Wild 2007 0.0433 0.0366 0.0504 John Day River Wild 2008 0.0551 0.0476 0.0630 John Day River Wild 2009 0.0677 0.0592 0.0761 John Day River Wild 2010 0.0355 0.0302 0.0416 John Day River Wild 2011 0.0090 0.0058 0.0123 John Day River Wild 2012 0.0312 0.0263 0.0361 John Day River Wild 2013 0.0418 0.0339 0.0497 John Day River Wild 2014 0.0383 0.0303 0.0467 John Day River Wild 2015 0.0354 0.0236 0.0465 John Day River Wild 2016 0.0210 0.0156 0.0262 John Day River Wild 2017 0.0092 0.0064 0.0124 John Day River Wild 2018 0.0234 0.0182 0.0292 John Day River Wild 2019 0.0156 0.0090 0.0228 249 John Day River Wild 2020 0.0424 0.0297 0.0556 John Day River Wild 2021 0.0243 0.0141 0.0360 John Day River Wild 2022 0.0230 0.0124 0.0354 Yakima River Wild 2000 0.0547 0.0500 0.0599 Yakima River Wild 2001 0.0089 0.0064 0.0118 Yakima River Wild 2002 0.0231 0.0192 0.0275 Yakima River Wild 2003 0.0167 0.0143 0.0192 Yakima River Wild 2004 0.0263 0.0225 0.0302 Yakima River Wild 2005 0.0128 0.0091 0.0167 Yakima River Wild 2006 0.0167 0.0128 0.0212 Yakima River Wild 2007 0.0150 0.0092 0.0208 Yakima River Wild 2008 0.0469 0.0397 0.0541 Yakima River Wild 2009 0.0436 0.0363 0.0516 Yakima River Wild 2010 0.0138 0.0105 0.0173 Yakima River Wild 2011 0.0085 0.0058 0.0113 Yakima River Wild 2012 0.0278 0.0215 0.0346 Yakima River Wild 2013 0.0165 0.0122 0.0211 Yakima River Wild 2014 0.0208 0.0148 0.0274 Yakima River Wild 2015 0.0145 0.0091 0.0203 Yakima River Wild 2016 0.0041 0.0000 0.0123 Yakima River Wild 2017 0.0129 0.0048 0.0224 Yakima River Wild 2018 0.0105 0.0038 0.0186 250 Yakima River Wild 2019 0.0218 0.0130 0.0312 Yakima River Wild 2020 0.0257 0.0142 0.0371 Yakima River Wild 2021 0.0123 0.0054 0.0214 Yakima River Wild 2022 0.0099 0.0031 0.0194 G.4 ÏSAS posterior mean, lower CI, and upper CI for each release group from the Upper Columbia. Release Group Origin Year Mean Lower CI Upper CI Leavenworth Hatchery 2000 0.0184 0.0148 0.0223 Leavenworth Hatchery 2001 0.0024 0.0011 0.0037 Leavenworth Hatchery 2002 0.0028 0.0026 0.0030 Leavenworth Hatchery 2003 0.0042 0.0039 0.0044 Leavenworth Hatchery 2004 0.0034 0.0031 0.0037 Leavenworth Hatchery 2005 0.0009 0.0004 0.0015 Leavenworth Hatchery 2006 0.0089 0.0072 0.0107 Leavenworth Hatchery 2007 0.0046 0.0036 0.0059 Leavenworth Hatchery 2008 0.0180 0.0155 0.0204 Leavenworth Hatchery 2009 0.0059 0.0044 0.0075 Leavenworth Hatchery 2010 0.0081 0.0066 0.0096 Leavenworth Hatchery 2011 0.0035 0.0023 0.0047 Leavenworth Hatchery 2012 0.0105 0.0087 0.0124 Leavenworth Hatchery 2013 0.0068 0.0054 0.0083 Leavenworth Hatchery 2014 0.0060 0.0045 0.0074 251 Leavenworth Hatchery 2015 0.0014 0.0007 0.0021 Leavenworth Hatchery 2016 0.0019 0.0011 0.0027 Leavenworth Hatchery 2017 0.0008 0.0004 0.0012 Leavenworth Hatchery 2018 0.0026 0.0019 0.0034 Leavenworth Hatchery 2019 0.0059 0.0047 0.0073 Leavenworth Hatchery 2020 0.0149 0.0124 0.0174 Leavenworth Hatchery 2021 0.0124 0.0097 0.0152 Leavenworth Hatchery 2022 0.0080 0.0045 0.0114 Winthrop Hatchery 2009 0.0066 0.0024 0.0122 Winthrop Hatchery 2010 0.0051 0.0030 0.0074 Winthrop Hatchery 2011 0.0072 0.0043 0.0107 Winthrop Hatchery 2012 0.0106 0.0080 0.0135 Winthrop Hatchery 2013 0.0119 0.0099 0.014 Winthrop Hatchery 2014 0.0057 0.0034 0.0081 Winthrop Hatchery 2015 0.0062 0.0042 0.0080 Winthrop Hatchery 2016 0.0056 0.0044 0.0069 Winthrop Hatchery 2017 0.0070 0.0055 0.0085 Winthrop Hatchery 2018 0.0023 0.0014 0.0033 Winthrop Hatchery 2019 0.0013 0.0007 0.0020 Winthrop Hatchery 2020 0.0082 0.0053 0.0109 Winthrop Hatchery 2021 0.0080 0.0060 0.0099 Winthrop Hatchery 2022 0.0051 0.0032 0.0087 252 Winthrop Hatchery 2009 0.0043 0.0012 0.0086 Winthrop Hatchery 2010 0.0040 0.0025 0.0056 Winthrop Hatchery 2011 0.0051 0.0032 0.0073 Winthrop Hatchery 2012 0.0078 0.0059 0.0101 Winthrop Hatchery 2013 0.0094 0.0079 0.0110 Winthrop Hatchery 2014 0.0046 0.0028 0.0065 Winthrop Hatchery 2015 0.0043 0.0030 0.0056 Winthrop Hatchery 2016 0.0043 0.0034 0.0053 Winthrop Hatchery 2017 0.0048 0.0040 0.0058 Winthrop Hatchery 2018 0.0019 0.0011 0.0028 Winthrop Hatchery 2019 0.0009 0.0005 0.0013 Winthrop Hatchery 2020 0.0048 0.0035 0.0062 Winthrop Hatchery 2021 0.0063 0.0052 0.0074 Winthrop Hatchery 2022 0.0046 0.0037 0.0056 Entiat and Methow River Wild 2006 0.0043 0.0011 0.0084 Entiat and Methow River Wild 2007 0.0075 0.0026 0.0129 Entiat and Methow River Wild 2008 0.0294 0.0253 0.0336 Entiat and Methow River Wild 2009 0.0222 0.0158 0.0288 Entiat and Methow River Wild 2010 0.0185 0.0147 0.0227 Entiat and Methow River Wild 2011 0.0040 0.0009 0.0078 Entiat and Methow River Wild 2012 0.0123 0.0082 0.0168 Entiat and Methow River Wild 2013 0.0220 0.0163 0.0283 253 Entiat and Methow River Wild 2014 0.0171 0.0125 0.0220 Entiat and Methow River Wild 2015 0.0070 0.0021 0.0130 Entiat and Methow River Wild 2016 0.0051 0.0019 0.0089 Entiat and Methow River Wild 2017 0.0035 0.0013 0.0061 Entiat and Methow River Wild 2018 0.0150 0.0085 0.0217 Entiat and Methow River Wild 2019 0.0184 0.0092 0.0275 Entiat and Methow River Wild 2020 0.0281 0.0169 0.0388 Entiat and Methow River Wild 2021 0.0118 0.0067 0.0168 Entiat and Methow River Wild 2022 0.0082 0.0015 0.0169 Wenatchee River Wild 2007 0.0076 0.0051 0.0102 Wenatchee River Wild 2008 0.0276 0.0238 0.0317 Wenatchee River Wild 2009 0.0198 0.0157 0.024 Wenatchee River Wild 2010 0.0137 0.0109 0.0164 Wenatchee River Wild 2011 0.0094 0.0064 0.0123 Wenatchee River Wild 2012 0.0096 0.0070 0.0120 Wenatchee River Wild 2013 0.0186 0.0140 0.0228 Wenatchee River Wild 2014 0.0091 0.0067 0.0118 Wenatchee River Wild 2015 0.0077 0.0060 0.0104 Wenatchee River Wild 2016 0.0114 0.0080 0.0147 Wenatchee River Wild 2017 0.0042 0.0026 0.0059 Wenatchee River Wild 2018 0.0091 0.0064 0.0121 Wenatchee River Wild 2019 0.0115 0.0082 0.0149 254 Wenatchee River Wild 2020 0.0335 0.0252 0.0406 Wenatchee River Wild 2021 0.0148 0.0108 0.0188 Wenatchee River Wild 2022 0.0122 0.0063 0.0170 Entiat and Methow River Wild 2008 0.0155 0.0119 0.0195 Entiat and Methow River Wild 2009 0.0111 0.0083 0.0163 Entiat and Methow River Wild 2010 0.0113 0.0089 0.0139 Entiat and Methow River Wild 2011 0.0029 0.0008 0.0056 Entiat and Methow River Wild 2012 0.0072 0.0047 0.0098 Entiat and Methow River Wild 2013 0.0131 0.0097 0.0169 Entiat and Methow River Wild 2014 0.0099 0.0073 0.0130 Entiat and Methow River Wild 2015 0.0032 0.0011 0.0058 Entiat and Methow River Wild 2016 0.0031 0.0011 0.0056 Entiat and Methow River Wild 2017 0.0026 0.0010 0.0046 Entiat and Methow River Wild 2018 0.0087 0.0052 0.0126 Entiat and Methow River Wild 2019 0.0058 0.0030 0.0088 Entiat and Methow River Wild 2020 0.0153 0.0098 0.0214 Entiat and Methow River Wild 2021 0.0102 0.0074 0.0134 Entiat and Methow River Wild 2022 0.0077 0.0038 0.0120 255 G.5 Stock-specific ÏSAS estimates for Snake River Chinook salmon from 2000 to 2022 on the primary y-axis. The dashed line at 0.02 on the primary y-axis represents a 2% survival rate to show years where recovery targets are not being met. Colored lines represent individual stocks, with solid lines for hatchery-origin and dotted lines for wild-origin. The solid black line shows the year effect for the Snake River region on the secondary y-axis. G.6 Stock-specific ÏSAS estimates for Middle Columbia Chinook salmon from 2000 to 2022 on the primary y-axis. The dashed line at 0.02 on the primary y-axis represents a 2% survival rate to show years where recovery targets are not being met. Colored lines represent individual stocks, with solid lines for hatchery-origin and dotted lines for wild-origin. The solid black line shows the year effect for the Middle Columbia region on the secondary y-axis. 256 G.7 Stock-specific ÏSAS estimates for Upper Columbia Chinook salmon from 2000 to 2022 on the primary y-axis. The dashed line at 0.02 on the primary y-axis represents a 2% survival rate to show years where recovery targets are not being met. Colored lines represent individual stocks, with solid lines for hatchery-origin and dotted lines for wild-origin. The solid black line shows the year effect for the Upper Columbia region on the secondary y-axis. G.8 Stock-specific ÏSAS estimates for Willamette Chinook salmon from 2006 to 2016 on the primary y-axis. The dashed line at 0.02 on the primary y-axis represents a 2% survival rate to show years where recovery targets are not being met. Colored lines represent individual stocks, with solid lines for hatchery-origin and dotted lines for wild-origin. The solid black line shows the year effect from 2000 to 2022 for the Willamette region on the secondary y-axis. 257 Appendix H H.1 Summary statistics of the estimated common shared year effects for each region and the global time series. The table includes the lag-1 autocorrelation coefficient, the maximum percent difference between the minimum and maximum year effects, and the years corresponding to the minimum and maximum values of the three-year running average. Region Lag-1 Autocorrelation Lag-1 SE Max percent difference Min 3-year avg. Max 3-year avg. Middle Columbia 0.39 0.19 176 2017 2001 Snake River 0.45 0.19 188 2016 2009 Upper Columbia 0.40 0.21 240 2005 2021 Willamette 0.36 0.20 263 2009 2005 Global 0.38 0.20 185 2016 2001 258 Appendix I I.1 Compilation of covariates used for analysis, their respective time series, and source of the data. Covariate Time Series Source Alaska SST 2000 â 2022 aoos.org BC SST 2000 â 2022 www.dfo-mpo.gc.ca/science/data-donnees/lightstations-phares/index-eng.html ENSO 2000 â 2022 psl.noaa.gov/enso/mei/data/meiv2.data NPGO 2000 â 2022 psl.noaa.gov/data/correlation/npgo.data PDO 2000 â 2022 https://www.ncei.noaa.gov/pub/data/cmb/ersst/v5/index/ersst.v5.pdo.dat Upwelling 48N, 125W 2000 â 2022 oceanview.pfeg.noaa.gov/products/pwelling/dnld Upwelling 51N, 131W 2000 â 2022 oceanview.pfeg.noaa.gov/products/pwelling/dnld Upwelling 54N, 134W 2000 â 2022 oceanview.pfeg.noaa.gov/products/pwelling/dnld Upwelling 57N, 137W 2000 â 2022 oceanview.pfeg.noaa.gov/products/pwelling/dnld Spring Transition date 2000 â 2022 www.fisheries.noaa.gov/west-coast/science-data/ocean-conditions-indicators-trends 259 Willamette Hatchery Releases 2003 â 2022 www.dfw.state.or.us/fish/hatchery Middle Columbia Hatchery Releases 2000 â 2021 McCann et al. (2024) Upper Columbia Hatchery releases 2000 â 2021 McCann et al. (2024) Snake River Hatchery Releases 2000 â 2022 McCann et al. (2024) Harbour Seals 2000 â 2020 DFO (2022) Pink Salmon 2000 â 2020 Ruggerone & Irvine (2018) Ruggerone et al. (2021) Sea Lions 1997 â 2022 Young et al. (2024) van der Leeuw & Tidwell (2022) Killer Whales 1997 â 2022 whaleresearch.com/orca-population DFO (2023) 260 I.2 Time series plots of standardized covariates from 2000 to 2022. Each panel displays the standardized value of a covariate (points) and a linear trend (line) over the years. 261 I.3 Summary of regression coefficients, standard errors, and p-values for all top models from the Snake River. Adjusted R² values for each model are also shown. Model Term Estimate Std Error P-value Adj R² 1 Intercept 9.27E-03 5.05E-04 2.00E-16 3.57E-01 1 Harbour seal -1.38E-03 8.14E-04 9.08E-03 1 ENSO 1.96E-03 6.25E-04 1.96E-03 1 PDO -2.64E-03 6.43E-04 6.03E-05 1 Hatchery Releases -3.51E-03 1.15E-03 2.70E-03 1 Spring Transition -3.12E-03 6.60E-04 4.42E-06 1 Upwelling 54N, 134W -1.97E-03 5.42E-04 3.63E-04 2 Intercept 8.99E-03 5.45E-04 2.00E-16 3.60E-01 2 Harbour seal -2.03E-03 9.42E-04 3.22E-02 2 ENSO 2.11E-03 6.33E-03 1.04E-03 2 PDO -2.11E-03 7.49E-04 5.34E-03 2 Hatchery Releases -3.84E-03 1.18E-03 1.32E-03 2 Alaska SST -9.57E-04 7.04E-04 1.75E-01 2 Spring transition -3.05E-03 6.60E-04 7.34E-06 2 Upwelling 54N, 134W -1.95E-03 5.41E-04 4.13E-04 3 Intercept 9.02E-03 5.46E-04 2.00E-16 3.61E-01 3 Harbour seal -1.99E-03 9.43E-04 3.65E-02 3 ENSO 2.13E-03 6.33E-04 9.06E-04 3 PDO -1.80E-03 7.97E-04 2.50E-02 3 Hatchery Releases -3.55E-03 1.20E-03 3.62E-03 262 3 Alaska SST -1.17E-03 7.29E-04 1.09E-01 3 Spring transition -3.05E-03 6.60E-04 6.93E-06 3 Upwelling 54N, 134W -2.48E-03 7.20E-04 6.95E-04 3 Upwelling 57N, 137W 7.80E-04 6.89E-04 2.59E-01 4 Intercept 9.61E-03 5.06E-04 2.00E-16 3.55E-01 4 Pink -1.29E-03 5.02E-04 1.07E-02 4 ENSO 1.78E-03 6.25E-04 4.91E-03 4 PDO -2.68E-03 6.51E-04 5.74E-05 4 Spring transition -2.45E-03 6.75E-04 3.65E-04 4 Upwelling 54N, 134W -3.03E-03 7.61E-04 9.65E-05 4 Upwelling 57N, 137W 1.67E-03 7.02E-04 1.80E-02 5 Intercept 9.45E-03 4.96E-04 2.00E-16 3.51E-01 5 ENSO 1.86E-03 6.26E-04 3.28E-03 5 PDO -2.89E-03 6.29E-04 8.02E-06 5 Hatchery releases -2.13E-03 8.27E-04 1.07E-02 5 Spring transition -2.76E-03 6.27E-04 1.85E-05 5 Upwelling 54N, 134W -1.77E-03 5.32E-04 1.06E-03 6 Intercept 9.68E-03 5.09E-04 2.00E-16 3.56E-01 6 Pink -9.18E-04 6.03E-04 1.30E-01 6 ENSO 1.80E-03 6.25E-04 0.00449 6 PDO -2.56E-03 6.60E-04 1.42E-04 6 Hatchery Releases -1.13E-03 1.00E-03 2.61E-01 263 6 Spring transition -2.45E-03 6.75E-04 3.74E-04 6 Upwelling 54N, 134W -2.79E-03 7.90E-04 5.25E-04 6 Upwelling 57N, 137W 1.31E-03 7.71E-04 9.00E-02 7 Intercept 9.33E-03 5.12E-04 2.00E-16 3.56E-01 7 Harbour seal -1.26E-03 8.33E-04 1.31E-01 7 ENSO 1.96E-03 6.26E-04 2.04E-03 7 PDO -2.52E-03 6.64E-04 2.01E-04 7 Hatchery releases -3.28E-03 1.20E-03 6.76E-03 7 Spring transition -3.14E-03 6.61E-04 4.17E-06 7 Upwelling 54N, 134W -2.31E-03 7.15E-04 1.47E-03 7 Upwelling 57N, 137W 4.89E-04 6.67E-04 4.64E-01 8 Intercept 9.52E-03 4..99E-04 2.00E-16 3.51E-01 8 ENSO 1.87E-03 6.25E-04 3.20E-03 8 PDO -2.69E-03 6.57E-04 6.41E-05 8 Hatchery releases -1.98E-03 8.39E-04 1.93E-02 8 Spring transition -2.82E-03 6.30E-04 1.30E-05 8 Upwelling 54N, 134W -2.28E-03 7.17E-04 1.76E-03 8 Upwelling 57N, 137Ww 6.92E-04 6.56E-04 2.93E-01 264 I.4 Summary of regression coefficients, standard errors, and p-values for all top models from the Middle Columbia. Adjusted R² values for each model are also shown. Model Term Estimate Std Error P-value Adj R² 1 Intercept 1.60E-02 1.45E-03 2.00E-16 7.17E-02 1 Pink -2.40E-03 1.27E-03 6.32E-02 1 PDO -2.77E-03 1.49E-03 6.69E-02 2 Intercept 1.65E-02 1.49E-03 2.00-16 7.20E-02 2 Pink -3.48E-03 1.29E-03 8.51E-03 2 Upwelling 54N, 134W -3.97E-03 1.91E-03 4.07E-02 2 Upwelling 57N, 137W 3.17E-03 1.93E-03 1.05E-01 3 Intercept 1.65E-02 1.49E-03 2.00E-16 7.11E-02 3 NPGO 5.30E-03 1.98E-03 8.91E-03 3 Upwelling 54N, 134WW -3.75E-03 1.89E-03 5.09E-02 3 Upwelling 57N, 137W 4.00E-03 2.03E-03 5.20E-02 4 Intercept 1.67E-02 1.50E-03 2.00E-16 7.95E-02 4 Pink -2.17E-03 1.64E-03 1.90E-01 4 NPGO 3.24E-03 2.51E-03 2.00E-01 4 Upwelling 54N, 134W -4.10E-03 1.90E-03 3.41E-02 4 Upwelling 57N, 137W 3.96E-03 2.02E-03 5.35E-02 5 Intercept 1.58E-02 1.46E-03 2.00E-16 5.87E-02 5 NPGO 2.98E-03 1.94E-03 1.29E-01 5 PDO -2.52E-03 1.56E-03 1.09E-01 6 Intercept 1.59E-02 1.45E-03 2.00E-16 6.76E-02 265 6 Pink -1.96E-03 1.39E-03 1.61E-01 6 PDO -2.44E-03 1.55E-03 1.18E-01 6 Spring transition -1.34E-03 1.69E-03 4.29E-01 7 Intercept 1.62E-02 1.51E-03 2.00E-16 7.77E-02 7 Pink -3.79E-03 1.31E-03 4.95E-03 7 Hatchery releases 1.83E-03 1.49E-03 2.23-01 7 Upwelling 54N, 134W -4.05E-03 1.90E-03 3.62E-02 7 Upwelling 57N, 137W 3.29E-03 1.93E-03 9.24E-02 8 Intercept 1.56E-02 1.44E-03 2.00E-16 6.08E-02 8 PDO -2.57E-03 1.56E-03 1.02E-01 8 Spring transition -2.28E-03 1.56E-03 1.47E-01 9 Intercept 1.57E-02 1.47E-03 2.00E-16 4.47E-02 9 Pink -2.83E-03 1.27E-03 2.83E-02 10 Intercept 1.61E-02 1.46E-03 2.00E-16 6.54E-02 10 Pink -2.55E-03 1.30E-03 5.28E-02 10 PDO -2.35E-03 1.63E-03 1.52E-01 10 Upwelling 54N, 134W -1.05E-03 1.59E-03 5.11E-01 11 Intercept 1.55E-02 1.45E-03 2.00E-16 5.64E-02 11 PDO -3.28E-03 1.49E-03 2.99E-02 12 Intercept 1.58E-02 1.46E-03 2.00E-16 5.43E-02 12 Sea lion -3.16E-03 2.27E-03 1.67E-01 12 PDO -2.93E-03 1.50E-03 5.44E-02 266 13 Intercept 1.60E-02 1.47E-03 2.00E-16 5.31E-02 13 Pink -2.99E-03 1.27E-03 2.07E-02 13 Upwelling 54N, 134W -1.94E-03 1.47E-03 1.90E-01 14 Intercept 1.60E-02 1.46E-03 2.00E-16 6.31E-02 14 Pink -1.91E-03 1.62E-03 2.42-01 14 NPGO 1.19E-03 2.46E-03 6.30E-01 14 PDO -2.57E-03 1.55E-03 1.02E-01 15 Intercept 1.57E-02 1.47E-03 2.00E-16 4.05E-02 15 NPGO 3.98E-03 1.86E-03 3.50E-02 16 Intercept 1.57E-02 1.46E-03 2.00E-16 5.09E-02 16 Pink -2.09E-03 1.40E-03 1.38E-01 16 Spring transition -2.04E-03 1.64E-03 2.17E-01 17 Intercept 1.60E-02 1.47E-03 2.00E-16 6.12E-02 17 Pink -2.44E-03 1.29E-03 6.22E-02 17 PDO -2.74E-03 1.50E-03 7.16E-02 17 Upwelling 57N, 137W 3.97E-04 1.49E-03 7.90E-01 18 Intercept 1.59E-02 1.50E-03 2.00E-16 6.12E-02 18 Pink -2.50E-03 1.34E-03 6.58E-02 18 PDO -2.55E-03 1.71E-03 1.41E-01 18 Hatchery releases 4.51E-04 1.72E-03 7.94E-01 19 Intercept 1.60E-02 1.49E-03 2.00E-16 6.08E-02 19 Pink -2.52E-03 1.45E-03 8.64E-02 267 19 PDO -2.99E-03 1.91E-03 1.23E-01 19 Alaska SST 3.50E-04 1.89E-03 8.53-01 20 Intercept 1.60E-02 1.47E-03 2.00E-16 6.04E-02 20 Pink -2.39E-03 1.29E-03 6.60E-02 20 ENSO -1.95E-05 1.74E-03 9.91E-01 20 PDO -2.76E-03 1.81E-03 1.31E-01 I.5 Summary of regression coefficients, standard errors, and p-values for all top models from the Upper Columbia. Adjusted R² values for each model are also shown. Model Term Estimate Std Error P-value Adj R² 1 Intercept 9.96E-03 7.57E-04 2.00E-16 2.81E-01 1 Pink -2.91E-03 7.59E-04 2.60E-04 1 ENSO 1.77E-03 8.10E-04 3.15E-02 1 Hatchery releases 3.32E-03 9.21E-04 5.58E-04 1 Spring transition -1.51E-03 9.67E-04 1.22E-01 1 Upwelling 54N, 134W -5.23E-03 9.97E-04 1.31E-06 1 Upwelling 57N, 137W 4.15E-03 9.71e-04 5.40E-05 2 Intercept 9.57E-03 8.14E-04 2.00E-16 2.88E-01 2 Pink -2.46E-03 8.31E-04 4.08E-03 2 ENSO 2.17E-03 8.62E-04 1.39E-02 2 Hatchery releases 3.60E-03 9.43E-04 2.69E-04 2 Alaska SST -1.09E-03 8.41E-04 1.97E-01 2 Spring transition -1.54E-03 9.63E-04 1.13E-01 268 2 Upwelling 54N, 134W -4.96E-03 1.01E-03 5.55E-06 2 Upwelling 57N, 137W 4.09E-03 9.68E-04 6.56e-05 3 Intercept 1.02E-02 7.53-04 2.00E-16 2.68E-01 3 Pink -3.36E-03 7.08-04 9.29E-06 3 ENSO 1.17E-03 7.18E-04 1.08E-01 3 Hatchery releases 3.25E-03 9.28E-04 7.79-04 3 Upwelling 54N, 134W -5.05E-03 9.99-04 2.81E-06 3 Upwelling 57, 137W 4.32E-03 9.74E-04 2.99E-05 4 Intercept 9.78E-03 8.11E-04 2.00E-16 2.73E-01 4 Pink -2.94E-03 7.84E-04 3.44E-04 4 ENSO 1.54E-03 7.75E-04 5.04E-02 4 Hatchery releases 3.52E-03 9.51E-04 3.97E-04 4 Alaska SST -1.06E-03 8.49E-04 2.16E-01 4 Upwelling 54N, 134W -4.78E-03 1.02E-04 1.16Ee-05 4 Upwelling 57N, 137W 4.26E-03 9.72E-04 3.62E-05 5 Intercept 1.01E-02 7.60E-04 2.00E-16 2.53E-01 5 Pink -2.96E-03 6.71E-04 3.22E-05 5 Hatchery releases 3.05E-03 9.30E-04 1.55E-03 5 Upwelling 54N, 134W -4.26E-03 8.82E-04 6.70E-06 5 Upwelling 57N, 137W 3.83E-03 9.36E-04 1.03E-04 6 Intercept 1.00E-02 7.65E-04 2.00-16 2.74E-01 6 Pink -2.70E-03 8.70E-04 2.66E-03 269 6 NPGO 5.91E-04 1.20E-04 6.23E-01 6 ENSO 1.70E-03 8.29E-04 4.43E-02 6 Hatchery releases 3.34E-03 9.26E-04 5.57E-04 6 Spring transition -1.38E-03 1.01E-04 1.74E-01 6 Upwelling 54N, 134W -5.23E-03 1.00E-04 1.47E-06 6 Upwelling 57N, 137W 4.29E-03 1.01E-04 6.49E-05 7 Intercept 9.86E-03 7.89E-04 2.00E-16 2.74E-01 7 Pink -2.69E-03 8.86E-04 3.32E-03 7 ENSO 1.90E-03 8.53E-04 2.89E-02 7 PDO -5.13E-04 1.04E-03 6.23E-01 7 Hatchery releases 3.12E-03 1.01E-03 2.75E-03 7 Spring transition -1.49E-03 9.73E-04 1.29E-01 7 Upwelling 54N, 134W -4.84E-03 1.28E-03 3.14E-04 7 Upwelling 57N, 137W 3.77E-03 1.25E-03 3.38E-03 8 Intercept 9.31E-03 9.21E-04 1.19E-15 2.82E-01 8 Pink -2.60E-03 8.68E-04 3.69E-03 8 NPGO -9.98E-04 1.68E-03 5.55E-01 8 ENSO 2.48E-03 1.01E-03 1.67E-02 8 Hatchery releases 3.69E-03 9.59E-04 2.46E-04 8 Alaska SST -1.59E-03 1.19E-03 1.86E-01 8 Spring transition -1.78E-03 1.04E-03 9.27E-02 8 Upwelling 54N, 134W -4.83E-03 1.04E-03 1.49E-05 270 8 Upwelling 57N, 137W 3.83E-03 1.07E-03 5.78E-04 9 Intercept 1.02E-02 7.56E-04 2.00E-16 2.66E-01 9 Pink -2.94E-03 8.57E-04 9.85E-04 9 NPGO 1.02E-03 1.16E-03 3.82E-01 9 ENSO 1.12E-03 7.21E-04 1.23E-01 9 Hatchery releases 3.30E-03 9.31E-04 6.83E-04 9 Upwelling 54N, 134W -5.08E-03 1.00E-03 2.63E-06 9 Upwelling 57N, 137W 4.53E-03 1.00E-03 2.29E-05 10 Intercept 9.56E-03 8.17E-04 2.00E-16 2.81E-01 10 Pink -2.62E-03 8.83E-04 4.09E-03 10 ENSO 2.14E-03 8.678E-04 1.62E-02 10 PDO 7.67E-04 1.42E-04 5.91E-01 10 Hatchery releases 4.01E-03 1.21E-03 1.43E-03 10 Alaska SST -1.52E-03 1.16E-03 1.93E-01 10 Spring transition -1.59E-03 9.71E-04 1.06E-01 10 Upwelling 54N, 134W -5.44E-03 1.36E-03 1.40E-04 10 Upwelling 57N, 137W 4.64E-03 1.40E-03 1.48E-03 I.6 Summary of regression coefficients, standard errors, and p-values for all top models from the Willamette. Adjusted R² values for each model are also shown. Model Term Estimate Std Error P-value Adj R2 1 Intercept 5.70e-03 3.73e-04 2.00e-16 9.46e-02 1 Pink -1.87e-03 7.75e-04 2.01e-02 271 2 Intercept 6.09e-04 2.88e-04 2.00e-16 1.06e-01 2 Killer whale -1.08e-03 4.44e-04 1.92e-02 2 Alaska SST -3.60e-04 2.55e-04 1.65e-01 3 Intercept 6.27e-03 2.64e-04 2.00e-16 8.65e-02 3 Killer whale -1.04e-03 4.48e-04 2.53e-02 4 Intercept 6.49e-03 4.24e-04 2.00e-16 1.19e-01 4 Killer whale -9.44e-04 4.53e-04 4.34e-02 4 Alaska SST -8.88e-04 4.84e-04 7.32e-02 4 Hatchery releases -1.06e-03 8.26e-04 2.07e-01 5 Intercept 6.05e-03 2.96e-04 2.00e-16 7.59e-02 5 Sea lion -1.80e-03 8.23e-04 3.41e-02 6 Intercept 6.56e-03 4.14e-04 2.00e-16 1.26e-01 6 Sea lion -1.98e-03 9.10e-04 3.51e-02 6 NPGO -1.08e-03 7.95e-04 1.83e-01 6 Alaska SST -1.14e-04 5.34e-04 3.94e-02 6 Hatchery releases -1.32e-03 8.14e-04 1.11e-01 7 Intercept 6.58e-03 4.18e-04 2.00e-16 1.09e-01 7 Sea lion -1.76e-03 9.04e-04 5.82e-02 7 Alaska SST -8.41e-04 4.92e-04 9.49e-02 7 Hatchery releases -1.53e-03 8.08e-04 6.52e-02 8 Intercept 6.14e-03 2.86e-04 2.00e-16 9.08e-02 8 Killer whale -1.19e-03 4.69e-04 1.45e-02 272 8 Spring transition -3.31e-04 3.02e-04 2.77e-01 9 Intercept 6.06e-03 2.90e-04 2.00e-16 1.06e-01 9 Killer whale -1.08e-03 4.44e-04 1.97e-02 9 PDO 3.87e-04 3.84e-04 3.20e-01 9 Alaska SST -6.34e-04 3.73e-04 9.65e-02 10 Intercept 6.15e-03 2.95e-04 2.00e-16 1.03e-01 10 Killer whale -1.01e-03 4.51e-04 2.95e-02 10 NPGO -7.20e-04 7.87e-04 3.66e-01 10 Alaska SST -6.44e-04 4.03e-04 1.17e-01 11 Intercept 5.82e-03 4.22e-04 2.00e-16 8.24e-02 11 Pink -2.02e-03 8.17e-04 1.73e-02 11 Hatchery releases -2.88e-04 4.54e-04 5.29e-01 12 Intercept 6.27e-03 2.64e-04 2.00e-16 8.05e-02 12 Killer whale -1.00e-03 4.51e-04 3.09e-02 12 Upwelling 54N, 134W -2.96e-04 3.51e-04 4.04e-01 13 Intercept 5.65e-03 3.91e-04 2.00e-16 7.78e-02 13 Pink -1.88e-03 7.83e-04 2.06e-02 13 Spring transition -1.23e-04 2.89e-04 6.73e-01 14 Intercept 5.65e-03 4.15e-04 2.00e-16 7.61e-02 14 Pink -2.03e-03 9.31e-04 3.50e-02 14 Upwelling 54N, 134W 1.30e-04 4.17e-04 7.57e-01 15 Intercept 6.05e-03 2.98e-04 2.00e-16 9.34e-02 273 15 Killer whale -1.17e-03 4.69e-04 1.68e-02 15 Alaska SST -2.95e-04 2.78e-04 2.94e-01 15 Spring transition -2.01e-04 3.25e-04 5.39e-01 16 Intercept 5.70e-03 3.77e-04 2.00e-16 7.45e-02 16 Pink -1.89e-03 7.96e-04 2.18e-02 16 ENSO 4.40e-05 2.55e-04 8.64e-01 17 Intercept 5.70e-03 3.78e-04 2.00e-16 7.45e-02 17 Pink -1.88e-03 7.92e-04 2.18e-02 17 PDO 3.85e-05 2.70e-04 8.87e-01 18 Intercept 6.09e-03 3.03e-04 2.00e-16 9.22e-02 18 Sea lion -1.97e-03 9.28e-04 3.94e-02 18 NPGO -1.32e-03 7.96e-04 1.06e-01 18 Alaska SST -5.64e-04 4.10e-04 1.76e-01 19 Intercept 5.70e-03 3.78e-04 2.00e-16 7.42e-02 19 Pink -1.91e-03 9.34e-04 4.67e-02 19 Alaska SST 2.59e-05 3.08e-04 9.34e-01 20 Intercept 6.50e-03 4.27e-04 2.00e-16 1.09e-01 20 Killer whale -9.04e-04 4.59e-04 5.56e-02 20 NPGO -5.74e-04 7.95e-04 4.74e-01 20 Alaska SST -1.07e-03 5.46e-04 5.72e-02 20 Hatchery releases -9.61e-04 8.41e-04 2.59e-01
Thesis/Dissertation
eng
Oceans and Fisheries
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
McAllister, M. K
Examining release-smolt and smolt-to-adult survival rates of spring Chinook salmon (Oncorhynchus tshawytscha) from the Willamette River
Text