Lower Cowlitz River Monitoring and Evaluation, 2016
Washington Department of Fish and Wildlife
John Serl Region 5 Fish Management 165 Osprey Lane, Toledo WA 98591
Chris Gleizes Region 5 Fish Management 165 Osprey Lane, Toledo WA 98591
Chip Nissell Region 5 Fish Management 165 Osprey Lane, Toledo WA 98591
Mara Zimmerman Fish Science Division 2108 Grand Boulevard, Vancouver WA 98661
Bryce Glaser Region 5 Fish Management 2108 Grand Boulevard, Vancouver WA 98661
July 2017
Acknowledgements
We would like to thank Mike Blankenship, Teresa Fryer, Bryan Wieser, Ian Brauner, Nathan Straten, Jesse Jones, Nels Parvi, Zack Malham, Brandon Harkleroad, Noll Steinweg, Matt Choowong, Elizabeth Skill, Elizabeth Lee, David Snyder, Keith Keown, Laura Bouchard, Jay Anderson, TC Peterson, Nate Abel, Carson Swart, Wade Heimbigner, Caroline Watson, and Grant Brink who assisted in the data collection for 2016. Scott Gibson and Jamie Murphy supervised the collection of adults and data entry at the Cowlitz Salmon Hatchery separator. Steve Vanderploeg provided GRTS survey reaches and prepared maps. WDFW Scale Ageing Laboratory provided scale age data. Thomas Buehrens and Dan Rawding contributed to the study design and analysis. Danny Warren and Tiffany Warren provided database management support. Coded-wire tag data were provided by Terry Wilson, Norm Switzler, Shelley Peterson and Tracey Scalici in the WDFW Coded-Wire Tag Lab. Teresa Fryer and Matt Sturza also contributed to this report.
This work was primarily supported by funding from Tacoma Power. The resistance board weir operations and maintenance was funded jointly by Tacoma Power and Columbia River Salmon and Steelhead Endorsement Funds administered by the Columbia River Salmon and Steelhead Advisory Board. Washington Department of Fish and Wildlife provided in-kind services for some of the data collected within and outside of the Cowlitz Basin.
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Table of Contents
TABLE OF CONTENTS ...... 3
LIST OF TABLES ...... 5
LIST OF FIGURES ...... 8
EXECUTIVE SUMMARY ...... 9
INTRODUCTION ...... 12
METHODS ...... 16
STUDY SITE ...... 16 TRIBUTARY WEIR OPERATION...... 18 STEELHEAD SPAWNER SURVEYS ...... 21 CHINOOK SPAWNER SURVEYS ...... 23 COHO SPAWNER SURVEYS ...... 25 ESTIMATES OF SPAWNER ABUNDANCE AND PHOS...... 28 SPOT CREEL SURVEYS ...... 33 ESTIMATED CATCH FOR NATURAL-ORIGIN FISH IN THE COWLITZ RIVER FISHERY ...... 34 CHINOOK AND COHO HATCHERY BROODSTOCK COMPOSITION...... 37 HATCHERY JUVENILE DIET, PREDATION AND PRESENCE TIMING IN THE LOWER COWLITZ RIVER ...... 37 OPERATION OF A ROTARY SCREW TRAP IN THE LOWER COWLITZ RIVER ...... 39
RESULTS ...... 44
MONITORING RESPONSIBILITY 1: WEIR OPERATION IN FOUR TRIBUTARIES TO THE LOWER COWLITZ RIVER ...... 44
MONITORING RESPONSIBILITY 2: STEELHEAD SPAWNER ABUNDANCE, COMPOSITION (PHOS), AND DISTRIBUTION
IN LOWER COWLITZ RIVER TRIBUTARIES ...... 53
MONITORING RESPONSIBILITY 3: CHINOOK SPAWNER ABUNDANCE, COMPOSITION (PHOS, AGE STRUCTURE), AND
DISTRIBUTION IN THE LOWER COWLITZ RIVER ...... 55
MONITORING RESPONSIBILITY 4: COHO SPAWNER ABUNDANCE, COMPOSITION (PHOS), AND DISTRIBUTION IN
LOWER COWLITZ RIVER TRIBUTARIES ...... 58
MONITORING RESPONSIBILITY 5: EFFORT, CATCH RATES, AND NOR:HOR RATIOS IN COWLITZ RIVER FISHERIES
IN 2016 ...... 60
MONITORING RESPONSIBILITY 6: ESTIMATES OF CATCH FOR NATURAL-ORIGIN FISH IN THE COWLITZ RIVER
FISHERIES IN 2015 ...... 65
MONITORING RESPONSIBILITY 7: COUNTS, BIOLOGICAL DATA AND DISPOSITION OF RETURNS TO BARRIER DAM,
INCLUDING HATCHERY BROODSTOCK SAMPLING ...... 69
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MONITORING RESPONSIBILITY 8: HATCHERY JUVENILE DIET, PREDATION AND PRESENCE TIMING IN THE LOWER
COWLITZ RIVER...... 79
MONITORING RESPONSIBILITY 9: OPERATION OF A ROTARY SCREW TRAP AND COLLECTION OF JUVENILE CHINOOK
GENETIC SAMPLES IN THE LOWER COWLITZ RIVER ...... 80
DISCUSSION ...... 85
STEELHEAD SPAWNER ABUNDANCE ...... 86 CHINOOK SPAWNER ABUNDANCE ...... 88 COHO SPAWNER ABUNDANCE ...... 89 CATCH OF NATURAL-ORIGIN FISH IN THE COWLITZ RIVER FISHERY ...... 90 RETURNS TO COWLITZ RIVER BARRIER DAM ADULT HANDLING FACILITY ...... 91 HATCHERY JUVENILE DIET, PREDATION AND PRESENCE TIMING IN THE LOWER COWLITZ RIVER ...... 92 OPERATION OF A ROTARY SCREW TRAP IN THE LOWER COWLITZ RIVER ...... 92 CONCLUSION ...... 93
REFERENCES ...... 94
APPENDICES ...... 96
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List of Tables
Table 1. Summary statistics used for mark-recapture estimates of spawner abundance above tributary weirs on the lower Cowlitz River...... 29 Table 2. Derived parameters and likelihoods used for mark-recapture estimate of spawner abundance above tributary weirs on the lower Cowlitz River...... 29 Table 3. Summary statistics used for redd-based estimates of spawner abundance in areas outside of tributary weirs on the lower Cowlitz River...... 31 Table 4. Derived parameters and likelihoods used for redd-based estimates of spawner abundance in areas outside of tributary weirs on the lower Cowlitz River...... 31 Table 5.Summary statistics used for estimating catch of natural-origin fish in the lower Cowlitz River fishery...... 36 Table 6. Derived parameters and likelihoods used for estimating catch of natural-origin fish in the lower Cowlitz River fishery...... 36 Table 7. Disposition of live steelhead captured and released from upstream traps at tributary weirs in the lower Cowlitz River, 2016 spawn year...... 47 Table 8. Disposition of steelhead kelts or carcasses captured in downstream traps or above tributary weir traps in the lower Cowlitz River, 2016 spawn year. Capture of natural-origin kelts included tagged (recaptured) and untagged (maiden) captures. Capture of hatchery-origin kelts were untagged only as hatchery steelhead were not intentionally passed upstream. All kelts were released downstream of the weirs...... 48 Table 9. Abundance and composition of steelhead spawners above tributary weirs in the lower Cowlitz River, 2016 spawn year. Data are abundance (N) and standard deviation (SD) of natural-origin (NOR), hatchery-origin (HOR), and total (Tot) spawners in each tributary. No estimate is available for Lacamas Creek due to low number of fish tagged and recaptured. ... 48 Table 10. Disposition of live adult coho salmon captured and released from upstream traps at tributary weirs in the lower Cowlitz River, 2016 spawn year...... 51 Table 11. Disposition of adult coho salmon carcasses recovered in stream surveys above tributary weirs or washed up on weir panels in the lower Cowlitz River, 2016 spawn year. Recoveries of natural-origin (NOR) coho included tagged (recaptured) and untagged (maiden) captures. Captures of hatchery-origin (HOR) coho were untagged fish only as hatchery coho were not intentionally passed upstream...... 52 Table 12. Abundance and composition of coho spawners above tributary weirs in the lower Cowlitz River, 2016 spawn year. Data are abundance (N) and standard deviation (SD) of natural-origin (NOR), hatchery-origin (HOR), and total (Tot) spawners as well as weir efficiency (WE) above each tributary weir. No estimate is available for Olequa Creek due to low number of fish tagged and recaptured...... 52 Table 13. Natural- and hatchery-origin and total steelhead spawner abundance (N) and variance and proportion of hatchery-origin spawners (pHOS) in lower Cowlitz River tributaries, spawn year 2016. Estimates are based on mark-recapture above tributary weirs and redd expansion...... 55 Table 14. Spatial and temporal distribution of hatchery-origin and natural-origin Chinook salmon spawners in the lower Cowlitz River, 2016...... 57 Table 15. Age and stock composition of fall Chinook salmon spawners in the lower Cowlitz River, 2016. Table provides spawner escapement by age class...... 57 Table 16. Coho spawner abundance estimated using mark-recapture above tributary weirs and redd expansion in lower Cowlitz River tributaries, spawn year 2016. Estimate includes
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natural-origin abundance and variance, hatchery-origin abundance and variance, and total abundance and variance...... 60 Table 17. Summary of effort (number of anglers, number of hours fished) by shore anglers as observed in the Cowlitz River creel survey, 2016...... 62 Table 18. Summary of effort (number of anglers, number of hours fished) by boat anglers as observed in the Cowlitz River creel survey, 2016...... 63 Table 19. Summary of catch of hatchery (HOR) and natural (NOR) salmon and steelhead by shore anglers as observed in the Cowlitz River creel survey, 2016...... 64 Table 20. Summary of catch of hatchery (HOR) and natural (NOR) salmon and steelhead by boat anglers as observed in the Cowlitz River creel survey, 2016...... 65 Table 21. Catch of hatchery-origin (HOR) and natural-origin (NOR) Chinook salmon in the Cowlitz River fishery, 2015. Catch between March and July are assumed to be spring Chinook salmon and catch between August and December are assumed to be fall Chinook salmon. ... 67 Table 22. Catch of hatchery-origin (HOR) and natural-origin (NOR) coho salmon in the Cowlitz River fishery, 2015...... 68 Table 23. Catch of hatchery-origin (HOR) and natural-origin (NOR) winter steelhead in the Cowlitz River fishery, 2015...... 69 Table 24. Disposition of natural (NOR) and hatchery-origin (HOR) spring Chinook salmon returns to Cowlitz Salmon Hatchery in 2016. Mark types include unmarked, adipose-clipped (AD only), adipose-clipped and coded-wire tag (AD + CWT), left pelvic clip (LV-clipped), right pelvic clip (RV-clipped)...... 72 Table 25. Disposition of natural (NOR) and hatchery (HOR) fall Chinook salmon returns to Cowlitz Salmon Hatchery in 2016. Mark types include unmarked, adipose-clipped (AD only), adipose-clipped and coded-wire tag (AD + CWT), unmarked and coded-wire tag (UM + CWT)...... 73 Table 26. Disposition of natural (NOR) and hatchery-origin (HOR) coho salmon returns to Cowlitz Salmon Hatchery in 2016. Mark types include unmarked, unmarked and blank-wire tagged (Unmarked + BWT), adipose-clipped (AD only), adipose-clipped and coded-wire tag (AD + CWT)...... 74 Table 27. Disposition of natural (NOR) and hatchery (HOR) winter-run steelhead returns to Cowlitz Salmon Hatchery in late 2015 and 2016. Mark types include unmarked, adipose- clipped (AD only), adipose-clipped and right ventral fin clip (AD + RV), adipose-clipped and left ventral fin clip (AD + LV), unmarked and blank-wire tag (UM + BWT)...... 75 Table 28. Age and length summary for spring Chinook broodstock at the Cowlitz Salmon Hatchery, 2016. Adipose clip (AD only) and adipose clip/coded wire tagged (AD+CWT) are used for the segregated broodstock program. Data are summarized by age category as total number sub-sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). Gilbert-Rich age notation includes total and freshwater age (e.g., 42 = four years total, exited freshwater as a yearling). N.D. indicates that age could not be determined...... 76 Table 29. Age and length summary for fall Chinook broodstock at the Cowlitz Salmon Hatchery, 2016. Unmarked fish were used for the integrated broodstock program. Adipose-clipped (AD only) fish were used for the integrated broodstock programs. Adipose-clipped/coded-wire tagged fish (AD+CWT) were used in either the segregated or integrated program. Data are summarized by age category as total number sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). Gilbert-Rich age notation includes total and freshwater age (e.g., 42 = four years total, exited freshwater as a yearling). N.D. indicates that age could not be determined...... 76 Page 6 of 119
Table 30. Age and length summary for unmarked coho salmon used for the integrated broodstock program at the Cowlitz Salmon Hatchery, 2016. Data are summarized by age category as total number sub-sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). Gilbert-Rich age notation includes total and freshwater age (e.g., 42 = four years total, exited freshwater as a yearling). N.D. indicates that age could not be determined. Table does not include age data which were not available at the time of this report...... 77 Table 31. Age and length summary for winter-run steelhead broodstock at the Cowlitz Salmon Hatchery. Unmarked fish were used for the upper and lower Cowlitz integrated broodstock programs. Adipose-clipped (AD only) fish were used for the integrated broodstock programs. Adipose-clipped/right ventral-clipped (AD+RV) were used in the upper Cowlitz integrated program. Data are summarized by age category as total number sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). European age notation includes freshwater age and saltwater age (e.g., 2.1+ = four years total age, exited freshwater as age two and over a full year plus in salt (two-salt)). N.D. indicates that age could not be determined...... 78 Table 32. The number of stomach samples examined in 2016 by species and rates of predation for Chinook, any salmonids and any fish...... 79 Table 33. Total fish captured in the Cowlitz River Rotary Screw trap by life stage and origin from January through December 2016. Life stages encountered included fry, parr (P), transitional (T), and Smolt (S)...... 81 Table 34. Size range and average fork lengths (mm) with 95% confidence intervals for Chinook (natural-origin (NOR) and hatchery-origin (HOR) respectively) downstream migrants captured from the Cowlitz River in the spring (Mar-May), summer (June-Aug), fall (Sept-Nov) and winter (Dec-Feb) of 2016...... 82 Table 35. Cowlitz Rotary Screw Trap (CRST) marks released and recaptured for Chinook for 2016. The release site for marked fish was approximately 1000 meters upstream from the CRST near the BNSF railroad bridge. Mark types include Bismark Brown dye (Brown), upper caudal clip (UCC), and lower caudal clip (LCC). Percent recapture is reported for weeks with at least 7 recaptures and as a seasonal rate...... 83 Table 36. Cowlitz Rotary Screw Trap (CRST) marks released and recaptured for coho and steelhead for 2016. The release site for marked fish was approximately 1,000 meters upstream from the CRST near the BNSF railroad bridge...... 84
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List of Figures
Figure 1. Map of the lower Cowlitz River basin showing locations of major tributaries below Mayfield Dam. Although the Toutle and Coweeman rivers flow into the Cowlitz River, fish populations in these tributaries are managed (and monitored) separately from the remainder of the lower Cowlitz River...... 16 Figure 2. Location of resistance board weirs on four lower Cowlitz River tributaries in 2016. .. 20 Figure 3. Resistance board weir on Olequa Creek, a lower Cowlitz River tributary. Floating panels are anchored to a substrate rail at their upstream end (right side of picture) and lifted by a series of resistance boards fastened to the underside of the panels on their downstream end (left side of picture). Live box shown in this picture captures fish moving in an upstream direction (moving from right to left side of the picture)...... 21 Figure 4. Winter-run steelhead spawner survey reaches in 2016 (including redds) and modeled distribution of steelhead in lower Cowlitz River tributaries. Modeled distribution is based on GIS-derived watershed characteristics as per the Cowlitz Monitoring and Evaluation Plan (FHMP Appendix J) published in 2011...... 23 Figure 5. Fall Chinook salmon spawner survey area in the main stem Cowlitz River, 2016...... 25 Figure 6. Coho salmon spawner survey reaches in 2016 with redds and modeled distribution of coho salmon in lower Cowlitz River tributaries. Modeled distribution is based on GIS-derived watershed characteristics as per the Cowlitz Monitoring and Evaluation Plan (FHMP Appendix J) published in 2011...... 27 Figure 7. Creel survey locations on Cowlitz River, 2016. Locations include Barrier Dam (1), Blue Creek (2), Mission Bar (3), Toledo Ramp (4), I-5 Ramp (5), Olequa Ramp (6), Toutle Confluence (7), Castle Rock Ramp (8), Camelot (9), and Gerhart Gardens (10)...... 34 Figure 8. Map of general predation sampling locations in the Lower Cowlitz River used in 2016...... 39 Figure 9. Site map of the Cowlitz River rotary screw trap location adjacent to the confluence of Rock Creek (RM 24)...... 41 Figure 10. Cowlitz River rotary screw trap (CRST) fishing position located at the Rock Creek site...... 42 Figure 11. Steelhead redd densities observed in 1-mile GRTS reaches in Cowlitz River tributaries, spawn year 2016. Gray bars are observations and black line is the fitted negative binomial function used to estimate redds in non-surveyed areas...... 54 Figure 12. Coho salmon redd densities observed in 1-mile GRTS reaches in Cowlitz River tributaries, spawn year 2016. Gray bars are observations and black line is the fitted negative binomial function used to estimate redds in non-surveyed areas...... 59 Figure 13. Cowlitz River rotary screw trap daily total salmonid catch at the Rock Creek site and daily maximum flow (cfs) recorded through Mayfield dam in 2016...... 80 Figure 14. Cowlitz rotary screw trap seasonal (winter, spring, summer, and fall time periods) migrant lengths of natural-origin (NOR) Chinook catch at the Rock Creek site in 2016...... 85
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Executive Summary
Hydroelectric development divided the Cowlitz River into an upper and lower watershed with a series of three dams constructed in the middle reaches of the river during the mid-20th century, and greatly reduced natural salmon and steelhead populations. Large hatcheries were constructed and operated to mitigate this impact. Naturally reproducing salmon and steelhead populations continued to exist in the Cowlitz watershed below Mayfield Dam, but potentially have significant adverse impacts from hatchery populations. An extensive reintroduction program in the Cowlitz River is underway to restore the anadromous migration corridor between the upper and lower Cowlitz River Watersheds. Listing of lower Columbia River salmonid populations under the Endangered Species Act and relicensing of the Cowlitz River Project have required significant hatchery reform on the Cowlitz River. Cowlitz hatchery programs have been modified to minimize impacts to the lower river natural populations while continuing to support fisheries in the lower Cowlitz River. Successful recovery of natural Cowlitz River salmonid populations will require both improving passage of smolts downstream from the upper basin and minimizing the impacts of the hatchery programs on populations currently spawning in the tributaries and main stem of the lower Cowlitz basin. A Monitoring and Evaluation Plan for the lower Cowlitz River was developed to provide the data needed for this management and this report describes these efforts during 2016. This monitoring plan is contained in Appendix J of the Fisheries and Hatchery Management Plan Update (2011). This plan is a requirement of the 2000 Cowlitz River Hydroelectric Project settlement agreement (Article 6). The focus of this effort is to estimate spawner abundance and composition of winter steelhead and coho in lower Cowlitz River tributaries and Chinook in the main stem lower Cowlitz River, document Cowlitz hatchery broodstock composition and estimate fishery impacts on natural-origin adults in the lower Cowlitz River. Operation of a rotary screw trap in the lower Cowlitz River will provide an index of juvenile abundance and timing of lower Cowlitz Chinook abundance and collect genetic samples from juvenile Chinook, as well as providing information on juvenile abundance of coho and steelhead and timing of hatchery juvenile migration.
Four resistance board weirs were operated on tributaries to the lower Cowlitz River in 2016. The purpose of the weir program is to manage proportion of hatchery spawners on the spawning grounds, collect natural-origin winter steelhead for an integrated broodstock program, and
Page 9 of 119 conduct mark-recapture estimates of steelhead and coho spawners. Mark-recapture estimates of steelhead abundance were made for three tributaries in 2016. The estimate of steelhead abundance above the weir locations was 119 fish (CV = 4.2%) on Ostrander Creek, 91 fish (CV = 8.9%) on Delameter Creek, and 273 fish (CV = 31.9%) on Olequa Creek. No steelhead estimate was derived for Lacamas Creek because too few (n = 5) fish were captured in the weir trap. Mark-recapture estimates of adult coho abundance were made for three tributaries in 2016. The estimate of coho abundance above the weir locations was 143 adult coho (CV = 18.9%) on Ostrander Creek, 161 adult coho (CV = 27.9%) on Delameter Creek, and 1,108 adult coho (CV = 29.2%) on Lacamas Creek. No coho estimate was derived for Olequa Creek because too few (n = 19) fish were captured in the weir trap.
Total spawner abundances for steelhead and coho salmon in Cowlitz River tributaries were derived by combining mark-recapture estimates above tributary weirs with redd counts obtained from stream surveys conducted outside the weir areas. The total number of steelhead spawners in lower Cowlitz River tributaries was estimated to be 972 fish (712 natural-origin and 260 hatchery-origin). The total number of adult coho spawners in lower Cowlitz River tributaries was estimated to be 3,997 fish (3,654 natural-origin and 343 hatchery-origin).
An estimate of spawner abundance for spring and fall Chinook salmon was derived from aerial redd counts during peak spawn timing. Biological data collected via carcass surveys were used to partition the spawners by origin (hatchery, natural) and age class. The total number of fall Chinook in the Cowlitz River main stem was estimated to be 4,021 spawners (2,979 natural- origin and 1,042 hatchery-origin). Spring Chinook in the Cowlitz River main stem were estimated to be 486 spawners (58 natural-origin and 428 hatchery-origin).
Estimated returns of natural-origin (NOR) and hatchery-origin (HOR) spawners of steelhead, spring Chinook, fall Chinook, and coho salmon returning to the lower Cowlitz River in 2016 are summarized in the table below. Integrated (I) and Segregated (S) hatchery programs are noted.
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Spawning Ground Cowlitz Separator Returns Abundance Broodstock Broodstockd Up-River Surplus LC NOR Winter 712 28 0 0 0 Steelheada LC NOR Spring 58 0 0 0 0 Chinookc LC NOR Fall 2,979 53 0 0 0 Chinook LC NOR 3,654 0 0 0 0 Cohoa,b HOR (I) Winter 260 0 NA NA NA Steelhead UC NOR Spring NA NA NA 230 NA Chinookc HOR (S) Spring 428 0 1,712 13,595 1,545 Chinookc HOR (I) Fall NA NA NA NA NA Chinook HOR (S) Fall 1,042 0 1,964 4,230 12 Chinook UC NOR NA NA 871 2,666 NA Cohob HOR (I) NA 0 64 10,632 0 Cohob HOR (S) 343 0 1,140 5,980 0 Cohob aSteelhead and coho spawner estimates are for lower Cowlitz River tributaries but not the main stem. bCoho estimates include adults only. Jacks are excluded to be consistent with coho estimates in other Lower Columbia tributaries. cSpring Chinook returns do not include mini-jacks. dBroodstock numbers at the separator are total fish retained for broodstock but do not represent the actual number of fish spawned.
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Introduction
Historically, large numbers of adult coho (Oncorhynchus kisutch) and Chinook salmon (O. tshawytscha), steelhead (O. mykiss) and cutthroat trout (O. clarki) returned to the Cowlitz River. Estimates from 1948, prior to dam construction, indicated that the Cowlitz River produced 244,824 total adult salmonids with a spawning escapement of 82,681 (HARZA 2000). Hydroelectric dam construction on the main stem Cowlitz River began in 1963 with the construction of Mayfield Dam by Tacoma Power. Mayfield Dam included both upstream adult and downstream juvenile passage facilities when built. Mossyrock Dam was constructed upstream of Mayfield Dam in 1968 and was too tall to include upstream passage. As a result, anadromous fish were blocked from accessing the upper Cowlitz River and production from the lower Cowlitz River hatcheries was emphasized to mitigate for lost anadromous fish production. Mayfield Dam, Mossyrock Dam and associated lands and structures are known as the Cowlitz River Project.
Cowlitz River populations of steelhead, Chinook and coho are listed as threatened under the Endangered Species Act (ESA) by the National Marine Fisheries Service (NMFS). Cowlitz River steelhead are included in the Lower Columbia River steelhead distinct population segment (DPS) that was listed as threatened on March 19, 1998 and reaffirmed on January 5, 2006 (www.nwr.noaa.gov/ESA-Salmon-Listing/Salmon-Populations). Critical habitat designation for this DPS became effective on January 2, 2006. Cowlitz River spring and fall run Chinook are included in the Lower Columbia River Chinook evolutionarily significant unit (ESU) that was listed with a threatened status on March 24, 1999. The listing status of these Chinook populations was reaffirmed on June 28, 2005. The Lower Columbia River and southwest Washington coho populations were originally combined into a large ESU. The Lower Columbia River ESU was listed separately as threatened on June 28, 2005 and included coho populations in the Cowlitz River. The NMFS conducted a five-year status review of 17 Pacific salmon and steelhead ESU and DPS within the Pacific Northwest region, including steelhead, Chinook and coho in the Lower Columbia River and on August 15, 2011 published the determination that continued listing of these populations was warranted. A second status review was completed in 2016 and determined that no reclassifications of Lower Columbia Chinook, coho or steelhead status were warranted (www.westcoast.fisheries.noaa.gov/publications/status_reviews/salmon _steelhead/2016/2016_lower-columbia.pdf).
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Listings under the Federal Endangered Species Act had significant impact on the Tacoma Power process to relicense their Cowlitz River Project and shaped the new license for these dams. Tacoma Power and stakeholders signed a Settlement Agreement on August 10, 2000 and the new license for the Cowlitz River project became effective on July 18, 2003. Through formal consultation with NMFS, Tacoma Power received a Biological Opinion on March 23, 2004 for the operation of the Cowlitz River Project. The emphasis of the Settlement Agreement is the restoration and recovery of wild, indigenous salmonid runs to healthy and harvestable levels. The Settlement Agreement states that “Fisheries obligations will be met through a combination of effective upstream and downstream passage, habitat restoration and improvement, an adaptive management program to restore natural production coupled with continued artificial production to compensate for unavoidable impacts at levels consistent with ESA recovery, and providing fish production for sustainable fisheries.”
Currently, an extensive reintroduction program is underway to restore the anadromous migration corridor between the upper and lower Cowlitz River basins. The key to this effort is improving juvenile downstream passage once fish have successfully spawned and reared in the upper Cowlitz River. Plans to improve this passage are currently being implemented. Successful recovery of salmonids to the Cowlitz River basin also includes minimizing the impacts of hatchery programs on populations currently spawning in the tributaries and main stem of the lower Cowlitz River. Hatchery programs have been reformed to support the reintroduction and minimize impacts to lower Cowlitz River populations while continuing to support fisheries. At present, there is significant uncertainty about key metrics (e.g., abundance and proportion of hatchery spawners) for these lower Cowlitz River populations, resulting in an increased monitoring effort.
The Settlement Agreement directed a Fisheries and Hatchery Management Plan (FHMP) to be developed every six years and the initial plan was completed in 2004. The current FHMP was updated and submitted to the Federal Energy Regulatory Commission in 2011. This updated plan included an adaptive management process to use new information about key population parameters for Cowlitz River salmonid populations to make management decisions. Appendix J of the updated plan outlined a monitoring and evaluation program to obtain this new information. Specifically, the monitoring and evaluation program was designed to obtain unbiased estimates of key metrics with a precision level recommended for monitoring the recovery of Pacific
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Northwest salmon and steelhead listed under the Federal Endangered Species Act (Crawford and Rumsey 2011). The information provided by this monitoring and evaluation is essential to adaptive management of hatchery production and successful hatchery reform.
This report provides the results of the Monitoring and Evaluation work that Tacoma Power has contracted with Washington Department of Fish and Wildlife to conduct in the lower Cowlitz River watershed during 2016. This information will provide input to improve the results of the FHMP Adaptive Management Process and addresses the objectives developed in the FHMP 2011 Update. In 2016, monitoring responsibilities for the lower Cowlitz River were to:
1. Operate resistance board weirs on select tributaries in order to: (1) minimize HOR escapement of summer and winter steelhead and coho into major lower Cowlitz River tributaries, (2) collect NOR winter steelhead for an integrated hatchery broodstock program, (3) generate mark-recapture estimates of NOR winter steelhead and NOR coho in lower Cowlitz tributaries, and 4) enumerate fall Chinook handled at the weir (FHMP Update – Appendix J, MA-J), 2. Estimate the spawner abundance, composition and distribution of winter steelhead in lower Cowlitz River tributaries (FHMP Update – Appendix J, MA-A and MA-J), 3. Estimate the spawner abundance, composition and distribution of spring and fall Chinook salmon in the Cowlitz River below the Barrier Dam (FHMP Update - Appendix J, MA- A), 4. Estimate the spawner abundance, composition and distribution of coho salmon in lower Cowlitz River tributaries (FHMP Update – Appendix J, MA-A and MA-J), 5. Describe the effort, catch rates, and NOR:HOR ratios in Cowlitz River fisheries in 2016 (FHMP Update- Appendix J, MA-C), 6. Derive catch estimates of NOR Chinook, coho and steelhead in Cowlitz River fisheries in 2015 (FHMP Update- Appendix J, MA-C), 7. Summarize counts, biological data, and disposition from returns to Barrier Dam, including hatchery broodstock sampling (FHMP Update – Appendix J, MA-E and MA-I), 8. Evaluate hatchery juvenile diet, predation, and presence timing in the lower Cowlitz River (FHMP Update – Appendix J, MA-B), 9. Operate a rotary screw trap in the lower Cowlitz River to assess smolt abundance and timing. Collect genetic samples from juvenile Chinook to facilitate potential future
Page 14 of 119 genetic mark-recapture estimation of Chinook natural spawning abundance (FHMP Update – Appendix J, MA-B).
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Methods
Study Site
The Cowlitz River is located in southwest Washington State and drains approximately 2,480 square miles of the west slope of the Cascade mountain range over a distance of 151 miles before it joins the Columbia River about 68 river miles upstream from the Pacific Ocean (Serl and Morrill, 2011). The Cowlitz River is divided in the upper and lower watershed by three main stem hydroelectric dams. The principle tributaries to the upper Cowlitz River include the Cispus and Tilton Rivers. The principle tributaries on the lower Cowlitz River include the Toutle and Coweeman Rivers and Mill, Salmon, Lacamas, Olequa, Blue, Arkansas, Delameter and Ostrander creeks (Figure 1). The Cowlitz River watershed has headwaters on three active volcanos. The Cowlitz River originates on Mt. Rainer, the Cispus River originates on Mt. Adams and the Toutle River originates on Mt. St. Helens.
Figure 1. Map of the lower Cowlitz River basin showing locations of major tributaries below Mayfield Dam. Although the Toutle and Coweeman rivers flow into the Cowlitz River, fish populations in these tributaries are managed (and monitored) separately from the remainder of the lower Cowlitz River.
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Anadromous fish populations on the Cowlitz River occur in three general areas, lower Cowlitz and tributaries below Mayfield Dam, the Tilton River sub-basin and the upper Cowlitz sub-basin including the upper Cowlitz and Cispus Rivers. The lower Cowlitz River populations that have Lower Columbia Fish Recovery Board recovery goals are fall Chinook, chum (summer and fall), winter steelhead and coho. Coho are designated a Primary recovery priority while the remaining populations are designated as Contributing. The Tilton River spring Chinook and coho are designated as Stabilizing and the winter steelhead are designated as Contributing. Fall Chinook in the upper Cowlitz, including Cispus and Tilton Rivers, are combined as one Stabilizing population. The remaining populations in the upper Cowlitz are designated as Primary recovery priority and include spring Chinook, winter steelhead and coho. Anadromous cutthroat also exist in both the Tilton and upper Cowlitz basins, but are not listed under the Endangered Species Act.
The Cowlitz Hatchery complex consists of the Cowlitz Salmon Hatchery, situated approximately two miles below Mayfield Dam, and the Cowlitz Trout Hatchery, situated approximately seven miles downstream of the salmon hatchery. The Cowlitz Salmon Hatchery has facilities for adult recovery and broodstock collection, adult holding and spawning facilities, early incubation for all species and juvenile rearing for coho, fall and spring Chinook. The Cowlitz Salmon hatchery has both segregated coho production and coho production integrated with the upper Cowlitz population. The Cowlitz spring Chinook hatchery stock is currently maintained as a segregated hatchery stock originally derived from the natural Cowlitz River population (FHMP, 2011). The fall Chinook population is currently maintained partially as a segregated population and partially as a population integrated with the lower river natural population. The Cowlitz Trout Hatchery rears late winter steelhead, summer steelhead and sea- run cutthroat trout. Winter steelhead production consists of three integrated stocks. Portions of the winter steelhead production are integrated with the upper Cowlitz, Tilton and lower Cowlitz tributary populations. The upper Cowlitz (right ventral fin clip) and Tilton (left ventral fin clip) production is uniquely marked for stock identification. The summer steelhead production is maintained as a segregated hatchery program of Skamania stock origin. The sea-run cutthroat production is currently maintained as a segregated hatchery program.
Cowlitz hatchery stocks for late winter steelhead, coho and spring Chinook were derived from the natural populations in the Cowlitz River. Therefore, these stocks were used as the basis
Page 17 of 119 for reintroducing anadromous fish to the upper Cowlitz River watershed in 1996 when smolt collection was added to the then new Cowlitz Falls Dam (CFD) constructed just upstream from Riffe Lake. The upper Cowlitz River reintroduction is based on trap and haul of both juveniles and adults to reconnect the historically productive habitat upstream of the CFD to the lower Cowlitz River migration corridor. Juveniles collected at the CFD are transported to the Stress Relief Ponds, located at the Cowlitz Salmon Hatchery, for a short recovery time before being released into the lower Cowlitz River via a release pipe that enters the river immediately downstream of the Barrier Dam fish ladder entrance. Juveniles not collected at CFD pass through the turbines and enter Riffe Lake and rarely continue their migration. The proportion of the juvenile fish collected and transported during their ocean ward migration has been identified as an important limiting factor to this reintroduction effort (Tacoma Power, 2011). Adults returning to the Barrier Dam, both natural and hatchery-origin, are transported by Tacoma Power in a truck for release into the upper Cowlitz River Watershed at Lake Scanewa or release sites on the upper Cowlitz or Cispus Rivers. Naturally produced and integrated coho and winter steelhead are transported to the upper Cowlitz River Watershed. Chinook transported to the upper Cowlitz include naturally produced and segregated hatchery stock spring Chinook and a small number of hatchery stock fall Chinook.
Natural anadromous fish production in the Tilton River still utilizes the original juvenile bypass system. Adults, both of natural and hatchery-origin, are transported to the Tilton River by truck as the Barrier Dam blocks access to the base of Mayfield Dam. Natural and segregated hatchery stock coho adults, natural and integrated adult winter steelhead, natural and hatchery fall Chinook adults are scheduled for release into the Tilton River.
Tributary Weir Operation
Resistance board weir operations on lower Cowlitz tributaries began in 2011 when WDFW was funded by the Columbia River Salmon and Steelhead Recreational Angler Board (CRSSRAB) to construct, install, and operate four resistance board weirs on select lower Cowlitz River tributaries. In 2015, Tacoma Power added an additional five months of funding to the existing seven months of operation and maintenance funding of these weirs to allow for year around operation. The original objective for these weirs was to exclude non-indigenous (Skamania stock) hatchery summer steelhead from straying into lower Cowlitz River tributaries
Page 18 of 119 and interacting (i.e., spawning and competing) with natural-origin winter steelhead. Once established, the weirs have served multiple purposes of monitoring and evaluation, fish management (e.g., control proportion of hatchery-origin spawners), and broodstock collection (winter-run steelhead).
Resistance board weirs were operated on four tributaries to the lower Cowlitz River in 2016 (Figure 2). Ostrander, Delameter, Olequa, and Lacamas Creek weirs were operated throughout the winter-run steelhead and coho salmon return (spawn year 2016) and were used to make mark-recapture estimates of spawner abundance for each species. The weirs were operated twelve months of the year. Original installation of the Ostrander Creek (entering the Cowlitz River at RM 8.7) weir was completed on September 4, 2013, the Delameter Creek (entering the Cowlitz River at RM 16.6) weir on July 15, 2011, the Olequa Creek (entering the Cowlitz River at RM 29.8) weir on June 1, 2011, and the Lacamas Creek (entering the Cowlitz River at RM 27.6) weir on December 20, 2013. Each weir was installed at a location as low as practical in each tributary so that the majority of available spawning habitat was above the weir site. Weir locations were selected based on numerous criteria including accessibility, landowner agreement, stream width, hydrology, substrate, and streambed uniformity. Each weir was comprised of a series of joined panels anchored to a substrate rail (Figure 3). The downstream end of each panel floats at the water surface due to resistance boards positioned perpendicular to the current and empty, air filled 55- gallon blue High Molecular Weight Polyethylene plastic drums attached to the underside of the panels for additional buoyancy. Fish travelling upstream are guided along the substrate rail into a live box. A set of cod fingers contains fish once they have entered the live box. Live fish travelling in a downstream direction were funneled into a downstream live box or seined from holding areas above the weir. Carcasses travelling in a downstream direction washed up on the weir panels and were removed for processing.
Weir traps were checked daily. All fish collected in live boxes were identified to species and run (i.e., summer versus winter steelhead). Biological data collected from salmonids included fork length (FL), age (scale sample), sex, life stage, mark status (ad-clipped, unmarked), coded- wire tag status (present/absent), and capture type (maiden, recapture). Coho were assigned as jacks in the field when less than 47-cm FL and age was updated with the results of scale analysis after the season. A genetic sample (fin tissue) was collected from all steelhead. Tag status (Floy®
Page 19 of 119 tag numbers, opercle punch) was noted for recaptures. After processing, live salmonids were Floy® tagged (two tags with sequential numbers) and opercle punched to indicate that they had been sampled. Natural-origin fish (unmarked salmonids and all other species) were released in the direction of travel. Hatchery-origin fish (ad-clipped salmonids) were culled. Data were collected using Panasonic Toughpad® tablets and downloaded daily into the standardized Traps-Weirs-Surveys (TWS) Microsoft Access database used to archive all adult monitoring data for all Lower Columbia tributaries. Ages were determined from scale samples by the WDFW Scale Ageing Laboratory (Olympia, WA). Steelhead genetic samples were archived with the WDFW Molecular Genetics Laboratory (Olympia, WA).
Figure 2. Location of resistance board weirs on four lower Cowlitz River tributaries in 2016.
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Figure 3. Resistance board weir on Olequa Creek, a lower Cowlitz River tributary. Floating panels are anchored to a substrate rail at their upstream end (right side of picture) and lifted by a series of resistance boards fastened to the underside of the panels on their downstream end (left side of picture). Live box shown in this picture captures fish moving in an upstream direction (moving from right to left side of the picture).
Steelhead Spawner Surveys
Census spawning surveys were conducted throughout the known distribution for steelhead above weirs on Ostrander, Delameter/Monahan, and Olequa creeks as well as below the weirs on Ostrander and Olequa creeks and on Arkansas Creek. In addition, index surveys were conducted in 30 one-mile reaches selected in a generalized random tessellation stratified design (GRTS) throughout the modeled spawning distribution of steelhead, including Lacamas, Blue, and Salmon creeks (Figure 4). Analysis of these data relies on accurate identification of the steelhead spawning distribution. When monitoring of steelhead spawners in Lower Cowlitz River tributaries began in 2015, the survey area was identified using modeled spawner distribution for steelhead. This model was derived using GIS-based watershed characteristics (stream gradient, upstream basin area, elevation, and mean annual precipitation; Fransen et al. 2006, adapted to lower Cowlitz River tributaries in 2011 FHMP Update). The steelhead distribution was further validated in 2016 by means of physically surveying the entirety of the modeled distribution and identifying any
Page 21 of 119 reaches within this area that did not have suitable spawning gravels or where access was prevented by a migration barrier. Suitable spawning gravels were defined as areas at least two foot by two-foot square patch of gravel consisting of a substrate composition of gravel/cobble that is ≥ 6-8mm (fine gravel) and ≤128-180mm (large cobble) at least six inches deep, located within the active channel or bankfull width of stream. (2017 WDFW Region 5, Coho Field protocols). Migration barriers for steelhead were defined according to WDFW SHEAR division (Salmonid Screening, Habitat Enhancement, and Restoration), and consisted of a waterfall greater than 3.7 meters (12.1ft) or a sustained gradient ≥20% for a distance ≥1620 meters, or when the channel has a sustained gradient ≥16% for a distance ≥160 meters and a channel width ≤0.6 meters as measured at the ordinary high water width. Within the census survey areas, a portion of the potential spawning distribution was not surveyed due to lack of suitable spawning gravels or migration barriers (i.e., 17 miles not surveyed of the 74 miles within the census survey areas). For the purpose of analysis, we have assumed there are zero redds in these reaches. The non-surveyed areas included three reaches above the Olequa Creek weir and two reaches below the Delameter Creek weir which did not have suitable spawning gravel. In addition, the lowest reaches in Arkansas, Delameter, Stillwater (Olequa sub-basin), and Brim Creeks (Olequa sub-basin) are lower gradient with silt and bedrock substrate that is not suitable spawning gravel. The middle reach of King Creek (Olequa sub-basin) has fast-flowing water with bedrock substrate, also unsuitable spawning gravel. A culvert at river mile 1.74 on Ostrander Creek is believed to be a barrier to fish passage, although the reach upstream from this culvert continues to be surveyed for fish presence during peak spawning week. Spawner surveys were conducted once every two weeks, from early February to late May depending on conditions. Each reach was surveyed by foot or raft in a downstream direction. Surveyors used polarized sunglasses, recorded visibility on a qualitative scale from 1 to 5 (Poor, Fair, Good, Very Good, and Excellent), and measured clarity to the nearest 0.5 feet using a modified secchi disk. During surveys, each new steelhead redd was identified by substrate disturbance and characteristics of a pitt, mound and tailout. Redds were documented as new, still visible, not visible or not observed. New redds were flagged with a redd number, date, and surveyor. Garmin Oregon 550 units generated a waypoint with latitude and longitude (NAD83 coordinate system, hddd.dddddᵒ format) for each new redd. Data were entered into the standardized TWS Microsoft
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Access database used to archive adult monitoring data for all Lower Columbia tributaries. Additionally, live fish observed were counted by hatchery, natural or unknown origin and tagged, untagged or unknown.
Figure 4. Winter-run steelhead spawner survey reaches in 2016 (including redds) and modeled distribution of steelhead in lower Cowlitz River tributaries. Modeled distribution is based on GIS-derived watershed characteristics as per the Cowlitz Monitoring and Evaluation Plan (FHMP Appendix J) published in 2011.
Chinook Spawner Surveys
Chinook spawner surveys were conducted on the main stem Cowlitz River between Castle Rock and Barrier Dam (Figure 5). Helicopter aerial surveys were conducted between mid- September and early-November, as conditions permitted. No flights were conducted in late- November or December due to high and turbid river conditions and flows ranging between 8,700 and 13,900 cfs. The purpose of the aerial surveys was to determine peak redd counts for spring and fall Chinook salmon. Boat surveys were conducted weekly between late August and mid- Page 23 of 119
November. The purpose of these boat surveys was to enumerate and biologically sample Chinook carcasses. Chinook redds were identified based on size, coloration, location, defined pit or bowl, and downstream tail-out. For each aerial survey, redd observations were tallied by reach and the location of each redd was georeferenced using GPS tracks, the time of the observation and the speed of travel for the aircraft. Redd counts on a given survey were the balance of redds still visible and no longer visible from previous surveys as well as new redds constructed between surveys. Carcasses were sampled for run (spring, fall), sex, fork length ( to 0.1 cm), scales (age), mark status (adipose-clip or unmarked), coded-wire tag presence (present/absent), and fin tissue (genetics). Snouts were retained from fish which scanned positive for coded-wire tags. Genetic samples were collected from fresh (clear eyes and pink gills) carcasses in order to implement the genetic mark-recapture study identified in the 2011 FHMP Monitoring and Evaluation plan (Rawding et al. 2014b). All age classes of hatchery Chinook returning in 2016 to the Cowlitz River were identifiable by the absence of an adipose fin. Twenty-five percent of all hatchery- origin fall Chinook were biologically sampled, 100% of spring Chinook and unmarked fall Chinook carcasses were sampled. Data were entered into the standardized TWS Microsoft Access database used to archive adult monitoring data for all Lower Columbia tributaries. Scale ages were determined by the WDFW Scale Ageing Laboratory. Snouts collected with coded wire were extracted and decoded by the WDFW Coded-Wire Tag Laboratory.
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Figure 5. Fall Chinook salmon spawner survey area in the main stem Cowlitz River, 2016.
Coho Spawner Surveys
Census surveys were conducted throughout the entire modeled distribution for coho salmon above and below tributary weirs on Ostrander and Delameter/Monahan creeks as well as on Arkansas Creek. In addition, index surveys were conducted in 37 one-mile reaches throughout the modeled spawning distribution of coho salmon including Lacamas, Olequa, Blue, Salmon, Campbell creeks, and two unnamed lower Cowlitz tributaries (Figure 6). Index reaches were selected using the GRTS method applied to a selected survey frame. An additional four (4) reaches were part of the original “draw” of GRTS reaches but were not surveyed because they were located upstream of or contained migration barriers (i.e., waterfalls, culverts) or were determined to lack adequate spawning gravels. For analysis purposes, these reaches were assumed to have zero redds. GRTS is a spatially balanced design for selecting survey reaches needed to obtain unbiased estimates of the redd density and distribution that can be applied to
Page 25 of 119 non-surveyed portions of the watershed (Stevens and Olsen 2004). The GRTS design is applied across the Lower Columbia River ESU with an initial goal of surveying the lesser of 30 reaches or 30% of the stream miles occupied by each population. This initial survey goal was based on ODFW calculations of the intensity of Oregon coastal coho surveys (Rawding and Rodgers 2013) needed to achieve a spawner estimate that met NOAA guidelines for precision (CV = 15%). As a time series from Cowlitz River tributaries become available, this initial survey goal needs to be further evaluated with respect to precision of the coho spawner estimates in Cowlitz River tributaries. GRTS sites are surveyed according to a rotating panel which is evenly divided into sites that are visited annually, every third year, and every ninth year. The survey frame for GRTS site selection was based on modeled coho spawning distribution in the lower Cowlitz River tributaries. A predictive model of the upper extent of coho spawner distribution was modeled using presence-absence data which was related to GIS-derived watershed characteristics including stream gradient, upstream basin area, elevation, and mean annual precipitation using logistic regression (Fransen et al. 2006 adapted to lower Cowlitz River tributaries in 2011 FHMP Update). This upper extent was then truncated where migration barriers were known to exist. The bottom of coho spawner distribution was defined as the lowest extent of spawning gravels; however, main stem areas were excluded from modeled distribution in the lower Cowlitz River. Surveys of each coho reach were conducted every 7 to 10 days between October and January. Surveys were conducted in a downstream direction by foot or raft. Surveyors used polarized sunglasses, recorded visibility on a qualitative scale from 1 to 5 (Poor, Fair, Good, Very Good, and Excellent), and measured clarity to the nearest 0.5 feet using a modified secchi disk. In each survey reach, observations of redds, carcasses, and live coho spawners were recorded. Redds were identified by substrate disturbance and characteristics of a pit, mound and tail-out and were recorded as new, still visible (SV), not visible (NV) or not observed (NO). New redds were flagged with a redd number, date, and surveyor. Data were collected using Apple® iPad mini tablets and new redds were flagged with a redd number, date, and surveyor. The iPad units generated a waypoint with latitude and longitude for each new redd. Carcasses were sampled for sex (male, female), fork length, scales, mark status (adipose-clip or unmarked), coded-wire tag presence (present/absent), spawn success (females only), and recaptures from fish tagged at the weirs (Floy® and opercle punch). In the field, a male coho less than 47-cm FL was considered a jack coho; after the survey season, age was corrected using scale analysis. Snouts were retained from fish which scanned positive for coded-wire tags. Live fish were recorded as
Page 26 of 119 holders or spawners, as defined by WDFW Region 5 spawner survey protocols (L. Brown, WDFW, personal communication). “Holders” were fish found to be milling around/holding in areas where spawning does not occur (pools and long glides without spawning substrate). “Spawners” were any fish not defined as a holder, including fish found in areas with spawnable habitat (in, on, or around, tailouts, riffles, and glides with spawning substrate). Data were downloaded daily from iPad tablets into the standardized TWS Microsoft Access database used to archive adult monitoring data for all Lower Columbia tributaries. Scale ages were determined by the WDFW Scale Ageing Laboratory. Snouts collected with coded wire were decoded by the WDFW Coded-Wire Tag Laboratory.
Figure 6. Coho salmon spawner survey reaches in 2016 with redds and modeled distribution of coho salmon in lower Cowlitz River tributaries. Modeled distribution is based on GIS-derived watershed characteristics as per the Cowlitz Monitoring and Evaluation Plan (FHMP Appendix J) published in 2011.
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Estimates of Spawner Abundance and pHOS
Chinook salmon spawner abundance was estimated by the peak redd counts adjusted by an expansion factor of 2.84 fish per redd. This expansion factor was developed for fixed wing aerial surveys using a carcass tagging mark-recapture study conducted in 1992 (Hymer 1994) and subsequently modified for helicopter aerial surveys (WDFW, unpublished data). No precision estimate is available for this method. Redd counts used in these calculations were from aerial surveys conducted during peak spawning. Based on historical survey efforts in the Cowlitz River, peak spawning week is typically the third week of September for spring Chinook and the first week of November for fall Chinook. In 2016, aerial surveys were not conducted after October 27th due to high water and poor visibility. Therefore, the ‘peak’ number of fall Chinook redds was estimated by expanding the October 27th count by the proportion of peak redd count that had been observed the last week of October in the previous ten years. The proportion of hatchery-origin spawners (pHOS) for Chinook salmon was calculated based on the mark rate (clipped or intact adipose fin) from carcasses recovered from all surveyed areas of the main stem and tributaries. Hatchery and natural spawners were further apportioned into stock of origin and age class. Origin and ages of hatchery spawners were apportioned using coded-wire tag data. Origin of natural spawners was assigned as spring or fall run and ages of natural spawners were apportioned using scale ages. Coded-wire tag recoveries in natural spawners can occur (e.g., Lewis River fall Chinook), and these are used to apportion out-of-basin natural spawners. Estimates of spawner abundance for coho salmon and steelhead were derived for tributaries; a similar method was used for both species. No estimation method is currently implemented for main stem spawning of these species. Tributary spawner abundance was based on mark- recapture estimates above tributary weirs and redd expansion in areas of the watershed where no mark-recapture estimates were available (Table 2). Abundance of spawners above tributary weirs was estimated for unmarked fish tagged and released upstream of each weir and later recaptured as carcasses (coho, steelhead) or kelts (steelhead). Carcasses were recovered during stream surveys and as wash-ups on the weir panels. Kelts were examined upon entry into a downstream trap box built into the weir structure or when captured just upstream of the weir. Tagging and recapture data were used to evaluate assumptions of a closed-population mark-recapture estimator (Seber 1982). Data were analyzed in a Bayesian framework using the ‘rjags’ and ‘R2jags’ packages in R© (Su and Yajima 2015, Plummer 2016). Summary statistics and derived Page 28 of 119 parameters used for the analysis are provided in Tables 1 and 2. Parameters were estimated using Markov Chain Monte Carlo sampling with 3 chains of 1,000,000 samples each (burn-in of 200,000 samples, thinning 1,000 samples). A Jeffries prior (0.5, 0.5) was used when deriving estimates of the proportion tagged and the proportion of spawners of hatchery-origin. A uniform prior (0, 3000) was used when deriving the estimate of unmarked spawners above the weir.
Table 1. Summary statistics used for mark-recapture estimates of spawner abundance above tributary weirs on the lower Cowlitz River. Statistic Definition
n1 number of live unmarked fish that were tagged and passed upstream of tributary weir
n.um2 number of unmarked carcasses and kelts recovered upstream of tributary weir, includes tagged and untagged recoveries
m2 number of tagged carcasses and kelts recovered upstream of tributary weir
푛. 푎푑2 number of adipose clipped carcasses and kelts recovered upstream of tributary weir
푛. 푡표푡2 total number of carcasses and kelts recovered upstream of tributary weir, includes unmarked and adipose clipped recoveries
Table 2. Derived parameters and likelihoods used for mark-recapture estimate of spawner abundance above tributary weirs on the lower Cowlitz River. Parameter Description Likelihood/Equation
푝̂푡푎푔 Proportion of tagged unmarked fish 푚2~푑푏푖푛(푝̂푡푎푔, 푛. 푢푚2) estimated from recovery of unmarked carcasses and kelts in the second sample 푝̂푡푎푔 ~ 푏푒푡푎(푎, 푏)
푁̂푁푂푅 Number of unmarked spawners above weir 푛1~푑푏푖푛(푝̂푡푎푔, 푁̂푁푂푅) estimated from the number of unmarked fish released upstream of the weir and the proportion of tagged unmarked carcasses and kelts recovered above the weir
푝̂퐻푂푆 Proportion of spawners above weir that are 푛. 푎푑2~푑푏푖푛(푝̂퐻푂푆, 푛. 푡표푡2) of hatchery-origin estimated from recovery 푝̂ ~ 푏푒푡푎(푎, 푏) of adipose clipped and total carcasses and 퐻푂푆 kelts in the second sample
푁̂푇푂푇 Number of total spawners above weir 푁̂푇푂푇 = 푁̂푁푂푅/(1 − 푝̂퐻푂푆) estimated from the unmarked spawners and the proportion of spawners of hatchery- origin above weir Page 29 of 119
푁̂퐻푂푅 Number of spawners above weirs of 푁̂퐻푂푅 = 푁̂푇푂푇 − 푁̂푁푂푅 hatchery-origin estimated from the total and the unmarked spawners above weir
푊퐸̂ Weir efficiency estimated from the number 푊퐸̂ = 푛1/푁̂푇푂푇 of unmarked fish released upstream of the weir and the number of total spawners above the weir
Spawner numbers in areas not included in the mark-recapture estimate (i.e., outside the tributary weirs) were derived from (1) an estimated number of redds in spawning reaches outside the tributaries with weirs, (2) an estimated female per redd ratio, (3) an estimated proportion of females, and (4) an estimated proportion of hatchery-origin spawners. Summary statistics and derived parameters used for the analysis are provided in Tables 3 and 4. The total number of redds outside the tributary weirs was the sum of observed redds in surveyed reaches (GRTS, other index) and estimated redds in non-surveyed areas. Redds in non-surveyed areas were estimated using the redd density in GRTS reaches applied to the non-surveyed miles within the sampling frame for each species. The female per redd ratio was derived using the mark-recapture estimate above selected tributary weirs and the count of redds observed above weirs in those tributaries. The proportion of females was derived from adults captured at all tributary weirs. The proportion of hatchery fish was estimated from live fish captured in tributary weirs and carcasses recovered in survey reaches outside of tributaries with weirs. The spawner estimate in areas not included in the mark-recapture estimate was apportioned into natural-origin and hatchery-origin fish based on the estimated proportion of hatchery fish. Due to the high proportion of hatchery- origin steelhead observed to spawn in Blue Creek and hatchery-origin coho salmon in Brights Creek, redd counts and calculations to apportion origin (natural, hatchery) were analyzed separately for these reach/species combinations for the 2016 spawn year. Data were analyzed in a Bayesian framework using the ‘R2WinBUGS’ packages in R© (Sturtz et al. 2005) using the methodology described in Rawding et al. (2014a).
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Table 3. Summary statistics used for redd-based estimates of spawner abundance in areas outside of tributary weirs on the lower Cowlitz River. Statistic Definition
푟. 푎푏표푣푒 number of redds observed above weirs with mark-recapture data used to derive redd per female (rpf) parameter 푟. 푔푟푡푠 number of redds observed in all surveyed GRTS reaches outside of weirs 푟. 푖푛푑푥 number of redds observed in all surveyed reaches outside of weirs, excluding GRTS reaches
r vector of redds counts for i GRTS reaches (푟1….푟푖) 푠푖푡푒푠 number of 1-mile GRTS index reaches
푛. 푡표푡1 number of maiden adult fish captured in tributary weirs, includes natural- origin and hatchery-origin fish
푛. 푓푒푚1 number of maiden females captured in tributary weirs, includes natural- origin and hatchery-origin fish
푛. 푎푑1 number of adipose-clipped adult fish captured in tributary weirs
푛. 푎푑2 number of adipose clipped carcasses and kelts recovered upstream of tributary weir
푛. 푡표푡2 total number of carcasses and kelts recovered upstream of tributary weir, includes unmarked and adipose clipped recoveries
푑푚푖푠푠푒푑 distance (miles) not surveyed within the sampling frame
Table 4. Derived parameters and likelihoods used for redd-based estimates of spawner abundance in areas outside of tributary weirs on the lower Cowlitz River. Parameter Description Likelihood/Equation p, r Negative binomial parameters (p, r) 푟~푑푛푒푔푏푖푛(푝, 푟) estimated from redd count data in GRTS index reaches λ Redd density estimated from negative 휆~푑푛푒푔푏푖푛(푝, 푟) binomial parameters (r, p) 푝~푑푏푒푡푎(푎, 푏) 푝~푑푔푎푚푚푎(푎, 푏)
푟푚푖푠푠푒푑̂ Missed redds estimated from redd density 푟푚푖푠푠푒푑̂ = 휆 ∗ 푑푚푖푠푠푒푑 and non-surveyed miles with sampling frame
푟푡표푡̂ Total number of redds estimated from 푟푡표푡̂ = observed redds in GRTS and other index 푟. 푔푟푡푠 + 푟. 푖푛푑푥 + 푟푚푖푠푠푒푑̂
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reaches and estimated redds in non- surveyed areas
푁̂푎푏표푣푒 Number of total spawners above weirs in 푁̂푎푏표푣푒 = 푑푛표푟푚(푁̂푤, 푡푎푢) tributaries included in the rpf parameter.
푁̂푤 is sum of weir mark-recapture estimates from Table X tau is the inverse of the variance associated with 푁̂푤from Table X.
푝̂푓 Proportion of adult fish that are female 푛. 푓푒푚1 ~ 푑푏푖푛(푝̂푓, 푛. 푡표푡1) estimated from the numbers of female and total adults captured in tributary weirs 푝̂푓 ~ 푏푒푡푎(푎, 푏)
퐹̂푎푏표푣푒 Number of females above weirs in 퐹̂푎푏표푣푒 = 푝̂푓 ∗ 푁̂푎푏표푣푒 tributaries included in the rpf parameter. Females are estimated from the proportion of adult fish that are female and the number of total spawners above weirs used to derive rpf parameter.. ̂ 푟푝푓̂ Redd per female estimated from number of 푟푎푏표푣푒~ 푑푏푖푛(푟푝푓 ∗ 퐹̂푎푏표푣푒) females and number of redds observed ̂ above weirs. 푟푝푓~ 푏푒푡푎(푎, 푏) ̂ ̂ 퐹푡표푡 Total number of female spawners 퐹̂푡표푡 = 푟푡표푡̂ /푟푝푓 estimated from total number of redds and rpf parameters
퐴̂푡표푡 Total number of adult spawners estimated 퐴̂푡표푡 = 퐹̂푡표푡/푝̂푓 from total number of females and the proportion of females
푝̂퐴퐷 Proportion of adipose-clipped adults 푛. 푎푑1 ~ 푑푏푖푛(푝̂퐴퐷, 푛. 푡표푡1) outside of tributary weir areas estimated 푝̂ ~ 푏푒푡푎(푎, 푏) from the number of adipose-clipped to 퐴퐷 total adults sampled as live weir captures or as carcasses outside of weir areas
퐴̂푁푂푅 Number of natural-origin adult spawners 퐴̂푁푂푅 = 퐴̂푡표푡 ∗ (1 − 푝̂퐴퐷) estimated from total number of adult spawners and the proportion of adults with an adipose clip
퐴̂퐻푂푅 Number of hatchery-origin adult spawners 퐴̂퐻푂푅 = 퐴̂푡표푡 ∗ 푝̂퐴퐷 estimated from total number of adult spawners and the proportion of adults with an adipose clip
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Spot Creel Surveys
Spot creel surveys were conducted for winter steelhead, spring and fall Chinook salmon, coho salmon and incidental summer steelhead between January 20, 2016 and December 31, 2016. Surveys were conducted on a daily basis. A single creel surveyor visited each of the ten interview locations between Gerhart Gardens at the mouth of the Cowlitz River and Barrier Dam and interviewed subsets of all boat and shore anglers at each location (Figure 7). Time spent at each interview location was proportional to the relative number of anglers at that location. In 2016, the Cowlitz Monitoring and Evaluation staff surveyed areas from Camelot (just below town of Castle Rock) to the Barrier Dam. Additional surveys below the I-5 bridge were conducted by WDFW staff from the Region 5 Vancouver office. This report includes results from both survey teams. Information collected included fishing method (boat, shore), start time, count of fish kept by species and origin (hatchery, natural). Coho were determined to be jacks when less than 47 cm fork length (FL). Fall Chinook were determined to be jacks when less than 56 cm FL and for spring Chinook when less than 59 cm FL. Landed catch was sampled for scales and coded-wire tags. Angler reported information included count of fish released by species and origin (hatchery, natural). Effort (number of anglers, hours fished) was summarized by month and location for boat and shore anglers. The summarized effort data are an index that represents relative effort among locations; an estimate of total effort will require a different and more rigorous statistical design for the creel surveys. Catch (NOR released, HOR retained) was summarized by location for boat and shore anglers. Similar to effort, the summarized catch data are an index of catch that show relative differences among locations on the lower Cowlitz River. Total catch was estimated using the approach described in the next section.
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Figure 7. Creel survey locations on Cowlitz River, 2016. Locations include Barrier Dam (1), Blue Creek (2), Mission Bar (3), Toledo Ramp (4), I-5 Ramp (5), Olequa Ramp (6), Toutle Confluence (7), Castle Rock Ramp (8), Camelot (9), and Gerhart Gardens (10).
Estimated Catch for Natural-Origin Fish in the Cowlitz River Fishery
Catch of natural-origin fish in the lower Cowlitz River was estimated using a combination of creel survey results and catch record card estimates. This method was recently demonstrated to be unbiased for winter steelhead when run timing of natural-origin and hatchery-origin fish overlap in the fishery (Bentley et al. 2015). Because catch record card data estimates are available twelve to eighteen months after the fishery occurs, these estimates necessarily lag behind the current sampling year. In this report, we provide catch estimates for the 2015 fishery for winter steelhead (November 2014-April 2015), Chinook, and coho in the Cowlitz River below Mayfield Dam, including Blue Creek.
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Catch record cards (CRC) are a self-reporting method used by WDFW to collect catch information for harvested fish of certain species (e.g., Kraig and Smith 2010). A uniquely numbered CRC is issued to all anglers who purchase a fishing license and indicate their intent to fish for salmon or the other catch card species (steelhead, sturgeon, and halibut). Anglers are legally required to record the species, date, location, and origin of all fish that they harvest and return their CRC each year. Prior to the license year, WDFW CRC unit randomly selects 25% of the issued CRC to be in the “in-sample” group. In-sample group CRCs that are returned are used to generate catch estimates, while out-of-sample CRCs that are returned are used in addition to the in-sample group to apportion catch among months. If in-sample CRCs are not returned voluntarily, multiple reminders are sent out to increase the return rate. Total harvest is estimated by multiplying reported catch by the sample proportion expansion factor (i.e., proportion of returned CRCs) and a non-response bias correction factor. Because CRCs collect catch data for harvested hatchery-origin salmon and steelhead only, additional information from the creel surveys were applied to estimate catch data for the released natural-origin salmon and steelhead. Catch estimates of natural-origin fish were derived from the proportions of hatchery-origin catch sampled in the creel and the CRC estimate of hatchery-origin fish caught in the fishery. Data were analyzed in a Bayesian framework using the ‘rjags’ and ‘R2jags’ packages in R© (Su and Yajima 2015, Plummer 2016). Summary statistics and derived parameters used for analysis are provided in Tables 5 and 6. Parameters were estimated using Markov Chain Monte Carlo sampling with 3 chains of 1,000,000 samples each (burn-in of 200,000 samples, thinning 1,000 samples). A Jeffries prior (0.5, 0.5) was used for the estimate of proportion of hatchery-origin fish in the creel sample. Catch estimates for each species were calculated by month and then summed for the entire reason. Credible intervals (95%) associated with the estimate were calculated from the posterior distribution of the analysis.
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Table 5.Summary statistics used for estimating catch of natural-origin fish in the lower Cowlitz River fishery. Statistic Definition
Stot Total number of fish sampled in the creel, includes harvested hatchery- origin fish and reported released natural-origin fish
Shor Total number of harvested hatchery-origin fish sampled in the creel
Table 6. Derived parameters and likelihoods used for estimating catch of natural-origin fish in the lower Cowlitz River fishery. Parameter Description Likelihood/Equation
퐶̂퐻푂푅 Number of harvested hatchery-origin fish 퐶̂퐻푂푅
estimated from catch record card data. = 푑푛표푟푚(퐶푅퐶̂퐻푂푅, 푡푎푢퐻푂푅)
퐶푅퐶̂퐻푂푅 is the estimate number 푡푎푢퐻푂푅 is the inverse of the variance associated with 퐶푅퐶̂퐻푂푅
푝̂퐻푂푅 Proportion of hatchery-origin fish in the 푆퐻푂푅~푑푏푖푛(푝̂퐻푂푅, 푆퐻푂푅) creel 푝̂퐻푂푅 ~ 푏푒푡푎(푎, 푏)
퐶̂푇푂푇 Number of fish estimated to have been 퐶̂푇푂푇 = 퐶̂퐻푂푅/푝̂퐻푂푅 caught in the fishery, includes harvested hatchery-origin fish and reported released natural-origin fish
퐶̂푁푂푅 Number of natural-origin fish estimated to 퐶̂푁푂푅 = 퐶̂푇푂푇 − 퐶̂퐻푂푅 have been caught and released in the fishery
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Chinook and Coho Hatchery Broodstock Composition
Chinook and coho spawner disposition at the Cowlitz Salmon Hatchery were summarized from the Cowlitz Salmon Separator database maintained by Tacoma Power (Scott Gibson, Tacoma Power, personal communication). Data were summarized as jack, male, and female using pre-established cutoffs between jacks and adult males for spring Chinook (>59 cm FL= adult), fall Chinook (>49 cm FL= adult), and coho (>42 cm FL= adult) salmon. Spring Chinook, fall Chinook and coho salmon retained for brood stock were biologically sampled. Spring Chinook are a segregated hatchery program and were sampled at a 1 in 3 rate. Fall Chinook have both a segregated and integrated hatchery program. Unmarked fall Chinook (collected from the river and used in the integrated program) were sampled at a 1 in 1 rate and adipose-clipped fall Chinook (used for either the integrated or segregated hatchery program) were sampled at a 1 in 3 rate. Coho have both segregated and integrated hatchery programs. Unmarked and coded-wire tagged coho (upper Cowlitz origin, used for integrated program) and adipose-clipped and coded-wire tagged coho (integrated hatchery-origin) were sampled at a 1 in 1 rate. Forty (40) total samples of adipose-clipped coho (segregated hatchery-origin) were sampled throughout the return. Data collected included species, run, sex, fork length (cm), scales (age), coded-wire tag status (present/absent–snouts were retained from all positive scans), and mark status (unmarked, adipose, or other clips). Biological sampling data were entered into the standardized TWS Microsoft Access database used to archive all adult monitoring data for all Lower Columbia tributaries. Scale ages were determined by the WDFW Scale Ageing Laboratory. Snouts collected with coded wire were extracted and decoded by the WDFW Coded-Wire Tag Laboratory.
Hatchery Juvenile Diet, Predation and Presence Timing in the Lower Cowlitz River
Collection sites used for the 2016 predation study were similar to used sites in 2015, however the effort for this monitoring was reduced in 2016 to allow staff to focus their efforts on the operation of the rotary screw trap. Collection sites sampled for hatchery fish were located between the hatchery release points and the mouth of the Toutle River, river mile (RM) 30 to RM 48, but focused on sites near the rotary screw trap due to the limited nature of this sampling (Figure 8). Sites sampled where catch occured included creek confluences, mouths of side channel spawning locations, and sites previously determined to have good sampling success in a
Page 37 of 119 cutthroat predation study. Sites that had abundant catches of juvenile hatchery fish were repeatedly sampled when possible. A small subsample of the hatchery smolts captured in the rotary screw trap were also sampled to gauge technique effectiveness, but these were not included in analysis due to the likely bias of holding these fish in a closed container with fry.
Hook-and-line sampling, using small artificial lures, was planned to be utilized at up to 25 distinct locations in the lower Cowlitz River during the 2016 sampling season while seining was limited to suitable areas (appropriate depth and smooth bottom) where the gear could be deployed. Predation sampling in 2016 was limited to times when staff were not otherwise occupied with rotary screw trap operation. When a juvenile salmonid was hooked and brought near the boat, the fish was quickly lifted into the boat and landed into a bucket filled with river water. Additional fish were collected until bucket capacity was reached or the sampling at that site was finished. Water quality in the bucket was maintained by changing water or aerating as needed. Once sampling was finished at a site or the bucket filled, the fish were sampled and released near the capture site.
All fish collected were identified by species, origin, and life stage. Salmonids were checked for the presence of CWTs and those with positive detections were noted along with visible marks or fin clips. Fork lengths of juvenile salmonids were recorded.
In 2016 non-lethal lavage methodology was used to obtain stomach samples. This consisted of a pressurized tank with river water connected to a probe that could safely be inserted into a juvenile fish’s stomach. Once the probe was placed into the stomach, water was released to flush the stomach contents into a dissecting tray. Prey items were identified and categorized in the field as Chinook, any salmonid, any fish, or other. Fish category prey items were counted in the field. Other prey items were counted or the number estimated and general type noted.
Collection events occurred between February and December in 2016 and focused on time periods that encompass fry emergence periods and hatchery release periods. Collection frequency was irregular and occurred when time allowed. The majority of collection events took place between the beginning of March and the end of June.
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Figure 8. Map of general predation sampling locations in the Lower Cowlitz River used in 2016.
Operation of a Rotary Screw Trap in the Lower Cowlitz River
Screw Trap Site & Installation The screw trap was located at river mile 23.2, one river mile below the WDFW Olequa Creek boat launch, and positioned off the mouth of Rock Creek (46.352367, -122.936976) (Figure 9). Site selection was evaluated based on specific river characteristics that would maximize trap efficiency, the anchor location, river accessibility, landowner agreements, and trap security. The trap can be moved laterally, upriver or down river about 20 feet without moving the anchor points in order to account for changing flows and to maximize fish capture efficiency rates. This site also features a protected low velocity area behind the Rock Creek delta where the trap can be moved to protect it during high river flows or for trap maintenance.
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The trap consists of an 8-foot cone that has interior baffles which are supported by a metal frame, and two 40-foot long pontoons. The structure is 16-feet wide and its tallest component is a 12-foot tall manual hoisting mechanism that moves the cone in and out of the water (Figure 10). The cone reaches approximately 4-feet below the surface of the water when lowered into position for fish collection. The trap is affixed with night time activated amber hazard blinking lights at all four corners and caution signs have been placed 200 meters upstream and downstream of the trap’s location. Informational and warning signs were placed at the Olequa Boat Ramp to alert boaters of the location and function of the trap. The bow lines of the smolt trap extend approximately 125 yards upstream and are anchored to a large cottonwood tree on the east bank and a large maple on the west bank. These lines are flagged for enhanced visibility and have sufficient clearance for boat traffic passing on the river.
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Figure 9. Site map of the Cowlitz River rotary screw trap location adjacent to the confluence of Rock Creek (RM 24).
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Figure 10. Cowlitz River rotary screw trap (CRST) fishing position located at the Rock Creek site.
Operation of the Screw Trap The lower Cowlitz rotary screw trap was intended to operate continuously in 2016, except when river flow was too high (i.e. 25,000 cfs or greater) or the trap needed repair. Trap efficiencies were estimated using mark-recapture of trap captured migrants. As many available migrants as practical and in good condition, up to a handling capacity limit, were used mark- recapture trap efficiency trials. Fish were not utilized for mark-recapture once the handling capacity of 500-800 juveniles was reached on sampling day. A marking rotation schedule for parr and smolts consisted of alternating marking weekly between upper caudal clip (UCC) and lower caudal clip (LCC). Bismark brown Y dye was used for staining and marking fry. All salmonids captured in the CRST were examined for marks and tags.
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All fish were enumerated by species, life stage, origin, mark and tag types. Life stage (fry, parr, transitional, smolt) was assigned based on Juvenile Life Stage Decision Tree developed for Lower Columbia juvenile monitoring programs (Appendix A). Coho, Chinook, and steelhead smolts were checked for the presence of internal (CWT or PIT) or external tags (Visual Implant Elastomer (VIE)). Biological data (length from steelhead and Chinook > 70 mm FL) were collected from a random sub-sample of up to approximately 30 fish per species per day. All data were entered into the WDFW Juvenile Migrant Exchange (JMX) Microsoft Access database. The release site used for marked fish was immediately upstream the railroad trestle bridge near a private boat launch, approximately one half mile upstream of the trap (46.357046,- 122.931355) and upstream of a bend that appeared to provide good mixing of released fish. Marked fish were held until fully recovered and were then transported upstream and released. Marking techniques utilized were Bismarck brown Y stain for fry and caudal fin clips for some fry and larger fish. Caudal fin clip marking also provided the material needed for genetic sampling of Chinook. Fin clip marks alternated between upper and lower caudle clips on a weekly basis for all species. Tag retention and mark related mortality was examined by holding a subset of fish for 24 hours post-marking last year and not repeated this season.
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Results
Monitoring Responsibility 1: Weir Operation in Four Tributaries to the Lower Cowlitz River
Winter steelhead, Chinook salmon, and coho salmon were captured in the tributary weirs. Additional species handled in the weir trap included largescale sucker (Catostomus macrocheilus), northern pikeminnow (Ptychocheilus oregonensis), mountain whitefish (Prosopium williamsoni), fall Chinook salmon (Oncorhynchus tshawytscha), chum salmon (O. keta), sockeye salmon (O. nerka), cutthroat trout (O. clarkii), and brown bullhead (Ameiurus nebulosus). Winter steelhead spawners and kelts (corresponding to the 2016 steelhead spawn year) were captured between November 1, 2015 and June 6, 2016 in both upstream and downstream traps on Delameter, Olequa, Ostrander, and Lacamas creeks. One summer-run hatchery steelhead was captured at the Delameter weir and removed from that tributary. All other hatchery steelhead were winter-run, but could not be definitively distinguished as Chambers Creek Stock early winter-run versus Cowlitz winter-run hatchery fish. Genetic samples were collected from these fish to potentially make this distinction in the future.
The mark-recapture estimates of steelhead above each tributary weir were based on live fish tagged and passed upstream (first sample) and kelts or carcasses (hereafter, “kelts”) captured in the downstream trap box built into the weir, just above the weir, or during spawner surveys (second sample). On Ostrander Creek, a total of 109 natural-origin steelhead were released upstream, 21 hatchery-origin steelhead were culled and buried above the high water mark as nutrient enhancement, and 12 natural-origin steelhead were retained for broodstock (Table 7). Of the kelts captured from above the weir, 59 were natural-origin recaptures, 2 were maiden natural- origin steelhead and 2 were maiden hatchery-origin steelhead (Table 8). On Delameter Creek, a total of 77 natural-origin steelhead were released upstream, 10 hatchery-origin steelhead were culled and buried above the high water mark as nutrient enhancement, and 9 natural-origin steelhead were retained for broodstock. Of the kelts captured above the Delameter weir, 30 were natural-origin recaptures, 4 were maiden natural-origin steelhead and there were no maiden hatchery-origin steelhead. On Olequa Creek, a total of 68 natural-origin steelhead were released upstream, 2 hatchery-origin steelhead were culled and buried above the high water mark as nutrient enhancement, and 7 natural-origin steelhead were retained for broodstock. Of the kelts captured above the Olequa weir, 11 were natural-origin steelhead recaptures, 26 were maiden
Page 44 of 119 natural-origin steelhead and 1 was a maiden hatchery-origin steelhead. On Lacamas Creek, 5 natural-origin steelhead were released upstream, and 4 hatchery-origin steelhead were culled and buried above the high water mark as nutrient enhancement. No natural-origin steelhead captured in Lacamas Creek were retained for broodstock to avoid mining the small population. Of the kelts captured above the Lacamas weir, 5 were recaptured natural-origin steelhead, 4 were a maiden natural-origin steelhead and there were no maiden hatchery-origin steelhead.
Five assumptions of the Lincoln-Petersen closed-population mark-recapture estimator were evaluated prior to completing the steelhead mark-recapture estimates (Schwarz and Taylor 1998). The first assumption is that the population is closed. No tagged fish were recaptured in a tributary where they were not originally tagged and only a few previously tagged fish (n = 9) were captured re-ascending the tributary where they had been previously tagged. As a result, data appear to meet the assumption of population closure. The second assumption is equal catchability in the first or second sample. A generalized linear model (binomial distribution) tested whether recapture rates of tagged steelhead were selective with respect to sex (male, female) or fork length. Data from all tributaries were pooled to increase sample size and statistical power of the analysis. Recapture rates were not selective with respect to length (p = 0.99) but female steelhead were recaptured at two times the rate of male steelhead (p < 0.001). Data from male and female steelhead were necessarily pooled in the analysis to maintain adequate sample size for the mark-recapture estimation. The third assumption is that tags are not lost. Loss of Floy tags was estimated based on fish in the second sample recovered with both tags
(mAB) or just one tag (mC = mA+ mB) was applied for each tributary (휋 = 푚푐⁄(푚푐 + 2푚퐴퐵) (Seber 1982). However, all recovered fish could be inspected for the opercle punch, which is a permanent mark (in relation to one spawning season), and this mark was used for the final analysis and the estimate was not adjusted for tag loss. The fourth assumption is that tagging status of each fish is correctly reported. This assumption was not directly tested but violations were minimized by training surveyors on the types and colors of tags they would expect to encounter. The fifth assumption is no handling mortality occurs as a result of the capture and tagging process. No direct mortalities were observed as a result of handling and delayed mortalities were minimized by careful training staff with respect to handling of live adult steelhead.
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Steelhead abundance above the Ostrander Creek weir was estimated to be 119 total steelhead (CV = 4.2%), including 114 natural-origin and 5 hatchery-origin fish (Table 9). Steelhead abundance above the Delameter Creek weir was estimated to be 91 total steelhead (CV = 8.9%), including 89 natural-origin and 1 hatchery-origin fish. Steelhead abundance above the Olequa Creek weir was estimated to be 273 total steelhead (CV = 31.9%), including 262 natural-origin and 11 hatchery-origin fish. No estimate was derived for Lacamas Creek due to low sample size. Weir efficiency for winter steelhead ranged between 27.1% and 92.1% in the three creeks where tributary estimates were derived.
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Table 7. Disposition of live steelhead captured and released from upstream traps at tributary weirs in the lower Cowlitz River, 2016 spawn year.
Disposition Released Released Weir Origin Sex Upstream Downstream Nutrients Broodstock Ostrander Unmarked (Natural) M 53 0 0 8 F 56 0 0 4 Ad-Clipped M 0 0 15 0 (Hatchery) F 0 0 6 0 Total 109 0 21 12 Delameter Unmarked (Natural) M 41 0 0 5 F 36 0 0 4 Ad-Clipped M 0 0 5 0 (Hatchery) F 0 0 2 0 Total 77 0 7 9 Olequa Unmarked (Natural) M 33 0 0 5 F 35 0 0 2 Ad-Clipped M 0 0 1 0 (Hatchery) F 0 0 1 0 Total 68 0 2 7 Lacamas Unmarked (Natural) M 0 0 0 0 F 5 0 0 0 Ad-Clipped M 0 0 1 0 (Hatchery) F 0 0 3 0 Total 5 0 4 0
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Table 8. Disposition of steelhead kelts or carcasses captured in downstream traps or above tributary weir traps in the lower Cowlitz River, 2016 spawn year. Capture of natural-origin kelts included tagged (recaptured) and untagged (maiden) captures. Capture of hatchery-origin kelts were untagged only as hatchery steelhead were not intentionally passed upstream. All kelts were released downstream of the weirs.
Natural-Origin Hatchery-Origin (Unmarked) (Adipose-Clip) Tagged Untagged Untagged Weir (Recapture) (Maiden) (Maiden) Ostrander 59 2 2 Delameter 30 4 0 Olequa 11 26 1
Lacamas 4 4 0
Table 9. Abundance and composition of steelhead spawners above tributary weirs in the lower Cowlitz River, 2016 spawn year. Data are abundance (N) and standard deviation (SD) of natural- origin (NOR), hatchery-origin (HOR), and total (Tot) spawners in each tributary. No estimate is available for Lacamas Creek due to low number of fish tagged and recaptured.
Weir 푁̂푁푂푅 SD( 푁̂퐻푂푅 SD( 푁̂푇푂푇 SD 푊퐸̂ ̂ ̂ ̂ Ostrander 114 푁푁푂푅) 4 5 푁퐻푂푅) 3 119 (푁푇푂푇)5 0.921
Delameter 89 7 1 2 91 8 0.855
Olequa 262 83 11 10 273 87 0.271
Lacamas ------
Coho spawners (corresponding to the 2016 coho spawn year) were captured between October 8, 2016 and March 14, 2017 in upstream weir traps and as carcasses above the weirs on Ostrander, Delameter, Olequa, and Lacamas creeks. The mark-recapture estimates of coho salmon above each tributary weir were based on live fish tagged and passed upstream (first sample) and carcasses captured during stream surveys or washed up on the weir panels (second sample). On Ostrander Creek, a total of 81 natural-origin adult coho salmon were released upstream and 15 hatchery-origin adult coho were culled and returned to the stream for nutrient enhancement (Table 10). Of the carcass recoveries, 16 were natural-origin recaptures, 9 were
Page 48 of 119 maiden natural-origin coho and 1 was a maiden hatchery-origin coho (Table 11). On Delameter Creek, a total of 48 natural-origin adult coho salmon were released upstream and 15 hatchery- origin adult coho were culled and provided as nutrient enhancement. Of the carcass recoveries, 13 were natural-origin recaptures, 16 were maiden natural-origin coho and 10 was a maiden hatchery-origin coho. On Olequa Creek, a total of 19 natural-origin adult coho were released upstream and 3 hatchery-origin adult coho were culled and provided as nutrient enhancement. Of the carcass recoveries, none were natural-origin coho recaptures, six were maiden natural-origin coho and none were maiden hatchery-origin coho. On Lacamas Creek, a total of 294 natural- origin adult coho were released upstream and four hatchery-origin adult coho were culled and provided as nutrient enhancement. Of the carcass recoveries, 11 were recaptured natural-origin coho, 25 were maiden natural-origin coho, and none were maiden hatchery-origin coho.
Five assumptions of the Lincoln-Petersen closed-population mark-recapture estimator were evaluated prior to completing the coho mark-recapture estimates (Schwarz and Taylor 1998). The first assumption, population closure, appears to be mostly met by the data as no coho were recaptured outside the tributary in which they were tagged and very few of the tagged coho (n = 3) were observed to re-ascend the weir after they were initially tagged. The second assumption is equal catchability in the first or second sample. A generalized linear model (binomial distribution) tested whether recapture rates of tagged coho were selective with respect to sex (male, female) or fork length. Data from all tributaries were pooled to increase sample size and statistical power of the analysis. Recapture rates were not selective with respect to length (p = 0.92) or sex (p = 0.62). The third assumption is that tags are not lost. Loss of Floy tags was estimated based on fish in the second sample recovered with both tags (mAB) or just one tag (mC
= mA+ mB) was applied for each tributary (휋 = 푚푐⁄(푚푐 + 2푚퐴퐵) (Seber 1982). However, all recovered fish could be inspected for an opercle punch, which is a permanent mark, and this mark was used for the final analysis and the estimate was not adjusted for tag loss. The fourth assumption is that tagging status of each fish is correctly reported. This assumption was not directly tested but violations were minimized by training surveyors on the types and colors of tags they would expect to encounter. The fifth assumption is no handling mortality occurs as a result of the capture and tagging process. No direct mortalities were observed as a result of handling and delayed mortalities were minimized by careful training of staff with respect to handling of live coho salmon.
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Coho abundance above the Ostrander Creek weir was estimated to be 143 adult coho (CV = 18.9%), including 135 natural-origin and 8 hatchery-origin spawners (Table 6). Coho abundance above the Delameter Creek weir was estimated to be 161 adult coho (CV = 27.9%), including 118 natural-origin and 43 hatchery-origin fish. Coho abundance above the Olequa Creek weir was not estimated using mark-recapture data because there were too few recoveries in the second sample. Coho abundance above the Lacamas Creek weir was estimated to be 1,108 adult coho (CV = 29.2%), including 1,092 natural-origin and 16 hatchery-origin fish. Weir efficiency for coho salmon ranged between 28.5% and 58.5% in the three tributaries where mark-recapture estimates were derived.
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Table 10. Disposition of live adult coho salmon captured and released from upstream traps at tributary weirs in the lower Cowlitz River, 2016 spawn year.
Released Released Weir Origin Sex Upstream Downstream Nutrient Ostrander Unmarked M 49 0 0 (Natural) F 32 0 0 Ad-Clipped M 0 0 9 (Hatchery) F 0 0 6 Total 81 0 15 Delameter Unmarked M 35 0 0 (Natural) F 13 0 0 Ad-Clipped M 0 0 10 (Hatchery) F 0 0 5 Total 48 0 15 Olequa Unmarked M 15 0 0 (Natural) F 4 0 0 Ad-Clipped M 0 0 2 (Hatchery) F 0 0 1 Total 19 0 3 Lacamas Unmarked M 174 0 0 (Natural) F 120 0 0 Ad-Clipped M 0 0 1 (Hatchery) F 0 0 3 Total 294 0 4
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Table 11. Disposition of adult coho salmon carcasses recovered in stream surveys above tributary weirs or washed up on weir panels in the lower Cowlitz River, 2016 spawn year. Recoveries of natural-origin (NOR) coho included tagged (recaptured) and untagged (maiden) captures. Captures of hatchery-origin (HOR) coho were untagged fish only as hatchery coho were not intentionally passed upstream.
NOR NOR HOR Tagged Untagged Untagged Weir (Recapture) (Maiden) (Maiden) Ostrander 16 9 1 Delameter 13 16 10 Olequa 0 6 0 Lacamas 11 25 0
Table 12. Abundance and composition of coho spawners above tributary weirs in the lower Cowlitz River, 2016 spawn year. Data are abundance (N) and standard deviation (SD) of natural-origin (NOR), hatchery-origin (HOR), and total (Tot) spawners as well as weir efficiency (WE) above each tributary weir. No estimate is available for Olequa Creek due to low number of fish tagged and recaptured.
Weir 푁̂푁푂푅 SD(푁̂푁푂푅) 푁̂퐻푂푅 SD(푁̂퐻푂푅) 푁̂푇푂푇 SD(푁̂푇푂푇) 푊퐸̂ SD(푊퐸̂ ) Ostrander 135 25 8 7 143 27 0.585 0.100 Delameter 118 31 43 20 161 45 0.318 0.080 Olequa ------Lacamas 1,092 320 16 24 1,108 324 0.285 0.074
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Monitoring Responsibility 2: Steelhead Spawner Abundance, Composition (pHOS), and Distribution in Lower Cowlitz River Tributaries
Abundance of winter steelhead is estimated to be 972 steelhead spawners (CV = 10.6%) in the lower Cowlitz River tributaries for spawn year 2016 (Table 13). This estimate includes the 482 (CV = 17.4%) steelhead estimated using mark-recapture methods above tributary weirs on Ostrander, Delameter, and Olequa creeks. The estimate also includes 241 (CV = 20.7%) steelhead estimated outside the tributaries with weirs, including Lacamas and Salmon creeks but excluding Blue Creek, and an additional 249 (CV = 13.2%) steelhead in Blue Creek. The proportion of females to total steelhead used to derive the abundance estimate was 0.47 (±0.05, 95% C.I.). This estimate was obtained from live adult steelhead arriving to the four tributary weirs and is therefore considered to be representative of the population. The redd per female ratio used to derive the abundance estimate was 0.52 (±0.12, 95% C.I.) based on a mark- recapture estimate of 209 steelhead spawners above the Ostrander and Delameter weirs, a proportion female of 0.47, and a census count of 51 new redds above the two weirs.
Composition of winter steelhead spawners, represented by the overall proportion of hatchery spawners (pHOS, unadjusted for reproductive success), is estimated to be 26.7%. This estimate includes 465 natural-origin and 17 hatchery-origin steelhead estimated above the three weirs (pHOS = 3.5%), 217 natural-origin and 24 hatchery-origin steelhead estimated outside weir areas excluding Blue Creek (pHOS = 10.0%), and 30 natural-origin and 219 hatchery-origin steelhead estimated in Blue Creek (pHOS = 87.9%).
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Distribution of winter steelhead spawners was described as a mean redd density calculated from 28 GRTS reaches (excluding Blue Creek reaches). Redd density was 0.11 observed redds per mile (Figure 11). Redd densities in the GRTS survey area were much lower than those observed above the tributary weirs and in index reaches outside the tributaries with weirs. For example, there were 36 redds observed in 3.6 miles above the Ostrander Creek weir, 15 redds were observed in 9.4 miles above the Delameter Creek weir, and 52 redds were observed in 39 miles above the Olequa Creek weir. Redd densities in index areas outside the tributary weirs included 25 redds observed in 5.9 miles of Arkansas Creek and 60 redds observed in 2 miles of Blue Creek. Although the two Blue Creek reaches were originally selected for survey as randomly selected (GRTS) reaches, data from these reaches were not used in the GRTS based approach of estimating redds in non-surveyed reaches because of the high densities of primarily hatchery steelhead spawners.
Figure 11. Steelhead redd densities observed in 1-mile GRTS reaches in Cowlitz River tributaries, spawn year 2016. Gray bars are observations and black line is the fitted negative binomial function used to estimate redds in non-surveyed areas.
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Table 13. Natural- and hatchery-origin and total steelhead spawner abundance (N) and variance and proportion of hatchery-origin spawners (pHOS) in lower Cowlitz River tributaries, spawn year 2016. Estimates are based on mark-recapture above tributary weirs and redd expansion.
Natural-origin Hatchery-origin Total Abundance Tributary and estimate N Variance N Variance N Variance pHOS
Ostrander (Mark- Recapture) 114 16 5 9 119 25 0.042 Delameter (Mark- Recapture) 89 49 1 4 90 53 0.111 Olequa (Mark- Recapture) 262 6,889 11 100 273 6,989 0.040 Outside Weirs (Redd Based) 217 2,467 24 42 241 2,509 0.100 Blue Creek
(Redd Based) 30 265 219 818 249 1,083 0.880 Total 712 9,686 260 973 972 10,659
Monitoring Responsibility 3: Chinook Spawner Abundance, Composition (pHOS, Age Structure), and Distribution in the Lower Cowlitz River
Abundance of spring Chinook salmon is estimated to be 486 spawners (171 redds * 2.84) in the lower Cowlitz River below Barrier Dam for spawn year 2016. Peak redd counts for spring Chinook occurred on the September 21, 2016 aerial flight. Composition of spring Chinook spawners, represented by the proportion of hatchery spawners, is estimated to be 88%. This estimate includes 107 natural-origin and 379 hatchery-origin spring Chinook salmon. Distribution of spring Chinook spawners occurred throughout the survey area between the Castle Rock and Barrier Dam with 66% of the redds observed in the two indexes closest to Barrier Dam (Table 14).
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Abundance of fall Chinook salmon is estimated to be 4,021 spawners (1,416*2.84, rounded) in the lower Cowlitz River below Barrier Dam for spawn year 2016. The peak redd counts for fall Chinook should have occurred on November 7, 2016 (Table 14) based on historical observations that peak redd counts for fall Chinook salmon occur during the first week of November. However, due to river conditions (i.e., visibility), the last aerial redd survey occurred on October 27, 2016 which was one week prior to the expected peak redd count. A total of 1,113 redds observed on this date was expanded to 1,416 redds during peak spawning week based on a calculated ratio of 79% of the peak redd counts being visible the last week of October.
Composition of fall Chinook spawners, represented by the proportion of hatchery spawners, is estimated to be 26%. This estimate includes 2,976 natural-origin and 1,045 hatchery-origin fall Chinook salmon. Natural-origin spawners included fall Chinook from the Cowlitz River. There were no recoveries of CWTs from Lewis River fall Chinook salmon (natural-origin) that are observed in some years. Based on CWT recoveries, approximately half of the hatchery-origin spawners were from the Cowlitz Salmon Hatchery and half of the hatchery-origin spawners originated from Kalama Falls Hatchery and Deep River net pens (Table 15). Composition of fall Chinook spawners, described by total age class, included 3.4% age-2, 10.2% age-3, 70.3% age-4, 15.9% age-5, and 0.2% age-6. Five hundred and six genetic samples were collected from fresh (clear eyes and pink gills) Chinook carcasses.
Distribution of spring Chinook spawners occurred throughout the survey area between the Castle Rock and Barrier Dam. Spawner distribution was more downstream than observed for spring Chinook salmon with 73% of the redds observed between Toledo Bridge and Baker Rock (Table 14). Natural-origin fall Chinook salmon were also observed at tributary weirs in 2016. A total of two fall Chinook were encountered at the Ostrander weir, nine at the Delameter weir, four at the Olequa weir and five at the Lacamas weir. One hatchery-origin fall Chinook was captured at Delameter weir and was culled and returned to the stream as nutrient enhancement.
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Table 14. Spatial and temporal distribution of hatchery-origin and natural-origin Chinook salmon spawners in the lower Cowlitz River, 2016.
Spring Chinook Fall Chinook Redds Carcass Redds Carcass Reach 9/9 9/21 NOR HOR 10/5 10/27 11/7 NOR HOR Kelso to Castle Rock R ------
Castle R Br to Toutle R Br 0 2 0 0 3 8 ------
Toutle River to I-5 Bridge 4 10 0 0 78 64 --- 29 8
I-5 Bridge to Toledo Bridge 0 16 0 1 65 44 --- 222 64
Toledo Bridge to Skook Creek 1 16 0 0 165 269 --- 183 55
Skook Cr to Blue Cr Boat Rp 9 42 0 1 266 358 --- 184 82
Blue Cr Boat Rp to Baker Rock 2 35 0 14 110 185 --- 161 50
Timber Trails side channel 0 4 0 4 16 75 --- 37 19
Baker Rock to Mill Creek 15 19 7 34 66 86 --- 172 77
Mill Creek to Barrier Dam 17 27 0 0 48 24 --- 0 0
Total 48 171 7 54 817 1113 1416 988 355
pHOS 0.88 Est. 0.26
Table 15. Age and stock composition of fall Chinook salmon spawners in the lower Cowlitz River, 2016. Table provides spawner escapement by age class. Origin 2-year 3-year 4-year 5-year 6-year Total
Cowlitz Natural 101 304 2,093 473 8 2,979
Cowlitz Hatchery 35 106 244 165 3 553
Kalama Hatchery 0 0 382 0 0 382
Deep R. Hatchery 0 0 107 0 0 107
Total 136 410 2,826 638 11 4,021
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Monitoring Responsibility 4: Coho Spawner Abundance, Composition (pHOS), and Distribution in Lower Cowlitz River Tributaries
Abundance of coho salmon is estimated to be 3,997 coho spawners (CV = 30.1%) in the lower Cowlitz River tributaries for spawn year 2016 (Table 16). This estimate includes the 1,412 (CV = 17.8%) coho estimated using mark-recapture methods above tributary weirs on Ostrander, Delameter, and Lacamas creeks. The estimate also includes 2,465 (CV = 47.1%) coho estimated outside the tributaries with weirs, including Olequa and Salmon creeks but excluding Brights Creek, and an additional 120 (CV = 17.7%) coho in Brights Creek. The proportion of females to total adult coho used to derive the abundance estimate was 0.38 (±0.04, 95% C.I.). This estimate was obtained from live adult coho arriving to the four tributary weirs and is therefore considered to be representative of the population. The redd per female ratio used to derive the abundance estimate was 0.82 (±0.20, 95% C.I.) based on a mark-recapture estimate of 304 adult coho spawners above the Ostrander and Delameter weirs, a proportion of females of 0.38, and a census count of 100 redds observed above the two tributary weirs.
Composition of coho salmon spawners, represented by the overall proportion of hatchery spawners (pHOS, unadjusted for reproductive success), is estimated to be 8.6%. This estimate includes 1,345 natural-origin and 67 hatchery-origin coho estimated above the three weirs (pHOS = 4.7%), 2,263 natural-origin and 202 hatchery-origin coho estimated outside weir areas excluding Brights Creek (pHOS = 8.2%), and 46 natural-origin and 74 hatchery-origin coho estimated in Brights Creek (pHOS = 61.7%).
Distribution of coho salmon spwaners was described as a mean redd density calculated from 37 GRTS reaches. Redd density was 2.24 observed redds per mile (Figure 12). Above tributary weirs, we observed 51 redds in 4.8 miles above the Ostrander Creek weir and 49 redds in 9.4 miles above the Delameter Creek weir. Redd densities in index areas outside the tributary weirs included 54 redds were observed in 8.9 miles of Arkansas Creek and 37 redds observed in 1 mile of Brights Creek.
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Figure 12. Coho salmon redd densities observed in 1-mile GRTS reaches in Cowlitz River tributaries, spawn year 2016. Gray bars are observations and black line is the fitted negative binomial function used to estimate redds in non-surveyed areas.
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Table 16. Coho spawner abundance estimated using mark-recapture above tributary weirs and redd expansion in lower Cowlitz River tributaries, spawn year 2016. Estimate includes natural-origin abundance and variance, hatchery-origin abundance and variance, and total abundance and variance.
Natural Total Total Hatchery Estimate Origin Variance Origin Variance Abundance Variance
Ostrander (Mark-Recapture) 135 625 8 49 143 674 Delameter (Mark-Recapture) 118 961 43 400 161 1,361 Lacamas (Mark-Recapture) 1,092 102,400 16 576 1,108 102,976 Outside Weirs (Redds) 2,263 1,334,173 202 11,653 2,465 1,345,826 Brights Creek (Redds) 46 194 74 257 120 451 Total 3,654 1,438,353 343 12,935 3,997 1,451,288
Monitoring Responsibility 5: Effort, Catch Rates, and NOR:HOR Ratios in Cowlitz River Fisheries in 2016
In 2016, a total of 5,342 shore anglers (15,581 hours of fishing effort) and 2,278 boat anglers (14,853 hours of fishing effort) were interviewed. The spatial distribution of effort and catch observed in the creel surveys differed between shore and boat anglers. For shore anglers, the overall number of anglers and the hours of effort were greatest at the Barrier Dam and Blue Creek locations (Table 17). For boat anglers, the overall number of anglers and the hours of effort were greatest at the Blue Creek, Castle Rock and Gearhart locations (Table 18).
Based on interviews with shore anglers (Table 19), 451 HOR spring Chinook salmon were retained and 4 NOR spring Chinook salmon were released (NOR:HOR = 0.008), 84 HOR fall Chinook were retained and 80 NOR fall Chinook were released (NOR:HOR = 0.95), 371 HOR coho salmon were retained and 78 NOR coho salmon were released (NOR:HOR = 0.21), 133
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HOR winter steelhead were retained and 4 NOR winter steelhead were released (NOR:HOR = 0.03), and 148 HOR summer steelhead were released and 0 NOR summer steelhead were retained (NOR:HOR ratio = 0).
Based on interviews with boat anglers (Table 20), 111 HOR spring Chinook salmon were retained and 5 NOR spring Chinook salmon were released (NOR:HOR = 0.05), 47 HOR fall Chinook were retained and 103 NOR fall Chinook were released (NOR:HOR = 2.2), 114 HOR coho salmon were retained and 67 NOR coho salmon were released (NOR:HOR = 0.59), 518 HOR winter steelhead were retained and 10 NOR winter steelhead were released (NOR:HOR = 0.02), and 131 HOR summer steelhead were released and no NOR summer steelhead were retained or released (NOR:HOR ratio = 0).
Together, the encounter rates of NOR (to HOR) fall Chinook salmon (shore = 0.95, boat = 2.2) are the highest of all species with two to three times the number of NOR fall Chinook than HOR fall Chinook being caught. Encounter rates of NOR coho salmon (shore = 0.21, boat = 0.59) are intermediate to the other species. Encounter rates of NOR spring Chinook salmon (shore = 0.008, boat = 0.05), winter steelhead (shore = 0.03, boat = 0.02), and summer steelhead (shore = 0, boat = 0) were the lowest in value.
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Table 17. Summary of effort (number of anglers, number of hours fished) by shore anglers as observed in the Cowlitz River creel survey, 2016.
Effort Month (Number)
Barrier Dam Blue Creek Mission Bar Toledo I5 Olequa Toutle R. Chapman Rd Castlerock Camelot Gearheart Total Anglers 2 5 0 0 0 5 0 6 0 0 18 Jan Hours 3 21.1 0 0 0 9.5 0 14.5 0 0 48.1 Anglers 35 28 4 0 0 64 0 10 0 7 148 Feb Hours 63.3 121.2 1 0 0 218.2 0 31.5 0 19.7 454.8 Anglers 221 95 7 0 4 63 0 22 0 11 423 March Hours 504.3 545.2 23.4 0 14.9 243.2 0 102.6 0 25.3 1,462 Anglers 556 138 19 0 5 48 0 10 0 112 888 April Hours 1,534.6 632.1 52.8 0 8.7 145.3 0 30.7 0 362.1 2,766.3 Anglers 234 46 1 0 0 9 0 0 0 32 322 May Hours 633.1 168.2 0.7 0 0 23 0 0 0 77.6 902.6 Anglers 209 31 2 0 2 10 0 0 0 15 269 June Hours 649.7 180.7 2.8 0 6.1 25.2 0 0 0 28.9 893.4 Anglers 97 74 2 0 2 10 0 1 1 26 213 July Hours 159.6 372.6 1.5 0 3.8 25.1 0 0.7 0.8 52.7 616.8 Anglers 164 33 0 0 0 6 5 0 0 51 6 260 Aug Hours 321.3 163.9 0 0 0 14.3 8 0 0 132.5 16 648 Anglers 413 88 7 0 2 14 102 1 0 51 0 678 Sept Hours 875.9 356.3 12.9 0 5 39.6 410.3 5.8 0 216.8 0 1,922 Anglers 752 255 11 0 7 92 35 1 13 37 6 1,218 Oct Hours 2,025.3 892.1 29.2 0 18.8 329.6 106.5 5.4 50.9 172.8 16.2 3,677.1 Anglers 484 57 13 0 4 115 0 9 0 5 0 687 Nov Hours 1,065.7 143.3 16.1 0 17.8 415.7 0 32.6 0 11.2 0 1,702.3 Anglers 101 51 5 0 0 49 0 0 0 11 0 217 Dec Hours 150 130.5 8.5 0 0 153.3 0 0 0 45.5 0 487.8 Anglers 3,268 897 71 0 17 485 137 60 14 358 12 5,342 Total Hours 7,984.8 3,726 149 0 70 2,126 517 234 52 1,503 32 15,581
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Table 18. Summary of effort (number of anglers, number of hours fished) by boat anglers as observed in the Cowlitz River creel survey, 2016.
Month Effort
Barrier Dam Blue Creek Mission Bar Toledo I5 Olequa Castlerock Camelot Gearhart Total Anglers 0 4 0 0 0 0 0 0 4 Jan Hours 0.0 26 0 0.0 0 0.0 0.0 0 26 Anglers 0 36 0 0 0 0 0 0 36 Feb Hours 0.0 227.4 0 0.0 0 0.0 0.0 0 227.4 Anglers 7 474 0 0 0 0 24 0 481 March Hours 33.5 3,622.2 0 0.0 0.0 0.0 142.8 0 3,798 Anglers 6 321 0 0 3 0 28 0 358 April Hours 28.1 2,239.9 0 0.0 6.6 0 133.8 0 2,408.4 Anglers 0 62 0 0 0 0 5 0 67 May Hours 0.0 501.3 0.0 0.0 0.0 0.0 18.7 0.0 520 Anglers 3 112 1 0 4 2 2 0 124 June Hours 8.3 846.2 3.5 0.0 13.6 8 5.8 0.0 885.4 Anglers 0 147 60 0 2 0 2 4 215 July Hours 0.0 1072.3 341.9 0.0 8.6 0.0 11 7.3 1441.1 Anglers 0 141 68 0 3 0 13 0 11 236 Aug Hours 0 1042.6 451.7 0.0 9.7 0.0 42.3 0.0 40 1586.7 Anglers 32 74 0 0 5 11 98 0 168 388 Sept Hours 105.45 590.25 0 0.0 18.5 39.75 588 0.0 962.5 2,304 Anglers 54 80 3 2 13 5 19 0 80 256 Oct Hours 186.6 501.65 19.35 7.4 57.3 36.75 94.9 0 366.8 1270.75 Anglers 13 29 2 0 14 0 6 0 64 Nov Hours 31.65 168.05 10.4 0.0 61.2 0.0 28.2 0.0 299.5 Anglers 4 6 0 0 7 0 0 0 17 Dec Hours 9.5 50.75 0.0 0.0 24.25 0.0 0.0 0.0 84.5 Total Anglers 119 1,494 134 2 51 16 197 4 259 2,278 Hours 403.1 10,888.6 961 7.4 199.8 76.5 1,065.5 7.3 1,369.7 14,853
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Table 19. Summary of catch of hatchery (HOR) and natural (NOR) salmon and steelhead by shore anglers as observed in the Cowlitz River creel survey, 2016.
Species Disposition Lexington
Barrier Dam Blue Creek Mission Bar Toledo I5 Olequa Toutle R. Chapman Rd rockCastle Camelot Total HOR Kept 434 1 0 0 0 4 0 3 0 9 0 451 HOR Rel 39 0 0 0 0 0 0 0 0 0 0 39 Spring Chinook NOR Kept 0 0 0 0 0 0 0 0 0 0 0 0 NOR Rel 4 0 0 0 0 0 0 0 0 0 0 4 Total 477 1 0 0 0 4 0 3 0 9 0 494 HOR Kept 79 2 0 0 0 0 2 0 0 1 0 84 HOR Rel 72 1 0 0 0 0 1 0 0 0 0 74 Fall Chinook NOR Kept 0 0 0 0 0 0 0 0 0 0 0 0 NOR Rel 70 4 0 0 0 1 4 0 0 1 0 80 Total 221 7 0 0 0 1 7 0 0 2 0 238 HOR Kept 328 6 0 0 0 18 8 2 0 7 2 371 HOR Rel 92 0 0 0 0 1 5 0 0 0 0 98 Coho NOR Kept 0 0 0 0 0 0 0 0 0 0 0 0 NOR Rel 69 1 0 0 0 3 5 0 0 0 0 78 Total 489 7 0 0 0 22 18 2 0 7 2 547 HOR Kept 8 107 0 0 0 8 0 9 0 1 0 133 HOR Rel 1 4 0 0 0 0 0 0 0 1 0 6 Winter Steelhead NOR Kept 0 0 0 0 0 0 0 0 0 0 0 0 NOR Rel 3 0 0 0 0 0 0 1 0 0 0 4 Total 12 111 0 0 0 8 0 10 0 2 0 143 HOR Kept 15 122 1 0 0 4 0 0 0 6 0 148 Summer HOR Rel 0 6 0 0 0 0 0 0 0 0 0 6 Steelhead NOR Kept 0 0 0 0 0 0 0 0 0 0 0 0 NOR Rel 0 0 0 0 0 0 0 0 0 0 0 0 Total 15 128 1 0 0 4 0 0 8 6 0 154
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Table 20. Summary of catch of hatchery (HOR) and natural (NOR) salmon and steelhead by boat anglers as observed in the Cowlitz River creel survey, 2016.
Species Disposition Gearhart
Barrier Dam Blue Creek Mission Bar Toledo I5 Olequa Toutle R. Chapman Rd Castlerock Camelot Total
HOR Kept 9 87 0 0 2 0 NA NA 13 0 0 111 Spring HOR Rel 1 1 0 0 0 0 NA NA 0 0 0 2 Chinook NOR Kept 0 0 0 0 0 0 NA NA 0 0 0 0 NOR Rel 1 0 1 0 0 0 NA NA 3 0 0 5 Total 11 88 1 0 2 0 NA NA 16 0 0 118 HOR Kept 4 3 1 0 0 1 NA NA 18 0 20 47 HOR Rel 2 5 2 0 1 0 NA NA 5 0 0 15 Fall Chinook NOR Kept 0 0 0 0 0 0 NA NA 0 0 0 0 NOR Rel 9 11 0 0 0 0 NA NA 31 0 52 103 Total 15 19 3 0 1 1 NA NA 54 0 72 165
HOR Kept 44 12 0 0 2 0 NA NA 16 0 40 114 HOR Rel 0 10 0 0 0 0 NA NA 0 0 0 10 Coho NOR Kept 0 0 0 0 0 0 NA NA 0 0 0 0 NOR Rel 42 4 0 0 0 1 NA NA 4 0 16 67 Total 86 26 0 0 2 1 NA NA 20 0 56 191
HOR Kept 0 517 0 0 0 0 0 NA 1 0 0 518 Winter HOR Rel 0 8 0 0 0 0 0 NA 0 0 0 8 Steelhead NOR Kept 0 0 0 0 0 0 0 NA 0 0 0 0 NOR Rel 0 10 0 0 0 0 0 NA 0 0 0 10 Total 0 535 0 0 0 0 0 NA 1 0 0 536
HOR Kept 0 41 76 0 4 0 0 NA 2 0 8 131 Summer HOR Rel 0 3 0 0 3 0 0 NA 0 0 0 6 Steelhead NOR Kept 0 0 0 0 0 0 0 NA 0 0 0 0 NOR Rel 0 0 0 0 0 0 0 NA 0 0 0 0 Total 0 44 76 0 7 0 0 NA 2 0 8 137
Monitoring Responsibility 6: Estimates of Catch for Natural-Origin Fish in the Cowlitz River Fisheries in 2015
In 2015, 235 (28-825) NOR spring Chinook and 6,216 (3,015-12,720) NOR fall Chinook salmon were estimated to have been caught and released in the Cowlitz River fishery below Mayfield Dam. This estimate was derived from a harvested catch of 7,789 (6,734-8,844, 95% C.I.) HOR spring Chinook salmon and 3,751 (3,129-4,373) HOR fall Chinook salmon (Table
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21). Of these, 182 (2.3% sample rate) HOR spring Chinook and 452 (5.5% sample rate) HOR fall Chinook salmon were sampled in the creel. In 2015, 975 (425-1,844) NOR coho salmon were estimated to have been caught and released in the Cowlitz River fishery below Mayfield Dam. This estimate was derived from a harvested catch of 1,297 (1,029-1,565) HOR coho salmon (Table 22). Of these, 77 (5.9% sample rate) HOR coho salmon were sampled in the creel. In 2015, 805 (225-2,036) NOR winter steelhead were estimated to have been caught and released in the Cowlitz River fishery below Mayfield Dam. This estimate was derived from a harvested catch of 14,512 (13,189-15,834) HOR winter steelhead (Table 23). Catch of HOR winter steelhead occurred in two pulses (December/January and March/April) representing the early and late timed hatchery programs. The last smolt releases from the early-timed program occurred in 2011 but returns from this release were still evident in the 2014-2015 winter fishery. Of the harvested HOR winter steelhead, 329 (2.2% sample rate) HOR steelhead were sampled in the creel.
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Table 21. Catch of hatchery-origin (HOR) and natural-origin (NOR) Chinook salmon in the Cowlitz River fishery, 2015. Catch between March and July are assumed to be spring Chinook salmon and catch between August and December are assumed to be fall Chinook salmon.
Creel Creel NOR NOR NOR Month CRC HOR CRC HOR HOR NOR Proportion Catch Catch Catch Harvest Est. Variance Kept Rel. Sampled Est. (Low 95) (High 95) Mar-15 0 0 0 0 --- 0 0 0
Apr-15 3,746 179,183 139 1 0.037 41 3 133
May-15 2,390 80,718 25 0 0.010 47 0 257
Jun-15 1,042 20,647 a1 0 0.001 20 0 98
Jul-15 611 9,375 17 3 0.028 127 25 337
Aug-15 557 8,236 2 2 0.004 896 70 3,987
Sep-15 2,349 78,388 122 116 0.052 2,257 1,545 3,121
Oct-15 791 13,604 73 177 0.092 1,928 1,233 2,788
Nov-15 54 516 8 157 0.148 1,135 167 2,824
Dec-15 0 0 0 0 --- 0 0 0
7,789 289,923 182 4 0.023 235 28 825 Total (Spring) 3,751 100,744 205 452 0.055 6,216 3,015 12,720 Total (Fall) aDue to the low sample size of creel data for the month of June, sampling data from May and June was used to estimate NOR catch in the month of June.
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Table 22. Catch of hatchery-origin (HOR) and natural-origin (NOR) coho salmon in the Cowlitz River fishery, 2015.
Creel Creel NOR NOR NOR CRC HOR CRC HOR HOR NOR Proportion Catch Catch Catch Month Harvest Est. Variance Kept Rel. Sampled Est. (Low 95) (High 95) Jun-15 0 0 0 0 --- 0 0 0
Jul-15 9 81 0 0 --- 0 0 0
Aug-15 36 335 0 0 --- 0 0 0
Sep-15 405 5,355 15 20 0.037 577 249 1,105
Oct-15 704 11,493 37 14 0.053 278 130 500
Nov-15 143 1,497 25 20 0.175 120 46 239
Dec-15 0 0 0 0 --- 0 0 0
Total 1,297 18,761 77 54 0.059 975 425 1,844
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Table 23. Catch of hatchery-origin (HOR) and natural-origin (NOR) winter steelhead in the Cowlitz River fishery, 2015.
CRC Creel Creel NOR NOR CRC HOR HOR HOR NOR Proportion NOR Catch Catch Month Harvest Est. Variance Kept Rel. Sampled Catch Est. (Low 95) (High 95) Nov-14 315 1,909 4 0 0.013 45 0 261
Dec-14 1,082 12,750 51 0 0.047 11 0 53
Jan-15 848 8,512 30 2 0.035 72 12 195
Feb-15 1,631 26,320 23 1 0.014 107 6 353
Mar-15 6,086 312,129 137 8 0.023 374 161 709
Apr-15 4,550 93,736 81 3 0.018 196 46 465
Total 14,512 455,356 326 14 0.022 805 225 2,036
Monitoring Responsibility 7: Counts, Biological Data and Disposition of Returns to Barrier Dam, Including Hatchery Broodstock Sampling
A total of 17,556 spring Chinook salmon returned to the Cowlitz Salmon Hatchery separator at Barrier Dam. Based on the 59-cm FL partition between jacks and adults, natural-origin returns to the hatchery included 200 adults and 30 jacks (Table 24). Hatchery-origin returns to the hatchery included 410 mini-jacks (precocious fish that appear to be one year younger than jacks), 2,186 jacks, and 14,730 adults. The dominant age classes for spring Chinook were 42 (adult, exit freshwater after one year and return after 2.5 years at sea) and 52 (adult, exit freshwater after one year and return after 3.5 years at sea (Table 28). Additional age classes observed were 41 (adult, exit freshwater in the first year and return after 3.5 years at sea) and 32 (jack, exit freshwater after one year and return after 1.5 years at sea). Average length of male spring Chinook used in the segregated broodstock program was 61.1 (±1 S.D.= ± 5.8) cm FL for jack males (age 32) and
75.7 (± 6.2) cm FL and 83.9 (± 5.6) cm FL for adults (ages 42 and 52 respectively). Average length of female spring Chinook used in the segregated broodstock program was 73.8 (± 4.5) cm
FL and 79.5 (± 5.1) cm FL for ages 42 and 52 respectively.
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A total of 6,264 fall Chinook salmon returned to the Cowlitz Salmon Hatchery separator at Barrier Dam. Based on the 49-cm FL partition between jacks and adults, natural-origin returns included 159 jacks and 3,068 adults (Table 25). Hatchery-origin returns included 167 jacks and 2,870 adult fall Chinook salmon. Although summary statistics are provided for the unmarked fish included in the integrated broodstock, sample sizes are too small to be reliable. The 2016 summary statistics for the adipose-clipped or adipose-clipped/coded-wire tagged fall Chinook used in the segregated broodstock are an appropriate surrogate for the integrated broodstock because the integrated broodstock was primarily derived from these fish due to low capture rates of unmarked fall Chinook from the lower river. The dominant age classes for hatchery fall
Chinook were 31 (adult, exit freshwater in the first year and return after 2.5 years at sea) and 41 (adult, exit freshwater in the first year and return after 3.5 years at sea). Additional age classes observed were 21 (jack, exit freshwater in the first year and return after 18 months at sea), 52
(adult, exit freshwater after one year and return after 3.5 years), 51 (adult, exit freshwater in the first year and return after 4.5 years at sea), and 61 (adult, exit freshwater in the first year and return after 5.5 years at sea). Average length of male fall Chinook (adipose clip or adipose clip and coded-wire tag) was 52.7 (±6.1) cm FL for jack males (age 21) compared to 69.9 (±6.0) cm
FL and 80.9 cm FL (±7.7) for adult males (age 31 and 41 respectively (Table 29). Average length of female fall Chinook (adipose clip or adipose clip and coded-wire tag) was 70.3 (±4.3) cm FL,
79.3 (±4.3) cm FL, and 82.7 (±4.8) cm FL for ages 31, 41, and 51 respectively. A total of 27,893 coho salmon returned to the Cowlitz Salmon Hatchery. Based on the 42-cm FL partition between jacks and adults, natural-origin returns included 466 jacks and 4,443 adult coho salmon (Table 26). Hatchery-origin returns included 5,162 jacks and 17,822 adult coho salmon. Historically the dominant age classes for coho are 22 (jack, exit freshwater after one year and return after 6 months at sea) and 32 (adult, exit freshwater after one year and return after 18 months at sea). Average length of CWT tagged male coho used in integrated hatchery program was 34.5 (±0.7) cm FL for jack males (age = 22) compared to 66.8 (±3.2) cm FL for adult males (age = 32). The average length for adult females (age = 32) was 71.9 (±5.9) cm FL.
A total of 5,480 winter-run steelhead returned to the Cowlitz Salmon Hatchery. Based on the 42-cm FL partition between jacks and adults, natural-origin returns included no jacks and 631 adult steelhead (Table 27). Hatchery-origin returns included no jacks and 4,849 adult winter steelhead. The dominant age classes for natural-origin steelhead incorporated into the broodstock were age 2.1+ (adult, exit freshwater after two years and return after one winter and Page 70 of 119 two summers at sea), age 2.2+ (adult, exit freshwater after two years and return after two winter and three summers at sea) and age 3.1+ (adult, exit freshwater after three years and return after one winter and two summers at sea) (Table 31). Mean length of unmarked male winter steelhead used in the integrated hatchery programs was 68.8 (±5.5) cm FL ‘two salt’ males (age = 2.1+) compared to 78.3 (±2.1) cm FL for ‘three salt’ males (age = 2.2+). The mean length for ‘two salt’ adult females (age = 2.1+) was 67.0 (±3.9) cm FL and 79.0 (±3.8) for ‘three salt’ females (age = 2.2+).
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Table 24. Disposition of natural (NOR) and hatchery-origin (HOR) spring Chinook salmon returns to Cowlitz Salmon Hatchery in 2016. Mark types include unmarked, adipose-clipped (AD only), adipose-clipped and coded-wire tag (AD + CWT), left pelvic clip (LV-clipped), right pelvic clip (RV-clipped).
Adult (≥ 59 cm FL) Jack Mini-jacks
Female Male Unknown Total Adult (<59 cm FL) Broodstock – Segregated HOR AD only 880 823 0 1,703 60 0 HOR AD + CWT 0 9 0 9 0 0 Sub-total 880 832 0 1,712 60 0 Release to Upper Cowlitz NOR Unmarked 98 102 0 200 30 0 HOR AD only 5,623 6,123 0 11,746 1,849 0 Sub-total 5,721 6,225 0 11,946 1,879 0 Release to Riffe Lake* HOR AD only 0 0 0 0 0 357 Sub-total 0 0 0 0 0 357 Foodbank/Surplus HOR AD only 0 10 0 10 0 0 HOR AD + CWT 628 630 0 1,258 277 53 Sub-total 628 640 0 1,268 277 53 Mortalities HOR AD only 4 0 0 4 0 0 NOR Grand Total 98 102 0 200 30 0 HOR Grand Total 7,135 7,595 0 14,730 2,186 410
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Table 25. Disposition of natural (NOR) and hatchery (HOR) fall Chinook salmon returns to Cowlitz Salmon Hatchery in 2016. Mark types include unmarked, adipose-clipped (AD only), adipose-clipped and coded-wire tag (AD + CWT), unmarked and coded-wire tag (UM + CWT).
Adult (≥ 49 cm FL) Jack
Female Male Total Adult (< 49 cm FL) Broodstock HOR AD only 995 917 1,912 52 Sub-total 995 917 1,912 52 Released to Tilton NOR Unmarked 1,616 1,440 3,056 157 HOR AD only 522 367 889 101 NOR UM + CWT 7 5 12 2 Sub-total 2,145 1,812 3,957 260 Release to Upper Cowlitz HOR AD only 7 4 11 2 HOR AD + CWT 0 0 0 0 Sub-total 7 4 11 2 Foodbank/Surplus HOR AD + CWT 20 35 55 12 Sub-total 20 35 55 12 Mortalities HOR AD only 3 0 3 0 Sub-total 3 0 3 0 NOR Grand Total 1,623 1,445 3,068 159 HOR Grand Total 1,547 1,323 2,870 167
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Table 26. Disposition of natural (NOR) and hatchery-origin (HOR) coho salmon returns to Cowlitz Salmon Hatchery in 2016. Mark types include unmarked, unmarked and blank-wire tagged (Unmarked + BWT), adipose-clipped (AD only), adipose-clipped and coded-wire tag (AD + CWT).
Adult (≥ 42 cm FL) Jack (<42) Female Male Total Total Broodstock NOR Unmarked + CWT 461 410 871 73 HOR AD+ CWT 64 0 64 6 HOR AD only 626 514 1,140 112 Sub-total 1,585 1,535 3,120 270 Released to Tilton NOR Unmarked 1,172 1,494 2,666 329 HOR AD only 3,136 2,844 5,980 1,995 Sub-total 1,331 2,048 3,379 424
Released to Upper Cowlitz NOR Unmarked + CWT 408 498 906 64 HOR AD + CWT 5,539 5,093 10,632 3,048 Sub-total 617 773 1,390 2,401
Mortalities HOR AD + CWT 2 1 3 0 HOR AD only 1 2 3 1 Sub-total 3 3 6 1
Foodbank/Surplus HOR AD only 0 0 0 0 Sub-total 0 0 0 0 NOR Grand Total 2,041 2,402 4,443 466 HOR Grand Total 9,368 8,454 17,822 5,162
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Table 27. Disposition of natural (NOR) and hatchery (HOR) winter-run steelhead returns to Cowlitz Salmon Hatchery in late 2015 and 2016. Mark types include unmarked, adipose-clipped (AD only), adipose-clipped and right ventral fin clip (AD + RV), adipose-clipped and left ventral fin clip (AD + LV), unmarked and blank-wire tag (UM + BWT). Adult (≥ 42 cm FL) Jack Female Male Total Adult (< 42 cm FL) Broodstock HOR AD only 132 153 285 0 HOR AD + RV 25 16 41 0 NOR Unmarked 19 43 62 0 NOR UM + BWT 35 39 74 0 Sub-total 364 337 701 0 Released to Tilton NOR Unmarked 175 199 374 0 HOR AD + LV 63 87 150 0 Sub-total 211 317 528 0 Release to Upper Cowlitz HOR AD + RV 159 172 331 0 NOR UM + BWT 64 56 120 0 NOR UM + RV 1 0 1 0 Sub-total 142 287 429 0 Foodbank/Surplus HOR AD only 1,793 2,249 4,042 0 Sub-total 1,793 2,249 4,042 0 Mortalities HOR AD only 0 0 0 0 NOR Unmarked 0 0 0 0 Sub-total 0 0 0 0 NOR Grand Total 294 337 631 0 HOR Grand Total 2,172 2,677 4,849 0
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Table 28. Age and length summary for spring Chinook broodstock at the Cowlitz Salmon Hatchery, 2016. Adipose clip (AD only) and adipose clip/coded wire tagged (AD+CWT) are used for the segregated broodstock program. Data are summarized by age category as total number sub-sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). Gilbert-Rich age notation includes total and freshwater age (e.g., 42 = four years total, exited freshwater as a yearling). N.D. indicates that age could not be determined. Female Male Mark Type Age n FL_avg SD FL Range FL n FL_avg SD FL Range FL
AD, 32 1 68.0 ------43 61.1 5.8 48-69 AD+CWT 41 2 73.5 3.5 71-76 ------
42 245 73.8 4.5 61-85 190 75.7 6.2 62-92
52 81 79.5 4.8 66-90 28 83.9 5.6 72-94 N.D. 57 76.4 5.1 63-91 43 73.1 9.1 50-89
Table 29. Age and length summary for fall Chinook broodstock at the Cowlitz Salmon Hatchery, 2016. Unmarked fish were used for the integrated broodstock program. Adipose-clipped (AD only) fish were used for the integrated broodstock programs. Adipose-clipped/coded-wire tagged fish (AD+CWT) were used in either the segregated or integrated program. Data are summarized by age category as total number sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). Gilbert-Rich age notation includes total and freshwater age (e.g., 42 = four years total, exited freshwater as a yearling). N.D. indicates that age could not be determined.
Female Male Mark Type Age n FL_avg FL_SD FL_Range n FL_avg FL_SD FL_Range
Unmarked 21 0 ------2 57 2.8 55-59
31 1 70.0 ------9 75.6 5.4 66-83
41 10 80.1 4.7 74-90 24 84.8 6.2 69-96
51 0 ------2 93.5 0.7 93-94
52 2 84.5 2.1 83-86 0 ------N.D. 0 ------3 77.3 18.8 57-94 AD only, 2 0 ------18 52.7 6.1 42-65 AD+CWT 1 31 116 70.3 4.9 60-82 181 69.9 6.0 55-88
41 172 79.3 4.3 69-93 141 80.9 7.7 64-106
51 47 82.7 4.8 71-94 21 87.6 7.4 75-100
61 1 81 ------2 84.0 5.7 80-88 N.D. 18 77.7 5.7 68-88 18 72.3 10.8 51-94
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Table 30. Age and length summary for unmarked coho salmon used for the integrated broodstock program at the Cowlitz Salmon Hatchery, 2016. Data are summarized by age category as total number sub-sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length
(FL in cm). Gilbert-Rich age notation includes total and freshwater age (e.g., 42 = four years total, exited freshwater as a yearling). N.D. indicates that age could not be determined. Table does not include age data which were not available at the time of this report.
Female Male Mark Type Age n FL_avg FL_SD FL_Range n FL_avg FL_SD FL_Range
Unmarked 21 0 ------0 ------
22 0 ------0 ------
32 0 ------0 ------
33 0 ------0 ------
43 0 ------0 ------N.D. 3 68.3 7.4 60-74 5 60.6 16.1 33-75 Unmarked+CWT 22 0 ------0 ------
32 10 71.9 5.9 57-77 12 66.8 3.2 61-78
41 0 ------0 ------
42 0 ------0 ------
51 0 ------0 ------N.D. 337 69.5 4.2 54-80 329 65.4 8.6 33-81 AD only N.D. 20 68.9 3.8 61-74 20 68.3 6.5 51-80
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Table 31. Age and length summary for winter-run steelhead broodstock at the Cowlitz Salmon Hatchery. Unmarked fish were used for the upper and lower Cowlitz integrated broodstock programs. Adipose- clipped (AD only) fish were used for the integrated broodstock programs. Adipose-clipped/right ventral- clipped (AD+RV) were used in the upper Cowlitz integrated program. Data are summarized by age category as total number sampled (n) and average, standard deviation (SD), and range (minimum to maximum) of fork length (FL in cm). European age notation includes freshwater age and saltwater age (e.g., 2.1+ = four years total age, exited freshwater as age two and over a full year plus in salt (two-salt)). N.D. indicates that age could not be determined.
Female Male
Mark Age n FL_avg FL_SD FL_Range n FL_avg FL_SD FL_Range Type
Unmarked 2.1+ 7 65.6 4.4 59-71 22 66.5 5.1 57-76
2.2+ 9 72.8 4.8 65-81 2 85.0 5.7 81-89
3.1+ 2 65.5 2.1 64-67 4 64.8 2.9 61-67
3.2+ 1 83.0 ------0 ------
W1.1+ 0 ------1 63.0 ------
R.1+ 7 69.1 2.9 64-72 10 65.7 5.4 60-75
R.2+ 1 77.0 ------2 80.0 1.4 79-81
N.D. 0 ------1 78.0 ------Unmarked 2.1+ 10 67.0 3.9 63-75 20 68.8 5.2 59-77 + CWT 2.2+ 12 79.0 3.8 74-87 3 78.3 2.1 76-80
2.3+ 0 ------1 92.0 ------
3.1+ 3 67.7 2.1 66-70 5 67.8 1.6 66-70
3.2+ 1 77.0 ------3 79.0 10.5 69-90
4.1+ 1 71.0 ------0 ------
W1.1+ 0 ------1 61.0 ------
R.1+ 4 65.0 6.1 56-69 6 68.8 4.6 61-73
R.2+ 3 81.3 1.5 80-83 5 82.0 6.0 75-90
N.D. 0 ------0 ------
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Monitoring Responsibility 8: Hatchery Juvenile Diet, Predation and Presence Timing in the Lower Cowlitz River
A total of 115, mostly brief, angling sampling efforts were completed at individual sites from February 26 through December 13, 2016. Effort was intermittent throughout the year. Hatchery spring Chinook were released starting February and fall Chinook beginning in June of 2016. Hatchery steelhead and cutthroat were released from April 15 to May 15 in 2016.
Coho, steelhead and cutthroat of hatchery-origin were the most commonly species encountered through angling. A total of 30 cutthroat (11 hatchery and 19 natural) were captured during the season. Relatively few Chinook (11) were encountered. The most common prey items by number in the sampled fish were amphipod scuds and other various invertebrates. Cutthroat Fourteen of the 105 stomachs lavaged contained Chinook. Of the 22 hatchery coho that were sampled, none contained salmonids (Table 32). Hatchery origin cutthroat, followed by natural- origin cutthroat were the most likely species to be observed to have eaten fish. No salmonids were observed in juvenile Chinook stomachs, but only 13 individuals of this species were sampled. The only other species and origin categories with a salmonid observed in their stomach included a Chinook found in a natural-origin coho juvenile (sample size = 9) and a Chinook found in a natural-origin steelhead (sample size = 2). Salmonid prey items found in stomachs consisted of both Chinook and coho fry. Non-salmonid fish prey items were most commonly sculpin (Cottus spp.) or redside shiner (Richardsonius balteatus).
Table 32. The number of stomach samples examined in 2016 by species and rates of predation for Chinook, any salmonids and any fish.
Chinook Coho Steelhead Cutthroat AD UM AD UM AD UM AD UM # Sampled 9 4 21 9 30 2 11 19 # Containing: Chinook 0 0 0 1 5 1 4 3 Any salmonid 0 0 0 0 0 0 5 5 Any fish 1 1 0 0 0 0 1 2
AD =Adipose clipped, UM = Unmarked (i.e. no fin clips)
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Monitoring Responsibility 9: Operation of a Rotary Screw Trap and Collection of Juvenile Chinook Genetic Samples in the Lower Cowlitz River
The CRST was operated on a daily basis in 2016. Intermittent outages occurred due to high flow, trap damage, and hatchery releases. In particular, outages from high flows occurred most frequently during the winter. The number of fish captured was highest in late-May through early-July before declining to low levels during the summer and fall months (Figure 13). The highest catches occurred immediately following hatchery releases during May and June. Catch increased from mid- October through the end of the year due to the collection of Chinook fry migrants (lengths <40 mm).
Figure 13. Cowlitz River rotary screw trap daily total salmonid catch at the Rock Creek site and daily maximum flow (cfs) recorded through Mayfield dam in 2016.
Total CRST catch was 61,910 salmonids for the season comprised of primarily HOR Chinook and coho, and NOR Chinook fry (Table 33). Additionally, NOR coho and HOR steelhead made up a smaller, but detectable portion of the salmonid catch. Lower numbers of
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NOR steelhead, cutthroat juveniles, and other salmonid species (chum and pink) were also captured. Even with intermittent outages, the CRST catch demonstrated that fish could likely be collected in sufficient numbers to meet project objectives identified in Appendix J of the 2011 FHMP update, specifically the collection of NOR Chinook tissue samples (estimated need = 3,000).
Table 33. Total fish captured in the Cowlitz River Rotary Screw trap by life stage and origin from January through December 2016. Life stages encountered included fry, parr (P), transitional (T), and Smolt (S). Species Life Stage Origin Total Chinook Fry NOR 25,582
P/T/S NOR 1,489
P/T/S HOR 17,898
Coho P/T/S NOR 2,138
P/T/S HOR 12,440
Steelhead P/T/S NOR 130
P/T/S HOR 1,855
Cutthroat P/T/S NOR 57
P/T/S HOR 77
Other Salmonid 244
Total Salmonids 61,910
Non-Salmonid 1,518
Mean fork length of NOR Chinook migrants collected at the CRST in 2016 increased from spring (45.8 mm) through summer (59.9 mm) and fall (64.5 mm) before declining in winter months (39.4 mm) (Table 34). This suggest that the NOR Chinook cohort was growing from spring through fall, when a new cohort began appearing in winter. This new cohort can be seen
Page 81 of 119 beginning during the fall season (Figure 14). The presence of the older cohort can be observed during the fall – spring time periods. NOR Chinook were most abundant in trap catches during the spring, followed by the winter, and least abundant during the summer and fall. HOR Chinook were only caught in sizeable numbers (>100) during the spring. Average fork lengths of HOR Chinook are routinely greater and more homogeneous in size than NOR Chinook, reflecting a lack of multiple cohorts among HOR Chinook. Mark-recapture trap efficiency trials were conducted to estimate the proportion of fish that the CRST was capturing during this initial season of operation. We utilized Bismarck brown dye and caudal fin clips for Chinook fry and caudal fin clips for parr, transitional and smolt Chinook, coho, steelhead and cutthroat. Recapture rates on Chinook fry marked with Bismarck brown dye averaged 0.74% while recapture rates on Chinook fry marked using caudal fin clips averaged 0.66% (Table 35). Recapture rates on Chinook parr, transitional, and smolts were higher at 2.94%. NOR and HOR coho marked with caudal fin clips had nearly identical recapture rates AT 0.72%, while recapture rates between NOR steelhead at 2.06% was higher than the 0.94% observed for HOR steelhead, however the number of NOR steelhead marked and released was notably fewer (n < 100) when compared to HOR steelhead (n = 969).
Table 34. Size range and average fork lengths (mm) with 95% confidence intervals for Chinook (natural-origin (NOR) and hatchery-origin (HOR) respectively) downstream migrants captured from the Cowlitz River in the spring (Mar-May), summer (June-Aug), fall (Sept-Nov) and winter (Dec-Feb) of 2016.
Spring Summer Fall Winter NOR Mean 45.8 59.9 64.5 39.4 95% C.I. 0.7 1.4 6.1 0.7 Range 15 - 170 35 - 179 31 - 190 24 - 191 n 2279 726 280 1,945 HOR Mean 84.4 101.1 152.3 117.8 95% C.I. 4.8 0.6 62.8 7.9 Range 40 - 210 67 - 185 104 - 186 95 - 138 n 133 14 4 14
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Table 35. Cowlitz Rotary Screw Trap (CRST) marks released and recaptured for Chinook for 2016. The release site for marked fish was approximately 1000 meters upstream from the CRST near the BNSF railroad bridge. Mark types include Bismark Brown dye (Brown), upper caudal clip (UCC), and lower caudal clip (LCC). Percent recapture is reported for weeks with at least 7 recaptures and as a seasonal rate. Number Mark Number Release Dates Marked Type Recaptured Percent Recaptured Chinook Fry Jan 2-8 656 Brown 12 1.82% Jan 9 - 13 432 Brown 2 Feb 8 - 11 1,689 Brown 5 Feb 17 -18 1,409 Brown 3 Apr 3 -9 2,544 Brown 20 0.78% Apr 10 -16 2,043 Brown 21 1.03% Apr 17 - 23 1,686 Brown 14 0.83% Apr 25 - 26 108 Brown 0 May 18 - 25 511 Brown 4 Nov 30 - Dec 1 177 Brown 1 Dec 6 - 8 228 Brown 1 Dec 13 - 15 399 Brown 0 Dec 20 - 22 543 Brown 4 Dec 28 - 29 1,374 Brown 15 1.09% Total 13,799 102 0.74% Chinook Fry Jan 104 UCC 1 266 LCC 7 2.63% Feb 543 UCC 2 1,730 LCC 2 Apr 393 UCC 1 447 LCC 3 May 664 UCC 7 1.05% 341 LCC 3 June - July 45 UCC 2 160 LCC 3 Nov - Dec 368 UCC 1 545 LCC 5 Total 5,606 37 0.66% Chinook P/T/S Jan 2 UCC 0 25 LCC 1 Mar - Apr 66 UCC 0 63 LCC 0 May - June 266 UCC 5 417 LCC 22 5.27% July - Dec 58 UCC 0 54 LCC 0 Total 951 28 2.94% Page 83 of 119
Table 36. Cowlitz Rotary Screw Trap (CRST) marks released and recaptured for coho and steelhead for 2016. The release site for marked fish was approximately 1,000 meters upstream from the CRST near the BNSF railroad bridge. Number Number Percent Release Dates Marked Mark Recaptured Recaptured Hatchery Coho Apr 26 - Jun 9 2,810 UCC 11 0.39% May 2 - Jul 1 3,897 LCC 37 0.95% Total 6,707 48 0.72% Hatchery Steelhead Apr 16 - Jun 22 631 UCC 6 Apr 18 - Jun 28 647 LCC 6 Total 1,278 12 0.94% NOR Coho 2016 422 UCC 3 2016 547 LCC 4 Total 969 7 0.72% NOR Steelhead Apr 15 - Oct 27 60 UCC 1 Apr 21 - Oct 20 37 LCC 1 Total 97 2 2.06%
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Figure 14. Cowlitz rotary screw trap seasonal (winter, spring, summer, and fall time periods) migrant lengths of natural-origin (NOR) Chinook catch at the Rock Creek site in 2016.
Discussion
The goal for the lower Cowlitz River Monitoring and Evaluation Program is to provide metrics of salmon and steelhead abundance, productivity, distribution, and diversity useful for monitoring progress towards meeting hatchery reform and salmonid recovery goals and for guiding fishery and hatchery management. In order for these estimates to provide useful feedback for adaptive management, they must be unbiased and of known precision. Methodology to achieve this quality of result was initially developed through Appendix J of the FHMP Update (2011). Many of the methods used to minimize bias and derive precise estimates have been
Page 85 of 119 previously developed in other watersheds, and these methods are being refined to the conditions and species of interest in the lower Cowlitz River. This report describes the efforts to implement the third year of the lower Cowlitz River Monitoring and Evaluation Plan. In this discussion, we highlight the most immediate issues and solutions proposed to improve this monitoring program in subsequent years. With respect to the quality of resulting estimates, our initial focus is to minimize bias of the estimates. A secondary and subsequent effort will be to increase precision (decrease uncertainty) of the estimates.
Several important steps were taken in 2016 to solidify tools for obtaining unbiased estimates and to combine information from the spawning grounds, hatchery returns, and in-river fisheries as described in the FHMP Update (2011). The most notable advances were the successful use of tributary weirs and a GRTS survey protocol to provide tributary estimates of both coho and steelhead spawner abundance and the estimation of NOR catch in Cowlitz River fisheries. An additional advance for monitoring was the operation of a smolt trap on the main stem Cowlitz River. Operations in 2016 demonstrated the ability of the trap to fish for the duration of the outmigration period (November through June) and to evaluate capture rates throughout the season. Both of these outcomes are needed to meet the long-term objectives for this smolt trap, including estimates of smolt abundance and timing, and collection of genetic samples from juvenile Chinook. Together, these results should significantly contribute to the evaluation of the management of Cowlitz River salmon and steelhead.
Steelhead Spawner Abundance
Steelhead spawner abundance was estimated above three tributary weirs in 2016. This area represented 43.9% of the modeled spawner habitat. The mark-recapture estimates above the tributary weirs met the assumptions of the closed-population estimator and was likely to be unbiased. Similarly, the reaches surveyed outside the tributary weirs were selected using an unbiased design (stratified random sampling) and covered a majority of the remaining modeled steelhead distribution. In total, the mark-recapture estimates and surveyed reaches covered 71.7% of the modeled steelhead distribution. The combination of good weir efficiency (27-92%) and a high level of spatial coverage resulted in a precise (CV = 10.6%) steelhead spawner abundance estimate.
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The methodology used to estimate the proportion of hatchery-origin steelhead spawners in these tributaries was updated for the 2016 spawn year. The proportion of hatchery-origin steelhead spawners in Cowlitz River tributaries is a subject of fishery management concern due to the large number of hatchery summer and winter steelhead produced at the Cowlitz Trout Hatchery and the relatively small population of NOR winter steelhead. Only one hatchery-origin summer steelhead was observed at the weir sites in fall of 2015; a time frame that overlapped with the 2016 spawn year of winter-run steelhead. The majority of hatchery-origin steelhead observed were winter run with an overall estimated pHOS of 26.7%. However, this estimate is misleading because it does not adjust for the extent of temporal or spatial overlap in spawning that occurred between NOR and HOR spawners. In the Cowlitz tributaries, lack of spatial overlap between NOR and HOR steelhead spawners is substantial and very likely to affect the extent of genetic exchange that occurs between NOR and HOR fish. For example, the overall pHOS of winter steelhead was heavily influenced by the relatively large numbers of hatchery steelhead spawning in Blue Creek, which is a tributary near the smolt release location for the hatchery fish. One quarter of the winter steelhead spawning in the lower Cowlitz River were estimated from two miles of spawning habitat in Blue Creek and 87.9% of the spawners in this tributary were hatchery-origin steelhead. In comparison to Blue Creek, the proportion of hatchery spawners in other tributaries of the lower Cowlitz River basin was relatively low. One half of the winter steelhead spawning in the lower Cowlitz River were estimated above the tributary weirs and just 3.5% of the spawners in this area were hatchery-origin steelhead. The remaining one quarter of the winter steelhead spawning occurred outside the tributary weirs (excluding Blue Creek) and 10.0% of the spawners in these areas were hatchery-origin spawners. With the exception of Blue Creek, therefore, operation of the tributary weirs reduced the numbers of hatchery steelhead spawners to one third the level that would have been observed had the weirs not been in place.
This is the second year that the combination of weir mark-recapture estimates and GRTS survey reaches were used to estimate steelhead spawning in the lower Cowlitz River. Results from this work provide important insight into the steelhead spawning activity that may be used to adaptively manage the monitoring study design in future years. In both years, very few steelhead were observed in Lacamas Creek at the weir or in spawner surveys. This tributary, which has consistently high numbers of coho spawners, does not appear to support a substantial portion of the steelhead population. Low numbers of steelhead returning to Lacamas Creek resulted in too Page 87 of 119 few fish to successfully generate a mark-recapture estimate for this tributary in both 2015 and 2016. If additional years of monitoring continue to demonstrate low numbers of steelhead spawning in Lacamas Creek, the operation of this tributary weir during the steelhead spawning season (February to June) may be more effectively implemented elsewhere for the purpose of estimating steelhead spawner abundance and reducing pHOS of the population. In addition, the majority of steelhead spawning appears to occur either above the tributary weirs or in index reaches (non-random, Arkansas Creek and Blue Creek) surveyed outside of tributary weirs. Very few of the redds were observed in the GRTS reaches themselves. In 2015, 24 of the 28 GRTS reaches had no observed redds all season. In 2016, 26 of the 28 GRTS reaches had no observed redds all season. This suggests that the GRTS methodology is currently applied to the area of the lower Cowlitz River tributaries with very little of the current steelhead spawning habitat and that the majority of spawning (core areas) is occurring above tributary weirs or in non-randomly selected index reaches outside the weirs. A more time-efficient and alternate survey design for steelhead may be warranted in the future and could focus on obtaining high quality estimates in the core spawning areas and an expansion of this estimate using surveys of the entire spawning distribution during peak spawn timing (Liermann et al. 2015).
Chinook Spawner Abundance
The existing method for deriving Chinook spawner abundance is of unknown bias and precision. A major concern with the peak count expansion method is that the origin of the modified expansion factor for helicopter aerial surveys is, to our knowledge, undocumented and therefore cannot be evaluated. Regardless, expansion or calibration factors need to be periodically validated and this type of validation has not occurred in recent history of monitoring for Chinook salmon on the Cowlitz River. Peak counts are also problematic when redd superimposition occurs due to years of high abundance or in high density spawning areas such as the reach between Barrier Dam and Mill Creek. In addition, peak redd count expansions were derived for main stem spawning only but fall Chinook are also observed to spawn in tributaries. The proportion of tributary spawners is unknown.
The Monitoring and Evaluation Plan in the FHMP 2011 proposes genetic mark-recapture (GMR) as the recommended method to derive unbiased estimates of Chinook spawner abundance. This method has been used successfully in multiple watersheds in Washington State
Page 88 of 119 using spawners and smolts (Seamons et al. 2012; Rawding et al. 2014b). The GMR method uses genetic markers as a “mark” to connect parent spawners (first sample) and juvenile offspring (second sample) in a closed population mark-recapture estimator. This method relies on tissue samples taken from a representative sample of spawners (tributaries and main stem) and juvenile outmigrants. Genetic samples have been collected from fall spawners for the past five spawn years (2012 through 2016) and were collected from juveniles in 2015 (partial year operation) and 2016.
Coho Spawner Abundance
The combination of moderate weir efficiency (29-59%) and moderate levels of spatial coverage resulted in an estimate precision (CV = 30.1%) higher than the 15% coefficient of variation recommended for monitoring of salmon and steelhead populations listed under the Endangered Species Act (Crawford and Rumsey 2011). Coho spawner abundance was estimated above three tributary weirs in 2016, representing 19.9% of the modeled spawner habitat. The mark-recapture estimates above the tributary weirs met the assumptions of the closed-population estimator and was likely to be unbiased. Similarly, the reaches surveyed outside the tributary weirs were selected using an unbiased design (stratified random sampling) and covered a portion of the remaining modeled steelhead distribution. In total, the mark-recapture estimates and surveyed reaches covered 31.6% of the modeled coho distribution.
Precision of the overall estimate was influenced by the lack of a mark-recapture estimate from Olequa Creek. Exceptionally high water during fall 2016 decreased the number of days that the Olequa Creek weir was effective at capturing adults and low sample sizes resulted in no mark-recapture estimate for this tributary. Expansion of the redd counts in GRTS reaches was used as an alternative method for estimating the number of coho spawners in Olequa Creek, which represents approximately one quarter of the tributary spawning area for coho salmon in the lower Cowlitz River. Mark-recapture estimates are typically much more precise than the GRTS redd expansion and overall coho spawner estimates in the lower Cowlitz River have been more precise (CV < 15%) in years when a mark-recapture estimates were available from Olequa Creek.
This is the fourth year that coho spawner abundance has been successfully estimated in the lower Cowlitz River tributaries. In all four years of the coho monitoring efforts, the analysis has
Page 89 of 119 required a flexible approach. Our study design, which includes multiple tributary mark-recapture weirs as well as redd counts in surveys above mark-recapture weirs, is intentionally redundant. When mark-recapture estimates can be successfully completed in multiple tributaries and cover a larger portion of the coho distribution, the resulting abundance estimate will be more precise. However, redundancies in the data collection also allow for an analysis to be successful when annual conditions preclude the generation of mark-recapture estimates.
Catch of Natural-Origin Fish in the Cowlitz River Fishery
The ultimate objective of the Cowlitz River creel surveys is to estimate incidental mortalities of natural-origin fish in the Cowlitz River fishery. Because release of all natural-origin salmon and steelhead is currently required in the fishery, mortalities of natural-origin fish are an assumed release mortality applied to the estimated number of NOR fish released. The Fisheries Management Evaluation Plan (FMEP) for the lower Columbia River (WDFW 2003) proposed a 5% release mortality rate for winter steelhead and an 8.6% release mortality rate for Chinook salmon in tributary fisheries. Release mortality for coho salmon was not included in the plan because coho salmon were not listed at the time the plan was developed.
The estimate of NOR catch relies on the availability of angler reported catch in WDFW Catch Record Cards and has an eighteen month to two-year lag between fishery and reporting. Catch estimates of hatchery-origin fish were available for 2015 and were used to estimate catch of NOR fish in these years. The estimates of NOR catch are derived from HOR catch estimates and the ratio of NOR to HOR fish encountered in the fishery, and both of these metrics rely on self-reporting by anglers. WDFW estimation of HOR catch from the catch record card reporting system incorporates a correction factor for self-reporting bias (Kraig and Smith 2010); however, the accuracy of encounter ratios reported in the creel surveys has not been independently validated.
In 2015, WDFW Science Division conducted a review of spot creel methodology in Cowlitz River and recommended that a minimum 5% sample rate be maintained to ensure that sample size did not bias the estimated NOR:HOR encounter ratio (Gleizes et al. 2016. Appendix B). However, the creel survey efforts in 2015 did not benefit from these recommendations because they were provided in December 2015. A post-hoc evaluation of our results suggest that the minimum sample rates recommended by the WDFW Science Division were met for fall Chinook
Page 90 of 119 salmon and coho in 2015. However, a post-hoc evaluation also revealed that creel sampling of the winter steelhead and spring Chinook fisheries in 2015 did not meet the recommended minimum rate and additional strategies should be employed to increase creel sample rates for the species in future years. Our initial strategy has been to increase sampling on weekend days to increase the number of fish sampled. If we continue to not meet sampling rates, multiple samplers covering different areas of the river may need to be implemented.
Returns to Cowlitz River Barrier Dam Adult Handling Facility
Unbiased estimates of returning hatchery fish rely on each hatchery stock having a distinct mark type, returning fish being accurately identified and counted at the Cowlitz Salmon Hatchery separator, and data management systems being available to facilitate data exchange and analysis. Four different databases are needed for successful data exchange and analysis of the hatchery returns. Total returns and their disposition (where they are released) are documented in the Cowlitz Hatchery Separator database (Tacoma Power). Biological sampling data (including scale ages) are archived in the WDFW Traps-Weirs-Surveys database. Coded-wire tag data are archived in WDFW coded-wire-tag database but the ages from this database need to be translated to the TWS database in order to make a final age assignment for all sampled fish (CWT ages, when available, are needed to validate scale age data). A fourth database, WDFW Fishbooks, is needed to interpret the marking and tagging combinations to hatchery broodstock program.
Although the age composition of hatchery broodstock has historically relied on coded-wire tags, evaluation of contemporary programs will benefit from age information provided by both coded-wire tags and scales for several reasons. Coded-wire tags give the most accurate age for fish reared in the hatchery, but are not necessarily available for natural-origin fish which are increasingly incorporated into integrated broodstock programs. Furthermore, scale age data interpret the age of ocean entry whereas coded-wire tag data assume that ocean entry occurs the year that fish were tagged and released. Given the emphasis on integrated hatchery programs for rebuilding stocks on the Cowlitz River and the higher residualism rates documented for some integrated programs, particularly steelhead programs (Hausch and Melnychuk 2012), scale ages are needed in addition to CWT based ages in order to evaluate the success of the hatchery practices.
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Hatchery Juvenile Diet, Predation and Presence Timing in the Lower Cowlitz River
Based on data collected in 2015, the predation rate and number of fish released would suggest that hatchery spring Chinook predation has a greater impact than cutthroat on the natural Chinook population. Data collected during 2016 did not support that conclusion as predation rates of both natural-origin and hatchery cutthroat were higher than the other species. Of the Chinook sampled during 2016, no stomach contents containing Chinook were recovered. The number of fish sampled during 2015 was approximately five times greater than the number of fish sampled during 2016. A smaller sample size may obfuscate conclusions based on this study. Since this was only one year of sampling and predation rates could vary with river conditions, management decisions based on these predation observations should consider all years of this study.
Operation of a Rotary Screw Trap in the Lower Cowlitz River
2016 was the first full year of operating a rotary screw trap in the lower Cowlitz River and provided additional information on migration timing of downstream migrants produced upstream of the confluence of the Toutle River. Variable catch rates of juvenile Chinook throughout the year confirmed that the majority of Chinook outmigration occurs between November and June. Chinook migration appeared to be relatively low during the summer, indicating that long-term operation of the trap may not be necessary during this time period. Catches of other salmonid species were also low during the summer.
Accurate estimates of juvenile outmigration will rely on estimating the probability of capture for each species in the smolt trap. In a large river such as the Cowlitz River, these capture rates are expected to be low (e.g., 1-5% for Chinook and ~0.5% for coho and steelhead based on Skagit River data, WDFW unpublished). For the purpose of abundance estimations, low capture rates can successfully result in an abundance estimate if high numbers of fish are used for mark and adequate numbers of fish are recaptured within the defined strata. In 2015, recapture rates of Chinook were estimated using fry marked with Bismarck brown or caudal fin clips. Although the recapture rates of these two mark types appeared to be similar, sample sizes were low and this reduced statistical power to detect a difference. We do not plan to use the clipped fish for efficiency trials in the future given the potential that the clips affect the swimming ability of the fry sized fish and the availability of large numbers of Bismarck brown dye fry available for
Page 92 of 119 efficiency trials. Instead, we will focus on increasing the numbers of fish used to estimate the probability of capture for each species and ensuring that the releases occur over the entirety of the species outmigration period.
The strategy to increase numbers of fish used to estimate the probability of capture will differ among species. Catches of juvenile Chinook in the smolt trap are high enough that a single-trap design will be implemented for this species. In comparison, catches of coho and steelhead in the smolt trap were low. In 2016, the mark-release groups for coho and steelhead were larger in number for HOR fish than for NOR fish and the availability of NOR coho and steelhead for mark-recapture trials was inconsistent among weeks. In the future, NOR and HOR coho will be used to evaluate the probability of capture for NOR coho and a combination of NOR and HOR steelhead will be used to evaluate the probability of capture for NOR steelhead at the smolt trap. Differences in capture rates of NOR and HOR smolts will be evaluated using a likelihood ratio test. NOR release numbers used for evaluating capture probability may also be improved by marking and releasing NOR fish transported downstream from the Upper Cowlitz watershed.
Although trap operation continued to pose challenges, high catches of juvenile NOR Chinook (>3,000) confirmed enough Chinook juvenile tissue samples can be collected to meet genetic mark recapture estimates of adult fall Chinook spawner abundance a viable technique in future years.
Conclusion
The 2000 Cowlitz River Project Settlement Agreement states that the emphasis the of agreement is ecosystem integrity and that fisheries obligations will be met by a combination of effective upstream and downstream passage, habitat improvement, and an adaptive management process coupled with continued artificial production. The adaptive management process requires input from monitoring activities as part of the iterative process to improve decision making. The monitoring and evaluation results reported here represent a significant commitment of resources by both Tacoma Power and WDFW towards meeting the obligations of the settlement agreement. The current Monitoring and Evaluation Plan, included in the 2011 FHMP update, began in 2013 and has improved our understanding of natural salmonid populations in the lower Cowlitz River. While our understanding of these populations is not complete or certain,
Page 93 of 119 information from monitoring has improved our ability to assess population assumptions and make better management decisions.
References
Bentley, K., Glaser, B., Buehrens, T., Byrne, J., and S. Kelsey. 2015. Evaluation of recreational steelhead catch in the South Fork Toutle and Washougal rivers, 2011-2014, FPT 15-06. Washington Department of Fish and Wildlife, Olympia, WA. Available online: http://wdfw.wa.gov/publications/01730/ Bentley, K. 2016. Evaluation of creel survey methodology on the Cowlitz River. Memo submitted to Tacoma Power. Bjorkstedt, E. P. 2005. Darr 2.0: Updated software for estimating abundance from stratified mark-recapture data, NOAA-TM-NMFS-SWFSC-368. National Marine Fisheries Service, Santa Cruz, California. Cooch, E., and G. White. 2006. Program MARK: a gentle introduction, Appendix B The 'delta method', http://www.phidot.org/software/mark/docs/book. Crawford, B. A., and S. M. Rumsey. 2011. Guidance for the monitoring recovery of Pacific Northwest salmon and steelhead listed under the Federal Endangered Species Act. NOAA's National Marine Fisheries Service, Northwest Region. Fransen, B. R., S. D. Duke, L. G. McWethy, J. K. Walter, and R. E. Bilby. 2006. A logistic regression model for predicting the upstream extent of fish occurrence based on geographic information systems data. North American Journal of Fisheries Management 26:960-975. Fisheries and Hatchery Management Plan Update. November 2011. Tacoma Power. Cowlitz River Project, FERC No. 2016, https://www.mytpu.org/file_viewer.aspx?id=2979, https://www.mytpu.org/file_viewer.aspx?id=2980. Gleizes, C., C. Nissell, J. Serl, M. Zimmerman, B. Glaser. 2016. Lower Cowlitz River Monitoring and Evaluation, 2015. Washington Department of Fish and Wildlife. Toledo Washington. Hausch, S. J., and M. C. Melnychuk. 2012. Residualization of hatchery steelhead: a meta- analysis of hatchery practices. North American Journal of Fisheries Management 32:905- 921. Hymer, J. 1994. Estimating the population size of natural spawning fall Chinook salmon in the Cowlitz River, Columbia River Laboratory Progress Report 94-24. Washington Department of Fish and Wildlife, Battle Ground, Washington. Kraig, E., and S. Smith. 2010. Washington state sport catch report 2003. Washington Department of Fish and Wildlife, Olympia, WA. Available online: http://wdfw.wa.gov/publications/01050/ Liermann, M. C., D. Rawding, G. R. Pess, and B. Glaser. 2015. The spatial distribution of salmon and steelhead redds and optimal sampling design. Canadian Journal of Fisheries and Aquatic Sciences 72:434-446. Martyn Plummer (2016). rjags: Bayesian Graphical Models using MCMC. R package version 4- 6. https://CRAN.R-project.org/package=rjags
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Rawding, D., B. Glaser, and T. Buehrens. 2014a. Lower Columbia River fisheries and escapement evalatuion in southwest Washington, 2010, FPT 14-10. Washington Department of Fish and Wildlife, Olympia, Washington, http://wdfw.wa.gov/publications/01702/. Rawding, D., and J. Rodgers. 2013. ISTM Fish Component Objective 2 Report: "Evaluation of the Alignment of Lower Columbia River Salmon and Steelhead Monitoring Program with Management Decisions, Questions, and Objectives" PNAMP 2012-001. http://www.pnamp.org/document/4143 Rawding, D. J., C. S. Sharpe, and S. M. Blankenship. 2014b. Genetic-based estimates of adult Chinook salmon spawner abundance from carcass surveys and juvenile out-migrant traps. Transactions of the American Fisheries Society 145:55-67. Schwarz, C. J., and G. G. Taylor. 1998. The use of stratified-Petersen estimator in fisheries management: estimating pink salmon (Oncorhynchus gorbuscha) on the Frazier River. Canadian Journal of Fisheries and Aquatic Sciences 55:281-297. Seamons, T. R., D. Rawding, P. Topping, D. Wildermuth, S. Peterson, and M. S. Zimmerman. 2012. Spawner abundance estimates for Green River Chinook salmon. Submitted to the Pacific Salmon Commission Sentinel Stock Committee, Washington Department of Fish and Wildlife, Olympia, Washington. Seber, G. A. F. 1982. The estimation of animal abundance and related parameters. Charles Griffin and Company Limited, London. Stevens, D. L., and A. R. Olsen. 2004. Spatially balanced sampling of natural resources. Journal of the American Statistical Association 99:262-278. Sturtz, S., Ligges, U., and Gelman, A. (2005). R2WinBUGS: A Package for Running WinBUGS from R. Journal of Statistical Software, 12(3), 1-16. Yu-Sung Su and Masanao Yajima, (2015). R2jags: Using R to Run 'JAGS'. R package version 0.5-7. https://CRAN.R-project.org/package=R2jags
Tacoma_Power. 2011. Cowlitz River Project FERC No. 2016: Fisheries and Hatchery Management Plan Update 2011 - Appendix J. WDFW. 2003. Washington Department of Fish and Wildlife’s lower Columbia River Fisheries Management and Evaluation Plan. Washington Department of Fish and Wildlife. Olympia, Washington.
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Appendices
Appendix A. Juvenile Life Stage Decision Tree
Y FRY < 45 mm FL? PARR-SUBYRLG
Date-Length PARR N N PARR-YRLG >300 mm FL distinct parr marks or or signs no signs of smoltification of maturation CUTTHROAT, < 500 mm FL RAINBOW TROUT Y ADULT ≥ 500 mm FL N STEELHEAD
TRANS-SUBYRLG Y show initial signs of smoltification, Date-Length TRANSITIONAL silvery appearance, faded parr marks TRANS-YRLG
N
SMOLT-SUBYRLG Advanced signs of smoltification, faded parr marks, deciduous Date Y OR SMOLT scales, silvery appearance, Date-Morphology black banding along the trailing SMOLT-YRLG edge of the caudal fin
N
UNKNOWN
Updated 2.3.2014 by Thomas Buehrens
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Appendix B. Deliverable to Tacoma Power. Memo describing potential methodology to use genetic mark-recapture to improve Chinook adult abundance estimates.
Memo
Trans-generational genetic mark-recapture and its application in the Cowlitz River
22 December 2016
Todd R. Seamons1 Mara Zimmerman1
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1Washington Department of Fish and Wildlife, 600 Capitol Way N., Olympia, WA 98501 Trans- generational genetic mark-recapture (tGMR) is proposed to be used to estimate spawner abundance of lower Cowlitz fall Chinook salmon. What follows here is a general description of tGMR methodology and how it would be applied to estimating the spawner abundance of lower Cowlitz River fall Chinook salmon.
Experimental design summary
Pearse et al. (2001) proposed a new method of estimating animal abundance that uses the standard mathematical application of closed-population Petersen mark-recapture models (Seber 1982) and exploits the ability to genetically identify parents and offspring, i.e., offspring represent a capture of their parents in the form of DNA. In the model, which we refer to as transgenerational genetic mark recapture (tGMR), parents are sampled in the first sampling event and their offspring are sampled in the second sampling event of a two-sample mark- recapture model and the abundance of the all adults in the parent pool, whether or not they successfully produced offspring, is estimated. That different collections of individuals are sampled during each sampling event makes this model fundamentally different from all other mark-recapture or markre-sight models. The probability of recapturing a parent in the second sampling event is a function of individual reproductive success. This difference modifies the standard assumptions of the closed-population mark-recapture model, and, in some cases, requires new assumptions.
The first sampling event is obtaining tissue samples from the parent pool. As currently practiced by Washington Department of Fish and Wildlife Molecular Genetics Lab (WDFW MGL) in Puget Sound Chinook populations, the parent pool is sampled after spawning has taken place, i.e., we sample naturally spawning natural- and hatchery-origin adult Chinook after they have died on the spawning grounds. The second sampling event is obtaining tissue samples from offspring produced by the parent pool sampled in the first event. As currently practiced by WDFW MGL, outmigrating, natural-origin, subyearling Chinook juveniles are collected and sampled as they are caught in a smolt trap the spring immediately following fall spawning. Carcass and juvenile tissue samples are genotyped and relationships among parents and offspring (parentage) are inferred using the genetic data. Counts derived from the relationship information are fed into tGMR models and abundances are estimated.
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What follows is a brief description of the main assumptions of the model followed by a detailed description of the procedures for each step of the tGMR method, the proposed application of those procedures to the lower Cowlitz fall Chinook population, and a description of critical considerations for meeting the assumptions of the model.
Assumptions of the tGMR model
The following standard assumptions of a closed population model (Seber 1982) must be met in order to produce an unbiased tGMR estimate of abundance:
1. Genetic marking (as opposed to some other form of marking, e.g., PIT tags) will not affect capture probability in the second sampling event, 2. Genetic marks will not be lost before the second sampling event, 3. All genetically marked and unmarked fish are correctly identified and enumerated, 4. The population is closed, and 5. a) All fish in the population have the same probability of being captured (genetically marked) in the first sampling event OR b) all fish, genetically marked and unmarked, have the same probability of being captured in the second sampling event OR c) the capture probabilities of the first and second events are independent.
First Sampling Event – sampling from the parent pool
Using tGMR methods, the first sampling event is getting tissue samples from a random, representative sample from the parent pool. As currently practiced by WDFW MGL, salmon carcasses found on the spawning grounds serve as the samples from the parent pool. Using carcasses ensures Assumption 1 (no marking effect) is met because clipping fin tissue from a fish that has already spawned and died does not affect the number of offspring it may (or may not) have produced, i.e., does not affect the probability of detection in the second sampling event.
Because the tGMR model is a closed-population model, it is critical that both the parent and offspring pools are properly defined and that the target population can be sampled without contamination from individuals from non-target populations (“immigrants”) in order to meet Assumption 4 (closed population). For the first sampling event, this means sampling carcasses found only upstream of the smolt trap. For some rivers, this also means sampling only fish with a particular run-timing. For example, in the Nooksack River there are spring Chinook and fall
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Chinook. If fall Chinook adults are included in the analysis when estimating spring Chinook abundance, the spring Chinook abundance estimate will be biased high. (If fall Chinook parents and offspring are included in the analysis, the abundance estimate will not be biased, but it will be a combined fall/spring Chinook abundance estimate, which may not be desired.) In the Nooksack River, in order to exclude fall Chinook, all carcass genotypes are compared to genetic baseline (genetic stock identification or GSI), which has sufficient statistical power to discriminate spring Chinook from fall Chinook. Any carcass genetically identified as a fall Chinook is removed from the dataset. A similar approach can be taken on the Cowlitz River to remove spring Chinook salmon, and retain fall Chinook, from the parent pool.
Assumption 5b (equal probability of capture in the second sampling event) is always violated because the probability of capturing a parent in the form of its offspring is a function of its reproductive success, which, in salmon and trout, is known to be highly variable among individuals (e.g., Seamons et al. 2004b; Williamson et al. 2010). Violation of 5b necessitates 5a (equal probability of marking in first sampling event) or 5c (independence of the sampling events) be met, i.e., the carcass collection must be representative and unbiased with regard to reproductive success in order to produce an unbiased abundance estimate. This means that it is acceptable, for example, to sample adults known to have failed to spawn (e.g., prespawning mortalities), just not too many or too few with respect to the remainder of the spawning population. With a two-sample design, it is impossible to directly test whether or not a carcass collection is representative or biased with regard to reproductive success. While carcass collections are known to be somewhat unrepresentative of the spawning population as a whole (e.g., jacks are undersampled), the expected bias is thought to be very small (Rawding et al. 2014; Seamons et al. 2013). Carcass collections are likely biased with regard to age and body size (Murdoch et al. 2010; Zhou 2002), and these traits are known to be positively correlated with Chinook reproductive success (Williamson et al. 2010). However, any bias is likely to be small since correlations of body size and reproductive success are typically weak (Dickerson et al. 2005; Rawding et al. 2014; Seamons et al. 2004a; Williamson et al. 2010).
Second Sampling Event – sampling from the offspring pool
Using tGMR methods, the second sampling event is getting tissue samples from a random, representative sample from the offspring pool. As currently practiced by WDFW MGL Page 100 of 119 for salmon, the offspring pool consists of sub-yearling migrant juvenile Chinook salmon, which are captured using a screw trap. As with the parent pool, because the tGMR model is a closedpopulation model, it is critical that the offspring pool is properly defined and that the target population can be sampled without contamination from individuals from non-target populations
(“immigrants”) in order to meet the closed-population assumption, Assumption 4.
Several possible non-target populations have been identified when performing tGMR in Pacific salmon populations: non-target brood years (e.g., yearling migrants), hatchery populations (i.e., unmarked hatchery-produced migrants), different stocks based on run-timing (e.g., a mix of fall and spring Chinook migrants), or non-target subsets of the target population (e.g., migrants spawned downstream of the smolt trap). Immigrants from non-target brood years are identified by aging individuals using scales or by the relationship of body length and date of migration. Immigrants from hatchery populations can be identified through parentage analysis if all hatchery broodstock from the appropriate brood year were genotyped, or adjustments to capture number based on QAQC marking rates can be made when parentage analysis is not possible. In most cases, immigrants from different stocks are identified using GSI. Genotypes of samples are compared to baseline genetic data, the posterior probability of belonging to the various baseline populations is calculated, and decision criteria are used to include or exclude individuals from further analysis. Immigrants from non-target subsets of the target population are avoided by careful sampling experimental design rather than identified post-capture, for example by placing the smolt trap downstream of all spawning of the target population. In order to meet Assumption 4, any and all immigrants identified are removed from further analysis.
Identification of recaptures
Using tGMR methods, “recaptures” of marked carcasses occur when a genotyped adult is genetically and statistically inferred as a parent to a genotyped offspring.
Genotyping – WDFW has used Pacific Salmon Commission/GAPS standardized microsatellite markers and SNP (Single Nucleotide Polymorphism) markers for parentage analysis. The laboratory procedures and analytical methods are well established for the microsatellite GAPS
Page 101 of 119 loci (Seeb et al. 2007) and GAPS loci have been used successfully for previous genetic markrecapture studies (e.g., Rawding et al. 2014; Seamons et al. 2013). The SNP markers are more recently developed but have as much or more statistical power than the microsatellite markers for parentage and GSI analysis.
Parentage Analysis –To assign parents, we use the well-established maximum likelihood parentage/sibship assignment algorithm employed in the software COLONY (Wang 2004; Wang
2007; Wang and Santure 2009). Using tGMR, Assumption 2 (loss of marks) and Assumption 3 (correct mark identification) apply to genotyping and parentage assignment errors. Genetic marks technically cannot be lost the same way other physical tags can, but using tGMR marks can be “misidentified” through genotyping and parentage assignment error. Laboratory protocols are designed to minimize genotyping errors; however, some genotyping error is unavoidable. The algorithms employed by COLONY explicitly account for genotyping error when calculating likelihoods, and the possible effects of parentage assignment error on tGMR estimates are complex and are likely random with respect to the recapture count, i.e., they are not likely to bias the number of recaptures or the tGMR abundance estimate. Thus, we assume Assumption 2 and Assumption 3 are met, but do not explicitly test this assumption.
tGMR Statistical Models
Once sampling, genotyping, and parentage assignments are completed, marks, captures, and recaptures are enumerated and entered into the standard Lincoln-Petersen model:
(2)
where 푁̂ is the abundance estimate, m is the number of marks or genotyped parents, r, recaptures, is a function of the number of marked parent individuals genetically identified as parents of sampled offspring, and c is the number of captures, which is a function of the number of genotyped offspring. Done this way, the model estimates the number of parents in the parent pool.
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There are two statistical models typically used to estimate abundance and uncertainty using the above equation, and using tGMR, each model requires slightly different procedures to be followed. The first assumes the binomial distribution, which is based on sampling with replacement (hereafter the “binomial model”). One benefit of this approach is that it uses all of the data. We used Bailey’s modification of the Lincoln-Petersen model, which corrects bias due to small sample sizes (Seber 1982):
(3)
For the binomial model, m is the number of genotyped parents, c is twice the number of genotyped juveniles (each juvenile is potentially a recapture of its mother and its father), and r is the number of sampled parents genetically identified as parents of sampled offspring. Note that all parentage assignments are used, i.e., each instance of the same parent being assigned to different offspring is counted. Approximate unbiased sampling variance for this model is estimated by:
(4)
The second model assumes the hypergeometric distribution, which is based on sampling without replacement (herein the “hypergeometric model”). We used Chapman’s modification of the Lincoln-Petersen model, which corrects for bias due to small sample sizes (Seber 1982):
(5)
For the hypergeometric model, m is the number of genotyped parents, c is the total number of unique marked and unmarked parents captured in the offspring collection. As with the binomial model, marked parents are identified by parentage assignment. However, unmarked parents must be inferred, which, using our protocol, is done using the sibship analysis performed by the algorithms of the COLONY software (Wang 2013; Wang and Santure 2009). Finally, r is the number of unique sampled parents genetically identified as parents of sampled offspring. Note Page 103 of 119 that when using this model, each captured or recaptured parent is counted only once, even if it was assigned to multiple offspring. Approximate unbiased sampling variance for this model is estimated by:
(6)
We have also used Bayesian models to estimate tGMR abundance for both statistical models. The binomial model is calculated as:
푟 ~ Bin(푐, 푝) (7)
푚 ~ Bin(푁̂, 푝) (8)
The hypergeometric model is calculated as:
푟 ~ Hypergeometric(푚, 푐, 푁̂) (9)
Where m, r, c, and 푁̂ are as defined above for method of moments estimators, and p is the probability of a successful draw from a binomial distribution. Both methods (method of moments and Bayesian) produce similar estimates of abundance and uncertainty, and both are amenable to making adjustments to include uncertainty (variance) from additional sources, for example when adjustments to capture number are made with an estimate (and associated uncertainty) of the number of unmarked hatchery-produced juveniles caught and genotyped.
Application of tGMR to lower Cowlitz fall Chinook
Below are additional details describing the application of the tGMR method to lower Cowlitz fall Chinook salmon.
First sampling event – carcass sampling
Multiple stocks of Chinook are present in the Cowlitz, including five natural-origin populations and three hatchery stocks. Spring Chinook salmon are managed as three populations, one population in the upper Cowlitz River (upstream of Cowlitz Falls dam), a
Page 104 of 119 second population in the Cispus River (upstream of Cowlitz Falls dam), and a third population in the Tilton River (upstream of Mayfield dam). Fall Chinook salmon are managed as two populations, one population in the lower Cowlitz River below Mayfield Dam and one population for all fish spawning upstream of Mayfield Dam, including the Tilton, upper Cowlitz, and Cispus rivers. The target population for the proposed tGMR project is the lower Cowlitz River fall Chinook defined as all hatchery- and natural-origin fall Chinook that spawn in the Cowlitz River mainstem and tributaries downstream of Mayfield Dam.
As with other tGMR projects, we propose to sample carcasses for the first sampling event, both for the relative ease of sampling and in order to easily meet the marking effect assumption. Carcasses are collected from the river and from river banks during weekly spawning grounds surveys throughout the salmon spawning season. Tissue samples are taken from all carcasses, which likely comprise both spring and fall run Chinook. Because genotyping success is low from highly degraded carcasses, carcasses are high-graded prior to sampling; tissue is taken from carcasses with clear eyes and pink gills. Sampled carcasses are classified by origin (hatchery or natural), based on their mark and tag status (adipose fin clip and CWT), and fin tissue from all high-graded carcasses is collected and fixed in vials of 100% ethanol. In order to minimize the opportunity for non-randomly sampling carcasses based on reproductive success (i.e., in an attempt to meet Assumption 5a), spawning grounds surveys are done in all spawning areas on a weekly basis from September through the end of November, and carcass selection is based only on carcass quality.
To date, genetic samples have been collected from carcasses in the lower Cowlitz River for four consecutive years (2013-2016, Table 1). These include both spring and fall Chinook. The spring Chinook are a non-target (i.e., immigrant) population. In order to produce an unbiased tGMR abundance estimate, the spring Chinook will be identified and removed from analysis. Spring Chinook will be identified genetically using genetic stock identification (GSI). In GSI, the likelihood of a test subject belonging to any number of reference or baseline populations is calculated from genotypes and reference population allele frequencies. Several different algorithms are available, but the WDFW Molecular Genetics Lab typically uses the partial-Bayesian algorithms of Rannala and Mountain (1997) as employed in the software ONCOR (Anderson et al. 2008). Statistical power to distinguish reference populations depends on the genetic differences among those reference populations. Using microsatellites, Chinook
Page 105 of 119 generally genetically segregate by location and run-timing (Seeb et al. 2007). To our knowledge, the power of GSI to specifically identify individuals of Cowlitz River spring and fall Chinook ancestry has never been tested, so testing of the baseline would be an initial step of a lower Cowlitz fall Chinook tGMR project. However, in general and more specifically in other parts of Washington State, spring and fall Chinook are genetically distinct enough for sufficient power for individual population assignment using GSI, and this method is currently being used for tGMR purposes in the Nooksack River in Puget Sound (Seamons et al. unpublished).
Table 1. Number of genetic samples collected from Chinook salmon carcasses in the lower Cowlitz River by year. Year Samples (N) 2013 267 2014 341 2015 714 2016 506 Total 1,828
Second sampling event – smolt sampling
As with other WDFW MGL tGMR projects, for a lower Cowlitz River fall Chinook tGMR project the second sampling event would be sampling migrating juvenile Chinook the spring following spawning of the target population. Capture and sampling takes place on a screw trap located at river mile 23.2, one mile downstream of the Olequa Creek boat launch. The live box in the trap is checked daily and genetics of juvenile Chinook salmon outmigrants are sampled at a 1 in 10 rate. In 2015, the trap was operated between the months of May and December whereas, in 2016, the trap was operated for 12 consecutive months between January and December. To date, over 6,000 smolt samples have been collected from two outmigration years (Table 2).
Table 2. Number of genetic samples collected from juvenile Chinook salmon captured in the Cowlitz River smolt trap by year. Outmigration Year Samples (N) 2015 575 2016 >6,000 Page 106 of 119
Juvenile migrants from five possible non-target (i.e., immigrant) populations may be captured through smolt trapping: spring Chinook of any of the three stocks, fall Chinook from the population spawning upstream of Mayfield Dam, yearling migrants (non-target brood year), and hatchery juvenile migrants. Individuals belonging to any of these non-target populations must be identified and removed in order to meet the closed population assumption and produce an unbiased tGMR estimate.
Spring Chinook juvenile migrants will be identified using GSI as described above for adults in the first sampling event. However, because the fall Chinook spawning upstream of Mayfield Dam are genetically indistinguishable from lower Cowlitz fall Chinook, we cannot use GSI to identify these non-target individuals. Two alternative methods for excluding upper Cowlitz fall Chinook juveniles are available. First, we could sample and genotype every adult fall Chinook passed upstream. Parentage analysis could then be done to identify individual “immigrant” upper Cowlitz fall Chinook juveniles. However, this method is cost-prohibitive because of the cost of genotyping the large number of fish passed upstream each year (Table 3) and the additional effort to obtain fin tissue from every fish passed upstream. To date, genetic samples have not been collected from fall Chinook passed upstream of Mayfield Dam, so if we were going to use this method we would need to begin collecting those tissues in 2017.
Table 3. Fall Chinook salmon that are potential parents of "immigrant" juveniles in the second sample of the two-sample Petersen mark-recapture model. Potential parents include those released to spawn naturally in the Tilton River or the Upper Cowlitz River as well as fall Chinook salmon spawned in either the segregated or integrated hatchery fall Chinook programs.
Released Released to Upper Segregated Integrated
Year to Tilton River Cowlitz R. Hatchery Parents Hatchery Parents 2014 1,709 3,209 1,858 0 2015 5,392 4,214 1,926 0 2016 3,961* 11 ~1,800** 0
*as of December 2016 **expected to be similar to previous years
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Second, we could adjust the timing of the sampling at the smolt trap to avoid sampling juveniles produced by upper Cowlitz fall Chinook. Juvenile fall Chinook produced from spawners upstream of Mayfield Dam reach the lower Cowlitz by physical transport (upper Cowlitz and Cispus river production) or migration through the downstream collector at Mayfield Dam (Tilton River production). Physical transport from the upper Cowlitz and Cispus rivers begins in the month of April and operation of the downstream collector at Mayfield Dam begins in the month of April. Few fry are thought to navigate the dam system during the months of January to March when assisted passage does not occur. Data from 1.5 years of smolt trapping in the lower Cowlitz River couple with more than a decade of migration timing data from the Cowlitz Falls Fish Facility (upper Cowlitz and Cispus production) and Mayfield Dam downstream facility (Tilton River) support this notion and suggest that sampling prior to the month of April would reduce the probability of including an fall Chinook from the upper Cowlitz in the tGMR collection to negligible levels (Figure 1).
Figure 1. Timing of juvenile Chinook salmon outmigration past three trap sites in the Cowlitz River. Mayfield and Cowlitz Falls Fish Facility (CFFF) begin operation in the month of April. Downstream migration from the Upper Cowlitz, Cispus, and Tilton rivers prior to this date are considered to be negligible. Migration past the Cowlitz River Screw Trap (CRST) occurs in all
Page 108 of 119 months of the year. Migration in the months of January to March does not overlap with downstream migration from the Upper Cowlitz, Cispus, and Tilton rivers.
Yearling migrants, i.e., “immigrants” from non-target brood years, will be identified using the relationship of individual capture date and length at capture. Yearling migrants migrate fairly early in the migration season and at that time are much larger than the subyearling migrants and are thus easily identifiable. (Figure 2)
Figure 2. Length at outmigration for Chinook salmon captured in the Cowlitz River screw trap. Ages are inferred from this data.
Hatchery “immigrants” are hatchery-produced juvenile migrants that should not, but do have an intact adipose fin (i.e., missed clips or mis-clips). These could be identified by parentage assignment if all parents of hatchery Chinook released upstream of the smolt trap were genotyped. However, this method is not recommended due to the expense of genotyping the large number of hatchery broodstock (Table 3) and the expected low number of sampled unmarked hatchery-produced juvenile migrants. Instead, the capture number in the model would be adjusted based on the estimated number of genotyped hatchery-produced unmarked juvenile migrants. In order to estimate that number, we use the hatchery QAQC data used to generate marking rates and a count of the number of marked (adipose fin clipped) juvenile migrants caught in the smolt trap.
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Lower Cowlitz fall Chinook spawning downstream of the smolt trap are the fifth possible non-target population. If juveniles spawned downstream of the smolt trap swim upstream and are captured in the trap, but carcasses of fish spawning downstream of the smolt trap are not sampled then the presence of these juveniles in a smolt collection could result in a biased tGMR estimate. As with upper Cowlitz fall Chinook, fall Chinook spawned downstream of the smolt trap could not be identified using GSI, and no other method of identifying them has been identified. However, the number and percent of fish spawning downstream of the smolt trap is fairly small, an estimated 1% to 4%, so any bias, if it existed, would likely be small.
Identification of recaptures
Genotyping – We will use the statewide panel of 299 SNP markers for parentage analysis, which includes 190 of 192 markers developed for coastwide application (Warheit et al. 2014) plus additional markers developed for application in the Columbia River basin. The panel includes one mitochondrial DNA marker and one sex identification marker, both of which are not useful for parentage assignment and are dropped from parentage analysis.
Parentage Analysis – To assign parents (adult carcasses) to naturally-produced offspring
(migrating subyearling Chinook juveniles), we will use the likelihood algorithms implemented in the software COLONY (v2.0.6.1, Wang 2004; Wang 2012; Wang 2013; Wang and Santure
2009). COLONY requires knowledge of the sex of the parents. Sex of adult fish is typically determined in the field, but is also diagnosed genetically. When field sex ID disagrees with genetic sex ID, the genetic sex ID is used for parentage assignment tests. COLONY is run using the polygamy mating system, without inbreeding, with the probability of parent (mother or father) being in the sampled dataset equal to 0.05, a value derived from sample sizes and tGMR estimates from previous years. In order to evaluate convergence, we run COLONY three times for each dataset with different random number seeds using the ‘short run’ option, the combined pair-full likelihood method, ‘medium’ precision of the likelihood, with no allele frequency updating, and no sibship priors. Results of the three runs are compared and evaluated for convergence. If convergence is not reached with short runs, we re-run COLONY analysis with the medium run option. As recommended by the author of COLONY (COLONY user manual, J. Wang), convergence is achieved when run-to-run variation in results was “minimal”. We
Page 110 of 119 expect minimal variability in parentage assignment of carcasses. However, we anticipate much more variability in the number of inferred, unsampled parents generated through sibship analysis. Thus, we have defined minimal variation as less than 5% CV among the hypergeometric abundance estimates calculated from the three COLONY runs. If convergence is achieved with short runs, the first short run is used to generate final tGMR estimates.
Genetic stock identification – Individual assignment of members of collections of individuals suspected to be from multiple stocks are estimated by using a partial Bayesian procedure based on the likelihood of unknown-origin genotypes being derived from genetic baseline reference stocks/populations (Rannala and Mountain 1997) using the software ONCOR (Anderson et al. 2008) and decision criteria that ensure identifying immigrant stocks. The baseline consists of known stock collections from populations found in the lower Columbia River and throughout the species range in North America.
Power analysis
To estimate the number of adult and juvenile samples needed to meet the precision standards, we performed Monte Carlo resampling of simulated data with an adult population size of N = 4,000 calculating the CV for each of 1000 Monte Carlo samples. The number of adults found as carcasses and successfully genotyped is more variable than the juvenile sample sizes and depends greatly on environmental conditions. Therefore, one should choose a juvenile sample size that has a reasonable probability of successfully obtaining a CV of 15% or less with most possible adult sample sizes. The simulations showed that in order to have a high probability of obtaining a CV of less than 15%, 1,000 or more juveniles must be genotyped (Figure 3). Based on our experience performing tGMR in other river systems both in the lower Columbia River basin (Coweeman River) and in Puget Sound (several rivers) we aim for a juvenile offspring sample size for genotyping of 2,000. This allows for some reduction in sample size due to genotyping failure (typically only a handful of samples) and the removal of non-target juveniles (e.g., spring Chinook or hatchery-produced Chinook) while maintaining a large enough offspring sample size to have a reasonable probability of obtaining a tGMR estimate with a CV > 15% with a relatively broad range of carcass sample sizes.
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CV (%) 4.52 (10,000) 55-60
2.26 (5,000) 50-55 45-50 1.13 (2,500) 40- 45 0.90 (2,000) 35- 40 0.68 (1,500) 30- 35 0.45 (1,000) 25- 30 0.23 (500) 20- 25 0.05 (100) 15- 20 0.02 (50) 10- 12.50 10.00 7.50 6.88 6.25 5.63 5.00 4.38 3.75 3.13 2.50 1.88 1.25 15 (500) (400) (300) (275) (250) (225) (200) (175) (150) (125) (100) (75) (50) 5-10 0-5
Percent of adults sampled (sample size)
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Figure 3. The effect of adult and juvenile sample sizes on the CV of tGMR Lincoln-Petersen markrecapture abundance estimates assuming binomial sampling. Data were from 1,000x Monte Carlo resampling of simulated data of a population of N=4,000. The plotted data are the averages of the 1,000 Monte Carlo samples for each adult and juvenile sample size combination. Green colors denote average CVs of 15% or less. Red-orange colors denote average CVs > 15%.
Questions from Tacoma Power: • Please compare and contrast a fry vs. smolts GMR with regard to sample size and study design. o What is the impact of using different life stages on the estimate? o Do different parents contribute to different life histories and how would this impact the estimate?
As long as the parent and offspring collections are uncorrelated, there will be no bias in the tGMR abundance estimate regardless of the life history stage of offspring used. By uncorrelated, I mean that you are not over- or under-sampling the offspring of the parents that were sampled. The question then becomes “is one more or less likely to sample the offspring of parents sampled as carcasses with offspring of one life stage vs. another?” I would answer that by saying with careful thought about the experimental design one could easily avoid any problems. The smolt trap probably is very good at sampling randomly with respect to (successfully-spawning) parents. I can think of examples where with other sampling methods and other life stages this might not be true. For example, seining fry in only the same locations where carcasses were sampled. But, for example, I think we could design a fry seining sampling design that would minimize or eliminate any potential bias.
There is undoubtedly variation among parent-pairs as to what life history of offspring they produce. That variation is part genetic and part environmental. However, in my own experience, and from what I’ve seen in the literature, the variation is in proportions, i.e., some parent-pairs produce more or less age 1 migrants than others, but almost all parent-pairs produce both age 0 and age 1 migrants. Again, we could probably bias a tGMR estimate if we weren’t carefully thinking about the study design. For example, we might only sample in the coldest tributary that produces more age 1 migrants than any other location and then when we don’t use age 1 migrants in our design we bias the estimate. However, very few yearling smolts are produced by fall
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Chinook in the lower Columbia River tributaries, and even if there were more yearling migrants, with careful planning, we could easily avoid sampling pitfalls related to life history.
• The lower Fall Chinook and Tilton populations are mixed and in total are from 6 to 8 million. What are different methods to remove/account for the Tilton population?
There are at least three methods to remove/account for the Tilton population when using tGMR to estimate the abundance of fall Chinook salmon in the lower Cowlitz River. One method is to select juvenile outmigrants from the Cowlitz River Screw Trap during the period of time (January to March) that few juvenile fry are thought to be outmigrating from the Tilton River. A second method is to genotype all fall Chinook salmon passed upstream to spawn in the Tilton River and use parentage analysis to remove juvenile offspring from these parents. A third method is to use tGMR to estimate an abundance estimate for the Tilton and lower Cowlitz River together (this would require genetic sampling of parents released in to the Tilton) and then estimating the lower Cowlitz River portion by subtracting the number of adults known to be released into the Tilton River.
• Please compare the cost and accuracy of the current method and the GMR method.
The tGMR method provides an abundance estimate of superior quality to the current method. The tGMR abundance estimate has a known precision and its accuracy (bias) can be evaluated based on the estimator assumptions described above. In comparison, abundance estimates derived with the current method are of unknown bias and precision and therefore represent poor quality estimates in comparison to the tGMR method. The current method expands peak redd counts by an expansion factor developed for fixed wing aerial surveys using a carcass tagging mark-recapture study (Hymer 1994) that was subsequently modified for helicopter aerial surveys (WDFW, unpublished data). The justification for this subsequent modification does not appear to have any written record. Biological data collection from carcasses and aerial flights are needed under both methods (current, tGMR) in order to obtain age composition, hatchery- natural composition, and spatial distribution information needed for the analysis. Therefore, the
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GMR method will add genetic analysis as a cost to surveys conducted using the current method.
• Please describe the sensitivity of tGMR to estimate abundance if it is not possible to sample adult fall Chinook with equal distribution spatially or temporally. Is there way to test in a controlled environmental what the effects of under or over estimating these inputs might have on this method?
The effect of sampling adult fall Chinook biased with regard to space or time depends on the degree to which space and time are correlated with individual reproductive success. Space and time are not inputs to the model, so they cannot be tested as asked in the question. However, using simulated data, we have examined the sensitivity of the tGMR method to correlation in sampling and reproductive success. The tGMR method is sensitive to correlations of sampling bias (with regard to any trait measurable in the field including time and space) with individual reproductive success. This sensitivity is a consequence of the probability of capture in the second sampling event being a function of the individual reproductive success. Any correlation of the adult sampling and individual reproductive success violates Assumption 5 (identical, independent probability of capture) by correlating probabilities of capture in both sampling events. The degree of bias in the abundance estimate is a function of the correlation of the adult sampling and individual reproductive success. We must assume we meet Assumption 5 because that assumption is untestable with a two-sample tGMR model. We minimize the likelihood of violating this assumption by careful planning and execution of adult sampling design.
• You have described your estimates for precision using the tGMR method for abundance, but Tacoma values the accuracy of these estimates at least as highly as precision. Please estimate accuracy of using this method and characterize assumptions the appropriate assumptions.
The tGMR method is accurate as long as the assumptions of the model are met. Assumptions and our efforts to meet and test them are listed in the document above. The accuracy and precision of the tGMR method have been evaluated using simulated data
(see Figure 3).
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• Please characterize the impact that sample population mixing (or lack thereof) may have on ability to measure abundance accurately using the tGMR method relative to current method. o How accurate is each method (tGMR vs. redd expansion)? o How sensitive is the current method to the population mixing assumption and does that affect its benefits over the redd expansion method?
The different populations of Chinook that exist in the Cowlitz River to some degree mix on the spawning grounds and as juveniles. The mixing of these populations affects the tGMR estimate only if the “immigrant” populations (identified above) cannot be excluded from analysis. As described above, we believe we can meet the closedpopulation assumption by excluding all possible “immigrant” population through either genetic identification or by avoiding them during sampling.
• In the Snohomish River Chinook genetic mark-recapture study there were significant discrepancies in the redd based counts compared to the tGMR estimates (Skykomish River = 7160 tGMR vs. 3,063 redd based; Snoqualmie River = 1490 redd based vs. 839 tGMR) due to violations of assumptions of either method, or each method estimated a different set of adults. What is the probability of redd based estimates having more precision than that of tGMR estimates? Can you please describe methods to ensure that all assumptions are met?
Uncertainty of redd-count based abundance estimates is almost never estimated, so it is impossible to quantifiably answer your question. The precision of redd-count based abundance estimates is likely poor. Redd-count estimates rely on and are quite sensitive to redd life – the length of time a redd is visible – which is rarely estimated and instead is assumed without uncertainty. Typically, the same redd life value is used every year even though there is undoubtedly year-to-year variation (and week-to-week and dayto-day). Redd-count estimates assume that the sampling frame is known and properly sampled. Expansion for unsurveyed reaches requires additional assumptions, all of which add uncertainty. Redd-count estimates also rely on a fish-per-redd value, typically (i.e., almost exclusively by management agencies across the Pacific coast) 2.5 fish per redd. Fish per redd is never estimated or validated, it assumes the sex ratio never changes, and there is no agreement on whether or not 2.5 fish per redd is intended to include jacks. Fish per redd can be influenced by observer efficiency which likely varies among years, and may even vary over the course of a spawning season. Page 116 of 119
On the other hand, with a tGMR abundance estimate we generate defensible, mathematically and statistically supported estimates of abundance and uncertainty. As described above, we are reasonably certain we meet all assumptions. Only one assumption is untestable with the two-sample tGMR model. We use careful planning to maximize our chances of meeting that assumption. The Snohomish River Chinook tGMR project suffered from small sample sizes in some years. The chances of getting an estimate that is wildly different from the truth just by chance during sampling is much higher with small sample size. However, the additional uncertainty due to small sample size is reflected in the larger error bars generated by the model. Analyses with simulated data show that unbiased estimates are generated when assumptions are met. They also show that precision improves with increasing sample sizes and that acceptable levels of uncertainty are expected with what we think are achievable sample sizes for the Cowlitz River. Consider that redd-count based abundance estimates suffer from the same relationship of sample size to uncertainty, but no estimate of uncertainty is ever calculated.
Where we have tGMR estimated paired with redd- or carcass-count abundance estimates, they are correlated. Rawding et al. (2014) showed this in the Coweeman River. For several of our Puget Sound rivers we have multiple years of tGMR estimates paired with redd-count or carcass-count based abundance estimates. Redd-count and carcass-count based estimates are almost always smaller than tGMR estimates, but they are highly correlated (0.5 < r < 0.9; preliminary unpublished data).
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