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Photo: R. Ehlke Thomas Buehrens & Dan Rawding Estimates of salmon and steelhead harvest rates in Columbia River fisheries based on the recovery of PIT.

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Presentation on theme: "Photo: R. Ehlke Thomas Buehrens & Dan Rawding Estimates of salmon and steelhead harvest rates in Columbia River fisheries based on the recovery of PIT."— Presentation transcript:

1 Photo: R. Ehlke Thomas Buehrens & Dan Rawding Estimates of salmon and steelhead harvest rates in Columbia River fisheries based on the recovery of PIT tags Thomas Buehrens thomas.buehrens@dfw.wa.gov 2015 PIT Tag Workshop Skamania Lodge 1/27/2015

2 Photo: A. Stephenson Alan Byrne Doug Case Quinten Daugherty Roger Dick Jr. Robin Ehlke Michelle Groesbeck Lisa Harlan Rick Heitz Jay Hesse Joe Hymer Acknowledgements Ken Keller Kevleen Melcher Bret Morgan Bryant Spellman Steve VanderPloeg Ben Warren Jimmy Watts Bob Woodard Numerous field samplers! Columbia River TAC Funding: BPA Washington Columbia River Salmon and Steelhead Endorsement NOAA-Mitchell Act Thomas Buehrens thomas.buehrens@dfw.wa.gov 2015 PIT Tag Workshop Skamania Lodge 1/27/2015

3 Photo: A. Stephenson Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Photo: A. Stephenson Historic Harvest Estimation in the Columbia River Historic Harvest Estimation Stock assignment based on CWTs, timing, size Hatchery stocks substituted for wild stocks Harvest reporting groups not based on biological populations Need for new methods ESA listed wild populations constrain fisheries Population dynamic models require accurate harvest impacts

4 Project History WDFW, ODFW, PSMFC have historically sampled fisheries catches for biological data and CWT to make harvest estimates In 2010 BPA began funding WDFW to sample mainstem Columbia River fisheries for PIT tags Sampling program includes mainstem sport, commercial, and treaty fisheries New methods include Parentage Based Tagging (PBT), Genetic Stock ID, and PIT tags, but unlike genetic and Coded Wire Tag (CWT) programs, PIT tagging does not occur for harvest purposes Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Photo: A. Stephenson

5 Goal: Determine feasibility of using PIT tags to estimate harvest rates in Columbia R. fisheries Sample PIT tags in fisheries catch Expand PIT tag recoveries by species- and week-specific fishery sample rates Identify biological harvest reporting groups based on PIT tags Estimate harvest rates for reporting groups Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Photo: A. Stephenson

6 Fishery Areas Also sport fishery Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

7 Fisheries & Sampling Sampling Data: – Species, weight, CWT, PIT tags, gutted/intact, number sampled – Total catch reported separately Treaty – Above BON (Zone 6) Summer and Fall fisheries Only fish sold to commercial buyers No C&S or overbank sales Commercial – Below BON (Zones 1-5) Spring, Summer, Fall Sport – Below BON Feb-Oct Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Photo: A. Stephenson

8 PIT Harvest Reporting Groups Harvest rate based on susceptibility to harvest – Run timing  confirmed with graphical analysis – Body size  tested for ocean age/size selectivity – Migratory Behavior  not yet! Based on population structure – NOAA-designated hierarchical population structure We developed hierarchical groups based on timing and biology Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

9 PIT Tag Harvest Model Components Harvest Rate = Tagged Catch / Tagged Run-size Tagged Catch = # of harvested fish with PIT tags – Number of tags sampled – # of harvested fish sampled for PIT tags (week by species strata) – Total number of harvested fish (week by species strata) Tagged Run-size = # of fish passing BON with PIT tags Organized by harvest reporting groups Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

10 Catch and Run-size Depend on PIT Reader Efficiency SpeciesRate Ck0.986 Co0.979 Sth0.987 So0.992 Photo: A. Stephenson Run-size: Bonneville Dam Catch: Handheld Readers Two best types >> 99% for all species Robust to minor protocol violations Other readers infeasible or lower detection rates Allflex RS601-3 Destron Fearing FS2001F-ISO Not many fish escape detection at BON Allows for BON count of tags to be denominator of harvest rate with little error 2011 data shown but consistent among years Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

11 Example: Steelhead Harvest in the Zone 6 Fall Fishery Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

12 PIT tag Recoveries (2011): Steelhead Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

13 Cumulative Timing of Steelhead at BON: Support for reporting groups? Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

14 Cumulative Timing of Steelhead at BON: Support for reporting groups? Cumulative Passage at BON 5/16/17/18/19/110/1 11/1 Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

15 Cumulative Timing of Steelhead at BON: Support for reporting groups? Cumulative Passage at BON 10/15/16/17/18/19/110/1 11/15/16/17/18/19/110/1 11/1 Lower Columbia (LCR) Snake A-run (SNA) Mid-Col. River (MCR) Snake B-run (SNB) Upper- Col. River (UCR) Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

16 Harvest Rates of Steelhead in Zone 6 Fall Fishery Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

17 Can we use PIT tags to incorporate age structure into harvest estimates? Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

18 Ocean Age based on PIT tag travel days 0 1 0 1 2 3 Based on days between release and detection as adult at BON Initially used graphical analysis Confirmed by examining individual tag histories Currently collecting scales for further validation Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions 1 123 2 34

19 Age Selectivity Suggests Age selectivity in fisheries Net fisheries catch is older than run Mostly not managed beyond jack/adult Can cause evolutionary change Suggests need to move to adult-only or age- structured harvest estimates Species PIT Ocean ages at return TreatySportCommercial Coho0,1 NA Sockeye1,2,3 NA Sp. Chinook0,1,2,3,4 Su. Chinook0,1,2,3,4 Fa. Chinook0,1,2,3,4 Steelhead1,2,3 NA Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Size-selective Weakly Size-selective Not Size-selective

20 Summary WDFW successfully built on CWT sampling infrastructure to add other sampling (genetic, PIT tags, etc.). Detection efficiency of handheld and BON readers was very high permitting harvest estimation PIT tag run timing data support grouping by geography/population designation Tag recoveries often sufficient to make biologically-based ESU- level harvest estimates; improve upon historical methods PIT tags allowed assignment of ocean age and showed age selectivity in fisheries Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

21 Future Age-structured/adult only PIT tag harvest estimates Hierarchical models for population-specific estimates Increase sample sizes? – Incorporate PIT tag fishery recoveries in other Col. River sampling programs – Expand juvenile PIT tagging to cover poorly represented populations Work with IDFG and CRITFC to combine genetic, PIT, CWT methods Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

22 Thanks! Photo: R. Ehlke Thomas Buehrens thomas.buehrens@dfw.wa.gov 2015 PIT Tag Workshop Skamania Lodge 1/27/2015

23 Extra

24 Harvest Model Assumptions Harvest susceptibility of PIT tagged fish is representative of untagged fish Sampled catch is representative of entire catch Total catch reported by TAC accurate Sport Creel, Commercial Fish Tickets, Tribal Creel (estimates total of catch sold to buyers + C&S + over the bank) For treaty fisheries, assumes commercial fish sales are representative of non sampled catch Model currently treats all tags as adults Lots of precocious life histories for Chinook, Less of an issue for coho, steelhead, sockeye Photo: A. Stephenson Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

25 Photo: A. Stephenson Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Introduction Background/Need for new methods to estimate harvest Project goals Methods Harvest rate data and model Detection study Fishery sampling Reporting Groups Harvest Reporting Groups Results Sampling stats BON detection rate PIT Harvest Groups Harvest Rates Coho Mixture Model Sockeye Subtraction Method More work to be done

26 Detection Study (what % of tags are detected when tagged adults scanned?) Conducted an experiment at hatcheries under replicated field conditions Tested efficiency under a variety of conditions: – Reader type – Species – Size – Sex – Simulated sampling protocol violations Lots of replicates (100 fish * 4 samplers * 4 units per reader * protocols w/ + w/o deviations) Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Photo: A. Stephenson

27 A E D F C B Biomark Pocket ReaderPsion Teklogix data logger with RFID – LF module Biomark 24” square Destron Fearing FS2001F-ISO All Flex RS601-3 Biomark Flat Plate G “Sword” Reader (2 units) (Not Pictured) H Destron Fearing HPR (2 units) (Not Pictured) Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Photo: A. Stephenson

28 Detection Study Cont.: effect of protocol violations Best units (AF and DF) only Protocol = oval method, touching fish Protocol violations Single Swipe Not touching fish Not touching fish AND single swipe Photo: A. Stephenson Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

29 Detection Results >> 99% for all species with: Allflex RS601-3 and Destron Fearing FS2001F-ISO when protocols followed ~ 60% for Biomark pocket reader ~ 95% but highly variable for Destron HPR ~ 85% for “Sword” Reader Flat Plate, Psion, Square not suitable for field sampling (slow, or unwieldy) Photo: A. Stephenson Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

30 Results: both readers robust to minor violations! Likely due to detection distances >> fish body depth Photo: A. Stephenson Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

31 Sockeye Subtraction Method The proportion of the tagged population is estimated by The number of Wenatchee and Snake PIT tags at BON is summed by statistical week and divided by the proportion of each population that is PIT tagged and is estimated by The weekly estimate of Okanogan sockeye passing BON is estimated by The total number of Wenatchee and Snake River fish harvested is the harvest rate of these groups calculated from PIT tags times the estimated number of these fish passing BON The number of Okanogan sockeye salmon harvested in the Zone 6 fishery is calculated by subtracting the number of Wenatchee and Okanogan sockeye from the total Zone 6 catch Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

32 Sockeye Subtraction Method Allowed estimation of weekly run timing of 3 populations Demonstrated different run timing Could allow fisheries to target abundant Okanogan & Wenatchee stocks while minimizing impacts to listed Snake stock Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

33 Coho Mixture Model Use Pit tag detections of “early” stock as prior for bi-model mixture model of two normal distributions Estimate early and late proportions for total counts for at BON Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

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35 Sampling Rates SeasonWeek Chinook Coho 2010201120102011 Spring14 37% Spring15 64% Spring20 23% Spring21 50% Summer25 19% Summer26 47% Fall32 14% 10% Fall34 15% 21% Fall35 18%17% 24%14% Fall36 11% Fall39 26%14% 31% 12% Fall4023%17% 26% 23% Fall4128% 41% 33% Fall4220%34%21% 36% Fall43 33% 40% SeasonWeek ChinookCohoSockeyeSteelhead 20102011201020112010201120102011 Summer25 10% 0% 3% Summer26 15% 5% 2% Summer27 25% 8% 12% Summer28 16% 8% 5% Summer29 16% 0% 7% Summer30 18% 0% 18% Summer31 16% 7% 20% 1% 16% 12% Fall3219%11% 23% Fall338%11% 2% Fall3412%24% 27% Fall3518%6% 11% Fall36 11% 22%26%16% 14% Fall37 13%25%15%17% 10%14% Fall38 25%29%13%16% 23%22% Fall39 19% 14% 8% Fall4018%20%33% 12% 5%16% Fall4124% 9% 14% Fall4224% 28% 20% Fall43+44% 30% 12% MonthChinookSteelhead 28%6% 317%6% 415%5% 58%4% 6 10%11% 713% 19% 8 10%16% 9 9% 10% 104%12% Commercial Sport Treaty Only non-dressed fish Goal of 20% Bold are periods w > 10% of annual catch Red is <20% sample rate Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

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37 Photo: A. Stephenson Outline Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions Introduction Background/Need for new methods to estimate harvest Project goals Fishery sampling for PIT tags Detection Study Harvest rate data and model Harvest Reporting Groups Results Sampling stats BON detection rate PIT Harvest Groups Harvest Rates Coho Mixture Model Sockeye Subtraction Method More work to be done

38 Age Selectivity Suggests Age selectivity in fisheries Net fisheries catch is older than run Mostly not managed beyond jack/adult Can cause evolutionary change Preliminary: catch is unexpanded could be biased by age-specific run timing 2012 move to age- structured harvest estimates BONTreatySportCommercial SpeciesOcean AgeRun%Catch% % % Coho 025100NA 00 120039950100NA 9100 Sockeye 159500NA 21040896100NA 373600NA Sp. Chinook 05058000000 11827303151048621 230135012607332175 36541152541914 410000000 Su. Chinook 053224000000 1890403140000 26102714674100788 3189941900113 410000000 Fa. Chinook 04779220013 1203640121024013 21021203227120824 315973173612402368 411000 013 Steelhead 1842531139450NA 2714451761450NA 32110000NA Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

39 PIT tag Recoveries (2011): Coho Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

40 Coho Harvest Reporting Groups Cumulative Passage at BON Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

41 PIT tag Recoveries (2011): Sockeye Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

42 Sockeye Harvest Reporting Groups Cumulative Passage at BON Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

43 PIT tag Recoveries (2011): Chinook Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

44 CK “ESU” and “Rivers” reporting groups

45 Direct Acyclic Graph for Estimation of Harvest Rates #estimate number of fish based on tickets by period #estimate detection rate Of PIT tag readers #Estimate expanded PIT Tags by sampling period Estimate Harvest Rate by Group PIT Tag Harvest Model Thomas Buehrens thomas.buehrens@dfw.wa.gov Introduction Methods Results Conclusions

46 Fishery Periods


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