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Tools and data requirements for estimating impacts from mark-selective fisheries

Tools and data requirements for estimating impacts from mark-selective fisheries. Kris Ryding, Ph.D. Washington Department of Fish and Wildlife AFS CA/NV Chapter Meeting 1 April 2009. In the beginning…. Pre-fisheries. Fisheries. Escapement. Because all fish treated the same. Hatchery ER.

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Tools and data requirements for estimating impacts from mark-selective fisheries

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  1. Tools and data requirements for estimating impacts from mark-selective fisheries Kris Ryding, Ph.D. Washington Department of Fish and Wildlife AFS CA/NV Chapter Meeting 1 April 2009

  2. In the beginning… Pre-fisheries Fisheries Escapement

  3. Because all fish treated the same Hatchery ER Wild ER Fishery 1 Fishery 2 Fishery 3 Fishery 4 Escapement 10% 10% 2% 3% 75% < 10% ? < 10% ? < 2% ? < 3% ? > 75% ?

  4. Adipose Fin

  5. UN-MARKED MARKED

  6. Lets keep only marked fish... Pre MSF MSF (S) Escapement Un Marked Marked

  7. MSF(S) Escapement Pre MSF ? Un Marked ? Marked

  8. ? ? ? ? ? ? Hatchery M ER Hatchery U ER Wild ER MSF Fishery NSF Fishery MSF Fishery MSF Fishery Escapement 10% 10% 2% 3% 75%

  9. Hatchery M ER Hatchery U ER Wild ER MSF Fishery NSF Fishery MSF Fishery MSF Fishery Escapement 10% 10% 2% 3% 75% Indirect estimate Indirect estimate Indirect estimate

  10. Double Index Tagging - DIT • Both groups CWTs (hence “double” – M&T or U&T) • Fishery and/or cohort specific unmarked mortalities (USF) • Total impacts to unmarked - multiple MSF • Selective Fisheries Evaluation Committee (SFEC),

  11. &Tagged #Unmarked& CWT UREL = lREL MREL &Tagged # Marked & CWT Unmarked (U) Marked (M)

  12. MSF (S) Escapement Pre MSF ? Un Marked ? lESC lREL lSF Marked

  13. Unmarked mortalities (USF) • USF for a CWT group i Fishery specific or total

  14. Hatchery M ER Hatchery U ER Wild ER MSF Fishery NSF Fishery MSF Fishery MSF Fishery Escapement 10% 10% 2% 3% 75% 2% 2% 0.5% 0.5% 95% 2% 2% 0.5% 0.5% 95%

  15. Estimating USF Requires • Mark to unmark ratio:  (Rel, SFEsc) each group • MSF:expandedCWT recoveries • Size of fisheries increase – more information on MSF • Hook and release mortality: sfm (agreed to)

  16. Indirect Estimate • Technical Controversy: indirect estimates are less reliable than directly sampled estimates • Perspective: regulations on size limits, species all produce incidental mortalities that must be indirectly estimated but… MSF: marked fish, (DIT) provide information on unmarked mortalities

  17. MSF (S) Escapement Pre MSF ? Un Marked ? < lESC lREL < lSF1… Marked l changes after each MSFs, maybe even significantly…

  18. CWTs can be rare in small fisheries. • Few or no observed MSF CWTs. • A lot of little things potentially add up to a bigger impact • Assess total impact by analyzing proportions of released unmarked and marked fish returning to hatchery

  19. Pre MSF or Release MSF (S) Escapement ? Un Marked ? Marked

  20. Escapement Release Un Marked Marked

  21. pu pm = 0 = 0 Ho: Escapement Release Marked Un Marked

  22. Estimation of total impact • As the number or size of MSFs increase, expect more marked fish harvested than unmarked • Proportion of returning unmarked (U) should be higher than marked (M) vs.

  23. Total impact - perhaps the more important of the two metrics • Major assumptions • Differences in return rate due to MSF only • CWTs of Marked and Unmarked fish have equal probability of tag recovery (hatchery and spawning ground)

  24. Tools and Information • CWT and DIT groups – hatchery release • Marked CWT recoveries – fishery • Unmarked to mark ratio – fishery (or use release, escapement l) • Hook & rel. mortality – fishery • M & U release numbers – hatchery; total • M & U recovery numbers – hatchery; total

  25. What do you need to implement MSF? • CWT and/or DIT tagging programs • CWT recovery programs (ETD, fisheries, hatcheries and spawning grounds) • Indirect estimation method agreed to by all stakeholders (including sfm) • Monitoring plan • Cooperation among agencies

  26. Estimation of total impact Test for differences between pu and pm using z-statistic where

  27. Estimation of total impact Proportion of returning M and U CWT fish Smolt-to-adult return (SAR) rate of each component of DIT group Estimated expanded recoveries from hatchery and escapement sampling

  28. Estimates of ERU : lREL vs. lREC vs. lESC • Divide a Chinook population into unknown 2 sub-populations • Sub-pop 1: 95% of pop., subject only to MSF at variable rates ( > lREL ) • Sub-pop 2: 5% of pop., subject only to NSF or no fisheries (~ lREL ) • Under the assumptions of equal maturation, natural survival - compare absolute bias of ERU using the 3 estimates of l

  29. Bias in ERU: lREL vs. lREC vs. lESC

  30. Biases in ERU: • lREL: Overestimates • lESC: Underestimates • lREC: Underestimates – not as much as lESC (closest to true) • In all cases, % bias < 0.25 for ER about 15%

  31. Option 3: Double Otolith Tag (DOT) • Paired Non-selective fishery (NSF) • Unmark to mark ratio, l, estimated from a NSF occurring simultaneously with a MSF • Can use other mark groups, e.g., ad- and un-clipped fish that are also otolith marked The paired fishery could be a test fishery

  32. Comparison of Options: based on fishery sizes

  33. Comparison of methods: SIT, DIT and DOT • Question: Which method for which fishery? • Compare methods using Mean Squared Error (MSE) • MSE(USF) = Variance(USF) + Bias2 • Examine MSE for Options 1, 2, and 3 for different fishery sizes

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