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North Sea saithe assessment NSAC: Saithe Workshop March 2018

This assessment workshop discusses the data, model, and recommendations for the North Sea saithe stock. Topics include stock ID and recruitment data, CPUE indices, IBTS indices, catch and discard data, biological data, and the assessment model.

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North Sea saithe assessment NSAC: Saithe Workshop March 2018

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  1. North Sea saithe assessmentNSAC: Saithe Workshop March 2018

  2. 2016: Saithe Benchmark Under review during benchmark: • Data: • Saithe Stock ID and recruitment data for saithe • CPUE indices for saithe • IBTS indices of saithe • Catch & discard data in Intercatch • Biological data for saithe • Model • Assessment model: SAM

  3. Saithe Stock ID & Recruitment data for saithe

  4. Saithe Stock ID & Recruitment data for saithe • Tagging studies (1950s-1980s), genetic studies, and egg-lavae surveys • Showed mixing of NEA and NS stocks both within the NS and north of 62 °N • Mixing adds to uncertainty in the survey indices and assessment Management boundary Taken from Bjørke & Sætre (1994) Taken from Saha et al. (2015) Taken from i Homrum et al. (2013)

  5. CPUE indices for saithe • Previously used 3 age based CPUE indices (French, Norwegian, German) • Concern using same catch-at-age matrix twice in the assessment giving them too much weight to the CPUE tuning series • Scientific surveys had hardly any weight in the previous assessment, which was criticized by the external reviewers

  6. Combined trawl CPUE (‘standardized’ cpue) • Combined ”standardized ” CPUE index • Nation, Year, Quarter, kW group and Area • Include the Year parameter estimates in the model • The model is then fit to the fishable biomass (no age structure used) • Concern that a trend in the use of engine power may explain a trend in abundance over the same time period • Changes in mesh size preference or in fishing areas may have a similar effect • Potential hyperstability of CPUES

  7. IBTS indices of saithe • Q1 indices not appropriate – fish are moving in and out of the survey area unrelated to abundance • ICES-generated Q3 indices, but extended the age range: 3-8, 1992-present • Index is influenced by occasional large catches

  8. Raising of catch data in Intercatch • 2002-2014 catch data was revised • Discards were included (raised if missing and not 0)

  9. Raising of catch data in Intercatch • Catch for a given age changed with revision 2002-2014 • Not solely due to including discard infobut also resubmission of catch data Old assessment Final assessment

  10. Biological data for saithe • Stock weights = catch weights

  11. Biological data for saithe • New (constant) maturity ogive - small change in rate

  12. Assessment model Pre-benchmark: assessment model XSA • 4 indices were used: 3 cpue indices (French, German, Norwegian trawler fleets) and 1 survey index (IBTS Q3) • Stock weights = catch weights = landings weights • No discards • Age range: 3–10+ • Fbar was estimated for ages 3-6 SAM model as exploratory run since 2013 assessment year • Objective estimation of important variance parameters, leaving out the need for subjective ad-hoc adjustment numbers (Transparent, reproducible results) • Allows error in input data • Provides estimates of uncertainty in summary statistics

  13. SAM Assessment model • All new input data • Revised 2002-2014 catch • Discards • Stock weights • Maturity ogive • Q3 (3-8) indices • 1 standardized cpue index • Ages 3-10+ • Fbar: ages 4-7 (before age 3 -6, but age 3 not fully selected) • AR1 autocorrelation structure for Fs • SR-relationship: random walk • Configuration • Catchability of final ages in surveys not coupled • Fishing mortality variances – ages 6-10+ coupled • Log N variances – ages 6-10+ coupled • Modeled survey correlation structure • Includes correlation between ages within years in survey index • Better estimates of SSB and CIs

  14. Green lines: 2015 assessment (old SAM model) Black lines: 2016 assessment (new SAM model, new data) • New assessment more optimistic, especially in recent years • Surveys have more weight in the assessment • More influenced by increase in e.g. age 3 fish • This caused an increase in the advice

  15. Issues still to resolve External reviewers were not satisfied with: • Difference in catch at age 2002-2014 compared to previous years • Raising of discards • Norwegian discards need to be resolved 2017 assessment – issues with CPUE to index of biomass of fishable saithe • Vessel experience and fishing behavior contribute to variability – not captured in model • Conflicting signals betweenscientific survey and CPUE index contributes to assessment uncertainty IBTS Q3 index • Doesnot cover the whole stock distribution, but is considered generally representative • Uncertainty in indices Age 3 is not fully represented in this survey Index is influenced by occasional large catches Year effects can lead to overly pessimistic and overly optimisitic estimates in the final years

  16. Recruitment data for saithe Recommendations during benchmark • The feasibility of a shallow water, inshore survey for 0-group saithe should be investigated, with the intention of providing an 0-group index. • Whilst not recruitment related, WGEGGS and IBTSWG should be encouraged to continue the egg surveys in conjunction with the MIK sampling as this will provide an indication of magnitude and location of spawning of gadoids in the North Sea, especially in the northern areas. NS ecosystem survey (April/May) IBTS Q1 MIK-M

  17. Solutions: New surveys Recruitment survey? • A recruitment index (before age 3) should be initiated for this saithe stock, but budget constraints limit this Potential new data for the future: • Beginning a new joint acoustic survey with Germany: spawning (adult) saithe  More details in the next presentation • In 2019: Will phase in data from a new survey (acoustic survey, July, ages 3-8). • Are allowed to begin trialing it in exploratory assessment after 5 years.

  18. Acoustic summer survey • July, current format since 2014 • Combined with the HERAS survey (herring acoustic) • Not ideal, but best use of ship time with limited resources

  19. Acoustic summer survey

  20. Current research • Further genetics work into stock definition • Stock differentiation and connectivity • Egg and larval drift modelling – • First step in the recruitment puzzle: Where do the young end up? • How much of the stock remains south of 62 °N? • Spatial simulation model for the adults that takes into consideration population structure and connectivity

  21. Spatial simulation models • Need to incorporate spatial complexity • Connectivity • Annual straying rates based on genetic, tagging, or simulated migration • Spawning isolation • Isolation-by-distance approaches • Divide the population into smaller (or larger) units and model population dynamics and response to management (over- and under-fishing) • Migration • IBD format using age-structured populations • Populations are sources, sinks, or allow 2-way migration • Migration can take place at any stage • Can test management strategies, fishing pressure, and management unit configurations to test the optimal management procedure given observed genetic structure

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