csassccs

CSAS

SCCS

Canadian Science Advisory Secretariat

Secrétariat canadien de consultation scientifique

Research Document 2007/002

Document de recherche 2007/002

Not to be cited without permission of the authors *

Ne pas citer sans autorisation des auteurs *

Stock Assessment for British Columbia Herring in 2006 and Forecasts of the Potential Catch in 2007

Évaluation de 2006 des stocks de hareng de la Colombie-Britannique et prévisions des prises pour 2007

J. Schweigert1 and V.Haist2 1

Fisheries and Oceans Canada Science Branch Pacific Biological Station Nanaimo, B.C. V9T 6N7 2

Haist Consulting 1262 Marina Way Nanoose Bay, B.C. V9P 9C1

* This series documents the scientific basis for the evaluation of fisheries resources in Canada. As such, it addresses the issues of the day in the time frames required and the documents it contains are not intended as definitive statements on the subjects addressed but rather as progress reports on ongoing investigations.

* La présente série documente les bases scientifiques des évaluations des ressources halieutiques du Canada. Elle traite des problèmes courants selon les échéanciers dictés. Les documents qu’elle contient ne doivent pas être considérés comme des énoncés définitifs sur les sujets traités, mais plutôt comme des rapports d’étape sur les études en cours.

Research documents are produced in the official language in which they are provided to the Secretariat.

Les documents de recherche sont publiés dans la langue officielle utilisée dans le manuscrit envoyé au Secrétariat.

This document is available on the Internet at: Ce document est disponible sur l’Internet à: http://www.dfo-mpo.gc.ca/csas/ ISSN 1499-3848 (Printed / Imprimé) © Her Majesty the Queen in Right of Canada, 2007 © Sa Majesté la Reine du Chef du Canada, 2007

ABSTRACT Herring stock abundance in British Columbia waters was assessed for 2006 and forecasts were made for 2007 using the new age structured assessment model (HCAM) for the major stock assessment regions and for the minor stocks in Areas 2W and 27. All available biological data on total harvest, spawn deposition, and age and size composition of the spawning runs were used to determine current abundance levels. No significant problems were evident in the extent and comprehensiveness of the data collections. However, the spawn survey for the Queen Charlotte Islands was a surface rather than a dive survey due to funding constraints and fewer samples were aged in 2006 than in recent years due to limitations on the ageing laboratory. All available data were included in and summarized from an Access database. On a coastwide basis, herring abundance decreased moderately in 2006. The estimated pre-fishery biomass was 115,800 metric tonnes (t), which represents a 36% decrease over the 2005 stock level (180,900 t). The recruitment of the 2003-year class in 2006 was poor for Prince Rupert District, Central Coast, Strait of Georgia and west coast of Vancouver Island, but poor to average in the Queen Charlotte Islands. Abundance declined moderately in all areas except the Queen Charlotte Islands. The estimated harvestable surplus of BC herring in 2007 (20% of the 2007 forecast spawning stock biomass), based on forecast abundance to the five assessment regions, is 26,202 tonnes. As was the case in 2006, both the Queen Charlotte Islands and West Coast Vancouver Island stocks are below their respective Cutoff levels and can not support removals. RÉSUMÉ On a utilisé le nouveau modèle d’évaluation structuré par âge pour déterminer l’abondance aussi bien des stocks de hareng des principales régions d’évaluation de la Colombie-Britannique, que des petits stocks des zones 2W et 27 en 2006 et pour faire des prévisions des prises pour 2007. Toutes les données biologiques disponibles sur les prises totales, la ponte et la composition par âge et par taille des reproducteurs ont été utilisées pour déterminer le niveau d’abondance actuel. Aucun problème important n’était évident dans l’étendue et la représentativité des séries de données. Toutefois, le relevé des géniteurs a été effectué en surface plutôt qu’en plongée à cause des restrictions financières et moins d’échantillons ont été soumis à une détermination de l’âge en 2006 qu’au cours des années précédentes à cause de contraintes imposées sur le laboratoire concerné. Toutes les données ont été saisies dans une base de données Access, puis résumées. À l’échelle de la côte, l’abondance du hareng a diminué de façon modérée en 2006. L’estimation de la biomasse avant la pêche était de 115 800 tonnes métriques (t), ce qui représente une baisse de 36 % par rapport au stock de 2005 (180 900 t). Le recrutement de la classe d’âge de 2003 au sein de la population exploitable en 2006 était médiocre pour le district de Prince-Rupert, la Côte centrale, le détroit de Georgia et la côte ouest de l’île de Vancouver, mais il oscillait de médiocre à moyen dans les îles Reine-Charlotte. Pour 2007, l’estimation de l’excédent exploitable de hareng de la C.-B. (20 % de l’estimation de la biomasse génitrice de 2007), selon l’abondance prévue dans les cinq régions d’évaluation, se chiffre à 26 202 t. Comme en 2006, les stocks dans les îles ReineCharlotte et la côte ouest de l’île de Vancouver sont inférieurs à leur seuil d’exploitation et ne peuvent soutenir aucun retrait.

iii

INTRODUCTION The stock assessment presented in this document differs substantially from previous reports (eg. Schweigert 2004). During discussions at the Pelagics PSARC Subcommittee meeting in May 2006, it was recommended that the herring assessment and forecasts for 2007 be based on the Herring Catch Age Model (HCAM) presented at the meeting. A full description of the model is provided in a Canadian Science Advice (CSA) research document (Haist and Schweigert, 2006). Additional model development and analysis with this implementation have been conducted and the results are described. The stock assessment and forecasts presented here essentially follow the assessment framework described in Schweigert (2005). In this document, stock assessments are presented for the five major migratory stocks and for the two significant minor stocks.

STOCK CONSIDERATIONS The stock groupings used for the current assessments are identical to those used since 1993 (Fig. 1.). The Queen Charlotte Islands stock assessment region includes most of Statistical Area 2E, spanning from Cumshewa Inlet in the north to Louscoone Inlet in the south. The Prince Rupert District stock assessment region encompasses Statistical Areas 3 to 5. The Central Coast assessment region separates the major migratory stocks from the minor spawning populations in the mainland inlets. The Central Coast assessment region includes Statistical Area 7 plus Kitasu Bay in Area 6 and Kwakshua Channel in Area 8. The Strait of Georgia stock assessment region includes all of Statistical Areas 14 to 19, 28, 29 excluding section 293, and Deepwater Bay and Okisollo Channel in Area 13. The west coast of Vancouver Island assessment region encompasses Statistical Areas 23 to 25. The minor stocks include all of Area 27 and Area 2W from Langara Island south to but not including Louscoone Inlet. Haist and Rosenfeld (1988) outline the current geographical stock boundaries.

1

Figure 1. The five major British Columbia herring stock assessment regions: Prince Rupert District (PRD), Queen Charlotte Islands (QCI), Central Coast (CC), west coast Vancouver Island (WCVI), the Strait of Georgia (SOG) and minor stocks in Areas 2W and 27.

2

DATA BASE The primary data sources for the stock assessments are spawn survey data, commercial catch landing data, and age composition data from biological samples of commercial fishery, pre-fishery charter, and research catches. These data are available in an Access database for the period 1951 to 2006. This time span includes the reduction fishery period to 1968 and the subsequent roe fishery period that began in 1972. All major herring spawning beds except those in the QCI were surveyed in 2006 by SCUBA. Unforeseen resource limitations precluded a SCUBA survey in the QCI and the survey was conducted instead using a combination of snorkelling and surface survey techniques. A number of minor spawning beds outside the main assessment areas were also surveyed by SCUBA in 2006. Catch information is obtained from landing slips or monitoring of plant offload data. Historically, landing slip data were summed by fishery season (seasons run from July 1 to June 30). Beginning in the 1997/98 season, roe catch figures are based on verified plant offload weights, a result of the introduction of the individual vessel quota (‘pool fishery’) system for all fisheries except the Strait of Georgia and Prince Rupert gillnet fisheries which were open fisheries. Beginning in the 1998/99 season, verified plant offload weights are available for all food and roe fisheries coast-wide. The history of catches in the major assessment areas is shown Figure 2. In contrast to recent assessments, no catch was assumed for the SOK fishery as there is no basis for verifying the harvest removed from the population. Instead, the validated landed weight of SOK product was used to estimate the egg removal from the spawning grounds and these data were converted to tonnes of fish equivalents based on data provided in Shields et al. (1985). These estimates were then added to the estimated spawning biomass for each area over the course of the SOK fishery from 1975 to present. Age structure data are used in the assessment model. The information from catch samples is used for years when there were commercial fisheries. Pre-fishery charters began in 1975 and these samples are used in addition to samples taken from the catch, particularly in areas with no fisheries, or when catch samples are few in number or not representative of the entire catch. Additional data used in both models are annual estimates of the mean weight-at-age. During the 2005/06 season a total of 212 herring samples (41 roe, 7 food and bait, 150 test fishery and 14 research samples) were collected and processed compared to 274 in the previous year. Of the roe and test fishery samples, none were collected in non-assessment areas, 9 were taken in the Queen Charlotte Islands assessment area (another 5 from Area 2W), 30 in the Prince Rupert area, 63 in the Central Coast, 71 in the Strait of Georgia, and only 13 on the west coast of Vancouver Island none of which came from Area 27. The age composition estimates for each major assessment region for 1951-2006 are presented in Figure 3 and Appendix Table 1.11.7. The year of life convention for ageing adopted in the 1991 assessment is used. Fish which were previously named age 3 are now referred to as the 2+ age class.

3

60000 40000 20000 0

Total Catch (tonnes)

80000

Queen Charlotte Islands

1955

1960

1965

1970

1980

1985

1990

1995

2000

2005

1985

1990

1995

2000

2005

1985

1990

1995

2000

2005

1985

1990

1995

2000

2005

1985

1990

1995

2000

2005

80000 60000 40000 20000 0


1975

Prince Rupert District

1955

1960

1965

1970

1980

20000

40000

60000

80000

Central Coast

0


1975

1955

1960

1965

1970

1980

20000

40000

60000

80000

Strait of Georgia

0


1975

1955

1960

1965

1970

1980

80000 60000 40000 20000 0


1975

W.C. Vancouver Island

1955

1960

1965

1970

1975

1980

Figure 2. Estimated total catch from all fisheries except spawn-on-kelp for each assessment region from 1951-2006.

4

8 10 6 4 2 0

Proportion at Age

QCI

2000

1960

1970

1980

1990

2000

1960

1970

1980

1990

2000

1960

1970

1980

1990

2000

1960

1970

1980

1990

2000

2

4

6

8 10

1990

8 10 6 4 2 0

Proportion at Age

1980

CC

GS

0

2

4

6

8 10

1950 Proportion at Age

1970

PRD

1950

WCVI

0

2

4

6

8 10

1950 Proportion at Age

1960

0

Proportion at Age

1950

1950

. Figure 3. Age composition estimates for five major assessment regions from 1951-2006 from biological sampling. These data are used in the catch-age analysis.

5

GENERALIZED HERRING CATCH-AGE MODEL In this section we provide a brief overview of the generalized herring catch-age model (HCAM), including descriptions of the options for population and fishery dynamics and the likelihoods used in fitting to observations. The model is described in detail in Haist and Schweigert (2006). Model Dynamics The state, or current status of the populations, partitions the fish by characters that define their distinct status. The possible characters include: age class, sex, maturity (called availability to reflect their being available to fisheries), and stock. Changes in state, or transition processes include: recruitment, natural mortality, fishing mortality, and ageing. Time steps or fishing periods The HCAM structure allows for a variable number of time steps (periods) each year, where each time step may have an associated fishery and natural mortality. The HCAM implementation separates the annual herring catch into three categories: a winter fishery; a spawning-season seine fishery (SN); and a spawning-season gillnet fishery (GN). Selectivity/Availability Options The model structure allows the distinction of fish that are available to the fishery from those that are not. The separation into available and non-available fish, which is modelled as age-specific, occurs at the beginning of the year. The available fish are subject to both fishing and natural mortality while the unavailable fish are subject to natural morality only. A number of options are available for the parameterization of age-specific fishery selectivity and age-specific availability. These include: fixed at 1; age-based logistic functions; a size-based logistic function; and free-at-age. Deviations from the prescribed availability-at-age or selectivity-at-age can be estimated. For availability deviations this adds an additional parameter for each year and for selectivity deviations this adds an additional parameter for each fishery. The methods for including deviations are different for the alternative parameterizations of availability and selectivity (see Haist and Schweigert 2006, Appendix A). Fishery Dynamics and the Catch Equations The fishery dynamics can be modelled using either the instantaneous (Baranov) form of catch equations where fishing and natural mortality are simultaneous or a discrete form of catch equations where natural mortality occurs prior to fishing. Solution of the catch equations can be done analytically (using an iterative Newton-Raphson algorithm for the instantaneous form) or by estimating parameters that define fully-selected fishing mortality rates. In the first case the implied assumption is that there is no error in the catch data while the second case acknowledges error in the catch data. Natural Mortality A number of options representing different assumptions about natural mortality rates are available. These include: fixed or estimated values for the constant natural mortality rate; age-dependent natural mortality rates; annual deviations from an average natural mortality rate; and a time-series approach using a “random walk” (Gudmundsson 1994) to parameterize annual changes in natural mortality rates (described in Haist and Schweigert 2006, Appendix A). Stock-Recruitment Assumptions A Beverton-Holt type stock-recruitment relationship is implemented in HCAM, using the “steepness” parameterization (Mace and Doonan 1988, Francis 1992). Estimated parameters of the stock-recruitment relationship are: R0 , the average recruitment at the unfished equilibrium biomass level ( B0 ); steepness ( h ), the fraction of R0 that is expected at 20% of B0 ; and the variance of the residuals from the stock-recruitment relationship ( σ r ).

6

Initializing the Populations The populations can be initialized either by estimating parameters for the number of fish in each age-class in the first year of the analysis, or by assuming equilibrium conditions in the first year. Equilibrium conditions can be estimated for populations that are subject only to natural mortality prior to the first year or they can be estimated for populations that are subject to a constant exploitation rate and natural mortality prior to the first year. HCAM models a “plus” age-class, which accumulates all fish of the “plus” age and older. Ageing Errors Two options for estimating ageing errors are incorporated into HCAM. The first option estimates two vectors for ageing errors – these represent the probabilities at each age of under-ageing fish by one year and the probabilities at each age of over-ageing fish by one year. The second option is based on an ageing error model developed by Francis (2003). The basis of this model is the assumption that for each ring in the ageing structure there is a probability that the ring will not be counted and second a probability that two rings will be counted. Thus, the probability of ageing error increases with age and may be asymmetrical. Parameter Estimation HCAM is structured for Bayesian estimation, though by not specifying parameter priors maximum likelihood estimation can be done. HCAM uses the ADMB model package (Otter Research 2000). ADMB allows multi-phase estimation, where initially some parameters are held fixed while the minimization is carried out, then some of the fixed parameters are freed and the minimization carried out, etc. For Bayesian analyses, ADMB uses the MCMC algorithm (Gelman et al. 1995) to estimate the joint posterior probability densities. Posterior densities are based on MCMC chains of length 1 million in this analysis. Likelihoods For age composition data, HCAM has two likelihood options. These are the multinomial distribution and a robustnormal distribution (Fournier et al. 1990, Starr et al. 1999). For fitting the spawn index data, HCAM only models the lognormal distribution. Priors The priors implemented in HCAM include uniform, normal, and lognormal distributions (Haist and Schweigert 2006, Appendix A). Residuals To assess deviations from model assumptions we examine two types of residuals; Pearson residuals which express the residual relative to the variability of the observation and normalized residuals which express the residual on a standard normal scale (see Haist and Schweigert 2006, Appendix A for descriptions). For the normalized residuals we calculate two statistics; the standard deviation of the normalized residuals (SNDR) which has an expected value of 1, and a potentially more robust statistic, the median of the absolute residuals (MAR) which has an expected value of 0.67.

FORMULATION OF THE HCAM MODEL The herring catch-age analysis (HCAM) presented at the 2006 spring PSARC meeting (Haist and Schweigert 2006) combined features of the model currently used for herring assessments (Schweigert 2005) and an alternative developed for the objectives based fishery management initiative (OBFM) referred as the new age-structured model (NASM, Fu et al. 2004). The HCAM computer code is designed to be general and it can be run to mimic both the existing herring age-structure model (EASM) and the new age-structure model (NASM) as well as various combinations of these and others. The Pelagics Subcommittee selected the R13 HCAM formulation for future assessments because it combined features of: only minor retrospective patterns; no obvious patterns in model residuals; consistency between the assumed and empirical error structure; and model parsimony.

7

The suite of HCAM model runs presented by Haist and Schweigert (2006) was not comprehensive, and prior to conducting analyses for the current herring stock assessment some additional runs were compared to assess whether better formulations of the model were possible. This series of runs initially looked at simplifying the model assumptions (R15 and R16), then looked at some different structural assumptions (R17, R18, and R19), and finally introduced additional model complexity to deal with the retrospective patterns (R20). A description of the options included in the different runs is presented in Table 1. The runs were conducted using data through 2005, and a brief summary of results follows. Run R13 The run R13, considered the preferred run of those previously presented, is taken as the reference run against which the new runs are compared. Features of R13 are described in Haist and Schweigert (2006). Run R15 Run R15 differs from run R13 in that no ageing error is assumed. This reduces the number of parameters to be estimated by 2. For the GS and CC stocks the increase in the objective function value is small (Table 1), suggesting the additional parameters do little to improve the model fit. Intermediate increases in the objective function values were obtained for the WCVI and QCI stocks, while for the PRD stock there was actually an improvement in model fit when the ageing error terms were not estimated. This suggests the PRD R13 fit was a local minima. The PRD fit to age-composition data improves and the fit to spawn index data degrades for the R15 run (see the standard deviation of normalized residuals statistics in Table 2). Overall, the assumption of ageing errors does not appear to be warranted, given no major improvements in model fits for the 5 stocks. Run R16 Run R16 differs from run R15 in that natural mortality is assumed to be constant with age. This reduces the number of parameters to be estimated by 1. The increase in the objective function value is small (or non-existent) for 3 of the 5 stocks, with only the WCVI and CC stocks showing somewhat better fits when age-dependent natural morality is assumed. We consider the simpler model (R16) preferable over the more complex model (R15). Run R17 The next set of model runs incorporates a substantial change in structural assumptions with the population dynamics modelled by the “availability” formulation, which assumes that all mature (i.e. available) fish are equally selected by the seine fisheries. The availability formulation is consistent with a fishery that is non-selective for fish on the spawning grounds. This set of runs, R17, does not change the number of parameters that are estimated. For 3 of the 5 herring stocks (GS, CC, and PRD) there is considerable improvement in model fit with the “availability” parameterization (Table 2). For the WCVI stock the selectivity parameterization is only slightly better than the availability parameterization and for the QCI stock the selectivity parameterization clearly produces a better fit. The autocorrelation in the spawn index residuals is reduced with the availability parameterization for all stocks but QCI. Overall, the availability formulation of the population dynamics appears to provide a more consistent fit to the herring data. Run R18 The set of runs R18 is the same as the set R17 except that the populations are initialized in 1951 and not assumed to be at equilibrium in that year. The previous runs initialized the populations in 1943, assumed initial equilibrium conditions, and assumed no catch prior to 1951. The revised formulation is more consistent with what we know about the fisheries and population dynamics (fisheries occurred prior to 1951, and the populations show large fluctuations independent of fisheries). The set of runs R18 has the same number of parameters as the set R17, and provides slight improvements in model fits for 4 of the 5 stocks (Table 2). This is clearly the preferred parameterization. Run R19 The R19 set of runs introduces another substantial change to the population dynamics. For this run we remove the inter-annual variation in natural mortality parameters and include annual variation in the availability parameters (with standard deviation of 0.25). The total number of parameters does not change from the R18 runs.

8

This change in model assumptions results in substantial improvement in model fits for all 5 stocks (Table 2). The improvements primarily result from better fits to the age-composition data (see age-composition summary statistics in Table 2). Based on model fits, this would appear to be a preferred model formulation. A retrospective analysis was conducted using the R19 model formulation and retrospective years from 1996 through 2003. Results from these retrospective runs are compared with those from R13 and R18 retrospective analyses in Table 3. Overall, the results are similar for the R13 and R18 analyses, with a mean absolute change in spawning biomass estimates of 14.1% for the R13 runs and 13.5% for the R18 runs. However, the retrospective pattern is substantially worse for the R19 runs with a mean absolute error of 34.6%. For virtually all stocks and retrospective years there is a negative bias in the initial estimates of spawning biomass (Table 3). Therefore, although the R19 model formulation is superior in terms of data fits, it is unacceptable in terms of the retrospective pattern. Run R20 For the set of runs R20 we maintain the structure of R19 but re-introduce the annual deviations in natural mortality rates. The availability deviations evaluated in R19 are maintained because they significantly improved the model fits. The annual deviations in natural mortality (random walk parameterization with a standard deviation of 0.25) are included to see if this will improve the retrospective patterns. The retrospective pattern is improved for the R20 run (Table 3), with a mean absolute change in spawning biomass estimates of 14.3%. This model formulation is used as the base case for the 2006 herring stock assessment. Three additional sets of runs, using the R20 model formulation but with a different sequence of phasing in parameter estimation, were conducted to determine if there were problems with attaining local minima solutions. In all cases the same minima resulted, suggesting this model formulation does not have substantial local minima problems.

9

Table 1. Description of the options included in various runs of the HCAM model. See Haist and Schweigert (2006) for a more detailed description. Run Run Run Run Run Run Run Run Run Run Run Run Run Run Run Run Run 1 2 3 4 5 6 7 8 9 10 11 12 13 13 15 16 17 R0-BH Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y diR Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Steepness Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Avg M Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y AgeY Y Y Y Y Y Y Y dependM Annual M Y Y Y Y Y Y Y Y Y devs Recruitment Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Variance const const const const const const const const const const const const const const const const const

Selectivity Selectivity devs Availability ogive Q Ageing error Age of +group Age-comp proc error Annual variation in availability

Y-7

Y-7

Y-7

Y-7

Y-7

Y-7

Y-7

Y-7

Y-7 Y

Y-7

Y-7

Y-7

Y-7

Run 19 Y Y Y Y

Y

Run 20 Y Y Y Y

Y

Y-2

Y const 1951 Y-2

Y const 1951 Y-2

Y const 1951 Y-2

Y

Y

Y

Y

Y-4

Y-2

Y-1

Y– 2 Y-1

Y-1

Y-1

Y-1 Y

Y-1 Y

Y-1 Y

Y-1 Y

Y-1 Y

Y-2 Y

Y-1 Y

Y-2 Y

Y-1 Y

Y-1 Y

Y-1

Y-1

Y-1

Y-1

Y-1

Y-1

10

10

10

10

10

7

9

9

9

9

9

9

9

9

9

9

9

9

9

9

.003

.003

.003

.003

.003

.003

.003

.003

.003

.003

.003

.003

.009

.009

.009

.009

.009

.009

.009

.009

Y

Y

10

Y-7 Y

Run 18 Y Y Y Y

Table 2. Summary statistics for the HCAM series of model runs (R3, R15-R20) for the five herring stocks. Statistics include the objective function value (F), the standard deviation of normalized residuals (SDNR), the median absolute normalized residual (MAR), the autocorrelation (AC) in the spawn index residuals, and the number of parameters estimated in the minimization (NVAR). The results are from analyses using data through 2005. The run R20* uses data through 2006. Stock

Statistic

R13

R15

R16

R17

R18

R19

R20

R20*

GS WCVI CC PRD QCI

F F F F F

404.3 389.0 460.9 892.2 606.3

408.4 398.1 462.4 890.1 611.5

408.4 406.2 470.3 890.2 612.0

381.8 408.9 455.9 832.7 622.1

381.4 406.1 452.7 829.1 624.0

252.2 333.9 279.4 572.7 441.7

233.6 286.7 269.6 557.0 408.6

272.0 284.5 242.3 554.9 350.6

0.98 0.55 1.24 0.58 1.20 0.60 1.90 0.92 2.48 0.76

0.99 0.59 1.28 0.59 1.20 0.62 1.69 0.89 3.27 0.79

0.99 0.59 1.32 0.60 1.23 0.64 1.69 0.90 3.40 0.79

0.96 0.55 1.32 0.58 1.21 0.57 1.68 0.87 2.18 0.77

0.96 0.52 1.31 0.58 1.21 0.57 1.68 0.87 2.83 0.76

0.77 0.44 1.14 0.57 0.94 0.50 1.30 0.74 1.35 0.72

0.78 0.45 1.14 0.55 0.93 0.49 1.29 0.72 1.41 0.70

1.43 0.46 1.14 0.56 0.85 0.50 1.30 0.70 1.40 0.67

0.95 0.64 0.98 0.60 1.16 0.72 1.15 0.45 1.37 0.72

0.97 0.67 1.00 0.60 1.16 0.74 1.43 0.72 1.36 0.77

0.97 0.67 0.93 0.54 1.18 0.79 1.44 0.72 1.36 0.74

0.92 0.60 0.84 0.57 1.08 0.64 1.04 0.57 1.54 0.81

0.93 0.54 0.85 0.57 1.08 0.61 1.05 0.60 1.64 0.94

0.82 0.52 1.12 0.74 1.09 0.75 1.27 0.65 1.33 0.91

0.78 0.51 0.89 0.57 0.93 0.57 1.19 0.60 1.12 0.66

0.79 0.50 0.87 0.43 0.97 0.65 1.20 0.79 1.10 0.62

AC AC AC AC AC

0.25 0.46 0.31 0.08 0.01

0.26 0.45 0.31 0.38 0.01

0.26 0.38 0.26 0.38 0.00

0.19 0.14 -0.06 -0.01 0.21

0.17 0.15 -0.07 0.00 0.24

0.38 0.31 0.27 -0.01 -0.10

0.38 0.09 0.12 -0.12 -0.21

0.38 0.09 0.05 -0.11 -0.21

NVAR

132

130

129

129

129

129

184

186

Age composition GS SDNR MAR WCVI SDNR MAR CC SDNR MAR PRD SDNR MAR QCI SDNR MAR Spawn Data GS SDNR MAR WCVI SDNR MAR CC SDNR MAR PRD SDNR MAR QCI SDNR MAR GS WCVI CC PRD QCI

11

Table 3. Summary statistics for retrospective changes in stock biomass estimates from the HCAM model runs for the five herring stocks.

100 ( Byy − By2005 ) By2005

Mean Mean absolute 17.1 17.1 -3.8 12.4 0.7 7.0 14.2 18.1 -6.4 16.2 4.3 14.1

Run R13

Stock GS WCVI CC PRD QCI Mean

1996 25.3 9.2 -11.0 18.2 -4.5

1997 8.4 -1.6 -1.2 29.6 19.7

1998 10.3 -26.3 14.7 36.0 -1.0

1999 11.0 -21.6 15.8 17.3 -8.4

2000 28.5 -6.4 0.4 10.8 -2.8

2001 25.1 13.0 -10.6 -15.6 -70.3

2002 15.5 12.1 -0.5 12.1 19.4

2003 12.5 -8.9 -1.9 4.8 -3.4

R18

GS WCVI CC PRD QCI Mean

8.3 -13.1 -5.5 -0.8 -18.5 -5.9

8.5 18.1 5.5 13.2 22.1 13.5

0.8 1.0 -7.5 4.8 -2.1

1.5 -22.4 -11.5 8.4 3.3

11.5 -46.4 -6.6 15.9 -44.6

8.7 -31.5 -1.7 8.4 -30.0

26.0 0.0 -5.5 12.2 -6.8

6.5 14.0 -8.1 -27.6 -64.2

12.5 4.7 -3.2 -13.4 11.1

-0.8 -24.4 0.0 -15.0 -14.8

R19


-8.2 -61.7 -21.5 -33.6 -46.6 -34.3

9.5 61.7 21.5 33.6 46.6 34.6

-22.2 -35.1 -6.2 -26.7 -22.7

-17.9 -40.6 -13.7 -33.4 -4.5

-3.3 -88.3 -27.6 -11.2 -34.3

-5.5 -86.1 -25.9 -25.8 -76.3

5.4 -80.0 -19.6 -28.2 -65.0

-8.2 -46.4 -30.6 -55.6 -108.0

-4.1 -43.8 -26.8 -57.2 -25.1

-9.3 -73.2 -21.9 -30.6 -37.0

R20


-11.7 -4.0 -10.8 -12.3 5.6 -6.6

14.4 13.5 10.8 17.2 15.5 14.3

-5.3 -5.9 -5.4 -8.3 18.1

-0.8 3.4 -13.1 -3.9 13.5

9.4 -20.0 -22.3 19.6 10.5

-14.9 -7.2 -12.3 -3.9 -19.0

1.7 -1.1 -4.8 -1.8 9.6

-31.1 20.8 -13.2 -48.7 -17.8

-19.1 13.9 -3.6 -33.4 32.6

-33.2 -35.8 -11.9 -18.0 -2.7

12

STOCK TRENDS AND ABUNDANCE FORECASTS Estimates of pre-fishery spawning stock biomass over the period 1951 to 2006 from the HCAM and EASM model used in the 2006 assessment are presented in Figures 4 and 5 for the five major coastal regions. Overall, there is reasonably good agreement between the two models with some notable exceptions. In the Central Coast the HCAM implementation suggests a much stronger 1977 year-class than the EASM model resulting in higher biomass estimates for the early 1980s. Subsequently, estimates are similar although HCAM estimates are slightly higher over the past decade. HCAM estimates for the Strait of Georgia and west coast of Vancouver Island are also substantially higher than EASM estimates since 1980. In particular, the 1977 year-class appears much larger than previously estimated. However, both models indicate similar estimates of current abundance. Estimates of the spawn index, spawning biomass and pre-fishery biomass determined by the HCAM implementation are presented in Figures 6 and 7 for the northern and southern migratory herring stocks. All stocks except the QCI suggest a dramatic decline in abundance in 2006 with all stocks except the Strait of Georgia estimated to be near or below the Cutoff level. Residual and Retrospective Analysis An examination of residuals provides the basis for assessing the fit of the model to the available data. The model estimate of the population egg production can be compared to the observed egg deposition and residuals reviewed for lack of model fit. The results of this comparison are shown in Figures 8 and 9 for the five major stocks. It is evident that the residuals have decreased over time in all areas since the inception of diving surveys in 1988. The standardized residuals presented here differ from those in previous assessments but are in the expected range of variation. The residuals for the SG and WCVI suggest some cyclic variation that is not currently captured in the model formulation. The residuals from the catch-age data are presented in two ways. First, the normalized residuals from the agecomposition fit are presented for the three fishing periods over time for the five major stocks in Figures 10 to 14. These residuals are substantially improved relative to recent assessments. A few large residuals remain but there are no clear patterns or trends in residuals evident over time or age in any area. The underlying data resulting in the largest residuals will be reevaluated and may be removed for future assessments. The normalized residuals are also presented as a function of age averaged over years in Figure 15. Overall, there is very good agreement between the observed and estimated age-composition with few observations falling outside the 10 and 90% quantiles. The estimates of natural and fishing mortality over the time period from 1951-2006 are presented in Figure 16. The average natural mortality rate estimates range between 0.55 and 0.93 with the highest levels in the QCI and WCVI. All stocks except the Strait of Georgia indicate an increasing trend in natural mortality since the early 1990s with the most marked effect in the WCVI stock. All stocks show a peak in natural mortality during the stock collapse of the late 1960s. Fishing mortality rates have decreased significantly in all stocks following the high levels during the reduction period and the subsequent collapse. Fishing mortality rates have been low and stable in all stocks since the early 1980s. A retrospective analysis for the HCAM model version R20 is presented for each of the major herring stocks in Figures 17. The plots show the stock trajectory determined for each year since 1996 demonstrating the effect of additional data on model performance relative to the estimates from the stock trajectory in the current year. The 95% confidence bands from the posterior distribution from the Bayesian analysis are also shown. In general, the retrospective patterns are very stable for all stocks with some minor exceptions for the Strait of Georgia since the 1970s. The retrospective patterns are much improved from recent assessments and suggest consistency in the interpretation of the data over time. Trace plots from the sub-sampling of the MCMC posterior distribution for estimated 2006 spawning stock biomass are presented in Figure 18. The plots show no evidence of trends over the course of the analysis. A total of 2000 samples were retained over the course of the 1 million simulations.

13

60


40 30 20 0

10

Spawning Biomass

50

HCAM SB EASM SB

1950

1960

1970

1980

1990

2000

2010


40 20 0

Spawning Biomass

60

HCAM SB EASM SB

1950

1960

1970

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1990

2000

2010

80

Central Coast

40 0

20

Spawning Biomass

60

HCAM SB EASM SB

1950

1960

1970

1980

1990

2000

2010

Figure 4. Comparison of HCAM and EASM estimates of spawning biomass for northern herring stocks for the period 19512006.

14

120

Strait of Georgia

80 60 0

20

40

Pre-fishery Biomass

100

HCAM SB EASM SB

1950

1960

1970

1980

1990

2000

2010

140


80 60 0

20

40

Pre-fishery Biomass

100

120

HCAM SB EASM SB

1950

1960

1970

1980

1990

2000

Figure 5. Comparison of HCAM and EASM estimates of spawning biomass for southern herring stocks for the period 19512006.

15


60 40 0

20

Pre-fishery Biomass

80

Spawn Index Spawning Biomass Pre-Fishery Biomass

1950

1960

1970

1980

1990

2000

2010

100


60 40 0

20

Pre-fishery Biomass

80


1950

1960

1970

1980

1990

2000

2010

80

Central Coast

60 40 20 0

Pre-fishery Biomass


1950

1960

1970

1980

1990

2000

2010

Figure 6. Estimates of pre-fishery spawning stock biomass (tonnes x 1000) from age-structured model (HCAM) analyses for northern B.C. herring stock assessment regions, 1951-2006. Horizontal line indicates the Cutoff level.

16

50

100


0

Pre-fishery Biomass

150

Strait of Georgia

1950

1960

1970

1980

1990

2000

2010

140


80 60 0

20

40

Pre-fishery Biomass

100

120


1950

1960

1970

1980

1990

2000

Figure 7. Estimates of pre-fishery spawning stock biomass (tonnes x 1000) from age-structured model (HCAM) analyses for southern B.C. herring stock assessment regions, 1951-2006. Horizontal line indicates the Cutoff level.

17


1 -1

0

Residual

10 9 8 6

-2

7

ln(Model Spawn)

11

2

12


6

7

8

9

10

11

12

1950

1960

1970

1980

1990

2000

2010

2000

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2010

ln(Obs Spawn)

Prince Rupert

1 -1

0

Residual

10 9 8 6

-2

7

ln(Model Spawn)

11

2

12

Prince Rupert

6

7

8

9

10

11

12

1950

1960

1970

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1990

ln(Obs Spawn)

Central Coast

1 -1

0

Residual

10 9 7

-2

8

ln(Model Spawn)

11

2

12

Central Coast

7

8

9

10

11

12

1950

1960

1970

1980

1990

ln(Obs Spawn)

Figure 8. The residuals from the observed spawn - true spawn relationship for the northern assessment regions for the period 1951-2006. The arrow indicates the most recent data point.

18

Strait of Georgia

8

-2

9

-1

0

Residual

10

ln(Model Spawn)

1

11

2

12

Strait of Georgia

8

9

10

11

12

1950 1960 1970 1980 1990 2000 2010

ln(Obs Spawn)

W.C. Vancouver Is.

0

Residual

10 7

-2

8

-1

9

ln(Model Spawn)

1

11

2

12

W.C. Vancouver Is.

7

8

9

10

11

12

1950 1960 1970 1980 1990 2000 2010

ln(Obs Spawn) Figure 9. The residuals from the observed spawn - true spawn relationship for the southern assessment regions for the period 1951-2006. The arrow indicates the most recent data point.

19

Seine - Fall

6 2

4

Age

8

10


1960

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

Seine - Roe

6 2

4

Age

8

10

1950

1960

Gillnet - Roe

6 2

4

Age

8

10

1950

1950

1960

Figure 10. Residuals from the age-structured model fit to the catch-at-age data by year and fishing period for the Queen Charlotte Islands, 1951-2006. Filled circles are positive residuals and open circles are negative residuals.

20

Seine - Fall

6 2

4

Age

8

10


1960

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

Seine - Roe

6 2

4

Age

8

10

1950

1960

Gillnet - Roe

6 2

4

Age

8

10

1950

1950

1960

Figure 11. Residuals from the age-structured model fit to the catch-at-age data by year and fishing period for the Prince Rupert District for 1951-2006. Filled circles are positive residuals and open circles are negative residuals.

21

Seine - Fall

6 2

4

Age

8

10

Central Coast

1960

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

Seine - Roe

6 2

4

Age

8

10

1950

1960

Gillnet - Roe

6 2

4

Age

8

10

1950

1950

1960

Figure 12. Residuals from the age-structured model fit to the catch-at-age data by year and fishing period for the Central Coast for 1951-2006. Filled circles indicate positive residuals and open circles are negative residuals.

22

Seine - Fall

6 2

4

Age

8

10

Strait of Georgia

1960

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

Seine - Roe

6 2

4

Age

8

10

1950

1960

Gillnet - Roe

6 2

4

Age

8

10

1950

1950

1960

Figure 13. Residuals from the age-structured model fit to the catch-at-age data by year and fishing period for the Strait of Georgia for 1951-2006. Filled circles indicate positive residuals and open circles are negative residuals.

23

Seine - Fall

6 2

4

Age

8

10

W.C. Vancouver Is.

1960

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

1970

1980

1990

2000

2010

Seine - Roe

6 2

4

Age

8

10

1950

1960

Gillnet - Roe

6 2

4

Age

8

10

1950

1950

1960

Figure 14. Residuals from the age-structured model fit to the catch-at-age data by year and fishing period for the west coast of Vancouver Island for 1951-2006. Filled circles represent positive residuals and open circles are negative residuals.

24

Roe-SN

Roe-GN

-1 -1 1 2 3 -3 -1 1 2 3 -3 1 2 3 -3 -3

-1

WCVI

-1

GS

Normalized Residual CC

PRD

1 2 3 -3

QCI

1 2 3

Winter

2

4

6

8

10

2

4

6

8

10

2

4

6

8

10

Age class Figure 15. Quantile plots of normalized residuals from age composition fits for the R20 HCAM model, by fishery and stock. The shaded boxes show the inter-quartile range (with the median shown by the solid bar) and the whiskers show the 10th and 90th quantiles. The horizontal lines indicate the expected values for the 10th, 25th, 50th, 75th, and 90th quantiles.

25

M F

PRD

0.0

0.5

1.0

1.5

CC

1.2

Instantaneous Mortality

0.0

0.4

0.8

1.2

0.0

1.0

2.0

QCI

WCVI

0.0

0.5

1.0

1.5 0.0

0.4

0.8

SG

1950

1960

1970

1980

1990

2000

Figure 16. Estimates of annual instantaneous natural (M) and fishing (F) mortality for major B.C. herring stocks from 19512006.

26

80 0

20

40

60

QCI

120 0 150 0 20 40 60 80

CC

SG

0

50

100

Spawning stock biomass

20

40

60

PRD

0

50

100

150

WCVI

1950

1960

1970

1980

1990

2000

Figure 17. Estimates of spawning stock biomass from retrospective analyses (1996-2006, light coloured lines) and from marginal posterior estimates (using data through 2006, 5th and 95th percentiles of the distribution are shown as heavy lines). Results are from analyses using the R20 model parameterization.

27

QCI-2006 18000 16000 14000 12000 10000 8000 6000 4000 2000 0 0

200

400

600

800

1000

1200

1400

1600

1800

2000

1200

1400

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1800

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1200

1400

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PRD-2006 40000 35000 30000 25000 20000 15000 10000 5000 0 0

200

400

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1000

CC-2006 60000 50000 40000 30000 20000 10000 0 0

200

400

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1000

28

SG-2006 160000 140000 120000 100000 80000 60000 40000 20000 0 0

200

400

600

800

1000

1200

1400

1600

1800

2000

1200

1400

1600

1800

2000

WCVI-2006 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 0

200

400

600

800

1000

Figure 18. Trace plots from the MCMC analysis showing the sub-samples of estimated spawning biomass in 2006 for the five assessment regions.

29

Stock Productivity and Unfished Biomass The productivity of a stock is directly related to the estimated steepness of the stock recruitment function at the origin. In the current implementation of the HCAM model in the Bayesian framework, an ad hoc normal prior was assumed for the steepness parameter in fitting the available data. The resulting distribution of the steepness parameter from the posterior distribution is plotted with the prior in Figure 19. Interestingly, the empirical estimates of the steepness are comparable to estimates for herring-like species found recently by Myers et al. (2002). However, further investigation with other priors should be conducted to evaluate this result. The variance of the residuals from the stock-recruitment relationship are plotted in Figure 20 together with the assumed prior. The figures indicate good agreement between the prior and posterior distributions. The posteriors for the three northern stocks suggest recruitment variation tends to be slightly greater than assumed by the prior. For the two southern stocks the recruitment variation assumed for the prior matches the posterior more closely. The posterior distribution of the estimate of unfished biomass (B0) is presented in Figure 21. The estimated unfished biomass is smallest for the QCI stock with estimates considerably lower than determined previously. The estimates for the PRD and CC stocks are similar followed by the WCVI and SG. The variation around the estimate of unfished biomass is similar for the latter four stocks although the SG and WCVI suggest the greatest variability. Table 4 presents the estimated 5, 25, 50, 75, and 95th percentiles of the posterior distribution for the estimated unfished biomass. Assuming that the 50th percentile provides the best estimate of unfished biomass it is possible estimate the potential Cutoff values as 25% of the B0. The estimates are very similar to the current values with the exception of the QCI stock which would have a substantially lower Cutoff than the current value of 10,700 mt. Although interesting, to be precautionary and given that the results are based on a new model we do not recommend revising the current Cutoff levels at this time. Table 4. Estimates of the 5, 25, 50, 75, and 95th percentile of the posterior distribution of the unfished biomass for the five major herring stocks. The potential Cutoff level based on the 50th percentile is also presented.

Potential Cutoff

Stock

5%

25%

50%

75%

95%

QCI PRD CC SG WCVI

10.9

14.0

16.6

19.7

25.8

4.1

35.4

41.8

46.9

52.9

62.0

11.7

39.1

47.8

55.8

66.8

85.0

14.0

82.6

92.7

100.0

107.7

120.8

25.0

56.4

66.0

74.4

85.1

109.2

18.6

30

3

PRD

0

0

1

1

2

2

3

QCI

0.2

0.4

0.6

0.8

1.0

0.2

0.6

0.8

1.0

0.4

0.6

0.8

1.0

GS

0

0

1

1

2

Density

2

3

3

CC

0.4

0.2

0.4

0.6

0.8

1.0

0.2

4

Steepness

3

WCVI

0

1

2

Prior Posterior

0.2

0.4

0.6

0.8

1.0

Steepness Figure 19. Bayesian prior and estimated steepness (h) from the posterior distribution for the five assessment regions.

31

4

PRD

0

0

1

1

2

2

3

3

4

QCI

1.0

1.5

0.0

0.5

1.0

6

0.5

5

0.0

SG

3

2

2

0

0

1

Density

4

4

CC

1.5

0.0

0.5

1.0

1.5

0.0

0.5

1.0

1.5

5

SigmaR

4

WCVI

0

1

2

3

Prior Posterior

0.0

0.5

1.0

1.5

SigmaR Figure 20. Bayesian prior and estimates of the variance of the stock recruitment function for the five assessment regions.

32

0.0

0.04

0.08

QCI

0.01

0.02

CC

0.0

Density

0.03

0.0

0.02

0.04

PRD

0.030 0.0

0.01

0.02

0.03

GS

0.0

0.010

0.020

WCVI

0

20

40

60

80

100

120

140

Bzero Figure 21. Bayesian distribution for the estimate of the unfished biomass (B0) from the posterior distribution for the five assessment regions.

33

ABUNDANCE FORECASTS Forecasts of pre-fishery spawning stock abundance for 2007 are calculated slightly differently than in past assessments. Forecasts of the pre-fishery biomass were determined by summing the prediction of age 4 and older biomass with the forecasts of age 2+ recruits for a poor, average, and good recruitment as determined from the posterior distributions of the Bayesian analysis. The results are presented in Figures 22 and 23. Poor, average, and good recruitment levels were calculated as the mean of the lowest 33%, the mid 33%, and the highest 33% of the estimates of historic age 2+ abundance. The calculation was conducted for each of the 1 million simulations and the distribution of forecasts is based on the sub-sample of 2000 traces from the MCMC analysis. Queen Charlotte Islands The posterior distribution for the estimate of 2006 spawning biomass is presented in Figure 22 and suggests abundance of about 5000 tonnes. The distribution of forecast biomass with poor and average recruitment indicates that abundance will be similar in 2007. A good recruitment in 2007 could increase biomass to 10-15,000 tonnes bringing the stock above the Cutoff level (Figure 22). Recruitment to this stock has been generally poor for the past decade (Fig. 24) with good year-classes occurring in 1995 and 2000. The 2001 through 2003 year-classes have been poor or average. The spawning run was composed primarily of age 3+ fish from the 2002 year-class constituting 43% of the spawners while age 6+ fish from the 2000 year-class contributed another 15% of the run (Appendix 1.1). The forecast with a poor recruitment is 5,000 tonnes and 6,800 tonnes with an average recruitment (Table 5). Prince Rupert District The posterior distribution from the MCMC simulation indicates that the spawning biomass in 2006 was slightly less than 15,000 tonnes (Fig. 22). The distributions of forecast biomass with both poor and average recruitment will retain abundance at similar levels just above the Cutoff of 12,100 tonnes for this assessment region. A good recruitment would increase abundance to well above 20,000 tonnes. Recruitment to this stock has been consistent, with good year-classes occurring roughly every few years since 1980 (Figure 24). Both the 2000 and 2002 year-classes were good but the 2001 and the 2003 year-class that recruited in 2006 were poor. The spawning run consisted of about 16% age 2+ recruits with the majority of the run (44%) comprised of age 3+ fish from the 2002 year-class with another 23% age 5+ fish from the 2000 yearclass (Appendix 1.2). The forecast run size to the Prince Rupert District in 2007 with poor recruitment is 15,400 tonnes and with average recruitment 19,100 tonnes (Table 5). Central Coast The estimate of the 2006 spawning biomass and 2007 pre-fishery forecasts are presented in Figure 22. The posterior distribution indicates that spawning abundance in 2006 was about 15,000 tonnes. The forecast for 2007 with poor recruitment would result in a similar level of abundance. An average recruitment would result in run size of just over 20,000 tonnes whereas a good recruitment would increase abundance above 30,000 tonnes. The projected abundance with an average recruitment would leave the stock just above the Cutoff of 17,600 tonnes for this assessment region. Recruitment to this stock has been characterized by intermittent strong year-classes with the most recent one being the 2002 (54% of the 2006 run) that recruited in 2005 (Fig. 24). The other strong year-class was 2000, still accounting for 20% of the spawning run at age 5+ while the recruiting 2003 year-class is poor and constituted only 10% of the run in 2006 (Appendix 1.3). The forecast run size to the Central Coast in 2007 with poor recruitment is 17,500 tonnes and with average recruitment is 21,700 tonnes (Table 5). Strait of Georgia The Strait of Georgia herring stock remains the most productive on the coast. The posterior distribution of the 2006 spawning biomass and the pre-fishery forecasts for 2007 is presented in Figure 23. The 2006 biomass was just over 50,000 tonnes and a similar level is projected in 2007 with a poor recruitment. An average recruitment would produce a run of just over 70,000 tonnes while a good recruitment would return the stock to almost 100,000 tonnes. Although abundance declined substantially in 2006 the stock remains well above the Cutoff of 21,200 tonnes for this assessment region. Recruitment to this stock has been characterized by consistent strong year-classes every second or third year since the mid-1980s (Fig. 25). The recent year-classes from 1998-2002 are among the largest ever observed in this assessment region. The 2000 through 2003 year-classes contributed 11, 19, 24, and 25% of the 2006 run, respectively. A substantial proportion of the run (17%) was also comprised of age 1+ spawners (Appendix 1.4). The forecast run size to the Strait of Georgia in 2007 with a poor recruitment is 57,100 and with average recruitment is 73,200 tonnes (Table 5).

34

West Coast Vancouver Island Abundance in the west coast of Vancouver Island assessment region has fluctuated dramatically from the historic high of the mid-1970s to the recent depressed levels (Fig. 7). The posterior distribution form the MCMC simulation indicates that the spawning biomass in 2006 was below 5,000 tonnes, a level not seen since the collapse of the late 1960s although the stock has been only lightly fished during the past decade (Figure 23). The forecast pre-fishery abundance for 2007 indicates that even a poor recruitment should double current levels to at least 10,000 tonnes. An average recruitment would increase abundance to around 20,000 tonnes just above the Cutoff of 18,800 tonnes for this assessment region. A good recruitment would increase abundance to above 30,000 tonnes but this is very poorly determined (Figure 23). Recruitment to this stock has been characterized by periods of good and bad recruitment prior to 1980. Subsequently, average or better year-classes have been intermittent occurring about every 4-5 years (Fig. 25). The majority of the 2006 run was comprised of only two year-classes (Appendix Table 1.5). The 2002 year-class contributed 34% while the recruiting 2003 year-class, while poor, contributed 37%. There was also an unusual abundance of precocious 1+ spawners (15%). The forecast run size to the west coast of Vancouver Island in 2007 with a poor recruitment is 13,100 tonnes and with an average recruitment is 20,600 tonnes (Table 5). Table 5. Estimated 50th percentiles of the posterior distributions from Bayesian analysis of 2006 spawning biomass and forecasts of the 2007 pre-fishery biomass with poor, average, and good recruitment.

2006 SB QCI PRD CC SG WCVI

2007 – 4+

5651 4132 14161 13936 15893 15125 53975 40111 2850 6970 * Harvest level is Forecast*0.2 minus Cutoff

Poor

Forecast Biomass Avg Good

5004 15384 17549 57125 13116

6820 19126 21683 73224 20612

35

12638 28293 32643 91468 38486

Poor

Available Harvest Avg Good

0 3077 0 11425 0

0 3825 4083* 14645 1812*

1938 5659 6529 18294 7697

B2006 B2007-4+ B2007-P B2007-A B2007-G

0.0

0.05

0.10

0.15

0.20

QCI

5

10

15

20

25

PRD

30

0.06

B2006 B2007-4+ B2007-P B2007-A B2007-G

0.0

0.02

Density

0.10

0

10

20

30

40

50

CC

60

B2006 B2007-4+ B2007-P B2007-A B2007-G

0.0

0.02

0.04

0.06

0.08

0

0

10

20

30

40

50

60

Spawning Biomass Figure 22. Estimated Markov chain Monte Carlo (MCMC) Bayesian profile likelihood distributions for spawning biomasss in 2006 and the forecast pre-fishery biomass in 2007 for the northern stock assessment regions. Arrow represents the 50th percentile of the forecast assuming an average recruitment.

36

0.025

GS

Density

0.0

0.005

0.010

0.015

0.020

B2006 B2007-4+ B2007-P B2007-A B2007-G

50

100

150

WCVI B2006 B2007-4+ B2007-P B2007-A B2007-G

0.0

0.1

0.2

0.3

0.4

0

0

10

20

30

40

50

60

Spawning Biomass Figure 23. Estimated Markov chain Monte Carlo (MCMC) Bayesian profile likelihood distributions for the 2006 spawning biomass and the forecast pre-fishery biomass for 2007 for the southern stock assessment regions. Arrow represents the 50th percentile of the forecast assuming an average recruitment.

37

4000 3000 2000 1000

Recruits (millions)

5000

6000


0

Good Avg Poor 1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

800 600

Good

400

Recruits (millions)

1000

1200


200

Avg

0

Poor

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

2000 1500 1000

Good

500

Recruits (millions)

2500

Central Coast

Avg

0

Poor 1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Figure 24. Estimates of abundance of recruiting age 2+ year-classes from age-structured analysis for northern B.C. herring stock assessment regions, 1951-2006. The horizontal lines delimit poor, average, and good recruitment categories and are the 33 and 66 percentiles of the cumulative frequency distribution.

38

1500 1000

Good

Avg

500

Recruits (millions)

2000

Strait of Georgia

0

Poor

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

2000

Good 1000

Recruits (millions)

3000

4000

W.C. Vancouver Is.

Avg

0

Poor

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Figure 25. Estimates of abundance of recruiting age 2+ year-classes from age-structured analysis for southern B.C. herring stock assessment regions, 1951-2006. The horizontal lines delimit poor, average, and good recruitment categories and are the 33 and 66 percentiles of the cumulative frequency distribution.

39

MINOR STOCKS – AREA 27 & 2W Abundance estimates for the minor herring stocks in Areas 2W and 27 were obtained using the HCAM assessment model. The version of the model used was R18 as described earlier in the document. Because of data limitations for these two stocks it was not possible to obtain estimates with the preferred model R20. In addition, the model was run for shorter time periods for these two stocks. Given the novelty of this approach and the patchiness of the data we continue to recommend a harvest rate of 10% of the forecast biomass for these two stocks rather than 10% of the estimate of current biomass as was the policy in the past. Area 27 The availability of consistent age structure and spawn deposition data for this stock began in the late 1970s. Some limited biological sampling data was available in the early 1970s but usually consisted of a single sample and was insufficient for catch-age analysis. As a result, the HCAM analysis for this stock was begun in 1977/78 to present. The available information on catch and spawning biomass as estimated from the escapement model is presented in Table 7. The HCAM analysis for this stock is consistent and fits the spawn deposition data closely suggesting a spawning biomass ranging between 1-5,000 tonnes (Figure 26). The lowest level occurred in 2001 and the stock has been increasing slowly since then. The forecast biomass for 2007 based on the HCAM model and assuming an average recruitment is 2651 tonnes (Table 6). Area 2W The availability of relatively consistent age structure and spawn deposition estimates for this stock began in 1972/73. Unfortunately, there was also a period from 1995-1997 when no biological samples were collected. The time series of available catch and spawn deposition data are presented in Table 8 as in previous assessments with spawning biomass determined using the escapement model. The estimate of spawning biomass for the available data suggests a stock varying between 4,000 to 10,000 tonnes from the early 1970s to the early 1990s (Figure 26) . The limited spawn survey coverage and absence of age structure data through the mid-1990s make it difficult to determine stock size and the model fits closely to the available spawn estimates. The more recent spawn surveys and biological sampling data suggest a stock size approaching 2,000 tonnes. The forecast biomass for the stock in Area 2W based on the HCAM model and assuming an average recruitment is 3864 tonnes (Table 6).

Table 6. Forecasts of the 2007 biomass for the minor stocks in Areas 27 and 2W assuming poor, average, and good recruitment.

2006 SB Area 27 Area 2W

2007 – 4+

2087 2076 *Assumes a 10% harvest rate.

2035 3599

Poor

Forecast Biomass Avg Good

2517 3670

2651 3864

40

3646 6032

Poor

Available Harvest* Avg Good

252 367

265 386

365 603

15

Area 27

10 0

5

Pre-fishery Biomass


1980

1990

2000

2010

12

Area 2W

8 6 0

2

4

Pre-fishery Biomass

10


1970

1980

1990

2000

Figure 26. Estimated pre-fishery biomass for the minor stocks in Area 27 and Area 2W.

41

2010

Table 7. Estimates of spawning stock biomass, catch, and pre-fishery stock abundance (tonnes) for the minor stock in area 27 for 1951-2006.

Season 19501 19512 19523 19534 19545 19556 19567 19578 19589 19590 19601 19612 19623 19634 19645 19656 19667 19678 19689T 19690 19701 19712 19723 19734 19745 19756 19767 19778 19789 19790 19801 19812 19823 19834 19845 19856 19867 19878 19889 19890 19901 19912 19923 19934 19945 19956 19967 19978 19989 19990 20001 20012 20023 20034 20045 20056

Surface 1,955.24 484.38 4,618.03 2,646.44 574.87 1.47 184.03 38.62 60.47 223.95 168.99 101.62 407.30 0.00 2,516.54 81.73 46.24 141.68 2,198.42 2,433.72 290.00 250.29 2,578.17 0.00 1,606.18 210.44 638.19 3,595.03 6,908.61 14,419.06 1,828.32 4,136.53 2,500.47 3,004.22 370.26 47.10 952.33 1,612.23 1,684.74 3,565.45 2,011.68 55.30 1,394.34

Spawn (mt) Macro Dive

0.00

284.64

122.10 37.96 11.15 613.94 2,536.51 1,967.85 559.20 14.41 61.77 214.65 153.05

100.68 140.56 230.06 178.70

1011.75 3,162.95

2,804.86 1,608.78 1,190.53 2,109.40 1,645.78 3,260.94 1,924.89 1,319.05 1,901.13 1,940.96 504.40 1,300.92 220.49 816.48 765.21 923.83 1618.23 511.29

Total

Seine

1,955.24 484.38 4,618.03 2,646.44 574.87 1.47 184.03 38.62 60.47 223.95 168.99 101.62 407.30 0.00 2,516.54 81.73 46.24 141.68 2,198.42 2,433.72 290.00 250.29 2,578.17 0.00 1,606.18 210.44 638.19 3,595.03 6,908.61 14,419.06 1,828.32 4,136.53 2,500.47 3,004.22 1,382.00 3,494.69 952.33 1,612.23 4,611.70 5,212.19 3,213.37 2,778.64 5,576.63 5,228.78 2,484.09 1,333.46 1,962.90 2,155.61 657.46 1,300.92 220.49 917.16 905.77 1,153.89 1,796.93 1,936.28

42

Catch (mt) Gillnet Other

Total

1,919.89 5,938.70

1,919.89 5,938.70

407.22

407.22

1,149.06 173.05 30.75 322.55 769.08 951.48 51.42

1,149.06 173.05 30.75 322.55 769.08 951.48 51.42

507.91

74.98 422.13

238.49

18.33

526.25

78.62

78.62

75.12 270.40 519.26 670.95 332.09 162.93 170.71

0.09 335.43 366.85 344.55 87.57

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

150.10 692.53 519.26 670.95 570.58 162.93 170.71 0.00 0.00 0.00 0.00 0.00 0.00 0.09 335.43 366.85 344.55 87.58 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Total Stock 1,955.24 484.38 4,618.03 4,566.33 6,513.58 1.47 184.03 38.62 467.69 223.95 1,318.05 274.67 438.05 322.55 3,285.62 1,033.21 97.66 141.68 2,198.42 2,433.72 290.00 250.29 2,578.17 526.25 1,606.18 289.06 638.19 3,745.13 7,601.13 14,938.32 2,499.27 4,707.11 2,663.41 3,174.93 1,382.00 3,494.69 952.33 1,612.23 4,611.70 5,212.19 3,213.46 3,114.07 5,943.49 5,573.33 2,571.67 1,333.48 1,962.90 2,155.61 657.46 1,300.92 220.49 917.16 905.77 1,153.89 1,796.93 1,936.28

Table 8. Estimates of spawning stock biomass, catch, and pre-fishery stock abundance (tonnes) for the minor stock in area 2W for 1951 to 2006. Spawn (mt) Catch (mt) Total Season Surface Macro Dive Total Seine Gillnet Other Total Stock 19523 19567 19578 19589 19590 19601 19612 19623 19634 19645 19656 19667 19678 19689 19690 19701 19712 19723 19734 19745 19756 19767 19778 19789 19790 19801 19812 19823 19834 19845 19856 19867 19878 19889 19890 19901 19912 19923 19934 19978 19990 20001 20012 20023 20034 20045 20056

202.90 3.82 156.88 1,915.96 1,569.27 558.49 1,715.31 1,436.26 968.87 439.48 23.51 261.65 72.62 593.04 576.86 603.53 1,010.77 1,603.60 1,674.84 1,153.98 826.10 1,174.40 831.97 494.02 2,114.38 1,811.18 4,781.24 4,869.26 2,522.18 1,719.33 683.72 988.92 3,380.16 2,718.92 2,787.76 355.53 0.61

1,461.95 10.94 226.33 3,021.64

13.39

8,157.95 2,459.14 3,740.13 76.16 231.10 455.21 142.79 34.58 135.89

345.16 18.08

2,639.56 330.69

170.74 169.14 12.54 17.13 13.70 145.60

202.90 3.82 156.88 1,915.96 1,569.27 558.49 1,715.31 1,436.26 968.87 439.48 23.51 261.65 72.62 593.04 576.86 603.53 1,010.77 1,603.60 1,674.84 1,153.98 826.10 1,174.40 831.97 494.02 2,114.38 1,811.18 4,781.24 4,869.26 2,522.18 1,719.33 683.72 988.92 3,380.16 2,718.92 10,945.72 2,985.41 3,909.28 89.31 248.24 468.91 288.39 34.58 149.28 1,461.95 2,995.66 575.09 3,021.64

43

105.83

105.83

312.49 1,251.27 172.37

312.49 1,251.27 172.37

705.73 403.25 449.34

705.73 403.25 449.34

574.68 690.59

0.00 574.68 690.59

770.26 1,225.32 2,518.17

770.26 1,225.32 2,518.17

199.47

199.47

2,271.92 2,558.29 1,283.54 1,305.66

2,271.92 2,558.29 1,283.54 1,305.66

179.63

179.63

202.90 109.65 156.88 1,915.96 1,569.27 558.49 1,715.31 1,436.26 1,281.35 1,690.75 195.87 261.65 72.62 593.04 576.86 603.53 1,010.77 2,309.33 2,078.09 1,603.31 826.10 1,174.40 1,406.66 1,184.61 2,114.38 2,581.44 6,006.56 7,387.44 2,522.18 1,918.80 683.72 988.92 3,380.16 2,718.92 13,217.64 5,543.70 5,192.62 1,394.98 248.24 648.53 288.39 34.58 149.28 1,461.95 2,995.66 575.09 3,021.64

POTENTIAL HARVESTABLE The Pacific Science Advice Review Committee (PSARC) has reviewed the biological basis for target exploitation rate, considering both the priority of assuring conservation of the resource and allowing sustainable harvesting opportunities (Schweigert and Ware 1995). The review concluded that 20% is an appropriate exploitation rate for those stocks that are well above Cutoff or minimum spawning biomass threshold levels (PSARC 1995). The 20% harvest rate is based on an analysis of stock dynamics which indicates this level will stabilize both catch and spawning biomass while foregoing minimum yield over the long term (Hall et al. 1988, Zheng et al. 1993). In addition to the 20% harvest rate, a Cutoff level set at 25% of the estimated unfished biomass level is used to ensure that adequate spawning biomass to sustain each population during natural reductions in abundant stock productivity, is maintained for each stock. To increase the probability that spawning biomass will be maintained above the Cutoff level, for those stocks which are marginally above Cutoff the following reduced catch level is recommended: Catch = Forecast Run - Cutoff. This will provide for smaller fisheries in areas where the 20% harvest rate would bring the escapement down to levels below the Cutoff. Cutoff levels have been established through a stock-recruitment curve or bootstrapping of the observed recruitment time series. The Cutoff levels for the five major migratory stocks are: 1992/93 Cutoffa 1994/95 Cutoff Queen Charlotte Islands

1996/97 Cutoff

Current Cutoffc

11700

10700

10700

10700


12100

12100

12100

12100

Central Coast

10600

18800

17600

17600

Strait of Georgia

22100

21200

21200

21200


20300

18800

18800

18800

b

- Cutoff level based on simulation model with stock-recruitment relationship, and two assessment areas on the WCVI. - Because of the poor performance of the age-structured model in this region in the past the Cutoff has not been recalculated using the bootstrap approach but is based on a stock-recruitment relationship. c – A Cutoff of 14,000 tonnes was proposed for the Central Coast in 1998. Uncertainty about ASM performance in 1998 resulted in retention of the existing Cutoff. a

b

It is important to note that the current Cutoff represents a commercial fishery fishing threshold rather than a conservation threshold or reference point. It is a reference point intended to maintain the reproductive capacity of the stock. Thus, even when a stock is near (or below) the stock-specific Cutoff, conservation concerns may be unwarranted as this information alone is insufficient to conclude that a stock may be at risk. The current commercial fishery Cutoff is used to maintain stock productivity or rebuild stock biomass following years when stock size decreases below the Cutoff. Predicting recruitment for Pacific herring and most other fish species is difficult. In the absence of independent information, the scientific advice has been to assume an average recruitment to minimize forecasting errors. Currently, recruitment forecasting has been tested and validated for only the SG and WCVI stocks by PSARC. This forecast relies upon independent, offshore survey data collected during the summer prior to the recruitment of age-2+ fish to the spawning population. Recruitment forecasting methodologies are being developed for other herring stocks but none are currently in routine use. Therefore, a decision on the level of recruitment to be used in the forecast must be made in the absence of independent data. The decision about recruitment strength must be consistent with the precautionary approach to fisheries management while assuring harvest opportunities are not unduly restricted. In the absence of alternative recruitment forecasting methods, the following rules have been adopted in developing the abundance forecast: 1.

If the pre-fishery biomass was below Cutoff in the previous year, then assume POOR recruitment for the forecast. The modified harvest rule is likely to apply.

2.

If the pre-fishery biomass was above Cutoff in the previous year and recruitment has been GOOD in the two previous years, then assume GOOD recruitment for the forecast.

44

3.

If Rule 1 or Rule 2 DO NOT APPLY then assume AVERAGE recruitment for the forecast. The modified harvest rule may apply.

The harvest of minor stocks is also conducted in a precautionary manner given that no forecast of abundance in the upcoming season has been possible until now. The harvest rule for minor stocks is that a maximum of 10% of the estimated abundance in the current season may be harvested in the coming season. The harvest rule is based on the assumption that minor herring stock dynamics are consistent with the major migratory stocks which can sustain substantially higher rates of harvest. (Hall et al. 1988, Zheng et al. 1993).

SIZE AT AGE TRENDS Inter-annual changes in growth rate of herring can have significant impacts on the size at age and consequently on estimates of stock productivity and availability to the harvesting sectors. Concern about declining size of herring in the late 1990s continues with no obvious indication of an increase in recent years (Fig. 27). Trends in size at age continue to be monitored and since 1999 have been incorporated into the management decision making process by providing an indication of the proportion of the stock estimated to be catchable by the gillnet sector.

ACKNOWLEDGEMENTS Chuck Fort, Bruce McCarter, and Kristen Daniel updated the catch, biological sampling and spawn survey data bases and reviewed all 2006 assessment data. Howard Stiff provided programming support for the Access databases used to summarize the assessment data series. Database upgrades and ongoing maintenance have been funded by the Herring Conservation and Research Society (HCRS). The HCRS through the test fishing program also funded the collection of spawn survey information and test fishery biological samples coast-wide in support of the stock assessment analysis presented in this report.

45

100

100

100

150 4 6

5 4 3

1970 150

200

200

250

100

150 6 5 4 150

200

200

250

100

3

CC

GS

WC

1980

1990

46 250

100

150

150

5 4

250

100

200

200

Weight at Age 250

250

PRD

250

100

Weight at Age

100

100

150

200

200

150

Weight at Age

4

200

250

Weight at Age

6 5

150

200 6

150

Weight at Age

250

250

QCI

3

6

3

5

3

2000

Figure 27. Estimates of weight-at-age (g) for 3-6 year old herring from 1951-2006 for the five major assessment regions.

REFERENCES

Fournier, D. A., Sibert, J. R., Majkowski, J., and Hampton, J. 1990. MULTIFAN: a likelihood-based method for estimating growth parameters and age composition from multiple length frequency data sets illustrated using data for southern bluefin tuna (Thunnus maccoyii). Can. J. Fish. Aquat. Sci. 47: 301–317. Francis, R.I.C.C. 2003. Analyses supporting the 2002 stock assessment of hoki. New Zealand Fisheries Assessment Report 2003/5. 34 p. Francis, R.I.C.C. 1992. Use of risk analysis to assess fishery management strategies: a case study using orange roughy (Hoplostethus atlanticus) on the Chatham Rise, New Zealand. Can. J. Fish. Aquat. Sci. 49: 922-930. Fu, C., Schweigert, J.F., and C.C. Wood, C.C. 2004. An evaluation of alternative age-structured models for risk assessment of Pacific herring stocks in British Columbia. DFO Can. Sci. Advis. Sec. Res. Doc. 2004/011: 59p. Gelman, A., Carlin, J.B., Stern, H.S., and D. B. Rubin. 1995. Bayesian data analysis. Chapman and Hall, London. Gudmundsson, G. 1994. Time series analysis of catch-at-age observations. Applied Statistician 43:117-126. Haist, V., and L. Rosenfeld. 1988. Definitions and codings of localities, sections and assessment regions for British Columbia herring data. Can. MS Rep. Fish. Aquat. Sci. 1994: 123p. Haist, V., and J. Schweigert. 2006. Catch-age models for Pacific herring: evaluation of alternative assumptions about fishery and stock dynamics and alternative error distributions. PSARC Working Paper 2006-02. Hall, D. L., R. Hilborn, M. Stocker, and C. J. Walters. 1988. Alternative harvest strategies for Pacific herring (Clupea harengus pallasi). Can. J. Fish. Aquat. Sci. 45: 888-897. Mace, P. M., and I. J. Doonan. 1988. A generalized bioeconomic simulation model for fish population dynamics. New Zealand Fisheries Assessment Research Document Number 88/4, Wellington, New Zealand. Myers, R.A., Barrowman, N.J., Hilborn, R., and D.G. Kehler. 2002. Inferring Bayesian priors with limited direct data: applications to risk analysis. N. Am. J. Fish. Manag. 22: 351-364. Otter Research Limited. 2000. An introduction to AD model builder, version 4: For use in nonlinear modelling and statistics. Otter Research Limited. Sydney, B.C. Canada. 127p. Schweigert, J. 2005. An assessment framework for Pacific herring (Clupea pallasi) in British Columbia. DFO Can. Sci. Advis. Sec. Res. Doc. 2005/083: 35p. Schweigert, J. 2004. Stock assessment for British Columbia herring in 2004 and forecasts of the potential catch in 2005. DFO Can. Sci. Advis. Sec. 2004/081: 95p. Schweigert, J., and D. Ware. 1995. Review of the biological basis for B.C. herring stock harvest rates and conservation levels. PSARC Working Paper H95: 2. Shields, T.L., Jamieson, G.S., and P.E. Sprout. 1985. Spawn-on-kelp fisheries in the Queen Charlotte Islands and the northern British Columbia coast – 1982 and 1983. Can. Tech. Rep. Fish. Aquat. Sci. 1372: 53p. Starr, P. J., Bentley, N., and Maunder, M.N. 1999. Stock assessment of two New Zealand rock lobster substocks. New Zealand Fisheries Assessment Research Document 99/34. pp 44. Zheng, J., F. C. Funk, G. H. Kruse, and R. Fagen. 1993. Threshold management strategies for Pacific herring in Alaska. In: Proc. Int. Symp. on Management Strategies for Exploited Fish Populations. Alaska Sea Grant Report 93-02. Univ. Alaska Fairbanks.

47

Appendix 1.1. Age composition and catch by season, fishery and gear type for the Queen Charlotte Islands stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19501 19512 19534 19545

Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Gillnet Seine Seine Gillnet Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Trawl Gillnet Seine Seine Seine Seine Trawl Seine Seine Seine Gillnet Seine Trawl Gillnet Seine Trawl

Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.00 1.92 0.06 0.00 0.00 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.07 24.77 2.90 8.74 8.74 0.15 20.71 81.58 81.98 81.58 1.05 1.05 4.21 4.21 2.57 0.37 0.37 1.02 1.02 1.02 1.71 1.67 18.36 0.88 29.95 6.50 3.59 0.20 0.12 0.00 0.62 0.13 0.00 0.30 0.44 0.00 0.05 0.09 0.00 0.16 0.00 6.22 7.06 0.00 0.69 0.00 0.42 1.33 0.00 0.45 0.85 0.00 4.14 4.88 0.00 2.09 2.70 0.00 0.12 0.10 0.00 0.16 0.31 0.00 1.78 1.74 3.64 1.34 1.33 3.43 1.27 0.14 0.00 5.60 1.06 0.00 1.05 1.08

19556 19567 19578

19589 19601 19612 19623 19634

19645 19656 19667 19678 19701 19712 19723 19734 19745

19756

19767

19778 19789

19790 19801

19812

19823

19834

19845

19856

19867 19878

19889 19890 19901

19912

P E R C E N T AT 2+ 3+ 4+ 5+ 15.31 20.96 29.02 14.08 14.08 16.02 24.66 16.68 16.24 16.68 63.16 63.16 32.63 32.63 38.97 50.00 50.00 15.92 15.92 15.92 82.31 81.75 32.77 67.25 50.57 50.40 34.24 32.91 27.40 5.73 27.82 33.28 0.00 2.98 2.81 0.00 18.42 19.67 0.00 22.75 0.00 4.91 5.39 0.00 83.10 6.50 3.05 3.92 0.30 3.26 4.68 0.21 4.21 5.23 0.00 36.57 36.39 2.81 8.63 8.15 8.30 2.00 2.80 0.00 9.60 10.42 51.01 41.98 68.11 5.12 31.75 10.61 0.51 4.25 4.26 0.00 30.50 54.84

52.91 29.67 21.28 39.42 39.42 9.64 15.96 1.26 1.29 1.26 28.42 28.42 36.00 36.00 44.12 27.11 27.11 60.00 60.00 60.00 10.25 10.30 16.38 26.49 17.23 29.30 40.98 18.91 41.39 48.41 36.04 45.41 22.50 44.51 36.87 0.75 9.26 8.12 2.53 17.10 4.17 32.53 32.35 28.24 4.49 4.56 85.37 88.65 72.00 3.50 4.48 3.35 3.02 3.51 1.19 4.17 4.54 1.28 25.14 24.49 24.48 21.05 10.56 12.73 4.90 5.85 7.52 5.34 11.63 85.99 45.90 6.53 8.18 10.74 8.51 2.27 4.25 9.68

15.31 17.98 33.66 18.06 18.06 62.17 9.38 0.18 0.20 0.18 7.37 7.37 24.84 24.84 5.88 18.16 18.16 16.53 16.53 16.53 3.63 4.02 10.40 2.65 2.25 8.00 12.30 32.99 17.67 25.48 24.53 13.55 40.00 31.53 29.25 21.80 36.66 29.70 16.61 11.34 11.81 18.23 18.23 25.88 5.44 44.47 5.13 2.94 8.55 87.61 84.32 89.10 5.75 6.86 2.38 2.64 2.87 4.60 3.52 3.51 2.90 37.46 37.58 53.42 24.93 24.35 4.77 3.24 1.66 3.74 4.03 78.55 44.50 33.21 21.28 22.44 8.27 2.15

11.52 3.71 10.19 14.85 14.85 8.38 26.29 0.14 0.16 0.14 0.00 0.00 1.26 1.26 7.35 2.11 2.11 5.31 5.31 5.31 1.34 1.47 7.45 2.72 0.00 4.30 5.57 11.77 10.64 16.56 8.53 5.29 30.00 15.24 23.18 60.90 22.74 22.91 39.71 33.12 20.14 20.31 20.80 27.06 2.58 19.36 3.08 1.73 9.84 2.19 2.47 3.35 77.05 72.87 90.32 9.56 10.10 8.95 3.93 3.95 4.56 3.69 8.70 4.04 38.44 37.76 11.75 14.50 6.98 0.18 2.55 2.43 9.97 33.99 46.81 43.47 4.46 15.05

48

A G E 6+ 7+ 4.20 0.93 1.93 4.37 4.37 2.74 2.37 0.14 0.12 0.14 0.00 0.00 0.42 0.42 0.74 1.99 1.99 1.22 1.22 1.22 0.55 0.59 5.89 0.00 0.00 0.80 2.14 2.10 2.32 3.18 1.94 1.72 5.00 4.61 6.41 14.29 9.92 14.66 27.08 13.29 38.89 14.19 12.45 15.29 1.79 19.58 1.92 0.69 5.88 1.34 1.53 2.31 3.65 3.91 2.72 43.33 41.76 80.05 12.79 12.94 12.45 3.28 9.63 5.28 3.88 3.84 14.86 22.71 6.64 0.77 7.00 0.33 8.44 3.68 4.26 9.66 48.40 11.83

0.61 0.07 0.71 0.29 0.29 0.74 0.44 0.00 0.00 0.00 0.00 0.00 0.21 0.21 0.37 0.00 0.00 0.00 0.00 0.00 0.20 0.20 4.92 0.00 0.00 0.50 0.77 1.13 0.40 0.00 0.40 0.46 2.50 0.76 0.96 2.26 2.64 4.44 11.55 2.03 20.14 3.06 3.08 3.53 1.22 4.20 0.68 0.35 2.84 0.95 0.99 1.05 1.33 1.58 2.38 1.11 1.12 1.79 45.24 46.22 46.89 8.88 11.18 9.01 4.36 4.33 1.37 1.91 1.33 0.47 4.81 0.85 17.39 2.00 6.38 7.10 2.42 3.23

8+

9++

Mean Weight

0.07 0.00 0.19 0.10 0.10 0.00 0.11 0.00 0.00 0.00 0.00 0.00 0.42 0.42 0.00 0.12 0.12 0.00 0.00 0.00 0.00 0.00 2.07 0.00 0.00 0.20 0.35 0.00 0.06 0.00 0.12 0.17 0.00 0.06 0.07 0.00 0.31 0.41 2.17 0.17 4.17 0.44 0.51 0.00 0.60 1.34 0.21 0.23 0.60 0.57 0.54 0.42 0.70 0.91 0.51 0.35 0.34 0.26 0.53 0.54 0.41 23.03 17.70 15.22 5.86 5.79 1.67 1.72 1.66 0.08 1.06 0.34 8.44 4.70 4.26 10.23 0.14 2.15

0.00 0.00 0.06 0.10 0.10 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.12 0.12 0.00 0.00 0.00 0.00 0.00 1.75 0.00 0.00 0.00 0.06 0.00 0.00 0.64 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.36 0.05 0.69 0.11 0.13 0.00 0.09 0.00 0.14 0.17 0.00 0.12 0.14 0.21 0.14 0.25 0.51 0.17 0.17 0.26 0.10 0.10 0.00 0.43 1.55 0.31 6.24 5.91 3.40 7.25 0.66 0.22 1.63 0.23 2.56 1.84 3.19 4.83 0.52 0.00

89.7 78.4 77.1 94.1 94.1 118.2 103.3 52.1 51.8 52.1 92.8 92.8 97.7 97.7 114.0 109.5 109.5 113.9 113.9 113.9 101.5 102.0 130.7 113.0 94.9 118.1 142.1 140.7 126.8 153.8 132.8 116.3 169.3 155.4 151.8 196.2 159.1 157.1 196.6 146.4 196.9 149.9 148.9 160.1 97.1 157.6 116.3 112.7 141.9 127.2 128.0 141.9 148.7 146.9 158.5 126.1 125.5 154.6 146.4 165.5 155.0 165.5 163.5 159.7 158.6 157.2 123.6 136.5 105.4 119.2 117.4 133.9 149.6 127.8 143.0 151.9 143.2 115.6

Number Aged 1,476 2,251 0 0 0 1,348 4,423 2,769 2,475 2,769 95 95 0 0 272 804 804 490 490 490 1,019 1,019 0 0 0 0 1,184 1,726 1,215 157 6,010 3,026 40 4,055 4,055 133 3,178 3,178 277 1,172 144 916 779 170 2,986 518 5,551 1,735 790 3,526 3,526 477 1,425 1,968 589 3,484 3,484 391 3,099 2,025 241 4,462 322 322 2,916 3,281 1,676 524 301 2,996 1,414 4,769 391 2,448 94 352 3,228 93

CATCH (tonnes) (millions)

* * *

+ + + + * * + + + + + * * * *

+ + + + + + + + + +

+

+

+

+ + + +

+ + +

+ +

+

2,847 10,147 1,786 99 1,136 77,681 23,711 721 10,426 19 199 6,828 576 77 7,632 14,705 275 28,600 131 46 35,304 145 2,746 213 80 102 3,972 7,520 6,191 127 7,602 17 105 11,939 374 1,802 11,125 21 1,489 9,172 2,553 50 5,817 2,086 2,106 1,210 3,888 39 1,705 2,353 18 1,407 4,601 67 929 4,054 58 535 4,581 35 1,493 2,613 0 890 2,028 33 0 32 0 1,449 13 5,542 1,170 3,899 0 543 2,524 0

31.744 122.347 23.168 1.047 12.066 657.044 227.806 13.844 201.343 0.357 2.140 73.560 5.901 0.789 66.952 134.232 2.508 251.046 1.154 0.401 348.556 1.419 21.016 1.883 0.843 0.861 27.954 49.735 47.881 0.824 60.181 0.147 0.619 82.499 2.466 9.186 73.628 0.132 7.575 62.947 12.967 0.336 39.078 13.028 22.050 7.739 32.912 0.342 11.930 18.420 0.138 9.918 30.942 0.457 5.860 31.997 0.459 3.459 27.888 0.209 9.632 15.278 0.000 5.576 12.787 0.210 0.000 0.232 0.000 11.972 0.108 39.649 7.821 30.506 0.000 3.576 16.695 0.000

~

~ ~

~

~

Appendix 1.1. Age composition and catch by season, fishery and gear type for the Queen Charlotte Islands stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19923

Seine Trawl Gillnet Seine Trawl Seine Seine Seine Seine Seine Gillnet Seine Seine Seine Seine Seine Seine Seine

Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.04 1.75 0.00 5.50 7.08 14.35 10.76 22.64 0.16 3.71 0.00 3.63 15.26 20.84 0.08 29.35 1.30 19.07

19934 19945 19956 19967 19978 19989 19990 20001 20012 20023 20034 20045 20056

P E R C E N T AT 2+ 3+ 4+ 5+ 2.79 4.68 0.00 5.50 2.36 15.82 53.81 26.17 58.12 2.16 0.67 17.30 31.65 22.90 68.16 2.37 46.29 10.10

67.33 59.65 2.27 5.63 5.42 2.32 9.30 33.41 27.55 65.00 30.78 3.71 22.32 25.47 18.33 50.65 15.66 42.78

4.25 5.85 22.44 40.75 53.30 4.43 3.24 5.23 9.74 16.83 22.80 60.69 5.06 12.99 6.43 8.76 28.57 9.40

4.68 6.43 43.47 12.87 8.49 37.55 3.34 1.52 2.53 8.03 29.12 8.26 20.92 3.11 3.24 4.02 3.90 15.15

A G E 6+ 7+ 9.73 11.70 9.66 14.48 6.60 9.70 15.57 4.44 0.48 2.78 9.98 5.25 3.05 12.83 1.13 2.60 2.37 2.81

9.95 7.02 7.10 11.13 8.49 8.02 2.40 5.36 0.40 0.67 2.66 0.39 1.39 1.36 2.10 1.42 1.22 0.42

8+

9++

Mean Weight

0.87 2.34 10.23 3.49 7.31 5.27 1.15 0.85 0.63 0.41 1.33 0.62 0.26 0.43 0.40 0.59 0.46 0.00

0.36 0.58 4.83 0.67 0.94 2.53 0.31 0.37 0.40 0.41 2.66 0.15 0.09 0.08 0.12 0.24 0.23 0.28

124.2 125.9 151.9 130.5 133.0 134.8 102.8 97.5 87.9 105.9 131.4 106.9 97.0 93.6 96.7 91.5 93.9 83.3

NOTE: * No biosample data available. Age composition and mean weight assigned from published reports. + Age composition calculated from biosample data aggregated from adjacent sections and/or fishery periods, by gear type. ~ No fishery openings this season. Age composition and mean weight obtained from pre-fishery charter

49

Number Aged 2,755 171 352 + 746 424 474 957 1,643 1,263 1,943 601 1,295 1,147 2,572 2,472 845 1,309 713

CATCH (tonnes) (millions) 2,699 0 0 299 0 0 0 0 1,372 2,500 473 1,764 0 706 0 0 0 0

21.742 0.000 0.002 2.291 0.000 0.000 0.000 0.000 15.597 23.604 3.596 16.500 0.000 7.543 0.000 0.000 0.000 0.000

~

~ ~ ~ ~

~ ~ ~ ~ ~

Appendix 1.2. Age composition and catch by season, fishery and gear type for the Prince Rupert District stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19501

Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Seine Seine Seine Seine Gillnet Seine Gillnet Seine Seine Gillnet Seine Seine Seine Gillnet

Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr

0.03 0.09 0.09 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

5.19 1.72 5.32 3.96 4.76 1.46 1.07 0.38 8.88 2.25 10.04 8.99 18.02 3.83 0.00 4.08 58.55 58.55 58.55 1.64 2.88 1.17 3.39 62.74 66.74 5.00 59.38 59.38 13.33 8.10 10.08 10.25 6.70 6.70 6.70 6.05 6.05 76.33 38.55 60.74 41.59 41.59 2.51 1.29 2.89 3.26 3.26 9.22 4.99 6.54 0.00 0.00 0.00 0.00 57.22 57.22 57.22 34.87 34.87 34.87 18.67 5.79 5.79 0.00 0.00 3.89 0.61 3.89 0.16 0.00 0.35 0.00 0.00 0.00 0.00 0.08 0.13 0.16 0.00

19512

19523 19534 19545 19556 19567

19578

19589

19590

19601

19612

19623

19634

19645

19656

19667

19678

19690 19701 19712 19723

19734 19745 19756

19767

P E R C E N T AT 2+ 3+ 4+ 5+ 18.96 15.86 9.32 8.08 8.81 38.05 38.17 22.98 47.88 4.08 58.11 59.62 19.80 19.26 7.11 21.43 24.14 24.14 24.14 62.11 61.03 62.96 58.98 8.21 7.43 3.26 7.49 7.49 69.22 60.17 59.51 60.16 32.01 32.01 32.01 30.85 30.85 15.42 15.20 16.33 13.61 13.61 71.43 48.47 67.52 65.07 65.07 19.05 13.41 15.87 5.29 5.29 5.29 5.29 32.31 32.31 32.31 39.74 39.74 39.74 62.91 45.91 45.91 5.32 0.96 35.37 33.23 35.37 17.88 0.96 4.42 0.00 1.60 0.90 0.00 13.52 21.43 18.12 1.07

57.83 60.43 33.19 34.32 33.65 28.90 20.04 31.95 19.11 70.30 9.51 9.14 35.57 42.33 44.95 52.04 6.24 6.24 6.24 19.52 19.34 19.29 20.35 20.55 18.52 51.30 23.25 23.25 4.76 6.91 7.23 7.07 38.46 38.46 38.46 38.31 38.31 4.46 21.58 12.62 17.25 17.25 11.94 10.21 11.86 10.15 10.15 45.55 53.55 50.81 21.38 21.38 21.38 21.38 5.37 5.37 5.37 19.40 19.40 19.40 15.11 31.35 31.35 17.93 39.42 4.95 4.45 4.95 53.16 39.42 26.83 31.91 6.86 7.22 15.79 6.40 3.97 7.08 2.14

10.05 11.38 45.08 45.41 45.22 26.40 24.95 27.13 13.51 15.80 18.95 18.79 12.24 13.46 37.16 12.24 7.24 7.24 7.24 5.96 5.06 6.19 5.15 5.57 4.46 20.22 6.10 6.10 9.50 18.06 17.13 16.63 7.44 7.44 7.44 7.66 7.66 3.10 17.43 7.12 21.11 21.11 7.88 19.65 10.20 11.10 11.10 10.13 9.70 10.48 23.45 23.45 23.45 23.45 1.88 1.88 1.88 4.59 4.59 4.59 3.12 9.51 9.51 64.43 21.15 27.58 30.09 27.58 7.44 21.15 51.39 59.57 27.66 32.25 57.89 24.30 20.78 22.73 19.93

5.42 6.21 5.66 6.84 6.14 4.99 14.29 14.48 6.76 6.01 2.55 2.65 13.25 19.05 9.17 10.20 0.80 0.80 0.80 7.16 7.96 6.74 8.73 1.63 1.48 10.65 2.21 2.21 2.44 4.38 4.07 3.97 11.41 11.41 11.41 11.69 11.69 0.28 3.27 1.42 3.14 3.14 5.04 17.00 6.38 8.98 8.98 10.34 9.66 9.83 16.32 16.32 16.32 16.32 2.70 2.70 2.70 0.73 0.73 0.73 0.03 5.05 5.05 5.88 34.62 23.05 26.25 23.05 16.46 34.62 9.06 8.51 43.89 49.73 22.81 35.92 34.28 31.85 54.09

50

A G E 6+ 7+ 2.27 3.79 0.91 1.19 1.03 0.21 1.39 2.52 3.28 1.34 0.53 0.66 0.90 1.61 1.38 0.00 3.02 3.02 3.02 2.05 1.81 2.21 1.44 1.10 0.94 7.39 1.17 1.17 0.44 1.74 1.43 1.38 2.23 2.23 2.23 3.43 3.43 0.35 3.61 1.69 2.79 2.79 0.85 1.48 0.60 0.69 0.69 4.75 7.23 5.18 19.08 19.08 19.08 19.08 0.41 0.41 0.41 0.26 0.26 0.26 0.08 1.63 1.63 3.78 2.88 3.26 3.38 3.26 4.43 2.88 6.31 0.00 9.26 7.47 3.51 14.53 14.49 13.84 14.59

0.20 0.43 0.40 0.16 0.30 0.00 0.11 0.56 0.58 0.22 0.18 0.07 0.22 0.41 0.23 0.00 0.00 0.00 0.00 1.54 1.85 1.44 1.88 0.08 0.22 1.96 0.22 0.22 0.25 0.43 0.42 0.41 0.74 0.74 0.74 0.60 0.60 0.06 0.21 0.01 0.41 0.41 0.35 1.38 0.43 0.60 0.60 0.71 1.03 0.95 9.66 9.66 9.66 9.66 0.20 0.20 0.20 0.14 0.14 0.14 0.08 0.59 0.59 2.38 0.96 1.26 1.26 1.26 0.32 0.96 1.26 0.00 8.46 1.74 0.00 4.01 3.18 4.45 6.76

8+

9++

Mean Weight

0.06 0.00 0.03 0.04 0.03 0.00 0.00 0.01 0.00 0.00 0.12 0.07 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.01 0.06 0.56 0.06 0.12 0.22 0.22 0.19 0.19 0.06 0.20 0.13 0.13 0.74 0.74 0.74 1.01 1.01 0.00 0.06 0.00 0.06 0.06 0.00 0.40 0.11 0.12 0.12 0.22 0.37 0.34 3.22 3.22 3.22 3.22 0.00 0.00 0.00 0.27 0.27 0.27 0.00 0.15 0.15 0.14 0.00 0.63 0.74 0.63 0.16 0.00 0.18 0.00 2.29 0.70 0.00 0.80 1.29 1.32 1.42

0.00 0.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.25 0.25 0.25 0.40 0.40 0.00 0.10 0.07 0.03 0.03 0.00 0.11 0.02 0.03 0.03 0.03 0.06 0.77 1.61 1.61 1.61 1.61 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.43 0.45 0.44 0.00

91.5 95.8 121.7 115.7 119.2 114.7 107.7 114.3 83.9 105.2 83.6 84.6 93.8 104.8 106.7 88.3 62.7 62.7 62.7 98.0 97.5 98.7 97.5 64.7 61.5 115.5 64.7 64.7 80.6 93.8 93.9 86.7 106.6 106.6 106.6 109.0 109.0 55.5 96.9 74.6 80.9 80.9 84.2 89.9 80.8 85.8 85.8 127.7 118.0 124.0 137.3 137.3 137.3 137.3 65.7 65.7 65.7 77.9 77.9 77.9 81.6 92.2 92.2 161.3 168.2 133.3 137.9 133.3 132.2 168.2 124.1 140.9 172.2 169.6 154.0 154.2 151.9 149.8 166.9

Number Aged 3,524 1,160 3,498 2,427 5,925 481 938 2,138 518 1,131 1,683 1,357 3,172 2,784 436 98 497 497 497 1,592 1,454 1,592 1,592 1,549 1,617 460 3,166 3,166 1,729 2,174 3,903 3,903 403 403 403 496 496 1,267 1,921 3,188 3,188 3,188 1,644 1,697 3,341 3,341 3,341 805 2,088 2,893 0 0 0 0 0 0 0 0 0 0 0 673 673 714 104 950 950 950 632 104 1,704 47 875 713 57 1,821 1,765 1,821 281


+

+ +

+ + + + + +

+ +

+ + + + + + +

+ + +

+ + +

+ * * * * * * * * * * * + + + + + + + + + + +

27,192 18,674 42,613 9,650 116 401 1,465 26,692 584 17,806 1,602 8,580 820 19,753 7,461 0 1,270 667 2,586 1,629 5,629 2,899 66 3,125 12,513 2,297 72 468 14,879 24,244 350 3,273 633 25,352 346 296 1,033 9,769 29,142 736 123 457 14,887 13,180 1,282 44 537 5,435 12,851 25,924 3,312 9,151 4,831 1 4,379 2,338 1,280 53 1,084 932 1,330 3,418 82 4,490 4 16 1,524 67 2,300 1,519 1,691 11 564 3,466 276 296 6,309 31 1,494

297.109 195.022 350.112 83.415 0.976 3.491 13.601 232.215 6.969 167.544 19.164 101.455 9.056 182.450 69.921 0.000 ~ 20.260 10.640 41.259 16.406 57.722 29.047 0.674 49.715 218.740 19.897 1.110 7.238 183.842 278.906 4.012 37.756 5.938 237.877 3.243 2.714 9.474 199.178 350.900 11.819 1.526 5.653 170.573 135.777 14.960 0.519 6.254 40.840 99.593 191.386 24.120 66.643 35.181 0.007 66.650 35.588 19.484 0.678 13.902 11.953 16.304 37.076 0.894 27.842 0.023 0.123 10.454 0.499 17.401 9.034 12.357 0.076 3.278 20.451 1.793 1.895 41.462 0.204 8.948

Appendix 1.2. Age composition and catch by season, fishery and gear type for the Prince Rupert District stock assessment region. These data are used for the age-structured model analysis. Season 19778

19789

19790

19801

19812

19823 19834

19845

19856

19867

19878

19889

19890

19901

19912

19923

19934

19945 19956

Gear

Fishery

0+

1+

Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Trawl Trawl Gillnet Seine Seine Trawl Trawl Gillnet Seine Seine Trawl Trawl Seine Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Trawl Gillnet Seine Seine Trawl Gillnet Seine Seine Trawl Gillnet Seine Trawl Gillnet Seine Gillnet Seine Gillnet

May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.00 0.00 0.00

0.00 1.66 1.35 1.73 1.36 0.99 0.00 1.42 2.91 2.19 2.04 2.04 0.00 1.82 1.69 1.59 0.00 0.00 1.13 0.57 1.07 1.07 0.00 0.83 4.57 2.34 2.34 1.35 1.83 0.43 0.72 0.93 5.59 0.00 17.10 0.33 2.15 2.31 0.00 1.77 1.75 1.69 12.11 12.11 0.00 0.60 0.45 1.06 0.00 0.52 0.52 0.45 0.26 0.00 0.21 0.70 0.00 0.63 0.14 0.00 1.07 0.55 17.05 0.00 0.19 0.70 14.10 0.00 0.04 0.40 6.59 0.00 0.47 3.61 0.00 3.82 0.00 1.08 0.00

P E R C E N T AT 2+ 3+ 4+ 5+ 1.07 7.66 12.58 12.50 10.03 2.97 0.00 9.81 9.88 14.84 9.07 9.07 0.00 62.62 85.42 73.25 47.95 4.98 7.37 10.08 7.67 7.21 0.37 14.25 11.84 11.99 11.85 20.82 34.08 32.79 36.17 36.45 42.86 0.99 8.92 7.91 7.95 7.95 0.36 12.72 12.79 13.34 11.13 11.13 0.38 38.78 39.37 36.99 0.50 35.53 35.53 30.98 13.73 0.24 25.24 19.15 0.00 20.05 14.00 0.00 51.92 40.80 28.41 0.00 45.84 24.97 21.79 0.32 6.28 21.17 31.87 0.00 3.34 4.64 0.00 12.91 0.12 65.37 0.78

2.14 32.30 34.86 38.39 31.95 20.79 20.53 10.85 12.21 11.37 10.37 10.37 8.25 6.88 4.98 7.18 12.33 7.66 53.52 82.32 56.82 55.35 39.18 24.70 7.15 19.03 18.08 17.74 15.42 11.18 14.18 14.29 16.77 1.98 20.45 50.78 50.48 50.46 16.36 10.13 10.09 9.55 9.48 9.48 4.09 9.59 9.51 9.81 2.67 36.87 36.87 38.94 41.19 4.97 29.11 41.92 5.11 21.02 25.59 6.25 9.89 10.75 5.68 4.26 29.44 53.31 20.94 13.21 56.22 25.83 31.32 8.32 10.44 27.84 3.15 5.38 1.18 8.94 4.11

19.93 17.60 9.09 9.35 13.18 19.80 5.96 25.36 32.17 28.12 27.96 27.96 41.24 6.93 2.89 5.79 10.96 35.25 10.15 3.36 8.62 8.89 16.42 45.73 71.51 39.60 40.14 5.26 15.21 9.48 10.77 10.74 9.94 12.87 30.67 11.15 14.31 14.58 14.91 44.29 44.41 46.09 27.58 27.58 54.02 7.26 7.32 7.06 6.37 5.23 5.23 5.97 11.92 4.59 30.29 25.84 30.02 29.59 26.19 21.32 11.11 16.94 22.73 18.67 6.36 5.57 8.97 9.13 21.93 39.41 22.53 40.54 54.82 38.66 18.85 9.57 16.98 2.82 5.68

54.09 16.98 19.63 18.12 19.41 25.74 32.45 19.39 13.57 14.72 15.37 15.37 18.56 7.57 2.29 4.99 16.44 19.92 10.64 1.46 9.09 9.56 23.13 6.01 2.93 10.11 10.37 49.16 10.14 17.31 13.79 13.57 8.70 21.39 12.83 6.74 7.07 7.09 15.82 9.00 9.10 10.53 16.27 16.27 18.86 29.94 29.04 32.66 55.23 7.15 7.15 8.35 11.14 20.02 4.94 4.00 13.98 18.95 24.51 42.46 15.82 17.49 6.82 31.44 5.42 5.34 18.80 23.52 4.18 4.26 2.75 9.53 20.19 20.10 48.99 49.66 34.79 4.26 25.83

51

A G E 6+ 7+ 14.59 13.46 18.84 15.88 17.48 20.79 33.11 17.10 21.32 17.26 15.37 15.37 22.68 5.81 1.69 3.78 1.37 19.54 8.82 1.55 9.02 9.66 14.55 3.80 1.41 6.80 6.94 3.73 19.68 27.38 22.65 21.95 6.21 57.43 4.46 12.95 10.01 9.74 21.82 5.23 5.23 5.26 9.30 9.30 8.71 5.84 5.78 6.01 16.65 11.18 11.18 11.53 11.92 48.56 4.83 4.19 22.91 3.90 3.85 10.29 7.04 11.29 6.82 31.33 7.73 5.23 6.41 25.35 4.46 3.73 3.85 18.52 4.55 2.58 11.78 13.84 39.39 11.72 32.68

6.76 6.21 2.66 2.73 4.37 7.92 6.62 8.63 5.81 6.93 8.52 8.52 7.56 5.21 0.70 2.12 5.48 8.43 4.51 0.32 3.68 4.17 4.48 3.07 0.35 6.60 6.24 1.13 3.04 0.95 1.27 1.30 1.86 3.37 4.28 9.81 7.61 7.41 29.82 8.78 8.69 7.46 5.81 5.81 7.65 3.59 3.72 3.21 9.37 1.59 1.59 1.95 4.40 13.52 4.40 3.39 21.87 3.41 3.58 11.58 1.23 1.82 0.00 6.66 3.60 3.95 4.70 19.66 4.86 3.20 1.10 13.29 4.05 1.55 11.14 2.46 4.13 5.19 26.42

8+

9++

Mean Weight

1.42 2.48 0.67 0.92 1.43 0.99 1.32 4.73 1.74 2.94 7.04 7.04 1.72 2.12 0.30 0.91 4.11 3.45 2.45 0.19 2.37 2.36 1.87 1.13 0.23 2.13 2.42 0.59 0.20 0.33 0.28 0.42 3.73 1.19 0.93 0.19 0.27 0.27 0.36 7.96 7.83 5.98 5.02 5.02 6.06 3.09 3.34 2.31 6.07 1.43 1.43 1.45 4.15 5.31 0.64 0.46 3.66 2.08 1.99 6.07 0.91 0.00 2.27 4.37 0.74 0.46 1.28 3.97 1.59 1.73 0.00 8.19 1.50 1.03 4.86 1.44 1.89 0.37 3.13

0.00 1.66 0.32 0.38 0.79 0.00 0.00 2.71 0.39 1.62 4.26 4.26 0.00 1.04 0.05 0.39 1.37 0.77 1.40 0.13 1.66 1.74 0.00 0.49 0.00 1.39 1.64 0.22 0.41 0.14 0.17 0.34 4.35 0.79 0.37 0.16 0.17 0.17 0.55 0.11 0.11 0.10 3.30 3.30 0.23 1.33 1.47 0.89 3.14 0.49 0.49 0.38 1.30 2.78 0.32 0.36 2.46 0.37 0.14 2.02 1.03 0.36 10.23 3.28 0.67 0.46 2.99 4.83 0.44 0.27 0.00 1.61 0.64 0.00 1.24 0.82 1.53 0.26 1.37

166.9 151.1 147.2 147.1 150.3 167.6 167.1 152.3 158.5 151.3 147.9 147.9 168.4 108.2 90.0 99.0 123.9 162.2 124.7 98.7 119.0 121.0 149.7 128.5 106.5 132.6 132.6 117.7 97.1 106.6 102.7 102.3 93.4 147.7 86.0 108.4 108.3 105.8 147.9 139.2 133.1 137.1 137.9 137.9 147.0 117.1 117.1 117.1 150.4 100.3 100.3 102.6 109.5 157.2 105.0 104.1 149.3 120.7 120.9 146.7 98.8 108.1 110.2 144.5 96.6 96.2 108.5 145.5 103.4 101.3 91.4 134.1 108.9 106.1 132.6 113.1 131.4 89.0 133.8

Number Aged 281 483 812 1,295 1,396 101 151 777 516 1,732 540 540 291 1,049 2,010 4,389 73 261 3,068 3,156 3,095 3,095 268 1,143 853 1,283 1,283 4,583 493 3,118 3,611 3,772 161 505 538 4,214 4,752 4,752 550 3,554 5,655 5,655 1,635 1,635 1,320 2,977 4,049 2,977 1,855 3,076 3,076 4,206 386 710 931 2,893 476 4,215 5,068 544 2,529 549 88 916 4,265 861 234 931 3,262 751 182 745 6,643 194 899 3,532 848 2,697 511

CATCH (tonnes) (millions) +

+ + +

+

+

+ +

+

+ +

+ + + +

+ + + +

+

+

+

+

+

12 2,263 2,202 68 1,024 0 3,031 971 1,411 10 690 0 1,236 460 1,641 278 0 1,046 733 1,051 949 0 356 794 170 1,021 0 0 87 1,679 6 54 0 1,880 48 3,070 70 83 3,476 130 3,823 105 47 0 4,573 47 2,100 52 4,071 23 3,550 56 0 4,340 42 3,686 4,745 2,295 32 2,361 1,348 19 0 2,143 1,377 3 0 3,797 2,204 5 0 4,112 2,364 0 2,324 706 1,355 0 3,086

0.072 14.977 14.957 0.469 6.814 0.000 18.142 6.314 8.905 0.063 4.664 0.000 7.338 4.238 18.223 2.806 0.000 6.449 5.870 10.652 7.928 0.000 2.378 6.481 1.593 7.686 0.000 0.000 0.900 15.337 0.055 0.529 0.000 12.731 0.556 27.724 0.662 0.787 23.500 0.937 27.523 0.778 0.343 0.000 31.100 0.398 17.695 0.448 27.067 0.229 35.399 0.542 0.000 27.459 0.403 35.672 31.739 19.231 0.263 16.100 13.642 0.172 0.000 14.832 14.161 0.027 0.000 26.100 20.895 0.046 0.000 30.661 21.475 0.000 17.614 6.242 10.311 0.000 23.053

~

~

~

~

~ ~

~

~

~

~

~

~

~

~

Appendix 1.2. Age composition and catch by season, fishery and gear type for the Prince Rupert District stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19967

Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Gillnet Seine Gillnet

Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

1.30 0.00 0.19 0.00 0.93 0.00 1.71 0.00 0.53 0.00 5.18 7.21 0.00 0.79 0.07 0.00 0.91 0.88 0.00 0.75 0.00 1.45 0.00

19978 19989 19990 20001 20012

20023

20034

20045 20056

P E R C E N T AT 2+ 3+ 4+ 5+ 22.79 0.16 33.18 0.65 3.39 0.00 24.71 0.12 28.84 0.29 19.99 19.39 0.11 67.83 53.06 0.34 1.98 1.76 0.09 26.59 0.00 16.34 0.00

53.63 19.49 21.98 3.05 51.17 11.18 8.27 2.10 25.30 5.58 36.74 32.03 7.05 13.49 13.44 4.60 69.32 69.88 21.84 8.92 0.80 44.33 2.77

8.01 11.57 36.29 43.07 20.68 16.22 36.25 23.06 5.65 9.33 18.99 20.34 20.25 11.10 14.53 37.13 11.20 10.58 13.52 45.51 46.42 8.80 7.11

2.52 13.95 4.44 20.52 17.76 48.98 14.34 20.47 23.85 32.40 3.93 4.16 11.72 3.13 9.54 25.98 10.06 9.88 36.88 9.21 18.04 22.99 59.88

A G E 6+ 7+ 4.93 20.29 1.42 9.89 2.92 13.23 11.83 42.17 9.15 20.67 9.56 11.12 27.42 1.52 2.97 10.57 4.20 4.45 15.40 6.06 25.86 3.90 15.22

4.74 20.60 1.09 11.28 0.47 4.72 1.99 9.37 5.34 25.58 3.51 3.83 15.81 1.15 4.24 12.30 0.91 0.97 4.92 2.02 5.84 1.60 13.64

8+

9++

Mean Weight

1.85 11.09 1.28 7.02 1.17 2.20 0.41 1.11 1.14 5.29 1.79 1.60 15.36 0.48 1.47 5.29 1.27 1.39 4.74 0.52 1.33 0.45 1.38

0.22 2.85 0.14 4.53 1.52 3.46 0.49 1.60 0.22 0.87 0.30 0.33 2.28 0.51 0.68 3.79 0.16 0.19 2.60 0.42 1.72 0.15 0.00

88.5 133.4 83.2 127.9 105.5 126.1 95.9 133.7 103.9 134.3 90.3 93.0 143.2 85.1 95.3 136.6 93.7 96.0 134.5 92.8 134.5 87.1 128.4


52

Number Aged 2,698 631 2,116 1,082 856 721 3,685 811 2,285 1,040 5,577 + 3,678 879 659 + 2,925 870 2,526 + 2,155 1,117 2,129 754 2,001 506

CATCH (tonnes) (millions) 0 5,541 0 3,217 256 1,858 1,314 3,001 1,012 1,905 1 2,061 2,432 5 1,446 2,562 11 1,908 2,192 1,750 2,050 956 1,661

0.000 ~ 41.550 0.000 ~ 25.158 2.426 14.716 12.980 22.441 9.743 14.183 0.009 22.159 16.982 0.068 15.169 18.760 0.116 19.885 16.304 18.855 15.239 10.975 12.942

Appendix 1.3. Age composition and catch by season, fishery and gear type for the Central Coast stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19501

Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Seine Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Seine Gillnet Seine Seine Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet

Oct-Dec Jan-Apr Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Oct-Dec May-Sep Oct-Dec Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr

0.00 0.06 0.25 1.11 0.43 0.15 0.00 0.07 0.29 0.00 0.10 0.00 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00

2.68 2.25 4.61 5.12 7.65 7.31 1.72 4.04 9.94 1.31 13.79 7.39 16.97 52.32 3.59 23.13 40.38 5.67 47.57 5.25 0.74 42.87 41.51 64.30 4.30 16.18 16.18 7.65 3.73 7.65 0.36 0.35 14.03 4.88 14.03 14.03 14.07 3.62 8.49 67.32 67.32 67.32 37.40 37.40 37.40 32.53 32.53 32.53 54.02 12.04 3.54 0.00 0.97 1.21 0.00 2.94 0.00 0.99 0.00 2.18 0.00 0.70 0.00 0.19 0.18 0.00 5.70 5.70 5.59 5.59 0.00 1.88 3.78 0.28 0.61 0.61 0.00

19512 19523 19534

19545 19556

19567

19578

19589 19590 19601

19612

19623 19634

19645

19656

19667

19678

19690 19701 19712 19723

19734 19745 19756 19767 19778

19789 19790

19801

19812

P E R C E N T AT 2+ 3+ 4+ 5+ 28.09 31.20 20.10 19.85 28.02 69.86 72.02 69.18 6.32 5.42 13.63 12.21 13.60 42.90 52.30 49.84 49.69 73.61 42.11 49.47 47.39 24.11 23.53 28.81 32.64 32.43 32.43 54.80 51.28 54.80 30.27 30.14 46.96 43.06 46.96 46.96 37.58 35.16 36.46 20.43 20.43 20.43 46.19 46.19 46.19 48.02 48.02 48.02 44.42 39.34 28.25 2.27 48.51 49.64 4.04 20.26 0.42 48.84 4.27 11.33 0.86 17.01 1.10 28.64 29.21 0.83 4.40 4.40 69.33 69.33 5.36 14.92 14.57 1.47 11.52 11.52 2.88

50.52 49.36 29.98 29.75 24.49 17.41 21.04 20.52 77.40 80.39 11.05 8.70 9.12 3.83 13.98 9.53 8.01 17.35 7.27 35.94 40.66 26.16 27.72 3.34 12.80 10.82 10.82 20.82 25.17 20.82 58.03 58.19 27.37 35.48 27.37 27.37 31.01 37.44 33.62 7.33 7.33 7.33 13.10 13.10 13.10 17.02 17.02 17.02 1.16 39.20 27.13 18.18 18.90 18.40 28.28 42.18 22.36 22.87 26.40 41.86 18.72 23.32 13.02 16.47 16.70 8.45 31.50 31.50 6.94 6.94 0.89 68.45 63.82 47.46 10.17 10.17 6.96

12.28 11.23 38.50 37.71 27.28 3.99 3.91 4.63 5.10 11.08 58.24 67.86 56.99 0.55 8.33 5.03 1.33 1.50 2.01 7.43 9.62 5.59 5.86 2.30 36.63 29.70 29.70 2.85 2.80 2.85 5.25 5.18 10.09 14.65 10.09 10.09 12.10 17.59 15.63 3.60 3.60 3.60 2.04 2.04 2.04 2.11 2.11 2.11 0.40 4.11 27.01 61.36 16.23 15.98 43.43 18.05 38.82 19.00 45.60 21.86 30.18 31.11 35.54 21.54 21.83 32.10 18.70 18.70 9.48 9.48 34.82 7.06 7.83 12.43 66.35 66.35 76.07

5.17 4.84 4.56 4.45 10.25 1.06 1.10 1.34 0.48 1.56 2.85 3.36 2.89 0.27 20.79 11.85 0.17 1.22 0.42 0.61 0.72 1.10 1.22 1.25 12.48 9.92 9.92 11.39 13.99 11.39 2.86 2.86 1.45 1.80 1.45 1.45 5.03 5.77 5.41 1.13 1.13 1.13 1.02 1.02 1.02 0.25 0.25 0.25 0.00 4.33 7.57 11.36 12.72 12.11 21.21 10.26 24.47 5.33 15.73 16.69 35.12 17.06 31.57 21.13 20.76 38.26 21.30 21.30 4.51 4.51 21.43 4.98 6.03 15.35 5.52 5.52 7.38

53

A G E 6+ 7+ 1.20 1.06 1.55 1.52 1.40 0.15 0.15 0.16 0.48 0.25 0.25 0.43 0.34 0.14 0.98 0.59 0.42 0.65 0.62 0.57 0.52 0.08 0.08 0.00 0.94 0.79 0.79 2.31 2.80 2.31 3.02 3.07 0.09 0.13 0.09 0.09 0.18 0.39 0.33 0.19 0.19 0.19 0.17 0.17 0.17 0.00 0.00 0.00 0.00 0.72 5.17 6.82 2.02 2.02 2.02 5.42 12.24 2.25 5.60 4.31 11.56 8.70 13.47 8.68 8.28 16.57 15.10 15.10 2.87 2.87 18.75 1.95 2.80 12.78 4.26 4.26 5.17

0.06 0.01 0.40 0.44 0.48 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.04 0.00 0.03 0.02 0.00 0.00 0.00 0.55 0.35 0.08 0.08 0.00 0.16 0.11 0.11 0.18 0.23 0.18 0.21 0.21 0.00 0.00 0.00 0.00 0.03 0.03 0.06 0.00 0.00 0.00 0.07 0.07 0.07 0.06 0.06 0.06 0.00 0.06 1.26 0.00 0.47 0.48 1.01 0.71 1.69 0.48 2.40 1.52 3.02 1.72 3.97 2.56 2.38 3.21 2.80 2.80 0.72 0.72 11.61 0.44 0.67 6.94 1.26 1.26 1.20

8+

9++

Mean Weight

0.00 0.00 0.04 0.04 0.00 0.08 0.06 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.05 0.04 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.00 0.00 0.00 0.00 0.13 0.08 0.00 0.19 0.16 0.00 0.18 0.00 0.04 0.00 0.24 0.44 0.34 1.32 0.59 0.50 0.44 0.40 0.40 0.42 0.42 6.25 0.29 0.36 2.48 0.30 0.30 0.33

0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.00 0.02 0.09 0.05 0.00 0.20 0.17 0.15 0.10 0.10 0.09 0.09 0.89 0.04 0.13 0.82 0.00 0.00 0.01

109.2 107.9 112.7 112.3 104.9 63.6 76.2 71.1 85.4 99.8 91.4 114.2 105.4 60.1 93.9 79.6 61.5 73.8 64.8 83.4 88.2 62.1 63.7 51.4 100.6 91.1 91.1 94.1 99.6 94.1 100.6 100.6 91.1 103.4 91.1 91.1 114.4 122.3 111.9 71.9 71.9 71.9 87.0 87.0 87.0 89.8 89.8 89.8 73.9 108.2 120.5 159.6 125.2 124.7 152.8 129.5 158.5 119.5 152.8 124.4 162.0 136.6 167.7 129.6 124.6 162.1 151.8 151.8 91.4 91.4 157.9 101.3 99.2 142.5 131.9 131.9 141.3

Number Aged 3,175 2,143 5,214 5,214 2,939 1,327 1,739 3,066 826 1,524 2,408 2,614 5,022 732 3,890 4,622 2,106 1,472 3,578 2,169 2,594 1,269 1,313 479 2,302 2,781 2,781 562 429 562 1,052 1,052 1,169 778 1,169 1,169 1,750 1,652 1,750 0 0 0 0 0 0 0 0 0 0 953 1,763 44 1,239 1,239 99 1,515 474 8,923 375 5,418 1,222 2,606 453 1,391 1,391 886 0 0 3,345 3,345 112 5,210 5,210 1,418 2,300 2,300 1,242


+

+

+

+

+

+

+ + + + + + + + + + * * * * * * * * * *

+ + +

+

+ * * + + +

+

15,508 26,950 33,072 123 768 6,389 18,119 109 2,559 9,035 22,335 21,018 275 1,788 21,002 470 4,928 4,454 467 10,774 17,096 3,397 640 956 30,641 104 4 677 14,942 90 124 43,930 3,214 28,288 165 228 1,562 12,630 1,477 16,217 19,101 2,163 2,910 17,206 1,774 497 309 722 209 3,614 9,143 137 6,664 22 1,113 3,621 5,267 3,343 5,395 6,198 6,213 4,201 6,904 4,723 46 9,277 0 5 10 0 528 263 6 2,304 2,258 0 4,112

141.986 250.936 290.690 1.091 7.304 100.473 243.703 1.531 28.033 90.856 208.767 178.311 2.606 29.756 211.756 5.669 79.258 60.180 8.141 125.789 192.788 54.675 10.054 18.581 302.709 1.136 0.042 7.197 150.045 0.954 1.232 436.570 35.288 273.620 1.808 2.507 14.266 101.310 12.553 225.703 265.835 30.107 33.432 197.668 20.378 5.535 3.439 8.043 2.832 32.684 74.425 0.855 52.842 0.178 7.288 28.835 33.230 31.457 35.308 50.662 38.357 30.702 41.171 37.629 0.369 56.466 0.001 0.031 0.111 0.000 ~ 3.347 2.570 0.063 15.892 17.116 0.003 29.155

Appendix 1.3. Age composition and catch by season, fishery and gear type for the Central Coast stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19823

Seine Gillnet Seine Gillnet Seine Gillnet Seine Seine Trawl Gillnet Seine Gillnet Seine Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Seine Seine

Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.58 0.00 2.29 0.00 0.61 0.00 4.00 0.94 4.00 0.00 4.13 0.00 0.82 0.81 0.00 0.84 0.00 0.81 0.00 1.76 0.00 0.94 0.00 3.37 0.00 0.87 0.00 0.58 0.00 12.82 0.00 2.20 0.00 0.52 0.00 0.38 0.00 0.19 0.00 2.00 0.00 4.71 0.00 0.09 0.00 1.27 0.67 0.75

19834 19845 19856

19867 19878

19889 19890 19901 19912 19923 19934 19945 19956 19967 19978 19989 19990 20001 20012 20023 20034 20045 20056

P E R C E N T AT 2+ 3+ 4+ 5+ 7.06 0.56 5.47 0.27 28.72 3.78 16.21 14.64 16.21 2.01 20.03 0.82 65.84 65.96 4.39 3.72 0.32 3.55 0.00 16.48 0.56 60.91 6.87 7.06 0.20 18.91 1.73 5.12 0.23 18.28 0.39 56.77 1.36 30.62 0.44 8.37 0.13 17.02 0.44 6.90 0.00 33.86 0.60 30.97 0.43 6.44 32.35 9.86

13.65 7.56 7.67 2.69 8.11 6.27 39.67 41.12 39.67 21.83 13.26 7.75 12.35 12.42 10.69 79.59 29.13 5.07 1.03 7.41 2.41 10.17 6.96 63.75 45.74 7.17 5.09 22.95 8.93 5.03 1.55 15.70 2.92 41.30 13.09 39.70 15.27 10.47 2.04 24.68 4.87 9.81 5.95 24.46 3.57 65.95 17.80 54.21

11.15 13.82 17.73 12.49 9.89 9.37 8.61 10.95 8.61 14.45 32.77 44.85 6.16 6.14 15.27 8.59 25.73 74.01 68.15 6.52 6.30 2.47 4.42 9.66 14.12 56.09 66.34 9.25 8.00 16.68 18.33 3.46 6.23 7.99 12.55 34.48 45.02 33.07 40.44 12.46 5.75 15.67 20.83 9.95 11.14 16.06 35.63 9.95

58.16 68.06 17.04 16.84 17.28 20.63 6.41 5.12 6.41 7.98 5.60 11.72 8.30 8.29 27.48 2.79 17.31 7.47 16.46 56.72 69.81 2.95 6.98 1.85 5.43 7.93 12.30 49.46 64.84 7.26 11.88 6.65 22.76 2.46 8.50 7.66 17.80 28.97 41.61 25.29 52.75 6.41 7.54 12.93 25.73 2.98 8.73 20.12

A G E 6+ 7+ 5.32 5.22 47.03 61.49 14.48 23.57 6.74 6.40 6.74 14.53 5.06 7.85 1.73 1.66 13.74 2.28 14.72 3.93 5.46 6.70 9.44 19.02 60.93 2.41 5.88 2.09 3.27 6.30 10.67 31.17 53.07 4.27 19.26 6.42 18.31 2.22 6.24 6.40 10.36 21.72 28.13 19.55 47.02 5.79 11.24 3.46 1.75 3.39

3.13 3.93 1.93 4.63 20.15 35.09 6.12 6.55 6.12 14.47 6.71 9.89 1.71 1.73 7.06 0.60 5.34 3.48 6.48 2.34 7.04 2.03 9.67 10.22 25.47 3.02 4.00 2.18 1.79 5.89 10.48 8.66 38.33 5.30 16.51 2.89 5.31 1.46 1.61 5.20 7.12 8.17 16.47 11.12 33.08 1.74 1.49 0.97

8+

9++

Mean Weight

0.64 0.62 0.69 1.07 0.49 0.85 11.63 13.85 11.63 24.18 5.11 8.15 1.68 1.66 9.73 0.87 3.72 0.81 1.10 1.70 3.52 0.79 2.99 1.24 2.48 3.51 6.51 2.34 2.23 1.57 1.97 1.70 7.20 4.48 22.13 2.74 5.44 1.17 0.88 1.21 1.13 1.56 1.39 3.98 12.32 1.67 1.12 0.70

0.31 0.23 0.14 0.53 0.26 0.44 0.62 0.43 0.62 0.56 7.33 8.97 1.40 1.34 11.64 0.71 3.72 0.85 1.32 0.36 0.93 0.72 1.19 0.43 0.67 0.42 0.77 1.81 3.31 1.31 2.33 0.58 1.95 0.90 8.46 1.55 4.78 1.26 2.63 0.54 0.25 0.26 0.20 0.72 2.49 0.43 0.45 0.04

134.7 146.7 128.0 145.1 136.5 161.3 135.0 138.7 135.0 155.5 143.9 165.2 107.5 110.9 162.2 112.1 147.9 131.1 144.7 133.9 154.7 107.2 155.5 112.3 138.9 118.7 133.8 127.0 137.4 124.2 146.4 94.3 143.5 97.1 140.4 100.2 128.8 109.3 133.0 119.7 135.3 98.5 128.6 104.9 143.2 96.1 92.2 89.6


54

Number Aged 5,445 1,703 6,294 1,092 3,690 1,507 5,995 + 3,983 5,995 + 1,020 3,614 981 4,159 2,835 + 524 4,321 618 6,843 806 7,107 540 7,264 1,119 6,939 781 6,174 1,951 8,932 1,267 4,087 566 5,235 514 1,339 1,031 3,861 753 2,624 685 1,653 800 3,164 504 2,212 925 2,094 2,680 2,271

CATCH (tonnes) (millions) 2,061 3,579 3,589 3,582 2,915 2,294 30 2,173 7 1,176 2,695 920 3,539 18 970 6,531 2,911 5,305 3,046 7,097 1,806 7,251 1,111 8,478 2,038 9,757 2,122 8,131 1,451 3,897 402 3,276 344 7,963 639 5,940 1,524 6,440 926 5,613 517 2,894 399 2,299 289 2,987 3,779 3,072

15.154 24.422 28.383 24.536 20.337 14.082 0.224 16.047 0.054 7.676 18.225 5.571 31.909 0.162 5.978 61.253 19.680 39.561 20.978 52.412 11.673 66.620 6.991 75.838 14.682 81.704 15.809 64.167 10.565 32.478 2.743 34.713 2.401 81.986 4.483 58.064 11.833 55.631 6.963 46.878 3.822 29.155 3.099 21.911 2.021 30.986 40.991 34.266

Appendix 1.4. Age composition and catch by season, fishery and gear type for the Strait of Georgia stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19501

Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Seine Seine Seine Trawl Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl Seine Seine Seine Trawl Trawl

Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Oct-Dec Jan-Apr Oct-Dec Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr

0.03 0.06 0.04 0.11 0.16 0.03 0.00 0.10 0.14 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.12 0.00 0.00 0.00 0.00 0.00 0.74 0.86 0.00 1.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.06 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

4.32 4.40 3.46 14.85 21.32 5.73 0.00 1.72 3.79 2.60 1.58 5.91 1.12 2.17 1.78 1.36 3.92 3.50 4.65 4.65 8.57 4.07 4.10 0.13 5.52 18.62 0.73 1.42 3.46 2.24 10.67 9.97 9.00 12.72 24.49 13.95 14.21 25.55 19.81 24.49 6.80 23.34 10.10 40.17 31.62 0.16 38.75 38.75 9.92 13.01 9.42 9.56 9.56 13.94 31.58 16.74 16.73 16.73 4.30 5.19 3.41 5.41 5.41 20.04 20.49 16.35 14.53 14.53 17.20 17.20 17.20 17.20 17.20 36.90 36.90 36.90 36.90 36.90

19512

19523

19534

19545

19556

19567

19578

19589

19590

19601

19612

19623

19634

19645

19656

19667

P E R C E N T AT 2+ 3+ 4+ 5+ 58.19 32.64 61.00 55.11 49.53 55.51 50.26 54.76 65.35 55.66 63.29 67.27 53.97 43.19 22.05 52.67 56.38 22.26 49.87 50.12 57.14 52.03 14.20 9.76 58.00 44.38 64.78 64.96 18.92 71.93 60.24 61.67 60.10 73.29 53.06 66.31 65.57 57.59 59.43 53.06 54.12 50.24 51.47 30.91 24.51 28.79 35.27 35.27 71.21 67.90 71.71 71.49 71.49 52.76 47.44 51.99 53.03 53.03 63.37 60.54 49.27 60.55 60.55 54.60 50.36 55.51 56.86 56.86 38.00 38.00 38.00 38.00 38.00 45.72 45.72 45.72 45.72 45.72

28.93 48.59 26.57 21.73 21.11 29.95 36.79 38.77 27.05 37.08 30.79 23.62 36.36 41.52 37.29 36.83 33.92 60.88 38.62 38.35 25.71 30.65 29.99 43.52 26.95 24.62 20.31 21.83 40.97 14.15 20.45 16.52 21.06 11.64 18.37 15.95 16.41 10.98 18.10 18.37 35.60 24.15 34.80 22.59 25.79 22.54 19.59 19.59 12.79 10.71 13.00 12.85 12.85 29.55 15.39 27.11 26.51 26.51 29.55 31.14 36.83 30.91 30.91 22.98 25.51 25.09 25.79 25.79 25.14 25.14 25.14 25.14 25.14 12.18 12.18 12.18 12.18 12.18

6.71 10.65 7.12 6.50 6.19 7.19 9.84 3.97 2.97 3.71 3.68 2.60 6.83 8.91 26.45 7.07 5.18 11.00 5.95 5.99 8.57 11.30 41.94 26.32 8.19 10.24 9.37 7.50 25.30 4.60 3.60 4.36 3.99 1.88 0.00 2.34 2.29 3.72 1.14 0.00 2.93 2.11 3.07 5.84 16.10 26.29 6.24 6.24 4.02 5.23 3.96 4.11 4.11 3.49 2.88 3.19 2.73 2.73 2.20 2.58 6.34 2.58 2.58 2.07 2.46 2.26 2.14 2.14 15.88 15.88 15.88 15.88 15.88 3.21 3.21 3.21 3.21 3.21

1.40 2.76 1.25 1.32 1.52 1.34 2.59 0.52 0.62 0.63 0.66 0.60 1.38 3.32 8.79 1.66 0.52 2.22 0.82 0.80 0.00 1.65 7.87 17.07 1.05 1.91 4.25 3.97 9.95 5.66 3.20 3.66 3.20 0.45 2.04 0.39 0.39 1.52 0.00 2.04 0.36 0.00 0.36 0.50 1.87 19.56 0.15 0.15 1.72 2.56 1.57 1.59 1.59 0.19 1.78 1.26 0.65 0.65 0.47 0.40 3.17 0.40 0.40 0.28 1.14 0.77 0.61 0.61 2.65 2.65 2.65 2.65 2.65 1.59 1.59 1.59 1.59 1.59

55

A G E 6+ 7+ 0.30 0.62 0.43 0.28 0.11 0.20 0.52 0.07 0.07 0.09 0.00 0.00 0.27 0.70 2.98 0.33 0.09 0.15 0.10 0.10 0.00 0.29 1.37 2.44 0.29 0.23 0.51 0.31 1.08 0.94 1.64 3.24 2.30 0.01 0.00 0.21 0.21 0.27 0.00 0.00 0.09 0.16 0.10 0.00 0.11 2.35 0.00 0.00 0.33 0.60 0.32 0.35 0.35 0.04 0.72 0.49 0.25 0.25 0.05 0.03 0.73 0.03 0.03 0.00 0.23 0.67 0.03 0.03 1.13 1.13 1.13 1.13 1.13 0.29 0.29 0.29 0.29 0.29

0.10 0.23 0.12 0.08 0.05 0.05 0.00 0.10 0.00 0.07 0.00 0.00 0.06 0.18 0.60 0.08 0.00 0.00 0.00 0.00 0.00 0.00 0.43 0.64 0.00 0.00 0.04 0.00 0.11 0.24 0.15 0.49 0.30 0.01 2.04 0.10 0.06 0.29 0.00 2.04 0.07 0.00 0.08 0.00 0.00 0.31 0.00 0.00 0.00 0.00 0.02 0.04 0.04 0.04 0.35 0.10 0.10 0.10 0.07 0.06 0.24 0.06 0.06 0.03 0.00 0.04 0.03 0.03 0.00 0.00 0.00 0.00 0.00 0.05 0.05 0.05 0.05 0.05

8+

9++

Mean Weight

0.02 0.06 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.07 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.00 0.00 0.00 0.00 0.00 0.11 0.00 0.04 0.09 0.05 0.00 0.00 0.01 0.01 0.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.06 0.06 0.06 0.06

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.13 0.00 0.00 0.00 0.00 0.11 0.12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

99.6 103.6 99.5 93.0 91.8 97.0 115.6 87.1 81.0 84.6 88.4 78.0 96.0 94.5 119.9 95.7 98.5 85.6 94.5 95.8 84.7 97.4 109.1 125.5 93.7 85.7 96.2 95.7 129.9 91.7 88.8 90.1 88.9 74.8 76.1 83.5 82.4 79.4 70.9 76.1 98.1 79.8 95.7 88.0 80.6 114.2 85.8 85.8 88.8 87.8 88.8 89.0 89.0 86.6 82.2 83.3 84.5 84.5 103.4 105.7 99.2 103.4 103.4 103.0 104.3 104.0 104.3 104.3 120.4 120.4 120.4 120.4 120.4 91.6 91.6 91.6 91.6 91.6

Number Aged 7,816 1,774 7,816 8,839 8,839 8,839 193 3,810 5,220 9,030 760 999 9,693 3,618 3,374 9,788 4,028 896 4,924 4,994 70 3,783 4,816 779 1,050 2,197 4,691 826 925 848 3,085 1,850 4,935 527 49 7,169 7,215 1,506 525 49 3,323 617 3,940 2,248 1,145 639 689 689 2,824 2,824 2,824 2,824 2,824 1,596 1,874 1,874 2,014 2,014 3,255 3,255 410 3,255 3,255 2,555 2,939 2,939 2,939 2,939 529 529 529 529 529 0 0 0 0 0

CATCH (tonnes) (millions) + + + +

+

+ +

+ +

+

+

+

+

+ + + + + + + + + + + + + + + + + + + + * * * * *

42,180 1,226 393 44,896 423 527 0 3,750 3,966 442 29 225 57,443 619 7,692 14 50,604 13,825 4,207 5 0 44,043 26,375 1,462 182 0 44,241 8,202 7,165 0 11,745 6,982 1,206 695 0 47,601 146 1,897 0 381 67,866 149 23 25,847 9,335 9,119 1,328 586 53,725 36 10,747 785 9 56,900 5,014 6,685 200 47 65,538 878 10,153 105 208 39,050 5,453 3,266 36 14 27,909 4,216 1,165 25 18 28,090 1,694 1,193 1 65

424.795 11.828 3.923 492.871 4.847 5.222 0.000 41.452 48.795 5.059 0.326 2.888 595.913 6.600 62.447 0.142 503.361 161.566 43.919 0.054 0.000 451.810 243.982 11.648 1.944 0.000 460.767 84.577 55.146 0.000 133.517 84.814 13.597 9.491 0.000 575.751 1.770 23.636 0.000 5.002 685.617 1.863 0.237 303.907 115.270 79.855 15.472 6.822 602.612 0.412 120.280 8.818 0.106 651.147 71.016 78.835 2.372 0.562 626.573 8.440 102.385 1.016 2.011 388.413 54.899 31.893 0.349 0.132 231.771 35.012 9.673 0.211 0.146 306.795 18.499 13.031 0.008 0.707

~

~

~

~

~

~


Gear

Fishery

0+

1+

19678

Seine Seine Seine Trawl Seine Seine Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Gillnet Seine Seine Trawl Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Gillnet Seine Seine Seine Trawl Trawl Gillnet Gillnet Seine Seine Seine Trawl Trawl Gillnet Gillnet Gillnet Seine Seine Seine Trawl Trawl Gillnet

Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.35 0.43 0.35 0.35 0.35 0.00 0.00 0.06 0.00 0.01 0.01 0.00 0.00 0.08 0.09 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.36 1.00 1.00 0.00 0.06 0.00 0.03 0.03 0.03 0.00 0.62 0.06 0.36 0.36 0.36 0.00 0.06 0.00 0.06 0.03 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.30 0.00 0.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.26 0.26 0.00

30.37 30.37 30.37 30.37 25.64 25.64 25.64 25.64 12.33 13.36 12.33 12.33 12.33 4.58 4.58 12.78 5.69 4.41 8.60 5.92 3.37 1.98 3.35 1.89 1.89 0.00 0.00 16.29 16.29 16.83 0.00 5.07 3.87 5.07 5.07 0.00 7.34 5.95 7.45 7.28 7.28 0.00 6.52 3.39 3.76 3.76 3.76 0.00 2.53 0.42 2.25 1.31 1.31 0.00 0.00 1.62 3.01 2.25 1.04 2.34 0.00 0.00 2.02 4.54 4.03 3.30 3.31 0.00 0.00 0.00 4.38 6.17 4.80 4.36 4.36 0.09

19690

19701

19712

19723

19734

19745

19756

19756 19767

19778

19789

19790

19801

P E R C E N T AT 2+ 3+ 4+ 5+ 50.62 50.62 50.62 50.62 60.32 60.32 60.32 60.32 40.03 41.17 40.03 40.03 40.03 11.75 11.75 32.57 32.75 29.73 34.61 11.45 50.48 36.48 39.83 31.61 31.61 17.41 17.41 60.29 60.29 61.15 3.74 54.83 57.31 54.83 54.83 4.88 23.01 20.35 21.69 21.54 21.54 0.54 56.39 52.68 52.98 52.98 52.98 3.50 36.75 34.65 36.56 35.05 35.05 0.37 0.37 17.91 23.91 20.19 17.08 21.31 1.15 1.25 42.12 41.60 43.30 46.70 49.04 1.52 1.52 1.52 33.94 34.93 38.21 39.15 39.15 2.19

14.68 14.68 14.68 14.68 9.49 9.49 9.49 9.49 36.36 34.74 36.36 36.36 36.36 46.61 46.61 33.30 36.27 34.98 33.23 45.25 20.94 29.31 27.62 30.52 30.52 30.36 30.36 17.53 17.53 17.24 43.04 26.49 27.80 26.49 26.49 46.34 40.08 46.41 41.20 41.65 41.65 42.00 19.55 22.31 21.04 21.04 21.04 27.75 40.07 42.60 39.10 42.37 42.37 20.33 20.33 38.42 33.51 36.76 39.67 33.82 23.14 22.00 22.71 20.45 19.97 22.21 22.17 9.89 9.89 9.89 34.26 30.73 36.28 29.90 29.90 18.16

3.04 3.04 3.04 3.04 3.27 3.27 3.27 3.27 7.12 7.01 7.12 7.12 7.12 28.49 28.49 16.53 19.69 23.32 18.40 28.69 18.35 20.75 19.68 23.07 23.07 37.50 37.50 4.19 4.19 3.42 32.01 7.34 7.04 7.34 7.34 32.32 20.31 19.28 20.01 19.99 19.99 43.88 12.05 16.46 15.51 15.51 15.51 47.32 9.39 13.62 10.46 11.19 11.19 30.50 30.50 27.23 25.54 25.68 29.98 29.30 54.68 55.02 18.78 20.27 19.34 15.90 14.65 44.49 44.49 44.49 14.82 11.93 10.06 13.16 13.16 22.98

0.88 0.88 0.88 0.88 0.72 0.72 0.72 0.72 2.82 2.58 2.82 2.82 2.82 6.77 6.77 3.36 4.21 6.08 3.79 6.90 5.39 10.01 7.90 11.01 11.01 11.16 11.16 1.47 1.47 1.23 17.56 3.17 2.49 3.17 3.17 12.80 5.57 5.46 5.53 5.44 5.44 10.28 3.06 3.70 4.16 4.16 4.16 16.68 7.18 7.09 7.84 7.52 7.52 36.04 36.04 8.82 7.92 8.39 8.28 8.39 13.77 14.11 9.35 9.00 8.73 8.60 7.90 34.22 34.22 34.22 8.57 10.58 7.77 7.76 7.76 37.37

56

A G E 6+ 7+ 0.18 0.18 0.18 0.18 0.56 0.56 0.56 0.56 0.92 0.67 0.92 0.92 0.92 1.49 1.49 1.21 1.29 1.39 1.17 1.65 0.91 1.24 1.15 1.51 1.51 3.13 3.13 0.11 0.11 0.14 3.21 1.50 0.77 1.50 1.50 3.05 2.38 1.60 2.57 2.59 2.59 2.70 0.95 0.86 1.25 1.25 1.25 4.08 3.08 1.22 2.83 1.95 1.95 10.91 10.91 4.77 3.91 4.95 2.76 3.55 5.54 5.74 2.56 2.55 2.59 2.01 1.78 8.75 8.75 8.75 3.14 4.58 2.22 3.57 3.57 16.05

0.23 0.23 0.23 0.23 0.00 0.00 0.00 0.00 0.07 0.04 0.07 0.07 0.07 0.20 0.20 0.12 0.09 0.09 0.17 0.14 0.45 0.14 0.33 0.26 0.26 0.45 0.45 0.11 0.11 0.00 0.43 0.44 0.23 0.44 0.44 0.61 0.79 0.71 1.04 1.01 1.01 0.40 0.66 0.42 0.62 0.62 0.62 0.54 0.56 0.32 0.57 0.34 0.34 1.48 1.48 1.01 1.48 1.27 1.04 0.56 1.53 1.66 1.54 1.29 1.42 1.29 1.15 0.76 0.76 0.76 0.66 0.67 0.46 1.13 1.13 2.81

8+

9++

Mean Weight

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.06 0.01 0.01 0.02 0.00 0.11 0.01 0.05 0.03 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.18 0.13 0.18 0.18 0.00 0.43 0.20 0.40 0.39 0.39 0.20 0.19 0.03 0.20 0.20 0.20 0.15 0.35 0.00 0.27 0.15 0.15 0.37 0.37 0.15 0.43 0.31 0.07 0.48 0.00 0.00 0.47 0.25 0.37 0.00 0.00 0.38 0.38 0.38 0.21 0.37 0.15 0.61 0.61 0.26

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.04 0.07 0.07 0.07 0.00 0.01 0.09 0.12 0.12 0.12 0.00 0.03 0.08 0.06 0.08 0.08 0.00 0.00 0.08 0.29 0.20 0.07 0.24 0.19 0.21 0.15 0.05 0.11 0.00 0.00 0.00 0.00 0.00 0.02 0.04 0.03 0.09 0.09 0.09

94.8 94.8 94.8 94.8 95.5 95.5 95.5 95.5 114.8 113.9 114.8 114.8 114.8 140.1 140.1 126.0 113.1 117.3 114.9 139.8 120.6 130.3 124.1 130.6 130.6 133.4 133.4 77.8 77.8 72.2 157.1 97.1 98.1 97.1 97.1 150.1 122.7 109.9 119.8 120.3 120.3 148.8 107.2 105.5 106.5 106.5 106.5 150.3 110.2 105.6 106.3 107.9 107.9 148.9 148.9 126.5 117.7 120.8 125.5 121.0 153.5 153.8 114.6 100.2 102.3 108.4 107.1 148.7 148.7 148.7 116.5 99.9 96.4 111.0 111.0 152.1

Number Aged 0 0 0 0 0 0 0 0 1,419 1,419 1,419 1,419 1,419 1,004 1,004 2,340 7,062 9,402 9,402 1,004 1,071 4,643 5,714 5,777 5,777 224 224 884 884 731 924 5,685 5,685 5,685 5,685 164 3,494 2,254 5,748 5,918 5,918 786 1,828 3,200 5,028 5,028 5,028 1,658 1,984 3,516 5,500 5,891 5,891 541 541 2,433 2,095 4,528 1,341 1,239 523 523 3,063 7,664 10,727 698 785 263 263 263 6,355 12,461 18,816 1,147 1,147 1,140

CATCH (tonnes) (millions) * * * * * * * * + + + + + +

+ +

+ + + + + + +

+ + + +

+ + +

+ + +

+ + + +

+

+

+ + + + +

+ +

1,031 58 700 101 1 220 0 22 588 857 66 95 4 40 44 1,017 7,240 98 0 456 256 5,161 167 1 0 6 2,057 842 62 5 3,095 218 575 55 1 5,331 4,313 834 28 3 86 6,975 616 8,257 25 73 802 7,736 10,648 3,919 30 1,792 296 63 7,253 10,046 54 71 2,734 607 7 6,818 1,188 903 52 242 254 0 3,177 2 4,152 2,133 79 501 121 5,067

10.881 0.616 7.390 1.061 0.007 2.299 0.004 0.230 5.118 7.672 0.577 0.828 0.032 0.286 0.311 8.277 63.276 0.815 0.002 3.275 2.082 41.003 1.351 0.008 0.000 0.048 15.421 10.833 0.795 0.064 19.692 2.243 5.995 0.564 0.006 35.526 35.358 7.166 0.238 0.021 0.711 46.818 5.836 78.397 0.236 0.683 7.534 51.507 96.197 36.641 0.287 16.618 2.746 0.425 48.694 79.075 0.461 0.587 21.790 5.018 0.048 44.171 10.051 9.224 0.514 2.234 2.373 0.001 21.367 0.017 34.800 19.819 0.813 4.510 1.087 33.319


Gear

Fishery

0+

1+

19812

Seine Seine Seine Trawl Trawl Gillnet Gillnet Seine Seine Seine Trawl Trawl Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Trawl Trawl Gillnet Seine Seine Seine Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Seine Gillnet Seine Seine Seine Gillnet Seine Seine Seine Gillnet Seine Seine Seine

Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.21 0.00 0.15 0.12 0.12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.05 0.05 0.05 0.00 0.10 0.03 0.03 0.03 0.00 0.41 0.00 0.07 0.06 0.06 0.00 0.00 0.00 0.01 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.00 0.00 0.49 0.06 0.08

5.36 7.65 3.86 2.19 2.19 0.00 0.00 3.37 3.36 10.91 1.59 1.59 1.59 0.00 19.24 4.70 10.57 11.35 11.35 0.00 32.93 23.09 24.05 25.68 25.68 0.09 0.09 14.33 9.76 13.71 13.71 13.71 0.00 23.34 2.73 11.92 11.82 0.00 6.52 2.35 4.82 4.74 4.74 0.00 26.15 12.31 12.64 12.64 12.64 0.00 6.68 10.09 7.51 0.00 13.89 3.82 10.74 10.74 0.00 3.96 3.62 4.95 4.95 0.00 26.95 11.22 16.80 0.00 5.65 3.72 4.74 0.07 20.87 7.09 11.65 0.00 29.31 9.29 14.92

19823

19834

19845

19845

19856

19867

19878

19889

19890

19901

19912

19923

19934

19945

19956

P E R C E N T AT 2+ 3+ 4+ 5+ 39.98 37.90 35.45 46.35 46.35 4.60 4.58 34.06 31.41 42.05 19.36 19.36 19.36 0.49 36.34 40.35 39.21 38.18 38.18 7.14 37.34 43.51 45.04 43.11 43.11 3.10 3.10 62.24 55.76 56.73 56.73 56.73 2.50 34.77 32.98 35.91 33.27 3.01 64.47 52.89 61.90 61.47 61.47 9.20 17.44 15.17 17.97 17.97 17.97 1.60 58.62 57.87 56.71 8.93 31.24 21.09 23.31 23.31 1.29 67.09 53.63 56.44 56.44 6.33 31.11 39.18 36.80 11.47 50.00 42.96 42.74 3.65 27.81 21.21 22.69 2.10 46.92 47.72 48.51

31.38 23.33 28.47 30.29 30.29 15.77 15.96 30.39 28.72 22.39 35.99 35.99 35.99 27.76 21.19 31.85 27.00 26.45 26.45 30.29 18.72 19.33 18.72 18.61 18.61 26.09 26.09 17.57 24.98 21.10 21.10 21.10 35.62 30.50 38.23 34.11 35.95 38.33 14.59 17.58 14.59 14.71 14.71 14.81 42.75 51.91 51.78 51.78 51.78 40.43 12.72 8.23 11.25 11.71 38.58 44.52 39.87 39.87 28.15 17.24 14.96 14.07 14.07 14.88 31.47 33.15 31.55 40.02 25.43 26.98 26.61 25.26 36.05 37.04 35.69 27.82 11.70 15.20 13.72

14.07 19.46 21.36 15.51 15.51 30.37 30.56 16.43 17.68 12.44 17.54 17.54 17.54 29.48 13.02 11.86 12.16 12.59 12.59 30.95 6.75 8.62 7.69 7.60 7.60 32.48 32.48 4.40 6.45 5.75 5.75 5.75 33.44 8.84 19.76 13.52 14.21 32.48 11.38 20.29 13.99 14.27 14.27 47.81 6.77 10.87 8.95 8.95 8.95 21.42 17.67 17.43 19.33 56.04 7.67 10.27 8.80 8.80 17.20 9.27 17.44 15.80 15.80 43.63 6.97 7.57 6.87 16.98 16.30 19.34 18.59 44.78 10.01 18.67 16.39 38.15 8.84 15.88 13.62

4.96 4.51 4.56 2.74 2.74 15.82 15.11 8.12 11.49 7.63 12.07 12.07 12.07 23.59 6.01 6.31 6.30 6.62 6.62 19.05 2.89 3.55 2.83 3.21 3.21 23.63 23.63 1.27 2.06 1.79 1.79 1.79 16.51 1.75 4.32 3.16 3.23 15.47 1.81 5.27 3.51 3.60 3.60 20.09 5.90 7.93 6.86 6.86 6.86 26.02 2.26 3.59 2.97 12.10 7.42 16.08 13.78 13.78 40.11 1.31 4.04 3.22 3.22 11.72 2.56 5.77 5.28 21.61 1.52 3.70 3.81 15.21 4.44 11.51 9.89 24.14 1.78 6.74 5.27

57

A G E 6+ 7+ 3.31 4.57 4.30 1.64 1.64 20.42 20.88 2.93 3.16 1.95 3.87 3.87 3.87 9.34 2.80 3.10 3.13 3.17 3.17 9.39 0.91 1.27 1.19 1.20 1.20 9.22 9.22 0.17 0.80 0.70 0.70 0.70 8.49 0.46 1.22 0.96 0.99 7.35 0.55 1.31 0.87 0.90 0.90 5.27 0.82 1.48 1.47 1.47 1.47 7.99 2.05 2.27 1.81 9.44 1.04 2.48 2.05 2.05 7.27 0.56 5.34 4.63 4.63 18.91 0.26 1.37 1.20 4.08 1.09 2.65 2.69 7.83 0.68 2.92 2.37 5.10 0.87 3.87 3.01

0.83 2.11 1.74 0.91 0.91 11.58 11.71 3.00 2.78 1.76 5.01 5.01 5.01 7.37 0.64 1.27 0.95 0.95 0.95 1.59 0.34 0.55 0.42 0.51 0.51 3.74 3.74 0.02 0.12 0.12 0.12 0.12 2.60 0.23 0.45 0.27 0.34 2.55 0.15 0.21 0.18 0.19 0.19 2.24 0.16 0.27 0.28 0.28 0.28 2.26 0.00 0.40 0.34 1.41 0.16 1.47 1.27 1.27 4.69 0.56 0.59 0.58 0.58 2.65 0.58 1.63 1.32 5.40 0.00 0.53 0.65 2.42 0.11 1.13 0.93 2.10 0.08 0.86 0.61

8+

9++

Mean Weight

0.06 0.40 0.22 0.00 0.00 1.03 0.85 1.43 1.16 0.72 3.87 3.87 3.87 1.72 0.34 0.44 0.39 0.41 0.41 0.66 0.11 0.07 0.05 0.06 0.06 0.82 0.82 0.00 0.08 0.06 0.06 0.06 0.57 0.00 0.19 0.08 0.11 0.60 0.11 0.10 0.06 0.06 0.06 0.34 0.00 0.04 0.03 0.03 0.03 0.28 0.00 0.07 0.06 0.30 0.00 0.24 0.17 0.17 1.20 0.00 0.38 0.28 0.28 1.45 0.11 0.06 0.14 0.22 0.00 0.13 0.14 0.62 0.00 0.35 0.29 0.30 0.00 0.27 0.19

0.06 0.06 0.04 0.36 0.36 0.41 0.34 0.26 0.24 0.14 0.68 0.68 0.68 0.25 0.22 0.11 0.14 0.16 0.16 0.93 0.00 0.00 0.01 0.01 0.01 0.82 0.82 0.00 0.00 0.00 0.00 0.00 0.26 0.00 0.10 0.05 0.05 0.21 0.00 0.00 0.00 0.00 0.00 0.22 0.00 0.03 0.01 0.01 0.01 0.00 0.00 0.06 0.01 0.06 0.00 0.03 0.02 0.02 0.09 0.00 0.00 0.02 0.02 0.43 0.00 0.06 0.03 0.22 0.00 0.00 0.00 0.16 0.02 0.08 0.10 0.30 0.00 0.11 0.07

121.1 104.8 106.8 119.5 119.5 150.9 151.6 116.0 113.5 109.6 144.1 144.1 144.1 152.8 108.4 103.8 105.9 106.6 106.6 142.9 101.9 90.8 90.3 93.7 93.7 147.4 147.4 103.3 94.7 95.2 95.2 95.2 145.1 104.8 97.6 94.2 98.6 145.3 106.4 104.0 99.7 100.5 100.5 144.4 109.1 104.6 102.2 102.2 102.2 140.3 101.3 100.2 97.4 141.6 107.5 109.4 108.1 108.1 146.0 103.6 105.6 104.1 104.1 147.6 98.6 101.3 99.6 137.9 101.3 97.2 97.4 133.7 102.9 110.4 107.9 139.6 85.9 98.2 95.1

Number Aged 3,876 5,332 9,208 548 548 589 589 5,296 13,007 18,303 439 439 439 407 3,634 7,318 10,952 10,952 10,952 756 2,528 8,187 10,715 10,799 10,799 1,096 1,096 1,390 6,773 8,163 8,163 8,163 1,920 1,148 7,957 9,105 9,105 1,920 1,632 6,338 7,970 7,970 7,970 891 1,252 6,517 7,769 7,769 7,769 823 928 5,915 6,843 1,371 698 5,291 5,989 5,989 1,087 641 5,036 5,677 5,677 1,169 973 5,445 6,418 907 460 5,969 6,429 1,201 1,130 5,754 6,884 927 1,662 8,243 9,905

CATCH (tonnes) (millions) + + +

+

+

+ + +

+ + + +

+ + + +

+ +

+ + +

+ + +

+

+ +

+ +

+

+

+

+

3,337 3,324 74 414 101 5,583 0 632 7,798 57 115 0 2 8,613 444 4,137 88 113 214 6,039 409 2,770 88 20 246 0 3,495 209 178 40 46 120 0 104 3,133 41 76 5,998 357 1,475 33 83 279 5,988 728 1,446 56 134 86 5,919 75 96 62 7,886 371 1,141 58 122 9,410 639 3,725 57 128 8,870 516 4,396 96 8,733 866 5,138 71 11,572 604 4,362 33 8,190 397 7,434 10

27.503 30.103 0.690 3.464 0.843 37.004 0.001 4.809 69.556 0.568 0.797 0.000 ~ 0.017 56.381 3.882 41.098 0.843 1.056 2.011 42.246 3.904 29.011 0.975 0.218 2.630 0.002 23.718 2.004 1.844 0.426 0.481 1.257 0.000 0.984 32.258 0.431 0.768 41.166 3.386 13.516 0.333 0.826 2.773 41.461 6.660 13.339 0.547 1.308 0.844 42.236 0.736 0.936 0.632 55.630 3.440 10.217 0.541 1.133 64.461 6.140 34.318 0.550 1.229 60.081 5.272 42.070 0.968 63.326 8.549 52.868 0.730 86.661 5.865 38.990 0.306 58.655 4.650 73.620 0.106

Appendix 1.4. Age composition and catch by season, fishery and gear type for the Strait of Georgia stock assessment region. These data are used for the age-structured model analysis. Season 19967

19978

19989

19990

20001

20012

20023

20034

20045

20056

Gear

Fishery

0+

1+

Trawl Gillnet Seine Seine Seine Gillnet Seine Seine Trawl Gillnet Seine Seine Trawl Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet

Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr

0.08 0.00 3.29 0.00 0.65 0.00 0.00 0.02 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.33 0.07 0.00

14.92 0.00 9.71 5.52 8.74 0.00 3.96 2.93 7.01 0.00 12.30 4.23 5.49 0.00 21.12 9.62 0.00 9.66 4.80 0.00 4.96 6.59 0.00 2.80 2.67 0.00 11.24 2.90 0.00 9.02 4.00 0.00 23.95 16.89 0.00

P E R C E N T AT 2+ 3+ 4+ 5+ 48.51 4.05 54.01 51.35 52.26 4.74 48.07 47.03 45.19 1.54 27.77 22.78 31.87 2.15 50.16 35.44 1.07 51.94 42.65 3.55 61.42 49.18 5.83 44.16 42.62 2.29 30.77 25.39 1.74 31.32 23.82 0.88 30.75 24.93 0.62

13.72 15.87 21.40 24.45 22.45 17.85 40.23 31.80 37.03 26.20 43.17 45.02 30.77 29.31 16.69 19.34 13.75 27.98 30.65 17.75 26.19 27.04 20.78 42.29 36.58 22.38 40.04 41.55 21.39 28.33 31.66 12.91 23.55 24.50 12.22

13.62 44.53 5.31 6.54 5.78 16.43 6.40 12.25 8.16 28.32 13.35 18.55 21.98 36.72 8.74 23.92 44.56 5.52 9.52 25.59 5.93 12.45 30.42 8.41 12.64 31.05 14.00 22.29 37.02 20.85 28.26 46.61 11.93 18.98 35.80

5.27 22.08 5.27 7.43 6.09 31.91 0.91 2.90 1.14 15.61 2.74 6.58 7.69 21.05 2.39 8.81 28.68 3.51 9.19 35.06 0.97 2.35 17.69 2.10 4.03 23.83 3.55 5.65 23.98 7.92 8.73 24.07 7.30 11.05 33.54

A G E 6+ 7+ 3.01 10.30 2.24 2.84 2.41 17.06 0.34 2.14 0.98 18.69 0.37 1.88 1.10 6.70 0.89 2.12 9.59 1.25 2.52 15.09 0.32 1.99 21.01 0.23 0.93 9.87 0.39 1.54 11.72 1.94 2.30 10.28 1.88 2.44 14.70

0.61 2.11 1.24 1.70 1.42 8.53 0.08 0.70 0.16 7.13 0.13 0.78 0.00 3.35 0.00 0.36 1.92 0.00 0.55 2.37 0.11 0.40 3.54 0.00 0.41 7.34 0.00 0.43 2.51 0.44 0.85 3.72 0.83 0.89 2.49

8+

9++

Mean Weight

0.19 0.84 0.14 0.12 0.13 2.53 0.00 0.21 0.33 1.54 0.00 0.13 1.10 0.60 0.00 0.28 0.43 0.13 0.09 0.30 0.00 0.00 0.49 0.00 0.10 2.65 0.00 0.25 1.49 0.10 0.28 1.31 0.31 0.21 0.62

0.07 0.21 0.16 0.04 0.07 0.95 0.00 0.03 0.00 0.96 0.00 0.06 0.00 0.12 0.00 0.02 0.00 0.00 0.02 0.30 0.11 0.00 0.24 0.00 0.00 0.60 0.00 0.00 0.14 0.03 0.09 0.22 0.01 0.04 0.00

95.1 138.2 88.1 88.8 91.7 136.7 86.1 86.8 74.3 130.4 91.3 100.0 92.3 130.8 75.0 92.2 135.1 95.6 97.3 133.4 87.0 87.7 131.8 91.9 87.2 131.6 83.1 83.1 124.0 87.7 95.6 130.6 79.5 84.5 129.8


58

Number Aged 9,905 544 7,667 7,297 7,667 633 1,288 5,837 613 519 1,297 3,192 91 836 1,077 5,042 938 797 4,558 676 928 4,475 915 428 7,293 831 507 1,707 1,185 5,135 3,174 457 4,891 2,824 810

CATCH (tonnes) (millions) + + +

+

+

39 6,233 279 9,390 7 6,148 954 5,755 0 6,895 1,471 4,976 0 6,837 1,156 6,454 7,593 1,423 7,275 7,682 1,328 9,299 7,986 1,696 10,670 8,010 1,356 7,019 5,226 1,332 7,929 8,954 1,371 9,308 7,277

0.406 45.214 3.120 96.287 0.071 44.974 11.072 66.260 0.000 ~ 52.858 16.123 49.748 0.000 ~ 52.248 15.363 69.966 56.219 14.897 74.770 57.589 15.265 106.015 60.800 18.466 122.311 60.889 16.316 79.437 41.630 15.157 82.942 68.542 17.913 110.102 56.028

Appendix 1.5. Age composition and catch by season, fishery and gear type for the West Coast Vancouver Island stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19501

Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Seine Seine Seine Seine Seine Seine Seine Trawl Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Seine Gillnet Seine Trawl Gillnet Seine Trawl Gillnet Seine Gillnet Gillnet Seine Seine Seine Trawl Trawl Trawl Gillnet Seine Seine Seine Trawl Gillnet Seine Seine Gillnet Seine Seine Gillnet Seine Seine Gillnet

Oct-Dec Jan-Apr Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr May-Sep Jan-Apr Oct-Dec Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr Jan-Apr May-Sep Jan-Apr

0.10 0.00 0.11 0.00 0.16 0.05 0.00 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

15.78 10.19 6.62 0.33 11.77 1.61 4.43 19.64 10.86 13.43 9.21 2.86 2.74 2.72 15.18 13.04 3.26 3.28 10.00 8.92 8.92 38.31 38.31 38.31 4.82 5.32 4.82 1.99 2.47 1.64 0.95 2.78 2.78 2.78 13.59 13.59 13.59 12.86 12.86 12.86 5.77 3.66 0.21 0.00 5.71 0.00 0.44 0.60 0.00 0.20 0.47 0.00 0.39 0.60 0.60 0.00 0.77 0.80 0.80 0.80 0.80 0.00 0.81 1.07 0.81 0.81 0.00 7.13 6.21 0.00 3.89 2.83 0.00 4.32 3.27 0.00

19512 19523 19534 19545 19556 19567

19578 19589

19590 19601

19612

19623 19634 19645

19656

19667

19701 19712 19723 19734 19745

19756

19767

19778

19778

19789

19790

19801

19812

P E R C E N T AT 2+ 3+ 4+ 5+ 39.08 36.69 61.99 12.08 57.76 61.40 65.53 57.81 65.09 67.98 49.51 71.84 71.92 71.94 54.28 52.03 45.21 19.68 58.10 54.85 54.85 37.97 37.97 37.97 82.29 80.46 82.29 43.18 41.39 60.61 65.05 34.38 34.37 34.37 26.83 26.83 26.83 60.28 60.28 60.28 44.57 19.01 25.15 8.81 43.66 29.87 51.61 53.85 2.90 8.31 14.55 0.68 11.51 3.61 3.61 31.00 39.43 41.49 41.63 41.63 41.63 1.42 13.91 14.94 13.91 13.91 1.05 37.93 43.91 0.00 32.52 27.39 1.78 24.84 23.96 0.70

37.78 43.89 20.85 27.32 28.08 29.42 24.81 18.59 20.01 14.82 19.28 24.69 24.81 24.83 25.87 25.41 29.96 23.88 9.50 23.26 23.26 19.15 19.15 19.15 9.63 10.07 9.63 48.71 49.75 25.86 22.91 48.44 48.44 48.44 26.12 26.12 26.12 20.52 20.52 20.52 36.95 50.10 23.05 23.56 22.09 27.92 19.95 19.75 32.37 48.06 54.46 41.72 32.16 17.47 17.47 23.75 18.78 19.07 19.02 19.02 19.02 5.45 50.09 51.51 50.09 50.09 24.79 13.75 15.58 5.31 33.31 22.26 21.00 28.55 27.41 12.02

5.35 7.69 9.27 50.77 1.67 6.70 4.06 3.27 3.47 3.09 17.88 0.41 0.35 0.34 3.98 5.47 14.51 26.94 19.00 8.64 8.64 4.41 4.41 4.41 2.41 3.10 2.41 5.16 5.41 10.83 10.00 10.07 10.07 10.07 23.17 23.17 23.17 4.84 4.84 4.84 7.85 21.81 35.64 51.44 15.14 27.92 12.00 11.36 36.51 19.79 18.78 34.00 38.00 43.37 43.37 15.00 16.78 15.66 15.66 15.66 15.66 21.33 14.23 13.82 14.23 14.23 28.57 20.24 20.00 52.51 10.62 14.13 14.95 22.53 26.05 44.25

1.56 1.25 0.89 6.88 0.50 0.59 0.83 0.64 0.52 0.50 3.68 0.20 0.18 0.17 0.47 2.30 3.46 9.15 2.60 2.81 2.81 0.17 0.17 0.17 0.86 1.05 0.86 0.75 0.71 0.77 0.85 3.99 3.99 3.99 9.07 9.07 9.07 1.15 1.15 1.15 2.77 3.39 13.81 12.23 10.96 10.39 8.70 8.01 19.92 12.97 6.10 14.77 12.43 16.87 16.87 22.50 18.80 17.60 17.52 17.52 17.52 49.05 10.79 9.87 10.79 10.79 23.74 8.99 6.37 22.35 13.65 17.84 36.30 5.50 5.45 11.67

59

A G E 6+ 7+ 0.26 0.30 0.27 2.08 0.05 0.12 0.21 0.00 0.05 0.16 0.11 0.00 0.00 0.00 0.17 1.35 1.82 7.94 0.50 0.95 0.95 0.00 0.00 0.00 0.00 0.00 0.00 0.21 0.27 0.29 0.25 0.35 0.35 0.35 1.23 1.23 1.23 0.18 0.18 0.18 1.62 1.23 1.89 3.06 2.32 3.90 5.71 4.96 7.88 7.65 5.16 5.92 3.89 11.14 11.14 4.25 4.14 3.85 3.85 3.85 3.85 17.54 7.94 7.04 7.94 7.94 18.07 8.11 5.30 12.01 4.07 8.83 18.86 7.92 9.51 27.53

0.05 0.00 0.00 0.48 0.00 0.12 0.04 0.00 0.00 0.02 0.11 0.00 0.00 0.00 0.04 0.34 1.45 6.52 0.20 0.35 0.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.46 0.79 0.17 0.72 0.12 0.00 1.38 1.28 0.41 2.57 0.47 2.50 1.42 5.12 5.12 1.50 1.10 1.18 1.18 1.18 1.18 4.74 1.60 1.43 1.60 1.60 3.15 3.14 2.20 7.26 1.51 4.77 7.12 3.73 2.72 3.31

8+

9++

Mean Weight

0.05 0.00 0.00 0.06 0.00 0.00 0.04 0.00 0.00 0.00 0.22 0.00 0.00 0.00 0.01 0.07 0.33 1.99 0.10 0.14 0.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.02 0.00 0.03 0.08 0.18 0.00 0.00 0.18 0.17 0.00 0.43 0.00 0.33 0.16 1.51 1.51 1.00 0.17 0.23 0.23 0.23 0.23 0.24 0.52 0.26 0.52 0.52 0.42 0.48 0.35 0.28 0.37 1.41 0.00 2.04 1.36 0.35

0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.62 0.00 0.07 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.08 0.03 0.30 0.30 1.00 0.04 0.11 0.11 0.11 0.11 0.24 0.11 0.06 0.11 0.11 0.21 0.23 0.08 0.28 0.05 0.53 0.00 0.58 0.27 0.17

96.8 99.3 98.9 123.8 82.4 95.6 87.2 87.6 80.9 87.4 87.2 86.4 86.4 86.4 76.8 78.3 92.2 99.6 97.6 95.7 95.7 85.5 85.5 85.5 93.2 92.8 93.2 101.3 101.0 103.4 101.0 122.5 122.5 122.5 137.0 137.0 137.0 114.9 114.9 114.9 132.8 135.3 139.1 159.4 114.9 133.5 124.6 122.5 169.0 140.0 131.6 150.2 136.7 154.2 154.2 127.3 109.2 111.9 111.8 111.8 111.8 157.6 124.5 123.1 124.5 124.5 161.5 110.8 108.2 163.6 116.1 133.6 148.6 120.4 115.9 137.0

Number Aged 1,927 2,112 996 3,897 3,764 3,655 2,439 1,723 754 3,730 923 490 588 588 1,480 1,480 2,843 751 0 2,846 2,846 590 590 590 1,163 1,117 1,163 1,862 1,633 1,107 769 576 576 576 0 0 0 0 0 0 433 1,482 2,556 556 5,221 154 10,038 10,038 241 9,230 213 1,199 6,684 332 332 400 7,454 7,854 7,898 7,898 7,898 422 3,689 3,689 3,689 3,689 476 3,735 3,735 358 5,026 566 281 4,775 4,775 574


+ + + +

*

+ + + + + + + + + * * * * * *

+ + +

+ +

+ + + + + + +

+ +

+ +

7,670 14,151 8,251 18,757 20 23,534 9,675 4,650 1,473 15,310 1,787 1,690 915 8 513 43 55,196 13,845 182 53,911 0 16,711 9,679 44 5,951 17,710 24 3,184 15,022 2,952 18,313 68 10,397 5,582 4,299 6,471 73 2,965 9,794 2,385 0 6,894 16,766 1,537 12,394 3,940 17,798 0 8,310 22,820 0 16,005 17,463 12,556 24 303 7,615 7 51 3 11 14,755 70 10,473 4 9 8,138 1,682 0 2,300 5,008 2 3,079 2,370 2 3,115

79.266 143.353 83.215 146.019 0.242 245.938 109.814 53.117 18.369 175.972 20.496 19.549 10.586 0.088 6.766 0.551 588.911 136.204 1.868 563.328 0.000 ~ 195.384 113.162 0.520 63.821 190.890 0.253 31.449 148.723 28.550 182.208 0.553 84.858 45.559 31.377 47.228 0.535 25.811 85.253 20.760 0.000 ~ 51.001 117.326 9.642 109.083 29.517 142.327 0.004 49.159 162.893 0.000 ~ 106.418 126.700 81.452 0.154 2.379 67.761 0.066 0.456 0.023 0.101 93.615 0.563 86.211 0.032 0.073 50.388 14.641 0.000 14.061 44.277 0.015 20.725 19.713 0.013 22.741

Appendix 1.5. Age composition and catch by season, fishery and gear type for the West Coast Vancouver Island stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19823

Seine Gillnet Seine Gillnet Seine Seine Seine Seine Seine Trawl Gillnet Seine Trawl Gillnet Seine Trawl Gillnet Seine Gillnet Seine Gillnet Seine Trawl Gillnet Seine Seine Trawl Trawl Trawl Gillnet Seine Trawl Trawl Seine Trawl Trawl Seine Seine Gillnet Seine Gillnet Seine Gillnet Seine Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine

Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr May-Sep Jan-Apr Jan-Apr Oct-Dec May-Sep Jan-Apr Oct-Dec May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

3.83 0.00 23.09 0.00 6.28 20.47 3.78 3.86 16.21 26.98 0.00 1.60 3.03 0.00 3.06 0.00 0.00 0.46 0.00 6.15 0.00 1.47 3.45 0.00 3.46 3.85 3.00 6.41 0.79 0.16 1.02 1.17 2.57 17.06 14.66 14.66 3.65 2.40 0.00 1.39 0.00 7.85 0.00 7.02 4.14 0.00 1.13 0.00 1.32 0.00 1.09 0.00 15.08

19834 19845 19856 19867

19878

19889

19890 19901 19912

19923 19934

19945

19956

19967 19978 19989 19990 20001 20012 20023 20034 20045 20056

P E R C E N T AT 2+ 3+ 4+ 5+ 19.37 0.35 37.97 1.68 48.74 53.62 50.45 48.16 16.21 26.03 1.82 63.80 59.09 5.38 14.96 14.29 0.20 26.32 1.35 19.13 3.26 43.29 31.03 6.29 26.25 18.47 22.74 25.64 26.11 5.65 13.98 13.32 34.57 22.43 22.14 22.14 70.44 21.91 0.86 21.95 0.82 24.06 1.28 45.66 51.73 0.00 38.66 2.61 13.73 0.79 33.21 0.80 37.26

23.62 14.19 13.00 6.72 22.86 14.22 29.70 27.50 36.29 28.57 24.55 7.41 19.70 7.10 61.92 63.10 54.50 11.72 7.87 22.02 6.84 10.77 20.69 13.49 39.83 22.30 24.13 37.18 29.11 32.10 21.55 25.60 29.07 12.83 12.66 12.66 8.47 61.07 41.37 23.61 9.98 19.88 7.52 20.20 22.77 10.28 39.14 17.43 52.30 28.37 23.84 10.80 33.54

23.39 23.82 8.86 17.98 6.40 3.71 8.29 10.68 18.16 13.65 61.82 14.70 15.15 41.29 7.11 10.71 11.00 48.79 68.99 10.60 12.70 14.97 26.44 30.76 7.14 31.82 30.04 12.82 26.58 54.84 19.83 20.52 10.02 15.22 19.38 19.38 4.17 6.56 10.51 39.60 60.36 17.32 27.04 8.38 9.91 28.79 14.95 31.86 22.60 24.41 27.65 49.80 7.89

16.69 44.83 9.48 32.61 5.12 2.74 3.13 3.83 7.70 1.59 5.45 8.38 3.03 28.60 8.47 9.52 22.30 4.89 8.31 35.06 64.50 6.62 2.30 13.85 8.29 8.69 8.00 12.82 7.91 5.32 27.32 25.29 13.75 12.76 12.53 12.53 5.11 2.75 10.55 8.41 18.46 25.46 52.80 7.57 3.00 15.33 2.87 19.84 7.34 25.04 9.92 23.80 5.37

60

A G E 6+ 7+ 4.60 6.48 5.52 31.93 6.21 3.17 2.24 2.92 2.56 0.95 2.18 2.75 0.00 12.90 3.45 2.38 9.40 5.99 10.34 2.99 6.84 18.95 10.34 29.86 4.57 6.19 5.00 3.85 5.38 1.13 7.46 6.44 4.52 14.03 13.75 13.75 4.02 2.40 14.67 2.67 5.32 3.65 6.24 9.44 4.36 20.56 1.45 9.82 1.89 14.58 3.45 10.60 0.78

5.45 9.81 0.88 5.38 3.47 1.70 1.76 2.21 1.38 1.90 2.91 0.65 0.00 3.01 0.79 0.00 1.60 1.53 2.47 3.39 8.14 2.42 2.30 2.88 8.71 6.58 5.26 0.00 2.85 0.65 4.66 4.02 3.93 3.39 2.82 2.82 3.18 1.65 12.41 1.29 3.35 1.07 2.56 1.32 3.73 22.43 0.88 12.83 0.51 3.80 0.60 3.80 0.09

8+

9++

Mean Weight

1.50 0.35 1.00 3.36 0.37 0.13 0.58 0.74 1.15 0.32 0.91 0.48 0.00 1.29 0.17 0.00 1.00 0.27 0.67 0.64 6.52 1.26 2.30 2.52 1.08 1.84 1.58 1.28 1.11 0.16 3.26 2.89 1.57 1.42 1.25 1.25 0.63 0.98 6.33 0.73 1.48 0.58 2.24 0.21 0.36 2.24 0.79 5.01 0.27 2.22 0.12 0.20 0.00

1.55 0.18 0.19 0.34 0.55 0.23 0.07 0.11 0.34 0.00 0.36 0.23 0.00 0.43 0.07 0.00 0.00 0.03 0.00 0.02 0.00 0.26 1.15 0.36 0.66 0.27 0.24 0.00 0.16 0.00 0.93 0.75 0.00 0.86 0.81 0.81 0.32 0.29 3.29 0.33 0.24 0.13 0.32 0.21 0.00 0.37 0.11 0.60 0.03 0.79 0.12 0.20 0.00

131.3 137.8 114.9 154.9 120.1 109.0 121.5 124.3 130.8 93.9 171.3 127.5 92.9 166.9 126.4 127.4 151.0 139.4 155.6 130.8 175.5 132.2 105.6 154.2 126.9 125.3 124.7 92.4 97.1 131.1 139.0 135.6 105.9 119.3 119.5 119.5 98.6 99.1 138.6 110.5 135.7 115.1 145.2 105.3 103.0 152.3 105.7 146.7 104.1 137.2 100.5 127.5 78.8

Number Aged 3,188 571 3,079 595 2,995 2,995 4,151 2,847 3,480 315 550 4,883 66 465 4,178 84 382 3,720 445 5,715 307 4,290 87 556 4,705 6,196 6,274 78 632 620 5,392 7,086 574 5,394 8,255 8,255 6,539 6,098 899 4,341 1,043 6,613 625 2,352 2,200 535 4,309 499 2,956 631 1,653 500 1,154


+ +

+

+

+

+

+ +

6,141 2,434 5,718 858 177 1 1 203 13,463 0 2,471 8,276 0 1,448 9,774 0 3,515 7,890 1,959 6,299 2,336 3,086 0 627 5,612 5,332 0 0 1 706 1,947 1 3 790 1 0 6,656 5,449 1,550 3,407 963 926 700 0 433 388 2,571 945 3,861 593 3,373 896 0

45.840 17.662 49.965 5.540 1.352 0.008 0.005 1.633 102.956 0.000 14.431 67.129 0.000 8.674 77.304 0.000 23.274 56.611 12.593 47.096 13.308 23.337 0.000 4.066 44.244 42.481 0.001 0.000 0.008 5.381 14.006 0.005 0.029 6.607 0.006 0.000 67.506 55.784 11.177 31.759 7.098 8.308 4.823 0.000 4.204 2.550 24.345 6.444 37.106 4.324 33.573 7.032 0.000

~

~

~

~

~

~

~

Appendix 1.6. Age composition and catch by season, fishery and gear type for the Area 27 stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19534 19545

Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Seine Gillnet Gillnet Seine Seine Seine Seine Seine Seine Seine Seine Seine Gillnet Seine Gillnet Seine Trawl Seine Trawl Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine

Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Oct-Dec Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr May-Sep Jan-Apr May-Sep Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

2.56 2.77 6.80 4.12 38.31 4.82 1.99 1.33 2.51 13.59 13.59 20.71 19.86 8.03 8.03 0.00 0.81 0.00 0.82 0.00 7.17 6.28 2.08 4.30 0.60 0.00 3.96 0.00 0.00 2.21 17.02 2.16 0.21 1.84 6.71 8.94 1.30 11.30 0.00 1.48 0.00 1.29 1.68 10.19 10.19 4.01 1.39 7.76 2.30 6.63 7.49 0.52 1.30 0.56 0.00

19589 19601 19612 19623 19634 19645 19656 19667 19701 19734 19756 19778 19789 19790 19801 19812 19823 19834 19856 19867 19878 19889 19890 19901 19912 19923 19934 19945 19956 19967 19978 19989 19990 20001 20012 20023 20034 20045 20056

P E R C E N T AT 2+ 3+ 4+ 5+ 62.55 35.29 34.77 44.71 37.97 82.29 43.18 59.98 31.20 26.83 26.83 55.46 30.14 43.12 43.12 1.03 41.60 1.42 13.88 0.93 82.08 46.56 13.73 34.23 30.57 0.63 20.79 0.31 0.00 23.62 27.66 62.53 12.66 22.68 22.27 39.30 66.59 35.79 3.28 31.75 1.28 6.83 6.37 24.60 24.60 76.83 38.89 28.03 54.36 20.92 62.74 51.13 21.50 54.19 0.00

28.12 52.50 49.72 27.63 19.15 9.63 48.71 26.04 46.10 26.12 26.12 16.68 40.41 23.94 23.94 41.48 18.95 5.45 50.49 27.43 8.96 15.12 60.33 32.33 8.73 11.62 31.68 13.52 4.17 63.47 15.96 11.05 57.51 14.25 20.52 8.94 13.39 38.93 53.28 24.55 19.40 30.93 35.29 7.91 7.91 7.32 48.61 33.82 24.20 35.71 15.63 37.09 54.15 24.02 0.00

5.74 7.55 6.94 14.44 4.41 2.41 5.16 11.56 14.62 23.17 23.17 3.43 4.79 13.56 13.56 32.92 15.70 21.33 14.19 27.61 1.43 18.71 8.74 9.78 47.59 44.58 10.89 22.73 42.13 2.58 35.46 6.20 8.15 39.63 10.65 10.30 4.27 5.02 14.09 30.90 61.19 27.19 24.37 20.91 20.91 1.57 4.86 24.87 9.65 12.76 10.06 6.24 19.69 12.85 0.00

0.69 1.48 1.42 3.90 0.17 0.86 0.75 0.83 4.60 9.07 9.07 0.80 2.05 8.83 8.83 15.35 17.59 49.05 10.61 23.32 0.00 5.93 13.59 12.20 4.07 11.77 28.71 47.00 16.67 1.48 1.06 15.36 8.37 5.83 32.59 22.49 3.20 1.57 7.92 5.50 9.81 25.26 24.65 17.75 17.75 4.01 0.35 4.08 7.50 12.24 0.64 3.99 1.04 7.26 0.00

61

A G E 6+ 7+ 0.19 0.33 0.28 2.45 0.00 0.00 0.21 0.25 0.42 1.23 1.23 0.26 1.37 2.23 2.23 6.05 3.84 17.54 7.80 17.35 0.00 4.93 1.53 4.73 7.53 27.63 0.00 5.99 33.33 1.85 0.00 1.62 11.37 7.13 2.99 2.71 7.11 1.41 7.53 2.12 3.41 5.28 4.13 14.76 14.76 4.70 2.78 0.53 1.23 9.69 2.36 0.17 1.55 0.56 0.00

0.08 0.08 0.07 2.06 0.00 0.00 0.00 0.00 0.28 0.00 0.00 0.19 0.68 0.22 0.22 2.80 1.17 4.74 1.59 2.80 0.36 2.07 0.00 1.79 0.75 3.30 3.96 9.98 2.55 2.58 1.06 0.81 1.29 7.78 3.50 4.88 1.42 5.02 11.58 2.86 3.84 1.55 1.33 3.16 3.16 1.57 2.43 0.53 0.15 1.02 0.86 0.69 0.78 0.56 0.00

8+

9++

Mean Weight

0.02 0.00 0.00 0.58 0.00 0.00 0.00 0.00 0.28 0.00 0.00 0.04 0.68 0.04 0.04 0.30 0.23 0.24 0.50 0.37 0.00 0.32 0.00 0.50 0.15 0.31 0.00 0.31 1.16 2.21 0.35 0.00 0.43 0.65 0.73 2.17 1.90 0.31 0.97 0.53 0.43 1.29 1.61 0.35 0.35 0.00 0.69 0.26 0.46 0.51 0.21 0.17 0.00 0.00 0.00

0.02 0.00 0.00 0.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.07 0.11 0.24 0.11 0.19 0.00 0.07 0.00 0.14 0.00 0.16 0.00 0.15 0.00 0.00 1.42 0.27 0.00 0.22 0.03 0.00 0.83 0.63 1.35 0.32 0.64 0.39 0.56 0.35 0.35 0.00 0.00 0.13 0.15 0.51 0.00 0.00 0.00 0.00 0.00

92.9 99.0 96.7 93.3 85.5 93.2 101.3 103.7 125.8 137.0 137.0 106.7 131.8 111.3 111.3 149.7 111.8 157.6 124.1 159.6 84.3 106.6 113.6 114.0 118.6 137.7 108.4 138.0 154.2 136.5 131.2 121.3 151.3 158.0 131.8 128.4 130.0 108.5 146.6 119.5 140.4 130.6 131.3 120.9 120.9 89.9 90.8 86.9 89.9 91.7 96.7 104.9 98.1 81.1 0.0

Number Aged 6,361 1,412 1,412 3,594 590 1,163 1,862 1,202 718 0 0 0 146 5,389 5,389 1,355 7,925 422 3,769 536 279 4,014 721 5,747 664 637 101 651 432 271 282 371 466 926 7,680 369 844 637 518 945 469 776 1,428 569 569 574 288 760 653 196 467 577 386 179 0

CATCH (tonnes) (millions) +

+ + + + + + * * * + + + + + + + + + + +

+

+ +

1,920 5,939 0 407 1,149 173 31 323 769 125 826 51 0 508 18 79 75 75 422 270 0 519 0 671 238 332 0 163 171 0 0 0 0 0 0 0 335 0 367 0 345 88 0 0 0 0 0 0 0 0 0 0 0 0 0

20.667 58.757 0.000 4.366 13.434 1.856 0.304 3.110 6.113 0.913 6.032 0.482 0.000 4.562 0.165 0.525 0.670 0.477 3.401 1.695 0.000 4.873 0.000 5.884 2.011 2.411 0.000 1.181 1.107 0.000 0.000 0.000 0.000 0.000 0.001 0.000 2.580 0.000 2.502 0.000 2.455 0.670 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

~

~

~ ~

~

~ ~ ~ ~ ~ ~ ~ ~

~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

Appendix 1.7. Age composition and catch by season, fishery and gear type for the Area 2W stock assessment region. These data are used for the age-structured model analysis. Season

Gear

Fishery

0+

1+

19567 19634 19645 19656 19723 19734

Seine Seine Seine Seine Seine Seine Gillnet Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine Seine

Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr Jan-Apr

0.07 0.00 0.00 1.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

20.00 1.02 1.59 18.05 0.16 0.61 50.98 0.63 23.71 0.15 1.49 0.37 4.98 0.02 0.50 6.45 0.40 0.82 22.14 1.79 0.49 0.19 0.50 1.48 0.76 5.32 18.50 15.60 14.77 4.37 28.69 1.03 7.24 0.36 10.75

19745 19756 19778 19789 19790 19801 19812 19823 19834 19845 19856 19867 19878 19889 19890 19901 19912 19923 19934 19978 19989 19990 20001 20012 20023 20034 20045 20056

P E R C E N T AT 2+ 3+ 4+ 5+ 25.34 15.92 80.07 32.22 38.08 31.47 11.11 26.50 6.70 23.63 18.84 76.03 1.87 53.90 1.52 1.61 0.67 0.27 61.32 74.01 3.42 1.71 6.46 6.34 11.71 12.23 34.75 32.38 63.64 8.48 23.83 73.49 9.74 26.68 13.98

16.22 60.00 10.20 16.11 21.42 38.54 5.88 34.13 41.24 18.15 22.95 13.11 66.92 2.31 68.64 0.60 5.80 11.48 0.25 19.31 76.06 2.28 0.89 13.44 16.46 43.62 23.10 28.09 18.18 40.62 4.77 15.31 71.71 8.63 17.63

9.41 16.53 5.14 10.23 26.62 17.89 15.69 27.01 23.71 9.48 16.23 4.49 11.97 34.93 3.59 35.28 2.56 11.75 1.27 0.26 15.88 80.41 1.84 1.37 13.53 14.89 18.68 14.30 0.00 24.42 21.64 3.39 7.50 58.76 6.88

25.92 5.31 1.78 7.33 10.93 8.36 5.88 9.18 4.64 28.96 22.95 3.37 6.35 3.91 20.49 2.42 13.75 5.46 1.27 0.53 0.49 13.18 68.91 2.79 1.91 9.57 2.62 7.28 2.27 12.08 9.72 3.69 1.71 4.04 44.95

A G E 6+ 7+ 2.46 1.22 0.84 5.79 1.93 2.58 9.15 2.05 0.00 13.11 13.81 1.87 5.02 2.55 2.37 51.01 1.62 20.77 1.27 0.66 0.49 0.46 19.83 60.55 4.57 2.13 0.63 1.56 0.00 6.94 6.86 1.15 1.58 0.54 3.44

0.47 0.00 0.37 4.84 0.80 0.49 1.31 0.41 0.00 5.04 1.87 0.00 1.79 2.02 1.43 1.81 74.39 7.38 8.14 0.79 0.98 0.18 0.72 12.46 44.54 5.85 1.53 0.52 1.14 2.06 2.67 1.33 0.26 0.81 1.72

8+

9++

Mean Weight

0.11 0.00 0.00 2.04 0.05 0.06 0.00 0.09 0.00 1.26 1.12 0.75 0.84 0.23 0.83 0.60 0.67 41.53 1.02 1.65 0.81 0.70 0.45 0.55 5.67 5.32 0.18 0.26 0.00 0.51 1.53 0.36 0.00 0.00 0.65

0.00 0.00 0.00 1.72 0.00 0.00 0.00 0.00 0.00 0.22 0.75 0.00 0.26 0.13 0.64 0.20 0.13 0.55 3.31 0.99 1.38 0.90 0.39 1.04 0.84 1.06 0.00 0.00 0.00 0.51 0.29 0.24 0.26 0.18 0.00

104.2 113.9 104.0 128.8 144.7 126.9 101.0 130.8 139.8 150.5 151.9 108.8 132.9 139.5 151.9 166.2 212.3 205.2 112.0 114.1 137.6 168.1 173.3 183.5 156.7 145.6 120.8 116.8 85.0 153.2 130.5 111.3 124.5 122.7 132.4


62

Number Aged 4,506 490 1,069 0 1,867 1,627 153 6,384 194 1,350 536 267 1,232 1,654 3,356 496 742 366 393 1,512 1,228 2,353 1,795 1,830 2,574 188 1,108 769 88 389 1,049 1,652 760 1,113 465

CATCH (tonnes) (millions) + + + * + + + +

106 312 1,251 172 706 403 0 449 0 575 691 0 770 1,225 2,518 0 199 0 0 0 0 2,272 2,558 1,284 1,306 0 180 0 0 0 0 0 0 0 0

1.016 2.743 12.030 1.338 4.878 3.178 0.000 3.436 0.000 3.819 4.546 0.000 5.808 9.099 16.808 0.000 0.940 0.000 0.000 0.000 0.000 13.608 14.762 6.994 7.985 0.000 1.487 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

~ ~

~

~ ~ ~ ~ ~

~ ~ ~ ~ ~ ~ ~ ~ ~

Appendix table 2.1. Estimates of numbers at age, spawning stock biomass (SB), spawn index (SI), estimated spawn-observed spawn residuals (RES), and other parameters from age-structured analysis for the Queen Charlotte Is. stock assessment region. Season 1950/51 1951/52 1952/53 1953/54 1954/55 1955/56 1956/57 1957/58 1958/59 1959/60 1960/61 1961/62 1962/63 1963/64 1964/65 1965/66 1966/67 1967/68 1968/69 1969/70 1970/71 1971/72 1972/73 1973/74 1974/75 1975/76 1976/77 1977/78 1978/79 1979/80 1980/81 1981/82 1982/83 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06

1+ 3461 10446 29205 4821 4147 2015 2851 6917 2443 8595 9968 17153 4710 11905 2300 4146 3762 4919 4485 6596 6636 13534 10999 9396 4752 5833 9959 5390 114732 8820 2680 1741 13073 7446 2398 3408 22585 10127 5091 3627 33506 3984 4883 13970 20875 19248 35687 2045 6554 6798 4896 22966 7452 6075 7401 6779

2+ 2100 1771 5531 17528 2955 2436 1064 1200 2692 1374 4668 5155 8494 2240 5148 714 1204 863 1298 1703 3077 3464 7461 6207 5499 2922 3699 6039 2975 55418 3645 1078 803 6872 4283 1353 1823 12102 5361 2777 1997 17310 1814 2026 5589 7407 7123 14233 773 2282 2247 1538 7282 2443 2043 2544

Estimated numbers at age (x10-5) for period 1 3+ 4+ 5+ 6+ 7+ 1734 320 163 47 7 1028 784 131 60 15 731 341 228 35 15 3319 439 205 137 21 10636 1977 255 115 75 1732 6200 1141 144 63 669 280 720 107 12 108 44 15 36 5 319 28 11 4 9 1098 108 9 3 1 746 596 59 5 2 2389 377 298 29 2 2399 1011 144 104 9 3641 887 324 41 27 690 746 129 36 4 506 42 37 6 1 164 104 8 7 1 272 36 23 2 1 226 71 9 6 0 493 86 27 4 2 795 230 40 13 2 1602 413 120 21 7 1830 789 188 50 8 4019 901 341 68 15 3498 2147 457 166 32 3268 1975 1148 233 81 1792 1870 1003 491 80 2160 971 912 427 181 3247 1088 429 322 98 1399 1432 420 139 82 22742 566 542 148 47 1448 8807 209 184 47 491 646 3838 88 74 397 239 310 1825 42 3845 214 123 155 890 2369 2034 105 56 64 717 1225 1007 49 23 969 375 623 491 22 6405 513 198 330 260 2900 3432 273 105 174 1497 1501 1659 121 42 1016 738 702 718 47 7825 452 320 292 279 745 3142 175 117 99 810 297 1245 69 45 1983 287 105 442 24 2741 734 106 39 163 2841 1093 293 42 16 5306 1041 395 105 15 261 1704 316 109 26 724 78 489 87 29 706 227 25 154 27 471 207 64 7 41 2387 154 68 21 2 821 803 52 23 7 702 282 276 18 8

8+

9+

1 2 4 9 12 40 5 1 1 3 1 1 1 2 2 0 0 0 0 0 1 1 3 2 7 16 28 30 41 25 27 15 19 35 20 362 27 11 12 137 69 16 18 94 38 16 9 65 6 4 7 9 7 13 1 2

0 0 1 3 6 10 4 0 0 0 2 1 1 0 0 0 0 0 0 0 0 1 1 1 2 4 7 13 9 13 12 13 11 14 24 18 157 84 50 32 67 52 27 15 42 28 16 10 27 7 3 3 3 3 6 2

SB 3491 6505 10250 11206 10900 9722 1650 7220 5194 8787 9035 9819 11837 4695 2660 2467 1095 2108 2846 7545 14717 8426 7486 25389 29291 17922 20244 9368 10757 40180 48438 42796 46981 25917 18180 12355 11075 22459 39964 20674 14112 13481 10754 7486 5207 7303 11310 19651 11032 6945 12789 3374 8753 5687 3656 5838

SI 4213 2578 7555 12408 6437 6042 1592 815 8981 6599 8981 5730 7297 4104 1378 2824 710 833 2075 5552 13291 9542 7960 14510 9686 16374 16408 18371 13649 31904 20294 23593 21391 23439 18625 6847 12289 15245 25201 27058 17998 12376 8152 14293 4701 7377 11215 21649 10610 6698 15195 3257 8801 5668 3614 5926

Estimated average availability at age ( Si ): 0.04

0.27 0.48 0.66 0.83 1.00 1.00 1.00 1.00

Estimated average relative selectivity at age for gillnet fisheries: 0.01 0.05 0.23 0.54 0.75 0.87 0.95 1.00 1.00 Spawn index-escapement conversion factor, pre-dive era (q) is 0.73

63

RES 1.25 -1.53 0.02 1.04 -0.53 -0.41 0.69 -4.67 2.15 0.07 0.77 -0.56 -0.43 0.45 -0.86 1.12 -0.30 -1.54 -0.01 0.02 0.53 1.09 0.94 -0.62 -1.98 0.56 0.26 2.47 1.38 0.21 -1.39 -0.71 -1.18 0.53 0.84 -0.69 1.04 -1.11 -1.32 0.77 0.70 -0.24 -0.79 1.85 -0.29 0.03 -0.02 0.28 -0.11 -0.10 0.49 -0.10 0.02 -0.01 -0.03 0.04

Appendix table 2.2. Estimates of numbers at age, spawning stock biomass (SB), spawn index (SI), estimated spawn-observed spawn residuals (RES), and other parameters from age-structured analysis for the Prince Rupert District stock assessment region. Season 1950/51 1951/52 1952/53 1953/54 1954/55 1955/56 1956/57 1957/58 1958/59 1959/60 1960/61 1961/62 1962/63 1963/64 1964/65 1965/66 1966/67 1967/68 1968/69 1969/70 1970/71 1971/72 1972/73 1973/74 1974/75 1975/76 1976/77 1977/78 1978/79 1979/80 1980/81 1981/82 1982/83 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06

1+

2+

Estimated numbers at age (x10-5) for period 1 3+ 4+ 5+ 6+ 7+

8981 10980 18586 4455 10614 3363 5518 9161 2683 14685 7578 4282 11697 2365 1375 2805 3954 2818 7444 5359 2377 8161 8842 6129 3480 5769 3197 2903 21229 6259 5360 5658 10893 2671 2328 7181 5209 3523 1941 7090 6064 2794 1520 3798 12155 5922 7607 2362 5424 8821 5685 20026 3244 10337 4032 4085

9418 4913 5919 9836 2355 5842 1853 3194 5663 1816 9475 5359 3243 7209 1598 764 1575 1390 1127 3415 2734 1339 4946 5381 3743 2127 3432 1735 1496 11411 3376 3045 3366 6788 1689 1468 4695 3443 2265 1207 4482 3873 1777 967 2402 7554 3531 4417 1358 3130 5067 3237 11200 1739 5425 1923

10689 4320 2150 3094 4618 1151 2896 671 1879 3424 1030 4623 3322 1643 3803 541 359 457 514 517 1684 1423 790 2977 3242 2274 1261 1833 865 791 6024 1891 1796 2097 4236 1028 922 3042 2145 1347 743 2814 2412 1104 602 1485 4503 2048 2539 781 1767 2850 1770 5919 897 2538

1540 3894 1353 1109 1160 1903 564 892 393 1077 1925 458 2595 1664 840 1207 185 103 168 236 253 849 788 465 1725 1944 1332 645 835 433 398 3283 1100 1119 1288 2526 607 575 1813 1212 794 450 1714 1426 661 367 874 2581 1172 1438 430 973 1505 917 2959 409

562 453 808 690 295 401 929 163 522 220 604 829 246 1296 842 261 264 53 38 77 115 126 401 447 245 1008 1091 601 245 369 199 205 1876 685 662 742 1385 347 311 912 665 451 238 915 775 383 200 454 1436 643 722 227 470 708 429 1238

246 151 75 411 145 94 196 264 96 291 123 258 440 123 654 261 42 75 19 17 38 57 49 221 225 140 509 428 202 96 163 98 116 1169 388 359 394 742 161 125 463 360 208 98 431 421 168 81 238 733 300 335 94 181 281 167

24 64 23 38 80 45 46 55 155 53 163 53 136 219 62 202 38 12 28 9 8 19 20 27 110 128 63 187 138 75 42 79 55 72 636 196 187 204 310 58 60 236 155 69 34 218 170 47 31 118 297 136 114 29 50 86

8+

9+

6 6 10 12 7 25 22 13 32 86 30 69 28 68 111 19 30 11 4 13 4 4 7 11 13 62 57 23 60 51 33 20 44 34 37 298 101 96 85 101 28 30 95 47 22 16 79 37 13 13 36 124 42 33 6 8

0 2 1 6 3 3 14 10 14 26 62 39 57 43 56 51 10 11 8 6 9 7 4 6 8 12 34 33 18 29 35 32 30 46 41 35 170 137 93 58 75 49 29 32 22 20 12 14 8 8 6 17 34 20 9 2

SB

SI

29668 14656 30298 11055 16534 41373 18270 37655 35783 54032 47481 52002 64607 55007 30743 4432 9860 8870 1631 17523 17394 5983 13388 21820 20800 12481 16520 14591 9181 22546 20553 27796 38927 39198 52651 42106 35709 29788 28358 23570 26370 37769 23143 13511 13467 18137 33028 22827 25600 20859 21941 18939 30181 24910 19113 14116

27149 24047 28468 13535 14482 14533 27518 9882 40961 16545 12059 26329 16981 26919 6055 7105 3386 5197 965 8814 8480 8774 10959 9244 10775 15587 11323 5724 9195 11937 14087 17186 24735 26699 40650 26353 39628 35042 15959 22288 25519 39833 24638 16180 18231 24444 25037 19420 29292 19320 36362 21987 33631 30085 26105 10251

Estimated average availability at age ( Si ): 0.09 0.42 0.65 0.85 0.96 1.00 1.00 1.00 1.00 Estimated average relative selectivity at age for gillnet fisheries: 0.00 0.01 0.15 0.37 0.57 0.73 0.88 1.00 1.00 Spawn index-escapement conversion factor, pre-dive era (q) is 0.63

64

RES 0.91 2.37 0.98 1.64 0.80 -1.48 2.16 -2.21 1.47 -1.83 -2.29 -0.57 -2.21 -0.65 -2.93 2.31 -1.54 -0.20 -0.18 -0.58 -0.66 2.09 0.63 -1.01 -0.51 1.69 0.19 -1.21 1.14 -0.46 0.19 -0.07 0.00 0.17 0.49 -0.04 1.39 0.46 -1.64 -0.16 -0.09 0.15 0.18 0.52 0.87 0.85 -0.79 -0.46 0.39 -0.22 1.44 0.43 0.31 0.54 0.89 -0.91

Appendix table 2.3. Estimates of numbers at age, spawning stock biomass (SB), spawn index (SI), estimated spawn-observed spawn residuals (RES), and other parameters from age-structured analysis for the Central Coast stock assessment region. Season 1950/51 1951/52 1952/53 1953/54 1954/55 1955/56 1956/57 1957/58 1958/59 1959/60 1960/61 1961/62 1962/63 1963/64 1964/65 1965/66 1966/67 1967/68 1968/69 1969/70 1970/71 1971/72 1972/73 1973/74 1974/75 1975/76 1976/77 1977/78 1978/79 1979/80 1980/81 1981/82 1982/83 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06

1+

2+


11358 15542 55072 4998 4338 8425 11547 13582 3571 6470 15178 9897 8192 5230 5687 11432 5637 3203 8960 6132 5514 8437 6813 9333 5582 5270 9039 6342 44839 8855 7152 2804 2410 7203 3903 6497 31727 3043 2286 5776 23668 3801 5074 2130 6513 22314 23885 5227 9116 4367 11146 26193 6664 21149 4422 4139

9976 5241 7180 25921 2205 1979 3873 5925 7539 2133 3839 9146 5958 4437 2263 2589 3428 1823 1266 3685 2863 3080 5361 4477 6073 3495 3230 5266 3458 24177 4752 3769 1604 1456 4399 2331 3822 18087 1664 1279 3432 14542 2336 3043 1246 3817 13041 13829 2916 4958 2323 5909 13858 3366 10021 1823

8841 3876 2033 3365 9994 922 483 1129 2764 3258 1235 1484 4769 2170 1111 734 283 643 690 521 1718 1504 1785 3323 2860 3719 2062 1831 2789 1865 12972 2498 2130 960 868 2559 1345 2146 9709 900 744 2043 8595 1340 1643 688 2167 7393 7446 1548 2550 1191 3049 6910 1565 3996

1425 2820 1183 947 1178 4105 182 98 499 847 1884 354 674 1121 480 263 69 50 242 284 243 883 749 1009 1964 1636 2038 1084 875 1504 1000 6734 1378 1248 549 482 1428 732 1118 4990 502 418 1145 4636 675 832 373 1190 3756 3788 761 1240 594 1488 3122 599

548 380 659 547 313 481 740 30 42 113 489 450 145 105 236 89 24 12 19 100 132 124 354 381 477 972 735 899 379 472 798 502 3530 770 669 289 259 736 364 512 2542 254 219 570 2187 306 421 196 556 1771 1749 345 593 279 649 1150

130 136 78 304 177 127 84 113 13 9 65 110 177 19 22 40 8 4 5 8 46 67 43 171 135 213 367 268 177 204 243 376 255 1890 388 343 152 129 352 152 234 1186 128 102 258 922 148 213 85 246 781 754 161 270 120 235

7 31 26 36 97 72 22 13 49 2 5 14 43 21 4 4 4 1 2 2 4 24 22 21 50 57 72 123 31 95 100 108 185 133 918 194 178 74 61 135 64 103 576 57 44 104 435 73 84 33 105 326 343 72 115 43

8+ 0 2 6 12 11 40 13 3 5 9 1 1 6 5 4 1 0 1 1 1 1 2 8 10 6 21 19 24 12 17 47 43 52 96 62 457 101 87 35 23 56 28 49 248 24 18 49 214 28 29 14 43 146 152 30 41

9+ 0 0 0 3 5 7 8 3 3 2 6 2 1 1 1 1 0 0 0 0 0 1 1 4 4 4 8 9 3 8 12 25 32 43 62 62 268 180 126 61 35 39 32 34 119 56 35 41 96 41 29 17 27 76 97 46

SB

SI

29186 15113 20487 40478 52538 15553 6248 21643 9494 39842 13153 20812 8643 15700 5502 5726 8790 11749 4653 32080 23652 9106 22791 15594 37753 30839 26342 12541 14474 12402 78398 66153 45343 32232 33125 29466 23559 39921 40602 30223 24345 38062 41736 41818 22228 18206 24269 28012 32474 33975 22975 21545 22118 23284 23157 14905

15390 10295 18237 13967 13564 6626 4607 3549 3904 12615 4265 11948 6485 6464 2097 1863 5434 5790 1837 8230 4156 3572 12434 8852 8037 13849 14613 7747 5779 13012 15919 16333 18482 14185 8850 20342 12827 26916 21561 28980 19183 43274 32392 29432 22348 21646 28255 31503 31813 32652 25109 23147 25679 29407 24158 12051

Estimated average availability at age ( Si ): 0.08 0.38 0.62 0.84 0.94 1.00 1.00 1.00 1.00 Estimated average relative selectivity at age for gillnet fisheries: 0.00 0.02 0.15 0.40 0.65 0.82 0.92 1.00 1.00 Spawn index-escapement conversion factor (q) is 0.42

65

RES 0.57 1.21 1.88 -0.49 -1.21 0.04 1.41 -2.35 -0.05 -0.70 -0.65 0.78 1.45 -0.05 -0.24 -0.64 0.97 0.40 -0.15 -1.23 -2.18 -0.17 0.66 0.76 -1.70 0.17 0.70 0.97 -0.12 2.29 -1.82 -1.33 -0.07 0.12 -1.13 1.25 0.65 -1.13 -1.81 -0.12 -0.68 0.37 -0.72 -1.00 0.02 0.49 0.44 0.34 -0.06 -0.11 0.25 0.21 0.43 0.67 0.12 -0.61

Appendix table 2.4. Estimates of numbers at age, spawning stock biomass (SB), spawn index (SI), estimated spawn-observed spawn residuals (RES), and other parameters from age-structured analysis for the Strait of Georgia stock assessment region. Season 1950/51 1951/52 1952/53 1953/54 1954/55 1955/56 1956/57 1957/58 1958/59 1959/60 1960/61 1961/62 1962/63 1963/64 1964/65 1965/66 1966/67 1967/68 1968/69 1969/70 1970/71 1971/72 1972/73 1973/74 1974/75 1975/76 1976/77 1977/78 1978/79 1979/80 1980/81 1981/82 1982/83 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06

1+

2+


20550 23854 33455 23862 15080 16410 14074 26057 17759 9881 24955 22080 25862 17781 11201 18697 12811 9371 14427 12158 10333 12004 17170 19379 12628 26002 23494 13671 22610 18707 18871 16686 14989 17477 21052 9694 24342 7796 18781 10791 28502 19818 22699 10897 20030 27777 28106 13240 20420 23174 33058 38644 24957 22282 13220 22194

10272 10978 12743 19337 13830 8051 8378 6828 13915 9686 5273 13677 12435 14126 8675 3772 5617 2835 2592 5297 5476 4718 5199 7796 9753 6824 14691 13609 7690 12406 9909 9586 7997 6169 6525 8870 4655 13144 4105 10476 5845 15363 10646 11995 5420 9503 13598 14204 6855 10602 12028 17869 21835 13965 11504 5949

3856 3884 4187 6999 9104 5426 2561 2070 2858 5271 3039 1750 4396 3820 3994 1893 586 659 738 948 2378 2455 1793 2233 3878 5217 3771 8120 7241 4097 6498 4860 4394 3053 2155 2611 4239 2399 6758 2236 5635 3089 7988 5425 5705 2457 4337 6352 7007 3382 5190 6125 9523 11656 6913 4889

843 1160 1283 2241 2460 3209 1245 415 671 1007 1495 901 421 1013 714 820 212 64 169 270 425 1056 865 676 1000 1938 2596 1896 3908 3538 2108 3088 2108 1452 947 787 1247 2016 1131 3493 1151 2767 1487 3817 2366 2407 1056 1886 2960 3242 1581 2491 3056 4753 5587 2842

167 235 369 682 668 844 658 175 120 222 280 433 199 89 163 145 83 23 16 62 121 188 361 282 288 393 829 1134 771 1671 1740 930 1264 577 346 291 376 485 821 503 1534 477 1125 629 1364 849 893 386 779 1197 1333 634 1123 1386 2170 2079

40 46 74 196 192 228 168 89 49 38 61 80 93 41 14 33 14 9 6 6 28 53 64 112 118 100 153 329 402 304 798 732 352 316 117 91 139 112 176 327 189 538 167 428 167 438 265 246 131 252 344 430 199 466 576 679

11 11 14 39 55 65 45 23 25 16 11 18 17 19 6 3 3 2 2 2 3 12 18 20 47 40 38 59 111 156 144 331 273 80 63 29 44 32 37 65 116 60 179 59 100 49 128 62 56 35 55 88 108 56 184 147

8+

9+

3 3 3 8 11 19 13 6 6 8 4 3 4 4 3 1 0 0 0 1 1 1 4 6 8 16 15 15 20 43 74 59 122 59 15 16 14 9 10 13 23 35 19 63 11 29 14 27 9 12 5 13 16 20 17 41

SB 0 1 1 2 3 5 5 2 2 3 3 2 1 1 1 1 0 0 0 0 0 1 1 1 3 4 7 9 8 11 25 41 37 34 17 8 11 5 4 5 6 9 14 12 12 7 10 4 3 2 2 2 1 5 8 6

31385 44000 65781 45416 79898 30653 14853 15733 54051 44643 32499 28142 28681 23018 32329 8021 9670 10416 20951 33069 35657 28140 19128 53167 59705 47723 79569 72034 61285 91784 95809 79925 45203 35084 41932 62003 49875 66349 72121 80477 65135 83090 118072 82050 67275 66756 69299 68637 68442 75127 73194 92847 95204 117447 94459 54490

SI 66143 72376 111307 82141 69854 25667 24126 16149 47864 55082 42864 31078 35135 33117 37116 7153 9619 9128 14644 33970 38180 25165 16191 40354 70211 60642 78562 102115 64266 85991 55121 100987 64575 26227 25247 41575 41737 24976 66052 67152 45830 82656 90198 67144 64899 71326 58232 74616 85095 72639 100248 117864 141651 113689 100760 46752


66

RES 1.73 1.11 1.18 1.34 -0.47 -0.58 1.08 -0.07 -0.44 0.39 0.55 0.11 0.37 0.77 0.21 -0.42 -0.15 -0.47 -1.03 -0.07 0.03 -0.42 -0.56 -0.83 0.27 0.46 -0.17 0.73 -0.02 -0.30 -1.52 0.45 0.75 -0.87 -1.41 -1.14 -0.58 -2.79 -0.25 -0.52 -1.00 -0.02 -0.77 -0.57 -0.10 0.19 -0.50 0.24 0.62 -0.10 0.90 0.68 1.14 -0.09 0.18 -0.44

Appendix table 2.5. Estimates of numbers at age, spawning stock biomass (SB), spawn index (SI), estimated spawn-observed spawn residuals (RES), and other parameters from age-structured analysis for the west coast of Vancouver Island stock assessment region. Season 1950/51 1951/52 1952/53 1953/54 1954/55 1955/56 1956/57 1957/58 1958/59 1959/60 1960/61 1961/62 1962/63 1963/64 1964/65 1965/66 1966/67 1967/68 1968/69 1969/70 1970/71 1971/72 1972/73 1973/74 1974/75 1975/76 1976/77 1977/78 1978/79 1979/80 1980/81 1981/82 1982/83 1983/84 1984/85 1985/86 1986/87 1987/88 1988/89 1989/90 1990/91 1991/92 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06

1+

2+


26198 32960 42337 30693 39579 41036 30919 31953 25456 17826 50981 28693 47415 27208 26396 24063 25393 21557 35032 44423 25426 28431 31361 47509 22928 23534 53173 19056 50415 32678 18456 11662 16668 32849 27599 12112 70896 17558 26417 20240 63142 38298 31517 15822 19839 82155 33710 21832 25590 30883 38161 41490 24447 33506 26403 29072

8337 10492 12881 14216 9194 12877 16182 13067 13348 10183 6055 18844 11366 18461 9341 7446 5706 5889 5494 11255 17940 11338 13377 15186 26061 13706 13995 29835 9815 26376 16531 8498 4693 6277 13434 12253 5709 37155 9070 12235 8556 27863 17025 13384 6069 8038 36089 14452 8165 8136 9965 14009 16541 9027 10136 6714

8195 2898 3583 4324 3290 2820 4444 6730 5440 3355 1821 1544 6314 3998 5692 2408 1623 1039 1501 1765 4545 8000 5201 6138 7851 14923 7823 7624 15149 5011 13276 7476 3375 1681 2403 5957 5769 2823 18863 4106 5066 3705 12283 7129 5024 2444 3516 15103 5289 2542 2607 3658 5566 6009 2639 2436

1106 2746 831 1203 862 991 924 1836 2800 987 423 414 476 1971 1128 1339 471 256 265 482 713 2027 3549 2196 3017 4172 7817 3968 3734 7448 2505 5921 2921 1158 621 1065 2802 2629 1387 8173 1642 2115 1610 5037 2605 2004 1064 1431 5332 1598 804 957 1444 1971 1669 593

254 365 650 279 221 258 317 381 764 406 102 92 122 132 523 246 234 68 65 85 195 318 867 1347 1017 1429 1785 3508 1692 1663 3656 1083 2250 953 418 275 501 1174 1222 562 3118 646 899 643 1787 1025 868 421 480 1527 489 295 371 484 514 328

54 83 72 218 49 66 82 131 158 95 38 22 26 31 34 108 39 32 17 21 34 87 131 297 604 452 505 682 1230 688 798 1551 395 711 340 185 130 198 513 463 206 1141 269 348 222 690 442 336 127 131 447 180 111 112 114 87

4 18 13 24 37 15 21 34 54 17 8 8 6 6 8 7 15 5 8 6 8 15 34 39 131 254 130 159 187 467 326 333 555 122 252 151 87 48 77 180 160 68 460 99 117 83 296 167 88 31 36 164 65 29 23 13

8+

9+

4 1 3 4 4 11 5 8 14 6 1 2 2 1 1 1 1 2 1 3 2 4 6 10 17 55 72 41 42 70 221 136 117 171 43 112 71 32 19 27 62 53 27 170 33 44 35 112 42 21 8 13 59 16 5 2

0 1 0 1 1 1 4 3 5 2 1 0 1 1 0 0 0 0 1 1 1 2 2 2 6 10 18 28 18 23 44 111 86 62 82 56 79 55 34 18 16 25 31 22 64 36 34 26 34 17 10 7 7 17 5 1

SB 53974 10560 42395 21451 32818 38084 54077 68722 16333 9435 18572 34823 14804 29351 17653 6818 8950 17537 16984 43274 59528 33335 29536 102719 94361 66224 57055 63414 85499 132462 138447 81422 45568 44580 87601 75023 41111 34662 53975 46848 28778 39797 34521 47089 19919 30377 44857 32081 22114 14320 14176 21363 19294 13720 10457 2777

SI 19597 13310 39571 20648 15112 27183 44114 18986 12979 6015 10556 34470 11245 22761 11891 3722 4813 11029 10465 26912 36206 41857 19481 25540 49149 64222 58679 45607 66397 62308 52063 33047 16771 23872 30010 39514 16858 46242 47718 46464 30456 42687 34728 25625 28057 33986 46490 41556 20390 13267 13955 22086 29750 15844 9075 2705


67

RES -1.28 1.83 1.08 1.15 -0.69 0.41 0.74 -1.97 0.68 0.12 -0.16 1.22 0.56 0.61 0.26 -0.26 -0.30 0.09 0.04 0.06 0.01 1.82 0.21 -2.23 -0.38 1.17 1.32 0.43 0.62 -0.64 -1.20 -1.01 -1.25 -0.31 -1.43 -0.35 -0.98 0.82 -0.35 -0.02 0.16 0.20 0.02 -1.74 0.98 0.32 0.10 0.74 -0.23 -0.22 -0.05 0.10 1.24 0.41 -0.41 -0.08

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