An Analytical Assessment of the Roughhead Grenadier Stock ...Power 1987). Roughhead grenadier is becoming an important commercial fish species in the waters managed by the Northwest

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†Corresponding author: [email protected].

An Analytical Assessment of the Roughhead Grenadier Stock in NAFO Subareas 2 and 3

Fernando González-Costas†

Instituto Español de Oceanografía, Cabo Estay—Canido Apartado de correos 1552, 36280, Vigo, Spain

Hilario MuruaAZTI Tecnalia

Herrera Kaia, Portualde z/g, 20110, Pasaia, Spain

American Fisheries Society Symposium 63:319–342, 2008 © 2008 by the American Fisheries Society

Abstract.—Catch and research survey data for 1992–2005 on the roughhead grenadier Macrourus berglax stock in the Northwest Atlantic Fisheries Organization (NAFO) Subareas 2 and 3 are fitted using the Extended Survivors Analysis (XSA) model.Despite the short time series available, the wide age range of this species, the low fishing mortality level as estimated by XSA, and the lack of convergence in the ret-rospective analyses, the results showed that the XSA model provides an adequate fit to the data and the XSA estimated trends are similar to those observed in research surveys. Therefore, we conclude that this assessment model could be an appropriate tool to be used in the quantitative assessment of the roughhead grenadier stock in NAFO Subareas 2 and 3. The model results indicated that the stock biomass has been increasing from 1996 to 2005. The biomass estimated for the beginning of 2005 was around 70,000 metric tons (mt), the highest in the time series. Fishing mortality has declined since 1999 and showed the lowest value in the time series in 2005. However, the retrospective analysis indicated a clear retrospective pattern in the model esti-mates, with fishing mortality underestimated and total biomass overestimated. Over the last few years, there have been two very good recruitments at age 3, which may lead to an increase of the exploitable biomass in the future. The assessment results showed that the current status of the roughhead grenadier stock in Subareas 2 and 3 is acceptable. The values calculated for the yield per recruit reference points were F

max = 0.130 and F

0.1= 0.083.

Introduction

Roughhead grenadier (Macrourus ber-glax Lacépède, 1802) is an abundant wide-spread fish species in the North Atlantic, usually found both on the shelf and on the continental slope (Scott and Scott 1988; Sav-

vatimsky 1994). It is predominant at depths ranging from 800 to 1,500 m (Murua and de Cárdenas 2005), although it may inhabit the whole range from 200 to 2,000 m (Snelgrove and Haedrich 1985; Murua and de Cárde-nas 2005). Occasionally, it has been found at depths down to 2,700 m (Wheeler 1969). This species is commonly found at tempera-

320 González-Costas and Murua

tures from about –0.5 to 5.4°C (Atkinson and Power 1987).

Roughhead grenadier is becoming an important commercial fish species in the waters managed by the Northwest Atlantic Fishery Organization (NAFO), especially in the NAFO Regulatory Area (NRA1) (Figure 1), and reliable information is needed for its assessment. The fishery for roughhead grena-dier is unregulated as it is taken as bycatch in the Greenland halibut Reinhardtius hippo-glossoides fishery, mainly in NRA Divisions 3LMN. Most of the roughhead grenadier catches are taken by trawl and the only man-agement regulation applicable in the NRA is a general groundfish regulation requiring the use of a minimum 130 mm mesh size. Catch-es of roughhead grenadier increased sharply between 1989 (333 mt) and 1992 (6,700 mt). After this time, catches fluctuated around 4,300 mt until 1997, reaching the highest lev-els of the time series in 1998 and 1999 (7,700 and 7,200 mt, respectively). Since then, catches decreased to 3,000 and 1,500 mt in 2004 and 2005, respectively (Figure 2).

The knowledge about the biology and population dynamics of Macrouridae is sparse (Gordon 1979; Middleton and Musick 1986; Atkinson 1995; D’Onghia et al. 2000). In particular, little has been published on the biology, growth and reproduction of rough-head grenadier on both sides of the North Atlantic. Savvatimsky (1989, 1994) and Jor-gensen (1996) investigated the age structure and growth of macrourids in the Northwest Atlantic, based on age readings from scales. Age structure and growth of the roughhead grenadier, based on otolith readings of speci-mens captured in the Northwest Atlantic, were estimated by Murua and González (2006). Those studies concluded that the growth tra-jectories of males and females are different, males grow slower than females beginning at

9–10 years old. Calibration of age estimates, derived from otolith readings, has been given by Rodríguez-Marín et al. (2002). Various au-thors have described the reproductive biology of M. berglax. For example, Yanulov (1962), Geistdoerfer (1979), Eliassen and Falk-Pe-tersen (1985), Savvatimsky (1989), Murua and Motos (2000), Fossen et al. (2003), and Murua (2003) carried out studies on the tim-ing of spawning, egg diameter, egg and ovary development and fecundity of this species.

The stock structure of this species in the North Atlantic remains unclear because there is little information on the number of different populations that may exist and the relationship between them. In the NAFO area (Figure 1), roughhead grenadier is distributed throughout Subareas 0–3. However, for as-sessment purposes, NAFO Scientific Council considers the population of Subareas 2 and 3 as a single stock (NAFO 2005). The as-sessment of the Subareas 2 and 3 roughhead grenadier stock is carried out by the NAFO Scientific Council and is at present a qualita-tive assessment, mainly based on survey ob-servations, rather than a quantitative analyti-cal assessment.

Gathering reliable information on bio-logical characteristics and the fishery of this species is essential as the catches of this un-regulated deep-water species are consider-able. Proper monitoring and assessment of the status of this “new” resource is even more important as many traditional groundfish fish-eries have collapsed or are in poor condition. Although current knowledge on the biology of this species is not extensive, there is more information than might be expected. And over the last few years, more biological informa-tion as well as research survey indices have been analyzed (Murua et al. 2005). The aim of this paper is to present for the first time an analysis of the status of this stock based on an age-disaggregated analytical assessment using all the available information.

1 Defined by NAFO as “the part of the NAFO Convention Area, which lies beyond the areas in which Coastal States exercise fisheries jurisdiction.”

321Roughhead Grenadier Assessment in NAFO

Figure 1. Map of NAFO area with Subareas and Division as well as the 200 miles Exclusive Eco-nomic Zone line. Reproduced with permission of NAFO Secretariat.


Methods

Input data

Catches

It has been acknowledged that a sub-stantial part of the past grenadier catches in Subarea 3, previously reported as roundnose grenadier Coryphaenoides rupestris, are of roughhead grenadier. However, Power and Maddock Parsons (1998) revised the rough-head grenadier catch statistics since 1987 to solve this problem. These revised catch sta-tistics were approved by the NAFO Standing Committee on Fisheries Science (STACFIS) for assessment purposes. Nevertheless, only the revised STACFIS catches since 1992 (Fig-ure 2) are used in this assessment because the length compositions, and thus, age composi-tions, were not available before 1992.

Length Distributions

Due to the growth differences between sexes (Murua 2003), length and age data

have been analyzed by sex. The length fre-quencies by sex from the Spanish, Portuguese and Russian trawl catches in Div. 3LMNO were available for different years (Table 1) (González and Murua 2005). According to the Spanish and Portuguese sampling proto-col, grenadiers are measured in terms of pre-anal fin lengths (PAFL), whereas Russians measure total length. Total length was con-verted to PAFL using the total length/PAFL relationship estimated by Murua and Motos (2000). Length frequencies by sex and Di-vision were raised to the total catches in the corresponding Division for each country and then all length distributions by Division were added to obtain the length distribution of to-tal catches by sex and year for each country.

Catch-at-Age

Aging was based on otoliths from speci-mens caught in NAFO Divisions 3LMN. Vali-dation of age estimates derived from otolith reading was examined by Rodríguez–Marín et al. (2002), where three validation methods were applied: back-calculation of length-at-

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Figure 2. Roughhead grenadier Macrourus berglax catches in tons by year in NAFO Subareas 2 and 3.


age, length-frequency analysis, and analyses of the progression of the length mode of an ex-ceptionally large year-class. The results of the latter two methods were internally consistent, but estimates by back-calculation were differ-ent and produced unrealistic growth curves.

The catch-at-age data presented by González and Murua (2005) has been updated with 2004 and 2005 data. Table 1 presents the data available to create the catch-at-age ma-trix.

The method used by González and Murua (2005) was as follows: the length distribu-tion of total catches by sex for each country was converted to age distribution by sex and country using the Spanish ALK (Age Length Key). For the years where ALK information was not available, a combined ALK (1999, 2000, 2002, and 2003) by sex was applied. Then both sexes were added together to ob-tain the age distributions by country and year. In this process mean weight and mean length by age, year and country was also calculat-

ed. Subsequently, the age distributions for the different countries were summed up and raised to the total catch estimate for that year in order to obtain the total catch numbers by age and year as well as the associated mean weights and lengths by age.

Survey Indices

Biomass indices for the Subareas 2 and 3 roughhead grenadier stock are available from several research surveys, with different depth and area coverage (Table 2) (NAFO 2006). None of them covers the total area and depth distribution of this stock. The Canadian fall survey (Divisions 2J and 3K) and the Spanish research survey in Divisions 3NO are consid-ered to provide the best information to moni-tor trends in resource status (NAFO 2005) because they cover depths down to 1,500 m, hence covering the depth distribution of roughhead grenadier fairly well (Murua and de Cárdenas 2005).

Data Length ALK Country Spain Portugal Russia Spain 1992 X X 1993 X 1994 X 1995 X X 1996 X X 1997 X X X 1998 X X X 1999 X X X X 2000 X X X X 2001 X X X 2002 X X X X 2003 X X X X 2004 X X X X 2005 X X X

Table 1. Roughhead grenadier Macrourus berglax catches length distributions and ALK available by country and year in NAFO Subarea 2 and 3.


With regards to the tuning indices used in this assessment, only the European Union (EU) Flemish Cap research survey in NAFO Division 3M and the Spanish research sur-vey in Divisions 3NO were used, since these were the only two surveys that provided the length distribution data necessary for esti-mating catch-at-age. Catch-at-age in num-bers are given as mean number at age per tow (MNPT).

The European Union (EU) Flemish Cap research survey in NAFO Division 3M covers depths down to 750 m. This survey was carried out with the R/V Cornide de Saavedra until 2003 and from then onwards with the R/V Viz-conde de Eza. Parallel fishing operations were conducted in 2003 and 2004 in order to cali-brate the two survey series. The transformed survey series (1994–2005) by age were pre-sented by Murua and González (2006).

The Spanish research survey in Divi-sions 3NO covers depths to 1,400 m. The length abundance indices between 1997 and 2005 (González-Troncoso et al. 2006) were transformed to age abundance indices by the method presented in González and Murua (2005).

Maturity ogive

The maturity ogive used to calculate Spawning Stock Biomass (SSB) was estimat-ed from ovaries collected in the Flemish Cap research survey and commercial sampling in NRA Division 3LMNO during 1998–2000. The maturity ogive was estimated micro-scopically, by means of histology (Murua 2003), and this constant ogive was applied to the whole time series of the assessment (1992–2005).

Data screening

Catch-at-age

In order to analyze the consistency of the catch-at-age matrix, the Separable Virtual Population Analysis stock assessment model (Pope and Shepherd 1982) was fitted to the roughhead grenadier catch data in NAFO Subareas 2 and 3. The model was fitted, in an initial step, to the whole catch-at-age data, i.e., catches from 1992 to 2005 and ages 1–24, to analyze the consistency of the catch-at-age matrix.

Survey Time Series NAFO Division Depth Range

Canadian Fall Survey 1978–2005 2GHJ 3KMLNO <1500 m

Canadian Spring Survey 1978–2005 3LNO <730 m

Canadian deepwater 1991, 1994, 1995 3LMN <1,500 m

Spanish Surveys in Div. 3NO 1997–2005 3NO <1500 m

EU Flemish Cap Surveys 1988–2005 3M <730 m

Russian 2001–2002 3M 120–1,280 m

EU Deepwater 1996 3LMN 700–3,100m

Table 2. Available survey biomass indices for the roughhead grenadier Macrourus berglax in NAFO Subareas 2 and 3 stock, with their depth and area coverage.


The residuals of the Separable VPA (Fig-ure 3) show the difference between the ob-served catch ratios (LN (Catch (year + 1, age + 1)/Catch (year, age))) and the model catch ratios (LN Ĉatch (year + 1, age + 1)/Ĉatch (year, age))). The largest errors were seen at ages younger than 3 and older than 20 years.

The consistency of different cohorts present in the catches is presented in Figure 4, where the younger and older ages of every cohort are difficult to track. The difficulty in tracking the younger ages are probably due to the selectivity of the gear, i.e., they are not fully recruited to the trawl. Age 8 or 9 is the first age to be fully recruited to the trawl gear. Figure 4 also shows that the individuals older than 20 years are more difficult to track in the cohort. For the older ages, this can be due to the difficulty in age determination.

Therefore, the assessment was to be car-ried out using an age range between 3 and 19 years, due to the selectivity of the young ages while age 19 was considered a plus group, in order to avoid the difficulties associated with the age determination of the older individuals.

Survey data

The research survey data were screened using the methods described in Beare et al. (2003), who suggested that simple tests are useful for evaluating the ability of research surveys to track cohort strength. The tests are grouped into three categories using simple correlation analyses in order to examine:

1. Within-survey consistency: correla-tion between log-transformed indices at age (a) and year (y) with log-transformed indices at age (a + 1) and year (y + 1) from the same survey.

2. Between-survey consistency: correla-tion between log-transformed indices at each age from different surveys.

3. Consistency between survey indices and the output from an analytical assessment: correlation between log-transformed survey indices and estimated total number at age from the analytical model.

These tests were conducted on the two research surveys used as tuning fleets and for the age range used in the assessment.

Figure 3. Difference of the catch ratios observed (LN (Catch (year + 1,age + 1)/Catch (year, age))) and the Separable Virtual Population Analysis model catch ratios (LN (Ĉatch (year + 1, age + 1)/Ĉatch (year, age))) of the roughhead grenadier Macrourus berglax in NAFO Subarea 2 and 3.


With regards to the analysis of internal survey consistency, Figure 5 shows that in the EU Flemish Cap survey the correlation for ages less than 6 was quite good (>0.5), whereas the correlation between ages 6 and 8 was weak (0.5 < x > 0.1 ). For ages older than 8, the most abundant age-class in the catches, the correlation was again good (>0.5), with the exception of ages 15–16 and 17–18. For the Spanish 3NO research survey, the correlation presented the same pattern as in the EU Flem-ish Cap Survey, except for ages older than 14 for which it was weaker than in the EU Flem-ish Cap Survey (Figure 5).

However, correlations between consecu-tive ages to analyze within-survey consistency can be affected by outlier values, that is, the correlation could show a high value based on only a couple of points. In our case, most of the correlations analyzed measure systematic patterns, i.e., the points are dispersed along the x-y-axis (Figures 6 and 7). Only the correla-tion between ages 3–4 in the Flemish Cap sur-vey and ages 5–6 and 6–7 in the Spanish 3NO

survey can be influenced by outlying values.Similarly, Figure 8 shows that the agree-

ment between surveys was quite good. Be-tween-surveys correlations were above 0.6 for the most important ages in the catches (7–14) and only three ages (6, 15 and 18) showed very low correlation. It can be observed that the two surveys sampled the population con-sistently and in a similar manner for the most important ages in the commercial catches.

These analyses provided an initial exami-nation of the ability of survey indices to track cohort strength and of the quality of the survey information used for tuning the analytical as-sessment. The results indicated that there were difficulties with two ages (6 and 15) which may introduce noise into the model, but all the other ages, including the most abundant in the catches, were suitable for tuning the analytical assessment.

The third analysis, where the consistency between survey indices and the output from an analytical assessment is tested, will be in-cluded in the “Results” section.

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Figure 5. Correlation between log-transformed indices at age (a) and year (y) with log-transformed indices at age (a + 1) and year (y + 1) from EU Flemish Cap survey and Spanish 3NO survey.

Figure 6. Pair-wise plot of log-transformed indices at age by cohort from EU Flemish Cap survey.


Assessment method and model set-up

A preliminary Extended Survivors Anal-ysis (XSA) (Darby and Flatman 1994; Shep-herd 1999) was carried out in order to ana-lyze the quality of the survey information as tuning indices using commercial catch-at-age from 1992 to 2005 and tuned separately with the EU Flemish Cap (ages 3–18 and years 1994–2005) and Spanish 3NO (ages 3–18 and years 1997–2005) surveys.

An XSA with the following specifica-tions was carried out for each tuning survey separately to observe the individual qual-

ity of the data: all years of the tuning data series have the same weight in the calcula-tions; catchability independent of stock size for all ages; catchability independent of age from age 17; no F shrinkage; a minimum value of 0.3 for the log catchability stan-dard errors.

The EU Flemish Cap survey only cov-ered depths to 750 m, but roughhead grena-dier is distributed to around 2,000 m (Murua and de Cárdenas 2005) with the largest fish at the greater depths. Therefore, information relating to ages 17 and 18 was very limited in this survey.

Figure 7. Pair-wise plot of log-transformed indices at age by cohort from Spanish 3NO survey.


Catchability provides the link between survey catches and population abundance as estimated from the catch-at-age data, and the model assumes that surveys’ catchabili-ties-at-age are constant over time. The log catchability residuals for each survey by year (Figure 9 and Figure 10) show that there were no strong trends, and the mean annual residu-als for all ages fluctuated around zero without trend.

In both surveys, the larger residuals oc-curred for younger and older ages; however, these ages are less frequent in the catches. The EU Flemish Cap survey log catchability residuals for older ages were greater than in the Spanish 3NO survey, and this could be related to the differences in depth coverage of the two surveys. The inverse variance weight-ing used within XSA takes this into account in the estimation of parameters. Some year effects can be observed in the log catchabil-ity residuals, the clearest being 1998 in the Spanish 3NO survey, which could be related to problems that arose trawling in the deepest strata in that particular year.

After the analysis of the log catchability residuals, a final XSA was carried out using the EU Flemish Cap survey series between 1994 and 2005 and restricted to ages 3–16, in order to avoid the scarce information provid-

ed by the oldest ages of this survey, and the Spanish 3NO research survey series between 1997 and 2005 and ages 3–18 as tuning se-ries. The XSA model specifications (Darby and Flatman 1994) are given next.

Input data

Catch-at-age data: from 1992 to 2005 for ages 3–19, last age as a plus group.

Tuning fleets: EU Flemish Cap indices from 1994 to 2005 for ages 3–16. Survey month: June. Spanish 3NO research survey indices from 1997 to 2005 for ages 3–18. Survey month: May.

Natural mortality (M) at age was assumed to be constant and was set equal to 0.1 for all years. The reason for selecting this value for M is that roughhead grenadier is a long-lived species that inhabits a stable deep-sea ecosystem and this value has been applied in the assessment of roundnose grenadier with similar biology and inhabiting similar eco-systems (ICES 2006).

Model specifications

All years in the tuning data series are giv-en the same weight in the calculations.

Catchability analysis: A mean model is

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Figure 8. Correlation between log-transformed indices at each age from EU Flemish Cap survey and Spanish 3NO survey.


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Figure 9. Extended Survivors Analysis log q errors of Flemish Cap survey by age and year. Each number symbolizes an age and the line symbolizes the annual mean residuals for all ages.


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Figure 10. Extended Survivors Analysis log q errors of Spanish 3NO survey by age and year. Each number symbolizes an age and the line symbolizes the annual mean residuals for all ages.


used to describe the relationship between catchability and abundance for all ages be-cause the regression statistics for testing the use of the power model for younger ages were not significant.

The model (XSA) makes the assumption that catchability is independent of age (con-stant) above a specific, user-defined age. We have defined this age as 17 because for older ages log q values decrease with age for both surveys.

Terminal population estimation: For each age, a mean of the F values for the four years that precede the final year is calculated. This time period has been selected to avoid F trends and to estimate a robust mean F value.

The survivors in years prior to the final year are shrunk to a terminal population derived from an average of the F values for the three ages that precede the oldest true age and the to-tal catch value for the true age. These ages have been selected because the exploitation pattern for them is approximately constant.

A weight of 1.0 has been given for the F shrinkage means. The reason for using the shrinkage means was that the tuning series are shorter than the catch-at-age matrix, and it is recommended to have an initial value to start the cohort analyses for the cohorts for which there is no tuning information. This weight is the same for all years and ages, and it prevents the shrinkage values from having a large influence in the parameter estimates.

A minimum value of 0.3 has been set for the log catchability standard errors used as weights for estimating survivors. Fleet stan-dard errors falling below 0.3 are replaced by this threshold value.

Prior weighting of fleets was not applied. The estimates derived from the different fleets get the same weight in the calculations.

Results and Discussion

The results presented in this paper are the first attempt to use an age-based model in

order to carry out a quantitative assessment of a grenadier stock in the North Atlantic, with the exception of roundnose grenadier in ICES Divisions Vb and XIIb and Sub-Areas VI and VII.

The XSA fitting procedure converged after 109 iterations and the model fit is con-sidered to be acceptable. The results are con-sidered to be illustrative due to the variety of factors that might introduce uncertainty in the outcome, such as the short time series of data, the wide age range of the population and natural mortality level.

Total biomass, spawning stock biomass (SSB), mean F between ages 11–16 (Fbar), and recruitment (Age 3) results are presented in Table 3. Fbar was taken as the average fish-ing mortality for ages 11–16 because these ages are the most abundant in the catches and are completely recruited to the gear.

Model results indicated that the stock biomass increased from 1996 onwards and that the current level of total biomass was twofold in comparison to the beginning of the time series. The biomass estimated for the beginning of 2005 was around 70,000 metric tons, which is at the same level as the highest value (73,000 metric tons corresponding to 2004) in the whole time series. Fishing mor-tality has declined since 1999 and showed the lowest value of the time series in 2005. In the last three years the level of F is much smaller than the value of the assumed natural mortal-ity. This fact increases the uncertainty of the results because the dynamics of the stock are mainly driven by the assumed value of natu-ral mortality. The uncertainty associated with the low value of F is smaller between 1992 and 2002 because the catches were greater in this period and because of the VPA con-vergence property. There have been two very good recruitments at age three in recent years (2003 and 2004), which could increase the exploitable biomass in the future.

This picture of the state of the stock con-tradicts the one presented by Devine et al.


(2006) who classified this stock, based on catch data from research-trawl surveys in Ca-nadian waters, as critically endangered fol-lowing the criteria of the World Conservation Union (IUCN). This contradiction may be due to: (i) differences between depth cover-age in the two studies (1500 m versus around 800 m); (ii) different survey information; and (iii) different temporal coverage.

As model settings may have a consider-able influence on final results, different values for some settings have been analyzed to study how sensitive biomass or fishing mortality es-timates are to these values. In the following paragraph, only results for biomass are pre-sented; because the results for fishing mortal-

ity are consistent with those of biomass.Natural mortality: the natural mortal-

ity values assumed in assessments of similar species are in the range of 0.1–0.2. Figure 11 presents the biomass results for three levels of M (0.1, 0.15, 0.2). Biomass results are sen-sitive to the chosen M value: the biomass lev-el increases with M, although the trend is the same for the three M values. Therefore, the lower value of M has been chosen because (i) roughhead grenadier is a long-lived species, (ii) a similar value is used in the assessment of similar species, and (iii) it is the most pre-cautionary value.

Weight of the F shrinkage: the different year range covered by the catch-at-age ma-

Year Recruits age 3 (thousands) Total Biomass (ton) SSB (ton) Fbar (11–16)

1992 15463 34156 3895 0.44

1993 22326 29512 3113 0.3446

1994 24342 30419 2998 0.3156

1995 22445 38624 2805 0.233

1996 20127 38954 2401 0.2095

1997 28220 43758 3131 0.2318

1998 32350 44985 3232 0.2501

1999 24032 54595 3952 0.3472

2000 21145 48072 5849 0.1917

2001 19558 46437 4491 0.1048

2002 27730 54798 5975 0.1063

2003 42418 64680 8122 0.0822

2004 54037 73377 6659 0.0603

2005 14380 70080 8564 0.0246

Table 3. Results of the XSA model run for recruitment (age 3), total biomass, spawning stock biomass (SSB) and mean F between ages 11 and 16 (Fbar) of roughhead grenadier Macrourus berglax in NAFO Subareas 2 and 3.


trix and the surveys’ tuning indices (starting, respectively, in 1992 and 1994) was the main reason for applying F shrinkage. Figure 12 shows the biomass results under three differ-ent options: without shrinkage, with shrink-age with a similar SE (weight) to the log catchability of the tuning indices (0.5), and with shrinkage with a high SE (1.0). The results under the first and third options are very similar, except for the last two years where the biomass is larger when shrinkage is not applied. The similarity under the first and third options is expected because when F shrinkage is applied with high standard er-ror (SE) its influence on years for which sur-vey information is available is very low and, hence, results are similar to those obtained under the no shrinkage option. The second option, where the shrinkage has a similar SE to log catchability of the tuning indices, led to lower biomass estimates than the other two options. In the latter case, as the fishing mortality shows a declining trend during the last years, applying shrinkage to the mean F leads to overestimation of F in the final year and, consequently, the survivors and biomass are underestimated. In order to avoid biomass

underestimation F-shrinkage is performed with a high standard error.

Catchability independent of age: the log q values of the older ages decrease as age increases, but starting from age 15 this de-crease is smaller. There were some doubts as to which were the first age for which it was reasonable to assume catchability indepen-dent of age. Figure 13 presents biomass esti-mates that take this age as 15 and 17 and the results are very similar in both cases. It was decided to let the model estimate a separate catchability for each age rather than to make the assumption that catchability is constant after a certain age.

Results display some sensitivity to the settings values. Accordingly, we have chosen the final options based on the reasons given above.

Correlation values between the XSA abundance at age estimates and the surveys indices used for tuning (Figure 14) were very high following similar trends; however, there were some inconsistencies for ages 5, 6, 7 and 15. These inconsistencies were mostly due to the poor quality of the survey informa-tion for those ages, as was already noted in

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Figure 11. Total biomass by year estimated by XSA for three different values of Natural Mortality (M).


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Figure 12. Total biomass by year estimated by XSA for three different values of the Standard Error (SE) of the F shrinkage.

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Figure 13. Total biomass by year estimated by XSA for two different ages from which catchability is independent of age (constant).


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Figure 14. Correlation between log-transformed indices of the EU Flemish Cap survey and Span-ish 3NO survey with the XSA results of abundance by age.

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Figure 15. Total biomass of the Canadian 2J and 3K fall survey, EU Flemish Cap survey, Spanish 3NO survey and XSA by year.


the within- and between-survey consistency analyses. These inconsistencies are likely to be due mainly to aging problems for older fishes and catchability issues for younger fishes, although they can also be affected by other factors such as immigration or emigra-tion to/from the survey area, or a combina-tion of all these factors.

Model and survey trends are similar. The Canadian fall survey series (Divisions 2J and 3K) and the Spanish survey in Divisions 3NO are considered by the NAFO Scientific Coun-cil as the best survey information available to monitor trends in the status of this resource. The Canadian fall survey information is not included as a tuning index in the model and can be considered independent of the XSA results. The trend in the Canadian survey bio-mass was very similar to the biomass trend estimated from the XSA (Figure 15). The EU Flemish Cap Survey trend was the one that differed most from the XSA results. This dif-ference could be expected since this survey only covered part of the depth distribution of the species and the survey information only represents biomass less than 17 years old.

In terms of fishing mortality estimates from different surveys, the trends of the ratio between total catch and total survey biomass from the Canadian fall survey (Divisions 2J + 3K), the Spanish survey in Divisions 3NO, and the Flemish Cap survey, which can be consid-ered as proxies for fishing mortality (F), and the trend in mean F (averaged over ages 3–18) estimated by XSA (all values standardized to the 1997 value), were all very similar (Figure 16). In this analysis, the average F between ages 3 and 18 estimated by XSA was used in order to make it comparable to the survey age-range.

Figure 17 shows the mean number per tow of age 3 in the Spanish survey in Divisions 3NO and in the Flemish Cap survey, as well as the number of age 3 recruits calculated by the XSA. In all three series the trend was similar and it is noted that the 2004 recruitment at age

3 was the best of the series, being more than twice the average level of the whole time se-ries. It is not possible to estimate recruitment from the Canadian fall survey because there is no length or age information available from this survey.

In order to check the consistency of the as-sessment model, a retrospective analysis of the XSA was run using the same data. Estimates of fishing mortality, total biomass and recruit-ment from this analysis are displayed in Fig-ure 18. Retrospective patterns generally arise as a result of model misspecification, often an assumption that a parameter is constant when in reality it exhibits a time trend or has a step change to a new level (ICES 1991; Mohn 1999) and can be reduced by introducing changes to the model formulation or by removing sec-tions of the data that do not conform to the model structure (ICES 1991, 1993).

The retrospective results (Figure 18) indi-cate that there were clear retrospective patterns in the model estimates, e.g., fishing mortality was underestimated whereas total abundance and biomass were overestimated. The lack of convergence in the retrospective values could be due to the short time series analyzed, the low fishing mortality levels, and the large number of the ages present in the catch-at-age matrix. In particular, the fact that there is not one fully out cohort in the assessment, i.e., there are more age-classes than years, could underestimate the F and, accordingly, overes-timate biomass of the stock.

With regard to recruitment, the retrospec-tive analysis showed that in last year’s assess-ment, the recruitment estimates for 2003 and 2004 were much lower than had been esti-mated in previous years, although they remain the highest estimates of recruitment in the time series.

Reference points

Precautionary approach reference points (Scientific Council 2003) have not been de-


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Figure 16. Total catch/survey total biomass ratio estimated by the swept area method of the Ca-nadian fall survey (Divisions 2J + 3K), the Spanish survey in Divisions 3NO, Flemish Cap survey, and XSA F mean (3–18) by year. All values standardized to 1997 value.

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Figure 17. Age 3 mean number per tow for the Spanish survey in Divisions 3NO, Flemish Cap survey and age 3 recruits (thousands) estimated by the XSA by year.


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Figure 18. Retrospective time series of the XSA mean F between ages 11 and 16 (Fbar), total biomass and number of recruits (age 3).


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Figure 19. Yield per recruit analysis based on average weights and the XSA mean exploitation pattern for the past 3 years, as well as the F0.1, Fmax, and 2005 Fbar values.

fined by NAFO for this stock. Yield per recruit analysis (Beverton and Holt 1957) provides long term reference points based on catch weight, fishing and natural mortality at age. Potential stock–recruitment relationships are ignored and equilibrium yield is calculated on the basis of one recruit. A relative yield per recruit (Y/R’) analysis was performed for the roughhead grenadier stock in NAFO Subareas 2 and 3 based on average weights and the XSA mean exploitation patterns for the past three years, despite the uncertainty in the XSA results, to calculate Fmax and F0.1 (Figure 19). The values calculated were Fmax = 0.130 and F0.1 = 0.083. The XSA estimate of Fbar for 2005 was 0.025, well below F0.1 and Fmax.

Conclusion

Despite the short time series available, the wide age range of this species, the low fishing mortality level estimated by XSA and the lack of convergence in the retrospective

analyses, the research survey indices and the XSA results give a similar picture of the state of the stock, and the model (XSA) seems to fit the available data adequately. Therefore, it could be considered that the model is illustra-tive and appropriate to be used in the assess-ment of roughhead grenadier in NAFO Sub-areas 2 and 3. However, in order to improve the assessment, further research on different topics is advised. For example, it would be convenient to study, in a future paper, the sensitivity of the results to the definition of the plus group age to avoid the uncertainty related to the fact that there are more ages than years with data in the analysis.

Based on the results of the XSA assess-ment presented, the current status of this stock would be acceptable. Current estimates of biomass are the highest in the time series, current fishing mortality is the lowest of the series, well below the F0.1 and Fmax values, and the 2003 and 2004 recruitments are the best of the time series. Total biomass was doubled between 1992 and 2005, and this


increase will probably continue in the com-ing years due to the growth of the good re-cruitments in the last years and to the reduced fishing mortality expected as a result of the NAFO recovery plan for Greenland halibut (NAFO 2003), since roughhead grenadier is the most important species in the bycatch in the Greenland halibut fishery.

Acknowledgments

The authors are indebted to all the peo-ple that helped with this review at different stages. We also thank colleagues at IEO and AZTI that have collaborated in the data col-lection and biological sampling. The study has been carried out under financial support from the Spanish Institute of Oceanography (IEO) and from the Department of Agricul-ture and Fisheries of the Basque Country Government. This paper is contribution n° 384 from AZTI-Tecnalia (Marine Research).

References

Atkinson, D. B. 1995. The biology and fishery of roundnose grenadier (Coryphaenoides rupestris Gunnerus, 1765) in the North west Atlantic. Pag-es 51–112 in A. G. Hopper, editor. Deep water fisheries of the North Atlantic Ocean Slope. Klu-wer, Dordrecht, Netherlands.

Atkinson, D. B., and D. Power. 1987. Distribution of roughhead and roundnose grenadiers in the Northwest Atlantic. NAFO SCR Doc., No. 94, Serial No. N1398.

Beare D., J. Castro, J. Cotter, O. Van Keeken, L. Kell, A. Laurec, J. C. Mahe, S. Moura, S. Munch-Pe-tersen, J. R. Nielsen, G. Piet, J. Simmonds, D. Skagen and P. J. Sparre. 2003. Evaluation of re-search surveys in relation to management advice (EVARES). EC-DG FISH/2001/02—Lot 1.

Beverton, R. J. H. and S. J. Holt. 1957. On the dy-namics of exploited fish populations. Fisheries Investment Series 2, volume 19. UK Ministry of Agriculture and Fisheries, London.

Darby, C. D., and S. Flatman. 1994. Virtual Popula-tion Analysis: Version 3.1 (Windows/Dos) user guide. Infomation Technology Series Number 1, Ministry of Agriculture, Fisheries and Food, Di-rectorate of Fisheries Research, Lowestoft.

Devine, J. A., K. D. Baker, and R. L. Haedrich. 2006. Deep sea fishes qualify as endangered. Nature (London) 439:29.

D’Onghia, G. D., M. Basanisi, and A. Tursi. 2000. Pop-ulation structure, age and growth of macrourid fish from the upper slope of the Eastern-Central Medi-terranean. Journal of Fish Biology 56:1217–1238.

Eliassen, J. E., and I. B. Falk-Petersen. 1985. Repro-ductive biology of the roughhead grenadier (Mac-rourus berglax Lacepede) (Pisces, Gadiformes) from the continental slope of northern Norway. Sarsia 70(1):59–67.

Fossen, I., O. A. Jorgensen, and A. C. Gunderson. 2003. Roughhead grenadier (Macrourus berglax) in the waters off east Greenland: distribution and biolo-gy. Journal of Northwest Atlantic Fishery Science 31:285–299.

Geistdoerfer, P. 1979. New data on the reproduction of macrourids (Teleostei, Gadiformes). Sarsia 64:109–112.

González, F., and H. Murua. 2005. Roughhead grena-dier NAFO Subareas 2 and 3 age disaggregate data (1992–2003). NAFO SCR Doc. 05/46.

González-Troncoso, D., F. González-Costas, and X. Paz. 2006. Biomass and length distribution for roughhead grenadier, thorny skate and white hake from the surveys conducted by Spain in NAFO 3NO. NAFO SCR Doc. 06/14.

Gordon. J. D. M. 1979. Lifestyle and phenology in deep sea anacanthine teleosts. Symposium of Zoologi-cal Society of London 44:327–359.

ICES. 1991. Report of the Working Group on Meth-ods of Fish Stock Assessment, St. John’s, New-foundland, 20–27 June 1991. ICES CM 1991/As-sess:25.

ICES. 1993. Report of the Working Group on Meth-ods of Fish Stock Assessment, ICES Headquar-ters, Copenhagen, Denmark, 3–10 February 1993. ICES CM 1993/Assess:12.

ICES. 2006. Report of the Working Group on the Bi-ology and Assessment of Deep-Sea Fisheries Re-sources (WGDEEP). ICES CM 2006/ACFM:28.

Jorgensen, O. A. 1996. Distribution and biology of grenadiers (Macrouridae) in west Greenland wa-ters. Journal of Northwest Atlantic Fishery Sci-ence 18:7–29.

Middleton, R. W., and J. A. Musick. 1986. The abun-dance and distribution of the family Macrouridae (Pisces: Gadiformes) in the Norfolk Canyon area. Fishery Bulletin 84:35–62.

Mohn, R. 1999. The retrospective problem in sequen-tial population analysis: an investigation using cod fishery and simulated data. ICES Journal of Ma-rine Science 56:473–488.


Murua, H. 2003. Population structure, growth and re-production of roughhead grenadier on the Flem-ish Cap and Flemish Pass. Journal of Fish Biology 63:56–373.

Murua, H., and L. Motos. 2000. Reproductive biology of roughhead grenadier (Macrourus berglax Lace-pède, 1801) (Pisces, Macrouridae), in northwest Atlantic waters. Sarsia 85:393–402.

Murua, H., and E. de Cárdenas. 2005. Depth distribu-tion of deep water species in Flemish Pass. Journal of Northwest Atlantic Fishery Science 37:1–12.

Murua, H., and F. González. 2006. A review on rough-head grenadier (Macrourus berglax) biology and population structure on Flemish Cap (NAFO Divi-sion 3M) 1991–2005 based upon EU Flemish Cap bottom survey data. NAFO SCR Doc. 06/07.

Murua, H., F. González, and D. Power. 2005. A review of the fishery and the investigations of roughhead grenadier (Macrourus berglax) in Flemish Cap and Flemish Pass. Journal of Northwest Atlantic Fishery Science 37:13–27.

NAFO. 2003. Report of the Fisheries Commission 25th Annual Meeting, September 15–19, 2003, Dart-mouth, Nova Scotia, Canada. Serial No. N4939. NAFO/FC Doc. 03/19.

NAFO. 2005. Report of Scientific Council Meeting, 2–16 June 2005. Serial No. N5155. NAFO SCS Doc. 05/10:164–169.

NAFO. 2006. Report of Scientific Council Meeting, 1–15 June 2006. Serial No. N5282. NAFO SCS Doc. 06/22:157–158.

Pope, J. G., and J. G. Shepherd. 1982. A simple method for the consistent interpretation of catch-at-age data. Journal du Conseil International pour l’Ex-Journal du Conseil International pour l’Ex-ploration de la Mer 40:176–184.

Power, D., and D. Maddock Parsons. 1998. An assess-1998. An assess-

ment of roundnose grenadier (Coryphaenoides rupestris) in NAFO Subareas 2&3 and catch in-formation on roughhead grenadier (Macrourus berglax). NAFO SCR Document No. 57, Serial No. N3049.

Rodríguez-Marín, E., M. Ruiz, and A. Sarasua. 2002. Validation of roughhead grenadier (Macrourus berglax) otolith reading. Journal of Applied Ich-thyology 18:70–80.

Savvatimsky, P. I. 1989. Investigations of roughhead grenadier (Macrourus berglax L) in the North-west Atlantic, 1967–83. NAFO Scientific Council Studies 13:59–75.

Savvatimsky, P. I. 1994. Age structure of roughhead grenadier (Macrourus berglax) in the Northwest Atlantic, 1985. NAFO Scientific Council Studies 20:53–64.

Scientific Council. 2003. Proposed NAFO precaution-ary approach framework. Serial No. N4900 NAFO SCS Doc. 03/23.

Scott, W. B., and M. G. Scott. 1988. Atlantic fishes of Canada. Canadian Bulletin of Fisheries and Aquatic Sciences 219:1–731.

Shepherd, J. G. 1999. Extended survivors analysis: an improved method for the analysis of catch-at-age data and abundance indices. ICES Journal of Ma-rine Science 56(5):584–591.

Snelgrove, P. V. R., and R. L. Haedrich. 1985. Structure of the deep demersal fish-fauna off Newfoundland. Marine Ecology Progress Series 27:99–107.

Wheeler, A. 1969. The fishes of the British Isles and northwest Europe: Anacanthini (p.255, 259). Mac-Millan, London.

Yanulov, K. P. 1962. On the reproduction of the rough-head grenadier (Macrourus berglax Lacépède). Zoologicheskij Zhurnal 8:1259–1262.

Documents

An Analytical Assessment of the Roughhead Grenadier Stock ...Power 1987). Roughhead grenadier is becoming an important commercial fish species in the waters managed by the Northwest