Data Loading...

Data evaluation of data limited stocks: Dab, Flounder ... Flipbook PDF

Data evaluation of data limited stocks: Dab, Flounder, Witch, Lemon Sole, Brill, Turbot and Horse mackerel Tessa van der


123 Views
119 Downloads
FLIP PDF 2.16MB

DOWNLOAD FLIP

REPORT DMCA

Data evaluation of data limited stocks: Dab, Flounder, Witch, Lemon Sole, Brill, Turbot and Horse mackerel Tessa van der Hammen & Jan Jaap Poos Report number C110/12

IMARES

Wageningen UR

(IMARES - Institute for Marine Resources & Ecosystem Studies)

Client:

Ministry of EL&I Attn. Henk Offringa PO box 20401 2500 EK Den Haag

BAS code: 12.04.001.036

Publication date:

10 oktober 2012

IMARES is: 

an independent, objective and authoritative institute that provides knowledge necessary for an integrated sustainable protection, exploitation and spatial use of the sea and coastal zones;



an institute that provides knowledge necessary for an integrated sustainable protection, exploitation and spatial use of the sea and coastal zones;



a key, proactive player in national and international marine networks (including ICES and EFARO).

P.O. Box 68

P.O. Box 77

P.O. Box 57

P.O. Box 167

1970 AB IJmuiden

4400 AB Yerseke

1780 AB Den Helder

1790 AD Den Burg Texel

Phone: +31 (0)317 48 09 00

Phone: +31 (0)317 48 09 00

Phone: +31 (0)317 48 09 00

Phone: +31 (0)317 48 09 00

Fax: +31 (0)317 48 73 26

Fax: +31 (0)317 48 73 59

Fax: +31 (0)223 63 06 87

Fax: +31 (0)317 48 73 62

E-Mail: [email protected]

E-Mail: [email protected]

E-Mail: [email protected]

E-Mail: [email protected]

www.imares.wur.nl

www.imares.wur.nl

www.imares.wur.nl

www.imares.wur.nl

© 2011 IMARES Wageningen UR

IMARES, institute of Stichting DLO

The Management of IMARES is not responsible for resulting

is registered in the Dutch trade

damage, as well as for damage resulting from the application of

record nr. 09098104, BTW nr. NL 806511618

results or research obtained by IMARES, its clients or any claims related to the application of information found within its research. This report has been made on the request of the client and is wholly the client's property. This report may not be reproduced and/or published partially or in its entirety without the express written consent of the client.

A_4_3_2-V12.3

2 of 62

Report number C110/12

Contents Contents................................................................................................................... 3  Summary ................................................................................................................. 4  1 

Introduction ..................................................................................................... 4 



Assignment ...................................................................................................... 4 



Methods .......................................................................................................... 5 



Dab ................................................................................................................ 8 



European Flounder .......................................................................................... 17 



Witch Flounder ............................................................................................... 21 



Lemon Sole .................................................................................................... 25 



Brill .............................................................................................................. 29 



Turbot ........................................................................................................... 33 

10 

Horse mackerel .............................................................................................. 37 

11 

Conclusions and Interpretation ......................................................................... 42 

References .............................................................................................................. 45

Appendix A

48

Appendix B

50

Appendix C

57

Appendix D

58

Report number C110/12

3 of 62

Summary Several commercially important demersal fish stocks for the North Sea fisheries are classified by ICES (International Council for the Exploration of the Sea) as “data limited” stocks, which are stocks for which the data are insufficient to perform a full analytical assessment and forecast (ICES 2012b). Until 2012 for most of these ‘data-limited’ stocks , there was no quantitative management advice that is based on the status of the stock, because the status is unknown. In this report catch per unit of effort (CPUE) indices, spatial distributions, length frequencies and agelength relationships are analysed for 7 species that have commercial importance for Dutch fisheries: dab, flounder, witch flounder, lemon sole, brill, turbot and North Sea horse mackerel. The data in this report may be used in future for catch advice by the International Council for Exploration of the Sea (ICES).

1

Introduction

Several commercially important fish stocks for the North Sea fisheries are classified as “data limited” stocks in the light of the EU policy paper on fisheries management (17 May 2010, COM(2010) 241). For stocks in this category, there is no STECF (Scientific, technical and economic committee for fisheries) management advice, due to the unknown status of the stocks. The reason for this is that the data and information available to perform analytical stock assessments are highly uncertain or lacking. For species of these stocks, the European Commission adjusts the TAC (Total Allowable Catch) towards recent catch levels, but the TAC should not be changed by more than 15% per year. Alternatively, if Member States can develop an implementation plan to provide advice within a short time, the European Commission can set the TAC on the basis of that plan.

Table 1-1 Data limited stocks of economic importance for the Netherlands Area

Species

ICES advice for 2012

North Sea

Turbot

Do not increase catches

Brill

Do not increase catches

Dab

Do not increase catches

Flounder

Do not increase catches

Lemon sole

Do not increase catches

Witch flounder

Reduce catches

Horse mackerel

Reduce catches

2

Assignment

The Ministry of EL&I asked to collate and analyse the data on these species in order to provide an assessment of the status of the category 11 species (Table 1-1). These analyses can be used by the Ministry for giving advice. Also, the analyses can be used by ICES for its advice on these data limited stocks.

4 of 62

Report number C110/12

3

Methods

Several data sources were used in the analyses described below. This included data from 2 surveys and data from the commercial fleet from EU logbooks and from market sampling. Each data source is shortly described below.

3.1

Survey Data

BTS An extensive description of the Beam Trawl Survey (BTS) can be found at http://datras.ices.dk/Documents/Manuals/Manuals.aspx. In short, the Dutch offshore beam trawl survey started in 1985 by the research vessel “Isis”. The main goal of the survey was to create fisheries independent indices for plaice and sole in the South‐eastern North Sea to be used in the ICES North Sea demersal working group (WGNSSK). Because the focus of the survey was on flatfish, the gear used was the beam trawl. Although the first focus was on plaice and sole, all fish species were measured. Otoliths have been collected for plaice, sole, dab, brill, turbot and cod since 1985. These otoliths can be used to determine the age of fish. Some otoliths are stored and the ages have not been read (see Appendix D for the number of otolith age readings per species per year). In 1996, the research vessel “Tridens” started carrying out a beam trawl survey in the Central North Sea (ICES 2009: WGBEAM Manual). Figure 3-1 shows the covered area of the BTS for both research vessels and the number of years with at least one haul in a specific rectangle. The BTS survey data used in this report were extracted from the ICES database DATRAS (http://datras.ices.dk/Data_products). This DATRAS database is publicly available. However, not all biological data such as age, weight and length measurements were added to the DATRAS database. Therefore we used data from IMARES Frisbe database for analyses on biological data.

Figure 3-1 Number of years sampled by ICES rectangle in the BTS. Left: research vessel Isis, right: research vessel Tridens. Source: DATRAS Report number C110/12

5 of 62

IBTS Q1 and Q3 The North Sea International Bottom Trawl survey (IBTS) survey aims to collect data on the distribution, relative abundance and biological information on a range of round- and flatfish species in ICES area IIIa and IV and VIId. The survey is executed during day-time and a bottom trawl is used (GOV: Grand Ouverture Verticale). A CTD (conductivity, temperature and depth) sampler was deployed at most trawl stations to collect temperature and salinity profiles. Age data are collected for cod, haddock, whiting, saithe, norway pout, herring, mackerel, and sprat, and a number of additional species (Appendix B). The survey takes place in quarter 1 (IBTS Q1) and quarter 3 (IBTS Q3). At present, seven countries participate in the quarter 1 survey: Sweden, Denmark, Norway, Scotland, France, Netherlands and Germany. Six countries participate in the quarter 3 survey: Denmark, Germany, Sweden, Norway, England and Scotland (ICES 2011, IBTSWG). The IBTS covers most of the North sea (Figure 3-2). IBTS survey data used in this report were extracted from the ICES database DATRAS (http://datras.ices.dk/Data_products). In quarter 1 most rectangles were sampled and present in DATRAS for 30-45 years, in quarter 3 most rectangles were sampled for 20 years (Figure 3-2, ICES 2011, IBTSWG). Age, weight and length measurements were not added to the DATRAS database by most countries.

Figure 3-2 Number of years sampled by ICES rectangle by the research vessels IBTS quarter 1 (left) and 3 (right). Source: DATRAS

3.1.1

CPUE estimation

BTS The CPUE is calculated as the number per hectare. Isis rectangles were included in the analysis only if no more than 5 (out of 25) years were missing in the time series (see Appendix A). Tridens rectangles were included if no more than 3 (out of 16) years were missing. For each year and vessel, the hauls were first averaged per selected ICES rectangle and consequently over the rectangles.

6 of 62

Report number C110/12

IBTS The CPUE is calculated as the number per hour. ICES rectangles were included in the analysis only if no more than 3 (out of 20) years were missing in the time series (see Appendix A). For each year the hauls were first averaged per selected ICES rectangle and consequently over the rectangles.

3.2

Commercial fisheries data

Landings and effort data from the commercial fleet were obtained from the EU logbooks; market category composition of landings was obtained from the auction data (sale slips); and a characterisation of the relation between size and age was derived from age-length sampling data. The methods for deriving landings per unit effort indices from the commercial data are described by Van der Hammen et al. (2011) in a report on data availability for the evaluation of stock status of species without catch advice. EU logbook data Official EU logbook data of the entire Dutch fleet are maintained by the NVWA (formerly known as the General Inspection Service, AID). IMARES has access to these logbooks and stores the data in a database called VISSTAT. EU logbook data contain information on: 

landings (kg): by vessel, trip, ICES statistical rectangle and species;



effort (days absent from port): by vessel, trip and ICES statistical rectangle, calculated from trip departure and arrival time; and



vessel information: length, engine power and gear used.

Logbook data are available of the entire Dutch fishing fleet and of foreign vessels landing their catches in the Netherlands. Auction data: landings by market category Auction data cover both the total Dutch fishing fleet and foreign vessels landing their catches on Dutch auctions. These data are also stored in VISSTAT and contain information on: 

landings by market category (kg): by vessel, trip (landing date) and species

Market sampling data In the IMARES market sampling data on length, age, sex and weight are collected for several commercially important species. This is often done on an irregular basis and for several species many years are missing (see Appendix B). In recent years, sampling was executed more regularly. Discard sampling In the IMARES discard sampling, data on length, age, sex and weight are collected for several commercially important species (see Appendix B).

Report number C110/12

7 of 62

4

Dab

Dab (Limanda limanda) is an abundant, widespread demersal species on the Northeast Atlantic shelf and distributed from the Bay of Biscay to Iceland and Norway; including the Barents Sea and the Baltic. Its centre of distribution in the North Sea is located in the southern North Sea (Lozán 1988; Daan et al. 1990, ICES 2010). Their diet consists mainly of crustaceans and echinoderms (Piet et al. 1998).

4.1

BTS

The BTS Isis and Tridens surveys in autumn catch substantial numbers of dab as a result of it being a very abundant species, and the BTS gear being designed to catch flatfish (Figure 4-1). There is considerable variability in the numbers of dab per hectare in BTS hauls for both vessels (Figure 4-1). The average BTS Isis CPUE is higher than the average CPUE in the BTS Tridens for almost all years in the dataset (Figure 4-2). A combined index for the two survey index series is available since 1996. From 1996 onwards, the combined index decreased until 2005, and increased since. In the BTS Tridens and the combined time-series, the index in 2011 has the highest observed value. The BTS survey catches of dab are mainly done in the South-eastern part of the North Sea (Figure 4-3). In addition, dab is caught in the Moray Firth. As a result, most of the North-eastern hauls of the BTS Tridens catch less dab (< 100 n/ha). Plotting the spatial distribution of the CPUE series for the BTS surveys since 1995 reveals no distinctive changes over time (Figure 4-4).

Figure 4-1 box and whisker plot of number of dab per hectare per year and ICES rectangle for the research vessels Isis (left) and Tridens (right). The plot shows the lower quartile (underside of the small blue boxes), median (black dot), upper quartile (upper side of the blue box). The whiskers are defined as the greatest value of the data points excluding outliers. The blue dots are outliers, which are data points that are no more than 1.5 times the length of the blue box away from the box.

8 of 62

Report number C110/12

Figure 4-2 Dab CPUE series: number caught per hectare. ‘Combined’ includes both surveys.

Figure 4-3 Mean CPUE (nha) for the period 2009-2011 per rectangle and vessel. Left: Isis, right: Tridens.

Report number C110/12

9 of 62

Figure 4-4 mean CPUE (number per hectare) for 5 year periods. Time periods: 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

4.1.1

Length distribution and growth

The main length classes caught in the BTS surveys are between 8 and 25 cm. Visual inspection does not reveal a shift in length frequency distribution in the period from 1987-2011 (Figure 4-6). The relationship between the length and weight of a fish is used for two main purposes. First, the relationship is used to predict the weight from the length of a fish. Second, the parameter estimates of the relationship for a sub-selection of fish can be compared to average parameters or parameter estimates from previous years, or parameter estimates among groups of fish to identify the relative condition of the population. Length-weight relationships are estimated by fitting the equation W=a*Lb to the data, where W is weight, L is length and a and b are constant parameters that differ per species.

The length-weight relationship for dab is very similar for males and females (Figure 4-6). The combined estimate for a in the length-weight relationship is 0.0095, and the estimate for b is 3.01 (Figure 4-6, Appendix C). Growth (age length relationships) are estimated by fitting the Von Bertalanffy growth curve, L = Linf (1-eK(t-t0)

) to the age-length data, where L is length, t is age, Linf is the ultimate length, K is the growth

coefficient and t0 is the time at which in theory the fish has a weight of 0.

10 of 62

Report number C110/12

For dab, as is common in flatfish species, the growth of the two sexes is different. The females grow larger than the males, with Linf for females being 25.9 cm and Linf for males being 21.5 cm (Figure 4-6, Appendix C).

Figure 4-5 CPUE (number per hectare) per length class over time. Time periods: 1985 = 1987-1989, 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

Figure 4-6 Left: Length Weight relationship for DAB (source FRISBE-BTS). Red females (a=0.0103, b=2.98), blue: males (a=0.0071, b=3.10). Black line: combined (a=0.0095, b=3.01). Right: Length age relationship for DAB (source FRISBE-BTS). Red: females (Linf=25.89, K= 0.50, t0=-0.46), blue: males (Linf=21.48, K= 0.41, t0=-1.31). Lines: von Bertalanffy fit.

Report number C110/12

11 of 62

4.2

Commercial Data

Almost all (~90%) dab is landed in only one market category (2, 23-30 cm) and for that reason is not sorted (Appendix D, Table D-1, Table D-2). Therefore, for this document no distinction between market categories was made. Tables of the data are listed in Appendix D. 4.2.1

Fishing Effort

Engine power has an effect on LPUE. With higher engine power, a vessel can trawl heavier gear or fish at higher speed, which likely results in higher landing rates. The majority of the Dutch beam trawl fleet consists of vessels with engine powers around 1471 kW (=2000 hp). The analyses have been restricted to the large cutters with engine power above 221 kW. To correct the effort for engine power, data were standardized to a vessel with a 1471 kW engine by applying the following relationship (Rijnsdorp et al. 2006, Quirijns et al. 2008):



Effort(1471)  Effort * kW  1471



where L are landings in kilograms; Effort is effort in days at sea; kW is engine power in kW; and β is a constant that varies between species. As the value of β for dab is unknown, β is set at 1. Figure 4-7 shows that effort of TBB > 221 kW has more than halved in the period 1995 -2011. This decrease is the result of fisheries management, low profitability in the fleet and decommissioning. In the last 4 years, the level of fishing effort has remained relatively stable at a level of approximately 16 000 days at sea, adjusted to the fishing efficiency of a 1471 kW vessel.

Figure 4-7 “Adjusted” Effort (days at sea per 1471 kW vessel) over time by Dutch large beam trawlers (< 221 kW).

12 of 62

Report number C110/12

Figure 4-8 Annual fishing effort by the Dutch large beam trawling fleet operating in the North Sea. Source: Visstat.

4.2.2

Landings

Dab landings fluctuate between 6086 tonnes in 1999 and 2856 tonnes in 2009 (Figure 4-9).

Figure 4-9 Dab landings by Dutch trawlers (TBB > 221 kW)

Report number C110/12

13 of 62

Figure 4-10 Average Dab landings (tonnes) per year per ICES rectangle (average 2009-2011) for large Dutch beam trawlers (>221 kW).

14 of 62

Report number C110/12

4.2.3

LPUE

This paragraph describes trends in Landings per Unit Effort (LPUE). Data from large Dutch trawlers are included. In the Dutch fleet average LPUE of dab is relatively stable since 1998, fluctuating around 175 kg per day at sea (Figure 4-11). No real interpretable cohort signal can be found in the age structured LPUE time series. (Figure 4-12).

Figure 4-11 Dab LPUE of Dutch beam trawlers. Source: VISSTAT.

Figure 4-12 Age composition of Dab LPUE. Left in kg per day, right in percentage. Age and length data from 2008 are missing, because in 2008 no age sampling (market sampling) was done (Appendix B, Table B1).

Report number C110/12

15 of 62

Figure 4-13 Mean LPUE per ICES rectangle (average 2009-2011). Source: Visstat

16 of 62

Report number C110/12

5

European Flounder

European Flounder (Platichthys flesus) occurs in the Eastern Atlantic in coastal and brackish waters including the white sea, black sea and the Mediterranean Sea. the smaller size classes of flounder feed mainly on polychaetes, the larger size classes feed on crustaceans (Piet et al 1998).

5.1

BTS

Flounder occurs mainly in coastal areas. For this reason it is caught regularly by the BTS Isis, whereas the BTS Tridens barely catches flounder (Figure 5-2). Data from the Isis show considerable variability in CPUE, ranging from 0 to over 60 individuals per hectare (Figure 5-1, the black dots show the medians and the blue dots show the outliers). The CPUE index for the Isis is available since 1987 and shows high numbers per hectare in the last two years (Figure 5-2). The average catch probability over the time series by the Isis is 20%, which means that in one out of five hauls flounder is caught. The catch probability shows a gradual increase since 1987 (Figure 5-2). Plotting the spatial distribution of the CPUE series for the BTS Isis surveys shows high variability over time, but does not show an obvious change in the spatial distribution (Figure 5-3).

Figure 5-1 box and whisker plot of number of flounder per hectare per year and ICES rectangle for the research vessels Isis (left) and Tridens (right). The plot shows the lower quartile (underside of the small blue boxes), median (black dot), upper quartile (upper side of the blue box). The whiskers are defined as the greatest value of the data points excluding outliers. The blue dots are outliers, which are data points that are no more than 1.5 times the length of the blue box away from the box.

Report number C110/12

17 of 62

Figure 5-2 Flounder CPUE series. Left: number caught per hectare. Right: catch probability: the chance that a flounder is caught. For each year and survey, the hauls were first averaged per selected ICES rectangle and consequently over the rectangles. ‘Combined’ includes both surveys.

18 of 62

Report number C110/12

Figure 5-3 mean CPUE (number per hectare) for 5 year periods. Time periods: 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011.

5.1.1

Length distribution and growth

Especially in the period around 2010, many small individuals of 3 to 8 cm were caught by the Isis. This can bean indication of strong recruitment. Overall, the length distribution is variable and does not show a clear trend (Figure 5-4). The length-weight relationship is similar for males and females (Figure 5-5). The combined estimate for a in the LW relationship W=aLb is 0.012, and the estimate for b is 2.98 (Figure 5-5). The growth of the two sexes is different, as is common in flatfish species. The females grow larger than the males, with the estimated Linf for females being 44.9 cm and Linf for males 35.7 cm (Figure 5-5, Appendix C). Do note that otolith sampling and reading in the BTS started only recently, resulting in a small amount of data points (Figure 5-5). The extreme difference in estimated length for small individuals is likely the result of a lack of data, rather than differences in growth.

Report number C110/12

19 of 62

Figure 5-4 CPUE (number per hectare) per length class over time. Left: equal y-axis scales, right: variable scales. Time periods: 1985 = 1987-1989, 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

Figure 5-5 Left: Length Weight relationship for European flounder (source FRISBE-BTS). Red: females (a=0.016, b=2.89), blue: males (a=0.024, b=2.75). Black line: combined (a=0.012, b=2.98). Right: Length age relationship for European flounder (source FRISBE-BTS). Red: females (Linf = 44.87, K = 0.27, t0 = 2.58), blue: males (Linf = 35.67 , K = 0.73, t0 = -0.16). Lines: von Bertalanffy fit.

20 of 62

Report number C110/12

6

Witch Flounder

Witch flounder (Glyptocephalus cynoglossus) is common in the northern North Sea, west of the British Isles, in Icelandic waters and along the North American east coast. This species is mainly found on soft bottoms, mostly clay, but in some cases on clean sandy bottoms (Molander, 1935, in ICES 2012). In the North Sea, witch flounder live at depths between 100 and 200 meters primarily in the Norwegian trench and in the northern parts of the North Sea. The main diet consists of crustaceans, polychaetes, brittle stars and fishes.

6.1

BTS

The BTS Isis catches virtually no witch flounder (Figure 6-1, Figure 6-2). The BTS Tridens survey catches some witch flounder (Figure 6-1, Figure 6-2), mainly in its north-western sampling area (Figure 6-3). The combined survey index fluctuates without a clear trend (Figure 6-2). The spatial distribution of witch flounder shows a an increase in the southern range (ICES rectangles 40F0-40F2) in the last time period (Figure 6-4).

Figure 6-1 box and whisker plot of number of witch flounder per hectare per year and ICES rectangle for the research vessels Isis (left) and Tridens (right).

Report number C110/12

21 of 62

Figure 6-2 Witch flounder CPUE series. Left: number caught per hectare. Right: catch probability: chance that witch flounder is caught in the survey. ‘Combined’ includes both surveys.

Figure 6-3 Mean CPUE (nha) for the period 2009-2011 per rectangle (Tridens).

22 of 62

Report number C110/12

Figure 6-4 mean CPUE (number per hectare) for 5 year periods. Time periods: 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011.

6.1.1

Length and growth

In the period around 1995 and 2000 relatively many small individuals were caught by the Tridens. Overall, the length distribution is variable and does not show a clear trend (Figure 6-5). The lengthweight relationship is similar for males and females (Figure 6-6). The combined estimate for a in the LW relationship W=aLb is 0.0020, and the estimate for b is 3.33 (Figure 6-6, Appendix C). Otholith sampling and age reading has not been done for witch flounder.

Figure 6-5 CPUE (number per hectare) per length class over time. Time periods: 1985 = 1987-1989, 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011.

Report number C110/12

23 of 62

Figure 6-6 Length Weight relationship for witch flounder (source FRISBE-BTS). Red females (a=0.0024 , b=3.28) , blue: males (a=0.0031, b=3.19). Black line: combined (a=0.0020, b=3.33).

24 of 62

Report number C110/12

7

Lemon Sole

Lemon sole (Microstomus kitt) occurs in the Northeast Atlantic from the Bay of Biscay to the White Sea and off Iceland. Lemon sole mainly feeds on polychaetes (Fishbase).

7.1

BTS

Lemon sole is caught frequently by the BTS Isis and BTS Tridens. CPUE ranges between 0 to around 55 individuals per hectare (Figure 7-1). The CPUE index for the Isis shows an moderate increase in lemon sole catches, the BTS Tridens is available since 1996 and shows a stronger increase (Figure 7-1). The probability of catching lemon sole shows similar increasing trends for both the Isis as the Tridens (Figure 7-2). Plotting the spatial distribution of the CPUE series for the BTS surveys indicates an offshore move of the species: both in the BTS-ISIS and the BTS-Tridens (Figure 7-4).

Figure 7-1 box and whisker plot of number of lemon sole per hectare per year and ICES rectangle for the research vessels Isis (left) and Tridens (right).

Figure 7-2 Lemon sole CPUE series. Left: number caught per hectare. Right: catch probability. ‘Combined’ includes both surveys. Report number C110/12

25 of 62

Figure 7-3 Mean CPUE (nha) for the period 2009-2011 per rectangle and vessel. Left: Isis, right: Tridens.

26 of 62

Report number C110/12

Figure 7-4 mean CPUE (number per hectare) for 5 year periods. Time periods: 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011.

7.1.1

Length distribution and growth

Both the BTS Tridens and the Isis indicate a decreasing trend in the average length in the catch (Figure 7-5). In the Tridens, the CPUE has increased over all length classes. The length-weight relationship is similar for males and females (Figure 7-6). The combined estimate for a in the LW relationship W=aLb is 0.0077, and the estimate for b is 3.08 (Appendix C). The growth of the two sexes differs: the females grow larger than the males, with Linf for females being 29.8cm and Linf for males 26.11cm (Figure 7-6, Appendix C).

Report number C110/12

27 of 62

Figure 7-5 CPUE (number per hectare) per length class over time. Time periods: 1985 = 1987-1989, 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

Figure 7-6 Left: Length-Weight relationship for lemon sole (source FRISBE-BTS). Red: females (a=0.0098, b=3.02), blue: males (a=0.0077, b=3.07). Black line: combined (a=0.0077, b=3.08). Right: length-age relationship (source FRISBE-BTS). Red: females (Linf=29.83, K= 0.39, t0=-0.85), blue: males (Linf=26.11, K= 0.37, t0=-1.35). Lines: von Bertalanffy fit.

28 of 62

Report number C110/12

8

Brill

The biogeographical range of brill (Scophthalmus rhombus) extends from the Mediterranean and North Atlantic Ocean in the south of the Irish Sea, North Sea, Skagerrak and Kattegat in the north. Brill is a demersal species that usually lives in sandy habitat and can reach a maximum length of 75 cm. Spawning is between March and August. Juvenile brill lives in the shallow coastal areas during the first two years, after which it moves to deeper water. Brill is a piscivorous species (from Teal and van Keeken 2011).

8.1

BTS

The BTS Isis survey in autumn often catches brill in low numbers, whereas the BTS Tridens only occasionally catches brill (Figure 8-1). The number caught per hectare lay between 0 and just above 3. Neither the CPUE in number per hectare nor the probability of catching brill in the Isis has changed much in the time-series. The highest average CPUE in the time-series is around 0.6 brill per hectare by the Isis in 1992 and 1993 (Figure 8-2). The Tridens has a low probability of catching brill. Although the combined index (in numbers per ha) shows an increase since 2007 (Figure 8-2) this increase is smaller than the inter-annual variation in the time series. The BTS survey catches brill primarily in the Dutch and Danish coastal areas (Figure 8-3). Plotting the spatial distribution of the CPUE series for the BTS surveys since 1995 reveals no distinctive changes in its distribution over time (Figure 8-4).

Figure 8-1 box and whisker plot of number of brill per hectare per year and ICES rectangle for the research vessels Isis (left) and Tridens (right).

Report number C110/12

29 of 62

Figure 8-2 Brill CPUE series. Left: number caught per hectare. Right: probability per haul. ‘Combined’ includes both surveys.

Figure 8-3 Mean CPUE (nha) for 2009:2011 per rectangle and vessel.

30 of 62

Report number C110/12

Figure 8-4 mean CPUE (number per hectare) for 5 year periods. Time periods: 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

8.1.1

Length distribution and growth

The main length classes caught in the BTS-Isis surveys are between 20 and 40 cm. Overall, the length distribution does not show a clear trend, which is probably caused by the low occurrences of brill catches (Figure 8-5). The length-weight relationship is very similar for males and females (Figure 8-6). The combined estimate for a in the LW relationship W=aLb is 0.014 and the estimate for b is 2.99. Age readings for brill in the BTS are available from 2001 (Appendix B). The females grow larger than the males, with Linf for females being 56.6 cm and Linf for males 38.8 cm (Figure 8-6, Appendix C). Brill is a fast growing species that reaches large sizes (fishbase indicates Linf ≈ 75 cm). The large difference between the Linf estimated from the BTS survey samples and the fishbase estimate may result from the low towing speed of the BTS (4 knots).This low towing speed reduces the catchability for larger specimens. This lack of large specimens in the sample likely causes a bias in the estimated growth curves.

Report number C110/12

31 of 62

Figure 8-5 CPUE (number per hectare) per length class over time. Time periods: 1985 = 1987-1989, 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

Figure 8-6 Left: Length-weight relationship for brill (source FRISBE-BTS). Red females (a=0.016, b=2.97) , blue: males (a=0.013, b=3.01). Black line: combined (a=0.014, b=2.99). Right: length-age relationship (source FRISBE-BTS). Red: females (Linf=56.62 , K= 0.32, t0=-1.19), blue: males (Linf=38.84, K= 0.59, t0=-0.94). Lines: von Bertalanffy fit.

32 of 62

Report number C110/12

9

Turbot

The geographical range of turbot extends from the Mediterranean and North Atlantic Ocean in the south to the Irish Sea, North Sea, Skagerrak and Kattegat in the north. Turbot is a demersal boreal species that lives in sandy and rocky habitat. Turbot spawns between April and August at 10-80 meters depth. Like brill, turbot is a piscivorous flatfish species (source: Teal and van Keeken 2011).

9.1

BTS

The BTS Isis survey in autumn frequently catches turbot in low numbers, whereas the BTS Tridens only occasionally catches turbot (Figure 9-1). The number caught per hectare in a rectangle lay between 0 and just above 8. Neither the CPUE in number per hectare nor the probability of catching turbot in the Isis has changed much in the time-series. The highest average number in the time-series are around 1 turbot per hectare by the Isis between 1990 and 1994 and in 2000 (Figure 9-2). The Tridens has a low probability of catching turbot over the whole time series, but similar to brill, the trend seems to be upwards (Figure 9-2). The BTS survey catches turbot primarily in the Dutch and Danish coastal areas (Figure 9-3). Plotting the spatial distribution of the CPUE series for the BTS surveys since 1995 reveals no distinctive changes in its distribution over time (Figure 9-4).

Figure 9-1 box and whisker plot of number of turbot per hectare per year and ICES rectangle for the research vessels Isis (left) and Tridens (right).

Report number C110/12

33 of 62

Figure 9-2 Turbot CPUE series. Left: number caught per hectare. Right: probability per haul. For each year and survey, the hauls were first averaged per selected ICES rectangle and consequently over the rectangles. ‘Combined’ includes both surveys.

Figure 9-3 Mean CPUE (nha) for the period 2009-2011 per rectangle by research vessel Isis.

34 of 62

Report number C110/12

Figure 9-4 mean CPUE (number per hectare) for 5 year periods. Time periods: 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011.

9.1.1

Length distribution and growth

The main length classes caught in the BTS-Isis surveys are between 15 and 40 cm. Overall, the length distribution does not show a clear trend, which is probably caused by the low occurrences of turbot catches (Figure 8-5). The length-weight relationship is very similar for males and females (Figure 8-6). The combined estimate for a in the LW relationship W=aLb is 0.014 and the estimate for b is 2.99 (Appendix C). Age readings for brill in the BTS are available from 2001 (Appendix B). The females grow larger than the males, with Linf for females being 56.62 cm and Linf for males 38.84 cm (Figure 8-6, Appendix C). Like brill, turbot is a fast growing species that reaches large sizes (fishbase indicates Linf ≈ 100 cm). The large difference between the Linf estimated from the BTS survey samples and the fishbase estimate may result from the low towing speed of the BTS (4 knots).This low towing speed reduces the catchability for larger specimens. This lack of large specimens in the sample likely causes a bias in the estimated growth curves.

Report number C110/12

35 of 62

Figure 9-5 CPUE (number per hectare) per length class over time. Time periods: 1985 = 1987-1989, 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

Figure 9-6 Left: Length weight relationship for turbot (source FRISBE-BTS). Red females (a=0.013, b=3.11) , blue: males (a=0.022, b=2.95). Black line: combined (a=0.012, b=3.13). Right: length-age relationship (source FRISBE-BTS). Red: females (Linf=54.74 , K= 0.39, t0=-0.39), blue: males (Linf=36.71, K= 0.56, t0=0.58). Lines: von Bertalanffy fit.

36 of 62

Report number C110/12

10 Horse mackerel

Horse mackerel is widely distributed, occurring in the Eastern Atlantic from Norway to South Africa, as well as in the Mediterranean Sea (ICES 2011b). In the list of species described in this report, horse mackerel is the only pelagic species. ICES distinguishes 3 stocks, the Southern, the Western and the North Sea stock, the last two being of importance for the Netherlands (Figure 10-1). The Western stock consists of ICES divisions IIIa and IVa in quarter 3 and 4 and of ICES divisions IIa, Vb, VIa, VIIa–c,e–k and VIIIa-e for all quarters. The North Sea stock consists of divisions IIIa and IVa in quarter 1 and 2 and of divisions IVb,c and VIId for all quarters. In the Eastern part of the North Sea (off Jutland), horse mackerel were found to forage predominantly on fish (Dahl and Kirkegaard, 1987), with 0-group whiting being the most important prey item, followed by other gadoids and herring (www.homsir.com/biology/biology.html). The ICES advice for the North Sea mackerel stock in the period 2002 – 2010 was to not increase the catches, in order to avoid an expansion of the fishery. For 2011 there was no ICES advice, and for 2012 the advice was to reduce catches (ICES 2011b). For the North Sea stock, fisheries independent indices are scarce and debated by the working group (ICES WGWIDE). Opinions differ whether IBTS data is representative for the North sea horse mackerel stock given that this survey uses a bottom trawl gear; although with a very wide opening. During the third and fourth quarters, the commercial catches are taken by pelagic fisheries (pelagic trawlers and purse seiners) and it is therefore questioned how well horse mackerel are represented in the IBTS data.However, Ruckert et. al. (2002) argue that horse mackerel of 2 years and older are predominantly demersal in habit (Eaton 1983). In addition, the species apparently stays very close to the seabed during daylight and migrates upwards during the night (Barange et al. 1998). This would mean that for older ages, CPUE data from IBTS may be used as an abundance index (ICES 2011). For the Western stock, ICES uses an egg survey to estimate the SSB (standing stock biomass), which is used in the stock assessment models. However, there is also discussion about the use of egg surveys for an index for horse mackerel. An assumption of the use of the egg survey is that horse mackerel is a determinate spawner. This means that fecundity can be determined prior to spawning. However, horse mackerel is now considered to be an indeterminate spawner, where the eggs to be spawned are not all present in the ovary at the start of the spawning season, and fecundity can therefore not be assessed at the start of the spawning season, whereas earlier, horse mackerel was assumed to be a determinate spawner. In addition, no egg surveys for horse mackerel were carried out in the North Sea since 1991 and the mackerel egg survey in the North Sea does not cover the spawning area of horse mackerel. Egg surveys for horse mackerel were carried out only during the period 1988-1991 (from ICES 2011b).

Report number C110/12

37 of 62

Figure 10-1 Distribution of Horse Mackerel in the Northeast-Atlantic and stock definitions. Map source: GEBCO, polar projection, 200 m depth contour drawn. (ICES WGWIDE 2011b)

10.1 IBTS Q3 Horse mackerel data from the IBTS Q3 shows very high variability in CPUE per haul, ranging from 0 to over 150.000 individuals per hour (Figure 10-2). The CPUE index is available since 1991 and also shows high variability per year in horse mackerel catches per hour. Since 2004, variability seems to have ceased, and the CPUE is also lower since 2004. The probability of catching horse mackerel in a haul shows a slowly declining trend over time (Figure 10-3). Horse mackerel CPUE in quarter 3 is highest in the Dutch and Danish coastal areas (Figure 10-4).

38 of 62

Report number C110/12

Figure 10-2 box and whisker plot of number of horse mackerel per hour per year and ICES rectangle in IBTS Quarter 3.

HOM 1.0

HOM

0.6

0.8

IBTS Q3

0.0

0.2

0.4

probability

500 1000 0

Nr/hour

2000

IBTS Q3

1995

2000 Year

2005

2010

1995

2000

2005

2010

year

Figure 10-3 Horse mackerel CPUE series. Left: number caught per hour in the IBTS Q3 survey. Right: probability per haul in the IBTS Q3 survey. For each year the hauls were first averaged per selected ICES rectangle and consequently over the rectangles.

Report number C110/12

39 of 62

Figure 10-4 Mean CPUE (number per hour) for 2009:2011 per rectangle and vessel.

Length distribution and growth The North Sea horse mackerel CPUE by length shows a peak at small individuals till 10 cm and a smaller peak at individuals between 20 and 25 cm. In the period between 2005 and 2009, the catches were very low. In 2010 and 2011 the CPUE of the older ages are also very low, but the CPUE of the younger ages has increased again. The length-weight relationship is similar for males and females (Figure 10-6). The combined estimate for a in the LW relationship W=aLb is 0.019, and the estimate for b is 2.82 (Figure 10-6). The two sexes have similar growth (Figure 10-6); females grow to similar sizes as the males, with Linf for females being 36.8 cm and Linf for males 36.3 cm. Because there were no horse mackerel age readings present in the DATRAS database and otoliths from horse mackerel IBTS- Tridens catches are not analysed either, market samples are used to estimate the growth of horse mackerel.

40 of 62

Report number C110/12

Figure 10-5 CPUE (number per hour) per length class over time. Time periods: 1990 = 1990-1994, 1995 = 1995-1999, 2000 = 2000-2004, 2005 = 2005-2009, 2010 = 2010-2011

Figure 10-6 Left: Length weight relationship for horse mackerel (source Frisbe-IBTS). Red females (a=0.0032, b=3.29), blue: males (a=0.0044, b=3.19). Black line: combined (a=0.0039, b=3.23). Right: length-age relationship (source FRISBE-IBTS). Red: females (Linf=34.29, K= 0.16, t0=-4.27), blue: males (Linf=34.52 , K= 0.15, t0=-4.43). Lines: von Bertalanffy fit.

Report number C110/12

41 of 62

11 Conclusions and Interpretation Time series such as the CPUE indices presented in this report only show how the state of the stock is relative to the other years in the time series. The starting point of the series is often the first year of the surveys. When interpreting the CPUE series, it is therefore essential to realize that the starting point of the series should not be interpreted as the unfished state of the stock. The length frequency distribution presented here, does not only depend on the occurrence of the species, but also on the catchability of the gear used. Selectivity of the gear and catchability heavily influence our perception of the size composition and abundance. For example, because the towing speed and the gear of the BTS vessels results in relatively high catchability for the intermediate size-classes compared to the larger and very small size classes. It is therefore likely that there is an underestimation of the larger size classes relative to the smaller size classes. Likewise, very small size classes may also be underrepresented, because the mesh size used may be too large to catch them. The spatial distribution of stocks may change over time. For example, plaice juveniles have moved offshore, away from coastal areas (van Keeken et al. 2007). This affects the indices as independent estimates of the overall stock size. We have visually inspected the spatial distribution of the survey CPUEs for such changes. Only in the case of lemon sole we detected off shore movement, and a possible southwards movement of witch flounder. The effects of changes in spatial distribution on the interpretation of survey indices should be studied. Dab 

Commercial LPUE is stable over the time series. The catch cohort signal is difficult to track. Dab is of commercially low value and mainly caught as bycatch in the sole and plaice targeting fisheries and it is therefore discarded substantially (Helmond et al. 2011). Because of the high discard rate, LPUE has to be interpreted carefully.



CPUE BTS-Isis decreases since beginning of time series, but increases in recent years.



CPUE BTS-Tridens increases since beginning of time series.



No shift in length frequency distribution is observed.



No shift in spatial distribution is observed.

European Flounder 

CPUE BTS-Isis shows high numbers per hectare in the last two years.



The average catch probability shows a gradual increase.



The length distribution is variable and does not show a clear trend.



No shift in spatial distribution is observed.

Witch Flounder 

The survey indices fluctuate without a clear trend.



The length distribution is variable without a clear trend.



The spatial distribution of witch flounder shows an increase in the southern range (ICES rectangles 40F0-40F2) in the last time period.

Lemon Sole 

The CPUE index for the BTS-Isis and BTS-Tridens show increasing trends.



There is an offshore move of lemon sole, based on data from the BTS-ISIS and the BTS-Tridens.



Both the BTS Tridens as the Isis indicate a weak decreasing trend in the average length in the catch.

42 of 62

Report number C110/12

Brill 

Neither the CPUE nor the probability of catching brill in the BTS-Isis has changed much.



No changes in spatial distribution over the years.



The length frequency distribution does not show a clear trend.

Turbot 

Neither the CPUE in number per hectare nor the probability of catching turbot in the BTS-Isis have changed much in the time-series.



No changes in spatial distribution over the years.



The length frequency distribution does not show a clear trend.

Horse Mackerel 

CPUE per haul in the IBTS is highly variable.



The probability of catching horse mackerel in a survey haul shows a slowly declining trend over time.



The length frequency distribution shows a peak at small individuals till 10 cm and a smaller peak at individuals between 20 and 25 cm, but no clear trend over the years



Lack of fisheries independent indices. Opinions differ whether IBTS data is representative for the North sea horse mackerel stock.

11.1 Future management advice For this report the authors collated the data available for ‘data limited’ fish stocks such as the flatfish species described in this report and horse mackerel in the North Sea. For those ‘data limited’ stocks for which a TAC is defined, the future TACs depend on the management objectives and the harvest control rules supporting these objectives. At this moment there are no stock assessments for these stocks. In 2012, the methodology for advice on these stocks is being finalized. One approach for formulation of advice, is to use survey trends. In short, trends in research vessel surveys are used to look at the trends in stocks. The survey index of the last two years is compared with the survey index of the three preceding years. Based on the outcome of the comparison, an increase or decrease in catch is advised. As such, our analysis can be used as input for the ICES advice. If the described method is applied to the stocks under consideration, the future catch advice depends on the trends in the surveys. Some of the species for which the stocks are described in this report are bycatch species in the fishery targeting plaice and sole (the so called ‘associated stocks’). For that reason, the measures applied for management of plaice and sole influence the development of the associated stocks. Sole and plaice are managed under a long term management plan (Council Regulation (EC) No 676/2007). The aim of the long term management plan for sole and plaice is to fish these stock at fishing mortality levels associated with high long term yields. If fishing mortalities are above the target of the plan, they should be gradually reduced. For plaice, fishing mortality is currently below the target in the plan (ICES WGNSSK 2012). As a result, the stock has increased, as have the TACs. For sole however, the current fishing mortality is estimated to be above the target, and further cuts in TACs and fishing effort are to be expected. Given the expected reductions of fishing effort in the long term management plan for sole and plaice, one could expect that the stock sizes of the associated stocks increase. However, the stock size of these associated stocks does not only depend on the fishing mortality. They also depend on the future recruitment and future growth of individuals, both are currently unknown. The recruitment of marine fish especially is highly variable. In addition, the spatial distribution differs per species. This may cause fishing fleets to change their fishing patterns as a result of fisheries management, and increasingly target the bycatch species. This would counteract the expected reductions in fishing mortality as a result of the Report number C110/12

43 of 62

sole and plaice management plan. In conclusion, the advised TACs by ICES for the associated species will unlikely follow the TACs for sole and plaice.

44 of 62

Report number C110/12

References Barange, M., Pillar, S. C., and Hampton, I. (1998) Distribution patterns, stock size and life-history strategies of Cape horse mackerel Trachurus trachurus capensis, based on bottom trawl and acoustic surveys. South African Journal of Marine Science, 19: 433–447. Daan, N. Bromley, PJ. Hislop, JRG. (1990) Ecology of North Sea Fish. Netherlands Journal of Sea Research, 26: 343–386 Dahl, K. and Kirkegaard, E. (1987) The diet and consumption of horse mackerel (Trachurus trachurus) in the Eastern North Sea. ICES CM 1987/H:43.Eaton, D. R. 1983. Scad in the North-East Atlantic. Laboratory Leaflet, Ministry of Agriculture, Fisheries and Food, Directorate of Fisheries Research, Lowestoft, 56: 20 pp. Hammen, T. van der; Poos, J.J.; Quirijns, F.J. (2011). Data availability for the evaluation of stock status of species without catch advice: Case study: turbot (Psetta maxima) and Brill (Scophthalmus rhombus). IJmuiden : IMARES, (Report C109/11) - p. 35. Handboek bestandsopnamen en routinematige bemonsteringen op het water. Versie 6, februari 2012 Helmond, A.T.M. van; Uhlmann, S.S.; Overzee, H.M.J. van; Bierman, S.M.; Bol, R.A.; Nijman, R.R. (2011) Discard sampling of Dutch bottom-trawl fisheries in 2009 and 2010. IJmuiden : Centrum voor Visserijonderzoek, (CVO report 11.008) - p. 101. ICES (2009) Manual for the Offshore Beam Trawl Surveys, Revision 1.2, June 2009, Working Group on Beam Trawl Surveys. 30 pp. ICES (2010) Report of the Working Group on Beam Trawl Surveys (WGBEAM), ICES CM 2001/SSGESST:17 ICES (2011) Report of the International Bottom Trawl Survey Working Group (IBTSWG), 28 March – 1 April 2011, ICES Headquarters, Copenhagen. ICES CM 2011/SSGESST:06. 237 pp. ICES (2011b) Report of the Working Group on Widely Distributed Stocks (WGWIDE), 23 - 29 August 2011, ICES Headquarters, Copenhagen, Denmark. ICES CM 2011/ACOM:15. 642 pp. ICES (2012) Report of the Working Group on Assessment of New MoU Species (WGNEW), 5 - 9 March 2012, ICES CM 2012/ACOM:20. 258 pp. ICES (2012b) Report of the Workshop on the Development of Assessments based on LIFE history traits and Exploitation Characteristics (WKLIFE), 13–17 February 2012, Lisbon, Portugal . ICES CM 2012/ACOM:36. 122 pp. Keeken, O.A. van, van Hoppe, M., Grift, R.E., Rijnsdorp, A.D. (2007) Changes in the spatial distribution of North Sea plaice (Pleuronectes platessa) and implications for fisheries management. Journal of Sea Research, 57: 187-197 Lozán, JL. (1988) Verbreitung, Dichte, und Struktur der Population der Klieschen (Limanda limanda L.) in der Nordsee mit Vergleichen zu Popualtionen um Island und in der Ostsee anhand meristischer Merkmale. Arch. Fischereiwiss, 38: 165–189 Molander, A. (1935) Further data concerning the witch (Pleuronectes cynoglossus L.). Svenska HydrografiskaBiologiska Kommissionens Skrifter. Ny serie Biologi. Band I. NR 6. 1935. Tryckeriaktiebolaget Tiden, Stockholm. Piet, G.J., Pfisterer, A.B., Rijnsdorp, A.D. (1998) On factors structuring the flatfish assemblage in the southern North Sea. Journal of sea research, 40(1-2): 143 -152

Report number C110/12

45 of 62

Punt, A. E., Smith, D. C., and Smith, A. D. M. (2011) Among-stock comparisons for improving stock assessments of data-poor stocks: the “Robin Hood” approach. – ICES Journal of Marine Science, 68: 972–981. Rijnsdorp, A. D., W. Dekker, and N. Daan. 2006. Partial fishing mortality per fishing trip: a useful indicator for effective fishing effort in management of mixed demersal fisheries. ICES Journal of Marine Science 63:556-566. Quirijns F.J., Poos J.J., Rijnsdorp AD (2008) Standardizing commercial CPUE data in monitoring stock dynamics: Accounting for targeting behaviour in mixed fisheries. Fisheries Research89:1-8 Rückert, C., Floeter, J., A. Temming. (2002) An estimate of horse mackerel biomass in the North Sea, 19911997. - ICES Journal of Marine Science, 59: 120-130. Teal, L.R.; Keeken, O.A. van (2011) The importance of the surf zone for fish and brown shrimp in The Netherlands. IMARES, (Report C054/11).

46 of 62

Report number C110/12

Justification Rapport C110/12 Project Number:

4308601031

The scientific quality of this report has been peer reviewed by the a colleague scientist and the head of the department of IMARES.

Approved:

Floor Quirijns Senior Fisheries Scientist

Signature:

Date:

10 October 2012

Approved:

Dr. ir. T.P. Bult Head of Fisheries department

Signature:

Date:

Report number C110/12

10 October 2012

47 of 62

Appendix A. Number of years sampled per research vessel

Table A-1 BTS: Number of years sampled per ship. Grey areas represent the rectangles that are included in the analysis. AREA_CODE 32F1 32F2 32F3 33F1 33F2 33F3 33F4 34F1 34F2 34F3 34F4 35F0 35F1 35F2 35F3 35F4 35F5 36F0 36F1 36F2 36F3 36F4 36F5 36F6 36F7 37F0 37F1 37F2 37F3 37F4 37F5 37F6 37F7 37F8 38E9 38F0 38F1 38F2 38F3 38F4 38F5 38F6 38F7 38F8 39E9 39F0 39F1 39F2 39F3 39F4 39F5 39F6 39F7 39F8 40E9 40F0 40F1 40F2 40F3 40F4 40F5

48 of 62

ISI 9 11 24 10 12 24 25 0 12 25 25 0 0 4 23 25 11 0 1 3 21 24 25 24 24 0 0 1 19 22 25 24 25 21 0 0 0 0 20 22 25 24 25 11 0 0 0 0 0 21 25 24 24 22 0 0 0 0 0 0 8

TRI2 5 4 0 1 5 0 1 7 9 0 1 7 15 16 9 0 0 14 15 15 8 2 0 1 0 16 15 15 15 2 0 1 0 0 6 16 15 16 16 16 0 1 1 0 16 16 9 3 6 16 3 1 1 1 16 16 16 14 15 16 16

AREA_CODE 40F6 40F7 41E8 41E9 41F0 41F1 41F2 41F3 41F4 41F5 41F6 42E8 42E9 42F0 42F1 42F2 42F3 42F4 42F5 42F6 43E8 43E9 43F0 43F1 43F2 43F3 43F4 43F5 43F6 43F7 44E6 44E7 44E8 44E9 44F0 44F1 44F2 44F3 44F4 44F5 45E6 45E7 45E8 45E9 45F0 45F1 45F2 45F3 45F4 45F5 46E8 46E9 46F2 47E9 47F3 48E9 48F2 49E9 49F2 50E9 50F2

ISI 10 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

TRI2 16 1 9 16 16 2 9 3 16 16 16 8 16 16 15 16 16 15 16 16 8 15 15 6 11 2 13 15 15 1 13 13 13 14 14 14 12 12 11 6 13 12 8 9 6 5 4 4 1 1 1 2 1 1 1 1 1 1 1 1 1

Report number C110/12

Table A-2 IBTS Q3: Number of years sampled. Grey areas represent the rectangles that are included in the analysis. AREA_CODE 31F1 31F2 32F1 32F2 32F3 33F1 33F2 33F3 33F4 34F1 34F2 34F3 34F4 35F0 35F1 35F2 35F3 35F4 36F0 36F1 36F2 36F3 36F4 36F5 36F6 36F7 37F0 37F1 37F2 37F3 37F4 37F5 37F6 37F7 37F8 38E9 38F0 38F1 38F2 38F3 38F4 38F5 38F6 38F7 38F8 39E8 39E9 39F0

IBTS Q3 1 4 20 20 20 5 20 20 19 4 20 20 20 14 20 20 20 20 20 20 20 20 20 20 19 5 19 19 19 20 20 20 20 20 9 20 20 20 20 20 20 20 20 20 7 3 20 20

Report number C110/12

AREA_CODE 39F1 39F2 39F3 39F4 39F5 39F6 39F7 39F8 40E8 40E9 40F0 40F1 40F2 40F3 40F4 40F5 40F6 40F7 40G2 41E7 41E8 41E9 41F0 41F1 41F2 41F3 41F4 41F5 41F6 41F7 41G0 41G1 41G2 42E7 42E8 42E9 42F0 42F1 42F2 42F3 42F4 42F5 42F6 42F7 42G1 42G2 43E8 43E9

IBTS Q3 20 20 20 20 20 20 19 7 20 20 20 20 20 20 20 20 20 20 5 20 20 20 20 20 20 20 20 18 18 19 18 19 19 20 20 20 20 20 20 20 20 20 20 18 19 19 20 20

AREA_CODE 43F0 43F1 43F2 43F3 43F4 43F5 43F6 43F7 43F8 43F9 43G0 43G1 43G2 44E6 44E7 44E8 44E9 44F0 44F1 44F2 44F3 44F4 44F5 44F8 44F9 44G0 44G1 45E6 45E7 45E8 45E9 45F0 45F1 45F2 45F3 45F4 45F9 45G0 45G1 46E6 46E7 46E8 46E9 46F0 46F1 46F2 46F3 46G0

IBTS Q3 20 20 20 20 20 17 17 15 19 12 19 19 19 20 20 20 20 20 20 20 20 20 20 19 19 19 19 19 20 20 20 20 20 20 20 20 17 19 19 3 20 20 20 20 20 20 20 17

AREA_CODE 47E6 47E7 47E8 47E9 47F0 47F1 47F2 47F3 48E6 48E7 48E8 48E9 48F0 48F1 48F2 48F3 49E6 49E7 49E8 49E9 49F0 49F1 49F2 49F3 50E7 50E8 50E9 50F0 50F1 50F2 50F3 51E8 51E9 51F0 51F1 51F2 37E9 44F6 52E9 52F0 52F1 38G2 46G1 36F8 38E8

IBTS Q3 3 20 20 20 20 20 20 20 4 20 20 20 20 20 20 13 4 19 20 20 20 20 20 20 5 18 20 19 20 20 10 19 20 20 20 19 2 3 8 10 12 1 7 1 1

49 of 62

Appendix B. Age and length samples by species Table B-1 Number of length and age samples per survey per year (nr samples taken) DAB

BTS

DISCARDS_BT

OTHER

length

age

length

DFS age

length

IBTS age

length

SNS Age

length

MARKET age

length

age

length

age

1966

0

0

0

0

384

0

0

0

0

0

0

0

0

0

1967

0

0

0

0

277

0

0

0

0

0

0

0

0

0

1968

0

0

0

0

256

0

0

0

0

0

0

0

0

0

1969

0

0

0

0

467

0

450

0

0

0

0

0

0

0

1970

0

0

1674

0

594

0

1076

0

0

0

0

0

0

0

1971

0

0

1307

0

421

0

487

0

0

0

0

0

0

0

1972

0

0

1725

0

281

0

997

0

0

0

0

0

0

0

1973

0

0

2398

0

416

0

833

0

0

0

0

0

0

0

1974

0

0

3189

0

546

0

1450

0

0

0

0

0

99

0

1975

0

0

3481

0

591

0

1520

0

0

0

0

0

216

0

1976

0

0

2040

0

537

0

1560

0

0

0

851

0

98

0

1977

0

0

3083

0

693

0

1768

0

0

0

348

0

319

0

1978

0

0

3512

713

559

0

3684

958

0

0

894

0

28

0

1979

0

0

3938

0

251

0

3071

0

0

0

0

0

34

0

1980

0

0

5173

165

2049

0

2856

0

0

0

1560

0

49

0

1981

0

0

4833

164

2510

0

3675

0

0

0

0

0

247

0

1982

0

0

6430

169

1777

0

3335

0

0

0

363

0

378

0

1983

549

0

7182

192

1424

0

3701

0

0

0

212

0

83

0

1984

0

0

5404

271

1838

0

3534

0

0

0

0

0

0

0

1985

1683

392

4704

105

2231

0

3817

0

0

0

0

0

13

0

1986

1774

212

3715

170

2935

0

4025

0

0

0

0

0

0

0

1987

1407

111

2487

189

3431

0

3265

0

0

0

0

0

0

0

1988

2379

215

3939

288

1843

0

3389

0

0

0

0

0

0

0

1989

1223

249

3022

295

2086

0

3595

0

0

0

627

0

0

0

1990

1563

371

2281

294

2344

0

1307

0

0

0

918

0

0

0

1991

1463

325

1553

300

2943

0

1244

0

0

0

0

0

0

0

1992

1542

343

1614

283

2355

0

1218

0

0

0

0

0

15

0

1993

1652

361

1179

262

3237

0

1155

574

0

0

0

0

386

0

1994

1421

249

1002

0

2509

0

1602

0

0

0

0

0

376

0

1995

1306

257

1414

203

1683

0

1107

0

0

0

0

0

0

0

1996

2341

252

1382

184

765

0

931

0

0

0

0

0

769

0

1997

2190

249

1137

220

1362

0

600

0

0

0

0

0

1360

0

1998

2453

255

602

0

838

0

673

0

0

0

0

0

1308

0

1999

2717

0

534

0

740

0

564

0

0

0

1488

122

82

0

2000

2745

0

639

0

802

0

574

0

0

0

5643

406

2696

34

2001

2302

0

884

0

770

0

425

0

0

0

1815

0

2974

0

2002

3449

0

736

0

768

0

406

0

300

300

2285

221

3239

28

2003

3868

1234

670

149

912

0

1570

557

300

298

4131

349

2291

0

2004

5123

0

2086

0

1746

0

2626

0

538

275

3937

280

1519

0

2005

6372

1820

1744

14

1792

0

2082

0

581

297

4771

224

4681

330

2006

5250

1648

1344

558

1822

0

1832

0

576

296

5209

138

241

0

2007

6102

1836

1820

395

1628

0

1618

686

551

299

3613

217

8650

0

2008

5480

1606

2336

786

1809

0

2376

0

0

0

5268

298

8978

0

2009

5840

1618

3864

1034

2134

0

2588

0

1235

717

6327

1383

5264

645

2010

4432

1392

2636

866

1592

0

2608

0

1335

776

9687

2318

27744

998

2011

6086

1329

798

9112

579

12583

575

50 of 62

1640

2516

Report number C110/12

Flounder

BTS

DFS

IBTS

SNS

MARKET

DISBT

OTHER

length

age

length

age

length

age

length

age

length

age

length

age

length

1966

0

0

0

0

20

0

0

0

0

0

0

0

0

0

1967

0

0

0

0

2

0

0

0

0

0

0

0

0

0

1968

0

0

0

0

6

0

0

0

0

0

0

0

0

0

1969

0

0

0

0

46

0

32

0

0

0

0

0

0

0

1970

0

0

246

0

32

0

78

0

0

0

0

0

0

0

1971

0

0

258

0

23

0

42

0

0

0

0

0

0

0

1972

0

0

238

0

7

0

110

0

0

0

0

0

0

0

1973

0

0

324

0

74

0

65

0

0

0

0

0

0

0

1974

0

0

554

0

72

0

82

0

0

0

0

0

9

0

1975

0

0

631

0

80

0

77

0

0

0

0

0

6

0

1976

0

0

796

0

54

0

70

0

0

0

0

0

8

0

1977

0

0

656

0

34

0

115

0

0

0

0

0

11

0

1978

0

0

427

0

45

0

179

0

0

0

30

0

0

0

1979

0

0

807

0

18

0

190

0

0

0

0

0

12

0

1980

0

0

1367

0

126

0

225

0

0

0

360

0

14

0

1981

0

0

1206

0

183

0

196

0

0

0

0

0

4

0

1982

0

0

1164

0

92

0

271

0

0

0

0

0

24

0

1983

0

0

1200

0

187

0

248

0

0

0

0

0

12

0

1984

0

0

784

0

181

0

79

0

0

0

0

0

0

0

1985

111

0

537

0

176

0

245

0

0

0

0

0

1

0

1986

30

0

527

0

260

0

228

0

0

0

0

0

0

0

1987

25

0

273

0

332

0

99

0

0

0

0

0

0

0

1988

44

0

293

0

220

0

107

0

0

0

0

0

0

0

1989

54

0

275

0

188

0

105

0

912

911

0

0

129

0

1990

144

0

252

0

192

0

45

0

425

0

7

0

53

0

1991

111

0

260

0

206

0

40

0

0

0

0

0

166

0

1992

80

0

308

0

154

0

40

0

0

0

0

0

877

15

1993

83

0

213

0

159

0

36

0

0

0

0

0

646

19

1994

110

0

355

0

133

0

74

0

0

0

0

0

1011

20

1995

165

0

541

0

75

0

75

0

0

0

0

0

851

45

1996

186

0

371

0

18

0

65

0

0

0

0

0

2877

0

1997

182

0

258

0

62

0

78

0

0

0

0

0

2454

0

1998

134

0

212

0

49

0

29

0

0

0

0

0

1706

76

1999

67

0

272

0

22

0

13

0

0

0

0

0

744

0

2000

107

0

479

0

26

0

15

0

0

0

153

0

1416

49

2001

101

0

462

0

21

0

36

0

0

0

134

0

2173

42

2002

143

0

529

0

38

0

25

0

0

0

13

0

2481

125

2003

105

0

340

0

33

0

50

0

0

0

27

0

3601

0

2004

284

0

736

0

106

0

242

0

0

0

61

0

2237

0

2005

384

90

1038

9

114

0

62

0

0

0

49

0

5497

78

2006

172

2

1172

552

88

0

142

0

0

0

169

0

1760

36

2007

340

0

1271

481

98

0

150

78

0

0

30

0

4726

46

2008

422

12

1924

790

271

0

176

74

0

0

107

0

5570

18

2009

310

4

1680

734

234

0

152

0

1663

849

38

0

5868

342

2010

282

14

1778

748

129

0

178

0

1716

900

256

0

4241

174

2011

458

0

NA

0

96

0

204

0

1489

900

112

0

1718

62

Report number C110/12

age

51 of 62

Lemon sole

BTS

DFS

IBTS

SNS

MARKET

DISBT

OTHER

length

age

length

age

length

age

length

age

length

age

length

age

length

age

1966

0

0

0

0

8

0

0

0

0

0

0

0

0

0

1967

0

0

0

0

7

0

0

0

0

0

0

0

0

0

1968

0

0

0

0

13

0

0

0

0

0

0

0

0

0

1969

0

0

0

0

72

0

4

0

0

0

0

0

0

0

1970

0

0

3

0

32

0

3

0

0

0

0

0

0

0

1971

0

0

5

0

9

0

2

0

0

0

0

0

0

0

1972

0

0

11

0

7

0

8

0

0

0

0

0

0

0

1973

0

0

17

0

66

0

12

0

0

0

0

0

0

0

1974

0

0

9

0

18

0

31

0

0

0

0

0

0

0

1975

0

0

16

0

63

0

24

0

0

0

0

0

0

0

1976

0

0

12

0

59

0

30

0

0

0

20

0

0

0

1977

0

0

21

0

32

0

37

0

0

0

20

0

0

0

1978

0

0

6

0

52

0

60

0

0

0

6

0

0

0

1979

0

0

10

0

54

0

65

0

0

0

0

0

0

0

1980

0

0

33

0

158

0

44

0

0

0

0

0

0

0

1981

0

0

35

0

346

0

89

0

0

0

0

0

0

0

1982

0

0

19

0

174

0

89

0

0

0

0

0

0

0

1983

272

0

5

0

124

0

69

0

0

0

0

0

0

0

1984

0

0

10

0

145

0

47

0

0

0

0

0

0

0

1985

149

0

8

0

135

0

62

0

0

0

0

0

0

0

1986

90

0

11

0

376

0

51

0

0

0

0

0

0

0

1987

102

0

14

0

397

0

41

0

0

0

0

0

0

0

1988

94

0

12

0

81

0

42

0

0

0

0

0

0

0

1989

86

0

23

0

142

0

54

0

0

0

1

0

0

0

1990

77

0

16

0

220

0

33

0

0

0

0

0

0

0

1991

77

0

1

0

559

0

8

0

0

0

0

0

0

0

1992

30

0

3

0

456

0

7

0

0

0

0

0

0

0

1993

19

0

13

0

415

0

15

0

0

0

0

0

0

0

1994

98

0

9

0

358

0

80

0

0

0

0

0

1

0

1995

87

0

12

0

252

0

59

0

0

0

0

0

0

0

1996

489

0

15

0

85

0

33

0

0

0

0

0

23

0

1997

415

0

7

0

141

0

42

0

0

0

0

0

49

0

1998

568

0

7

0

103

0

26

0

0

0

0

0

69

0

1999

649

0

10

0

90

0

18

0

0

0

32

0

16

0

2000

745

0

54

0

118

0

33

0

0

0

267

0

60

0

2001

780

0

37

0

61

0

14

0

0

0

44

0

34

0

2002

955

0

26

0

104

0

15

0

136

133

22

0

23

0

2003

1545

0

12

0

123

0

22

0

437

437

222

0

31

0

2004

2012

0

13

0

252

0

94

0

417

415

119

0

18

0

2005

1974

852

7

0

186

0

34

0

394

387

141

0

19

0

2006

1908

764

66

0

178

0

28

0

211

205

83

0

21

0

2007

2408

898

1

0

202

42

54

0

220

215

93

0

218

0

2008

2404

946

12

0

534

0

18

0

216

210

219

0

150

0

2009

2310

886

118

0

268

0

34

0

461

0

127

0

160

0

2010

2122

890

98

0

186

0

60

0

396

0

364

0

384

0

2011

2762

0

0

0

174

0

64

0

729

153

716

0

555

0

52 of 62

Report number C110/12

Witch Flounder

BTS length

DFS age

length

IBTS age

length

SNS age

length

length 0

DISBT age

length 0

OTHER age

length

1969

0

0

2

1970

0

0

47

0

0

0

0

1972

0

0

1

0

0

0

0

1973

0

0

10

0

0

0

0

1974

0

0

3

0

0

0

0

1975

0

0

33

0

0

0

0

1976

0

0

44

5

0

0

0

1977

0

1

5

0

0

0

0

1978

0

0

7

0

0

0

0

1979

0

2

3

0

0

0

0

1980

0

0

16

0

0

0

0

1981

0

0

52

0

0

0

0

1982

0

0

17

0

0

0

0

1983

124

0

75

0

0

0

0

1984

0

0

7

0

0

0

0

1985

44

0

33

0

0

0

0

1986

22

0

69

1

0

0

0

1987

23

0

57

0

0

0

0

1988

1

0

31

0

0

0

0

1989

0

0

40

0

0

0

0

1991

0

0

53

0

0

0

0

1992

0

0

44

0

0

0

0

1993

0

0

54

0

0

0

0

1994

1

2

4

0

0

0

0

1995

1

0

12

0

0

0

0

1996

38

2

3

0

0

0

0

1997

69

0

5

0

0

0

0

1998

120

0

6

2

0

0

2

1999

148

0

9

0

0

8

8

2000

226

0

2

0

0

17

6

2001

332

0

1

0

0

18

6

2002

158

0

3

0

0

0

6

2003

915

0

8

0

0

0

9

2004

598

0

6

0

0

1

2

2005

672

0

30

0

0

0

1

2006

660

0

8

0

0

1

6

2007

240

0

2

0

0

0

20

2008

216

0

16

0

0

0

58

2009

238

0

6

0

0

1

3

2010

240

0

2

0

0

3

30

2011

382

0

4

0

0

16

20

Report number C110/12

0

MARKET age

age

0

53 of 62

Turbot

BTS

DFS

IBTS

SNS

MARKET

DISBT

OTHER

length

age

length

age

length

age

length

age

length

age

length

age

length

age

1966

0

0

0

0

1

0

0

0

0

0

0

0

0

0

1967

0

0

0

0

1

0

0

0

0

0

0

0

0

0

1969

0

0

0

0

1

0

13

0

0

0

0

0

0

0

1970

0

0

20

0

5

0

24

0

0

0

0

0

0

0

1971

0

0

17

0

0

0

13

0

0

0

0

0

0

0

1972

0

0

3

0

1

0

17

0

0

0

0

0

0

0

1973

0

0

11

0

0

0

10

0

0

0

0

0

0

0

1974

0

0

35

0

2

0

39

0

0

0

0

0

11

0

1975

0

0

9

0

5

0

40

0

0

0

0

0

6

0

1976

0

0

17

0

3

0

35

0

0

0

201

0

33

0

1977

0

0

35

0

6

0

97

0

0

0

31

0

31

0

1978

0

0

26

0

1

0

77

0

0

0

112

0

15

0

1979

0

0

14

0

2

0

42

0

0

0

0

0

4

0

1980

0

0

72

0

39

0

27

0

0

0

322

0

0

0

1981

0

0

71

0

32

0

43

0

316

315

0

0

52

0

1982

0

0

161

0

20

0

35

0

1181

1181

142

0

58

0

1983

11

0

155

0

44

0

78

0

1535

1535

10

0

12

0

1984

0

0

110

0

22

0

70

0

1509

1509

0

0

0

0

1985

70

0

60

0

51

0

51

0

1499

1499

0

0

3

0

1986

100

0

27

0

42

0

20

0

1240

1240

0

0

0

0

1987

93

0

37

0

28

0

14

0

423

423

0

0

0

0

1988

106

0

26

0

35

0

44

0

398

397

0

0

0

0

1989

87

0

51

0

49

0

48

0

477

477

41

0

0

0

1990

212

0

27

0

75

0

54

0

599

599

169

0

0

0

1991

214

0

36

0

51

0

24

0

0

0

0

0

0

0

1992

178

0

48

0

35

0

30

0

0

0

0

0

0

0

1993

225

0

63

0

65

0

41

0

0

0

0

0

17

0

1994

230

0

19

0

19

0

39

0

0

0

0

0

8

0

1995

172

0

39

0

19

0

42

0

0

0

0

0

0

0

1996

182

0

37

0

1

0

21

0

0

0

0

0

30

0

1997

183

0

18

0

8

0

14

0

0

0

0

0

24

0

1998

114

0

9

0

4

0

18

0

542

542

0

0

28

0

1999

126

0

24

0

2

0

42

0

0

0

12

0

0

0

2000

172

0

6

0

0

0

30

0

0

0

155

0

97

0

2001

245

112

31

0

1

0

13

0

0

0

37

0

47

0

2002

149

30

16

0

3

0

27

0

2378

2346

0

0

64

0

2003

343

212

46

19

3

0

10

0

2442

2421

70

0

58

6

2004

663

388

78

0

8

0

200

76

1020

1004

22

0

4

0

2005

564

288

78

16

4

0

122

52

1150

1138

253

0

231

0

2006

516

240

56

10

6

0

160

76

1178

1160

158

0

8

0

2007

642

342

35

16

24

12

92

56

1147

1139

232

0

1115

0

2008

592

324

114

38

32

0

136

92

949

927

62

0

954

0

2009

470

242

58

22

22

0

54

36

2030

875

1752

0

226

2

2010

422

228

94

40

4

0

90

0

1967

878

2309

6

952

0

2011

534

0

NA

0

4

0

96

54

2535

888

2042

0

1119

0

54 of 62

Report number C110/12

Brill

BTS

DFS

IBTS

SNS

MARKET

DISBT

OTHER

length

age

length

age

length

age

length

age

length

age

length

age

length

1970

0

0

18

0

0

0

26

0

0

0

0

0

0

0

1971

0

0

17

0

2

0

7

0

0

0

0

0

0

0

1972

0

0

11

0

0

0

13

0

0

0

0

0

0

0

1973

0

0

19

0

0

0

10

0

0

0

0

0

0

0

1974

0

0

18

0

7

0

18

0

0

0

0

0

7

0

1975

0

0

20

0

2

0

21

0

0

0

0

0

0

0

1976

0

0

31

0

2

0

17

0

0

0

32

0

5

0

1977

0

0

13

0

6

0

40

0

0

0

6

0

6

0

1978

0

0

16

0

0

0

50

0

0

0

38

0

0

0

1979

0

0

33

0

3

0

21

0

0

0

0

0

15

0

1980

0

0

120

0

10

0

29

0

0

0

159

0

0

0

1981

0

0

89

0

14

0

33

0

241

241

0

0

18

0

1982

0

0

119

0

10

0

24

0

559

559

40

0

22

0

1983

2

0

99

0

6

0

26

0

1311

1311

8

0

15

0

1984

0

0

45

0

9

0

34

0

1540

1540

0

0

0

0

1985

13

0

13

0

10

0

17

0

1185

1184

0

0

2

0

1986

17

0

9

0

13

0

9

0

1371

1371

0

0

0

0

1987

54

0

21

0

11

0

8

0

380

380

0

0

0

0

1988

41

0

12

0

4

0

12

0

318

318

0

0

0

0

1989

31

0

54

0

14

0

26

0

358

358

1

0

0

0

1990

96

0

24

0

27

0

15

0

442

441

78

0

0

0

1991

74

0

29

0

20

0

13

0

0

0

0

0

0

0

1992

133

0

58

0

29

0

28

0

0

0

0

0

0

0

1993

151

0

18

0

24

0

14

0

0

0

0

0

40

0

1994

102

0

36

0

2

0

14

0

0

0

0

0

15

0

1995

77

0

14

0

4

0

4

0

0

0

0

0

0

0

1996

42

0

13

0

2

0

2

0

0

0

0

0

21

0

1997

89

0

13

0

3

0

14

0

0

0

0

0

23

0

1998

54

0

14

0

0

0

1

0

458

458

0

0

42

0

1999

38

0

26

0

1

0

11

0

0

0

0

0

2

0

2000

88

0

32

0

1

0

15

0

0

0

94

0

162

0

2001

64

38

16

0

1

0

16

0

0

0

51

0

123

0

2002

60

4

22

0

2

0

13

0

2044

2026

3

0

91

0

2003

211

108

52

17

0

0

45

0

2042

2023

14

0

59

17

2004

217

109

58

0

10

0

46

12

746

737

15

0

44

10

2005

160

78

170

14

2

0

28

10

658

644

71

0

380

0

2006

190

90

50

12

0

0

66

32

731

713

85

0

14

0

2007

258

140

28

9

0

0

32

20

845

830

168

0

501

0

2008

122

74

208

102

0

0

94

56

997

978

60

0

537

4

2009

242

134

100

44

4

0

108

30

1719

752

524

0

194

0

2010

342

182

148

66

10

0

56

0

1712

781

1439

0

346

0

2011

444

0

0

0

0

0

98

60

2167

736

1492

0

770

0

Report number C110/12

age

55 of 62

Horse Mackerel

BTS

DFS

IBTS

SNS

MARKET

DISBT

OTHER

length

age

length

age

length

age

length

age

length

age

length

age

length

age

1969

0

0

0

0

0

0

13

0

0

0

0

0

0

0

1970

0

0

63

0

0

0

17

0

0

0

0

0

0

0

1971

0

0

78

0

0

0

4

0

0

0

0

0

0

0

1972

0

0

104

0

2

0

10

0

0

0

0

0

0

0

1973

0

0

80

0

7

0

10

0

0

0

0

0

0

0

1974

0

0

55

0

4

0

10

0

0

0

0

0

1

0

1975

0

0

160

0

7

0

48

0

0

0

0

0

0

0

1976

0

0

116

0

16

0

59

0

0

0

0

0

0

0

1977

0

0

112

0

12

0

38

0

0

0

0

0

27

0

1978

0

0

99

0

7

0

39

0

0

0

9

0

0

0

1979

0

0

102

0

3

0

59

0

0

0

0

0

10

0

1980

0

0

268

0

490

0

53

0

25

25

6

0

14

0

1981

0

0

196

0

524

0

84

0

0

0

0

0

11

0

1982

0

0

264

0

488

0

58

0

500

500

0

0

0

0

1983

26

0

66

0

245

0

42

0

700

700

11

0

0

0

1984

0

0

144

0

496

0

31

0

950

950

0

0

0

0

1985

20

0

103

0

786

0

23

0

1400

1400

0

0

0

0

1986

13

0

105

0

695

0

43

0

1050

1050

0

0

0

0

1987

27

0

95

0

891

0

21

0

1300

1300

0

0

0

0

1988

19

0

48

0

398

0

8

0

1498

1498

0

0

0

0

1989

32

0

68

0

357

0

24

0

1525

1525

0

0

0

0

1990

33

0

40

0

523

0

42

0

1775

1775

57

0

0

0

1991

25

0

96

0

1638

526

36

0

2049

2049

0

0

0

0

1992

69

0

96

0

656

45

66

0

1525

1525

0

0

0

0

1993

19

0

28

0

930

231

31

0

2775

2775

0

0

556

0

1994

63

0

17

0

805

201

43

0

2775

2775

0

0

1133

0

1995

55

0

22

0

290

0

96

0

1875

1875

0

0

314

0

1996

17

0

114

0

158

0

32

0

1900

1900

0

0

741

0

1997

85

0

42

0

285

0

48

0

2449

2449

0

0

0

0

1998

31

0

21

0

111

0

35

0

2825

2825

0

0

2

0

1999

63

0

35

0

4

0

10

0

3025

3025

13

0

5

0

2000

97

0

75

0

5

0

24

0

1950

1950

76

0

85

0

2001

84

0

70

0

19

0

55

0

3350

3350

1

0

136

0

2002

134

0

26

0

18

0

42

0

3125

3125

42

0

1641

0

2003

137

0

88

0

89

0

0

0

2225

2225

32

0

1195

0

2004

121

0

66

0

214

0

78

0

3046

2500

48

0

1111

0

2005

132

0

131

0

80

0

118

0

3646

2664

16

0

2706

0

2006

136

0

202

0

256

0

54

0

3089

2268

45

0

1981

0

2007

24

0

13

0

258

0

20

0

2531

1822

89

0

2957

0

2008

40

0

36

0

84

0

58

0

3545

2559

3

0

4415

0

2009

68

0

54

0

48

0

56

0

3519

2493

31

0

5377

0

2010

72

0

114

0

102

0

94

0

3387

2497

87

0

8642

0

2011

14

0

0

0

12

0

50

0

3903

2798

31

0

3932

0

56 of 62

Report number C110/12

Appendix C. Parameters of length-weight relationships and growth Table C-1 Length weight parameters Species Dab

European Flounder

Witch Flounder

Lemon Sole

Brill

Turbot

Horse Mackerel

a

b

Source

female

0.0103

2.98

DATRAS BTS

male

0.0071

3.10

all

0.0095

3.01

female

0.016

2.89

male

0.024

2.75

all

0.012

2.98

female

0.0024

3.28

male

0.0031

3.19

all

0.002

3.33

female

0.0098

3.02

male

0.0077

3.07

all

0.0077

3.08

female

0.016

2.97

male

0.013

3.01

all

0.014

2.99

female

0.013

3.11

male

0.022

2.95

all

0.012

3.13

female

0.0032

3.29

male

0.0044

3.19

all

0.0039

3.23

DATRAS BTS

DATRAS BTS

DATRAS BTS

DATRAS BTS

DATRAS BTS

FRISBE IBTS Q3

Table C-2 Estimated Von Bertalanffy parameters Species Dab European Flounder Lemon Sole Brill Turbot Horse Mackerel

Report number C110/12

Linf

K

t0

Source

female

25.9

0.50

-0.46

BTS (FRISBE)

male

21.5

0.41

-1.31

female

44.9

0.27

-2.58

male

35.7

0.73

-0.16

female

29.8

0.39

-0.85

male

26.1

0.37

-1.35

female

56.6

0.32

-1.19

male

38.8

0.59

-0.94

female

54.7

0.39

-0.39

male

36.7

0.56

-0.58

female

34.3

0.16

-4.27

male

34.5

0.15

-4.43

BTS (FRISBE) BTS (FRISBE) BTS (FRISBE) BTS (FRISBE) IBTS (FRISBE)

57 of 62

Appendix D. Commercial data on dab Table D-1 Dab market sampling per category. Source: Frisbe 2002

2003

2004

2005

2006

2007

2009

2010

2011

0

225

275

465

438

505

475

898

1181

1282

2

0

0

0

0

0

0

0

0

32

Table D-2 Total Dutch landings in tonnes per market category. Source: Visstat 1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011*

0

1426

2261

1584

1811

0

0

0

0

0

0

0

0

0

1

1

73

2

2

4

9

11

6

5

11

3

4

11

14

2

2

3802

4595

3484

3262

4010

4424

4341

4829

4455

5561

4906

4831

4281

1860

*2011 market categories data are not yet complete

Table D-3 Effort and landings estimation for Dutch beam trawlers (> 221kW). Corrected data: days at sea by 1471 kW vessel (equation 1). Uncorrected: days at sea. Landings in tonnes. Source: Visstat year

corrected effort

uncorrected effort

Landings (tonnes)

1998

33841

30273

5172

1999

33002

29502

6086

2000

32661

29258

4497

2001

30949

27800

3860

2002

28654

25705

3032

2003

26572

23949

3068

2004

24882

22754

3163

2005

25081

22973

3777

2006

22488

20974

3652

2007

21725

20398

4960

2008

15958

15654

3703

2009

16625

16375

2856

2010

16635

16164

2994

2011

15956

15429

2914

Table D-4 Dab landings (kg) per rectangle and year (TBB >221 kW) 1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

31F1

73596

55025

43990

33480

10595

9030

11395

10295

7410

14060

9971

9102

18495

8470

31F2

265439

271057

303034

366037

354015

316373

343541

302734

293640

453318

619098

482414

333549

255857

31F3

11563

2556

2080

6260

2975

5245

8813

4413

4180

17500

6820

2340

1638

1400

31F5

0

0

40

0

0

0

0

0

0

0

0

0

0

0

31F6

400

0

0

0

0

0

1200

0

0

0

0

0

0

0

32F0

0

0

0

0

0

0

0

900

0

0

0

0

0

0

32F1

4440

6490

5790

3735

5540

19650

11510

5090

1830

6710

4145

4662

1855

12601

32F2

282096

346635

372025

491025

404480

363818

345519

316004

217676

493304

446215

388649

262731

263240

32F3

228164

171593

233876

195704

217779

111933

125775

98907

89013

278309

327864

114417

93624

111400

32F4

15993

1850

14090

6810

5590

2340

2278

1275

770

1950

1325

0

0

165

32F5

0

0

0

0

0

40

0

0

0

0

0

0

0

0

33F1

200

260

0

150

1350

980

0

1200

150

0

0

25

0

355

33F2

110892

76311

135835

55194

69693

82615

85548

92440

65140

87207

80807

107205

100591

87425

33F3

396286

341133

402144

255892

230809

198811

239373

230442

203371

405847

326990

166922

203869

263031

33F4

23813

21992

13063

31098

22620

21469

23345

36097

19193

59966

48185

27954

15528

13220

33F5

300

0

0

0

870

0

0

95

0

0

0

0

0

0

34F0

0

0

40

108

0

650

0

0

0

0

0

0

0

0

34F1

980

620

2430

1019

1500

3862

1688

330

160

0

0

0

88

415

34F2

111940

150911

168197

191133

153922

185403

108377

123089

132441

183256

98530

185684

237845

142152

34F3

201933

199914

146381

111809

128137

140915

151552

225675

218625

226651

132191

109010

196878

151362

34F4

71233

60795

72987

54917

55059

78771

90022

115838

134901

140205

85035

55253

55790

63085

34F5

0

200

100

520

2024

0

625

2170

50

480

0

50

0

411

34F6

200

0

100

2500

100

0

200

0

0

0

0

0

0

0

34F7

0

0

0

0

0

0

0

0

0

0

0

0

0

39

58 of 62

Report number C110/12

35F0

0

400

50

150

280

400

520

0

0

0

200

0

140

0

35F1

8471

4629

4991

25566

9168

8430

7332

8883

5449

7562

4020

3833

5447

6234

35F2

129245

133157

75349

114339

108074

99654

100604

83137

87345

118987

70888

87834

85307

46269

35F3

200092

223307

143920

157058

103231

111691

152901

211911

168586

262296

101996

93701

89388

67308

35F4

104088

103329

66114

58975

45974

62817

64569

102682

108830

83151

53815

32189

28726

40198

35F5

3578

2050

2100

1195

1488

1830

883

1267

2520

775

1142

553

340

242

35F6

0

0

0

250

1090

260

259

0

250

0

2545

0

0

0

36F0

9675

8045

17199

17750

18654

8265

10779

14434

15625

2650

5113

5042

13399

10476

36F1

39825

54688

34966

62019

42458

31019

30227

28596

42120

21852

13381

19904

21740

35142

36F2

70708

125574

72090

73935

33959

28819

39102

54649

54848

62712

18462

25067

23323

26218

36F3

80032

106011

43023

49332

26253

34878

44074

93313

64093

70133

39099

53824

63309

44712

36F4

103672

205247

60024

98118

68318

99702

157285

216273

184578

174848

140084

90634

73012

55089

36F5

45558

79728

34772

60811

42974

49038

57985

103463

79569

102281

75773

33878

37939

20459

36F6

12505

14529

13686

12594

5130

1950

7435

9849

5820

12051

5499

8179

6656

3602

36F7

4010

6275

3800

3360

790

1110

4150

4707

2879

3132

6896

3619

14982

280

36F8

40

0

0

0

0

200

0

0

0

0

0

0

0

0

37E9

0

0

250

0

0

0

0

0

0

0

0

0

0

0

37F0

79222

99740

78928

62205

30985

19201

16896

23756

21382

12744

5306

10028

14899

18030

37F1

155504

209709

157248

99310

61535

51354

51514

58008

61938

50406

15395

23309

30699

41025

37F2

192771

346595

166552

46898

48713

51218

47535

44750

18949

30602

4256

8460

11218

19285

37F3

82475

112285

34375

26737

14195

13070

11925

10781

10018

8999

3395

4975

4332

22529

37F4

91618

97170

41521

35374

33430

26181

34742

36453

24788

34055

9996

16383

37928

44217

37F5

95656

109511

51128

70514

32949

44848

74777

94629

94748

131100

61543

64589

104525

126436

37F6

343629

293909

305882

252931

106136

115793

202453

339159

400799

445610

243438

216459

220650

285527

37F7

302072

284359

175201

214145

80994

78907

151340

223589

220319

400674

330958

188099

196304

239591

37F8

120

0

0

0

250

0

0

0

0

0

960

0

760

80

38E8

0

0

0

980

0

0

0

0

0

0

0

0

0

0

38E9

190

175

240

930

1960

40

810

1365

0

120

0

0

0

0

38F0

14169

16138

17313

9645

7630

5720

1295

4220

750

2154

675

40

261

1798

38F1

47670

68520

24200

6027

3020

9280

7605

1375

750

600

0

0

200

133

38F2

335190

542889

213999

30600

30995

46915

43875

15720

9430

11746

2757

1046

1320

3581

38F3

177733

261876

41852

14709

12935

18425

1952

3128

2455

2475

1960

180

822

3517

38F4

38371

61997

21023

9835

14220

14588

4110

7330

2435

5856

2320

1938

7267

15259

38F5

30087

46293

34847

20691

20651

25065

20879

23703

31113

27531

18655

15362

24820

24425

38F6

110958

175141

150377

71322

74137

64886

49465

102301

126349

162368

95112

79716

149554

117538

38F7

4025

22845

5965

11880

5200

2260

1585

3900

26529

16205

9440

2909

410

340

38F8

0

100

500

550

810

0

0

0

0

200

0

0

0

0

39F0

2265

1380

140

0

200

0

0

0

80

0

0

0

0

0

39F1

11356

6100

790

1640

680

3980

2760

700

100

80

0

0

0

467

39F2

78845

51332

26155

7615

10785

26435

9545

14095

10700

300

0

1226

1730

4725

39F3

94945

102337

92190

37784

20063

32181

13298

13360

28225

4555

6075

2987

10163

6544

39F4

57879

108388

56232

33711

28856

30255

6490

18295

7675

420

6221

4022

23857

9518

39F5

14357

20665

18238

19286

35420

25954

12059

24306

10381

6126

3507

5319

7303

6527

39F6

58927

68848

78228

52609

67424

84005

24709

55425

65483

52659

50116

26576

68846

66293

39F7

4065

4835

19185

32801

36641

22395

17708

23530

37102

41610

11860

3949

7783

6200

39F8

0

0

0

0

100

0

0

0

0

0

0

0

0

0

40E9

150

0

0

0

0

0

0

0

0

0

0

0

0

0

40F0

80

0

0

0

0

0

0

40

0

0

0

0

0

0

40F1

1290

300

0

0

0

0

0

0

0

0

0

0

0

180

40F2

13200

3770

1405

900

1030

2270

1320

1790

678

40

0

80

0

989

40F3

18806

15766

27037

8645

8707

4760

4920

3350

12580

160

800

4853

1005

8958

40F4

51180

91624

86746

42175

15031

60109

35990

28765

34049

1710

39846

4577

14136

37630

40F5

5195

18716

18656

9090

14512

22651

13550

6790

5960

5756

12528

949

3770

9087

40F6

11195

21775

26922

26047

16122

36415

9531

19355

31077

27072

7085

14031

21671

28722

40F7

1750

5520

15100

26110

7220

8940

2040

24654

24620

132580

6200

9202

23983

19274

41F1

240

600

0

0

0

0

0

0

0

0

0

0

0

0

41F2

3315

20

0

0

0

0

0

0

0

0

0

0

0

0

41F3

378

585

0

0

0

800

0

25

0

340

0

0

0

0

41F4

1120

7581

1370

2160

1760

1875

1380

2455

2880

1445

735

0

1259

320

41F5

3448

6745

2295

5768

1070

2760

5560

4350

9663

3851

2620

4759

2730

1974

41F6

5555

4370

6850

12819

7220

6545

16770

9155

33210

10757

100

11536

4506

2395

41F7

320

480

640

7085

0

1300

2790

2460

5610

7450

80

776

2630

560

42F2

0

80

140

0

70

25

0

0

40

70

0

0

0

0

42F3

1014

753

226

35

130

1360

1900

0

950

300

500

0

0

0

42F4

955

2557

2030

2780

365

650

0

580

3596

835

1235

0

0

0

42F5

2193

2315

225

780

550

760

3615

90

1055

940

0

636

80

160

42F6

3520

3590

735

1100

1755

4710

12260

2800

17097

5480

680

9760

3241

3001

42F7

5350

80

0

120

0

280

100

1860

6800

1825

3117

940

974

1609

42F8

0

0

0

0

0

0

1000

0

0

0

0

0

170

0

43E8

0

0

0

0

0

0

320

0

0

0

0

0

0

0

43F2

130

900

660

0

60

30

0

0

0

0

0

0

0

0

43F3

2236

4016

1509

360

125

1890

40

0

230

130

0

0

0

0

43F4

540

1892

190

0

345

240

375

910

1060

2235

180

65

0

0

43F5

215

2230

825

5

0

300

1095

405

45

1080

2110

5

0

0

43F6

225

130

1640

40

80

1580

540

3700

7080

1050

2621

1254

48

80

43F7

2426

370

360

365

0

11715

8953

17864

25253

13420

10523

3057

2199

4636

Report number C110/12

59 of 62

44F2

270

400

455

40

20

140

0

30

170

0

0

0

0

0

44F3

780

730

310

0

0

1000

5

90

1500

0

0

0

0

0

44F4

20

335

100

0

60

0

315

120

560

290

1545

460

0

0

44F5

0

280

40

0

0

0

0

20

250

470

150

10

0

0

44F6

0

40

0

0

0

0

0

0

0

0

0

0

0

0

45F2

0

0

0

0

0

40

0

40

0

0

0

0

0

0

45F3

40

140

40

0

0

0

110

90

225

0

25

0

0

0

45F4

0

0

0

25

0

0

0

0

0

86

0

0

0

0

45F5

0

80

0

0

0

0

0

0

2625

0

0

0

0

0

46F5

0

120

0

0

0

0

0

0

0

0

0

0

0

0

46F6

0

0

0

285

0

0

0

0

0

0

0

0

0

0

49F4

0

0

0

0

0

0

0

760

0

0

0

0

0

0

49F5

0

0

0

0

0

0

0

400

0

0

0

0

0

0

52F3

0

0

0

0

0

0

0

365

0

0

0

0

0

0

Table D-5 DAB LPUE (kg landings/days at sea by 1471 kW vessel, see equation 1). First LPUE calculated by rectangle, subsequently averaged over the rectangles (for Dutch beam trawlers > 221kW). Source: VISSTAT Year

1998 173

LPUE

1999 201

2000 154

2001 143

2002 133

2003 141

2004 145

2005 177

2006 185

2007 232

2008 202

2009 160

2010 194

2011 157

Table D-6 NL Dab LPUE (kg/day at sea by 1471kW vessel) per age and year. No market sampling was done in 2008. age

year

2002

2003

2004

2005

2006

2007

2009

2010

2011

2

0.6

13.9

15.4

1.8

17

12.1

4.2

0.5

9.7

3

16

28.9

31.5

31.1

69.5

37.3

25.6

15.8

21.2

4

33.2

32

34.1

43.5

36.2

61.5

25.3

39

34

5

36.8

33

29.6

33.7

36.2

42.9

32.4

44.1

39.4

6

27.9

18

19.3

32.9

5.9

42

43.5

38.4

23.9

7

9.5

11.9

9.0

24

11.8

4.7

8.4

35.2

14.9

8

6.5

1.6

5.8

4.4

6.7

18.7

16.2

8.0

10.9

9

2.4

0.5

0

5.3

0

2.8

2.3

8.5

0.4

10

0

0.5

0

0

1.5

0

2.0

1.3

2.1

11

0.6

0

0

0

0

10.3

0

2.9

0

12

0

0.5

0

0

0

0

0

0

0.2

13

0

0

0

0

0

0

0.3

0

0

15

0

0

0

0

0

0

0

0

0.2

19

0

0

0

0

0

0

0

0.3

0

2004 183 217 106 0 0 0 0 194 194 137 214 0 0 128 109 159 0 0 109 93 98

2005 160 187 206 0 0 0 89 134 168 118 178 0 174 123 106 164 36 0 67 95 126

Table D-7 Dab LPUE by rectangle (kg per day). 31F1 31F2 31F3 31F4 31F5 31F6 32F0 32F1 32F2 32F3 32F4 32F5 33F1 33F2 33F3 33F4 33F5 34F0 34F1 34F2 34F3

60 of 62

1998 152 156 271 0 0 213 0 160 155 212 151 0 143 141 182 189 0 0 103 99 134

1999 150 173 154 0 0 0 0 165 179 182 241 0 65 127 181 202 0 0 79 131 182

2000 176 179 114 0 22 0 0 136 176 223 667 0 0 132 150 137 0 34 96 131 107

2001 166 219 275 0 0 0 0 153 199 206 384 0 144 95 124 183 0 106 119 140 84

2002 126 217 111 0 0 0 0 83 178 212 411 0 112 120 100 149 298 0 100 105 70

2003 145 197 195 0 0 0 0 227 177 153 345 13 107 116 104 149 0 185 110 114 83

2006 146 182 159 0 0 0 0 119 137 134 80 0 78 102 126 158 0 0 154 100 149

2007 203 377 357 0 0 0 0 141 259 400 181 0 0 151 273 377 0 0 0 142 198

2008 291 567 342 0 0 0 0 162 348 426 384 0 0 166 256 389 0 0 0 100 144

2009 173 445 243 0 0 0 0 202 271 279 0 0 28 147 142 551 0 0 0 117 122

2010 245 314 621 0 0 0 0 103 201 292 0 0 0 155 178 361 0 0 19 159 173

2011 0 252 0 0 0 0 0 44 179 316 0 0 166 108 208 208 0 0 66 87 158

Report number C110/12

34F4 34F5 34F6 34F7 35F0 35F1 35F2 35F3 35F4 35F5 35F6 36F0 36F1 36F2 36F3 36F4 36F5 36F6 36F7 36F8 37E9 37F0 37F1 37F2 37F3 37F4 37F5 37F6 37F7 37F8 38E8 38E9 38F0 38F1 38F2 38F3 38F4 38F5 38F6 38F7 38F8 39F0 39F1 39F2 39F3 39F4 39F5 39F6 39F7 39F8 40E9 40F0 40F1 40F2 40F3 40F4 40F5 40F6 40F7 41F1 41F2 41F3 41F4 41F5 41F6 41F7 42F1 42F2 42F3 42F4 42F5 42F6 42F7 42F8 43E8 43F2

126 0 69 0 0 66 102 116 115 77 0 133 102 116 112 86 98 116 208 37 0 115 145 197 125 66 79 170 394 95 0 94 54 354 590 438 112 92 156 189 0 40 132 349 346 237 164 152 388 0 29 49 49 142 341 298 157 165 148 0 316 105 223 178 87 114 0 0 39 79 127 88 153 0 0 17

151 214 0 0 287 130 120 156 142 88 0 244 147 151 137 135 103 133 171 0 0 248 252 265 164 99 89 141 309 0 0 35 130 471 509 411 110 80 147 271 75 63 189 413 484 364 171 211 162 0 0 0 83 148 548 421 259 183 236 82 10 31 127 261 111 241 0 29 37 84 78 97 69 0 0 279

Report number C110/12

93 85 145 0 61 111 102 99 91 76 0 202 171 163 79 59 51 118 199 0 125 220 211 287 124 54 44 123 182 0 0 36 160 313 586 386 56 58 113 146 36 128 166 344 371 291 90 104 176 0 0 0 0 179 256 294 177 72 163 0 0 0 137 52 73 241 0 46 38 32 54 48 0 0 0 59

91 143 2783 0 165 141 102 88 73 53 59 184 156 110 65 55 57 119 115 0 0 194 143 91 73 56 67 123 294 0 93 45 90 150 237 176 52 63 88 194 81 0 160 201 249 198 99 100 166 0 0 0 0 83 219 274 187 108 346 0 0 0 174 203 100 252 0 0 10 87 207 73 58 0 0 0

73 52 87 0 61 87 78 74 61 84 163 142 102 73 46 52 49 69 59 0 0 109 88 92 51 56 50 79 130 313 0 106 91 86 329 181 81 70 110 141 85 175 87 268 227 303 226 142 193 124 0 0 0 265 263 289 513 143 190 0 0 0 149 105 89 0 0 15 7 36 42 99 0 0 0 46

81 0 0 0 59 64 81 90 81 104 57 121 90 69 61 67 72 93 140 53 0 120 88 78 46 58 66 125 179 0 0 35 112 121 174 190 68 87 136 173 0 0 224 200 178 178 183 232 221 0 0 0 0 163 211 275 346 237 323 0 0 90 120 128 165 606 0 9 100 14 140 180 0 0 0 0

104 48 122 0 96 73 82 104 102 71 216 146 97 85 84 111 100 123 186 0 0 118 90 109 69 89 105 153 201 0 0 58 57 95 172 129 141 102 141 233 0 0 115 137 177 199 196 186 237 0 0 0 0 114 114 188 435 137 188 0 0 0 141 239 156 57 0 0 190 0 215 173 40 748 172 0

141 227 0 0 0 77 101 163 151 159 0 231 127 133 153 156 166 156 276 0 0 162 121 130 96 100 127 234 307 0 0 76 135 163 131 145 113 138 196 219 0 0 73 183 178 277 296 234 270 0 0 9 0 157 183 314 311 231 402 0 0 24 39 261 241 167 0 0 0 24 32 92 61 0 0 0

157 62 0 0 0 68 93 156 159 144 49 227 165 146 152 162 164 174 275 0 0 133 126 117 131 115 133 274 386 0 0 0 38 71 142 118 118 151 206 661 0 11 69 204 276 170 246 210 386 0 0 0 0 173 273 301 214 183 320 0 0 0 74 186 171 179 0 40 43 39 73 201 219 0 0 0

181 116 0 0 0 77 143 189 137 161 0 154 157 144 149 134 167 197 233 0 0 152 170 118 93 89 155 297 559 0 0 68 50 93 126 164 66 141 259 562 246 0 16 98 413 190 194 297 530 0 0 0 0 29 0 219 499 277 632 0 0 107 69 173 235 209 0 0 250 43 240 125 92 0 0 0

146 0 0 0 179 64 112 138 128 104 493 173 112 95 132 139 182 355 570 0 0 142 124 44 53 51 119 279 350 1176 0 0 79 0 63 84 35 69 241 182 0 0 0 0 148 221 89 287 535 0 0 0 0 0 315 509 381 159 446 0 0 0 184 118 118 78 0 0 480 80 0 70 325 0 0 0

130 53 0 0 0 64 96 110 98 83 0 137 98 68 106 87 114 208 281 0 0 175 121 69 47 55 110 240 323 0 0 0 41 0 34 12 64 74 192 250 0 0 0 57 84 162 119 151 246 0 0 0 0 90 136 142 116 168 287 0 0 0 0 123 308 164 0 0 0 0 243 266 151 0 0 0

100 0 0 0 124 54 115 133 90 46 0 202 108 74 107 95 124 228 472 0 0 162 148 68 47 116 128 276 427 825 0 0 96 90 88 75 165 131 289 120 0 0 0 123 456 491 262 302 414 0 0 0 0 0 63 171 145 203 485 0 0 0 128 99 146 180 0 0 0 0 41 142 75 61 0 0

127 0 0 0 0 35 59 112 110 42 0 347 159 65 69 138 202 160 0 0 0 480 157 62 36 126 277 391 357 0 0 0 475 66 62 17 196 139 303 0 0 0 0 0 0 153 134 249 206 0 0 0 36 0 75 127 197 241 260 0 0 0 0 101 0 0 0 0 0 0 0 0 0 0 0 0

61 of 62

43F3 43F4 43F5 43F6 43F7 44F2 44F3 44F4 44F5 44F6 45F2 45F3 45F4 45F5 46F5 46F6 49F4 49F5 52F3

62 of 62

26 25 16 49 51 20 37 8 0 0 0 17 0 0 0 0 0 0 0

84 93 63 19 24 91 48 9 7 4 0 18 0 18 16 0 0 0 0

30 20 40 40 24 27 20 2 1 0 0 4 0 0 0 0 0 0 0

54 0 1 46 48 17 0 0 0 0 0 0 4 0 0 132 0 0 0

10 13 0 22 0 8 0 4 0 0 0 0 0 0 0 0 0 0 0

79 73 293 217 187 7 68 0 0 0 39 0 0 0 0 0 0 0 0

30 52 63 59 162 0 0 5 0 0 0 15 0 0 0 0 0 0 0

0 62 26 242 162 2 11 5 4 0 10 13 0 0 0 0 209 220 84

48 41 7 262 175 20 61 27 16 0 0 11 0 0 0 0 0 0 0

39 75 57 62 120 0 0 6 23 0 0 0 15 0 0 0 0 0 0

0 0 113 464 189 0 0 43 28 0 0 11 0 0 0 0 0 0 0

0 31 5 316 102 0 0 24 3 0 0 0 0 0 0 0 0 0 0

0 0 0 44 91 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Report number C110/12