Shrimp-BarentsSea.pdf (185.5Kb)

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Management of shrimp fishery(Pandalus borealis) in the Barents Sea and Spitsbergen

area

by

Michaela Aschan ¹ Sergey Bakanev ² Boris Berenboim² Knut Sunnanå ¹

1 IMR, Tromsø, Norway

2 PINRO, Murmansk, Russia

10th Norwegian- Russian Symposium,

Bergen, Norway 27-29 august 2003

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The aim

The aim is to inform the science community and

fishermen about the status of research on and

regulation of the shrimp stock in the Barents Sea

and Spitsbergen area.

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Stock characteristics



Found at depths 100-600 m



Change from male to female at age 4-7



Opportunistic omnivore



Prey for demersal fish



One population in the Barents Sea and

Spitsbergen area

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0 50 100 150 200 250 300 350 400 450 500

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Years

Shrimp ('000 t)

0 50 100 150 200 250 300 350

CPUE (kg/h)

Index Landings N-CPUE R-CPUE

Biomass indices from the Norwegian surveys, total landings and Norwegian and Russian CPUE

for ICES areas I, IIa and IIb.

Catch Per Unit Effort

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Biomass indices

0 200 400 600 800 1000 1200 1400

1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Years

Russian Biomass Index ('000 t)

0 50 100 150 200 250 300 350 400 450 500

Norway Biomass Index ('000 t)

R-index N-index

Shrimp biomass indices from Norwegian (N-index) and Russian surveys (R-index) in the Barents Sea and

Spitsbergen area in 1982-2002.

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Cod-Shrimp

0 500 1000 1500 2000 2500 3000

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Ye ars

Cod ('000t)

0 50 100 150 200 250 300 350 400

Shrimp ('000 t)

Shrimp index Cod (+3)

Shrimp consumed

Biomass indices from the Norwegian surveys, biomass estimate for cod (age 3 years and older) and the shrimp consumed

by the cod in the Barents Sea.

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Recruitment index

0 20 40 60 80 100 120 140

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

year

recruitment index

1+ in juvenile bag 3+ in cod end

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The great plasticity in growth of shrimp and age at sex change, as well as lack of biological data and length distributions from the catches make it difficult to apply traditional analytical fishery assessment methods to the

data.

A spreadsheet performance report has been used to assess the available information (Caddy 1999, Koeller et al. 2001).

Evaluation of the Stock

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Models

I. Production models

Shaefer and Fox stock models; stock production model including predation (Stefánsson et al. 1994, Berenboim and Korzhev 1997).

II. Catch at age analysis (cohort models)

1) single species virtual population analysis;

2) multi species virtual population analysis.

III. Length at age analysis

Jones analysis (for sustainable stock); analysis including stochastic growth (Sullivan et al. 1991);

Fleksibest (Froeysa et al. 2002); Bormicon – multispecies analysis (Stefánsson and Pálsson 1997).

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Fishery

Shrimp landings from the Barents Sea (ICES area I) and Spitsbergen area, (ICES area IIb) by Norway, Russia and

other countries in the period 1970–2002

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Regulation

 Number of fishing days and number of vessels by country in Spitsbergen area.

 Fishing grounds are closed if fish by-catch limits are exceeded: Cod and haddock 8, redfish 10 and Greenland halibut 3/ 10 kg shrimp.

 Minimal mesh size of shrimp trawls is 35 mm.

 Selective grids are used since 1993.

 Norway: - Smallest allowable shrimp size (10% of catch weight may be <15 mm CL)

- Licence to attend the shrimp fishery

 Russia: - Experimental TAC is established annually in the Russian Economic Zone

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Conclusions

•Norwegian and Russian scientists agreed upon the procedures for obtaining shrimp biological data in 1993.

•Scientists agree on how the available length-at-age data should be implemented in the production of recruitment indices, maturity- at-age and catch at age data.

•The great plasticity in growth of shrimp and age at sex change, as well as a lack of biological data and length distributions from the catches make it difficult to apply traditional analytical fishery assessment methods.

•Production, cohort models and length at age analysis have been used in attempts of assessing shrimp stock.

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Conclusions

•There is a strong correlation between the Norwegian and the Russian survey results since 1984.

•Biomass indices were highest during 1984, and have since fluctuated between 30% and 60% of this level.

• The shrimp stock in the Barents Sea and Spitsbergen area is not managed by a TAC. Indirect effort regulations are conducted.