Download Sustainable management of mixed demersal

652
Sustainable management of mixed demersal fisheries in the
North Sea through fleet-based management—a proposal
from a biological perspective
Hans-Joachim Rätz, Eckhard Bethke, Hendrik Dörner, Doug Beare, and Joachim Gröger
Rätz, H-J., Bethke, E., Dörner, H., Beare, D., and Gröger, J. 2007. Sustainable management of mixed demersal fisheries in the North Sea through
fleet-based management—a proposal from a biological perspective. – ICES Journal of Marine Science, 64: 652– 660.
Cod, haddock, whiting, saithe, plaice, sole, and Norway lobster are main target species for the mixed demersal fisheries of the North
Sea, Skagerrak, and eastern Channel. Management by total allowable catch has not been able to constrain exploitation of individual
species, so the potential for a fleet-specific effort management system to reach the management objectives established for the stocks is
simulated. Relative fleet-specific effort factors are estimated based on the sum of partial fishing mortalities of the species caught,
weighted by the stocks at risk of reduced reproductive capacity. The strategy promotes the use of selective gear and levies nonselective gear. The factors were applied in medium-term simulations of the annual decision process in accordance with existing
and proposed multi-annual management plans (including for cod recovery). Strict effort reduction would be required for fleets targeting cod, plaice, or sole (specifically large- and medium-mesh trawler fleets, beam trawlers, and gillnetters) for 5 years, reducing the
exploitation rates on all stocks substantially. Cod and plaice are predicted to recover by 2010 and cod catches to exceed recent levels
continually, with the more selective longliners and some other gear types profiting most. Management objectives for cod dominate
annual effort adjustments, resulting in substantial underexploitation of other stocks. However, even a 10% bias caused by non-compliance would largely halt cod recovery and the restoration of other stocks.
Keywords: mixed demersal fisheries, multi-annual fleet effort management, North Sea.
Received 30 June 2006; accepted 30 January 2007; advance access publication 16 April 2007.
H.-J. Rätz and J. Gröger: Federal Research Centre for Fisheries, Institute for Sea Fisheries, Palmaille 9, D-22767 Hamburg, Germany. E. Bethke: Federal
Research Centre for Fisheries, Institute for Gear Technology, Palmaille 9, D-22767 Hamburg, Germany. H. Dörner and D. Beare: European
Commission, DG Joint Research Centre (JRC), IPSC Institute for the Protection and Security of the Citizen, AGRIFISH Unit, TP 266, 21020 Ispra,
Italy. Correspondence to H-J. Rätz: tel.: þ49 40 38905 169; fax: þ49 40 38905 263; e-mail: [email protected]fisch.de
Introduction
For several decades, landings from the demersal fisheries in the
North Sea, the Skagerrak, and eastern Channel (here referred to
for convenience as part of the North Sea) have been declining as
a consequence of the deterioration in target stocks (ICES,
2005a). The seven main demersal species are cod (Gadus
morhua), haddock (Melanogrammus aeglefinus), whiting
(Merlangius merlangus), saithe (Pollachius virens), plaice
(Pleuronectes platessa), sole (Solea solea), and Norway lobster
(Nephrops norvegicus). Figure 1 illustrates the average geographical
distribution patterns of the international landings of these species
during the period 2000–2004. Haddock and saithe are caught
mainly in the northern North Sea, and cod and whiting in the
northern and southern North Sea, the Skagerrak, and eastern
Channel. The flatfish plaice and sole are caught mainly in the
southern North Sea and eastern Channel, and Norway lobster
overlapping with gadoids in the northern North Sea and the
Skagerrak.
European fleets exploit these stocks with non-selective gears in
“mixed fisheries”. Mixed fisheries often cause management conflict between ecological (Greenstreet and Hall, 1996; Jennings
et al., 1999; Pope et al., 2000) and economic objectives. They are
also characterized by high levels of discarding (Pastoors et al.,
2000; Cotter et al., 2002). Single-species quota allocations may
add to the discard problem because fishing may continue when
the quota for one or more species is exhausted. This is perhaps
one reason that total allowable catch (TAC) regulations, based
on single-stock considerations, have failed to curtail the exploitation of demersal species to sustainable levels, and that the cod and
plaice stocks are now failing to show signs of recovery, despite the
conservation measures enacted recently.
Here, we investigate the potential for fleet-specific effort management in the North Sea mixed demersal fisheries with the aim of
maximizing catches within constraints set by stock conservation,
as defined in multi-annual management or recovery plans (CEC,
2004, 2005a) and their associated interim measures (CEC, 2002,
2003, 2005b, 2006), and by the precautionary approach (FAO,
1995). Effort management and its decisive procedures are simulated in medium-term predictions over ten years.
Material and methods
Stock parameters and management objectives
Of the seven main target species, cod, plaice, and sole stocks are
the most severely reduced (see Table 1 for the essential stock
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Sustainable management of mixed demersal fisheries in the North Sea
653
Figure 1. Distribution patterns of international landings of cod, haddock, saithe, whiting, plaice, sole, and Norway lobster (Nephrops) in the
North Sea, the Skagerrak and the eastern Channel, 2000 –2004.
654
H.-J. Rätz et al.
Table 1. Essential stock parameters (stock numbers-at-age in 2005, F, SSB) of five demersal stocks in the North Sea, the Skagerrak, and
the eastern Channel, precautionary reference points for SSB (Bpa) and F (Fpa, Ftarget), major management regulations, and Ricker
stock recruitment function parameters.
Parameter
Cod
Haddock
Saithe
Plaice
Sole
Age
1
(in
thousands)
157
309
422
200
–
913
747
97
039
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
2
(in
thousands)
54
555
74
800
–
638
000
58
657
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
3 (in thousands)
8643
43 100
123 801
171 629
59 561
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
4
(in
thousands)
7668
11
400
61
629
328
564
77
407
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
5 (in thousands)
1221
116 100
59 872
58 278
14 069
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
6
(in
thousands)
1324
317
200
38
086
28
608
12 997
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
7
(in
thousands)
100
3600
28
880
14
816
3560
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
8
(in
thousands)
–
–
6916
8523
2659
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
9 (in thousands)
–
–
6710
10 256
3017
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
10
(in
thousands)
–
–
2301
2787
701
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
SSB
2005,
(kt)
40
266
244
205
41
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
(kt)
150
140
200
230
35
B. . .pa
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
SSB
annual increase (recovery plan), %
30
–
–
–
–
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Age
range
reference
F
2
–4
2
–4
3–
6
2–
6
2
–6
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Reference
F 2005
0.55
0.33
0.27
0.58
0.35
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
0.65
0.70
0.40
0.60
0.40
F. . pa
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
0.40
0.30
0.30
0.30
0.20
F. . target
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Maximum
annual
reduction
in
F,
%
210
–
210
210
210
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Maximum
annual change in TAC*, %
+15
–
+15
+15
+15
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Ricker
k
(kt)
352
395
298
270
47
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Ricker
a
5.46
23.73
1.49
9.69
6.05
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
5%
quantile
of
recruitment
(thousands)
114
000
412
000
78
000
418
000
28
000
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Recruitment CV
0.83
1.58
0.5
0.68
0.9
*Disregarded for all stocks because of frequent conflicts in the simulation results when effective for more than one stock at the same time.
parameters used in medium-term predictions and management
benchmarks). Since 2000, the spawning-stock biomass (SSB)
of cod has remained below the limit reference biomass (Blim ¼
70 000 t; ICES, 2005a) that should be avoided because it implies
an immediate risk of reduced reproductive capacity. Recently, estimates of SSB have ranged around 40 000 t. Annual exploitation
rates, expressed as mean rates of fishing mortality (F ) on age
groups 2 –4, increased steadily until 1980, to exceed the limit
reference point for F (Flim ¼ 0.86). Subsequently, exploitation
remained too high and is held responsible for the current poor
status of the stock. Mean stock and catch weight-at-age, maturity
ogives, and natural mortality represent long-term averages used in
the most recent assessment (ICES, 2006a). Initial population estimates (of numbers at 1 January 2005) were generated from the
short-term prediction outputs for 2005 (ICES, 2005b) based on
status quo exploitation patterns because conflicting survey
indices and uncertainties in catch statistics prevented an updated
assessment. However, F-at-age in 2005 was reduced by 40% to
reflect the reduced mortalities deduced from survey indices
(ICES, 2006a). As the stock remained depressed and F remained
high, the model results are robust against the starting values for
2005.
The plaice stock has also been depleted by exploitation rates
that were too high. Discard rates (in numbers) exceed 80%
(Pastoors et al., 2000). Since the early 1990s, SSB has fallen
by 50%, but remained above the limit reference level (Blim ¼
160 000 t). Since the mid-1950s, F has increased steadily, varying
around Flim (0.74) over the past 10 years (ICES, 2006a). The
historical dynamics of recruitment are largely unknown because
of extremely variable discard rates. The limit and target reference
points listed in Table 1 allow for the recently proposed management plan (CEC, 2005a).
In contrast to cod and plaice, haddock and saithe stocks
recently matched what is thought to be their full reproductive
capacity. However, discard rates of haddock have been high, and
some saithe quota has not been utilized as a consequence of
poor prices. Differences between the SSB estimated by short-term
prediction (ICES, 2006a) and the medium-term estimates presented here, result from the latter being based on the much
higher weight-at-age derived from long-term averages.
The sole stock has sustained intensive exploitation for decades,
but also appears to be overfished in terms of maximum sustainable
yield (MSY; ICES, 2005a). The target F is taken from the proposed
management plan and is consistent with its geographic interaction
with plaice.
Unfortunately, the data available for whiting prohibit a reliable
assessment of stock status. The six functional stock units distinguished for Norway lobster display constant or increasing abundance, while total landings of around 20 000 t have been
maintained. However, an equally rigorous assessment as for
demersal fish is not possible, so whiting and Norway lobster
have been excluded from the analysis.
Fleet-specific effects
The definition of fisheries and fleets requires precise knowledge of
their specific effect on exploited stocks through landings and
655
Sustainable management of mixed demersal fisheries in the North Sea
Table 2. Quantitative interactions among six fleets regarding their
effects on five North Sea demersal stocks expressed as relative
partial fishing mortality.
Fleet
Cod Haddock Saithe Plaice Sole
Beam
trawl
80
mm
0.15 0.03
0.03
0.72
0.85
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . .
Demersal
trawl
100
mm
0.43
0.81
0.80
0.10
0.03
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . .
Demersal
trawl 70 –99 mm 0.19 0.08
0.03
0.10
0.03
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . .
Static
0.20
0.03
0.07
0.05
0.05
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . .
Longline
0.02 0.03
0.03
0.02
0.03
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . .
Other
0.02 0.03
0.03
0.02
0.03
discarding. Since 2001, sampling of landings and discards by fleets
and gear type has been supported and regulated by a data collection regulation (CEC, 2001). Catch data from various European
fleets for 2004 have been collated by the Scientific, Technical and
Economic Committee for Fisheries (STECF, 2005). Table 2 lists
the quantitative effects of six gear categories on the five demersal
stocks for which sufficient data were available, expressed as relative
partial fishing mortalities (Rijnsdorp et al., 2006) based on the
catch-at-age proportions taken (excluding unallocated catches).
This information is regarded as representing technical interaction
in the mixed fisheries. The small-mesh (16 –31 mm) demersal
trawl is entirely disregarded in the analyses because it is used
mainly by industrial fisheries directed at sandeel (Ammodytes
spp.) and Norway pout (Trisopterus esmarki), and has minor
effects on the stocks considered here.
Cod biomass appears most affected by large-mesh demersal
trawls (100 mm), whereas medium-mesh demersal trawls (70 –
99 mm), beam trawls (80 mm), and static gears have less, but
still measurable, effect (ICES, 2006a). Haddock and saithe are
almost exclusively taken by large-mesh demersal trawls, though
small shares are also taken by medium-mesh trawls. Plaice
catches are widely spread over the gear categories, but most are
taken by beam trawls. Sole are caught mainly by beam trawls
and to a small extent by static gear (e.g. trammel-nets and tangle
nets).
Fleet-based management
Based on the data, fleet-specific effects on the five demersal fish
stocks in the North Sea (i.e. our original seven, but without
whiting and Norway lobster) can be quantified for 2004. We
believe that such knowledge can be used to safeguard sustainable
catches (as well as meeting the goals of multi-annual recovery
plans) of all species caught in mixed fisheries. Important issues
are the number of fleets involved and the number of stocks,
their exploitation rates, and their SSBs in relation to sustainable
levels (stock status).
The fleet-specific effect on different stocks can be derived from
the partial fishing mortality (Fpar) on each, which is defined as the
proportional contribution of a fleet to the total catch times F
(averaged over an appropriate range of age groups; Rijnsdorp
et al., 2006). We express the relative partial F (Fparrel) by fleet as
Fparrel ð f; sÞ ¼
Fparð f; sÞ
;
FðsÞ
where f is the fleet index, and s is the species index.
ð1Þ
Fleet-based effort management in a mixed fishery may be visualized as a scheme that allows some maximum effort for each individual fleet, which is determined by individual effort factors on
each species. The fleet- and species-specific reciprocal value of
the relative partial F (rFp( f,s)) appears to be a suitable starting
point for calculating an effort factor for all species combined: if
rFp( f,s) is high, the effect of a given fleet on a given stock is low,
and vice versa. The sum of rFp( f,s) over all fleets by species
equals 1, and the sum over all species by fleet represents the
numerically assessed effect of that fleet on the species mix relative
to other fleets (the sum of these values over all fleets equals the
number of fleets). In this way, a relative fleet-specific effort
factor can be derived that constrains the least selective (or least targeted) fleet in the mixed fishery through a handicap. In practice,
we deal with species that need different levels of effort constraints
because of their stock status. Therefore, it would seem appropriate
to put a weighting factor on rFp( f,s) that depends on the assessed
SSB relative to the value considered sustainable. Because we use
forward projections, the precautionary reference point (Bpa)
rather than Blim is appropriate here, and the relative fleet-specific
effort factor (Efac( f )) would become
Ps
1 1=ðFparrel ð f; sÞ SSBðsÞ=Bpa ðsÞÞ
Efacð f Þ ¼ Pf P
:
s
1
1 1=ðFparrel ð f; sÞ SSBðsÞ=Bpa ðsÞÞ
ð2Þ
Because extremely low bycatches of any species could have a
major effect on Efac( f ), we put a lesser constraint of 0.01 on the
value that Fparrel( f,s) can take, although low bycatches ought to
be neglected in considerations of the catch composition of the
main target species.
For making medium-term predictions of stock-specific parameters (SSB, catch, and F) and fleet-specific parameters (relative
effort changes and catches) for the period 2005–2015, Efac( f )
values were proportionally increased until either Fpa or Bpa was
reached. The model simulates annual management decisions on
effort adjustments by fleet, the constraining decision being
recorded each year. The forecast scenarios were also constrained
by a target F, a proxy for FMSY. Reaching this target was to be realized through annual reductions of a maximum of 10%, as stipulated in the multi-annual management plans for stocks shared with
Norway and currently under review for plaice and sole. For cod,
the reference SSB was calculated according to the recovery plan
(CEC, 2004) to ensure an annual increase of SSB by 30% during
the years 2005– 2015. However, the agreed maximum annual variation in the TACs for cod, saithe, plaice, and sole (+15%) had to
be disregarded, because that constraint was quite often exceeded in
the simulations, implying conflicting decision rules when the
maximum variation was exceeded for more than one species at
the same time.
The forecasts assume a Ricker (1975) stock-recruitment function for all stocks. Recruitment was generated allowing for
random error and with a minimum value set at the 5% quantile
of the distribution of recruitment observed (Table 1). Random
errors (+10%) were generated on the stock- and fleet-specific
catch weights-at-age, maturity, and natural mortality; stock size
in numbers and partial mortality-at-age were varied by +20%.
To simulate effects of non-compliance with the regulations,
stock numbers were subjected to a negative bias (overestimation)
and partial Fs to positive biases (underestimation) of 10% and
656
20%, respectively. Simulations without any bias (i), and with a
10% (ii), or 20% bias (iii) were run iteratively 100 times.
Results
Figure 2a illustrates the productivity potential of the five stocks
under the effort-management regime outlined, given the current
management objectives (excluding the +15% constraint on
annual variation in catches). All stocks grew steadily except
haddock, which decreased temporarily until 2007 as a consequence
of the strong 1999 year class being fished out. However, with a 10%
bias attributable to non-compliance, the cod stock did not recover
and the SSB of other species hardly improved relative to the
present. With a 20% bias, the cod stock disappeared and estimates
of SSB for all stocks dropped substantially, and projected catches
largely followed the same pattern (Figure 2b). Specifically and
without a non-compliance bias, annual catches of cod grew steadily, including during the recovery phase, until 2010. The technical
interactions of the main fleets in terms of catch composition were
responsible for marked initial reductions in the catches of other
stocks, whereas the large reduction in haddock catches was
driven by a declining abundance of the 1999 year class. Under
the simulation, cod catches rose to 250 000 by 2015, and catches
of haddock, saithe, and plaice stabilized at around 40 000,
70 0000, and 90 000 t, respectively. The interaction between
H.-J. Rätz et al.
plaice and sole in the beam trawl fleet constrained the catches of
sole below 10 000 t. Even a 10% bias attributable to noncompliance would markedly reduce catches of all species relative
to current levels.
Driven by the F-reduction and SSB constraints in the cod
recovery plan (no bias scenario), F on all other stocks simulated
reduced quickly from the starting values in 2005 (Figure 3) to
below the species-specific targets and at a faster rate than intended
in the management plans (.10% per year; Table 1). The target F
for cod (0.4) continued to be the major constraint on all demersal
fisheries, even after cod had recovered, resulting in underutilization of the other four stocks owing to their technical interactions
with cod.
The effort-management system simulated caused changes in
the distribution of fleet-specific relative effort (Figure 4) and the
associated catches (Figure 5). As intended, the fleets most affected
were those characterized by relatively large catches of the most
overexploited species. Large-mesh demersal trawls (100 mm)
contributed most to the required effort reductions until the cod
recovered in 2010. A similarly large effort reduction applied to
beam trawls (80 mm), which affected both cod and plaice.
Effort of medium-mesh demersal trawls (70 –99 mm) and static
gears had to be reduced initially by about 30%, because their
impact on cod and plaice is quite low. The more selective fleets
using longlines and other gear benefitted initially, and their
effort initially increased. After the projected cod stock recovery
by 2010, there were gradually fewer fleet-specific effort changes.
The trajectories of the projected fleet-specific catches (Figure 5)
indicated immediate, substantial declines for the fleets of beam
trawls (80 mm) and demersal trawls (100 mm). In contrast,
catches of static gears and medium-meshed demersal trawls
(70–99 mm) appeared to be more stable until 2010 and, subsequently, to increase. Compared with early years in the simulations, the catches of fleets deploying longline or other gears
almost exclusively for cod increased substantially as a consequence
of both their increase in effort and cod recovery.
Discussion
Figure 2. Comparative medium-term projections of five stocks in
the period 2005 – 2015 under three scenarios, without bias (A),
taking into account a +10% (B), and a +20% bias (C) in F
(underestimation) and in stock size (overestimation). Presented are
median values of 100 iterative simulations for (a) SSB and (b) catch.
TAC regulations based on single-stock considerations alone appear
insufficient for the effective management of mixed fisheries,
because they act as an incentive for discarding and misreporting
of landings that are in excess of the allocated quota (Cotter
et al., 2002; Daan et al., 2005). To adjust TAC regulations to the
potential catches of fleets engaged in mixed fisheries, either a
dictate for landing all catches or a fleet-based effort management
regime appears necessary. Closed areas are often applied to
protect endangered species or habitats but, applied in a fisheries
management context, would still require appropriate regulations
on effort (Horwood et al., 1998; Dinmore et al., 2003).
Fleet-based management might be an effective and malleable
tool for controlling F at sustainable levels, in the case of mixed fisheries through fleet-specific effort regulations, to avoid high rates of
discarding and unallocated landings (Shepherd, 2001). However,
effort management requires predefined, transparent management
goals, and control rules. Any attempt to realize effort management
immediately leads to the question, what are “good” fishing practices? A variety of adequate fleet-specific parameters and numerical
procedures are conceivable, including different weightings of catch
compositions. Available model approaches have recently been
reviewed by ICES (2006b). Vinther et al. (2004) applied recommended rates of exploitation for the stocks under consideration
Sustainable management of mixed demersal fisheries in the North Sea
Figure 3. Comparative medium-term projections (2005 – 2015) of
F for five stocks for scenario A (without bias). Presented are 0.05,
0.25, 0.5 (median), 0.75, and 0.95 quantile values of 100 iterative
simulations.
657
Figure 4. Comparative medium-term projections (2005 – 2015)
of effort changes (relative to 2005) for six fleets for scenario A.
Presented are 0.05, 0.25, 0.5 (median), 0.75, and 0.95 quantile values
of 100 iterative simulations. See also Figure 3.
658
Figure 5. Comparative medium-term projections (2005 – 2015)
of fleet-specific catches for six fleets for scenario A. Presented
are median values of 100 iterative simulations.
H.-J. Rätz et al.
in combination with stock-specific weighting factors to provide
effort management advice based only on short-term management
goals.
Our method considers the sum of the fleet-specific effects on
jointly caught species, including ecological quality goals regarding
recent stock status in relation to reference values (UN, 1995; Piet
and Rice, 2004). Such a strategy promotes fleets deploying
highly selective gears for undepleted stocks. This is balanced by
an effort reduction in fleets deploying non-selective gears taking
large proportions of their catches from overexploited stocks.
Note, though, that the method proposed is based entirely on arbitrary choices of parameters and operations, which are available
and considered meaningful for fleet-based effort management.
Although the ultimate goal is to attain maximum catches within
the constraints set by various stock conservation objectives, the
agreed maximum annual variation in TACs could not be
implemented, because these would imply conflicting decision
rules, when they are exceeded simultaneously for more than one
species.
An appropriate definition of fleet is a critical issue and probably
requires more than a simple classification based on a quantification of their effects on the stocks (i.e. mainly ecological
considerations). Fisheries-related economic parameters and arguments have been disregarded here largely because of a general lack
of relevant information.
A disadvantage of the method is the assumed precision of stock
assessments. Also, only stocks that have been assessed analytically
by age, and for which precautionary reference points for SSB and F
have been defined, are included. A variety of taxa taken in these
gears (all invertebrate and vertebrate bycatch species, but also
target species such as whiting and Norway lobster) do not fulfil
these requirements and, therefore, were not considered.
The application presented here is intended to demonstrate the
operational behaviour and medium-term consequences of fleetbased effort management. Major underlying assumptions are
that the productivity of the stocks in terms of natural mortality,
growth, and recruitment does not change relative to observations
during the past 40 years. Recent analyses of the impact of global
warming suggest major changes in stock productivity
(Beaugrand, 2004; Cook and Heath, 2005; Drinkwater, 2005)
and distribution patterns (Perry et al., 2005), though Kell et al.
(2005) emphasize the robustness of stock productivity under
appropriate exploitation strategies, taking into account effects
induced by climate changes.
The data used here were compiled from various databases
developed for providing routine management advice in the ICES
area. However, grave concerns have been expressed repeatedly
about the uncertainties in these databases, which would undermine their application for management purposes (Stratoudakis
et al., 1999). For instance, the fleet data have been compiled for
just a single year, and it seems doubtful that these could reasonably
be extrapolated over a 20-year period. Slightly different extensions
of the management areas for the five demersal stocks considered in
the analyses have been ignored. However, for a comprehensive
effort-management strategy, such discrepancies should be
resolved.
The simulation results suggest that, assuming full compliance
with regulations, the cod stock could recover by 2010. Until
then, however, the fisheries would have to suffer from marked
reductions in catch and effort. Thereafter, stocks are predicted to
continue to increase to levels comparable with those observed in
Sustainable management of mixed demersal fisheries in the North Sea
the mid-1960s. However, exploitation rates would have to remain
below the sustainable target levels, after initial drastic reductions,
except for cod. The technical interactions of all fleets catching
cod cause underutilization of other demersal stocks by 30 –50%.
This undesirable situation might be averted through the development of more selective fishing strategies, by considering technical
as well as geographical and seasonal measures (Madsen et al.,
1999). Despite technical interactions between different roundfish
fisheries, it is possible to take almost clean catches of a single
species on specific fishing grounds (Weber, 1999). Further, the
initiative to use sorting grids in Norway lobster fisheries to avoid
fish bycatches should provide scope for better utilization of that
valuable resource.
Global management targets in terms of MSYs to be attained
by 2015 were formulated in the Johannesburg declaration (UN,
2002). Based on the simulations here, realization of these targets
does not appear to be unrealistic, if appropriate measures were
implemented and respected. However, even a bias as low as
10%, introduced to simulate non-compliance with the regulations,
delays the cod stock recovery considerably and will not improve
medium-term yields anywhere close to the maximum sustainable
level (Horwood et al., 2006).
In the North Sea mixed fishery, the fleets operating demersal
trawls (100 mm) and beam trawls (80 mm) would have to
be cut more than those using medium-size-meshed demersal
trawls (70 –99 mm) and static gears. In contrast, but consistent
with the assessment of good fishing practice, longline effort and
the use of other gears might be increased because of the balancing
element in the relative effort factor proposed. The model results
appear similar to the fleet-specific effort limitations enacted
since 2003 (CEC, 2002, 2003, 2005b, 2006). After cod recovery,
annual effort adjustments for all the fleets defined here become
gradually smaller, but they remain controlled by constraints set
by the target F for cod rather than any other management or recovery plan. Such dominance of cod-related targets in the management of demersal stocks is to be expected because the historical
abundance of cod, and its wide distribution, are responsible for
the strong technical interactions among these fisheries.
Acknowledgements
We are indebted to Chris Darby, Ewen Bell, Coby Needle, Steven
Holmes, Rick Officer, Franck Coppin, Per Sparre, Stuart Reeves,
Willy Vanhee, Martin Pastoors, Rob Grift, and Joakim Hjelm for
their valuable contributions and comments during hard ICES
and STECF meetings. The manuscript benefited from the many
comments by Niels Daan and Sarah Kraak. The work itself and
many of the related events and evaluations were financially supported by the Commission of the European Community, DG Fish.
References
Beaugrand, G. 2004. The North Sea regime shift: evidence, causes,
mechanisms and consequences. Progress in Oceanography, 60:
245– 262.
CEC. 2001. Commission Regulation (EC) No. 1639/2001 of 25 July
2001 establishing the minimum and extended Community programmes for the collection of data in the fisheries sector and
laying down detailed rules for the application of Council
Regulation (EC) No. 1543/2000, L 222/53. Official Journal of
the European Communities EN.
CEC. 2002. Council Regulation (EC) No. 2341/2002 of 20 December
2002 fixing for 2003 the fishing opportunities and associated conditions for certain fish stocks and groups of fish stocks, applicable
659
in Community waters and, for Community vessels, in waters where
catch limitations are required. Official Journal of the European
Communities EN.
CEC. 2003. Council Regulation (EC) No. 2287/2003 of 19 December
2003 fixing for 2004 the fishing opportunities and associated conditions for certain fish stocks and groups of fish stocks, applicable
in Community waters and, for Community vessels, in waters where
catch limitations are required. Official Journal of the European
Communities EN.
CEC. 2004. Council Regulation (EC) No. 423/2004 of 26 February
2004 establishing measures for the recovery of cod stocks.
Official Journal of the European Communities EN.
CEC. 2005a. Commission Proposal COM(2005) 714 final of 10
January 2006 for a Council Regulation Brussels establishing a management plan for fisheries exploiting stocks of plaice and sole in the
North Sea. Official Journal of the European Communities EN.
CEC. 2005b. Council Regulation (EC) No. 27/2005 of 22 December
2004 fixing for 2005 the fishing opportunities and associated conditions for certain fish stocks and groups of fish stocks, applicable
in Community waters and, for Community vessels, in waters where
catch limitations are required. Official Journal of the European
Communities EN.
CEC. 2006. Council Regulation (EC) No. 51/2006 of 22 December
2005 fixing for 2006 the fishing opportunities and associated conditions for certain fish stocks and groups of fish stocks, applicable
in Community waters and, for Community vessels, in waters where
catch limitations are required. Official Journal of the European
Communities EN.
Cook, R. M., and Heath, M. R. 2005. The implications of warming
climate for the management of the North Sea demersal fisheries.
ICES Journal of Marine Science, 62: 1322– 1326.
Cotter, A. J. R., Course, G., Buckland, S. T., and Garrod, C. 2002. A
PPS sample survey of English fishing vessels to estimate discarding
and retention of North Sea cod, haddock, and whiting. Fisheries
Research, 55: 25– 35.
Daan, N., Gislason, H., Pope, J. G., and Rice, J. C. 2005. Changes in the
North Sea fish community: evidence of indirect effects of fishing?
ICES Journal of Marine Science, 62: 177 – 188.
Dinmore, T. A., Duplisea, D. E., Rackham, B. D., Maxwell, D. L., and
Jennings, S. 2003. Impact of a large-scale area closure on patterns of
fishing disturbance and the consequences for benthic production.
ICES Journal of Marine Science, 60: 371 – 380.
Drinkwater, K. F. 2005. The response of Atlantic cod (Gadus morhua)
to future climate change. ICES Journal of Marine Science, 62:
1327– 1337.
FAO. 1995. Code of Conduct for Responsible Fisheries. FAO, Rome.
49 pp. ftp://ftp.fao.org/docrep/fao/005/v9878e/v9878e00.pdf.
Greenstreet, S. P. R., and Hall, S. J. 1996. Fishing and ground-fish
assemblage structure in the north-western North Sea: an analysis
of long-term and spatial trends. Journal of Animal Ecology, 65:
577– 598.
Horwood, J. W., Nichols, J. H., and Milligan, S. 1998. Evaluation of
closed areas for fish stock conservation. Journal of Applied
Ecology, 35: 893 – 903.
Horwood, J., O’Brien, C., and Darby, C. 2006. North Sea cod recovery?
ICES Journal of Marine Science, 63: 961 – 968.
ICES. 2005a. Report of the ICES Advisory Committee on Fishery
Management, Advisory Committee on the Marine Environment
and Advisory Committee on Ecosystems, 2005. ICES Advice, 1 –
11. 1418 pp.
ICES. 2005b. Report of the Working Group on the Assessment of
Demersal Stocks in the North Sea and Skagerrak. ICES
Document CM 2005/ACFM: 07. 783 pp.
ICES. 2006a. Report of the Working Group on the Assessment of
Demersal Stocks in the North Sea and Skagerrak. ICES
Document CM 2006/ACFM: 09. 981 pp.
660
ICES. 2006b. Report of the Working Group Workshop on Simple
Mixed Fisheries Management Models (WKMIXMAN), 9 – 13
January 2006, Copenhagen. ICES Document CM 2006/ACFM:
14. 47 pp.
Jennings, S., Greenstreet, S. P. R., and Reynolds, J. D. 1999. Structural
change in an exploited fish community: a consequence of differential fishing effects on species with contrasting life histories. Journal
of Animal Ecology, 68: 617 –627.
Kell, L. T., Pilling, G. M., and O’Brien, C. M. 2005. Implications of
climate change for the management of North Sea cod (Gadus
morhua). ICES Journal of Marine Science, 62: 1483 – 1491.
Madsen, N., Moth-Poulsen, T., Holst, R., and Wileman, D. 1999.
Selectivity experiments with escape windows in the North Sea
Nephrops (Nephrops norvegicus) trawl fishery. Fisheries Research,
42: 167– 181.
Pastoors, M. A., Rijnsdorp, A. D., and van Beek, F. A. 2000. Effects of a
partially closed area in the North Sea (“plaice box”) on stock development of plaice. ICES Journal of Marine Science, 57: 1014– 1022.
Perry, A. L., Low, P. J., Ellis, J. R., and Reynolds, J. D. 2005. Climate
change and distribution shifts in marine fishes. Science, 308:
1912– 1915.
Piet, G. J., and Rice, J. C. 2004. Performance of precautionary reference
points in providing management advice on North Sea fish stocks.
ICES Journal of Marine Science, 61: 1305– 1312.
Pope, J. G., MacDonald, D. S., Daan, N., Reynolds, J. D., and Jennings,
S. 2000. Gauging the impact of fishing mortality on non-target
species. ICES Journal of Marine Science, 57: 689– 696.
Ricker, W. E. 1975. Computation and interpretation of biological statistics of fish populations. Bulletin of the Fisheries Research Board
of Canada, 191. 382 pp.
Rijnsdorp, A. D., Daan, N., and Dekker, W. 2006. Partial fishing mortality per fishing trip: a useful indicator of effective fishing effort in
H.-J. Rätz et al.
mixed demersal fisheries. ICES Journal of Marine Science, 63:
556– 566.
Shepherd, J. G. 2001. Fisheries management: breaking the deadlock. In
Sea-Power at the Millennium, pp. 233– 235. Ed. By G. Till. Royal
Naval Museum Publications. Sutton Publishing Co.
STECF. 2005. STECF Sub-group SGRST Evaluation of the Cod
Recovery Plan, Joint Research Centre, Ispra, Italy, 13 – 17 June
2005. 107 pp. http://stecf.jrc.cec.eu.int/meetings/sgrst/0504/
report.pdf.
Stratoudakis, Y., Fryer, R. J., Cook, R. M., and Pierce, G. J. 1999. Fish
discarded from Scottish demersal vessels: estimators of total discards and annual estimates for targeted gadoids. ICES Journal of
Marine Science, 56: 592 – 605.
UN. 1995. Agreement for the Implementation of the Provisions of the
United Nations Convention on the Law of the Sea of 10 December
1982 Relating to the Conservation and Management of Straddling
Fish Stocks and Highly Migratory Fish Stocks. United Nations
Conference on Straddling Fish Stocks and Highly Migratory Fish
Stocks, sixth session. New York, 24 July– 4 August 1995. A/
CONF.164/37, 8 September 1995.
UN. 2002. Report of the World Summit on Sustainable Development.
Johannesburg, South Africa, 26 August – 4 September 2002. A/
CONF.199/20*, United Nations publication, Sales No.
E.03.II.A.1, ISBN 92-1-104521-5. 173 pp.
Vinther, M., Reeves, S. A., and Patterson, K. R. 2004. From singlespecies advice to mixed-species management: taking the next
step. ICES Journal of Marine Science, 61: 1398– 1409.
Weber, W. 1999. Discard in der deutschen Seelachsfischerei.
Informationen aus der Fischereiforschung, 46: 24– 28.
doi:10.1093/icesjms/fsm030