SCRS/2016/119 Collect. Vol. Sci. Pap. ICCAT, 73(3): 1115-1132 (2017)
1115
UPDATED CATCH RATES OF SWORDFISH (XIPHIAS GLADIUS) CAUGHT BY
THE MOROCCAN FLEET IN THE STRAIT OF GIBRALTAR, 1999-2015
Noureddine Abid1, Abdelouahed Ben Mhamed2 & Mohammed Malouli Idrissi2
SUMMARY
The catch rates from the Moroccan fleet targeting swordfish in the Strait of Gibraltar, from
1999 to 2015, were analyzed using the General Linear Modelling approach (GLM), under
lognormal error assumption in order to compute standardized abundance indices. The relative
abundance index showed a relative stable trend over the period 1999-2011, but the index
showed an increase in 2012 to remain stable thereafter.
RÉSUMÉ
Les taux de capture de la flottille marocaine ciblant l’espadon dans le détroit de Gibraltar
entre 1999 et 2015 ont été analysés au moyen de l’approche de modélisation linéaire
généralisée (GLM), en postulant une erreur lognormale afin de calculer les indices
d’abondance standardisés. L'indice d'abondance relative présentait une tendance relativement
stable entre 1999 et 2011, mais l’indice affichait une augmentation en 2012 avant de rester
stable par la suite.
RESUMEN
Las tasas de captura de la flota marroquí que se dirigió al pez espada en el estrecho de
Gibraltar, desde 1999 a 2015, se analizaron utilizando un enfoque de modelación lineal
generalizado (GLM), con un supuesto de error lognormal con el fin de calcular índices de
abundancia estandarizados. El índice de abundancia relativa presentaba una tendencia
relativa estable durante el periodo 1999-2011, pero el índice mostraba un aumento en el año
2012 y permaneció estable a partir de entonces.
KEYWORDS
Swordfish catch rates, Strait of Gibraltar, General linear modelling (GLM)
1 INRH, regional centre of Tangier, [email protected] 2 INRH Casablanca
1116
1. Introduction
During the period 1990-2011, the Moroccan driftnet fishery was one of the most important fisheries exploiting
the Mediterranean swordfish. The vessels were mainly operating in the Strait of Gibraltar.
With an annual average catch of about 2850 TM, Morocco came in the second place among the producing
countries of this species in the Mediterranean Sea after Italy. The fleet targeted swordfish from April to June
when fish is undertaking a genetic migration to the Mediterranean Sea and during its feeding migration from
the Mediterranean to the Atlantic, during July-September (El Hannach, 1987, Abid, 1998, Srour and Abid, 2004;
Abid and Idrissi, 2007a).
During the 90s, the Moroccan swordfish catches taken by driftnet were the most important and represented about
60% on average of the total catches of this species at the national level. Nevertheless, since 2008, swordfish
catches taken by this gear have steadily decreased because of the implementation of the National plan for
banning gradually driftnet due to ICCAT recommendation (Rec. 03-04). In 2012, fishery department banned
driftnet from the Moroccan waters.
The swordfish stocks are assessed at regional level by the International Commission for the Conservation of
Atlantic tunas (ICCAT) mainly by means of Analytical and production models which make use of relative
abundance indices from the major fisheries targeting this species (Anonymous, 2013).
The scientific monitoring of the Moroccan swordfish fishery operating in the Strait of Gibraltar was of a great
importance at the regional level, especially in terms of updating and analyzing the trend of the relative
abundance index. The ICCAT scientific committee has used this index for the assessment of the Mediterranean
swordfish stock in 2007, 2010 and 2014 (Anonymous, 2008; 2011; 2015).
The standardization of catches rate of the Mediterranean swordfish by eliminating the effect of the external
factors other than the stock abundance is required for the stock assessment purposes (Anonymous, 2013). The
aim of this document is to update the relative annual abundance index to be taken into consideration in the 2016
stock assessment.
2. Material and Methods
2.1 Description of data source
The catch (in weight) and effort data per trip related to the Moroccan driftnet fleet for the period 1999-2011 and
to longliners targeting swordfish in the Strait of Gibraltar during the period 2001-2015, were collected from the
commercial fishing statistics recorded in the fish market at the port of Tangier.
The structure of the dataset is as follow: date of landing, vessel name, GRT, catch in weight, estimated length of
net, estimated number of hooks. A total of 37144 daily trips were available for analysis.
2.2 Size/age range of fish
The abundance index is applied to fish whose size ranged from 100 to 240 cm LJ-FL, with an average size of
145cm LJ-FL. These sizes correspond to fish aged 2-9 years (Figure 1).
2.3 Management regulation
The Moroccan driftnet fishery has known a noticeable development since the early 90s in terms of fishing effort
and the volume of swordfish catches. It recorded a peak of about 5000 TM in 1997. Nevertheless, with the
driftnet ban in 2012, the fishing effort as well as the catches displayed a downtrend during the period 2012-2015
(average catch of 800 TM) where the catches have been made only by longliners.
In order to take into account the effect of the recent management regulation on the catch rates, the CPUE data
related to driftnet for the period 1999- 2011 were included in the analysis, with the gear effect included in the
GLM model.
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2.4 Model standardization
As recommended by the SCRS, the fishing effort for drift netters was defined as the total length of net set by a
given vessel. The fishermen spend one fishing day at sea during which one fishing operation is carried out. The
fishing effort per vessel and per trip was estimated using the following formula:
Unit fishing effort = 1.171xGRT^0.416
Previous analyses showed that there is a strong correlation between the total length of net used by a vessel and
its Gross Registered Tonnage (GRT), (r2=0.80) (Abid and Idrissi, 2007).
For longliners, the length of each trip is on average 5 days. During one fishing operation, about 1000 hooks were
set.
As to longliners, the nominal CPUE was defined as the total weight of swordfish in kg/1000 hooks, whereas for
drift netters, the nominal CPUE was calculated as the total weight in kg/1000m of net.
All the daily trips catch rate data were analysed by means of the General Linear Modelling analysis (Gavaris,
1980; 1988) to analyse the effect of the month, vessel Gross Registered tonnage (GRT), on the catch rate and
compute an annual standardized abundance index under a lognormal error distribution.
As in the previous analyses, we considered 5 levels for the factor month: April, May, June, July and August for
drift netters and 4 levels for longliners: January, February, November and December.
As to GRT, we considered the six (6) levels below:
Vessel size levels GRT
1 GRT< 10
2 10≤GRT<20
3 20≤GRT<30
4 30≤GRT<40
5 40≤GRT<50
6 GRT> 50
The step AIC analysis was performed to select the statistically significant factors in the final model.
For drift netters, the final model is as follow:
Log CPUE w= U + Y i + M j + S k + Y i: M j + Y i : S k + M j : S k + e ijk
For longliners, the final model is as follow:
Log CPUE w= U + Y i + M j + S k + e ijk
Log : natural logarithm
CPUE w : catch rate in weight
U : intercept
Y i : year effect
M j : month effect
S k : vessel GRT effect
Y i: M j : interaction between year and month
Y i : S k : interaction between year and vessel GRT
M j : S k: interaction between month and vessel GRT
e ijk : error
1118
3. Results and Discussions
The numbers of observations (trips) by year, month and vessel GRT class combination levels for drift netters and
longliners are summarised in the Table 1A and 1B. In general, the number of trips analysed by level
combination seems to be satisfactory.
Figures 2, 3 and 4 display the distribution of Log CPUEw by year, month, vessel GRT class and gear.
Differences in CPUE can be observed among years, months, vessel GRT classes and Gear types.
Tables 2A and 2B shows the results of the deviance analysis. All the factors considered in the analysis: year,
month, vessel GRT class and gears are statistically significant at 0.5% level. The selected model explains about
9% of the total deviance. The factors month, vessel- GRT class and year contribute with 45%, 32% and 22% of
the total deviance, respectively. The factor gear explained only 0.25% of the variability in CPUE.
The selected models fit well the observed data as the residuals distribution follows a normal pattern (Figures 5A
and 5B).
The nominal CPUE, the standardized CPUEs, with their corresponding lower and upper confidence interval
(95%), the coefficient of variation (CV) by fishing gears are presented in the Tables 3A and 3B. The trend of
the annual standardized index is illustrated by the Figures 6A and 6B.
1119
References
Abid, N.1998. Contribution à l’étude de la pêcherie marocaine de l’espadon dans le détroit de Gibraltar. 217
Mémoire de troisième cycle pour l’obtention du diplôme d’ingénieur d’état, spécialité : Halieutique. I.A.V,
218 Hassan II. Rabat. 92 p
Abid, N and. Idrissi, M. 2007a. Situation récente de la pêcherie marocaine de l’espadon (Xiphias gladius).
Période: 1996-2005. Collect. Vol. Sci. Pap. ICCAT, 60(6): 2018-2028.
Abid, N and Idrissi, M. 2008. Standardized catch rates of swordfish (Xiphias gladius) from the Moroccan
driftnet fishery operating in the Mediterranean Sea during the period 1998-2006. Collect. Vol. Sci. Pap.
ICCAT, 61(4): 1107-1111.
Abid, N and Idrissi, M. 2009. Analysis of the size data of swordfish (Xiphias gladius) caught by the Moroccan
driftnet fishery operating in the Mediterranean Sea. Period 1999-2006. Collect. Vol. Sci. Pap. ICCAT, 64(6):
2093-2104.
Abid, N and Idrissi, M. 2011. Standardized catch rates of swordfish (Xiphias gladius) caught by the Moroccan
driftnet fleet in the Mediterranean Sea. Period 1999-2009. Collect. Vol. Sci. Pap. ICCAT, 66(4): 1480-1488.
Anon. 2008. Report of the 2007 ICCAT Mediterranean swordfish stock assessment session. Collect. Vol. Sci.
Pap. ICCAT, 62(4): 951-1038.
Anon. 2011. Report of the 2010 ICCAT Mediterranean swordfish stock assessment meeting. Collect. Vol. Sci.
Pap. ICCAT, 66(4): 1405-1470.
Anon. 2013. Report of the 2012 meeting of the ICCAT working group on stock assessment methods. Collect.
Vol. Sci. Pap. ICCAT, 69(3): 1354-1426.
Anon. 2015. Report of the 2014 ICCAT Mediterranean Swordfish Stock Assessment meeting (Heraklion,
Greece, 21-25 July 2014). Collect. Vol. Sci. Pap. ICCAT, 71(5): 1870-1879.
El Hannach, A. 1987. Données biologiques et écologiques sur l’espadon (Xiphias gladius) L.1758 à partir de la pêcherie marocaine dans le détroit de Gibraltar. Thèse de Doctorat, spécialité halieutique. ENSA, Rennes,
France. 162 p.
Gavaris, S. 1980, Use of multiplicative model to estimate catch rate and effort from commercial data. Can.J.Fish.
Aquat.Sci.37: 2272-2275.
Gavaris, S. 1988, Abundance indices from commercial fishing. Collected papers on stock assessment methods.
CAFSAC Res. Doc.88/61. 167 pp.
Srour, A and Abid, N. 2004, Situation de la pêcherie de l’espadon (Xiphias gladius) des côtes marocaines.
Collect. Vol. Sci. Pap. ICCAT, 56(3): 898-903.
1120
Table 1A. Number of observations by factors levels combination for driftnet (1999-2011).
Month/GRT class 1 2 3 4 5 6 Total
1999 280 161 70 24 8 27 570
4 47 20 10 2 1
80
5 74 49 18 8 3 7 159
6 48 30 14 4 2 6 104
7 36 25 12 6
6 85
8 75 37 16 4 2 8 142
2000 88 112 68 36 10 15 329
4 3 32 22 14 5 6 82
5 15 39 25 10 2 1 92
6 27 18 10 6 2 2 65
7 29 16 8 5 1 5 64
8 14 7 3 1
1 26
2001 1355 1147 584 275 84 185 3630
4 281 208 101 38 11 40 679
5 618 408 200 79 23 49 1377
6 111 195 85 54 21 36 502
7 55 96 57 33 9 23 273
8 290 240 141 71 20 37 799
2002 1604 1355 775 414 124 241 4513
4 174 168 99 51 14 39 545
5 509 497 246 121 32 81 1486
6 384 282 166 84 26 59 1001
7 96 62 46 26 7 10 247
8 441 346 218 132 45 52 1234
2003 1002 958 645 360 108 172 3245
4 218 219 147 109 28 53 774
5 374 350 204 121 30 63 1142
6 146 161 111 73 20 34 545
7 98 102 75 28 16 11 330
8 166 126 108 29 14 11 454
2004 964 993 638 381 209 149 3334
4 173 161 139 72 49 27 621
5 405 434 239 145 81 60 1364
6 139 158 96 56 28 28 505
7 30 32 15 7 1 1 86
8 217 208 149 101 50 33 758
2005 475 775 578 345 172 146 2491
4 41 119 125 81 33 29 428
5 248 384 262 138 71 65 1168
6 52 87 65 50 30 27 311
7 33 55 19 9 7 3 126
8 101 130 107 67 31 22 458
2006 608 1074 688 408 221 231 3230
1121
4 163 305 168 112 44 61 853
5 205 378 215 139 63 84 1084
6 42 120 102 70 43 45 422
7 43 62 47 16 17 6 191
8 155 209 156 71 54 35 680
2007 514 969 737 410 200 259 3089
4 53 188 153 95 47 69 605
5 274 456 268 124 69 84 1275
6 47 107 97 56 29 35 371
7 5 11 14 1
31
8 135 207 205 134 55 71 807
2008 467 925 821 564 272 327 3376
4 65 156 135 89 33 63 541
5 192 471 285 192 105 143 1388
6 54 88 85 60 36 48 371
7 47 59 92 54 21 12 285
8 109 151 224 169 77 61 791
2009 347 807 819 505 261 286 3025
4 62 188 214 168 98 92 822
5 141 308 254 163 63 100 1029
6 63 138 123 77 47 49 497
7 39 59 69 20 23 2 212
8 42 114 159 77 30 43 465
2010 252 744 836 439 188 260 2719
4 26 114 158 99 43 47 487
5 115 347 291 160 71 106 1090
6 48 150 186 101 47 68 600
7 24 43 48 20 4 10 149
8 39 90 153 59 23 29 393
2011 35 620 700 438 225 240 2258
4 7 125 126 74 35 47 414
5 14 195 196 108 72 64 649
6
88 86 69 37 41 321
7 10 76 115 66 25 30 322
8 4 136 177 121 56 58 552
Total 7991 10640 7959 4599 2082 2538 35809
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Table 1B. Number of observations by factors levels combination for longliners (2001-2015).
Month/GRT class 1 2 3 4 5 6 Total
2001 1 29 12 4 3 24 73
1
5
8 13
2 1 14 9 1 1 9 35
11
7 3 3 2 5 20
12
3
2 5
2002 1 26 35 16 4 18 100
1
3
1
3 7
2 1 16 16 5 2 8 48
11
7 16 2 1 4 30
12
3 8 1 3 15
2003
11 29 22 1 15 78
1
1 3 4
4 12
2
3 10 3
2 18
11
4 9 4
4 21
12
3 7 11 1 5 27
2004
22 19 20 13 19 93
1
6 4 4
5 19
2
1 2 2
1 6
11
7 8 6 7 6 34
12
8 5 8 6 7 34
2005
8 21 29 6 23 87
1
6 11 9 2 9 37
2
2 3 3 1 2 11
11
1 6 1 5 13
12
6 11 2 7 26
2006
8 51 25 11 19 114
1
7 4 2 1 14
2
2 7
2 11
11
4 27 6 5 10 52
12
4 15 8 4 6 37
2007 1 4 26 21 20 40 112
1
2 10 6 3 7 28
2
2 1
3 6
11 1 2 7 4 8 9 31
12
7 10 9 21 47
2008
32 45 30 36 143
1
6 8 10 19 43
2
7 3
1 11
11
16 22 14 13 65
12
3 12 6 3 24
2009 1 13 52 59 24 29 178
1
1 3 2 2 8
2
1 3 1 5
1123
11
1 3 3 2 1 10
12 1 12 48 52 17 25 155
2010
14 53 36 21 23 147
1
3 13 11 7 8 42
2
2 3 2 1 2 10
12
9 37 23 13 13 95
2011 1 7 30 26 18 15 97
1 1
9 10 9 3 32
2
3 17 13 6 6 45
12
4 4 3 3 6 20
2012 1 1 16
10 13 41
1
2
2
2
1
1
3
2
2
9
2
3 2 7
12 1 1 10
6 11 29
2013
5 12
6 16 39
1
1 3
4 3 11
2
2
2 2 6
4
2
2
5
1
2 3
9
1 3
1 5
12
2 2
8 12
2014
7 2 5 3 9 26
1
1
2 3
2
1
1
4
1 1
9
1 1
12
7 1 5 2 5 20
2015
1
3 2 1 7
1
1
2 1 4
12
3
3
Total général 6 156 390 311 172 300 1335
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Table 2A. Analysis of deviance results for driftnetters.
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Table 2B. Analysis of deviance results for longliners
Table 3A. Least square means, standard errors, standardized abundance indices with corresponding 95% upper
and lower confidence limits and coefficient of variation. Driftnetters, 1999-2011.
Year Nominal
CPUE Std.CPUE Upper Lower CV (%)
1999 57.32291
56.2554
79.4133
39.8506 4.6
1.2%
1.3%
1.4%
1.4%
1.9%
1.6%
1.7%
1.8%
1.7%
2.2%
4.7%
2.8%
2000 71.61301
64.8483
55.3103
55.473
53.0692
60.7784
55.4009
64.8643
61.0197
69.5657
63.1766
65.038
51.6316
123.3478
120.9122
113.9048
117.4016
71.0641
59.1762 1.2
2001 54.47799
56.1695
62.2694
50.6671 1.3
2002 54.33921
42.6038
46.9444
38.6645 1.4
2003 52.55259
57.2728
63.5672
51.6016 1.4
2004 65.04154
57.2728
61.4932
41.3861 33.4251
67.46 51.8576
58.7345 45.1325
71.6191 54.6035
65.0892 46.9382
79.4891 39.5927
96.4963 60.737
46.1178 1.9
2005 61.00112
37.1932
41.3861
33.4251 1.6
2006 70.06632
59.1466
67.46
51.8576 1.7
2007 68.67038
51.4863
58.7345
45.1325
1.8
2008 77.81795
62.5352
71.6191
54.6035
1.7
2009 68.73809
55.2736
65.0892
46.9382 2.2
2010 71.99499
56.0998
79.4891
39.5927 4.7
2011 54.49585
76.5565
96.4963
60.737 2.8
Factors df Residual
deviance
Change in
deviance F Pr(>F)
% in the
total
deviance
Null
27112
Year
12 26645 467
59.1725 < 2.2e-16 ***
12.79
Month
4 25557 1088
413.4694 < 2.2e-16 ***
29.80
GRT_class
5 24836 721
219.1715 < 2.2e-16 ***
19.75
Year:Month 48 24289 547
17.3216 < 2.2e-16 ***
14.98
Year:GRT_class 60 24018 271
6.8581 < 2.2e-16 ***
7.42
Month:GRT_class 20 23461 557
42.2960 < 2.2e-16 ***
15.26
Factors df Residual
deviance
Change in
deviance F Pr(>F)
% in the
total
deviance
Null
1151.13
Year
14 1064.78 86.347 8.5491 < 2.2e-16 ***
41.61622
Month
7 1034.64 30.139 5.9680 7.407e-07 ***
14.52594
GRT_class
5 943.64 90.998 25.2267 < 2.2e-16 ***
43.85784
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Table 3B. Least square means, standard errors, standardized abundance indices with corresponding 95% upper
and lower confidence limits and coefficient of variation. Longliners, 2001-2015.
Year Nominal
CPUE Std. CPUE Upper Lower CV
2001 40.1178
26.4668
60.9507
11.4927
14.43
2002 52.4140
31.8979
74.196
13.7133
13.74
2003 64.1436
36.0351
83.3281
15.5833
13.13
2004 78.9591
38.6269
89.164
16.7336
12.83
2005 62.1609
30.4991
70.347
13.2229
13.79
2006 84.5596
43.9984
100.5334
19.2559
12.19
2007 79.1482
41.2178
94.4756
17.9825
12.47
2008 62.4420
33.106
75.6302
14.4917
13.28
2009 75.6978
34.469
78.883
15.0617
13.14
2010 58.9551
34.5673
79.2475
15.078
13.16
2011 64.6639
40.1586
95.0174
16.9728
13.07
2012 157.9268
72.7279
175.2437
30.1828
11.35
2013 119.1333
70.8365
174.7483
28.7145
11.75
2014 105.8385
63.5715
190.4096
21.2244
14.81
2015 108.3714
67.2613
155.6885
29.0586
11.03
1126
Figure 1. Monthly size distribution of swordfish landed at the port of Tangier (Strait of Gibraltar), 2006-2011.
1127
A
B
Figure 2. Box plots indicating the distribution of Log CPUEw by year for driftnetters (A) and longliners (B).
1128
A
B
Figure 3. Box plots showing the distribution of Log CPUEw by month for driftnetters (A) and longliners (B).
1129
Figure 4. Box plots showing the distribution of Log CPUEw by vessel GRT class for driftnetters (A) and
longliners (B).
1130
A
B
Figure 5A. Diagnosis plots: normal qq plots (A) and residuals vs fitted positive catch distribution (B) for
Driftnetters.
1131
A
B
Figure 5B. Diagnosis plots: normal qq plots (A) and residuals vs fitted positive catch distribution (B) for
longliners
1132
Figure 6A. Standardized abundance index, with its corresponding upper and lower confidence limits for
driftnetters, 1999-2001.
Figure 6B. Standardized abundance index, with its corresponding upper and lower confidence limits for
longliners, 2001-2015.