SCRS/2014/081 Collect. Vol. Sci. Pap. ICCAT, 71(1): 275-287 (2015)

JAPANESE LONGLINE CPUE FOR YELLOWFIN TUNA (THUNNUS ALBACARES)

IN THE ATLANTIC OCEAN STANDARDIZED USING GLM UP TO 2013

Takayuki Matsumoto1 and Keisuke Satoh1

SUMMARY

Japanese longline CPUE in number for yellowfin tuna caught in the Atlantic Ocean was standardized in quarter and annual base using GLM (General Linear Model) for the period from 1965 to 2013 in order to provide indicator of the stock. Annual CPUE in weight was also estimated from 1970 to 2013. CPUE decreased until 1993 with some fluctuation, kept stable until 2003, and after that they increased.

RÉSUMÉ

La CPUE palangrière japonaise en nombre d'albacores capturés dans l'océan Atlantique a été standardisée par trimestre et année à l'aide d'un GLM (modèle linéaire généralisé) pour la période 1965-2013 afin de fournir un indicateur du stock. La CPUE annuelle en poids a également été estimée de 1970 à 2013. La CPUE a chuté jusqu'en 1993 avec quelques fluctuations, elle s'est maintenue stable jusqu'en 2003, et elle a augmenté par la suite.

RESUMEN Se estandarizó la CPUE del palangre japonés en número de rabiles capturados en el océano Atlántico por trimestre y por año utilizando un GLM (Modelo lineal generalizado) para el periodo 1965-2013 para proveer la indicación del stock. También se estimó la CPUE anual en peso desde 1970 hasta 2013. La CPUE descendió hasta 1993 con alguna fluctuación, se mantuvo elevada hasta 2003, y aumentó después.

KEYWORDS

Atlantic, Yellowfin, Longline, Catch/effort 1. Introduction Longline is the only tuna-fishing gear deployed by Japan at present in the Atlantic Ocean, and yellowfin tuna is one of the target species (Anon., 2013). Fishing effort for Japanese longline fishery covers almost entire Atlantic (Appendix, Figure 1), and yellowfin tuna is mainly caught in the tropical area (Appendix, Figure 2). Japanese longline CPUE for yellowfin in the Atlantic Ocean was standardized by GLM with lognormal error assumption up to 2013 in order to provide stock indicator of this species. As no stock assessment of this species is scheduled this year, updated CPUE based on the same method as that in Okamoto and Satoh (2008) or Satoh et al. (2012) is provided in the present study. 2. Materials and methods 2.1 Data The Japanese longline catch (in number and in weight) and effort statistics from 1965 (from 1970 for weight data) to 2013 were used. Data for 2013 are preliminary. The catch and effort data set was aggregated by month, 5-degree square and the number of hooks between floats (NHBF). The data in which the number of hooks was less than 5000 were not used for analyses. The NHBF from 1965 to 1974 is not available from logbook, 1National Research Institute of Far Seas Fisheries 5-7-1, Orido, Shimizu-Ku, Shizuoka-Shi, 424-8633, Japan.

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therefore the NHBF was regarded to be 5 for these years. Area definition is whole Atlantic, east Atlantic and west Atlantic (Figure 1). As environmental factor, which is available for the analyzed period from 1965 to 2013, SST (Sea Surface Temperature) was applied. The monthly SST data for 1-degree latitude and 1-degree longitude was obtained from NEAR-GOOS Regional Real Time Data Base of Japan Meteorological Agency (JMA). The SST data was averaged and recompiled into 5-degree latitude and 5-latitude longitude by month from 1965 to 2013 using the procedures described in Okamoto et al. (2001). 2.2 Model used for standardization The initial annual and quarterly models are the same as those for the last Japanese longline CPUE standardization analyses (Okamoto and Satoh, 2008 or Satoh et al., 2012). The effects of several factors on yellowfin catch were assessed using GLM procedure (log normal error structure model, SAS ver. 9.3, SAS Inst., Inc.). We intended to select the final model after variable selection with backward stepwise F test with a criterion of P-value = 0.05. In the cases in which the factor is not significant as main factor but is significant as interaction with other factor, the main factor was kept in the model. In order to explain two dimensional distribution of CPUE, the nonlinear relationship between SST and CPUE is applied into the model as explanation variables as SST2 and SST3. The interaction term between latitude and longitude was included in the model as the cubic expression (i.e., Lat + Lon + (Lat + Lon)2 + (Lat + Lon)3). The number of hooks between float (NHBF) were divided into 5 classes (CNHBF 1: less than 6, CNHBF 2: 6-8, CNHBF 3: 9-12, CNHBF 4: 13-16, CNHBF 5: larger than 16). The details of the initial models are as follows; For annual CPUE in number base and weight base Log (CPUE +const) = mean+YR+MN+AREA+NHFCL+SST+SST2+SST3+ML+BL+ interaction + error where Log: natural logarithm, CPUE: catch in number (weight) of bigeye per 1000 hooks, const: 10% of overall mean of CPUE mean: overall mean,

YR: effect of year, MN: effect of fishing season (month), AREA: effect of sub-area, NHFCL: effect of gear type (category of the number of hooks between floats), SST: effect of SST (as a continuous variable), SST2: effect of SST2 (=SST x SST, as a continuous variable), SST3: effect of SST3 (=SST x SST x SST, as a continuous variable), ML: effect of material of main line, BL: effect of material of branch line, Interaction: YR*AREA+YR*MN+MN*AREA+AREA*NHFCL+MN*SST+AREA*SST

+NHFCL*SST+ML*NHFCL+BL*NHFCL error: error term.

Effect of year was obtained by the method used in Ogura and Shono (1999) that uses lsmean of Year-Area interaction as the following equation. The sub-area is showed in Figure 2, which was used in last assessment. CPUEi = Σ Wj * (exp(lsmean(Year i*Area j))-constant), where CPUEi = CPUE in year i, Wj = Area rate of Area j , (ΣWj = 1), lsmean(Year*Area ij) = least square mean of Year-Area interaction in Year i and Area j (As for the quarter based CPUE, least square mean of Year*Quarter*Area was used instead), constant = 10% of overall mean of CPUE. For quarterly CPUE in number base Log(CPUE+const)=mean+YR+QT+Lat+Lon+Lat2+Lat*Lon+Lon2+Lat3+Lat2*Lon+Lat*Lon2+Lon3+NHFCL+SST+SST2+SST3+ML+BL+YR*QT+QT*SST+NHFCL*SST+ML+NHFCL+BL+NHFCL+QT*Lat+QT*Lat2+QT*Lat3+QT*Lon+QT*Lon2+QT*Lon3+NHFCL*Lat+NHFCL*Lat2+NHFCL*Lat3+NHFCL*Lon+NHFCL*Lon2+NHFCL*Lon3+SST*Lat+SST*Lat2+SST*Lat3+SST*Lon+SST*Lon2+SST*Lon3 +error Explanatory variables included in the initial model for quarterly CPUE are listed as follows. Explanatory variables which is included in the model for annual CPUE were not included in the list where, QT : effect of fishing season (quarter)

Lat, Lon, Lat2, Lat*Lon, Lon2, Lat3, Lat2*Lon, Lat*Lon2, Lon3: interactions between Latitude and Longitude expressed as third order polynomial functions. Latitude and Longitude are included as continuous variables.

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QT*Lat (*Lat2, *Lat3): interaction term between quarter and Latitude, QT*Lon (*Lon2, *Lon3): interaction term between quarter and Longitude, NHFCL*Lat (*Lat2, *Lat3): interaction term between gear type and Latitude, NHFCL*Lon (*Lon2, *Lon3): interaction term between gear type and Longitude, SST*Lat (*Lat2, *Lat3): interaction term between SST and Latitude, SST*Lon (*Lon2,* Lon3): interaction term between SST and Longitude, YR*QT : interaction term between year and quarter,

3. Results and discussion Annual CPUE in number and weight base standardized by GLM is shown in Figure 3 in relative scale with nominal CPUE. In the relative scaled CPUE, average CPUE during the period analyzed was regarded as 1.0. ANOVA result is shown in Table 1 and histogram and QQ-plot of standard residual are shown in Figure 4. Distributions of the standard residual did not show remarkable difference from the normal distribution for both analyses. During the period analyzed, standardized CPUEs for number and weight base decreased until 1993 with some fluctuation, kept stable until 2003, and after that they decreased. The trends of these standardized CPUEs are almost identical with those of last assessment except late 2000s, whose data were updated after that (Figure 5). Trends of quarterly standardized and nominal CPUEs in number for all Atlantic and those divided into two areas are shown in Figure 6. Results of ANOVA and distributions of the standard residual in each analysis are shown in Table 2 and Figure 7, respectively. In both areas and whole Atlantic, seasonal oscillation in standardized CPUE was observed. The historical changes of CPUEs of last assessment and this study are quite similar (Figure 8). References ICCAT, 2013. Report for Biennial Period, 2012-13, Part II, 16pp. Okamoto, H., N. Miyabe and D. Inagake 2001. Interpretation of high catch rates of bigeye tuna in 1977 and 1978

observed in the Japanese longline fishery in the Indian Ocean. IOTC/WPM/01/01: 25p. Okamoto H. 2008. Japanese longline CPUE for bigeye tuna standardized for two area definitions in the Atlantic

Ocean from 1961 up to 2005. Collect. Vol. Sci. Pap. ICCAT, 62(2): 419-439. Okamoto H. K. Satoh. 2008. Japanese longline CPUE for yellowfin tuna (Thunnus albacares) in the Atlantic

Ocean standardized using GLM up to 2006. Collect. Vol. Sci. Pap. ICCAT, 64(3): 960-976. Satoh, K., H. Okamoto, and H. Ijima. 2012. Japanese longline CPUE for yellowfin tuna (Thunnus albacares) in

the Atlantic Ocean using GLM up to 2010. Collect. Vol. Sci. Pap. ICCAT, 68(3) 818-834. Shono, H. and M. Ogura. 2000. The standardized skipjack CPUE including the effect of searching devices, of the

Japanese distant water pole and line fishery in the Western Central Pacific Ocean. Collect. Vol. Sci. Pap. ICCAT, 51(1) 312-328.

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Table 1. Results of ANOVA table for annual CPUE in weight (left) and number (right) base standardization by log-normal error structured model.

Weight Number Year Year

1970-2013 1965-2013

Source DF Type III SS

Mean Square F Value Pr > F R-Square= Source DF

Type III SS

Mean Square F Value Pr > F R-Square=

Model 679 22123.0 32.58 34.81 <.0001 0.39 Model 749 27127.4 36.22 41.27 <.0001 0.44 Error 37527 35128.3 0.94 CV = Error 39547 34705.3 0.88 CV =

Corrected Total 38206 57251.3 25.42

Corrected

Total 40296 61832.7 455.28

year 43 2992.4 69.6 74.34 <.0001 year 48 664.8 13.9 15.78 <.0001

month 11 647.9 58.9 62.92 <.0001 month 11 96.9 8.8 10.03 <.0001 area 2 4279.5 2139.7 2285.84 <.0001 area 2 81.3 40.7 46.34 <.0001 nhfcl 4 411.1 102.8 109.81 <.0001 nhfcl 4 151.3 37.8 43.11 <.0001 sst 1 5428.5 5428.5 5799.19 <.0001 sst 1 67.4 67.4 76.85 <.0001

sst2 1 2980.9 2980.9 3184.45 <.0001 sst2 1 93.3 93.3 106.36 <.0001 sst3 1 161.3 161.3 172.32 <.0001 sst3 1 137.3 137.3 156.48 <.0001 ML 1 21.8 21.8 23.32 <.0001 ML 1 1.1 1.1 1.26 0.2609 BL 1 39.5 39.5 42.22 <.0001 BL 1 4.8 4.8 5.53 0.0187

year*area 86 1434.3 16.7 17.82 <.0001 year*area 96 1342.2 14.0 15.93 <.0001 year*month 473 2355.5 5.0 5.32 <.0001 year*month 528 2352.6 4.5 5.08 <.0001 area*month 22 458.8 20.9 22.28 <.0001 area*month 22 263.9 12.0 13.67 <.0001 area*nhfcl 8 92.6 11.6 12.36 <.0001 area*nhfcl 8 67.3 8.4 9.59 <.0001 sst*month 11 161.4 14.7 15.68 <.0001 sst*month 11 93.1 8.5 9.64 <.0001 sst*area 2 313.4 156.7 167.37 <.0001 sst*area 2 164.4 82.2 93.66 <.0001 sst*nhfcl 4 208.2 52.1 55.61 <.0001 sst*nhfcl 4 278.0 69.5 79.18 <.0001

ML *nhfcl 4 125.5 31.4 33.52 <.0001 ML *nhfcl 4 45.2 11.3 12.86 <.0001 BL *nhfcl 4 10.4 2.6 2.77 0.0255 BL *nhfcl 4 9.7 2.4 2.76 0.0261

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Table 2. Results of ANOVA table for quarterly CPUE standardization by log-normal error structured model for each of two Multifan-CL areas, West and East Atlantic and all Atlantic Ocean.

WEST EAST ALL

Source DF Type III SSMean

SquareF Value Pr > F R-Square= Source DF Type III SS

MeanSquare

F Value Pr > F R-Square= Source DF Type III SSMean

SquareF Value Pr > F R-Square=

Model 270 14499.04 53.70 82.66 <.0001 0.57 Model 268 29250.91 109.15 117.63 <.0001 0.46 Model 275 42260.71 153.68 172.17 <.0001 0.47Error 16670 10830.30 0.65 CV= Error 36890 34230.04 0.93 CV= Error 53925 48133.25 0.89 CV=

CorrectedTotal

16940 25329.34 119.90Corrected

Total37158 63480.95 -278.06

CorrectedTotal

54200 90393.96 3322.99

yr 48 615.64 12.83 19.74 <.0001 yr 48 1564.23 32.59 34.78 <.0001 yr 48 1352.69 28.18 31.57 <.0001qt 3 39.10 13.03 20.06 <.0001 qt 3 352.36 117.45 125.35 <.0001 qt 3 239.79 79.93 89.55 <.0001lt 1 21.18 21.18 32.6 <.0001 lt 1 729.94 729.94 778.99 <.0001 lt 1 85.38 85.38 95.66 <.0001ln 1 35.26 35.26 54.27 <.0001 ln 1 0.24 0.24 0.26 0.6102 ln 1 172.00 172.00 192.7 <.0001lt2 1 5.99 5.99 9.22 0.0024 lt2 1 22.25 22.25 23.75 <.0001 lt2 1 246.56 246.56 276.23 <.0001ltln 1 199.34 199.34 306.82 <.0001ln2 1 31.54 31.54 48.54 <.0001 ln2 1 75.47 75.47 80.54 <.0001 ln2 1 177.17 177.17 198.49 <.0001lt3 1 143.80 143.80 221.33 <.0001 lt3 1 57.02 57.02 60.86 <.0001 lt3 1 77.62 77.62 86.96 <.0001

lt2ln 1 129.95 129.95 200.03 <.0001 lt2ln 1 118.53 118.53 132.79 <.0001ltln2 1 57.83 57.83 61.72 <.0001 ltln2 1 40.81 40.81 45.73 <.0001

ln3 1 26.79 26.79 41.23 <.0001 ln3 1 30.95 30.95 33.03 <.0001 ln3 1 27.31 27.31 30.6 <.0001nhfcl 4 65.11 16.28 25.05 <.0001 nhfcl 4 723.86 180.97 193.13 <.0001 nhfcl 4 707.96 176.99 198.29 <.0001sst 1 32.08 32.08 49.37 <.0001 sst 1 59.66 59.66 63.67 <.0001 sst 1 185.45 185.45 207.77 <.0001sst2 1 61.28 61.28 94.32 <.0001 sst2 1 85.47 85.47 91.21 <.0001 sst2 1 191.88 191.88 214.97 <.0001sst3 1 64.87 64.87 99.85 <.0001 sst3 1 126.34 126.34 134.83 <.0001 sst3 1 227.77 227.77 255.18 <.0001ml 1 0.71 0.71 1.09 0.2958 ml 1 16.15 16.15 17.24 <.0001 ml 1 9.90 9.90 11.09 0.0009bl 1 2.59 2.59 3.99 0.0457 bl 1 0.20 0.20 0.21 0.6461 bl 1 4.18 4.18 4.68 0.0305

yr*qt 144 791.57 5.50 8.46 <.0001 yr*qt 144 1204.85 8.37 8.93 <.0001 yr*qt 144 1386.56 9.63 10.79 <.0001sst*qt 3 109.92 36.64 56.39 <.0001 sst*qt 3 381.73 127.24 135.79 <.0001 sst*qt 3 274.83 91.61 102.63 <.0001

sst*nhfcl 4 106.61 26.65 41.02 <.0001 sst*nhfcl 4 850.93 212.73 227.03 <.0001 sst*nhfcl 4 872.71 218.18 244.43 <.0001ml*nhfcl 4 9.58 2.39 3.69 0.0053 ml*nhfcl 4 73.83 18.46 19.7 <.0001 ml*nhfcl 4 80.46 20.12 22.54 <.0001bl*nhfcl 4 8.66 2.16 3.33 0.0098 bl*nhfcl 4 14.13 3.53 3.77 0.0045 bl*nhfcl 4 8.47 2.12 2.37 0.05

lt*qt 3 231.95 77.32 119.01 <.0001 lt*qt 3 48.89 16.30 17.39 <.0001 lt*qt 3 573.79 191.26 214.28 <.0001lt2*qt 3 155.23 51.74 79.64 <.0001 lt2*qt 3 64.12 21.37 22.81 <.0001 lt2*qt 3 130.74 43.58 48.82 <.0001lt3*qt 3 237.52 79.17 121.86 <.0001 lt3*qt 3 428.15 142.72 159.89 <.0001ln*qt 3 15.78 5.26 8.09 <.0001 ln*qt 3 56.47 18.82 20.09 <.0001 ln*qt 3 127.02 42.34 47.43 <.0001ln2*qt 3 11.58 3.86 5.94 0.0005 ln2*qt 3 75.82 25.27 26.97 <.0001 ln2*qt 3 115.57 38.52 43.16 <.0001ln3*qt 3 12.33 4.11 6.33 0.0003 ln3*qt 3 129.35 43.12 48.31 <.0001lt*nhfcl 4 39.80 9.95 15.32 <.0001 lt*nhfcl 4 56.17 14.04 14.99 <.0001 lt*nhfcl 4 76.83 19.21 21.52 <.0001

lt2*nhfcl 4 221.72 55.43 59.15 <.0001 lt2*nhfcl 4 247.42 61.86 69.3 <.0001lt3*nhfcl 4 67.84 16.96 26.11 <.0001 lt3*nhfcl 4 10.38 2.59 2.77 0.0257 lt3*nhfcl 4 49.09 12.27 13.75 <.0001ln*nhfcl 4 71.09 17.77 27.35 <.0001 ln*nhfcl 4 144.73 36.18 38.61 <.0001 ln*nhfcl 4 169.28 42.32 47.41 <.0001ln2*nhfcl 4 57.13 14.28 21.98 <.0001 ln2*nhfcl 4 10.45 2.61 2.79 0.0249 ln2*nhfcl 4 105.01 26.25 29.41 <.0001ln3*nhfcl 4 43.02 10.76 16.56 <.0001 ln3*nhfcl 4 12.82 3.21 3.42 0.0084 ln3*nhfcl 4 78.01 19.50 21.85 <.0001

lt*sst 1 63.68 63.68 98.02 <.0001 lt*sst 1 30.65 30.65 32.71 <.0001 lt*sst 1 170.10 170.10 190.57 <.0001lt2*sst 1 18.44 18.44 28.38 <.0001 lt2*sst 1 30.65 30.65 32.71 <.0001 lt2*sst 1 304.97 304.97 341.67 <.0001

lt3*sst 1 176.91 176.91 188.8 <.0001 lt3*sst 1 128.50 128.50 143.96 <.0001ln*sst 1 37.26 37.26 57.35 <.0001 ln*sst 1 6.19 6.19 6.61 0.0101 ln*sst 1 102.99 102.99 115.39 <.0001ln2*sst 1 30.14 30.14 46.39 <.0001 ln2*sst 1 184.58 184.58 196.99 <.0001 ln2*sst 1 91.06 91.06 102.02 <.0001ln3*sst 1 24.96 24.96 38.42 <.0001 ln3*sst 1 58.48 58.48 62.41 <.0001 ln3*sst 1 16.74 16.74 18.76 <.0001

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Figure 1. Area definition (west and east are divided by pink dashed line) which is used in yellowfin stock assessment using Multifan-CL (from http://www.iccat.int/Data/ICCATMaps2011.pdf).

Figure 2. Sub-area definitions used for Japanese longline CPUE standardization, which is the same as that in last yellowfin assessment (Okamoto and Satoh, 2008; Satoh et al., 2012).

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Figure 3. Standardized (solid line) and nominal (open circle) annual CPUE in number (top) and weight (bottom) base expressed in relative scale in which the average from 1965 (1970) to 2013 is 1.0.

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Figure 4. Overall histogram and QQ-plot of standard residuals from the GLM analyses for annual CPUE in number (top) and weight (bottom) base applying the final model in this study.

Figure 5. Comparison of standardized CPUE between last assessment (dashed line) and this study (solid line) in number (upper) and weight (bottom) base.

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Figure 6. Number based standardized (solid line) and nominal (open circle) quarterly CPUEs for West, East and all Atlantic Ocean relative scale.

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Figure 7. Overall histogram and QQ-plot of standard residuals from the GLM analyses for quarterly CPUE in West (top), East (middle) and all (bottom) Atlantic base applying the final model in this study.

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Figure 8. Comparison of standardized CPUE between last assessment (dashed line) and this study (solid line) in West (upper), East (middle) and all (bottom) Atlantic.

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Appendix

Figure 1. Geographical distribution of fishing effort for Japanese longline fishery in recent years.

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Figure 2. Geographical distribution of yellowfin catch by Japanese longline fishery in recent years.

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