SCRS/24/12 Col. Vol. Sci. Pap. ICCAT, 58(3): 1135-1149 (25) TRENDS IN STANDARDIZED FOR SHORTFIN MAKO SHARK CAUGHT BY THE JAPANESE LONGLINE FISHERY IN THE ATLANTIC OCEAN Yasuko Senba 1 and Yukio Takeuchi 2 SUMMARY The of shortfin mako shark (Isurus oxyrinchus) was estimated from the data of the Japanese tuna longline fishery that operated in the Atlantic Ocean from 1971 to 23 and the server program conducted from 1995 to 23. We extracted the data with a high proportion of shortfin mako shark catch from the Japanese tuna longline data for the standardization of. As a result, the has gradually decreased from 1971 to 23 in the entire Atlantic Ocean. RÉSUMÉ La standardisée du requin taupe bleue (Isurus oxyrinchus) a été estimée à partir des données de la pêcherie palangrière thonière du Japon qui opérait dans l océan Atlantique de 1971 à 23 et les programmes d servateurs menés de 1995 à 23. Aux fins de la standardisation de la, nous avons extrait les données avec une forte proportion de prises de requins taupes bleues à partir des données palangrières thonières japonaises. En conséquence, la a progressivement diminué de 1971 à 23 dans l ensemble de l Atlantique. RESUMEN Se estimó la estandarizada del marrajo dientuso (Isurus oxyrinchus) partiendo de los datos de la pesquería japonesa de túnidos al palangre que faenó en el océano Atlántico, desde 1971 hasta 23, y de un programa de servadores que se desarrolló desde 1995 hasta 23. Para estandarizar la, se extrajeron los datos con una fuerte proporción de captura de marrajo dientuso de los datos de la flota japonesa de pesca de túnidos al palangre. Como resultado, la mostró una tendencia gradualmente decreciente desde 1971 hasta 23 en todo el océano Atlántico. 1 Department of Aquatic Bioscience, College of Agriculture, University of Tokyo. 2 National Research Institute of Far Seas Fisheries, Fisheries Research Agency. 1135
1. Introduction Shortfin mako shark Isurus oxyrinchus, is a common, extremely active, offshore, littoral and epipelagic species found in tropical and warm-temperate seas (Compagno 1984). Though this shark is one of main by-catch species caught by the Japanese tuna longline fishery in the Atlantic Ocean, there were few accurate catch data on this species until the 199s. There are increasing concerns about the impact of longline fishery to animals which are not targeted. Pelagic sharks are no exception and it is necessary to assess the trends of abundance of pelagic sharks. Since the Japanese longline fishery has widely operated in the whole Atlantic Ocean, its fishery statistics would be one of the most valuable sources to assess the stock status of the concerned shark. In this report, we estimated the trends of (catch per unit effort in number) of shortfin mako shark from data of the Japanese tuna longline fishery that operated in the Atlantic Ocean from 1971 to 23 (hereinafter referred to as logbook data ), using and arranging the method devised by Nakano and Honma (1996). 2. Materials and methods 2.1 The data source The Japanese server data for 1995-23 (Senba and Nakano 24) and logbook data for 1971~23 were used for the analysis. The areas were defined based on the spacial distribution of logbook data (Figure 1). For standardizing of shortfin mako shark, data from operations without shark catch or data with too many sharks (above 2 individuals of sharks per one operation: this baseline was decided based on the server data) or too small numbers of hooks (below 1 hooks per one operation) was excluded from the analysis in the logbook data. The Japanese logbook system was revised from 1993 and catch record of sharks has been separated by species: blue, porbeagle, shortfin mako and other sharks, and it was revised again to include oceanic whitetip, thresher sharks and other sharks in 1997. 2.2 Specification of reporting rate of shortfin mako shark According to server data (Senba and Nakano 24), shortfin mako sharks occupy relatively small proportion to total shark catch unlike the case of blue shark. This proportion is not due to nonreporting but reflects proportion in the actual total catch. To extract real and accurate shortfin mako catch and effort from logbook data, we have to select appropriate data that reflects real situation. For extraction of appropriate data, in the case of blue shark, Nakano and Honma (1996) devised the reporting rate, which is defined as percentage of operations with shark (all species) catch to total number of operations in each cruise. It is suggested that this index reflects the frequency that blue shark is caught. In the case of shortfin mako shark, Shiode and Nakano (21) showed that shortfin mako shark dominates in reporting rate data while proportion of blue shark increases in higher reporting rates. Nakano (21) described that there is some trade-off prlems how to select appropriate reporting rate. So, in order to extract real and accurate shortfin mako catch and effort data, we don t have to choose data with high reporting rate, but choose data that fell in intermediate range of reporting rate. Besides their (shortfin mako) low proportion to total shark catch described above, the percentage would vary depending on areas as indicated in the summary of server data by Senba and Nakano (24). In the summary, the of shortfin mako shark varied largely among areas. Therefore, it is suggested that appropriate choice of reporting rate in abundant area may be higher than other less abundant area. Reflecting these servations, we attempt to specify the reporting rate of this species by area. We specified the reporting rate having shortfin mako shark as majority of catch using the server data by area. The procedure is as follows. 1. We calculated the nominal of shortfin mako shark at each by each area using server data. Those values were used as bases to determine the reporting rates of each area. 2. We separated the logbook data in each area in to 1 sets of reporting rate, that is, the data with reporting rates of -1%, that with 1-2% and so on. 3. In each area, we compared the two calculated from logbook data specified with selected reporting rates, and server data by with each intervals. 4. The most suitable reporting rate was decided such that the difference between s from the server and logbook data becomes minimum. In that process, some intervals were integrated so as that the number of data becomes sufficient to run the model (e. g. -1%, 1-4%). 1136
5. As the example, this process in area 1 is shown in Appendix 2. After comparison of each interval and some combined intervals, 1~4% was adopted in area 1. For sensitivity test, the data whose reporting rate is less than 2%, 3%, 4% and 1~4% through all areas were used. In addition, the data with reporting rates of 11~3% recommended by Clark and Nakano (24) was also considered. 2.3 Standardization Standardized was calculated using GENMOD procedure of SAS8.2 to eliminate some biases by change of fishing ground and fishing s. For standardization, was calculated by operation. We used the area strata as defined above. Numbers of hooks between baskets were classified into two categories (3-9 hooks and 1-24 hooks). We calculate the of shortfin mako shark by three geographical units; the north, south and overall Atlantic Ocean. The north unit includes area 1-3 and the south unit includes area 4-6. Figure 2 shows the frequency of catch number of shortfin mako shark per one operation from server data. It indicates excessive number of zero with small number of high catch, As shortfin mako shark was seemed to show distribution with high concentration to zero, we believe shortfin mako catch distributes as negative binominal distribution as error distribution. We selected catch number (total shark) as response variable with hook as offset because negative binominal takes count as response. The model for standardizing is as follows. Catch = hook*exp ( + + area + gear + *) For each covariate represents, : effect of (1971~23), : effect of. (Jan~Mar., Apr.~Jun., Jul.~Sep., Oct.~Dec.) area: effect of area. gear: effect of fishing depth *: the two-way interaction between and. With regard to area 1 and area 6, the number of logbook data was so small that it couldn t work as independent area in running the program, so the data of area 1 and area 6 were integrated into area 2 and area 5, respectively. is derived by the definition. catch = = exp( + + area + gear + hook * ) 3. Results and discussion 3.1 Reporting rates of shortfin mako shark The reporting rates adopted by each area are as follows. Area 1: 1~4% Area 2: ~3%, Area 3: ~2%, Area 4: -2%, Area 5: -3%, Area 6: 1-4%. Figure 3 demonstrates how our criteria works well out of operations with sharks by in the extracted data from 1994~23. In our data, if there are shark catch in operation, almost 8% of data are shortfin mako shark. 3.2 Standardization Table 1 shows number of servations in each by geographical unit.type 3 analysis revealed that all main effects (except gear) and interaction of and are significant in the whole Atlantic(Table 2). Table 3 shows annual with and 95% confidence intervals. Figure 4 shows the for the whole, North and South Atlantic. 95% confidence intervals are shown in addition. When running the model for whole Atlantic, we excluded gear effect because gear was not 1137
significant. The results suggest the was slightly and gradually declining from 1971 in whole Atlantic Ocean. In the North, the decreasing trend was similar to whole Atlantic until around 199, but the fluctuations became larger than whole Atlantic after 1993. In contrast to the North, the trend in the South was opposite from the North in 1975~198 but the after 1981 was gradually decreasing. The trend after 199 was flat. Sensitivity tests of data sets were done with the data of 5 different types of reporting rate (Figure 5). These reporting rates were chosen to cover the various range of reporting rates. For each data set, reporting rate was applied to all areas and data was extracted. In all cases, the until 1993 was decreasing, but showed different trend in some cases after 1993. The trend of -2%was similar to that of our method. The trend of in -3% and 11-3% after 1993 showed some fluctuations. The trend of in -4% and 1-4% began to increase after 1993. These results showed the trend, especially after 1993, changed depending on the reporting rate. To examine which reporting rate is most appropriate, the proportion of data with shortfin mako shark to the data with sharks in 4 reporting rate (-3%, -4%, 1-4% and 11-3%) was compared with that of our method (Appendix 3). In the case of -4% and 1-4%, the proportion was than our method and the difference was larger than other 2 reporting rates. This means that the data extracted using these reporting rates contain other sharks and this contamination makes the trend different. In the case of -3% and 11-3%, the proportion was as high as our method. The shortfin mako shark is one of the sub-target species for Japanese tuna longline fisheries and its market value is among the highest of the pelagic sharks caught in the longline fisheries in Japan. Considering that their biological information such as growth, reproduction and distribution is scare, it is necessary to pay and keep more attention to its stock status. Moreover, the further research activities on board and collecting more information are vital. References COMPAGNO, L.J.V. 1984. FAO species catalogues. Vol 4. Sharks of the world. An annotated and illustrated catalogue of the shark species known to date, Parts 1 and 2. FAO Fish. Synopsis 125, Vol. 4, parts 1 and 2, 655p. FAO, Rome. CLARKE, S. and H. Nakano. 24. Catch and Time Series for Shortfin Mako (Isurus oxyrinchus) in the Atlantic Ocean using Japanese Logbook Data and an Extension of Methods Developed for Blue Shark(Prionace glauca). Document to be submitted to the inter-sessional Meeting of the ICCATT Sub-Committee on By-catch, Tokyo, Japan, June 24. NAKANO, H. and M. Honma. 1996. Historical of pelagic sharks caught by the Japanese longline fishery in the Atlantic Ocean. ICCAT CVSP Vol. XLVI (4): 393-398. NAKANO, H. 21. Preliminary results of Standardized for shortfin mako shark caught by Japanese longline fishery in the Atlantic Ocean. ICCAT CVSP Vol. LIV 22, SCRS/21/88 11pp. SENBA, Y. and H. Nakano. 24. Summary of species composition and nominal of pelagic sharks based on server data from the Japanese longline fishery in the Atlantic Ocean from 1995 to 23. Document to be submitted to the inter-sessional Meeting of the ICCATT Sub-Committee on By-catch, Tokyo, Japan, June 24. SHIODE, D. and H. Nakano. 21. Verification of shark catch data of the logbook records in Japanese longline fishery in comparison with server reports. Document submitted to the Shark Data Preparation Meeting of ICCAT. 1138
Table 1. Number of servations by geographic unit in each. Year North South Entire Atlantic 1971 1,815 237 2,52 1972 1,264 241 1,55 1973 715 275 99 1974 1,6 56 1,116 1975 1,867 55 1,919 1976 1,221 117 1,323 1978 833 78 911 1978 544 135 679 1979 632 295 845 198 1,195 719 1,878 1981 1,642 82 2,462 1982 1,36 2,45 3,337 1983 1,197 1,6 2,246 1984 1,22 1,435 2,454 1985 1,237 2,257 3,494 1986 1,752 1,579 3,331 1987 1,596 78 2,278 1988 1,7 1,412 3,112 1989 1,571 2,281 3,852 199 1,996 3,767 5,616 1991 2,38 2,917 4,851 1992 1,841 2,558 4,233 1993 2,171 4,846 6,932 1994 2,711 8,744 11,453 1995 2,667 1,97 12,76 1996 4,117 9,773 13,881 1997 3,642 6,483 1,124 1998 3,31 6,155 9,456 1999 2,969 6,394 9,337 2 3,726 7,614 11,281 21 3,147 4,27 7,416 22 2,68 2,942 5,1 23 1,115 3,124 4,239 1139
Table 2. Outputs of Type 3 analysis for the models selected. Entire Atlantic LRStatistics For Type 3 Analysis Source DF Chi-Square Pr>Chisq yr 32 168.5 <.1 area 3 411.96 <.1 yr*se 96 648.25 <.1 gear 1 1.3.315 North Atlantic LR Statistics For Type 3 Analysis Source DF Chi-Square Pr>Chisq yr 32 22.22 <.1 se 3 19.69.2 area 1 271.59 <.1 yr*se 96 56.14 <.1 gear 1 14.41.1 South Atlantic LR Statistics For Type 3 Analysis Source DF Chi-Square Pr>Chisq yr 32 219.75 <.1 se 3 137.24 <.1 area 1 14.16 <.1 114
Table 3. Annual, with and 95% confidence intervals for shortfin mako shark from the model selected in each unit. Year 1971 1972 1973 1974 1975 1976 1977 1978 1979 198 1981 1982 1983 1984 1985 1986 1987 1988 1989 199 1991 1992 1993 1994 1995 1996 1997 1998 1999 2 21 22 23 North Atlantic: South Atlantic: Entire Atlantic: Lower Upper Lower Upper Lower Upper.1158.974.1376.798.52.1223.917.788.169.1178.966.1437.996.662.1499.958.84.1142.1258.935.1691.17.695.1459.943.766.116.114.797.1289.152.463.2392.81.644.995.1125.946.1338.344.17.11.842.715.992.1136.94.1373.629.328.127.871.727.143.1288.123.1622.275.99.763.938.756.1163.176.132.224.466.25.867.1225.968.155.126.781.1347.475.313.721.747.587.952.84.663.165.733.576.932.67.567.791.949.783.1152.1155.935.1426.857.748.981.1171.966.1421.769.664.891.791.699.895.827.668.124.673.546.83.691.588.812.728.449.1181.571.472.69.621.512.754.719.51.114.724.627.835.721.62.838.681.559.829.816.692.963.663.58.757.693.56.857.865.676.116.647.548.764.619.511.751.639.531.769.569.495.655.712.584.869.82.697.922.739.651.838.688.553.855.678.64.76.686.62.759.735.594.99.66.579.752.653.585.729.711.582.87.567.491.655.625.554.74.92.752.182.596.538.661.73.645.767.624.538.724.593.551.638.65.69.695.967.837.1117.479.446.515.598.56.638.711.628.85.546.58.588.66.569.645.82.79.96.533.487.583.626.583.673.696.67.8.57.464.555.574.532.618.88.759.12.545.5.595.745.696.798.736.653.83.529.488.573.633.592.676.665.579.763.679.612.753.652.599.71.783.666.92.474.416.54.619.558.687.54.386.657.69.616.774.612.54.742 1141
Figure 1. Area classification used for the analysis for shortfin mako shark. 1142
Figure 2. The distribution of each catch number of shortfin mako shark calculated using server data. Figure 3. The ratio of shortfin mako shark in the data used in the analysis. 1143
Entire Atlantic Ocean.18.16.14.12.1.8.6.4.2 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 21 23 North Atlantic Ocean.25.2.15.1.5 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 21 23 South Atlantic Ocean.3.25.2.15.1.5 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 21 23 Figure 4. Standardized and 95% confidence intervals of shortfin mako shark. The data of 23 in the North is small and the results are preliminary. 1144
-2%.2.18.16.14.12.1.8.6.4.2 1971 1974 1977 198 1983 1986 1989 1992 1995 1998 21-3%.2.18.16.14.12.1.8.6.4.2 1971 1974 1977 198 1983 1986 1989 1992 1995 1998 21-4%.25.2.15.1.5 1971 1974 1977 198 1983 1986 1989 1992 1995 1998 21 1-4%.25.2.15.1.5 1971 1974 1977 198 1983 1986 1989 1992 1995 1998 21 11-3%.25.2.15.1.5 1971 1974 1977 198 1983 1986 1989 1992 1995 1998 21 Figure 5. Sensitivity test of of shortfin mako shark using data by 5 type of reporting rate. 1145
Appendix 1. The flow chart of process used in the analysis. Fishery statistics from 1971-23(catch number, effort) 1971-1993: there is only one entry as "total sharks" Extract the data corresponding to shortfin mako shark Concept Extract data of shortfin mako shark referring to "reporting rate" method used in the blue shark Reporting rate Number of operations with sharks (all species combined) Total number of operations in each cruise Affected by the frequency that shark is caught in one cruise Best reporting rate with certain shark as majority in catch varies depending on the species of sharks Ex.Blue shark caught in almost all operations: best reporting rate becomes high. How about shortfin mako sharkmaybe than blue shark because it is rarely caught. The process of determination of the reporting rate by area 1 Calculating shortfin mako by in each area using server data Use as reference for determining reporting rate by each area 2 (1)Calculate reporting rate by each cruise from logbook data (2)Divide data into each area (3)Calculate by using 1% interval data of reporting rate for each area exarea 3 data with -1% reporting rate(catch number, hooks) calculate by data with 1-2% reporting rate(catch number, hooks) calculate by data with 2-3% reporting rate(catch number, hooks) calculate by 3 Compare 1 and 2-(3) in each area 4 Determine the area-specific reporting rate such that the residual sum of square between server and logbook by become minimum. When the number of data is too small to run the model, we combined some intervals and decided the reporting rate. 1146
Appendix 2-1. Comparison of the between data of server data and logbook data extracted in each 1% reporting rate intervals in area 1. The results of the intervals with 1% are shown (-1%, 1-2%, 3-4%, 4-5%, 5-6%, 6-7%, 8-9%, 9-1%). The results of 1-2%, 2-3%, and 3-4% indicate a similar trend with that of the server data. area1:9% area1:4-5%.25.2.15.1.5 9%.2.18.16.14.12.1.8.6.4.2 4-5% area1:8-9% area1:3-4%.35.4.3.35.25.3.2.15.1.5 8-9%.25.2.15.1.5 3-4% area1:7-8% area1:2-3%.12.4.1.8.6.4 7-8%.35.3.25.2.15 2-3%.2.1.5 area1:6-7% area1:1-2%.7.4.6.35.5.4.3.2.1 6-7%.3.25.2.15.1.5 1-2% area1:5-6% area1:-1%.25.25.2.2.15.1 5-6%.15.1-1%.5.5 1147
Appendix 2-2. Comparison of the of data of server data and logbook data extracted in each 1% reporting rate intervals in area 1. The results of combined intervals are shown (1-3%, 1-4%, 2-4%). Considering the residual sum of square and the number of data, the 1-4% reporting rate was adopted in area 1. area1:1-3%.35.3.25.2.15.1.5 1-3% area1:1-4%.35.3.25.2.15.1.5 1-4% area1:2-4%.35.3.25.2.15.1.5 2-4% 1148
Appendix 3a-d. Comparison of the ratio of operations with shortfin mako shark to operations with sharks. The high proportion means that the majority of the data contain the shortfin make shark catch. Each figure indicates data extracted with a) -3% reporting rate, b) -4% reporting rate, c) 1-4% reporting rate, and d) 11-3% reporting rate. -3% the proportion of data wit shortfin mako shark to da with sharks (%) 1 9 8 7 6 5 4 3 2 1 our method -3% reporting category 1994 1995 1996 1997 1998 1999 2 21 22 23-4% the proportion of data wi shortfin mako shark to da w ith sh ark s ( % ) 1 9 8 7 6 5 4 3 2 1 1994 1995 1996 1997 1998 1999 2 21 22 23 our method -4% reporting category 1-4% the proportion of data with shortfin mako shark to data wi sharks (%) 1 9 8 7 6 5 4 3 2 1 1994 1995 1996 1997 1998 1999 2 21 22 23 our method 1-4% reporting category 11-3% the proportion of data with shortfin m ako shark to data with sharks ( % ) 1 8 6 4 2 our method 11-3% reporting category 1994 1995 1996 1997 1998 1999 2 21 22 23 1149