Size distribution of southern bluefin tuna (Thunnus maccoyii) by depth on their spawning ground.
Three types of boats operate in the Indonesian fishery (Davis et al., 1995). Deep longline boats (generally [is greater than] 50 tonnes) use multifilament mainlines that are set deep. Mini ([is less than] 20 tonnes gross weight) and regular longline boats (20-50 tonnes) use mono filament mainlines and generally make shallow longline sets. However, the depth at which the lines fish varies considerably because they carry live or frozen baits according to different phases of the moon, and both the number of hooks and their placement on the catenary between floats changes. Prediction of fishing depth based on catenary geometry, line length, and distance between floats (Yoshihara, 1954) differs significantly from actual depth fished (Saito, 1973; Nishi, 1990; Boggs, 1992). In this fishery, the number of hooks between floats is recorded (Davis et al., 1999), but this parameter alone is a poor indicator of the depth of fishing.
Using hook timers, Boggs (1992) determined depth at the time of hooking. He found that bigeye catch rates peaked at 360-400 m and 8-10 [degrees] C (temperature), but were still high at 200-360 m. Bigeye tuna have a shallower distribution at night (modal depth of 80 m) than during the day (220 m) (Holland et al., 1990). However, on the SBT spawning ground, longline setting starts at about 06:00 h and hauling starts at about 14:00 h (Davis(4)); therefore most bigeye tuna would be caught during the day when they are deeper.
The preferred depths of bigeye tuna vary regionally depending on thermocline structure, but lie within 10 [degrees] and 15 [degrees] C (Hanamoto, 1986; Mohri et al., 1996) and where [O.sub.2] [is greater than] 1 mL/L (Hanamoto, 1986). These temperatures occur at 180-400 m on the SBT spawning ground (Yukinawa and Miyabe, 1984; Yukinawa and Koido, 1985; Yukinawa, 1987). Yellowfin tuna, on the other hand, are found in warmer waters and are mainly caught at depths of 40-230 m (Suzuki and Kume, 1982; Yang and Gong, 1988; Boggs, 1992). The proportion of bigeye to yellowfin tuna might therefore be used as a proxy for the depth of fishing in the Indonesian longline fishery. In our study we used this depth proxy to investigate whether there is size partitioning by depth of SBT on the spawning ground, and what underlying biological processes might be involved.
We used catch data obtained from 15,882 Indonesian longline landings monitored at export processing factories at the Port of Benoa, Bali, from 1992 to 1999 (Davis et al., 1995; 1999). About 65% of the SBT in these landings were measured (fork length in cm). Fewer high-grade export tuna (30%) were measured than low-grade tuna (89%) because the former were immersed in an ice slurry immediately after grading, leaving little opportunity for measurement. Grading, however, was not dependent on size. There was no significant difference in the length distributions of 102 export tuna and 102 low-grade tuna from 20 landings in which all tuna were measured (Kolmogorov-Smirnov two sample test, P=0.22).
For each landing we calculated a bigeye (BE) tuna index as
BE index Weight of bigeye/(weight of bigeye + weight of yellowfin).
This equation was used as a proxy for the depth of fishing, with an index of 1 = deep and 0 = shallow. Landings were grouped into one of five levels of this index, i.e. 0-0.2, 0.2-0.4, etc., and then the length-frequency distributions of SBT within landings at each level were compared.
In order to investigate patterns of distribution of fish size with depth, we grouped fish into 10-cm length classes and calculated their relative abundance across the five levels of the BE index. Because of uneven sampling with depth, the number of fish in each BE index were first weighted inversely by the effort (number of landings) at each level of the index.
The ovaries of 475 SBT were collected during monitoring from 1992 to 1995. These were examined histologically for evidence of recent or imminent spawning (Farley and Davis, 1998). Spawning fish were classed as those having spawned less than 24 hours previously (postovulatory follicles present in ovary), or about to spawn that day (ovaries containing oocytes at migratory nucleus or hydrated stage). Postspawning SBT were identified by the proportion and type of atretic oocytes present (see details in Farley and Davis, 1998). Nonspawning SBT were mature fish on the spawning ground that were neither spawning nor postspawning individuals.
Chi-square contingency analyses were used to test for differences in length classes of SBT, and for differences in the proportion of spawning and nonspawning SBT at different levels of the BE index (the proxy for depth).
The length-frequency distribution of SBT caught at five levels of the BE index shows a trend of increased proportions of small SBT with an increase in this index (Fig. 1). Fish [is less than] 165 cm ranged from 3.3% of catch at an index [is less than] 0.2 to 15.7% at a index [is greater than] 0.8.
Chi-square contingency analyses indicated significant differences in the proportion of length classes with the BE index (Table 1, Fig. 2). The chi-square test ignores the ordered and continuous nature of the categories, making it less powerful than it could be. However, we obtained a highly significant test result despite this weakness, reflecting how strong the size-with-depth patterns are. The smaller length classes (150-169 cm) were better represented in the deep catches (BE index [is greater than] 0.8) than they were in the shallow catches (BE index [is less than] 0.2). Conversely, the larger length classes (190-209 cm) were better represented in the shallow catches (BE index [is less than] 0.2) than they were in the deep catches (BE index [is greater than] 0.8). Smaller fish were more likely to be caught in the deepest sets, which target bigeye, whereas the bigger fish were more likely to be caught in the shallow sets. Significantly, there is a systematic change in depth distribution with size over the whole size range of SBT that occur on the spawning ground. This pattern is very clear when comparing the proportion of fish caught in shallow (BE index of 0.0-0.2 or 0.0-0.4) versus deep (BE index of 0.8-1.0 or 0.6-1.0) sets for each length class. The proportion of SBT caught at the surface increases with size (Fig. 3).
Table 1 Distribution (%) of length groups (10-cm intervals) of southern bluefin tuna across bigeye tuna (BE) indices (Pearson chi-square=516, n=8416, df=24, <0.001). BE indices Length (cm) 0.0-0.2 0.2-0.4 0.4-0.6 0.6-0.8 0.8-1.0 140-149 13.3 6.7 13.3 26.7 40.0 150-159 2.8 10.1 17.0 18.6 51.4 160-169 8.7 15.4 19.5 24.5 31.8 170-179 12.7 25.7 20.8 20.8 20.0 180-189 17.9 26.6 18.5 19.3 17.8 190-199 27.0 23.7 18.9 14.7 15.7 200-209 35.9 21.8 19.6 10.9 12.0 No. of landings 2100 3585 3876 4421 1900 Length (cm) Total no. Total 140-149 15 100.0 150-159 247 100.0 160-169 1019 100.0 170-179 2442 100.0 180-189 3520 100.0 190-199 990 100.0 200-209 184 100.0 No. of landings
The proportion of spawning and nonspawning fish (based on the subset of histological data) was then determined for each level of BE index (Fig. 4). Chi-square contingency analyses indicated significant differences in the proportions (Table 2). Spawning fish were better represented in the shallow catches than in the deep catches. Conversely, nonspawning fish were better represented in the deep catches than in the shallow catches. There were insufficient numbers of SBT in the smaller size classes (only seven SBT [is less than] 160 cm) to use the histology data to examine directly the relation between size and proportion of spawning fish or spawning frequencies. Because spent fish were rarely encountered on the spawning ground, Farley and Davis (1998) concluded that they move south soon after spawning. However, the two spent fish detected were in landings with a BE index [is greater than] 0.9.
Table 2 Percentage of spawning and nonspawning southern bluefin tuna caught at different bigeye indices (Pearson chi-square=24.1, n=326, df=4, P<0.001). BE index 0.0-0.2 0.2-0.4 0.4-0.6 0.6-0.8 0.8-1.0 Spawning 85.5 71.4 80.8 56.4 56.3 Nonspawning 14.5 28.6 19.2 43.6 43.7 Total no. Spawning 227 Nonspawning 99
There is a systematic change in depth distribution with size over the whole size range of SBT caught on the spawning ground. This pattern is clear, even though the BE index may only represent a crude approximation of depth. Deep longline catches are often contaminated by surface catches--10% of bigeye tuna are caught when hooks are not at settled depths (Boggs, 1992). Also, both SBT (Gunn et al.(5); Davis and Stanley(6)) and bigeye tuna (Holland et al., 1990) might be caught outside their preferred depth as they regularly traverse the water column.
The pattern of size distribution with depth is mirrored by the pattern of spawning and nonspawning with depth. Both smaller and nonspawning SBT are more abundant at depth, whereas both larger and spawning SBT are more abundant near the surface. The vertical distribution of SBT larvae suggests that SBT spawn at the surface (Davis et al., 1990), as do caged Atlantic bluefin tuna (Thunnus thynnus) (Fushimi et al., 1998). Surface-water temperatures on the spawning ground usually exceed 24 [degrees] C (Yukinawa and Miyabe, 1984; Yukinawa and Koido, 1985; Yukinawa, 1987). These warm surface waters may be necessary for the survival of their eggs and larvae, but adult SBT normally feed in colder water (often as low as 5 [degrees] C [Olson, 1980]). Temperatures of 10 [degrees] -15 [degrees] C preferred by bigeye tuna (Hanamoto, 1986; Mohri et al., 1996) may offer more favorable conditions for nonspawning SBT and explain their strong association with high BE indices on the spawning ground.
Previous studies have shown that yellowfin tuna caught by purse seine and handline have higher gonadosomatic indices than yellowfin caught by longline (Hisada, 1973; Suzuki, 1988; Koido and Suzuki, 1989). Histological studies have found that yellowfin tuna catches from purse-seine sets and shallow (Taiwanese-style) longline sets have a higher proportion of actively spawning fish than catches from deep (Japanese-style) longline sets (Itano(7)). Thus, spawning fish are more likely to be caught near the surface and nonspawning fish are more likely to be caught in deeper water.
The biological basis for size partitioning with depth could be that large fish spawn more frequently than small fish and, therefore, bigger fish will be caught at the surface more often than smaller ones. Spawning frequency is known to increase with size in female yellowfin tuna (Schaefer, 1998) but could not be determined for SBT. The pattern of size distribution may reflect recruitment into spawning. However, this hypothesis is unlikely because histological examination of ovaries indicated that all SBT caught on the spawning ground were mature i.e. had advanced yolked oocytes (Farley and Davis, 1998), although this does not preclude the possibility that they might not be ready to spawn. The most likely reason for size partitioning is that the spawning frequency or the proportion of time spent spawning to time spent in a nonspawning condition increases with size.
If the ability to tolerate higher than preferred water temperatures improved with fish size, then this would facilitate longer spawning episodes or more extensive feeding in shallow waters, both of which would produce the observed pattern of size distribution with depth. Although the ability to conserve heat in cold waters may increase with size in SBT, it is not clear what size-dependent processes might be involved in avoiding overheating at high ambient temperatures.
We do not understand the temporal and spatial scale of vertical movements of SBT on the spawning grounds in relation to spawning and feeding, nor how these might change with fish size. This behavioral information is needed in order to interpret the patterns presented in our study and might best be achieved by pop-up satellite archival tagging.
Because SBT aggregate by size and depth on the spawning ground, it is necessary to account for their distribution when determining the age and size structure of the spawning stock. This is especially important when evaluating time series of size and age distributions in a fishery where there have been shifts in targeting between yellowfin and bigeye tuna. In the absence of reliable information on the depth of fishing, the most practical way of doing this in the Indonesian fishery would be to inversely weight the effort directed at the different levels of the BE index. The determination of spawning frequency should also take into account longline fishing strategies because it is likely that spawning frequency is affected by fish size and because samples will be caught within or outside the spawning depth.
If the increase in the proportion of SBT at the surface with size is due to spawning activity, then this feature will affect the contribution different size fish make to total annual egg production. A lower spawning frequency, coupled with an exponential relationship between length and batch fecundity (Farley and Davis 1998), would mean that individual small, but mature, fish make a relatively small contribution to total annual egg production. When making stock projections, it may therefore be more appropriate to adopt a parameter that reflects size at mean annual egg production rather than the currently accepted parameter of mean size at first maturity. Further histological research on the reproductive dynamics of small fish is required to better define these parameters. Small fish were rarely caught when the histological work of Farley and Davis (1998) was carried out in 1992-95 but they have become more abundant in recent years (Davis et al.(8)) making such a study possible.
We thank the managers at PT. Perikanan Samodra Besar, PT. Sari Segara Utama, and PT. Bandar Nelayan for facilitating catch sampling at their processing plants in Benoa. We are grateful to Waluyo Suharto, Kiroan Siregar, Mashar Machmud, and Labuhan Siregar for monitoring catches at the various plants; Sofri Bahar at the Research Institute of Marine Fisheries, Indonesia, for coordinating the monitoring program; and Duyet Le for laboratory assistance. We thank Kurt Schaefer, Bill Hearn, and John Stevens for their reviews of the manuscript and Vivienne Mawson for editing. This research was supported by Fisheries Resources Research Fund Grants from the Australian Fisheries Management Authority.
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Tim L. O. Davis Jessica H. Farley CSIRO Division of Marine Research PO Box 1538, Hobart Tasmania 7001, Australia E-mail address (for T. L. O. Davis): email@example.com
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|Author:||Davis, Tim L. O.; Farley, Jessica H.|
|Article Type:||Statistical Data Included|
|Date:||Apr 1, 2001|
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