Marine Biology (2002) 140: 1023–1037 DOI 10.1007/s00227-001-0776-3
A. Bertrand Æ F.-X. Bard Æ E. Josse
Tuna food habits related to the micronekton distribution in French Polynesia
Received: 23 April 2001 / Accepted: 10 December 2001 / Published online: 8 February 2002 Springer-Verlag 2002
Abstract Stomach content analyses are commonly used to study both fish feeding behaviour and trophic conditions. However, the interpretation of such data depends on fish foraging behaviour for a given environment and how representative the stomach contents are to the prey distribution. Tuna feeding behaviour was studied within the context of a research programme conducted in French Polynesia. Tuna prey distribution was characterised using acoustic measurements and pelagic trawls; thereafter, this distribution was compared with the stomach contents of tuna caught using an instrumented longline. Acoustic, pelagic trawling and stomach content analyses give complementary elements to describe the pelagic trophic habitat and to better understand tuna–prey relationships. The classic concept of a reduced food availability for tunas in the tropical pelagic environment seems relative. Tunas able to dive enough during daytime to exploit the migrant micronektonic species secure a source of regular food. This is particularly true of bigeye tuna (Thunnus obesus), which have ecophysiological capacities for this purpose. The behaviour of albacore tuna (T. alalunga), which dive >400 m in depth, remains less clear, as little is known about their vertical behaviour. Lastly, yellowfin tuna (T. albacares), which are distributed in more superficial waters, can better exploit the biomass of
Communicated by S.A. Poulet, Roscoff Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/ 10.1007/s00227-001-0776-3. A. Bertrand (&) Institut de recherche pour le de´veloppement (IRD), Rue Jean Monnet, BP 171, 34207 Se`te Cedex, France E-mail:
[email protected] F.-X. Bard IRD, 15 BP 917, Abidjan, Ivory Coast E. Josse IRD, BP 70, 29280 Plouzane´, France
juvenile fish and crustaceans exported from the reefs. Analysis of the stomach fullness of tuna caught by longline, a passive gear, generally showed an empty state. This result suggests that most tuna foraging on large prey aggregations present in the study area are quickly satiated and escape longline capture and sampling. A consequence is that studies of tuna feeding behaviour based on longlining may be biased, particularly when large aggregations of prey are present such as in convergence zones. Another potential consequence is that longline tuna catch rates could differ according to prey richness. Longline tuna catch rates may sometimes reflect the relative abundance of prey rather than relative tuna abundance. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00227-0010776-3.
Introduction The distribution of tuna, which are fish with a high metabolic rate (Kitchell et al. 1978; Olson and Boggs 1986), is known to be linked to the availability of forage (Sund et al. 1981; Dagorn 1994; Roger 1994). Considered as opportunistic feeders (Sund et al. 1981), tropical tuna feed on a variety of fish, crustaceans, squid and gelatinous organisms. Tuna diet is often considered to reflect the different habitats they occupy horizontally and vertically. However, predator–prey relationships are complex, and stomach content analysis could be biased, particularly if the tuna need to be actively foraging to be captured, then studied, as is the case with longline fishing. To improve the results of stomach content analyses it is necessary to know: (1) how tuna forage in a given environment and (2) how tuna diet as ascertained from stomach content, can be a good indicator of prey diversity and of actual diet. Prey distribution and tuna feeding behaviour were studied within the context of a research programme, ECOTAP (Etude du comportement des thonide´s par
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acoustique et par peˆche/study of tuna behaviour using acoustics and fishing) conducted in the French Polynesian EEZ (exclusive economic zone). One of the concepts of the ECOTAP programme was to study the biological environment of adult tuna and their diet using three simultaneous approaches: (1) mesopelagic trawls, (2) stomach content analysis of tuna captured by an instrumented longline and (3) acoustic measurements. Three species of tuna were studied: bigeye tuna (Thunnus obesus), yellowfin tuna (T. albacares) and albacore (T. alalunga). The three sources of observations present specific limits. Pelagic trawls are selective, and organisms can commonly avoid the trawls. Models of trawl performance compared to acoustic biomass estimation showed that micronekton catchability by large mesopelagic trawls was about 0.06–0.13 (Gjøsaeter 1984; May and Blaber 1989). Stomach content analysis of fish caught with passive gears, such as longline, can also be biased, as capture depends on the feeding behaviour of active fish. Acoustic data is also biased in relation to depth, because there is a great variability of acoustic responses between organisms. Thus, there is no ideal solution as each method has potential biases; therefore, we have used the data within their limits, while acknowledging that they are not fully quantifiable. The ECOTAP programme focused on adult tuna targeted by longliners, which were distributed between the surface and >500 m in depth. The main features of hydrographic and trophic environments as well as tuna distribution were previously described in various studies (Josse et al. 1998; Bertrand et al. 1999, in press; Bertrand and Josse 2000; Dagorn et al. 2000; Bach et al., in press). Bertrand et al. (1999) proposed a typology of the micronekton distribution on a regional scale and divided the study area into three zones (Fig. 1). The first one, located south of 13S, was characterised by a very low biomass and a small number of micronekton aggregates (or patches). The second zone, mainly located between 8S and 13S, corresponded to a weak convergence; this zone represented the highest biomass and a large number of micronekton aggregations. In the third zone, located north of the Marquesas Archipelago, the micronekton biomass was average compared to the whole study area, and there were few micronekton aggregations. Then, Bertrand et al. (in press) showed that at a regional scale, tunas were more abundant in areas rich in prey and with favourable hydrological conditions. Inside such areas, at a longline set scale, however, the longline catches were maximal only when prey were not distributed in dense patches (except for yellowfin tuna). They proposed a hypothesis according to which areas with high prey abundance attract tunas, but, at a small scale, if prey are distributed in very dense patches, tunas are more inclined to feed on them rather than on longline bait. The aim of the present work was to test this hypothesis and to study the distribution of the micronektonic communities on a small scale, in order to try to determine: (1) how tuna forage, according to the available
Fig. 1. Micronektonic biomass zones as described by Bertrand et al. (1999). Zone 1 was characterised by a very low biomass and few micronekton aggregations. Zone 2 had the highest biomass and large micronekton aggregations. In zone 3, micronekton biomass was average compared to the whole study area, and micronekton aggregations were few
prey and their spatial distribution, and (2) whether the analysis of the stomach contents of tuna caught with a longline is representative of their entire diet.
Materials and methods Data were collected on-board the IRD’s R.V. ‘‘ALIS’’ (28 m long) during ECOTAP experiments carried out in the French Polynesian EEZ. The study was conducted between 4S and 20S and 134W and 154W, in the vicinity of the Society, Tuamotu and Marquesas Archipelagos, from October 1995 to August 1997 (Fig. 2). ECOTAP programme objectives and spatio-temporal constraints determined the sampling design. Experimental longline fishing and oceanographic measurements were carried out each day. Fishing sets were distributed continuously along a route, such that the largest possible area would be sampled. Acoustic data measurements Acoustic data were collected with a SIMRAD EK500 (version 4.01) echosounder connected to a split-beam, hull-mounted transducer (SIMRAD ES38B, 38 kHz, beam angle 6.9), used with a pulse duration of 1 ms. The water column was sampled to a depth of 500 m. Acoustic and navigational data were stored on a PC with SIMRAD EP500 software. The on-axis and off-axis calibration was performed with a 60 mm copper sphere using a standard procedure (Foote et al. 1987). Acoustic data obtained in this study came either from diurnal rectangular surveys above the longline or from nocturnal rectangular or straight surveys between each fishing operation (Fig. 2). A –70 dB threshold was applied on data to minimise bias due to integration of noise or non-micronekton organisms. With such threshold, Bertrand et al. (1999) showed that the acoustic back-scattered energy by the surface unit (sa) can be considered representative of micronektonic fish and cephalopod biomass. Acoustic structure morphology is determined by the composition of the specific community and its physicochemical factors, which may be subject to regional changes. Therefore, scattering structure was coded as described by Bertrand et al. (1999), in order to take into account the structural information of the echograms.
1025 Fig. 2. Longline and hydrographic station positions during ECOTAP cruises in French Polynesia. Lower right inset: acoustic observations were conducted along rectangular tracks above the longline (fine line) during the daytime and along rectangular or linear tracks, between each fishing operation (bold line) at night
Pelagic trawl characterisation Micronekton sampling was done using a fry pelagic trawl (5 mm mesh, mouth 18 m high) coupled with echo-sounding. The micronekton have a heterogeneous distribution; thus, one of the consequences in carrying out regular and systematic sampling is that the observations may not reflect the phenomenon studied (Marchal et al. 1996). Therefore, a decision was made to conduct trawling according to the scattering structures observed through the echosounder. As far as possible, diurnal and nocturnal trawling was performed in the greatest number of different structures. Samples were frozen onboard. In the laboratory, each sample was sorted and each taxonomic group was weighed (wet) and counted. Wet weight was converted to dry weight using conversion factors from Young et al. (1996). Each trawled zone was classified according to the types of acoustic structures observed (Fig. 3). The trawled water layer was cut into ten sections of equal length. The acoustic back-scattering energy by the surface unit (sa), minimal (samin.), average (saavg.), maximal (samax.) values and maximal/minimal (max./min.) were then calculated for each trawl. To improve the understanding of the spatial area of the water mass occupied by the micronekton, we calculated additional parameters (Marchal 1990) of the acoustic elementary cells, i.e. 2 m high over 1 ping long, with the settings used. Parameter sa+ corresponds to the sa calculated only on the non-null cells: P saelem saþ ¼ Cne with sa-elem, the sa calculated in a basic cell; and Cne, the number of non-null, i.e. non-empty, cells. The percentage of non-null cells (Pnnul) was also calculated: P nnul ¼
Cne 100 Ctot
with Ctot, the total number of elementary cells. Pnnul corresponds to the spatial level of the micronekton as detected with the echosounder. Because of the low number of trawls for each diurnal structure type, we could not analyse the spatial variation of each specific composition. In contrast, all the night trawls were carried out in continuous sound-scattering layers, often with the presence of a dense nucleus. Consequently, to better understand the micronekton community structure and distribution in the study area, we were able to more precisely classify these nocturnal structures using principal component analysis, followed by an ascending hierarchical clustering analysis on the spatial variables and the acoustic descriptors (Table 1).
We could not classify trawls conducted during the twilight phases. This resulted from difficulties in following the layers of migration and problems of vertical positioning due to the distance between the research vessel carrying the echo-sounder and the trawl and prevented us from determining which structures had actually been sampled. An ANOVA was used to compare the distribution of the taxa in dry weight between night structures. Since the conditions of normality were not met, the Kruskal–Wallis test, a non-parametric alternative to the ANOVA (Scherrer 1984), was employed using STATISTICA (StatSoft, Tulsa Okla.). Stomach content characterisation Tuna captured by an instrumented longline (Bach et al. in press) were immediately dissected on the deck. Stomachs were opened, and the contents were sifted, rinsed and items from non-empty stomachs were fixed in 10% formalin. In the laboratory, organisms were sorted and weighed (wet) to the nearest 1 mg. Degrees of digestion similar to those used by Magnuson (1969) were assigned to each individual food item (Table 2). In cases of doubt, intermediate coefficients were given (e.g. 2.5 or 3.5). For a majority of prey items, lengths were also measured to the nearest millimetre. Empirical method for reconstructing initial weight of the prey To appropriately estimate the importance of each prey item, it is necessary to reconstitute the initial prey weight or length. Some work has focused on this subject, such as Scharf et al. (1998), who used the bones of ingested remains. Such a method requires a perfect knowledge of the prey morphometry, which is very difficult when the taxonomic diversity is as large as in a tropical ecosystem. An original empirical method based on the degrees of digestion was developed. Several ‘‘test animals’’ were selected in order to calculate conversion factors for each digestion index. The selection of the taxa was based on a criterion of common occurrence in the stomach contents. Four species were selected: the fish Brama orcini, the cephalopod Ommastrephes bartrami and the peneid shrimps Funchalia taaningi and Pelagopeneus balboae. To establish the coefficient of weight loss (Table 3), each digested weight was then compared with the initial weight at a given size from length–weight relationships established on individuals captured with midwater trawls or sometimes collected fresh in stomachs. For gelatinous organisms, where length–weight relationships are dubious, loss ratios were assumed to be similar to those of cephalopods. These
1026 Fig. 3a–e. Echotraces utilised for classification. a ‘‘Classic’’ sound-scattering layer (SSL), which can be diurnal, nocturnal and more-or-less thick; b nucleus in scattering layer (NSL); c large, aggregated structures (LAS); d stick-shaped structures (SSS); e small aggregates (SAG)
average ratios were then used for reconstructing the initial prey weights (Bard 2001). Taxonomic identification One of the goals of our biological samplings was to compare the observations coming from both trawls and stomach contents. Two difficulties were apparent. On the one hand, there are large differences in our ability to identify some taxonomic groups, as fish identification was most precise, while gelatinous organisms were poorly identified. In addition, even if a level of family is adopted, the number of observations are often weak and dispersed (a more detailed list of species identifications is available as electronic supplementary material). Therefore, organisms were placed in ‘‘functional groups’’, taking into account the criteria of size, trophic level and range of vertical distribution (Table 4). Fish were separated into six categories, according to the trophic level and the range of daily vertical migration, as defined by Grandperrin (1975). Cephalopods were separated into two categories, according to their mean depth of habitat, as indicated by Grandperrin (1975). Crustaceans were also separated into two categories, according to their life cycle (Table 4).
Results Pelagic trawl characterisation A total of 71 pelagic trawls were used for data analysis. It did not appear relevant to calculate the volume of water sampled, because organism escapement and net satura-
tion seemed significant. Indeed, no clear relationship was observed between trawling duration and the amount of catches. Consequently, the taxonomic compositions used in data analyses were expressed as a percentage of total dry weight. In number, the main taxonomic groups caught in descending order were crustaceans, fish, gelatinous organisms and cephalopods (Table 5). According to the scattering structure sampled, the diurnal trawls were classified into three main categories, with the third category further subdivided into three subcategories (Table 6). The micronekton aggregate category (SAT) corresponds to the grouping of the three categories of aggregated structures (LAS, large aggregate structures; SSS, stick-shaped structures; SAG, small aggregates) described by Bertrand et al. (1999). Indeed, acoustic observations carried out on these structures showed that these three types correspond to a different state of a same patch (see ‘‘Discussion’’). The category sound-scattering layer (SSL) was divided according to depth: surface (SSLS), intermediate (250 m, SSLI) and deep (>400 m, SSLD). The deepest category was only sampled once. It should be noted that, during the day, all trawls, except those from the surface sound-scattering layers, were ‘‘contaminated’’, as organisms were captured during the setting and retrieval of the trawls. The different types of sampled diurnal structures can be described by their taxonomic composition (Fig. 4):
1027 Table 1. Description of parameters used in the multivariate analysis for trawl characterisation (M modality; C continue) Abbreviations
Description
Type
DISL DSM LATI LONG Zmoy Zone M samax. samin.
Distance to the closest island (in nautical miles) Distance to the closest seamount (in nautical miles) Latitude Longitude Mean trawling depth (m) Belonging to one of the three micronektonic zones Maximal back-scattering energy by surface unit on one of the ten sections of the trawled water layer Minimal back-scattering energy by surface unit (sa) on one of the ten sections of the trawled water layer Average back-scattering energy by surface unit on one of the ten sections of the trawled water layer Maximal/minimal back-scattering energy by surface unit on one of the ten sections of the trawled water layer Mean back-scattering energy by surface unit calculated only on non-null cells Percentage of non-null cells Total dry weight of catches Presence (2)/absence (1) of dense nucleus in scattering layer Total dry weight of each functional group Percentage of total dry weight of each functional group
C C C C C M C C
saavg. max./min. sa+ Pnnul Total NDI MYCT, PISC, etc. PMYCT, PPISC, etc.
• NUL: this category represents when trawling was performed in the absence of acoustic detection or when there were no micronekton patches. Consequently, the average weight of captures was very low. The catch frequencies in dry weight were distributed over a large number of taxa. This category can be considered as the ‘‘background noise’’ of the pelagic environment. • SAT: the average weight of the catches was the highest of the diurnal trawl categories. Myctophids were largely dominant, with >60% of the total dry weight. Other taxa were mainly holoplanktonic crustaceans and mesopelagic cephalopods (mainly ommastrephids). • SSLS: epipelagic fish and meroplanktonic crustaceans were the main taxa caught in the surface layer. Reef fish and small pelagic fish were also abundant. No myctophids or piscivorous fish were caught. It should be noted that no functional group exceeded 30% of the total catches in dry weight and that the total amount of captures was very low. • SSLI: myctophids largely dominated the trawls performed in the intermediate layer. Myctophids were followed by leptocephalus larvae, cephalopods and holoplanktonic crustaceans. • SSLD: only one trawl was performed in this structure; thus, results are considered preliminary. The dominant taxa were mesopelagic fish, myctophids and holoplanktonic crustaceans. Two classes were defined by the multivariate analyses for the night trawls. The first one is characterised by ‘‘loose’’ layers (SSLL). The corresponding stations were mainly located south of the study area, in the South Pacific Central Gyre. A ‘‘thick’’ layer (SSLT) characterises the second class. The corresponding stations were mainly located in the northern part of the study area in zones 2 and 3 (Table 6; Fig. 5). The average weight of the micronekton was more than three times greater in
C C C C C M C C
the thick layers than in loose ones (Fig. 6). Myctophids dominated the two types of night structures, and proportionally they were significantly more abundant in zones 2 and 3 (Kruskal–Wallis test, P550 m during the day, depending on the zone (Dagorn et al. 2000). Yellowfin tuna have a rather different diet, mainly composed of animals present in the shallower layers. Yellowfin feed significantly on the juveniles of reef fishes when available (zone 1, Fig. 8). Other consumed taxa are epipelagic fish, meroplankton, holoplankton and cephalopods. This diet is indicative of yellowfin beha-
viour, as they largely forage in the upper 100 m and are often encountered close to the coasts in French Polynesia. Albacore differ from the two other tuna species by the high proportion of cephalopods in their diet. Crustaceans also had great importance. Albacore seem to forage in deep water, but its vertical behaviour is still largely unknown, because the fragility of its swimbladder makes it difficult to capture fish in suitable condition for tagging and tracking (Bard et al. 1998). Comparison of pelagic trawling and tuna stomach contents Comparison of the average weights of the functional categories observed in the stomach contents of the three tuna species and in the pelagic trawls shows significant differences (Table 8). Fish and cephalopods were smaller on average in the trawls, or, if they were of equal size, as in the case of piscivorous fish, they were very rare in the trawl catches. Differences in sizes were weaker for the crustaceans, which showed less avoidance of the trawl. The differences in number and in size show that fish and cephalopods avoided the trawl and/or that tuna seem to feed on larger organisms.
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Fig. 8. Distribution (percentage of total dry weight) of functional groups in the tuna stomachs by species (abbreviations, see Table 4) and micronektonic zone (BET bigeye; YFT yellowfin; ALB albacore)
Because of these differences in ‘‘sampling efficiency’’, it is not possible to directly associate the stomach contents of each tuna species with a type of trawled structure. Nevertheless some tendencies can be illustrated. The greatest difficulty relates to bigeye, which consumed large amounts of piscivorous fish, which were rarely encountered in the trawl samples. The vertical behaviour of this species, as observed by sonic tracking in the study area (Bach et al. 1998; Dagorn et al. 2000), as well as the taxa observed in its stomach contents show that bigeye forage during the day on the deep scattering layers or on myctophid aggregations when they are present. Yellowfin seem to forage more than the other tuna species on the shallower scattering layers at the surface, the only structure in which reef fish and epipelagic fish were caught in significant quantities and in which the two taxa were abundantly consumed by yellowfin. Lastly, albacore mainly consume cephalopods, which were very difficult to sample by trawling and were not easily distinguishable from myctophids with the acoustic tech-
niques we used. Nevertheless, a larger amount of cephalopods was caught in the intermediate scattering layers, where albacore are assumed to forage, given the depth of longline catches (Bertrand 1999). The comparison of pelagic trawl, stomach content and echo-integration data highlights an essential contradiction: the disproportion between the biomass of myctophids observed in situ and the presence in the tuna stomachs. This disproportion is less important for bigeye, which can forage at depths >500 m. However, even in this case, myctophids do not constitute the most abundant taxon in the stomach contents. Three hypotheses can be formulated to explain these results: (1) myctophids are distributed too deeply or are not sufficiently concentrated to be accessible to tuna during the day; (2) adult tuna indirectly exploit the biomass of myctophids by predation on the predators of myctophids; and (3) tuna that feed on myctophids aggregations are quickly satiated, which decreases the effectiveness of longline fishing. The first of these possibilities was the main hypothesis of Roger and Grandperrin (1976) and is applicable for yellowfin in zone 1. The second hypothesis is supported by the high proportion of piscivorous fish and
1034 Fig. 9. Various phases of an aggregative structure: a night phase; b, c, d, e diurnal phases at 1500, 1600, 1630 and 1730 hours, respectively
cephalopods in the tuna stomach contents. This may suggest that adult tuna preferentially target the predators of myctophids (i.e. the results illustrate selectivity
differences between tuna and trawling). However, a particular case must be noted: the stomach of a bigeye, caught at dawn at 390 m of depth, contained a notable
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Fig. 10. Rate of stomach filling (prey weight divided by theoretical weight of a full stomach) versus individual body mass for 287 longline caught large tunas (>15 kg) with non-empty stomachs
quantity of large myctophids (166 Myctophum asperum for a total of 763 g). The acoustic survey during the previous night showed the presence of a dense nucleus in shallow scattering layers. At dawn, micronekton aggregations were also present. Tuna can thus target these myctophid aggregations if concentrated. This type of behaviour follows the third hypothesis and was observed by McPherson (1988) and Me´nard et al. (2000). Magnuson (1969) showed that prey attack decreased rapidly when stomach content exceeded 50% of the stomach’s capacity. Therefore, it can be assumed that if a tuna succeeds in consuming a large quantity of myctophids it will become quickly satiated and will not continue to search for additional prey outside of the prey aggregations. Thus longline catchability is reduced, as observed by Bertrand et al. (in press). On the other hand, in the absence of prey aggregations, tuna are assumed to forage in the scattering layers, where prey density is several orders of magnitude lower than in prey aggregations, and have a higher probability to be caught by longline. Such behaviour, reflected in a notable paucity of food in the stomachs of longline-caught tunas, contrasts with various observations showing that the stomachs of tunas captured by other types of gear in similar foraging situations can occasionally be full (Bard 2001). Roger and Marchal (1994) observed that small Table 8. Mean weight of the organisms in various functional groups observed in trawls and tuna stomachs. Numbers in parentheses are the ratios of stomach content weight to trawl contents (taxon abbreviations, see Table 4)
Group
MYCT PISC REEF EUPE FISH BATY MCEP DCEP HCRU MCRU GELA
tuna captured by trolling had full stomachs. In the case of live bait fishing, the frenzy behaviour of tunas is such that tuna attack even if satiated (Bard, personal observations). For a widely used active gear, purse seine, numerous observations of full stomachs in large, captured yellowfin have been reported (Olson and Boggs 1986; Bard and Pezennec 1991; Bard et al. 2001). A recent study (Essington et al. 2000) shows that satiation was unlikely an important factor in predation rates of a fish predator in lake. However, they do show that the satiation effect may be important when prey density is high or when prey encounters are highly patchy, which is the case in convergence zones, and, on the other hand, that feeding rate can exceed normal satiation levels when prey are rare and patchy. Tuna foraging into micronekton patches are assumed to rapidly become satiated, reducing then their motivation to forage on dispersed bait. If such tuna are less often captured with a longline, part of the tuna diet escapes sampling. In conclusion, acoustic measurements, pelagic trawling and stomach content analyses provide complementary elements to describe the pelagic trophic habitat and to better understand tuna–prey relationships. Each sampling method has a specific bias, which could not be quantified in this study. The classic concept of reduced food availability for tunas in the tropical pelagic environment seems to be relative. Tunas able to dive enough during daytime to exploit the migrant micronektonic species in cold and obscure waters secure a source of regular food. This is particularly the case for bigeye tuna, which have ecophysiological capacities for this purpose. The patterns for albacores, which dive >400 m in depth, remain less clear, as little is known about albacore vertical behaviour. Lastly, yellowfin tuna, which are distributed in more superficial waters, can better exploit the biomass of juveniles and crustaceans exported from the reefs. The low level of stomach fullness and the quasi absence of monotypic prey in the composition of the stomach contents of tuna captured by longlining lead us to propose the following hypothesis: a longline is probably an efficient sampling gear for studying the tuna diet when prey are scarce and tuna are not satiated. On the other hand, tuna foraging on prey aggregations could be assumed to escape longline
Trawl
Stomach content
Mean weight (g)
Number
0.9 8.7 0.4 7.3 0.4 1.5 1.8 0.7 0.2 0.1 0.2
94,685 95 3,556 469 4,516 728 6,176 2,347 83,547 9,765 34,664
Mean weight (g) 3.2 9.3 1.7 6.3 8.7
(3.6) (1.1) (4.3) (0.9) (20.1)
11.2 9.0 0.3 0.3 0.6
(6.1) (12.3) (1.5) (3.0) (3.3)
Number 545 641 355 433 782 2 560 444 2,161 1,256 353
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sampling; therefore, an important part of tuna diet may escape observation. Such a hypothesis is supported by the results of Bertrand et al. (in press), which show that in an area globally rich in prey, the longline catches are lower if local prey are abundant and distributed in aggregations, as an interference effect between prey and longline bait probably occurs. Another potential consequence is that catch rates of tuna captured by longline could be driven more by the relative spatial distribution of the prey and tuna predation rather than actual tuna abundance. If true, such a situation could represent an important factor in the interpretation of longline catch per unit effort data, when used for deriving abundance indexes. Acknowledgements This research was supported by the Government of French Polynesia. The authors wish to thank the officers and crew of the R.V. ‘‘Alis’’ for their kind assistance during experiments. Sincere thanks are extended to all of our colleagues from SRM (ex-EVAAM), IFREMER and IRD (ex-ORSTOM), who worked with us during the ECOTAP programme, particularly R. Abbes for taxonomic identification. We are also grateful to E. Marchal for helpful comments. K. Bigelow is warmly thanked for revising the English of this paper. Experiments comply with the current laws of the country in which the experiments were performed.
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