© 2006 International Council for the Exploration of the Sea
The genetic structure of Pandalus borealis in the Northeast Atlantic determined by RAPD analysis
a Norwegian Institute of Fisheries and Aquaculture Ltd. N-9291 Tromsø, Norway
b SINTEF Fisheries and Aquaculture Ltd N-7465 Trondheim, Norway
c Institute of Marine Research PO Box 6404, N-9294 Tromsø, Norway
d Den Norske Veritas Research Veritasveien 1, N-1322 Høvik, Norway
e Department of Biochemistry and Molecular Biology, Federal University of Parana Politechnique Center UFPR, PO Box 19046, CEP 81531-990, Curitiba, PR, Brazil
*Correspondence to I. Martinez: SINTEF Fisheries and Aquaculture Ltd, N-7465 Trondheim, Norway. tel: +47 95709772 fax: +47 93270701. e-mail: iciar.martinez{at}sintef.no.
The genetic structure of shrimp (Pandalus borealis) in the Northeast Atlantic was examined by RAPD analysis on specimens caught at eight stations in the Barents Sea, three off Svalbard, two off Jan Mayen, and in two northern Norwegian fjords (19 < n > 31 per station). A total of 34 polymorphic markers generated by seven 10-mer arbitrary primers was used to assess the genetic population structure using analysis of molecular variance (AMOVA). There was considerable RAPD diversity (>90%) among shrimp at all stations. The two Norwegian fjords and the Jan Mayen stations were different from all the others, and the Jan Mayen stations also differed from each other. More than 98% of the genetic variation between Barents Sea and Svalbard was ascribed to individual diversity, and there was no significant difference between the two areas, although there seemed to be a subpopulation structure in the Barents Sea. Principal component analysis on the frequency of each RAPD marker on each sampled station confirmed the presence of three populations: Barents Sea and Svalbard, northern Norwegian fjords, and Jan Mayen. We postulate that the large genetic variability found at an individual level may provide the total population with a diverse genetic pool from which traits can be selected to respond to variations in local environmental conditions, and that this local selection may be the cause of the subpopulation structure observed.
Keywords: AMOVA, North Atlantic, Pandalus borealis, RAPD, shrimp
Received 22 November 2004; accepted 17 March 2006.
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Introduction |
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The shrimp Pandalus borealis (Krøyer, 1838) is a protandric hermaphrodite with a discontinuous circumboreal distribution (Shumway et al., 1985). The largest shrimp stocks are in the North Atlantic, off Canada, Greenland, Iceland, and in the Barents Sea and around Svalbard. The species is important commercially for Norway, which harvested about 67 000 t with a commercial value of more than 100 million euros in 2003 (Anon., 2003). The main Norwegian fishing grounds are in the Barents Sea and around Svalbard. Shrimp in the Barents Sea change sex from male to female at an age of five years. In the Svalbard area and off Jan Mayen, the age for sex change may be later because of the lower water temperature. Shrimp spawn in early autumn in cold water and in late autumn in the Barents Sea. Females carry their eggs throughout winter, and the eggs hatch in spring. The hatching date is dependent on water temperature: the colder the water, the later the hatching. Shrimp size increases with water depth, males being more abundant in shallow areas (<300 m; Aschan, 2000). Larvae are pelagic for approximately two months, after which they settle (Pedersen et al., 2003).
For stock assessment and management of shrimp, knowledge of the genetic structure of the stock is important. Kartavtsev et al. (1991) studied population differentiation of shrimp at four allozyme loci, and found the Barents Sea population to be homogeneous, supporting a hypothesis previously proposed by Berenboim (1982) that all populations in the Barents Sea should be considered as one superpopulation. Rasmussen et al. (1993) assessed the frequency distribution of two allozyme loci in populations of pink shrimp from Svalbard and in two northern Norwegian fjords and found significant differences between the samples from Svalbard and those in the fjords, but not among the samples from Svalbard or among those from the fjords. The allozyme analyses of Jonsdóttir et al. (1998) permitted identification of significant genetic differences between shrimp inhabiting inshore and offshore Icelandic waters and the Denmark Strait. Drengstig et al. (2000), also using allozyme studies, failed to find significant heterogeneity in allele frequencies in the Barents Sea/Svalbard region, supporting earlier suggestions of there being just one population in the Barents Sea. These results accord with the model of larval dispersion and mother populations of P. borealis recently postulated by Pedersen et al. (2003).
The present study was undertaken as complementary to that of Drengstig et al. (2000), in order to examine more closely the possible genetic structure of P. borealis in the Northeast Atlantic, analysing variation in the genomic DNA by random amplified polymorphic DNA (RAPD) markers (Welsh and McClelland, 1990; Williams et al., 1990). RAPD analysis was chosen instead of restriction fragment length polymorphism or minisatellite DNA analysis, because RAPD can be performed without any previous knowledge of specific DNA sequences of the species under study. RAPD requires small amounts of DNA and it is faster, less costly, and less labour-intensive than the other two DNA techniques (Caetano-Anollés et al., 1991; Hadrys et al., 1992). RAPD analysis has been successfully used to study genetic structure, inter alia, in plants (Huff et al., 1993; Stewart and Excoffier, 1996), birds (Haig et al., 1996), and snails (Jacobsen et al., 1996). Treatment of RAPD markers by analysis of molecular variance (Excoffier et al., 1992) has been proven to be adequate in allocating RAPD genetic variation among individuals/within sampled stations, among stations/within regions, and among regions, as shown by Huff et al. (1993) and Stewart and Excoffier (1996).
Here we use analysis of molecular variance (AMOVA) and principal component analysis (PCA) on 34 genetic markers obtained by RAPD fingerprint analysis of about 400 shrimp captured at 15 different stations in the Barents Sea, Svalbard, Jan Mayen, and in two Norwegian fjords, to study the genetic structure of the species in the Northeast Atlantic.
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Material and methods |
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Shrimp (Pandalus borealis) were caught with a Campelen 1800 shrimp trawl, at depths varying from 150 m to 550 m, at 15 stations in the North Atlantic (Figure 1). Sampling was done during the annual shrimp surveys conducted in the Barents Sea between April and June, and in the Svalbard and Jan Mayen areas between July and August of 1995 and 1996 (Aschan and Sunnanå, 1997). Fjord shrimp were collected before the autumn spawning season. The location, exact position of the stations, and the number of individuals analysed from each station are shown in Table 1. About a third of the shrimp analysed at each station were male and intersex (sex stages 2 and 3); the balance were shrimp with gonads (stage 4 or 8), outroe (5), or signs of previous spawning (6 and 7; Aschan and Sunnanå, 1997). Immediately after capture, shrimp were beheaded and immersed in 96% ethanol, then stored at room temperature until the DNA was extracted. As indicated in Table 1, shrimp samples from 11 of the 15 stations had also been examined by allozyme analysis, by Drengstig et al. (2000).
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DNA extraction
Several procedures were tried to preserve shrimp tissue and to extract DNA. The protocol reported here is the one that was finally selected for its convenience and for rendering the greatest amount of DNA. About 50–100 mg of ethanol-embedded muscle was cut and blotted onto tissue paper to eliminate as much ethanol as possible. Pieces of muscle were transferred to 2-ml Eppendorf tubes, finely minced with scissors, and the balance of the ethanol allowed to evaporate by incubating at 55°C for about 2 min. To each tube was first added 400 µl of lysis buffer (Miller et al., 1988), 0.4-M NaCl, 10-mM Tris–HCl, pH 8.0, and 2-mM EDTA, pH 8.0, then 36 µl of 20% SDS and 8 µl of 20 mg ml–1 proteinase K was added, to give final concentrations of 1.6% and 400 µg ml–1, respectively. The contents of the tubes were mixed by inversion several times, and incubated at 55°C for 3 h or overnight with occasional mixing. After incubation, samples were allowed to cool, and 360 µl of 6-M (saturated) NaCl was added to each tube (Miller et al., 1988). Tubes were vortexed for 1 min at maximum speed, then centrifuged in an Eppendorf bench centrifuge at 14 000 rpm for 20 min. Supernatants were recovered, transferred to new tubes, and 100% ethanol in a 2:1 (ethanol:sample) ratio was added to each tube. Tubes were inverted several times, incubated at –20°C for at least 1 h, then centrifuged for 30 min at 14 000 rpm. Supernatants were discarded and the DNA pellets were washed with 70% ethanol. Pellets were dried at room temperature and resuspended in 300 µl ddH2O. The amount and quality of the DNA was estimated by 1% agarose gel electrophoresis and comparison with known amounts of
DNA.
Selection of primers
Seven 10-mer primers (Table 2) were chosen after screening about 200. The criteria for selection were that the primers should consistently (between replicate PCRs and for a DNA concentration ranging from about 1 to 5 ng µl–1) produce polymorphic bands, and that the bands had to be clear to score and of a size between approximately 300 and 600 bp (Stewart and Excoffier, 1996).
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DNA amplification
Arbitrarily primed amplifications (Welsh and McClelland, 1990; Williams et al., 1990) were performed in 30-µl volumes. Initially for each sample, two dilutions containing 1 and 5 ng µl–1 DNA were amplified, as described below. Once it was established that both DNA concentrations gave the same RAPD profile (Welsh and McClelland, 1990), only the sample containing 1 ng µl–1 was used. A volume of 10 µl of the DNA extracts containing 10 ng and 50 ng, respectively, of the template DNA, was added to 20 µl of a mixture containing 1x DNA polymerase buffer (supplied by the manufacturer), 100 µM each of dATP, dCTP, dGTP, and dTTP, 0.4-µM 10-mer primer (Operon Technologies Inc., Alameda, CA), and 4-mM MgCl2 (Ellesworth et al., 1993), with 2 units of the Stoffel fragment of AmpliTaq DNA polymerase (Perkin Elmer). The reaction mixtures were overlaid with 20 µl of Chill Out Wax (MJ Research Inc., Watertown, MA), and amplification was performed on a PTC-100 programmable thermal controller (MJ Research Inc., Watertown, MA). The thermal programme for amplification was 94°C for 2 min, followed by 40 cycles of 94°C for 20 s (denaturation), 35°C for 20 s (annealing), and 72°C for 1 min (extension). The programme included a final step of 72°C for 5 min, and the products were maintained at 4°C until ready to load onto the gels.
Agarose electrophoresis
The DNA extracts were examined in 1%Seakem LE FMC agarose gels. In all, 15 µl of the products obtained after RAPD analysis were resolved in 20 x 13 cm, 2% (1:3) Nusieve:Seakem LE FMC agarose gels. Gel and electrophoresis buffers were 0.5 x TBE (Sambrook et al., 1989), and electrophoresis took place for about 2 h at 200 V.
After electrophoresis, the gels were stained for 20 min in 0.5 x TBE buffer containing 0.5 µg ml–1 ethidium bromide, destained for another 20 min in the same buffer without ethidium bromide, then photographed under ultraviolet light with a Polaroid camera and film type 55.
Statistical analysis
The presence (1) or absence (0) of each polymorphic marker was determined for each individual, and a binary matrix was constructed. The analysis of molecular variance (AMOVA; Excoffier et al., 1992) was performed with the program ARLEQUIN (Schneider et al., 1996), downloaded from the Internet (http://lgb.unige.ch/arlequin/). AMOVA partitions the observed genetic variation into three levels: differences between genetic groups (in this case the four regions of Jan Mayen, Svalbard, Barents Sea, and the fjords), differences among populations within groups (the sampled stations), and differences within populations (genetic variation attributable to individuals). The pairwise genetic distances FST were also provided by Arlequin. FST can be used as short-term genetic distances between populations, with the application of a transformation to linearize the distance with population divergence time (Reynolds et al., 1983; Slatkin, 1995).
The presence of genetically similar clusters of sampled stations was examined by multivariate data analysis on the average frequency of each of the 34 RAPD markers in each of the 15 stations (Demeke and Adams, 1994). Principal component analysis (PCA) was performed using the program Unscramble (Esbesen et al., 1994), with full cross validation. The 34 variables (RAPD markers) were centred, and each was given a weight of one.
Monotonic multidimensional scaling (MDS; Kruskal and Wish, 1978) was used to study (i) the variation between individuals attributable to age/sex distribution from five stations in four regions: north Norwegian fjord (Malangen) Station 1, Barents Sea Stations 9 and 5, Svalbard Station 12, and Jan Mayen Station 14, and (ii) the variation within four stations in the Barents Sea: one with a common genotype (Station 5), and the three other stations (4, 7, and 9), which seemed to cause subpopulation structure. The analysis was run in SYSTAT 10.2. Binary similarities were calculated according to Jaccard's dichotomy coefficient, and analysed by MDS, minimizing Kruskal stress.
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Results |
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RAPD profile
After excluding markers that were monomorphic for the entire data set, the seven primers yielded 34 polymorphic markers (Table 2). The frequency of each marker at each station is shown in Table 3. Five markers (4, 6, 9, 30, and 32; 14.7%) were fixed at some stations, and another five markers (7, 12, 15, 20, and 24; 14.7%) were not detected at some stations.
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Estimating population genetic structure
The first part of the work was to examine whether there was some intra-"geographical region" structure, or whether the regions could be considered genetically homogeneous. Results of the analysis, shown in Table 4, revealed that there was some genetic structure among the stations sampled in the Barents Sea (p < 0.0005), Svalbard (p < 0.05), and in Jan Mayen (p < 0.01), but not in the fjords. Both the fjords and the Jan Mayen stations were significantly different from all other regions (see also Table 5, showing the pairwise genetic distances between populations). However, in all regions, >96% of the total genetic variability originated in individuals within the sampled stations, and the percentage of the total genetic variability that could be attributed to different stations within the same region was always low, varying from zero in the fjords to 3.22% in Jan Mayen.
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Possible differences attributable to the year of sampling were also tested; no significant differences were found in the Barents Sea or the two Norwegian fjords, but Svalbard Station 13 sampled in 1996 was significantly different from Stations 11 and 12, sampled in 1995 (Tables 4 and 5).
There was detectable genetic structure between the shrimp collected in the Barents Sea (1.4%), which was attributable mostly to Station 4, but also to Station 9 or 7 (Table 5). As already mentioned, the genetic structure in Svalbard was due to Station 13 (1.4%; Tables 4 and 5). However, there was no significant genetic variation among samples from the Barents Sea and Svalbard when all stations were included in the model (–0.01% of the total genetic variability could be ascribed to such regional differentiation), so the populations of the Barents Sea and Svalbard may be considered to be a single population (Table 4). Samples from the Barents Sea and Svalbard were significantly different from the Jan Mayen region (about 5% of the total genetic variability in each case). The Barents Sea–Svalbard population was also significantly different from both the Jan Mayen and the Norwegian fjord populations, and analysis of the genetic structure in the three areas (Barents Sea and Svalbard vs. Jan Mayen vs. the Norwegian fjords) indicated a highly significant (p < 0.0001) but small (6.7%) genetic diversity among them. The major component of the total genetic diversity was always attributable to individual diversity within the sampled stations (92%, p < 0.0001).
The pairwise genetic distances (FST) between pairs of stations are shown in Table 5. The two Norwegian fjords were significantly different from the others, as were the two stations from Jan Mayen, with the exception in the latter case of Station 14, which was not significantly different from Barents Sea Station 10. Significant differences between pairs of stations were noted within the Barents Sea, in particular caused by Station 4, the most easterly station sampled, but also by Stations 7 and 9, which are in a region in the Barents Sea with incoming cold water from the Arctic.
Principal component analysis (PCA)
A PCA analysis (Figure 2) on the average frequency of each marker at each station (shown in Table 3) confirmed the genetic structure indicated by AMOVA. The first and second components explained 29% and 17% of the total variation present in the data set, respectively (Figure 2). Three clear clusters were observed, one corresponding to samples from the Barents Sea and Svalbard, the second to samples from the fjords, and the third to samples from the Jan Mayen area. However, samples from Jan Mayen, although clearly segregated from the other two groups, did not cluster, which indicated that individuals from the east and from the west of the island are not genetically homogeneous.
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Multidimensional scaling (MDS)
As shown in Figure 3, monotonic MDS confirmed the notable variability among individuals, with no differences attributable to the sex or the age of the shrimp analysed, and an important overlap between shrimp sampled in the open sea. Although the variation between shrimp collected in the fjords was also high, there was very little overlap with shrimp collected in the open sea. The MDS analysis confirms the differentiation among shrimp according to geographical distance: the Norwegian fjord and Jan Mayen samples were most different from each other, but were also different from the Barents Sea and Svalbard stations, although there was some overlap between Jan Mayen Station 14 and Svalbard 12. The overlap between the clusters for Svalbard Station 12 and Barents Sea Station 5 was notable, while the cluster corresponding to Barents Sea Station 9 seemed to correspond to a subsample contained within the larger cluster of Station 5.
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This last observation led us to examine the distribution of Barents Sea stations that were responsible for the subpopulation differentiation. We wished to assess whether those stations would form clusters separate from the other stations (and therefore have different genotypes from those found in the common stations), or whether they would be sub-clusters within the main "common" stations (and therefore the result of selection of genotypes within the main pool available). Figure 4 shows the latter to be the case, with all stations causing the subpopulation structure seemingly contained within the cluster of Station 5, which represents a "common" genotype. Interestingly, the cluster formed by shrimp from Station 4 seemed to be more compact than the clusters of Station 7 or 9, but not more different from Station 5; i.e. there was less individual variation in that station than in the rest, although the shrimp did not have a different genetic structure.
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Discussion |
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Except for the two fjord populations, which were not significantly different from each other according to RAPD analysis, there seemed to be highly significant but very small genetic differences (<3.2% of the total genetic variability) attributable to the station within the regions of the Barents Sea, Svalbard, and Jan Mayen.
Stations 4 and 9 and/or 7 caused some genetic structure within the Barents Sea (See Table 5). As mentioned above, Station 4 was the most easterly station, so the difference in this sample may be explained by a relationship between longitude and genetic distance, whereas Stations 7 and 9 receive cold-water Arctic currents. However, unlike Station 4 which seemed to be different from the rest, the centrally located Stations 7 and 9 were not significantly different from several other stations in both the Barents Sea and near Svalbard (Stations 3, 8, 10, and 12 were not different from Station 7, and Stations 5, 6, 10, and 13 were not significantly different from Station 9; see Table 5). Differences were also noted in the sample from Svalbard, clearly attributable to Station 13, which was, however, not significantly different from the Barents Sea Stations 3, 5, 6, and 10. The two stations at Jan Mayen were also significantly different from each other, but these stations are on opposite sides of the island, Station 15 northwest of Jan Mayen and receiving cold Arctic water, and Station 14 in the southeast receiving warmer water. One explanation for the differences, which is discussed below, is the possible existence of subpopulations in the Barents Sea and Jan Mayen regions. An alternative explanation, which we cannot exclude, for the differences found between these stations (numbers 4, 7, and 9 in the Barents Sea, 13 near Svalbard, and 14 or 15 from Jan Mayen), may have been introduced by sampling and the type of analysis: the sample size was small (approximately 30 shrimp) which, combined with the extremely high individual variability found at all stations (always higher than 96.5% of the total genetic variability) may have produced a biased sample of individual shrimp, perhaps not fully representative of the genetic diversity at the particular sampling station.
In accord with the findings of Drengstig et al. (2000), results of the RAPD analysis indicate that shrimp from the Barents Sea and Svalbard can be considered as belonging to the same population. Differences between the two regions were not significant (–0.01% genetic variability; Table 4), but there may be subpopulations, as indicated by Berenboim (1982) and by the "among stations genetic variability" found in this work (1.4%, p < 0.0005), which was caused by Stations 4 and 9 (or 4 and 7, results not shown) in the Barents Sea. The Barents Sea and Svalbard population was significantly different from the populations of Jan Mayen and in the Norwegian fjords. This finding supports the findings of Pedersen et al. (2003) and Jonsdóttir et al. (1998). The first authors showed that Barents Sea shrimp in all subareas produced offspring, and that the pooled offspring can be considered as a single population, and the latter authors found significant genetic differences among shrimp inhabiting three areas around Iceland and in the Denmark Strait, especially between inshore and offshore Denmark Strait shrimp.
The genetic structure of P. borealis depicted by this work using RAPD markers is comparable with that described by Fevolden (1992) of Chlamys islandica, using allozyme variability in the same areas. C. islandica and P. borealis both have a planktonic larval stage that lasts for 2–3 months (Shumway et al., 1985) allowing large potential for dispersion while the larvae are carried by the currents. Dispersion of larvae among the fjords will be dictated by the intricate coastal current system. The distance between the two fjords examined here, Malangen in the south and Balsfjord in the north, is about 25 km. This short distance and the known currents can explain the genetic similarity between the two samples which, according to our results, may be considered as a single population. The lack of genetic differentiation between the fjords agrees with the findings of Rasmussen et al. (1993), but contradicts the findings of Drengstig et al. (2000), who used samples collected simultaneously with those analysed here but found a significant difference between the populations in these two fjords by allozyme analyses. The only explanations we can find for this, also mentioned by Drengstig et al. (2000), is that RAPD and allozyme polymorphisms examine different loci, and the differences in the sensitivity of the two techniques. However, our results agree with those obtained by Fevolden (1992) on C. islandica sampled from two other northern Norwegian fjords, Berg and Andammen, which are, respectively, about 20 and 80 km north of Balsfjord.
The surface current system schematically depicted on Figure 1 would appear to make it reasonable to assume a dispersion of larvae from the Barents Sea to Svalbard, some dispersion of larvae from the west coast of Jan Mayen towards the Barents Sea, and also some limited dispersion from the west to the east coast of Jan Mayen. Kartavtsev et al. (1993) studied the genetic structure of P. borealis in Far Eastern Seas and found that shrimp sampled at different stations in the same sea were genetically homogenous, but that there were statistically significant differences in morphology among them. The same authors considered these morphological differences to be due to the effect of local selection at larval and juvenile developmental stages, and assumed the existence of a subpopulation structure. Similarly, in the present work, morphometric traits of P. borealis in the Barents Sea–Svalbard area vary: Aschan (2000) found differences in the growth rate and the age and size at sex change of P. borealis. In the southern Barents Sea, where the water temperature is higher, the shrimp grew faster and changed sex earlier than those in the central and northern Barents Sea, where the water temperature is lower (Stations 7 and 9). The same trend was observed temporally: during the 1980s, when water temperatures were low, shrimp had slower growth and changed sex later than in the 1990s, when water temperature was higher. This seems to indicate a relationship between morphometry and environmental factors, especially water temperature, which is very likely to have an effect on the hormonal status of a shrimp as well on the availability (both quantitative and qualitatively) of food. Water temperature influences the rate of development of many marine species, including shrimp (Shumway et al., 1985) and Arctic fish species (Martinez and Pedersen, 1992; Martinez et al., 1995).
In summary, although the Barents Sea–Svalbard population seems to be genetically homogeneous, there may be some subpopulation structure in environmentally extreme areas (Stations 4, 7, and 9), migration distance and water temperature being two factors that may exert a selection at the larval and juvenile stages, as suggested by Kartavtsev et al. (1993). Consequently, had there been some type of selection during the larval or juvenile stages (so that shrimp with a more appropriate growth rate survived better), the negatively selected shrimp, which would have perished early in life, would not have been available for analysis at the "negatively selected" stations. This should have been reflected in the frequencies of the genetic markers, as seemed to have been the case for Stations 4, 7, and 9 in the Barents Sea, and at Station 13 in Svalbard. This hypothesis seems to be supported by the MSD plot (Figure 4), where the clusters corresponding to Stations 4, 7, and 9 seem to be nothing more than subsamples of the more "universal" Station 5, rather than different populations. The same hypothesis would apply to the two Jan Mayen stations: differences in water temperature and currents supplying the two stations may justify selection of larvae or juveniles with different traits. As a result, there may be a reason to consider the existence of subpopulations based on differences in observed morphometry and in the frequencies in some RAPD markers. A more in-depth study of the physiology of P. borealis, together with mapping of relevant environmental variables and of the shrimp's genome to ascertain its genetically determined morphometric traits, should help to clarify this point.
In support of this hypothesis would be the very large genetic variability that was always observed at an individual level. That variability, together with the intricate system of major and local water currents that help to mix the shrimp during their early stages, would provide the whole Northeast Atlantic shrimp population with a diverse genetic pool to allow the species fast selection of given traits, to respond in a swift manner to local changes in the environment. This hypothesis would help to explain also the great variability in morphometric traits and differences in local subpopulations that may change from year to year and according to environmental factors.
Concluding, the present study indicates that a characteristic of P. borealis in the Northeast Atlantic is large genetic variability at an individual level. Agreeing with earlier results (Rasmussen et al., 1993; Drengstig et al., 2000), the findings presented here confirm that shrimp from the Barents Sea and Svalbard areas belong to a single population, and that they differ from the Norwegian fjord and the Jan Mayen populations. Subpopulation structure was detected in the Barents Sea and around Jan Mayen, possibly because of local selection of some of the genotypes contained within the larger common genetic pool of the Northeast Atlantic population, rather than to the presence of specific different genotypes.
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Acknowledgements |
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The officers and crew of the RV "Jan Mayen" are acknowledged for help with the sampling. We also thank Bent Dreyer (Norwegian Institute of Fisheries and Aquaculture Ltd, Tromsø) and Peter E. Smouse (Rutger University, New Jersey) for explanations and help in using the program AMOVA, Laurent Excoffier (University of Geneva, Switzerland) for making the programs AMOVA (ftp:\\acasun1.unige.ch) and ARLEQUIN (http://anthropologie.unige.acasun/methods.html) available via the Internet, and Oddvar Dahl from the Norwegian Institute of Fisheries and Aquaculture for drawing Figure 1. Timothy D. Dempster proofread the manuscript, and the Norwegian Research Council supported the work financially (project 108151/120). To both we are very grateful. Finally, comments by the referees are acknowledged for being very pertinent in terms of interpretation of the results.
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References |
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