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M .I. Roldan et al. J. Exp. Mar. Biol. Ecol. 253 2000 63 –74
consequence of its broad distribution and the existence of oceanographical barriers, the species may be comprised of multiple disjunct populations. In the South West Atlantic
Ocean, many studies of local fishing grounds have highlighted different aspects of the ´
species’ biology Perrotta, 1992, 1993; Pajaro, 1993; Perrotta and Christiansen, 1993; Perrotta et al., 1997 and the fishery Perrotta and Pertierra, 1993; Perrotta et al., 1998b.
Two fishing stocks of chub mackerel north and south of latitude 398009S have been designated by their seasonal occurrence, observed behaviour and environmentally
induced morphometric characteristics. These stocks are operational units used in fishery management, with small purse-seining boats Lampara net operating in the Mar del
´ Plata area and large trawling boats in El Rincon Perrotta et al., 1998a.
Allozyme data have clarified intraspecific relationships in two mackerel species Scomber scombrus, Jamieson and Smith, 1987, and references therein; Scomberomorus
cavalla, Johnson et al., 1994. Nevertheless, in spite of the interest to fisheries, no study has been published on S
. japonicus. This paper examines the population structure of chub mackerel in the South West
Atlantic Ocean based on genetic variation at 16 protein-coding loci and seven morphologic characters. Moreover, we summarize current information on growth,
migration and spawning time and propose a possible mechanism to explain the observed patterns with regard to the water circulation of the area. We also compare levels of
genetic diversity and differentiation with the North Atlantic population Mediterranean Sea.
2. Methods
2.1. Sample collection Chub mackerels 136–423 mm total length were caught at about 50 m depth by
INIDEP’s research vessels in the Argentinian Sea and immediately frozen with dry ice. ´
´ Two geographical areas, Rıo de la Plata sample 1: 358269S, 548319W and El Rincon
sample 2: 408129S, 608099W, were sampled N 5 102 during May and August 1996, respectively. The Mediterranean sample was captured in December 1997 sample 3:
468509N, 58159E approximately in front of Pals Fig. 1. All individuals were stored at 2808C prior to electrophoretic analysis.
2.2. Genetic analysis Tissue extractions, electrophoresis and procedures for visualizing proteins generally
followed the methods outlined by Aebersold et al. 1987. Extracts from liver, eye and skeletal muscle were electrophoretically screened for resolution and activity with the
buffer systems and stain procedures detailed in Table 1. Genetic interpretations of these patterns followed the principles outlined by Utter et al. 1987. Alleles were denoted
according to their mobility relative to the most commonly observed allele, which was assigned a mobility of 100 units. Genetic nomenclature follows Shaklee et al. 1990.
Genotypic distributions of all loci were tested for conformance to Hardy–Weinberg expectations using the exact probabilities test. Allele frequency differences among
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.I. Roldan et al. J. Exp. Mar. Biol. Ecol. 253 2000 63 –74 65
Fig. 1. South West Atlantic distribution of Scomber japonicus diagonal lines, spawning area grey, samples sites 1 and 2 and Mediterranean sample site 3.
samples were tested by contingency chi-square, and the sequential Bonferroni technique Rice, 1989 was used to adjust significance levels. Within-sample variation was
assessed by mean unbiased expected heterozygosity per locus He Nei, 1978. Genetic differentiation of populations was assessed by F-statistics Wright, 1978. Pairwise
multilocus comparisons between samples were calculated by Nei genetic distance Nei, 1972 and Cavalli-Sforza and Edwards chord distance Cavalli-Sforza and Edwards,
1967.
2.3. Morphologic analysis Six morphometric length measurements Table 2 and a meristic character Table 3
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M .I. Roldan et al. J. Exp. Mar. Biol. Ecol. 253 2000 63 –74
Table 1
a
Enzyme systems, loci abbreviations and tissues with strongest expression in S . japonicus
Enzyme E.C. No.
Locus Tissue
Buffer Stain
Aspartate aminotransferase 2.6.1.1
AAT- 1
L, E 2, 4, 5, 1
1 AAT-
2 M, L, E
Creatine kinase 2.7.3.2
CK- 2
M, L, E 2, 3, 6, 1
1 CK-
3 M
Esterase 3.1.1.-
EST- 2
M, L, E 3, 1
1 Fumarate hydratase
4.2.1.2 FH
L, M 6, 4, 1, 2
1 b-N-Acetylgalactosaminidase
3.2.1.53 bGALA
L 3, 2, 6, 4
1 Glyceraldehyde-3-phosphate
1.2.1.12 GAPDH-
1 M, L
5, 2 1
dehydrogenase GAPDH-
2 M, L, E
Glycerol-3-phosphate 1.1.1.18
G 3PDH-1
M 4, 5, 6, 2,
1 dehydrogenase
G 3PDH-2
M, L, E 3
N-Acetyl-b-glucosaminidase 3.2.1.30
bGLUA L
6 3
Glucose-6-phosphate
b
dehydrogenase 1.1.1.49
G 6PDH
M, L, E 7, 6, 4, 3
2 Glucose-6-phosphate isomerase
5.3.1.9 GPI-
1 M
4, 3, 1 1
GPI- 2
E Glutamate dehydrogenase
1.4.1.2 GLUDH
L 3, 5
1 Glutation reductase
1.6.4.2 GR
L 3, 1
1
b
Isocitrate dehydrogenase 1.1.1.42
IDHP- 1
M 2
2 IDHP-
2 M, L
b
L
-Lactate dehydrogenase 1.1.1.27
LDH- 1
M, L 2, 4, 1, 3
2 LDH-
2 E
LDH- 3
M, L, E Lactoylglutathione lyase
4.4.1.5 LGL
M, L, E 1, 5, 3
1
b
Malate dehydrogenase 1.1.1.37
MDH- 2
M, L, E 2
2 MDH-
3 M, L, E
MDH- 4
M, L, E MDH-
5 M, L, E
1 b
Malic enzyme NADP 1.1.1.40
MEP- 1
M, E 2
2 Malic enzyme NAD
1.1.1.39 MEL
M, L, E 2
4 a-Manosidase
3.2.1.24 aMAN
L 3, 2, 4, 6
3 Peptidase leucyl-glycyl-glycine
3.4.-.- PEP-LGG
M, L, E 4, 5
3 Peptidase leucyl-tyrosine
3.4.-.- PEP-LT
M, L, E 4, 5
3 Phosphoglucomutase
5.4.2.2 PGM-
2 M, L, E
2, 4, 1 1
Phosphogluconate dehydrogenase 1.1.1.4
PGDH L, M
2 1
Pyruvate kinase 2.7.1.40
PK- 2
M, L, E 3, 6, 2, 1
5 Superoxide dismutase
1.15.1.1 SOD
M, L, E 2, 5, 1
1
a
Buffers: 1, TC LB; 2, AC; 3, Poulik; 4, TBE; 5, TBE1NAD; 6, TP; 7, TP1NADP. Stains: 1, Aebersold et al. 1987; 2, Allendorf et al. 1977; 3, Jorde et al. 1991; 4, Verspoor and Jordan 1989; 5, Pasteur et al.
1988.
b
Stain modified with agar 2.
were taken in a subsample from each location. These characters were defined according to Cousseau and Cotrina 1980, Perrotta et al. 1990 and Roby et al. 1991 and
selected based on their diagnostic value observed in previous works Perrotta et al., 1990; Perrotta and Aubone, 1991; Perrotta, 1993. To avoid allometric effects according
to the logarithmic transformation procedure of Terry et al. 1988 and Perrotta et al. 1990, all measurements y were standardized to a selected size of reference, which
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.I. Roldan et al. J. Exp. Mar. Biol. Ecol. 253 2000 63 –74 67
Table 2
a
Estimates of the power function by linear regression analysis Sample
Relation Ln a
b r
´ Rıo de la Plata
Lc Lt 0.444
0.639 0.769
N 5 35 B1 Lt
23.457 1.048
0.769 B2 Lt
21.701 0.908
0.757 Dp1 Lt
20.132 0.808
0.787 Dp2 Lt
20.007 0.910
0.920 Io Lt
24.279 1.246
0.796 ´
El Rincon Lc Lt
20.403 0.797
0.970 N 5 32
B1 Lt 22.018
0.773 0.709
B2 Lt 20.876
0.768 0.922
Dp1 Lt 21.132
0.976 0.984
Dp2 Lt 20.606
1.001 0.989
Io Lt 21.659
0.771 0.863
Pals Lc Lt
20.599 0.850
0.972 N 5 19
B1 Lt 23.243
0.991 0.881
B2 Lt 22.000
0.948 0.920
Dp1 Lt 20.900
0.953 0.984
Dp2 Lt 20.412
0.975 0.987
Io Lt 22.189
0.863 0.882
a
Lt, total length; Lc, head length; B1, mouth width; B2, mandible length; Dp1 and Dp2, snout to dorsal 1 and 2 distances; Io, interorbital length. All variables in mm.
was 264.09 mm total length average length of total samples. The relationship between
b
y versus Lt total length is y 5 aLt , which in lineal form is ln y 5 ln a 1 b ln Lt, where b is the allometric coefficient Table 2. Principal components analysis and discriminant
functions analysis were performed Bouroche and Saporta, 1983 by AMACP and AMDIS software.
3. Results
