Allozyme evidence of the bigeye croaker (Micropogonias megalops) fishery collapse in the Upper Gulf of California.
The bigeye croaker, Micropogonias megalops (Gilbert), is a coastal bottom-dwelling species, and is one of the 100 reported species of the family Sciaenidae in the eastern Pacific. Members of the family are an important component in the coastal fisheries catch in the eastern Pacific (Chao 1995). The bigeye croaker has a restricted distribution (Allen and Robertson 1994; Chao 1995) and was formally considered endemic to the Gulf of California (Castro-Aguirre 1978). The fishery formally began in the Upper Gulf of California (UGC) in the 1990s (Cudney-Bueno and Turk-Boyer 1998) with a maximum capture of 5,200,000 kg and a sudden decrease at the end of the decade to 1,500,000 kg. The bigeye croaker fishery was developed as a socioeconomic alternative to the prohibited totoaba fishery, Totoaba mcdonaldi, and the low capture rate of shrimp. The high demand for bigeye croaker by the Korean surimi industry supported the fishery and reduced the social problem caused by the depletion of the traditional fishery-capture species (Cudney-Bueno and Turk-Boyer 1998). Unpublished fishery studies of bigeye croaker suggest instituting a catch reduction as a precautionary measure to avoid overexploitation (Roman-Rodriguez et al. 2000). However lack of fishery regulations is allowing declining catches, and the lack of knowledge of the abundance and population structure imperils its permanency and stability in the UGC. This fishery is being depleted.
Molecular indicators of bigeye croaker population structure are nonexistent. Genetic studies of other sciaenid species in the Pacific and Atlantic coasts are available, but are inappropiate for comparisons (Bartley and Kent 1990; Beckwitt 1983; Levy et al. 1998; Suzuki et al. 1983; Ramsey and Wakeman 1987; Wakeman and Ramsey 1988; Gold et al. 1988, 1993; Bohlmeyer and Gold 1991; Gold and Richardson 1994; Crawford et al. 1988; Ramsey and Wakeman 1987).
Data related to fisheries, genetic variability, and population structure of bigeye croaker are necessary to design an effective capture effort for the management of the fishery. This paper evaluates the allozyme variability of bigeye croaker in the UGC to lay the foundations for management and conservation.
One hundred and thirty specimens of M. megalops were collected from the commercial fishery in the UGC. Fifty-five specimens were collected in April 1998 in fishing zone 1 (Fig. 1), where a fishery of outboard-motor boats that use 100-mm gill nets operates. This fishery has its base in El Golfo de Santa Clara, Sonora, inside the Upper Gulf of California and Colorado River Delta Biosphere Reserve (UGCRBR). Sixty-five fish were collected from January to March 1999 from fishing zone 2, where a bottom-gear trawler fishery based in Puerto Penasco, Sonora operates, outside of the UGCRBR, using 100-mm nets. Tissue samples of skeletal muscle, liver, heart, and eyes were taken from each fish, frozen at -20[degrees]C in the field, stored at -70 [degrees]C in the laboratory, and analyzed for allozyme variation.
[FIGURE 1 OMITTED]
Approximately five grams of muscle and liver, and the whole heart and eyes were macerated individually in an equal volume of 0.1 M TRIS.HCl, pH 8.0, NAD, NADP and Polyvinyl-pyrrolidone solution (100:0.1:0.1:1, v:w:w:w), and homogenates were centrifuged at 3500 rpm for 20 minutes at 4 [degrees]C. The extracts were stored at -70 [degrees]C until analysis. Horizontal 12% starch (Sigma S4501) gel electrophoresis (Aebersold et al. 1987) was used in the analysis of 20 enzymatic systems with four buffer solutions (Table 1). Preliminary screening resolved 47 loci, and at least 30 loci showed enough activity and good resolution to be genetically interpreted for each sampled zone (Table 1). Grant and Utter (1980) and Grant et al. (1984) were followed for the zymogram interpretation. Locus nomenclature follows Shaklee et al. (1990), which designates the loci in ascending order beginning with number 1 for the most cathodal locus. A locus was considered polymorphic if the frequency of the most common allele did not exceed 0.95. Alleles for polymorphic loci were designated by relative electrophoretic mobility with the most common allele at each locus designated as "100".
Data from zymograms were analyzed with BIOSYS-1 (Swoford and Selander 1981) and Genepop (Raymond and Rousset 1995). Genetic variability was assessed using the mean heterozygosity (Ho) and the unbiased estimate of mean expected heterozygosity per locus under random mating (He) (Nei 1978), and the proportion of polymorphic loci (P). Deviations of genotype frequencies from those expected under Hardy-Weinherg equilibrium hypothesis was tested for all polymorphic loci by means of a Chi-square test, pooling genotypes when more than two alleles were observed. All Chi-square tests were appropriately corrected for multiple tests with the sequential Bonferroni procedure (Rice 1989). Genetic similarity and distance (Nei 1978) between fishing zones were calculated. An evaluation of deficiency and excess of heterozygosity was made by D = (Ho-He)/ He. The standardized variance in allelic frequencies ([F.sub.ST]), the inbreeding coefficient ([F.sub.IT]), and the inbreeding coefficient in the fishing zones ([F.sub.IS]) were calculated to assess inbreeding and genetic differentiation among fishing zones (Wright 1965). The null hypothesis [F.sub.IS] = 0 was tested by means of [chi square] = [F.sub.IS.sup.2]n, with k[(k-1).sup.2] degrees of freedom, where "n" is the sample size and "k" denotes number of alleles (Li and Horvitz 1953). The null hypothesis [F.sub.ST] = 0 was tested by means of [chi square] = 2N[F.sub.ST](k-1), with (s-1)(k-1) degrees of freedom, where "N" is the number of individuals, "s" is the number of geographic locations and "k" the number of alleles (Workman and Niswander 1970). To prove genotypic independence, [chi square] analysis among pairs of polymorphic loci was carried out (Weir 1996). The heterogeneity of allelic frequencies at polymorphic loci was tested with the log-likelihood ratio test (G-test) with Yates's correction for continuity (Zar 1984). The number of migrants per generation was estimated by [N.sub.e]m = ([Fst.sup.-1]-1)/4 (Hartl 1988).
Forty-seven loci from 20 enzymatic systems were detected. Thirty loci from 14 enzymatic systems showed suitable activity for consistent scoring (Table 1). The loci EST-2*, EST-3*, XDH-2*, and SOD* were polymorphic and the rest were monomorphic. Table 2 summarizes the genetic variation from both locations. The total average sampled size was 56.7 [+ or -] 1.00. Total observed and expected heterozygosity were 0.010 [+ or -] 0.006 and 0.050 [+ or -] 0.030. The average number of alleles per locus was 1.50 [+ or -] 0.80. Polymorphism of 13% was recorded for both fishing zones.
All polymorphic loci significantly deviated from the equilibrium of Hardy-Weinberg before and after the correction for multiple simultaneous tests using the sequential Bonferroni procedure. Heterozygote deficiency for all polymorphic loci was detected and values were from -1.000 to -0.442 for both fishing zones. According to Fisher exact test, nine pairs of loci had linkage disequilibrium in all samples (MDH-1/MDH-2*, MDH-1*/LDH-1*, MDH-1*-2/EST-3*, MDH-1*/ XDH-1*, LDH-1*/XDH-1*, MDH-1*/ADH-1*, MDH-2*/ADH-2*, LDH-1*/ADH-1 *, MDH-1*/SOD*).
The absence of the faster allele EST-2*114 was detected for fishing zone 2 (Table 3). Monomorphic loci MDH-1*, MDH-2*, and LDH-1*, which did not show enough variation to reach the 0.95 criterion, showed the indistinct absence of low frequency alleles between fishing zones.
The analysis of heterogeneity of allelic frequencies showed EST-2* and XDH-2* with highly significant differences and a total G = 25.206 (P<0.001), which means a strong difference between fishing zones (Table 4). The overall genetic identity between fishing zones varied between 1.000 and 0.888 and the genetic distance from 0.000 to 0.119 for all polymorphic loci. The weighted average Fis was 0.862 and the weighted average Fst was 0.027, both different from zero, and Fit was 0.849 (Table 4). Using the Fst value, the estimated number of migrants per generation was 9 migrants every generation.
The mean heterozygosity (Ho) can be used to evaluate population structure in coastal fisheries. Comparison of mean Ho between different species at different times results in imprecise conclusions for fishery management. However, the Ho of M. megalops (0.010 [+ or -] 0.006) in the UGC was low compared to the Ho reported by Nevo (1978) (0.051 [+ or -] 0.003) for 60 and Ward et al. (1994) (0.064 [+ or -] 0.004) for 57 marine fish species, and to the estimates proposed by Smith and Fujio (1982) (0.055 [+ or -] 0.036) for 106 marine teleost species. Though comparisons with other underexploited populations of the sciaenid family are not valid, Cynoscion nebulosus has a lower Ho than the bigeye croaker (0.009 [+ or -] 0.005, Ramsey and Wakeman 1987), whereas other sciaenids show higher values (M. furnieri 0.055, Levy et al. 1998; Sciaenops ocellatus 0.029 [+ or -] 0.017, Ramsey and Wakeman 1987 and 0.047, Bohlmeyer and Gold 1991; Atractoscion nobilis 0.044, Bartley and Kent 1990; Genyonemus lineatus 0.030, and Seriphus politus 0.043, Beckwitt 1983).
The low Ho of the bigeye croacker may be caused by the small number of polymorphic loci detected. Ward et al. (1994) showed that subpopulation heterozygosity was significantly less in freshwater than marine fish, suggesting that marine fish subpopulations have a higher gene flow than freshwater subpopulations or restricted-distribution species. Nevo (1978) and Smith and Fujio (1982) suggested that many factors are involved in the expression of the genetic variability, and some could be related to distribution of the species. Several authors suggest that genetic variability in marine fish will also be influenced by the mobility of each species (Selander and Kaufman 1973), niche variability or divergence in time (Somero and Soule 1974), effective population size (Fujio and Kato 1979), ecological heterogeneity (Nevo 1978; Smith and Fujio 1982), and environmental variation (Mitton and Lewis 1989). Endemic fishery species like M. megalops apparently show a low genetic variability and low average number of alleles per locus because of a complex of factors beyond the natural expression of the species.
Significant deviation from the Hardy-Weinberg equilibrium for all polymorphic loci, the heterogeneity in allele frequencies detected by contingency Chi-square analysis, and the small but significant value of Fst suggest a complex population structure despite the small or restricted distribution. Absence of the allele EST-2*114 from fishing zone 2 and the lack of low mobility alleles from MDH-1 *, MDH-2 *, and LDH-1 * are also indicators of genetic structure. Several authors suggest the absence or reduced level of population structuring in sciaenids (Beckwitt 1983; Ramsey and Wakeman 1987; Ward et al. 1994; Levy et al. 1998), which is inconsistent with our results. This sciaenid characteristic is usually associated with environmental conditions of life history parameters (Levy et al. 1998). However, inbreeding (Fis and Fit) and population difference indicators are concordant with the deficiency of heterozygotes. The low sample size as a technical consideration would usually explain our results, but a 57 average sample size was higher than suggested for allozyme variability studies (Allendorf and Phelps 1981). Large Fis value observed is not related to hermaphroditism or sex reversal, because there is not histological evidence to support it (Castro-Longoria, pers. comm.).
Gorman and Renzi (1979) showed that genetic variability was more affected by the number of loci included in the analysis than the number of specimens involved in the sample. Zymogram misinterpretation was reduced by involving only the loci in which banding pattern was clear and consistent for genetic interpretation. The Wahlund effect would be a side explanation (Maynard Smith 1989), but pooled analysis from both fishing zones show that heterozygote deficiencies were congruent with the deficiencies expressed in the analysis by fishing zone. The average polymorphism of 13% ([P.sub.0.95]) was very close to values detected in other studies of sciaenids (Beckwitt 1983; Ramsey and Wakeman 1987) and high levels of variation in polymorphism were observed for those species. No differences in polymorphism from both fishing zones of M. megalops reduce the application of this indicator of genetic variability. Ayala and Kiger (1984) mention this characteristic of animal genomes as imprecise and arbitrary.
Apparently enough migrants per generation ([N.sub.e]m = 9.0) are not concordant with differences between molecular indicators. On average, Ward et al. (1994) concluded that marine subpopulations exchange 10 to 100 more migrants per generation than restricted distribution species like freshwater subpopulations, presumably because of the relative absence of barriers to dispersal in the marine environment. However, one migrant per generation will be enough to homogenize allelic differences between fishing zones (Slatkin 1987). Natural selection, a fragmented gene pool, and low fish abundance in the reduced occupational distribution appear to be responsible for the genetic structuring of the bigeye croaker in the UGC in the face of genetic flow.
G and Fst indicators of differences among fishing zones of M. megalops are complementary to evidence of low heterozygosity, low number of alleles per locus, and deviation from Hardy-Weinberg expectations for all polymorphic loci. They form conclusive evidence of genetic variability erosion, and the reduction in population size is now evident through allozyme analysis. The fishing pressure is one of the more determining factors in this decreased genetic variability in this restricted distribution species in the Gulf of California. Effective population size estimations of M. megalops in the UGC are nonexistent. Official monthly landing captures of the entire fishery were recovered by SEMARNAP (Ministry of Environment, Natural Resources, and Fisheries, by its initials in Spanish). Capture was 2,346,000 kg in 1997, 4,030,000 kg in 1998, and 5,180,000 kg in 1999 (Portillo-Balderrama and Pedrin-Osuna, pers. comm.). Sampling protocols for this study and subsamples of the specimens from commercial fishery of the bigeye croaker in the UGC report an average weight of 0.5 kg/fish. In a conservative estimation of the level of specimen extraction from the UGC, according the official landing, more than 12 million specimens were taken from 1997-1998, and more than 10 million in 1999. A low-level capture in 2000 was evident, and no restriction measure was made by the federal government because of the lack of precise information of catch per unit effort. Additionally, the volume of illegal catch not included in the official data, and the incidental catch by shrimp trawlers, which was reported as an important volume of catch by several authors in the UGC and in the entire Gulf of California (Perez-Mellado and Findley 1985; Cudney-Bueno and Turk-Boyer 1998), were not included in the final accounting. The high capture reported results in a reduced population, causing genotypic disequilibrium as a final consequensce (Van-Doornik and Winans 1998).
Another sciaenid, Totoaba macdonaldi, an endangered marine fish endemic to the Gulf of California, has been, for a long time, an example of population disequilibrium through fishing pressure (Barrera-Guevara 1990; Lagomarsino 1991). Smith et al. (1991) measured the loss of genetic diversity in the orange roughy, Hoplostethus atlanticus, as an integral consequence of heavy exploitation of natural populations. The authors although were not testing the correlation between the heterozygosity and the fish size, their results suggest that fishing activities differentially remove the largest and oldest individuals from virgin stocks and could have a significant influence on the genetic structure of a commercially important species. There are a lack of molecular studies for the bigeye croaker to compare with our data and to measure the impact of the fishery. However, genetic variability and inbreeding indicators from the allozyme study must be a primary tool in the baseline data required to keep a sustainable fishery through appropriate management practices inside and outside of the UGCRBR. Sladek-Nowlis and Roberts (1999), based on fishery population models, show that marine reserves are a viable fishery management alternative. They predict that a reserve will enhance catch from any overfished population that meets the key assumptions that adults did not cross reserve boundaries and that larvae mixed thoroughly across the boundary but were kept sufficient to produce a stock-recruitment relationship for the management area. Little evidence exists of fast recuperation levels in natural overexploited populations after a prolonged decline. However overfishing effects on a single species fishery could be reversible (Hutchings 2000).
Regulations and model assumption applications in the bigeye croaker fishery for the management and population recovery may include a fishing moratorium inside the UGCRBR. Although the social impact associated with prohibition could be disastrous to local fisherman, implementation of a fishery program for the species should permit a level of population recovery adequate to sustain a regulated fishery activity and conservation of the species outside of the UGCRBR. The only alternative to assure M. megalops as fishery resource is a well-designed fishery management plan incorporated into the traditional economic activities in the UGCRBR.
Table 1. Enzymatic systems assayed, buffers, detected and analyzed loci, and tissues of the bigeye croaker M. megalops in the Upper Gulf of California. N.C.E. = Enzyme Commission Number (IUBNC 1984); (-) Loci analyzed. Buffers: A = TRIS Citrate 7.0 (Ayala et al. 1973); B = TRIS Malate 7.4 (Selander et al. 1971); C = TRIS Citrate 8.0 (Selander et al. 1971), D = TRIS Citrate 8.7 (Poulik 1957); E = TRIS EDTA Borate 8.0 (Shaw and Koen 1968). Stain: 1 = Shaw and Prasad (1970); 2 = Shcaal and Anderson (1974); 3 = Abreu-Grobois (1983); 4 = Rosa-Velez (1986). Enzymatic systems N.C.E. Locus Aspartate aminotransferase 188.8.131.52 - AAT-1 * - AAT-2 * AAT-3 * Acid phosphatase 184.108.40.206 - ACP * Alcohol dehydrogenase 220.127.116.11 - ADH-1 * ADH-2 * ADH-3 * Alkaline phosphatase 18.104.22.168 - AKP * Esterase 3.1.1.- - EST 2 * - EST-3 * - EST-5 * Glycerol-3-phosphate dehydrogenase 22.214.171.124 G3PDH-1 * - G3PDH-2 * - G3PDH-3 * Glucose-6-phosphate dehydrogenase 126.96.36.199 G6PDH-1 * G6PDH-2 * Glyceraldehyde-3-phosphate dehydrogenase 188.8.131.52 GAPDH * Glutamate dehydrogenase 184.108.40.206 - GDH-1 * - GDH-2 * - GDH-3 * GDH-4 * Glucose-6-phosphate dehydrogenase 220.127.116.11 GPI-1 * GPI-2 * Isocitrate dehydrogenase 18.104.22.168 - IDH-1 * IDH-2 * Lactate dehydrogenase 22.214.171.124 - LDH-1 * - LDH-2 * Malic enzyme 126.96.36.199 MEZ * Malate dehydrogenase 188.8.131.52 - MDH-1 * - MDH-2 * Octanol dehydrogenase 184.108.40.206 ODH-1 * ODH-2 * Phosphoglucomutase 220.127.116.11 PGM * General protein - - PTO-1 * - PTO-2 * - PTO-3 * - PTO-4 * - PTO-5 * Sorbitol dehydrogenase 18.104.22.168 SDH-1 * - SDH-2 * - SDH-3 * - SDH-4 * Superoxide dismutase 22.214.171.124 - SOD * Xanthine dehydrogenase 126.96.36.199 XDH-1 * - XDH-2 * - XDH-3 * - XDH-4 * Enzymatic systems Tissue Buffer Stain Aspartate aminotransferase Liver D 2 Heart Liver Acid phosphatase Liver D 1 Alcohol dehydrogenase Liver B 1 Eye Eye Alkaline phosphatase Liver D 1 Esterase Liver E 1 Liver Muscle Glycerol-3-phosphate dehydrogenase Muscle E 2 Muscle Liver Glucose-6-phosphate dehydrogenase Liver A 2 Liver Glyceraldehyde-3-phosphate dehydrogenase Muscle C 2 Glutamate dehydrogenase Liver E 2 Muscle Liver Muscle Glucose-6-phosphate dehydrogenase Liver C 1 Muscle Isocitrate dehydrogenase Liver B 3 Liver Lactate dehydrogenase Eye C 1 Eye Malic enzyme Muscle B 2 Malate dehydrogenase Eye C 1 Eye Octanol dehydrogenase Liver B 1 Liver Phosphoglucomutase Muscle C 2 General protein Muscle D 4 Muscle Muscle Muscle Muscle Sorbitol dehydrogenase Muscle E 2 Liver Muscle Liver Superoxide dismutase Liver E 1 Xanthine dehydrogenase Eye E 2 Liver Muscle Liver Table 2. Genetic variability of the bigeye croaker M. megalops in two fishing zones of the Upper Gulf of California. Santa Clara Number of specimens 55 Number of analyzed loci 30 Number of polymorphic loci (0.95) 4 % polymorphic loci 13.33 Average number of alleles per locus 1.50 [+ or -] 0.20 Sample size per locus 51.6 [+ or -] 0.80 Mean heterozygosity Observed 0.012 [+ or -] 0.007 Expected 0.070 [+ or -] 0.032 Puerto Penasco Number of specimens 65 Number of analyzed loci 30 Number of polymorphic loci (0.95) 4 % polymorphic loci 13.33 Average number of alleles per locus 1.53 [+ or -] 0.18 Sample size per locus 61.7 [+ or -] 1.20 Mean heterozygosity Observed 0.008 [+ or -] 0.005 Expected 0.060 [+ or -] 0.029 Table 3. Allelic and phenotypic frequencies, and heterozygosity under the Hardy-Weinberg equilibrium for the polymorphic loci of the bigeye croaker M. megalops in the Upper Gulf of California. Loc = Locality; SC = Santa Clara; PP = Puerto Penasco. * = P < 0.05. Allelic frequencies Locus Loc 93 96 100 104 109 114 EST-2 * SC 0.100 0.382 0.382 0.055 0.018 0.064 (55) PP 0.040 0.254 0.484 0.032 0.190 0.000 (63) 98 100 103 EST-3 * SC 0.127 0.818 0.055 (55) PP 0.092 0.877 0.031 (65) 95 100 111 XDH-2 * SC 0.302 0.585 0.113 (53) PP 0.560 0.380 0.060 (50) 71 100 148 SOD * SC 0.209 0.745 0.045 (55) PP 0.109 0.875 0.016 (64) Phenotypic Heterocygosity frequencies Locus Ob Exp Phenotype Obs Exp [chi square] EST-2 * 0.164 0.697 100/100 19 7.899 126.00 * 110/114 4 2.697 114/114 0 0.193 114/96 3 2.697 96/96 19 7.899 96/109 1 0.771 93/93 5 0.505 93/109 1 0.202 109/109 0 0.009 104/104 3 0.138 0.063 0.668 100/100 30 14.640 141.27 * 100/109 1 1.952 96/96 15 3.968 96/109 2 1.024 93/93 2 0.080 93/109 1 0.160 104/104 12 2.208 EST-3 * 0.000 0.314 100/100 45 36.743 95.31 * 103/103 7 0.835 98/98 3 0.138 0.000 0.223 100/100 57 49.930 107.15 * 103/103 6 0.512 98/98 2 0.047 XDH-2 * 0.000 0.559 100/100 31 18.010 97.75 * 95/95 16 4.724 111/111 6 0.629 0.000 0.544 100/100 19 7.101 88.25 * 95/95 28 15.556 111/111 3 0.152 SOD * 0.402 0.145 100/100 37 30.468 41.57 * 100/148 1 3.761 100/71 7 17.303 148/148 2 0.092 71/71 8 2.321 0.125 0.224 100/100 52 48.945 13.71 * 100/148 2 1.764 100/71 6 12.346 148/148 0 0.008 71/71 4 0.717 Table 4. Chi-square test for the analysis of heterogeneity of allelic frequencies and F-statistics for the polymorphic loci of bigeye croaker M. megalops in the Upper Gulf of California. G = log-likelihood ratio test, Ns = P > 0.05; * = 0.01 < P < 0.05; ** = 0.001 < P < 0.01; *** = P < 0.001. Locus Alleles G Fis [chi square] EST-2 * 6 14.072 ** 0.832 408.12 *** EST-3 * 3 0.535 ns 1.000 240.00 *** XDH-2 * 3 7.151 ** 1.000 206.00 *** SOD * 3 3.446 ns 0.564 75.71 *** TOTAL 15 25.206 *** 0.862 930.12 *** Locus Fit Fst [chi square] EST-2 * 0.835 0.019 22.42 * EST-3 * 1.000 0.005 2.40 ns XDH-2 * 1.000 0.049 20.19 ** SOD * 0.589 0.022 10.47 ** TOTAL 0.849 0.027 55.48 **
Research herein was funded by Fondo Mexicano para la Conservacion de la Naturaleza A.C. (project C1-253). Also, we thank the director and personnel of the Reserva de la Biosfera Alto Golfo de California y Delta del Rio Colorado and Instituto del Medio Ambiente y Desarrollo Sustentable del Estado de Sonora for all the logistic support provided for developing this study. The Secretaria de Educacion Publica provided complementary funds for this research (PROADU 99-18-26-001-052). Thanks to Dr. Ellis Glazier for editing this English-language text. Thanks to Carl Safina and a anonymous reviewer for the improvement of the manuscript.
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Accepted for publication 11 September 2003.
Alejandro Varela-Romero * and Jose Manuel Grijalva-Chon
Universidad de Sonora, Departamento de Investigaciones Cientificas y Tecnologicas, Rosales y Ninos Heroes s/n. Hermosillo, Sonora, 8300, Mexico
* Author to whom correspondence should be sent.
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|Author:||Varela-Romero, Alejandro; Grijalva-Chon, Jose Manuel|
|Publication:||Bulletin (Southern California Academy of Sciences)|
|Date:||Aug 1, 2004|
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