10 resultados para Genetic Variance-covariance Matrix

em Aquatic Commons


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ENGLISH: The map method, the Jones method, the variance-covariance method, and the Skellam method were used to study the migrations of tagged yellowfin tuna released off the southern coast of Mexico in 1960 and 1969. The first three methods are all useful, and each presents information which is complementary to that presented by the others. The Skellam method, as used in this report, is less useful. The movements of the tagged fish released in 1960 appeared to have been strongly directed, but this was probably caused principally by the distribution of the fishing effort. The effort was much more widely distributed in 1970, and the movements of the fish released in 1969 appeared to have been much less directed. The correlation coefficients derived from the variance-covariance method showed that it was not random, however. The small fish released in the Acapulco and 10°N-100°W areas in 1969 migrated to the Manzanillo area near the beginning of February 1970. The medium and large fish released in the same areas in the same year tended to migrate to the southeast throughout the first half of 1970, however. SPANISH: El método de mapas, el de Jones, el de la variancia-covariancia y el de Skellam fueron empleados para estudiar las migraciones del atún aleta amarilla marcado y liberado frente a la costa meridional de México en 1960 y 1969. Los tres primeros métodos son todos útiles, y cada uno presenta información que complementa la presentada por los otros. El método de Skellam, conforme se usa en este informe, es menos útil. Parece que los desplazamientos de los peces marcados y liberados en 1960 hubieran sido fuertemente orientados, pero ésto probablemente fue causado principalmente por la distribución del esfuerzo de pesca. El esfuerzo se distribuyó más extensamente en 1970, y parece que los desplazamientos de los peces liberados en 1969 fueran menos orientados. Los coeficientes de correlación derivados del método variancia-covariancia indicaron, sin embargo, que no eran aleatorios. Los peces pequeños liberados en las áreas de Acapulco y los 10°N-100°W en 1969 migraron al área de Manzanillo a principios de febrero 1970. Los peces medianos y grandes liberados en las mismas áreas en el mismo año tuvieron, sin embargo, la tendencia a desplazarse al sudeste durante el primer semestre de 1970. (PDF contains 64 pages.)

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Genetic structure and average long-term connectivity and effective size of mutton snapper (Lutjanus analis) sampled from offshore localities in the U.S. Caribbean and the Florida Keys were assessed by using nuclear-encoded microsatellites and a fragment of mitochondrial DNA. No significant differences in allele, genotype (microsatellites), or haplotype (mtDNA) distributions were detected; tests of selective neutrality (mtDNA) were nonsignificant after Bonferroni correction. Heuristic estimates of average long-term rate of migration (proportion of migrant individuals/generation) between geographically adjacent localities varied from 0.0033 to 0.0054, indicating that local subpopulations could respond independently of environmental perturbations. Estimates of average longterm effective population sizes varied from 341 to 1066 and differed significantly among several of the localities. These results indicate that over time larval drift and interregional adult movement may not be sufficient to maintain population sustainability across the region and that there may be different demographic stocks at some of the localities studied. The estimate of long-term effective population size at the locality offshore of St. Croix was below the minimum threshold size considered necessary to maintain the equilibrium between the loss of adaptive genetic variance from genetic drift and its replacement by mutation. Genetic variability in mutton snapper likely is maintained at the intraregional level by aggregate spawning and random mating of local populations. This feature is perhaps ironic in that aggregate spawning also renders mutton snapper especially vulnerable to overexploitation.

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A total of 1006 king mackerel (Scomberomorus cavalla) representing 20 discrete samples collected between 1996 and 1998 along the east (Atlantic) and west (Gulf) coasts of Florida and the Florida Keys were assayed for allelic variation at seven nuclear-encoded microsatellites. No significant deviations from Hardy-Weinberg equilibrium expectations were found for six of the microsatellites, and genotypes at all microsatellites were independent. Allele distributions at each microsatellite were independent of sex and age of individuals. Homogeneity tests of spatial distributions of alleles at the microsatellites revealed two weakly divergent “genetic” subpopulations or stocks of king mackerel in Florida waters—one along the Atlantic coast and one along the Gulf coast. Homogeneity tests of allele distributions when samples were pooled along seasonal (temporal) boundaries, consistent with the temporal boundaries used currently for stock assessment and allocation of the king mackerel resource, were nonsignificant. The degree of genetic divergence between the two “genetic” stocks was small: on average, only 0.19% of the total genetic variance across all samples assayed occurred between the two regions. Cluster analysis, assignment tests, and spatial autocorrelation analysis did not generate patterns that were consistent with either geographic or spatial-temporal boundaries. King mackerel sampled from the Florida Keys could not be assigned unequivocally to either “genetic” stock. The genetic data were not consistent with current spatial-temporal boundaries employed in stock assessment and allocation of the king mackerel resource. The genetic differences between king mackerel in the Atlantic versus those in the Gulf most likely stem from reduced gene flow (migration) between the Atlantic and Gulf in relation to gene flow (migration) along the Atlantic and Gulf coasts of peninsular Florida. This difference is consistent with findings for other marine fishes where data indicate that the southern Florida peninsula serves (or has served) as a biogeographic boundary.

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Atlantic menhaden (Brevoortia tyrannus), through landings, support one of the largest commercial fisheries in the United States. Recent consolidation of the once coast-wide reduction fishery to waters within and around Chesapeake Bay has raised concerns over the possibility of the loss of unique genetic variation resulting from concentrated fishing pressure. To address this question, we surveyed variation at the mitochondrial cytochrome c oxidase subunit I (COI) gene region and seven nuclear microsatellite loci to evaluate stock structure of Atlantic menhaden. Samples were collected from up to three cohorts of Atlantic menhaden at four geographic locations along the U.S. Atlantic coast in 2006 and 2007, and from the closely related Gulf menhaden (B. patronus) in the Gulf of Mexico. Genetic divergence between Atlantic menhaden and Gulf menhaden, based on the COI gene region sequences and microsatellite loci, was more characteristic of conspecific populations than separate species. Hierarchical analyses of molecular variance indicated a homogeneous distribution of genetic variation within Atlantic menhaden. No significant variation was found between young-of-the-year menhaden (YOY) collected early and late in the season within Chesapeake Bay, between young-of-the-year and yearling menhaden collected in the Chesapeake Bay during the same year, between YOY and yearling menhaden taken in Chesapeake Bay in successive years, or among combined YOY and yearling Atlantic menhaden collected in both years from the four geographic locations. The genetic connectivity between the regional collections indicates that the concentration of fishing pressure in and around Chesapeake Bay will not result in a significant loss of unique genetic variation.

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For study the genetic diversity of Caspian brown trout population in five rivers in the southern part of Caspian Sea in Iran 182 number generators in the fall and winter of 1390 were collected in Chalus, Sardab Rud, Cheshmeh Kileh, Kargan Rud and Astara rivers. Then about 3-5 g of soft and fresh tissue from the bottom fin fish removed and were fixed in ethanol 96°. Genomic DNA was extracted by using ammonium acetate, then quantity and quality of the extracted DNA were determined by using spectrophotometry and horizontal electrophoresis in 1% agarose gel. The polymerase chain reaction was performed by using 16 SSR primers and sequencing primers (D-Loop) and the quality of PCR products amplified by SSR method were performed by using horizontal electrophoresis in 2% agarose gel. Alleles and their sizes were determined by using vertical electrophoresis in 6% polyacrylamide gel and silver nitrate staining method. Gel images were recorded by gel documentarian, the bands were scored by using Photo- Capt software and statistical analysis was performed by using Gene Alex and Pop Gene software. Also the PCR sequencing products after quality assessment by usinghorizontal electrophoresis in 1.5% agarose gel were purified and sent to South Korea Bioneer Corporation for sequencing. Sequencing was performed by chain termination method and the statistical analysis was performed by using Bio- Edit, Mega, Arlequin and DNA SP software. The SSR method, 5 pairs of primers produced polymorphic bands and the average real and effective number of alleles were calculated 5.60±1.83 and 3.87±1.46 in the Cheshmeh Kileh river and 7.60±1.75 and 5.48±1.32 in the Karganrud river and the mean observed and expected heterozygosity were calculated 0.44 ±0.15 and 0.52 ±0.16 in the Cheshmeh Kileh river and 0.50 ±0.11 and 0.70±0.13 in the Karganrud river. Analysis of Molecular Variance results showed that significant differences in genetic diversity between and within populations and between and within individuals in the studied rivers (P<0.01). The sequencing method identified 35 different haplotype, the highest number of polymorphic position (251) and haplotype (14) were observed in the Chalus river. The highest mean observed number of alleles (2.24±0.48) was calculated in the Sardabrud river, the highest mean observed heterozygosity (1.00±0.03) was calculated in the Chalus river and the highest mean nucleotide diversity (0.13±0.07) was observed in the Sardabrud river and mean haplotype diversity was obtained (1) in three studied rivers. The overall results show that there are no same population of this fish in the studied rivers and Karganrud and Chalus rivers in the SSR and sequencing methods had the highest levels of genetic diversity.

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Platycephalus indicus is a large benthic fish that inhabits temperate and tropical coastal waters of the Indo-West Pacific and found on sand or mud bottom in vary shallow area of estuary and near shore to depth of 25m. This species is dominant species of platycephalidae family, in Khuzestan, Bushehr and Hormozgan provinces and mainly is captured by bottom trawl, gillnet and moshta in Hormozgan. This study was designed to evaluate population variation and differentiation of bartail flathead (Platycephalus indicus (Linnaeus, 1785))in the Iranian waters of Persian Gulf using the morphometric and meristic characters and by AFLP marker. . A total 180 fish specimens were collected by gill net from six station(khor mosa, bahrekan, shif, motaf, charak and bandar abbas) that was 30 individual related to every station in Iranian shores of Persian Gulf . 28 morphometric factors and 11meristic specialties were measured and morphometric factors was standardized with Beacham formula. Univariate analysis of variance (One-way ANOVA) revealed significant differences with varying degrees between the means for 21 standardized morphometric measurements and 6 meristic counts that showed high significant differences between the six stations sampling. Discriminate function analysis (DFA) or the overall random assignment of individuals into their original groups was for morphometric and meristic characters was 47.9% and 53.9% respectively. The data were subjected to a principle component analysis (PCA) which grouped in eight and four factors for morphometric and meristic charactersrespectively.. Genetic diversity of six populations of bartail flathead (Platycephalus indicus) was investigated using amplified fragment length polymorphism (AFLP). A total of 118 reproducible bands amplified with ten AFLP primer combinations were obtained from 42 fishes that were collected from six different locations in the northern of Persian Gulf. The percentage of polymorphic bands was 57.06%. Average of Nei’s genetic diversity was 0.200±0.008, and Average of Shannon’s index was 0.300±0.011. The results of AMOVA analysis indicated that 66% of the genetic variation contained within populations and 34% occurred among populations and gene flow was 0.6454.The estimated level of population differentiation asmeasured by average Fst value across all loci was 0.327. Plotting discriminant functions 1 and 2 and UPGMA dendrograms based on Euclidian distance and genetic distance also showed at least five separate populations of bartail flathead in the northern Persian Gulf.

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In order to carry out Biometric studies, 75 samples were caught from 3 locations ( Tajan river, Sefidrud and Shirud) using Salic and the length (±1 mm) and weights (± 5 gr) of samples were determined. Using One-way ANOVA by SPPSS software, there wasn’t significant difference between locations in length and fecondity (P ≥0.01(, but there was significant difference between Shirud and tajan samples with sefidrud in weight ) P≤0.01(. In order to carry out genetic variation studies, 210 fish were caught from 3 different regions of the Iranian coastline (Khoshkrud, Tonekabon, Gorganrud) and 1 region in Azerbaijan (Waters of the Caspian Sea close to Kura River mouth) during 2008-2009 . Genomic DNA was extracted of fin using the phenol-chloroform. The quantity and quality of DNA from samples were assessed by spectrophptometer and 1% agarose gel electro-phoresis. PCR was carried out using 15 paired microsatellite primers. PCR products were separated on 8% polyacrylamide gels that were stained using silver nitrate. Molecular weight calculate using UVTech software. The recorded microsatellite genotypes were used as input data for the GENALEX software version 6 package in order to calculate allele and genotype frequencies, observed (Ho) and (He) expected heterozygosities and to test for deviations from Hardy-Weinberg equilibrium. Genetic distance between two populations was estimated from Nei standard genetic distance and genetic similarity index (Nei, 1972). Genetic differentiation between populations was also evaluated by the calculation of pairwise estimates of Fst and Rst values. From 15 SSR markers were used in this investigation, 9 of them were polymorph. Average of expected and observed heterozygosity was 0.54 and 0.49 respectively. Significant deviations from Hardy-Weinberg expectations were observed in all of location except Anzali lagoon- autumn in AF277576 and EF144125, Khoshkrud in EF144125 and Gorganrud and Kura in AF277576. Using Fst and Rst there was significant difference between locations ) P≤0.01(. According to Fst , the highest population differentiation (Fst= 0.217) was between Gorganrud and Khoshkrud that have the lowest Nm and the lowest (Fst= 0.086) was between Gorganrud and Tonekabon that have the highest Nm. Using Rst the highest population differentiation (Rst= 0.271) was between Tonekabon and spring Anzali lagoon and the lowest (Rst= 0.026) was between Tonekabon and Autumn Anzali 159 lagoon. Also the difference between Spring Anzali lagoon and Autumn Anzali lagoon was noticeable (Fst=0.15). AMOVA analysis with consideration of 2 sampling regions (Iran and Azerbaijan) and 7 sampling locations (Iran: Khoshkrud, Tonekabon, Gorganrud, Spring Anzali lagoon and Autumn Anzali lagoon ; Azerbaijan: the Kura mouth) revealed that almost all of the variance in data namely 83% )P≤0.01( was within locations, Genetic variances among locations was 14% )P≤0.01( and among regions was 3% )P≤0.01(. The genetic distance was the highest (0.646) between Gorganrud and Autumn Anzali lagoon populations, whereas the lowest distance (0.237) was between Gorganrud and Tonekabon River. Result obtained from the present study show that at least 2 different population of Rutilus frissi kutum are found in the Caspian sea,which are including the kura river population and the southern Caspian sea samples and it appears that there is more than one population in southern Caspian sea that should be attantioned in artifical reproduction Center and stoke rebilding.

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A total of 361 caudal fin samples were collected from adult A. stellatus specimens caught in the north Caspian Sea, including specimens from Kazakhstan (Ural River), Russia (Volga River), Azerbaijan (Kura River), specimens caught in the south Caspian Sea including specimens from Fishery Zone 1 (from Astara to Anzali), Fishery Zone 2 (from Anzali to Ramsar), Fishery Zone 3 (from Nowshahr to Babolsar), Fishery Zone 4 (from Miyankaleh to Gomishan) as well as from specimens caught in Turkmenistan (all specimens were collected during the sturgeon stock assessment survey). About 2 g of fin tissue was removed from each caudal fin sample, stored in 96% ethyl alcohol and transferred to the genetic laboratory of the International Sturgeon Research Institute. Genomic DNA was extracted using phenol-chloroform method. The quality and quantity of DNA was assessed using 1% Agarose gel electrophoresis and Polymerase Chain Reaction (PCR) was conducted on the target DNA using 15 paired microsatellite primer. PCR products were electrophoresed on polyacrylamide gels (6%) that were stained using silver nitrate. Electrophoretic patterns and DNA bands were analyzed with BioCapt software. Allele count and frequency, genetic diversity, expected heterozygosity and observed heterozygosity allele number, and the effective allele number, genetic similarity and genetic distance, FST and RST were calculated. The Hardy Wienberg Equilibrium based on X2 and Analysis of Molecular Variance (AMOVA) at 10% confidence level was calculated using the Gene Alex software. Dendrogram for genetic distances and identities were calculated using TFPGA program for any level of the hierarchy. It is evident from the results obtained that the 15 paired primers studied, polymorphism was observed in 10 pairs in 12 loci, while one locus did not produce DNA bands. Mean allele number was 13.6. Mean observed and expected heterozygosity was 0.86 and 0.642, respectively. It was also seen that specimens from all regions were not in Hardy Wienberg Equilibrium in most of the loci (P≤0.001). Highest Fst (0.063) was observed when comparing specimens from Fishery Zone 2 and Fishery Zone 4 (Nm=3.7) and lowest FST (0.028) was observed when comparing specimens from the Volga River and those from the Ural River (8.7). Significant differences (P<0.01) were observed between RST recorded in the specimens studied. Highest genetic distance (0.604) and lowest genetic resemblance (0.547) were observed between specimens from Fishery zones 2 and 4. Lowest genetic distance (0.311) and highest genetic resemblance (0.733) was observed between specimens from Turkmenistan and specimens from Fishery zone 1. Based on the genetic dendrogeram tree derived by applying UPGMA algorithm, A. stellatus specimens from Fishery zone 2 or in other words specimens from the Sepidrud River belong to one cluster which divides into two clusters, one of which includes specimens from Fishery zones 1, 3 and 4 and specimens from Turkmenistan while the other cluster includes specimens from Ural, Volga and Kura Rivers. It is thus evident that the main population of this species belongs to the Sepidrud River. Results obtained from the present study show that at least eight different populations of A. stellatus are found in the north and south Caspian Sea, four of which are known populations including the Ural River population, the Volga River population, the Kura River population and the Sepidrud River populations. The four other populations identified belonging to Fishery zones 1, 3, and 4 and to Turkmenistan are most probably late or early spawners of the spring run and autumn run of each of the major rivers mentioned. Specific markers were also identified for each of the populations identified. The Ural River population can be identified using primers Spl-68, 54b and Spl-104, 163 170, 173, the Volga River population can be identified using primers LS-54b and Spl-104, 170, 173 113a and similarly the population from the Kura River can be identified using primers LS-34, 54b and Spl-163, 173 and that from the Sepidrud River can be identified using primers LS-19, 34, 54b and Spl-105, 113b. This study gives evidence of the presence of different populations of this species and calls for serious measures to be taken to protect the genetic stocks of these populations. Considering that the population of A. stellatus in Fishery zone 2 is an independent population of the Sepidrud River in the Gilan Province, the catch of these fishes in the region needs to be controlled and regulated in order to restore the declining stocks of this species.

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The genetic structure of pikeperch (Sander lucioperca) and perch (Perca fluviatilis) populations was studied using microsatellite technique. A total of 207 specimens of adult pikeperch were collected from Aras dam (57 specimens), Anzali wetland (50 specimens), Talesh (50 specimens) and Chaboksar (50 specimens) coasts. Also a total of 158 specimens of adult perch were collected from Anzali (Abkenar (50 specimens)and Hendekhale(48 specimens)) and Amirkolaye(60 specimens) wetlands. About 2 g of each specimen's dorsal fin was removed, stored in 96% ethyl alcohol and transferred to the genetic laboratory of the International Sturgeon Research Institute. Genomic DNA was extracted using ammonium-acetate method. The quality and quantity of DNA was assessed using 1% agarose gel electrophoresis. Polymerase Chain Reaction (PCR) was conducted on the target DNA using 15 pairs of microsatellite primers. PCR products were electrophoresed on poly acryl amide gels (6%) that were stained that were stained using silver nitrate. DNA bands were analyzed with BioCapt software. Allele count and frequency, genetic diversity, expected and observed heterozygosity , allele number and the effective allele number, genetic similarity and genetic distance, Fst, Rst, Hardy Weinberg Equilibrium based on X2 and Analysis of Molecular Variance (AMOVA) at 10% confidence level was calculated using the Gene Alex software. Dendogram for genetic distances and identities were calculated using TFPGA program for any level of hierarchy. The results for P. fluviatilis showed that from 15 pair of primers that were examined 6 polymorphic and 7 monomorphic loci were produced, while 2 loci didn't produce any DNA bands. Mean allele number was 4.1±1.1 and mean observed and expected heterozygosity was 0.56±0.12 and 0.58±0.14 respectively. It was also seen that specimens from all regions were not in Hardy Weinberg Equilibrium in some of loci (P<0.001). Highest Fst (0.095) with Nm=2.37 was observed between Hendekhale and Amirkolaye and the lowest Fst (0.004) with Nm=59.31 was observed between Abkenar and Hendekhale. According to AMOVA Significant difference (P<0.05) was observed between recorded Rst in the studied regions in Anzali and Amirkolaye lagoons. In another words there are two distinct populations of this species in Anzali and Amirkolaye lagoons. The highest genetic distance (0.181) and lowest genetic resemblance (0.834) were observed between specimens from Hendekhale and Amirkolaye and the lowest genetic distance (0.099) and highest genetic 176 resemblance (0.981) were observed between specimens from Abkenar and Hendekhale. Based on the genetic dendogram tree derived by applying UPGMA algorithm, specimens from Anzali and Amirkolaye wetlands have the same ancestor. On the other hand there is no noticeable genetic distance between the specimens of these two regions. Also the results for S. lucioperca showed that from 15 pair of primers that were examined 6 polymorphic and 7 monomorphic loci were produced, while 2 loci didn't produce any DNA bands. Mean allele number was 3.0±0.6 and mean observed and expected heterozygosity was 0.52±0.21 and 0.50±0.14 respectively. It was also seen that specimens from all regions were not in Hardy Weinberg Equilibrium in some of loci (P<0.001). Highest Fst (0.093) with Nm=2.43 was observed between Aras dam and Anzali wetland and the lowest Fst (0.022) with Nm=11.27 was observed between Talesh and Chaboksar coasts. Significant differences (P<0.05) were observed between recorded Rst in the studied regions exept for Talesh and Chaboksar Coasts. In another words there are three distinct populations of this species in Caspian sea, Anzali wetland and Aras dam. Highest genetic distance (0.110) and lowest genetic resemblance (0.896) were observed between specimens from Aras dam and Anzali wetland and the lowest genetic distance (0.034) and highest genetic resemblance (0.966) were observed between specimens from Talesh and Chaboksar coasts. Based on the genetic dendogram tree derived by applying UPGMA algorithm, specimens from Talesh and Chaboksar coasts have the lowest genetic distance. On the other hand the main population of this species belongs to Anzali wetland. Phylogenetic relationship of these two species was inferred using mitochondrial cytochrome b gene sequencing. For this purpose 2 specimens of P. fluviatilis from Anzali wetland, 2 specimens of S. lucioperca from Aras dam and 2 specimens of S. lucioperca from Anzali wetland were sequenced and submitted in Gene Bank. These sequences were aligned with Clustal W. The phylogenic relationships were assessed with Mega 4. The results of evolutionary history studies of these species using Neighbor-Joining and Maximum Parsimony methods showed that the evolutionary origin of pikeperch in Aras Dam and Anzali wetland is common. On the other hand these two species had common ancestor in about 4 million years ago. Also different sequences of any region specimens are supposed as different haplotypes. 177 As a conclusion the results of this study showed that microsatellite and mtDNA sequencing methods respectively are effective in genetic structure and phylogenic studies of P. fluviatilis and S. lucioperca.

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Sardines and other Microfilidae have very important ecological role in marine ecosystems because they are first consumers in marine food chain and they are the main food of valuable species as tuna. So decries in their population will decline fishing of these spices. There are 10 genus of Clupeidae in south of Iran and Sardinella is the one of the most abundant of them. In this study we investigated about morphological and genetically differences in population of 3 species: Sardinella sindensis, Sardinella abella, Dussomieria acuta. About 65 specimens of Sardinella sindensis, 61 specimens of Sardinella albella and 63 specimens of, Dussomieria acuta from three regions of their distribution: Jask (Oman Sea), Qeshm (Hormoz) and Lengeh (Pearsian Gulf) have been collected. Morphological research of their characters and statistical studies were done. To determine the genetically structure of specie's population we sequenced 500 bp of mitochondrial control region. Genetical studies determine meaningful difference in alleles and heterozigosity frequency of Sardinella sindensis. This must be the result of divergence in population of this species. Morphological investigation of Sardinella albella shows the meaningful difference. But detailed studies diffused it. Genetical studies show a meaningful variance in allele and heterosigosity frequency. This may be an aspect of sardine tendency to live in estuaries. Morphological research of Dussomieria acuta in Jask and Lengeh show a meaningful variance in these regions. Such a situation might be result of Monsoon, upwelling and better weather which occur in Oman Sea in spite of Persian Gulf.