Morphological Variability of Liza Aurata (Risso, 1810), Along the Southern Caspian Sea

The Journal of Basic & Applied Zoology (2014) 67, 100–107

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Morphological variability of Liza aurata (Risso, 1810), along the southern Caspian Sea

Huseyn Khayyami *, Abdolali Movahedinia, Hossein Zolgharnein, Negin Salamat

Khorramshahr University of Marine Science and Technology, Iran

Received 13 July 2014; revised 18 September 2014; accepted 18 September 2014 Available online 18 October 2014

KEYWORDS Abstract Morphological variability of Liza aurata (Risso, 1810), was studied in traditional Morphological differentia- morphometric measurements in 25 morphological characters from 90 specimens in three fishery tion; areas in the southern Caspian Sea (Guilan, Mazandaran and Golestan). Univariate analysis of Phenotype plasticity; variance showed significant differences between the means of the three groups for 22 out of 25 stan- Distance effect; dardized morphometric measurements. In discriminant function analysis (DFA), the proportion of Environmental effect; individuals correctly classified into their original groups was 100%. Principal component analysis Mugilidae results (PCA) for morphometric data indicated that samples of Guilan and Mazandaran showed high degree of overlap and these two regions were highly different from Golestan. The dendrogram derived from cluster analysis showed that the samples of L. aurata from Guilan and Mazandaran had same clade while both were obviously distinct from Golestan. ª 2014 The Egyptian German Society for Zoology. Production and hosting by Elsevier B.V. All rights reserved.

Introduction the years 1930–1934, scientists from the former Soviet Union introduced different mullet species, including the golden mullet The golden grey mullet, Liza aurata is a mugilidae species in (L. aurata), from the Black Sea to the Caspian Sea. The intro- which adults are neritic usually in schools, entering lagoons duction of L. aurata was successful, and it is currently of high and lower estuaries (Thomson, 1990). Golden grey mullet hab- economic importance (Ghelichi et al., 2004; Thomson, 1997; itats in eastern Atlantic, Mediterranean and Black Sea during Zenkevich, 1956). In the catch composition in the southern Caspian Sea, the golden grey mullet, L. aurata, predominated in the years 1995–2009, accounting for 76–98% of the catch * Corresponding author at: Khorramshahr University of Marine (Fazli, 2011). Golden grey mullet in the Caspian Sea spends Science and Technology, Khorramshahr City, Khuzestan Province, spring in the north and autumn in the south (Probatov and Iran. Tel.: +98 9399231628. Tereshchenko, 1951). They feed on small benthic organisms, E-mail addresses: [email protected], Huseyn_khayyami@ detritus, and occasionally on insects and plankton (Ben- hotmail.com (H. Khayyami), [email protected] (A. Movahedinia), [email protected] (H. Zolgharnein), Tuvia, 1986). L. aurata is one of threatened species with least [email protected] (N. Salamat). concern which is in red list (IUCN, 2012). Study of fishes in Peer review under responsibility of The Egyptian German Society for aquatic ecosystem is important from point of evolution, ecol- Zoology. ogy, behaviour, conservation, water resource management http://dx.doi.org/10.1016/j.jobaz.2014.09.003 2090-9896 ª 2014 The Egyptian German Society for Zoology. Production and hosting by Elsevier B.V. All rights reserved. Morphological variability of Liza aurata (Risso, 1810) 101 and stock assessment (Anvarifar et al., 2011). Suitable management success of aquatic animal stock will be gained by study of genetic stock of endemic species, and identification of populations (Coad, 1980). To rational and effective fishery management, determination of exploitive fish stock is too important, because each stock needs separate management to aim of optimal harvest (Erguden and Turan, 2005; Salini et al., 2004). The study of morphological characters with the aim of defining or characterizing fish stock units has for some time been a strong interest in ichthyology (Tudela, 1999). Golden grey mullet has been broadly studied, in terms of biological characteristics (Fazli, 1998), age and growth (Andaloro, 1983; Fazli et al., 2008; Ilkyaz et al., 2006; Kraljevic et al., 2011; Mehanna, 2006), reproduction (Ghaninejad et al., 2010; Hotos et al., 2000), systematic status (Turan et al. 2011), distribution and migration (Mickovic et al., 2010), genetic diversity (Ghodsi et al., 2011), and phylogenetic relationships (Turan et al., 2005). However, information on popu- Figure 1 Map of the southern Caspian Sea showing the location lation differentiation of adult specimens in the Southeastern of fishing regions (1– Guilan, 2 – Mazandaran and 3 – Golestan) Caspian Sea is still rather limited (Kohestan-Eskandari et al., for Liza aurata (Risso, 1810). 2013). In addition, it is important to understand that this unit population has morphological differentiation. The aim of the present study was to examine the morphological variation of L. aurata in the southern Caspian Sea basin to evaluate the differences between golden grey mullet community runs to be employed in the future enhancement programs to maintain this valuable species in the sea.

Material and method

Sampling

A total of 90 adult individuals of L. aurata were collected from three northern provinces of Iran in February 2014, that comprising 30 individuals from Guilan (37290N, 49260E), 30 individuals from Mazandaran (36360N, 52100E) and 30 individuals from Golestan (36560N, 53590E) (Fig. 1). The Figure 2 Codes of morphological characters investigated in Liza specimens were caught by beach seine and preserved in 4% aurata (Risso, 1810), along the southern Caspian Sea. formalin and sent to the marine biology laboratory of Khorramshahr University of Marine Science and Technology.

b Laboratory work Madj ¼ MðLs=L0Þ

where M is original measurement, Madj is the size adjusted 25 traditional morphometric characters were measured in cen- measurement, L0 is the standard length of the fish, Ls the over- timetres using a digital caliper to the nearest 0.01 mm (Fig. 2); all mean of standard length for all fish from all samples in each measurements followed Ibanez-Aguirre et al. (2006), Kastelis analysis, and b was estimated for each character from the et al. (2006), Konan et al. (2014) and Rezaei et al. (2012).To observed data as the slope of the regression of logM on logL0 avoid human error all morphological measurements were per- using all fishes in any group. The results derived from the allo- formed by the same person. After measuring, fish was dissected metric method were confirmed by testing the significance of the to identify the sex by macroscopic examination of the gonads. correlation between transformed variables and standard Gender was used as the class variable in ANOVA to test for length. Univariate analysis of variance (ANOVA) was per- the significant differences in the morphometric characters if formed for each morphometric character to evaluate the signif- any, between males and females of L. aurata. icant difference between the three locations (Zar, 1984) and the morphometric characters that were significant were used for Data analysis function analyses (DFA) and principal component analysis (PCA). As a complement to discriminant analysis, morpho- As variation should be attributable to body shape differences, metric distances between the individuals of three groups were and not related to the relative size of the fish, an allometric inferred to cluster analysis (CA) (Veasey et al., 2001). Statisti- method (Elliott et al., 1995) was used to remove size-dependent cal analyses were performed using the SPSS version 21 soft- variation in morphological characters: ware package and Excel 2007. 102 H. Khayyami et al.

Table 1 Morphological character abbreviations and description and the results of ANOVA for morphological characteristics between two sexes of Liza aurata (Risso, 1810) along the southern Caspian Sea. Abbreviations Description Code F value P value TL Total length 1–10 .004 .952 FL Fork length 1–9 .052 .820 SL Standard length 1–8 .003 .975 BH Body height 4–14 .012 .966 PrD1 First predorsal distance 1–4 .017 .923 PrD2 Second predorsal distance 1–6 .015 .952 DFL1 First dorsal fin length 4–5 .001 .893 DFL2 Second dorsal fin length 6–7 .002 .872 CFL Caudal fin length 8–10 .019 .942 PrP Prepectoral distance 1–3 .017 .945 PrV Preventral distance 1–15 .051 .971 PrA Preanal distance 1–12 .015 .959 PFH Pelvic fin height 3–21 .002 .852 VFH Ventral fin height 15–22 .009 .812 PFL Pelvic fin length 19–20 .033 .945 VFL Ventral fin length 14–15 .031 .982 AFL Anal fin length 11–12 .021 .960 ED Eye diameter 2–17 .043 .950 SNH Snout to nose hole 1–18 .014 .909 AAF Anus to anal fin 12–13 .092 .716 PrOC Preoperculum distance 1–16 .001 .980 SA Snout to anus 1–13 .002 .977 NHs Nose holes .067 .797 HdW Head wide .047 .958 EW Eye wide .019 .894

Table 2 Results of ANOVA for morphological characters of Liza aurata (Risso, 1810), along the southern Caspian Sea. Abbreviations Guilan Mazandaran Golestan F value P value Mean ± S.D. Mean ± S.D. Mean ± S.D. TL 42.6 ± .61 42.7 ± .51 38.5 ± 1.31 218.8 .000 FL 34.8 ± 1.47 34.1 ± 1.34 32.9 ± .98 144.2 .000 SL 35.2 ± 1.21 38.7 ± 1.37 43.3 ± 1.76 1.8 0.112 BH 5.4 ± .46 5.5 ± .48 5.8 ± .71 3.1 .047 PrD1 15.9 ± .91 16.6 ± .54 15.6 ± .26 19. 3 .000 PrD2 25.3 ± .54 24.3 ± .27 22.1 ± .78 240.7 .000 DFL1 2.9 ± .31 2.6 ± .47 3.1 ± .28 12.5 .000 DFL2 2.8 ± .23 2.8 ± .23 3.2 ± .13 16.4 .000 CFL 7.2 ± .48 6.7 ± .64 6.4 ± .21 23.3 .000 PrP 8.9 ± .24 8.3 ± .15 8.4 ± .86 11.5 .000 PrV 17.9 ± 4.03 14.5 ± 1.63 11.1 ± .46 56.8 .000 PrA 27.2 ± 1.43 23.7 ± .64 23.8 ± .86 114.6 .000 PFH 6.6 ± .19 6.4 ± .17 7.5 ± 1.06 22.7 .000 VFH 3.5 ± .14 3.7 ± .07 5.1 ± .93 66.8 .000 PFL 1.5 ± .36 1.6 ± .29 1.9 ± .11 10.6 .000 VFL 1.4 ± .39 1.5 ± .42 1.8 ± .12 11.7 .000 AFL 3.2 ± .66 3.2 ± .39 3.4 ± .22 1.7 .179 ED 1.5 ± .14 1.4 ± .13 1.6 ± .13 3.7 .028 SNH .87 ± .13 .81 ± .13 .92 ± .19 7.4 .001 AAF .78 ± .14 .82 ± .14 1.1 ± .21 58.3 .000 PrOC 8.1 ± .31 7.8 ± .31 6.7 ± .47 115.6 .000 SA 24.7 ± .55 23.5 ± .37 20.7 ± .43 589.1 .000 NHs 2.2 ± .29 2.3 ± .28 2.3 ± .11 .61 .556 HdW 5.2 ± .29 5.1 ± .14 4.6 ± .13 56.6 .000 EW 4.4 ± .08 4.1 ± .38 4.1 ± .17 27.5 .000 Morphological variability of Liza aurata (Risso, 1810) 103

Table 3 Eigenvalues, percentage of variance and percentage of cumulative variance for the seven principal components in the case of morphometric variables of Liza aurata (Risso, 1810), along the southern Caspian Sea. Factor Eigenvalues Percentage of variance Percentage of cumulative variance PC1 10.776 46.854 46.854 PC2 5.156 22.417 69.271 PC3 2.86 12.436 81.708 PC4 1.357 5.9 87.607

Result others discarded (Table 3). Principal component analysis of 22 morphometric characters showed that PC I accounts for Morphological character abbreviations and the results of 46.854% of the variation and PC II for 22.417% (Table 3) ANOVA for morphological characteristics between two sexes and that the most significant weightings on PC I were from of L. aurata (Risso, 1810) from the southern part of Caspian TL, PrD2, PFH, VFH, AAF, PrOC, and SA and on PC II Sea are shown in Table 1. Interaction between morphometric were from DFL1, DFL2, PFL, and VFL and on PC III were characteristics used in this study and sex was not significant from PrP, PrA, and EW (Table 4). The rotated (Varimax) (p > 0.05), demonstrating a negligible effect of sex on component loadings for the four components (factors) are pre- observed variations (Table 1). There was no significant corre- sented in Table 4. Visual examination of plotted PC I and PC lation between any of the transformed measured morphomet- II scores for samples (Fig. 3) revealed that there were a rela- ric variables and standard length (p > 0.01) indicating that the tively high degree of overlap between two samples of L. aurata size effect was accounted for. Descriptive data for mean length from Guilan and Mazandaran on the southern part of the and standard deviation (S.D.) of sampled specimens are shown in Table 2. Differences (p < 0.05) between L. aurata of Guilan, Mazandaran and Golestan were observed for 22 out of 25 of the morphometric characters (Table 2). Significant traits were used for PCA, DFA and CA. Being KMO coefficient approx- imately more than 0.6, it indicates that the PCA method will be suitable for the data (Kaiser, 1974). In this study the KMO coefficient obtained was 0.869 that is explaining of appropria- tion of this test at good and medial levels. In this analysis the characteristics with an eigenvalue of 1 were included and

Table 4 Factor loadings for the seven principal components and correlations between the measured morphometric variables and the discriminant functions of Liza aurata (Risso, 1810), along the southern Caspian Sea. Abbreviations PC1 PC2 PC3 PC4 TL .862 FL BH PrD1 Figure 3 Plot of the factor scores for PC1 and PC2 of 22 PrD2 .87 morphometric characters for Liza aurata (Risso, 1810), along the DFL1 .836 southern Caspian Sea. DFL2 .874 CFL PrP .921 PrV Table 5 Percentage of specimens classiﬁed in each group and PrA .865 after cross validation for morphometric characters of Liza PFH .855 VFH .94 aurata (Risso, 1810), along the southern Caspian Sea. PFL .939 Original Guilan Mazandaran Golestan VFL .953 Guilan 100 0 0 ED Mazandaran 0 100 0 SNH Golestan 0 0 100 AAF .825 PrOC .95 Cross validated SA .809 Guilan 100 0 0 HdW Mazandaran 0 100 0 EW .754 Golestan 0 0 100 104 H. Khayyami et al.

Figure 4 Coordinate plot of Liza aurata (Risso, 1810), along the southern Caspian Sea according to the ﬁrst two discriminant functions from morphometric data analysis.

Caspian Sea, while both study areas (Guilan and Mazandaran) Discussion were distinct from Khuzestan in these regions (Fig. 3). For discriminant analysis, the averages of percentage of correctly This is one of the first reports on differentiations between the L. classified (PCC) were 100.0% for morphometric characters. aurata populations in the southern Caspian Sea basin High classification success rates were obtained for Guilan (Kohestan-Eskandari et al., 2013). Discriminant function anal- (100%), Mazandaran (100%) and Golestan (100%) stocks ysis could be a useful method to distinguish different stocks of a indicating a high correct classification of individuals into their same species, concern to stock management programs original populations with respect to morphometric characters (Karakousis et al., 1991). The results of DFA obtained in this (Table 5 and Fig. 4). The dendrogram derived from cluster study, demonstrated a high differentiation among the popula- analysis showed that the samples of L. aurata from Guilan tions of L. aurata in the study areas. The causes of morpholog- and Mazandaran on the southern part of the Caspian Sea ical differences between populations are often quite difficult to had same clade with great homogeneity and they were obvi- explain (Poulet et al., 2004). Although Laevastu and Favorite ously distinct from Golestan confirming the results obtained (1988) reported that behaviour of the fish in relation to the fish- from PCA and DFA (Fig. 5). ing gears might vary according to their body size, age and phys- iological condition, but being caught all fishes in same way (beach seine), clarifies this problem (Ibanez-Aguirre et al., 2006). The allometry among sexes would not be a cause of variability in this case, since there were no different variables among two sexes in L. aurata in the southern Caspian Sea. It is well known that morphological characteristics can show high plasticity in response to differences in environmental conditions. This raises the possibility that phenotypic plasticity may itself be adaptive, allowing stocks to shift their appearance to match their ecological circumstances (Swain and Foote, 1999). Therefore, the distinctive environmental conditions of Guilan, Mazandaran and Golestan may underlie the morphological differentiation between these three locations. Based on Figure 5 Dendrogram derived from cluster analyses of 22 our study, there are at least three distinct communities of L. morphometric variables of Liza aurata (Risso, 1810), along the aurata living in Guilan, Mazandaran and Golestan, confirming southern Caspian Sea. by different spawning times in mentioned areas. The spawning Morphological variability of Liza aurata (Risso, 1810) 105 peak for golden grey mullet in the waters of Guilan was in In the other hand, factor of size plays a predominant role in October whereas this peak was in November in Mazandaran morphometric analysis and make result in erroneous status if and Golestan waters. The magnitude of mullet spawning in it cannot be removed in statistical analyses of data (Tzeng, October tends to decline from west (Guilan waters) to east 2004). In present study, the size effect had been removed suc- (Golestan Province) in Iranian coastal water of the Caspian cessfully by allometric transformation, so any significant differ- Sea. Most of the spawning in December was in Golestan waters ences represented the body shape variation when it was tested (Ghaninejad et al. 2010). This segregation was confirmed by using ANOVA and multivariate analysis. In general, fishes another multivariate analysis, PCA, where the visual examina- demonstrate greater variance in morphological traits both tion of plotted PC I and PC II scores for each sample revealed within and between populations than other vertebrates, and that samples of Guilan and Mazandaran with a higher degree are more susceptible to environmentally induced morphologi- of overlap between two locations were distinct from each other cal variations (Thompson, 1991; Turan et al., 2006; with respect to morphometric characters and these two regions Wimberger, 1992), which might reflect different feeding envi- were highly different and distinct from Golestan. Discrimina- ronments, prey types, food availabilities or other features tion between regions can be explained by the life history of (Rezaei et al., 2012). Antovic and Simonovic (2006) surveyed the mullet, as they migrate to the ocean to spawn (Ibanez and interspecific variability and phenetic relationships in six south- Gutierrez-Benitez, 2004). The overlapping distribution of these ern Adriatic mullet species and declared that they were clearly samples may be attributable to extensive migration in these separated from the other species. Turan et al. (2011) investi- waters. There is no significant literature on the precise migra- gated the systematic relationships among four genera and nine tion of L. aurata in the Caspian Sea. Kohestan-Eskandari species of the Mugilidae family living in the Mediterranean Sea et al. (2013) revealed that there is no significant migration in and stated all species except Chelon labrosus and Oedalechilus L. aurata in the Caspian Sea and they have limited dispersal. labeo detected appreciable degree of morphologic differentia- Gonzalez-Castro et al. (2012) explained that non-contact pop- tion. So, various environmental factors may determine the phe- ulations of Mugilidae species, reflected broad shape differenti- notypic differentiation in the golden grey mullet. Results ation. It has been suggested that the morphological obtained from ANOVA analysis showed that 22 out of 25 characteristics of fish are determined by an interaction between transformed morphometric data were significantly different in genetic and environmental factors. As morphology is especially three groups of golden grey mullets living in the southern Cas- dependent on environmental conditions during early life his- pian Sea basin that demonstrates a high phenotypic variation tory stages (Lindsey, 1988), the environmental characteristics among these three populations. are of particular importance (Pinheiro et al., 2005; Tudela, 1999). So different spawning times occurring of early develop- Conclusion ment stages in different times may affect on early hatched individuals and influenced them phenotypically. L. aurata has a continuous distribution across a range. We studied three sta- The present study provided basic information about morpho- tions with a great distance from each other. The balance logical variability of L. aurata (Risso, 1810) populations from between gene flow and the forces responsible for population the southern part of the Caspian Sea and it suggests that there differentiation, such as genetic drift or differential selection, are at least three separated groups living in the southern Cas- may result in clines, whereby genetic differentiation increases pian Sea. Therefore morphological variations observed in with geographic distance (Borsa et al., 1997; Pinheiro et al., golden grey mullets should be considered in fishery manage- 2005). Kohestan-Eskandari et al. (2013) revealed that high ment and commercial exploitation of this species. Data were inbreeding and geographical separation by distance in L. aurata analysed by using multivariate methods to establish the value may cause morphological variabilities. They studied L. aurata of conducting deeper and more detailed morphological and in a lesser scale than this study and they reported at least two molecular analyses in the future. communities of L. aurata in a limited area. The phenotypic variability may not necessarily reflect population differentiation at Acknowledgement the molecular level (Tudela, 1999). Ghodsi et al. (2011) investigated the level of genetic variation of L. aurata in the southern We would like to express our sincere thanks to Dr. Ranjbar, Caspian Sea using microsatellite marker and they showed com- Dr. Hedayati, Dr. Varamesh, Dr. Ghahri, Mr. Aghaei and pulsory inbreeding of golden grey mullet lead to no conspicu- Mr. Lefteh for their help in specimen collection. ous genetic variations and accordingly a relatively high level of gene flow was found among populations. Also, they stated in result of irregular capturing, short time after introducing References to the Caspian Sea, closed environment and no connection with ocean waters can lead to decrease of genetic variation and Abdolhay, H.A., Daud, S.K., Rezvani, S., Pourkazemi, M., Siraj, S.S., increase of gene flow among populations. Abdolhay et al. Laloei, F., et al., 2012. Population genetic structure of Mahi Sefid (2012) showed that the high inbreeding happened in the Mah- (Rutilus frisii kutum) in south of the Caspian Sea: implications for isefid (Rutilus kutum) population, which is another economic fishery management. Iran. J. Anim. Biosyst. 8, 15–26. Andaloro, F., 1983. Contribution on the knowledge of the age and species in the Caspian Sea, can lead to low genetic variability growth of the Marsala Lagoon golden grey mullet, L. aurata in four populations of Mahisefid in the southern shores of the (Risso, 1810). Rapports Commission Internationale Mer Mediter- Caspian Sea. The morphological differences may be solely ranean 28, 81–82. related to body shape variation and not to size effects which Antovic, I., Simonovic, P., 2006. Phenetic relationships of six species of were successfully accounted for by allometric transformation. mullets (Mugilidae) from the south Adriatic, as inferred from the 106 H. Khayyami et al.

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