Environmental degradation can create noticeable changes in the biology of individuals and populations, possibly resulting in the extirpation of species (Koprivnikar et al. 2006). Additional indirect effects may result in decreased growth, increased disease vulnerability, and more significant morphological deformities (Jawad & Abed 2020). Rapid alerts to such negative impacts allow scientists and resource administrators to adopt corrective actions that may prevent additional habitat degradation and population failures.
One morphological characteristic associated with habitat changes and environmental impact is fluctuating asymmetry, defined as the arbitrary divergence from normal bilateral symmetry (Van Valen, 1962). The homeostatic regulation of morphological development may be adversely affected when individuals are subjected to either anthropogenic or natural impacts, which may be reflected in the development of bilateral asymmetry. Although no bilateral characters are perfectly symmetric, higher levels of asymmetry may result when organisms are subjected to various environmental impacts during their developmental process (Allenbach 2011). Asymmetry levels may also be affected by biological activities that individuals are subjected to, such as inbreeding (e.g., Leamy & Klingenberg 2005). Quantifying disparities in morphological traits represents a cheap method for defining the overall health rank of populations (Jawad & Abed 2020).
Pollution is reported to be the causative agent for several cases of skeletal deformities in fishes (Härdig et al. 1988). Pollutants can produce abnormal changes in the skeletal system of the fish in two ways, (1) by alteration of the biological processes necessary for maintaining the biochemical integrity of bone, or (2) through neuromuscular effects, which lead to deformities without a chemical change in vertebral composition (Raj et al. 2004). Trace elements such as cadmium and mercury can decrease collagen synthesis (Bhatnager & Hussain 1977). Arsenic binds certain enzymatic sulfhydryl groups, acting as a protoplasmic poison (Luh et al. 1973). Cadmium inhibits the cross-linking (i.e., stiffening) of collagen. It causes pathological bone changes that probably lead to the altered structural integrity of bone (Iguchi and Sano 1982) and reduced proline hydroxylation and collagen biosynthesis (Vistica et al. 1977). Pollutants might also act indirectly, increasing susceptibility to diseases and vertebral damage.
Oil is one source of trace metal pollution in the aquatic environment. Although oil dispersants make oil more bioavailable to oil-eating bacteria (Redmond & Valentine 2012), their short and long-term effects on marine flora and fauna have not been adequately elucidated (White et al. 2012). Rico-Martínez et al. (2013) measured the acute toxicity of dispersed crude oil on rotifers. They found that the combination of oil and dispersant produces higher toxicity than the use of only a single compound at a time (Ralph & Burchett 1998).
The Arabian yellowfin seabream,
The current investigation aimed to assess the levels of bilateral asymmetry in two common marine fish species found in brackish and freshwater environments in southern Iraq,
The Shatt al-Arab River and Shatt al-Basrah Canal are well known to be heavily polluted (Al-Saad et al 2015, Al-Hejuje et al. 2017, Hassan et al. 2018) and were therefore selected for the present study. A total of 200 fish specimens of
Since fish live in water, they directly react with this environment which also provides the food that enters their body and is metabolised (Yavuzcan et al. 2017). Therefore, water sampling was selected to indicate pollution in the studied areas. Before use, 5% nitric acid was added to the water sampling bottles and thoroughly washed with distilled de-ionised water. Al-Saad et al. (2015) followed the method for water sampling. Polyethene sampling bottles have been washed at least three times before sampling at each site. Clean polyethylene containers were dipped about 10 cm underneath the water surface. Approximately 0.5 l of water samples were taken at each station. Samples were acidified with 10% HNO3, cooled with ice on-site, and transported to the laboratory, where they were filtered through a 0.45 μm micropore membrane filter and retained at 4°C pending analysis.
As with water, sediment is considered a good indicator of the pollution load at a given location (Hahladakis et al. 2013). Consequently, samples of sediment were collected from the studied areas. Sediment samples were obtained using a grab sampler. They were taken to the laboratory and kept firmly closed at room temperature. Later, sediment samples were crushed and filtered through a 160 μm sieve. The sieved samples were packed in polyethylene bags and stored below -20°C before analysis. Samples were weighed, positioned into digestion bombs with 10 ml of HNO3/HCl (1:3 v/v), and digested in a microwave digestion system. Sediment analysis was carried out according to the methodology of Binning & Baird (2001).
Fish specimens were taken directly to the laboratory after being caught and kept on ice during the journey. The total length and weight of the fish were noted. All specimens were held at -30°C until analysis. The method of Bernhard (1976) was followed in the preparation and analysis of the fish samples. Before analysis, muscle tissues taken from the area above the pectoral fin were removed and whipped in a mixer, and one gram of the mixed material was digested. A microwave digestion system (CEM Mars 5 ESP 1500 PLUS) was utilised to prepare the specimens for analysis. Recently, microwave digestion procedures have frequently been used in investigations (Kucuksezgin et al. 2001), which involve rapid digestion and fewer chances of impurity throughout the process. Muscle tissues (without skin) were mixed with 5 ml HNO3 (65%) and 5 ml H2SO4 in polypropylene vials. After 10 minutes of mixing, 1 ml H2O2 was added, and samples were placed in a microwave (1 hour at 105°C). After digestion, the residues were diluted to 25 ml with HNO3 (0.3%)
Fe, Cu, Pb, Cr, Ni, and Cd were detected in all samples using ICP–AES (Varian-Terra Model Liberty II). Identification limits are summarised in Table 1. These limits represent the lowermost analytical levels differentiated regarding quality at a definite assurance value from background levels. The accuracy of the analytical method was tested by analysing comparable standard samples (water: SRM-143d, National Institute of Standards and Technology; sediment: CRM-277, Community Bureau of Reference; fish: DORM-2, National Research Council). Recovery rates ranged from 79 to 96% for all components analysed.
Spectral lines used in emission measurements and the instrumental detection limit for the elements measured by using ICP–AES
Element | Wave length (nm) | Instrumental detection limit (μg l-1) |
---|---|---|
Cd | 227.9 | 0.001 |
Cr | 268.7 | 0.006 |
Cu | 325.9 | 0.013 |
Fe | 258.6 | 0.07 |
Ni | 230.7 | 0.05 |
Pb | 221.5 | 0.05 |
The body features (Fig. 3) assessed for bilateral asymmetry in the current investigation were previously used in earlier reports (Jawad et al. 2010, 2016; Hechter et al. 2000). These morphological characteristics were proved to be quickly affected by environmental factors such as pollution (Jawad et al. 2010). The characters assessed included external features (4 characters) and meristic traits (2 features): (1) snout length (SnL); (2) eye diameter (ED); (3) head length (HL); (4) caudal peduncle length (CPL); (5) number of the lateral line scales (LLS); and (6) number of pectoral fin rays (PFR). External body features were computed to the nearest 0.1 cm using digital callipers. Lateral line scales were counted for
In the equation, we see this: Sl–r is the standard deviation of the signed variance, and Xl+r is the character’s mean, computed by totalling the absolute scores for both sides and dividing by the sample size. To remove variation related to growth in external traits (non-discrete, measurable), the body’s external attributes were divided by a predictable standardising measurement (head length, from the mouth to the posterior edge of the operculum). Every external feature was dealt with similarly, and the squared coefficient of asymmetry was determined. The ANOVA test evaluated the coefficients of asymmetry between the diverse total length groups. Further to the ANOVA test, a Tukey HSD post hoc test was used to assess whether the alterations were significant between couple assessments of length groups (StatSoft, Inc., 1991). Fish specimens were categorised into ranks for every character examined based on their total length. Three- and four-size ranks of fishes of both species were collected from both sampling sites. Coefficients of asymmetry were compared between the fish groups of each species and the collaborative groups using ANOVA tests.
Table 2 summarises the water quality constituents at the two sampling sites compared with reference freshwater values. Heavy metal concentrations in the waters of the Shatt al-Arab River and Shatt al-Basrah Canal were reduced in the sequence of Fe > Cu > Pb > Cr > Ni > Cd.
The heavy metal concentrations in the waters of the Shatt al-Arab River and Shatt al-Basrah Canal and comparison with guidelines and different literature (Mean ± SD) (mg l-1)
Location | Cd | Cr | Cu | Fe | Ni | Pb | Reference |
---|---|---|---|---|---|---|---|
Shatt al-Arab River | 0.02 ± 0.002 | 0.009 ± 0.005 | 0.01 ± 0.001 | 0.9 ± 0.4 | 0.004 ± 0.002 | 0.03 ± 0.007 | Present study |
Shatt al-Basrah Canal | 0.02 ± 0.012 | 0.059 ± 0.004 | 0.01 ± 0.003 | 0.89 ± 0.95 | 0.059 ± 0.006 | 0.025 ± 0.007 | |
Shatt al-Arab River | 3.01 | - | 2.35 | 89.45 | 9.51 | 7.58 | Al-Hejuje et al. 2017 |
WHO | 0.01 | 0.05 | 2 | - | 0.02 | 0.05 | WHO, 1993 |
EC | 5 | 50 | 2 | 0.2 | 20 | 10 | EC, 1989 |
Table 3 summarises the total concentrations of metals in the sediment samples at the two sampling sites compared with other sediments estimates that have been published worldwide. Heavy metal concentrations in the sediments of the Shatt al-Arab River and Shatt al-Basrah Canal were reduced in the sequence of Fe > Ni > Cu > Cr > Pb > Cd.
The heavy metal concentrations in the Shatt al-Arab River and Shatt al-Basrah Canal sediments and comparison with sediment quality guideline and different literature (Mean ± SD) (mg kg-1 dry weight)
Location | Cd | Cr | Cu | Fe | Ni | Pb | Reference |
---|---|---|---|---|---|---|---|
Shatt al-Arab River | 0.76 ± 0.4 | 84.47 ± 4.4 | 28.9 ± 4.7 | 25272 ± 920 | 29.71 ± 7.4 | 2.38 ± 2.1 | Present study |
Shatt al-Basrah Canal | 0.76 ± 0.1 | 13.41 ± 2.1 | 22.56 ± 9.8 | 22732 ± 4084 | 28.21 ± 6.7 | 4.03 ± 2.0 | |
Shatt al-Arab River | 0.17 – 2.8 | 81.8 – 112.4 | 21.8 – 44.0 | 5452 – 7584 | 530 – 811 | 11.3 – 28.1 | Abaychi and Douable 1985 |
Shatt al-Arab River | 0.3 | 48.1 | 39.6 | 6205 | 57.2 | 19.0 | Abaychi and Al-Saad 1988 |
The average concentrations of these metals in the muscle samples of
The heavy metal concentrations of
Location/species | Cd | Cr | Cu | Fe | Ni | Pb | Reference |
---|---|---|---|---|---|---|---|
Shatt al-Arab River | |||||||
0.18 ± 0.07 | 1.19 ± 0.73 | 3.85 ± 2.18 | 16.65 ± 6.99 | 1.28 ± 1.18 | 2.15 ± 2.09 | Present study | |
0.19 ± 0.06 | 1.20 ± 0.73 | 3.90 ± 2.20 | 16.95 ± 6.89 | 1.30 ± 1.19 | 2.17 ± 2.12 | ||
Shatt al-Basrah Canal | |||||||
0.17 ± 0.08 | 1.18 ± 0.74 | 3.81 ± 2.16 | 16.96 ± 6.79 | 1.29 ± 1.17 | 2.15 ± 2.10 | Present study | |
0.20 ± 0.05 | 1.19 ± 0.71 | 3.85 ± 2.13 | 16.99 ± 6.69 | 1.99 ± 6.69 | 2.17 ± 2.15 | ||
Avşar Dam Lake, Turkey | 0.17 ± 0.07 | 1.18 ± 0.73 | 3.85 ± 2.18 | 1116.55 ± 6.99 | 1.27 ± 1.18 | 2.14 ± 2.09 | Öztürk et al. 2009 |
The bilateral asymmetry results for six external body traits of
Squared coefficient asymmetry (CV2a) values and character means (
Location | Characters | ||||||
Snout length | Eye diameter | Head length | Caudal peduncle length | Pectoral fin ray count | Number of lateral line scales | ||
CV2a | Shatt al-Arab River | 89.371 | 78.874 | 63.412 | 75.981 | 65.412 | 77.982 |
Shatt al-Basrah Canal | 87.964 | 75.651 | 64.914 | 73.912 | 65.298 | 74.329 | |
N | Shatt al-Arab River | 50 | 50 | 50 | 50 | 50 | 50 |
Shatt al-Basrah Canal | 50 | 50 | 50 | 50 | 50 | 50 | |
Character mean (Xr + 1) | Shatt al-Arab River | 0.9 | 1.4 | 3.65 | 1.3 | 12.5 | 37 |
Shatt al-Basrah Canal | 0.80 | 1.29 | 3.59 | 1.29 | 12.40 | 36 | |
% of individuals with asymmetry | Shatt al-Arab River | 83 | 85 | 86 | 89 | 86 | 87 |
Shatt al-Basrah Canal | 81 | 82 | 82 | 86 | 81 | 82 | |
CV2a | Shatt al-Arab River | 92.751 | 81.376 | 61.286 | 79.518 | 73.298 | - |
Shatt al-Basrah Canal | 87.251 | 79.521 | 69.825 | 77.538 | 70.156 | - | |
N | Shatt al-Arab River | 50 | 50 | 50 | 50 | 50 | - |
Shatt al-Basrah Canal | 50 | 50 | 50 | 50 | 50 | - | |
Character mean (Xr + 1) | Shatt al-Arab River | 0.7 | 1.95 | 3.30 | 1.55 | 13.5 | - |
Shatt al-Basrah Canal | 0.6 | 1.86 | 3.29 | 1.53 | 13.3 | - | |
% of individuals with asymmetry | Shatt al-Arab River | 89 | 87 | 88 | 91 | 89 | - |
Shatt al-Basrah Canal | 76 | 74 | 81 | 89 | 87 | - |
Individuals of
Squared coefficient asymmetry (CV2a) values and character means (
Character | CV2a | N | Character mean | % of individuals with asymmetry |
---|---|---|---|---|
Shatt al-Arab River | ||||
Snout length | ||||
101 – 130 | 76.354 | 10 | 0.90 | 70 |
131 – 150 | 78.426 | 25 | 0.87 | 86 |
151 – 180 | 80.631 | 15 | 0.86 | 92 |
Eye diameter | ||||
101 – 130 | 65.981 | 10 | 1.40 | 67 |
131 – 150 | 67.421 | 25 | 1.38 | 87 |
151 – 180 | 72.332 | 15 | 1.40 | 93 |
Head length | ||||
101 – 130 | 77.541 | 10 | 3.64 | 88 |
131 – 150 | 79.981 | 25 | 3.62 | 79 |
151 – 180 | 81.321 | 15 | 3.65 | 91 |
Caudal peduncle length | ||||
101 -130 | 65.552 | 10 | 1.29 | 95 |
131 – 150 | 69.442 | 25 | 1.30 | 93 |
151 – 180 | 71.332 | 15 | 1.28 | 86 |
Number of pectoral fin rays | ||||
101 – 130 | 67.771 | 10 | 12.4 | 88 |
131 – 150 | 69.991 | 25 | 12.5 | 79 |
151 – 180 | 72.441 | 15 | 12.2 | 95 |
Number of lateral line scales | ||||
101 – 130 | 81.932 | 10 | 37 | 93 |
131 – 150 | 82.554 | 25 | 36 | 90 |
151 – 180 | 84.221 | 15 | 35 | 87 |
Shatt al-Basrah Canal | ||||
Snout length | ||||
101 – 130 | 55.221 | 10 | 0.79 | 88 |
131 – 150 | 56.551 | 25 | 0.80 | 76 |
151 – 180 | 57.112 | 15 | 0.78 | 82 |
Eye diameter | ||||
101 – 130 | 61.331 | 10 | 1.28 | 91 |
131 – 150 | 61.998 | 25 | 1.29 | 87 |
151 – 180 | 62.778 | 15 | 1.27 | 88 |
Head length | ||||
101 – 130 | 73.221 | 10 | 3.58 | 77 |
131 – 150 | 74.001 | 25 | 3.59 | 43 |
151 – 180 | 75.112 | 15 | 3.57 | 88 |
Caudal peduncle length | ||||
101 – 130 | 81.239 | 10 | 1.28 | 92 |
131 – 150 | 81.998 | 25 | 1.29 | 90 |
151 – 180 | 82.552 | 15 | 1.29 | 94 |
Number of pectoral fin rays | ||||
101 – 130 | 77.321 | 10 | 12.40 | 89 |
131 – 150 | 77.998 | 25 | 12.39 | 85 |
151 – 180 | 78.999 | 15 | 12.38 | 84 |
Number of lateral line scales | ||||
101 – 130 | 78.8871 | 10 | 36 | 78 |
131 – 150 | 78.999 | 25 | 36 | 89 |
151 – 180 | 79.932 | 15 | 36 | 95 |
Squared coefficient asymmetry (CV2a) values and character means (
Character | CV2a | N | Character mean | % of individuals with asymmetry |
---|---|---|---|---|
Shatt al-Arab River | ||||
Snout length | ||||
141 – 150 | 89.751 | 20 | 0.70 | 89 |
151 – 160 | 90.332 | 15 | 0.68 | 93 |
161 – 170 | 91.256 | 10 | 0.70 | 96 |
171 – 180 | 92.665 | 5 | 0.69 | 92 |
Eye diameter | ||||
141 – 150 | 81.998 | 20 | 1.96 | 88 |
151 – 160 | 83.552 | 15 | 1.98 | 85 |
161 – 170 | 84.998 | 10 | 1.95 | 82 |
171 – 180 | 85.002 | 5 | 1.95 | 89 |
Head length | ||||
141 – 150 | 88.286 | 20 | 3.29 | 78 |
151 – 160 | 88.990 | 15 | 3.30 | 77 |
161 – 170 | 89.543 | 10 | 3.28 | 75 |
171 – 180 | 90.432 | 5 | 3.30 | 86 |
Caudal peduncle length | ||||
141 – 150 | 78.998 | 20 | 1.49 | 91 |
151 – 160 | 80.442 | 15 | 1.54 | 99 |
161 – 170 | 85.678 | 10 | 1.55 | 98 |
171 – 180 | 88.965 | 5 | 1.53 | 99 |
Number of pectoral fin rays | ||||
141 – 150 | 75.664 | 20 | 13.4 | 77 |
151 – 160 | 78.987 | 15 | 13.5 | 69 |
161 – 170 | 80.425 | 10 | 13.6 | 89 |
171 – 180 | 84.763 | 5 | 13.5 | 98 |
Shatt al-Basrah Canal | ||||
Snout length | ||||
141 – 150 | 88.776 | 15 | 0.58 | 77 |
151 – 160 | 88.995 | 20 | 0.59 | 86 |
161 – 170 | 89.435 | 10 | 0.60 | 87 |
171 – 180 | 90.993 | 5 | 0.57 | 89 |
Eye diameter | ||||
141 – 150 | 79.998 | 15 | 1.85 | 92 |
151 – 160 | 80.554 | 20 | 1.87 | 97 |
161 – 170 | 85.667 | 10 | 1.86 | 98 |
171 –180 | 88.798 | 5 | 1.84 | 99 |
Head length | ||||
141 – 150 | 68.998 | 15 | 3.28 | 96 |
151 – 160 | 69.443 | 20 | 3.26 | 97 |
161 – 170 | 71.775 | 10 | 3.29 | 87 |
171 – 180 | 72.003 | 5 | 3.25 | 88 |
Caudal peduncle length | ||||
141 – 150 | 79.998 | 15 | 1.52 | 84 |
151 – 160 | 80.332 | 20 | 1.54 | 85 |
161 – 170 | 83.665 | 10 | 1.53 | 88 |
171 – 180 | 87.442 | 5 | 1.53 | 89 |
Number of pectoral fin rays | ||||
141 – 150 | 80.366 | 15 | 13.2 | 98 |
151 – 160 | 83.281 | 20 | 13.3 | 98 |
161 – 170 | 84.987 | 10 | 13.5 | 99 |
171 – 180 | 87.669 | 5 | 13.3 | 92 |
The Cd, Cr, Cu, Fe, Ni, and Pb levels in the water at the two sampling sites were comparable with universal values. Except for Cd, Fe, and Pb, the heavy metal levels in the water samples did not exceed the WHO (World Health Organization, 1993) and EC (European Community 1998) guidelines (Table 2). The high Pb, Cd, and Fe levels in the water samples in the Shatt Al-Arab River agreed with previously recorded raised levels (Al-Saffie 2005, Hassan 2007, Al-Hejuje et al. 2017). Mastoi et al. (2008) obtained similar elevated values for Cd, which they attributed to the overflow of chemical fertilisers originating from agricultural areas. The elevated values may also be linked to land-based point of origin releases associated with the rapid development of Basrah city centre (Al-Hejuje 1997). The high levels of Cd may also be due to various human-related effects connected to disparities in population density, wastewater releases, and manufacturing events. The Shatt al-Arab River is widely used for cleaning cars. Indeed, Al-Hejuje et al. (2017) remarked that cities are the primary sources of heavy metals in the river. In general, the variation in the levels of heavy metals could be related to several influences. For example, plankton and other water plants in the river may absorb ionic metals. Sandstorms and high fuel consumption may also be contributory factors, particularly during the summer. Electrical energy production also discharges large quantities of metals, notably lead compounds (Al-Hejuje et al. 2017).
The Cd, Cr, Cu, and Fe levels obtained from the sediment samples at the two sampling sites were either comparable to or exceeded the results previously obtained by other investigators.
The Cd, Cr, Ni, and Pb levels found in the tissue samples of
Since water in the Shatt al-Arab River is widely used for agricultural irrigation, and water from the Shatt al-Basrah Canal mixes with the water in the southern marshes of Iraq, the focus of pollution research should be concentrated on these two water bodies in terms of both environmental impact and public health issues.
High levels of bilateral asymmetry for snout length and eye lens diameter have previously been reported in numerous freshwater and marine fish species (Al-Hassan et al. 1990, Jawad 2013, Jawad et al. 2016, Jawad & Abed 2020). Such agreement in the finding of bilateral asymmetry can clarify the tendency of this characteristic to steer deviations in the niche. Consequently, it can be exploited as an operative stress biomarker in aquatic animal niches. Otherwise, head length displayed lower bilateral asymmetry levels in both fish species examined from both locations investigated, which suggests that this feature may be more vulnerable to ecological impact measures comprising contamination. The lesser bilateral asymmetry levels obtained for head length in both species could be explained on the grounds that the growing time of head length may not coincide with the occurrence of opposing ecological measures (Jawad 2003).
Analysis of variance showed that bilateral asymmetry levels for the external body traits examined diverged significantly between
Animals living in marine and freshwater habitats globally (Elie & Girard 2014) and in Iraq were influenced by chemical and organic pollution, resulting in external body feature anomalies (Jawad et al. 2017).
In the present report, the ANOVA test analysis shows that the specimens falling near the upper size limits of
Comparison of the coefficient of asymmetry (CV2a) of six and five morphological characters of
Species | Coefficient of asymmetry (CV2a) | Reference | |||||
---|---|---|---|---|---|---|---|
Snout length SnL | Eye diameter ED | Head length HL | Caudal peduncle length CPL | Number of pectoral fin ray PFR | Number of lateral line scales LLS | ||
89.371 | 78.874 | 63.412 | 75.981 | 65.412 | 77.982 | Present study | |
Shatt al-Basrah Canal | 87.964 | 75.651 | 64.914 | 73.912 | 65.298 | 74.329 | |
92.751 | 81.376 | 61.286 | 79.518 | 73.298 | 81.297 | ||
Shatt al-Basrah Canal | 87.251 | 79.521 | 69.825 | 77.538 | 70.156 | 80.312 | |
98.77 | 87.48 | 91.92 | 88.74 | 79.69 | 89.96 | Jawad and Abed (2020) | |
Callionymidae |
19.10 | 65.00 | 18.57 | - | 31.58 | - | Al-Mamry et al. (2011b) |
Carangidae |
5.65 | 18.29 | 2.87 | - | 10.04 | - | Jawad et al. (2011a) |
18.37 | 21.36 | - | - | 11.55 | 14.05 | Jawad et al. (2010) | |
Cichlidae |
20.7 | 58.3 | - | - | - | 48.7 | Jawad et al. (2016) |
33.48 | 56.09 | - | - | 15.85 | - | Jawad (2002) | |
28.4 | 49.4 | - | - | - | 48.7 | Jawad et al. (2016) | |
Claroteidae |
61.3 | 60.4 | 62.8 | - | 62.1 | - | Jawad and Gnohossou (2019) |
Clupeidae |
123.2 | 125.3 | 98.4 | - | 178.7 | - | Jawad et al. (2012e) |
Gerreidae |
328.29 | 92.90 | 50.50 | 478.98 | Jawad et al. (2011b) | ||
Hemiramphidae |
2.44 | 121.30 | 0.51 | - | 24.20 | - | Al-Mamry et al. (2011a) |
Leiognathidae |
25.76 | 0 | 17.03 | 3.25 | Al-Mamry et al. (2011a) | ||
Mugilidae |
62.2 | 59.6 | 58.4 | - | 60.1 | - | Jawad and Gnohossou (2019) |
Mullidae |
1.35 | 0 | 25.81 | - | 4.47 | - | Jawad et al. (2012d) |
Pinguipedidae |
59.64 | - | 12.39 | - | 34.70 | 6.81 | Jawad et al. (2012a) |
Scombridae |
154.57 | 55.74 | 12.11 | - | 47.33 | - | Jawad et al. (2012c) |
12.19 | 35.30 | - | - | 35.30 | - | Jawad et al. (2001) | |
Siganidae |
24.62 | 47.08 | 8.84 | - | 80.75 | - | Al-Mamry et al. (2011–2012) |
Siluridae |
95.78 | - | - | - | 87.24 | - | Al-Hassan et al. (1990) |
Sparidae |
3.03 | 23.98 | - | - | 36.69 | - | Jawad (2003) |
35.49 | 18.60 | - | - | 10.43 | - | ||
28.14 | 9.53 | - | - | - | - | ||
26.31 | 35.30 | - | - | - | - | ||
Tetraodontidae |
74.88 | 22.8 | 9.677 | - | 39.7 | - | Jawad (2013) |
To appraise the values disparity in regularity obtained for the six external body features of