Geometric Morphometrics Analysis of Fish

Use of Fish Geometric Morphometric Markers for Characterizing Shape Variations of Selected Fishes: Family Leiognathidae in the Marine Waters of Zamboanga City, Western Mindanao, Philippines

• Roldan T. Echem

Abstract

[AU1]

In this investigation, geometric morphometric analysis was used to determine the extent and degree of morphological diversity within and among four species of fishes under Family Leiognathidae and one out-group under Family Menidae collected in the marine waters of Zambonaga City. A total of 200 of fish samples, these include Leiognathus equulus, L. fasciatus, L. bindus, L. daura and one out-group Mene maculata which showed evolution and diversification of L. fasciatus, were subjected to various geometric morphometric analyses. Fish samples were scanned at uniform 400 dpi and the resulting images were binarized using SCIONIMAGE, an image analysis and processing software. The x and y coordinates of a total of 15 landmark points were collected from around the contour of the fish samples. For the landmark analyses, the 15 landmark coefficients were used as morphometric variables for multivariate and cluster analyses in order to assess its shape. Procrustes fitting of the landmark points allowed for the comparison of the various shapes of the fish samples. The resultant shape variables were analyze to determine differences in form, contour and profile of the fishes using geometric thin-plate spline grids (TPS), partial warps (PW) and relative warps (RW). Results of this study showed variations in the various species of fishes under Family Leiognathidae and within each species. Significant differences were found among species and these shape changes are probably related to differences in habitat and feeding habits among the species.

Keywords: Biology, Leiognathidae, Geometric morphometrics, Partial-warp scores, Multivariate Analysis, Western Mindanao, Philippines

Introduction [AU2]

Leiognathids are schooling, bacterially bioluminescent fishes abundant in coastal bay and estuarine environments throughout the Philippine Islands (Borja, 1978)[AU3]. The family is readily divided into three genera namely; Gazza, Leiognathus and Secutor, but due to the wide geographical distribution of the family and morphological similarity of the species within genus, much confusion presently exists over identification of the 20 to 30 species (Borja, 1978; James, 1985)[AU4]. Menidae (moonfishes) are a morphologically distinctive group represented by a single recent and numerous fossil species. Members of this family are easily recognized by their laterally compressed disc-like bodies, dorsally oriented mouth large, distinctly shaped maxillae and long ascending processes of the premaxillae, anteroposteriorly elongated dorsal and anal fins with relatively short rays, and narrow pelvic fins with a compressed and greatly elongated second ray. This unique morphology is conserved over the known fossil history of this group, and characterizes the only extant member of Menidae, Mene maculata (Bloch and Schneider, 1801)[AU5]. This recent form is found throughout the Indo-Pacific, ranging from the eastern coast of Africa, India, the Philippines, northern Australia, and Japan. The phylogenetic affinities of Mene have been the subject of some historical debate.

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Morphological characters have been commonly used in fisheries biology to measure discreteness and relationships among various taxonomic categories (Bookstein, 1991). However, the major limitation of morphological characters at the intra-specific level is that phenotypic variation is not directly under genetic control but subjected to environmental modification. Blake (1983) stated that the phenotypic plasticity of fish allows them to respond adaptively to environmental change by modification in their physiology and behavior which leads to changes in their morphology, reproduction or survival that mitigate the effects of environmental variation. Such phenotypic adaptations do not necessarily result in genetic changes in the population, and thus the detection of such phenotypic differences among populations cannot usually be taken as evidence of genetic differentiation. According to Sparks (2004) that environmentally induced phenotypic variation may have advantages in the stock identification, especially when the time is insufficient for significant genetic differentiation to accumulate among populations.

A fundamental problem facing systematists and comparative biologists is that of deciding just how two separate phenotypes are different. Geometrics morphometric analyses can thus be a first step in investigating the stock structure of species with large population sizes of Leiognathids and Menids. No study so far has examined the relation of body form in these groups of fishes using the methods of geometric morphometrics analyses of landmark data. Morphometric studies are based on a set of measurements which represent size and shape variation and are continuous data. The geometric morphometric analysis covers the entire fish in a uniform network, and theoretically should increase the likelihood of extracting morphometric differences within and between species (Rohlf, 1990). There is evidence that geometric morophometric analysis is much more powerful in describing morphological variation between closely related fish taxa than traditional measurements (Turan, 1998). When combined with multivariate statistical procedures, they offer the most powerful tool for testing and graphically displaying differences in shape (Loy et al. 1993, Rohlf and Marcus 1993, Rohlf et al. 1996).

The main objective of this paper was to use geometric morphometric analyses to determine the extent and degree of morphological diversity within and among four species of fishes under Family Leiognathidae and one out-group under family Menidae collected in the marine waters of Zamboanga City. Second, to determined patterns of significant differentiation and its biological implications, and third, to analyzed the taxonomic classification of the four species fishes belonging to family leiognathidae and one out-group under family menidae based on their morphological characters.

Method [AU6]

A total of 200 of fish samples, these include Leiognathus equulus, L. fasciatus, L. bindus, L. daura and one out-group M. maculataan evolution and diversification of L. fasciatus, were subjected to various geometric morphometric analyses (Figure 1).

Figure 1. Fish samples under family Leiognathidae and family Menidae.

Geometric morphometric methods usually begin with digitized images. The fish samples were scanned at uniform 400 dpi and the resulting images were binarized using SCIONIMAGE, an image analysis and processing software. The x and y coordinates of a total of 15 landmark points were identified and collected from around the contour of the fish samples (Figure 2).

Figure 2. Relative positions of all landmarks assigned on the body of the fishes. landmark’s description (Leiognathus equulus in the example): (1) snout tip; (2) nostrils; (3) anterior and posterior;(4) insertion of the dorsal fin; (5) insertion of the second dorsal fin;(6) origin of the caudal fin;(7) middle of the caudal fin;(8) insertion of the caudal fin;(9) insertion of the anal fin;(10) origin of the anal fin;(11) origin of  the pelvic fin;(12) origin of pectoral fin;(13) posteriormost margin of the operculum;(14) junction between maxilla and upper lip;(15) middle of the eye

Then contours of the fish samples were then summarized as chain codes. For the landmark analyses, the 15 landmark coefficients were used as morphometric variables for multivariate statistical analyses and hierarchical cluster analyses in order to assess the shape. To remove all information unrelated to shape, a generalized orthogonal least-squares Procrustes (GPA) superimposition (translation, scaling and rotation) described in Rohlf and Slice (1990) was conducted on the sets of landmarks. Procrustes fitting of the landmark points allowed for the comparison of the various shapes of the fish samples. Consensus configurations of each species were subjected to thin-plate spline (TPS), partial warps (PW) and relative warps (RW) to determine variations in shapes through examination of the deform shape of the grids.

The extent and degree of variability within and between species belonging to the same family leiognathidae including the out-group were also assessed using the method of Principal component analysis. PCA is a discriminant function analysis to confirm size and shape variations. PCA involves the calculation of the eigen value of the data and the results of a PCA are usually described in terms of component scores and loadings. Discriminant function analysis is used to determine which variables discriminate between two or more naturally occurring groups. Canonical analysis are obtained to performed a multiple group discriminant analysis and automatically determine some optimal combination of variables so that the first function provides the most overall discrimination between groups, the second provides second most, and so on. The uniform components were tested for significant differences among species by multivariate analysis of variance MANOVA: (Neff and Marcus 1980). Multivariate analysis of variance was performed to test for significant differences in shapes between species, a multivariate was obtained F value (Wilks’ lambda) based on a comparison of the covariance matrix.

Results and Discussion

[AU7]

Table 1 revealed that there was a high significant difference between the x and y components (p = 0.0001) of the landmarks on the contours of the fish.

Table1

Analysis of variance of the x and y uniform components

The extent and degree of variability within and between species belonging to the same family Leiognathidae including one out-group under family Menidae were also assessed using the method of Principal component analysis. The result of PCA shows largest component scores at 96.9%. The first principal component showed high significance and accounts for as much of the variability in the data, and each succeeding component accounts for as much of the remaining variability (Table 2).

Table 2

Principal Component Analysis (PCA) of the 5 Groups of Fishes

Figure 3 shows that the canonical analysis was performed to automatically determine some optimal combination of variables that provides overall discrimination between groups. Results showed that the shape variations can be attributed to changes in the upper lip, caudal fin and pectoral fin and dorsal fin as shown in the deformation of shapes of the grids. The 1st relative warp extracted from the matrix of the partial-warp scores accounted for about 69.45% of the total nonaffine shape variation, whereas the 2nd relative warp explained 39.61% of the total variation. The 1st relative warp is characterized by shape changes along the upper lip between the male and female Leiognathus equulus. The specimens with highest scores on the 1st relative warp is between male and female Leiognathus fasciatus which accounted 96.9% variation and is characterized by shape changes along the dorsal fin. Biological meaning of these partial shape variations can be explained in the change in fin morphology and position, the central component of the evolutionary transformation of functional design in leiognathid fishes. Documenting phylogenetic patterns in the structure of the dorsal fin, caudal fin and pectoral fin, and interpreting the functional significance of such patterns, has been the subject of ongoing study by systematists (Breder, 1996). There is significant anatomical variation because of hydrodymic significance of evolutionary transformation in dorsal fin and the important similarities in patterns of diversity in fishes seem to indicate competition for food resources that may cause diversity in jaw apparatus among fish (Lauder, 2000). [AU8]

Figure 3. Transformation Grid and Warps of the Five Species Including the Out-Group,

Deformations of Grids in the Anteriormost Tip Or the Upper Lip, Dorsal Fin and Caudal Fin.

Table 3 shows that the canonical vector analysis indicated the existence of large and highly significant among group differences. The first discriminant variable is the caudal fin and highly significant (Wilks Λ = 2.0, F = 1.76, P= 0.002), the second variable that provides discrimination between groups is the pectoral fin and displayed high significance (Wilks Λ =1.0.35, F = 0.75, P= 0.81), and the snout tip (Wilks Λ = 0.51, F = 2.60, P= 0.002) and dorsal fin (Wilks Λ = 0.35, F =1.89, P= 0.002).

Table 3

Canonical Vector Analysis

Prosanta (2006) reported that the family Leiognathidae, commonly known as ponyfish or slip mouth, comprises three genera, each being characterized mainly by mouth morphology. The relationships allowed phylogenetic analyses of mouthpart structures and light organ systems. The results suggested that the morphology of the mouthparts is ancestral in the family. The results also suggested that internal sexual dimorphism of the light organ system was present in the common ancestor of a sister clade to L. equulus, whereas external sexual dimorphism seems to have evolved subsequently in two monophyletic subgroups. The evolution and diversification of L. fasciatus to other group Mene maculata under family menidae support the result of this study that the out-group exhibited similarity of morphological features from L. fasciatus.

The analysis of the shape differences depicted in the fish species sampled mainly according to their systematic relationships. This agrees with the findings of Loy et al. (1993) and Rohlf et al. (1996), that the shape components may contain more taxonomic information than the uniform components of shape variation. The shape variation using geometrical analysis of landmark data can describe and locate differences of form in organisms more efficiently (Bookstein 1991). This approach has been shown to yield the most accurate information in fish morphological studies (Walker 1996; 1997), [AU9]and is expected to find increasing applications in the near future.

As reported by Loy et al. (2001) shape differences between 3 sparids of the genus Diplodus juveniles appear to be related to ecological differences in their ecology. Webb (1984) [AU10]showed evidence that body shape is a reliable indicator of the swimming behavior and the ecology of fish. The link between morphology and diet in fish is provided by feeding performance (Norton 1991; Wainwright 1991; Motta and Kotrschal 1992). [AU11]As suggested by Wainwright and Richard (1995),[AU12] morphology and shapes is influence on a fish’s feeding capability. A major challenge in fish ecology is to establish the linkage between morphology and diet. Functional morphological, biomechanical, and physiological analyses may be used to determine the expected consequences of morphological variation on feeding performance (Wainwright 1988).[AU13]

Conclusion and Recommendation[AU14]

In this present study, the findings reveal the potential power of the use of geometric morphometric markers for characterizing shape variations in several species of fishes under family Leiognathidae for identifying phenotypic stocks. The geometric system can be successfully used to investigate stock separation within a species that allows, in a long term, a better and direct comparison of morphological evolution of stocks, while using the same set of measurements.

Results of this study revealed variations in shape of the selected species of fishes under Family Leiognathidae and within each species and one out-group under family Menidae. Significant differences were found among species with respect to caudal fin, pectoral fin, upper lip and dorsal fin. These shape changes are probably related to differences in habitat and feeding habits among the species.

This present study concluded the usefulness of the geometric morphometric system as a fisheries management tool and it is capable of examining large numbers of samples in a short time. It is also effective in identification of stocks and improving the biological basis of management of fishes.

References

Bookstein, FL. (1991). Morphometric tools for landmark data. Cambridge Univ. Press, p 435.

Blake, R.W. (1983). Functional design and burst-and-coast swimming in fishes. Can J Zool, 61 (11):2491–2494

Breder, .CM. (1996). The locomotion of fishes. Zoologica, 4:159–297.

Sparks, J.S. (2004). Phylogeny and biogeography of cichlid fishes (Teleostei: Perciformes: Cichlidae) Cladistics, 20 (6), 501-517.

Loy, A.; Bertelletti, M.; Costa, C; Ferlin, L. & Cataudella, S. (2001). Shape changes and growth trajectories in the early stages of three species of the genus Diplodus (Perciformes, Sparidae). J Morphol, 250:24–33.

Prosanta, C. (2006). Evolution and diversification of a sexually dimorphic luminescent system in ponyfishes (Teleostei: Leiognathidae), including diagnoses for two new genera. Cladistics, 20 (6), 501-517.

Rohlf, F.J. (1990). Rotational fit (Procrustes) methods. In FJ Rohlf, FL Bookstein, eds. Proceedings of the Michigan Morphometrics Workshop. Special Publication No. 2. Ann Arbor: Univ. of Michigan Museum of Zoology, pp. 227-236.

Rohlf, F.J. (1993). Relative warp analysis and an example of its application to mosquito wings. In LF Marcus, E Bello, A [AU15]

Rohlf, F.J. (1995). Multivariate analysis of shape using partial-warp scores. In KV Mardia, CA Gill, eds. Proceedings in current issues in statistical shape analysis. Leeds: Leeds Univ.Press, pp. 154-158.

Rohlf, F.J. (1996). Morphometric spaces, shape components, and the effects of linear transformations. In LF Marcus, M Corti, A Loy, G Naylor, DE Slice, eds. Advances in morphometrics. NATO ASI Series A: Life Sciences, 284.[AU16]

Rohlf, F.J.; Loy, M. & Corti (1996). Morphometric analysis of Old World Talpidae (Mammalia, Insectivora) using partial-warp scores. Syst. Biol. 45: 344-362.

Rohlf, F.J. & Marcus, L.F. (1993). A revolution in morphometrics. Trends Ecol. Evol. 8: 129-132.

Rohlf, F. & Slice, D.E. (1990). Extensions of the Procrustes method for the optimal superimposition of landmarks. Syst. Zool., 39: 40-59.

Turan, C. & Basusta, N. (2001). Comparison of Morphometric Characters of Twaite Shad (Alosa fallax nilotica, Geoffroy Saint-Hilaire, 1808) among three areas in Turkish Seas. Bull. Fr. Peche Piscic. ; 362/363 : 1027-1035.

Smith, P.J. (1990) Protein Electrophoresis for Identification of Australian Fish Stocks. Aus. J. Mar. Fresh. Res., 0; 41: 823- 833.

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