Advances in Environmental Biology, 9(11) June 2015, Pages: 47-53 AENSI Journals
Advances in Environmental Biology
ISSN-1995-0756 EISSN-1998-1066
Journal home page: http://www.aensiweb.com/AEB/
Describing variations within populations of Arabian cowry, Cypraea Arabica collected along the coast of Sindangan Bay, Philippines
1Ma. Lotus E. Patiluna and 2Cesar G. Demayo
1 Central Philippine Adventist College, Murcia, Negros Occidental, Philippines 2 Department of Biological Sciences, College of Science and Mathematics, MSU-Iligan Institute of Technology, Iligan City, Philippines
ARTICLE INFO ABSTRACT Article history: This study was conducted to describe variations in the Arabian cowries Cypraea arabica Received 23 March 2015 collected from the coastal area of Sindangan Bay, Philippines. While this species and its Accepted 18 June 2015 subspecies can be characterized by a dozen of characters, in this study, variations within Available online 25 June 2015 the species were characterized based on qualitatively described morphological characters (i.e. shell shape, color, bands, banding pattern, etc.), quantitative Keywords: morphometric characters (i.e. shell length, width, height, etc.) and relative warp scores morphological morphometrics generated from outline and landmark-based geometric morphometric analysis and Cypraea arabica CORIANDIS correlation analysis based on distances (CORIANDIS). From a total of 21 traits scored from 63 Arabian cowries, 5 were grouped based on their axial bands and banding pattern - 3 clusters were generated from 11 qualitatively described morphological characters and 5 from morphometric characters. CORIANDIS analysis show the congruence and disparity of multivariate traits shown in stacked bar graph and compromise space revealed no differences between dorsal and ventral shapes, lower variability for qualitatively described morphological characters and higher variability in morphometric characters within the species. The use of hierarchal cluster analysis and CORIANDIS were found to be useful in understanding the nature of diversity in the species.
© 2015 AENSI Publisher All rights reserved. To Cite This Article: Ma. Lotus E. Patiluna and Cesar G. Demayo., Describing variations within populations of Arabian cowry, Cypraea Arabica collected along the coast of Sindangan Bay, Philippines. Adv. Environ. Biol., 9(11), 47-53, 2015
INTRODUCTION
The cowries have long been considered one of the most popular collectable seashells due to their glossy appearance and varied colors and patterns. They are called the “gems of the sea” [1,2]. The beautiful glossy shells of cowries have historically been exploited for human use as souvenirs and even currency [3], collected for food by coastal populations in many parts of the Philippines and shell craft industry [4]. They are also important decomposer and some are significant predators. Generally, they are associated with coral reefs, under slabs and stones and in caverns of the outer edge of coral reefs in well-aerated waters, from low in the intertidal zone to shallow sublittoral depths. They feed most actively at night, browsing on encrusting algae and sponges or tiny animals that grow on rocks and corals [4]. Cowries or Cypraeidae (Gastropoda) are taxonomically one of the best known molluscs used frequently to examine speciation and biogeographic patterns in the marine tropics. A wealth of taxonomic, anatomical and fossil data is available for the group [5]. The approximately 217 species and numerous subspecies and forms have been the focus of many popular and scientific publications. All of the cowry species were classified, into well-defined genera based on shell characteristics but with little acceptance. The Arabian cowry, Cypraea arabica for example, was found to be a variable species based on its dense and irregular pattern of thin longitudinal brown lines interrupted by empty spaces giving an appearance that is considered to be similar to that of Arabic script.(4). This species has been described in literature to comprise five subspecies namely, C. arabica arabica, C. arabica asiatica, C. arabica immanis, C. arabica grayana and C. arabica merguina which are mistakenly identified from each other [6]. Since cowry shells can be characterized by a dozen of characters, there is a need to use many characters to describe variability in the species [7]. To have a better discrimination of the variants of this species, the use of several qualitative and quantitative tools should be employed. In this study, phenotypic variations in Cypraea
Corresponding Author: Cesar G. Demayo, Department of Biological Sciences, College of Science and Mathematics, MSU-Iligan Institute of Technology, Iligan City, Philippines. 48 Ma. Lotus E. Patiluna and Cesar G. Demayo, 2015 Advances in Environmental Biology, 9(11) June 2015, Pages: 47-53 arabica were described using not only qualitative characters (i.e. shell shape, color, bands, banding pattern, etc.), quantitative characters (i.e. shell length, width, height, etc.) but also new tools of landmark-based geometric morphometrics (GM). Correlation analysis based on distances [9] (CORIANDIS) was used to describe the overall differences and/or similarities in the species shell phenotypic characters. This study is important in advancing our knowledge in understanding the nature of variations in populations of organisms living in different ecological environments. MATERIALS AND METHODS
Due to restrictions in the number of individual cowries to be collected, 63 shells were collected from the marine protected areas or MPAs within the municipal water of Sindangan, Zamboanga del Norte, Philippines. Sindangan Bay (8° 13' 37" N; 122° 54' 55" E) is located at the western part of Zamboanga Del Norte facing the Sulu Sea. It is bordered by the municipalities of Sindangan, Leon B. Postigo (Bacungan), Salug and Liloy with a 94.03 km stretch of coastline. The municipal water of Sindangan is estimated to be at 405.47 km2 and a coastline length of 39.16 km. The coral reefs cover an area of 115.24 ha. Healthy coral reefs are concentrated in shoals with depths of between 6-35 m and located at a distance between 300 m to 3 km from the shoreline. The surveyed area was estimated to be about 5 km2, extending from the highest watermark at shoreline over the reef flat (seaward) and up to 3 to 5 m in depth. Gastropods particularly sea snails were collected from three (3) marine protected areas within the municipal water of Sindangan (Fig. 1) specifically at Marine Sanctuaries of Guisukan in Doña Josefa, Languyon in La Concepcion, and RG Macias. The samples were grouped according to its axial bands and banding patterns. Groups 1 and 2 have 4 distinct axial bands with numerous or few white rounded spaces, groups 3, 4 and 5 have fused axial band and those with none, few or numerous white rounded spaces (Fig 2). A total of 21 characters, 11 of which were qualitative and 10 quantitatively described were scored and summarized in a matrix prior to data analysis (Table 1). Morphometric measurements such as shell length, width and height, aperture length and width in mm were measured using digital vernier caliper (Fig 3). Average weight in mg was determined using a digital weighing scale. Columellar and labial teeth (CTR and LTR) were normalized with the following formula: LTR=7+(LT-7)x(25/L)1/2 and CTR=7+(CT-7)x(25/L)1/2, where L is the length of a real shell in mm [7] (Fig 4);. For landmark-based geometric analysis, coordinates on the captured dorsal and ventral images were obtained (Fig. 5) and subjected to relative warp analysis. The relative warp scores generated from the analysis of the geometric data using the Paleontological Statistics Software (PAST ver. 9) were included in the data analysis. These were then subjected to cluster analysis using SPSS ver19 to determine the groupings of phenotypic variants within C. arabica. The correlation analysis based on distances made use of the free software CORIANDIS ver. 1.1 Beta [8] to describe the overall differences and/or similarities. In this analysis, the relative warp scores generated from the analysis of geometric coordinate data on the digital images of the dorsal and ventral shapes of the shell were used. The CORIANDIS software implements a broad spectrum of data types, including 2-D landmark and distance data [9] to determine associations among multivariate datasets, projections on compromise space, trait variance or disparity, congruence and multivariate covariance measure on how similar are the qualitative, quantitative morphometric measurements and relative warp scores (shape) generated define the characteristics of the shell. This is interpreted as a decomposition of group distinctiveness from other groups in terms of specific traits or characters [10]. The squared distances of each group to the origin are computed for each of the characters or data sets, and are plotted in a stacked bar graph to give an overall impression [11].
Fig. 1: Map showing the study area.
49 Ma. Lotus E. Patiluna and Cesar G. Demayo, 2015 Advances in Environmental Biology, 9(11) June 2015, Pages: 47-53
Fig. 2: Photograph showing axial bands and banding patterns of each group. (a-b) groups 1 and 2 have 4 distinct axial bands and numerous or few white rounded spaces, respectively (c-e) group 3, 4 and 5 have fused axial bands; no, few and numerous white rounded spaces, respectively.
Table 1: List of shell characters used in the analyses. 1. Shape (0) oblong; (1) ovate 2. Color - dorsal (0) creamy- white; (1) light fawn 3. ventral (0) creamy grey; (1) creamy-light fawn 4. sides (0) grayish-white; (1) creamy-light fawn 5. teeth (0) reddish-brown; (1) light brown 6. Axial bands (0) 4 axial bands; (1) fused axial bands 7. Banding patterns (0) numerous; (1) few; (2) no white rounded spaces 8. Dorsal line (0) distinct; (1) not distinguishable (0) partially covered by a callus; (1) visible, slightly protruding at the 9. Spire posterior ends (0) distinctly calloused at proximity; (1) not distinctly calloused at 10. Lateral magins proximity 11. Lateral spots (0) few brown/black spots; (1) numerous brown/black spots 12. No. of Labial teeth (0) 19-23; (1) 24-28 13. No. of Columellar teeth (0) 18-22; (1) 23-27 14. LTR (0) 17-19; (1) 20-22 15. CTR (0) 16-18; (1) 19-21 16. Shell Length (mm) (0) 32-43; (1) 44-55; (2) 56-67 17. Shell Width (mm) (0) 22-27;(1) 28-33; (2) 34-49 18. Shell Height (mm) (0) 17-22; (1) 23-28; (2) 29-34 19. Aperture length (0) 31-42; (1) 43-54 20. Aperture width (0) 2-3; (1) 4-5 21. Ave. weight (g) (0) 8-17; (1) 18-26
Fig. 3: Measuring Shell Characters.
Fig. 4: Counting teeth. (Designations: A- a terminal ridge; L1-the first labial tooth; L20-the last labial tooth; 1- the first columellar tooth; 17-the last columellar tooth).
Fig. 5: Landmarks s of the (A) dorsal and (B) ventral of C. arabica shell. 50 Ma. Lotus E. Patiluna and Cesar G. Demayo, 2015 Advances in Environmental Biology, 9(11) June 2015, Pages: 47-53
RESULTS AND DISCUSSION
Based on the qualitative analysis of the morphology of the shells, 9 out of 11 morphological characters examined in this study were found to be consistent for all except for characters 6 and 7 comprising the axial bands and banding patterns. Cluster analysis (Figure 4a) show the relationships of the five groups of shells (Table 2). Cluster 1 comprise mostly of group 1, 4 and 5. Cluster 2 consists group 3 while Cluster 3 comprise groups 1 and 2. However, cluster analysis of quantitatively described characters using the ten (10) morphometric attributes show 5 clusters (Fig 4b, Table 2 Relative warp scores generated from 100 outline coefficients and 17 identified landmark points in the ventral side of the shell which were used to describe the variations in shell shapes based on the observed bending of grids [12] were also included in the graphical comparison of the variations between the 5 groups of the Arabian cowry (Figures 6-8).
Fig. 4a: Hierarchical clusters of individuals to the various qualitatively described morphological characters.
Table 2: Average Linkage Values (Between Groups) of Morphological Characters (see Figure 4a). Cluster Combined Percent (%) Coefficients Description (Morphological) cluster Similarity No white rounded spaces, dissolve or not 1 30-37 63 1.000 distinguishable axial bands (group 3) Few white rounded spaces, dissolve axial bands 2 38-53 28 1.000 (group 4); numerous white rounded spaces, dissolve or not distinguishable axial bands (group 5) Few white rounded spaces, 3 axial bands (group 1) 4 3 1-29 28 2.270 axial bands (group 2)
Fig. 4b: Hierarchical clusters of individuals to the various quantitatively described morphometric characters.
Table 2: Average Linkage Values (Between Groups) of Morphometric Characters (see Figure 4b). Cluster Combined Percent (%) Description (Morphometrics) cluster Similarity Varies in shell length (SL), shell width (SL) and 1 6-22 2.333 average weight (AvWt) 2 Varies in shell length (SL), nos. of labial teeth (LT) 2 4-10 2.375 and average weight (AvWt) Varies in shell apertural length (SAL), shell thickness 3 5-16 2.556 (ST), and real numbers of labial teeth (LTR) Varies in shell width (SW), shell aperture length 4 1-11 2 2.148 (SAL), nos. of collumelar teeth (CT) and average weight (AvWt) Varies in nos. of columellar teeth (CT), shell width 5 2-31 2.857 and shell spertural length (SAL) 51 Ma. Lotus E. Patiluna and Cesar G. Demayo, 2015 Advances in Environmental Biology, 9(11) June 2015, Pages: 47-53
The graphical comparison of the variations between the 5 groups of the Arabian cowry which utilized correlation analysis based on distances or CORIANDIS show what traits that are said to be positively congruent, and show in this plot as a general tendency to cluster together [11, 13]. The congruence and disparity of multivariate traits shown in stacked bar graph and compromise space (Figures 6 and 7) revealed no differences in the dorsal and ventral shapes of the five groups, low variability based on qualitative descriptions of morphology. Differences between the groups were more pronounced based on quantitative descriptions of morphometric characters. Cluster analysis in CORIANDIS show groups 4 and group 5 has 70% resemblance, between groups 1 and 2 has 52% resemblance. Group3 has 56% resemblance with groups 1 and 2. The location of the five groups in the “compromise” space shows low congruence of the four groups of characters used in the analysis (dorsal and ventral shapes, quantitatively measure morphometric characters and qualitative morphological characters). Groups 1 and 2 were observed to be closely clustered together as well as that of groups 4 and 5. The results of this study indicates that the variations in the shells of C. arabica are only distinguishable in the axial bands, banding patterns and morphometric measurements.
Specimen/Group
Fig. 6: Stacked bar graph showing disparity between groups or specimen based on banding pattern of C. Arabica.
Fig. 7: Plot of the principal components of “compromise” space axis of C. Arabica between different traits (in set).
Fig. 8: Clustering of groups based on the degree of similarity of shell characters of C. Arabica.
52 Ma. Lotus E. Patiluna and Cesar G. Demayo, 2015 Advances in Environmental Biology, 9(11) June 2015, Pages: 47-53
It can be argued from the results of this study that phenotypic plasticity exists in C. Arabica which could be due to several factors. Environmental effects such as physico-chemical and predation factors may have contributed to the variations observed [14] as a strategy because it allows organisms that cannot change their genes a way of changing their phenotypes to meet the demands of the environment [15] thus allowing them a greater chance of survival in changing environments [16]. The shells of the five groups of C. arabica described in this study differ in their banding pattern of shells, morphometric characters such as number of labial and columellar teeth; shell length, width and height; aperture length and width; and average weight. Since other characters were similar in the shells, the phenotypic differences observed can be argued to have poor genetic basis thus the variations can be attributed primarily to phenotypic plasticity [17, 18]. Contributions from environmental cues cannot be ignored since one of the most important influences on shell shape in marine organisms appears to be the animal’s own growth rate [19] which can be influenced by environmental factors such as food availability and quality, feeding time and densities of conspecifics and competing species [20].
Conclusion: This study show the use of hierarchical cluster analysis and correlation analysis based on distances (CORIANDIS) using both qualitative and quantitative characters including geometric morphometric data were found useful in assessing phenotypic variations in C. Arabica which may reflect their function in nature.
ACKNOWLEDGEMENT
The senior author would like to acknowledge the administration of Central Philippines Adventist College for the faculty development support, to the Commission of Higher Education HEDF program for the scholarship, Prof. Muhmin Michael E. Manting for the technical assistance, and the members of the advisory committee for the evaluation of the manuscript.
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