Periodicity of the Banding in Polished and Etched Shells

Published Date: 29 Mar 2018

CHAPTER 3: GENERAL METHODOLOGY

Background

This chapter describes the sampling areas and methodological procedure used in all experiments undertaken in this study. Specific materials and methods are explained in the respective chapters.

Sample collection

Various experiments were carried out to determine the periodicity of the banding in polished and etched shell section. A total of 950 samples of A. granosa (shell length: 10 mm) were obtained from Kuala Juru (N 5° 20ʹ 26.44ʺ E 100° 24ʹ 32ʺ), one of the main productive mudflats for cockle harvesting in Peninsular Malaysia. At the landing site, the cockles were placed into rotator machine where water continuously sprayed onto the cockles in order to remove sediments and muds. Samples were then sorted to various size groups and cockles with shell length of about 10 mm were subjected to staining process (Figure 3.1).

Figure ‎3.1: Rotation machine for mud clearing and sample sorting.

Staining

Alizarin red influenced both the behaviour and shell structure of A. granosa even though the red colour is not visible within the shell layer. During the immersion period in alizarin solution, the shells were remained closed causing a minimal disruption of the metabolic activities of the cockles. Therefore, the direction of growth lines deposition was changed in the shell structure. For this reason, all of the cockles were stained using Alizarin red combined in seawater at 30 ppm for 24 hours (Figure 3.2). Exposure of samples to alizarin red dye in the filtered seawater for 24 hours was sufficient to stain the shells (Riascos et al., 2007). At the study site, cockle shells resumed their growth on the stained again. Therefore, a coloured thick growth break of the shell with a V-shape cleft in periostracum region was readily observed.

Figure ‎3.2: The staining procedure using shell dye, Alizarin red.

Study site

A study on the microgrowth line formation of A. granosa was conducted at three points (A, B and C) in intertidal and subtidal areas of Balik Pulau, west coast of Peninsular Malaysia from December 2011 to November 2012 (Figure 3.3).

The cockles at site A (N 5° 20ʹ 67ʺ E 100° 11ʹ 56ʺ) were exposed during all low tides while cockles at site B (N 5° 20ʹ 40ʺ E 100° 11ʹ 85ʺ) were exposed only during spring tides and site C (N 5° 20ʹ 03ʺ E 100° 11ʹ 71ʺ) were constantly immersed (Figure 3.4). The study on effects of environmental and physiological parameters on shell growth was carried out at site A located close to natural habitat of cockle populations).

Figure ‎3.4: Diagram showing the position of sites A, B and C in relative to the tidal change.

Site preparation

The cockles A. granosa were placed in a plastic mesh cage made of plastic net and PVC pipe frame. Cage was located at Site A, where the cockles were exposed on almost all low tides (Figure 3.5). The cage was specifically designed to have all four vertical sides lined with nylon net. The dimension of the cage was 2.0×2.0×1.2 in meters. Netting material attached to the frame was sufficiently small (0.5×0.5 cm) to prevent specimens from passing through it. The water level was lower than the height of the cage therefore upper surface of the cage was open for easy access to the cockles during sample collection.

The samples in sites B and C were placed in ten small plastic mesh baskets (mesh size: 0.5×0.5 cm). All containers were filled with mud from the surrounding environment and five baskets were placed in each site (Table 3.1). Dimension of the baskets were 0.7× 0.5× 0.35 m. The top Side of basket was covered with a net to protect against predators and the bottom was fixed with weights. The sites were clearly marked with poles (Figure 3.6).

Table ‎3.1: Description of the study area at site A, B and C in Balik Pulau, Pulau Pinang, west coast of Peninsular Malaysia.

Preparation of shell cross section

After removing the soft tissue, thin radial sections were prepared from one valve of any specimen based on standard methods by Neves and Moyer (1988) (Figure 3.7A).

Cutting of shells

Valve of each specimen was marked by a pencil from the umbo to the ventral margin along the maximum growth line at a point from the shell posterior (Figure 3.7A). The valve was then fixed on the low speed saw with a diamond-impregnated blade (Buehler Ltd., Lake Bluff, IL) as inner valve surface was toward the diamond blade of a saw machine. Low speed was used to cut fragile materials that would otherwise fracture. The valve was oriented toward the saw machine to cut through the pencil mark at the ventral margin (Figure 3.7B).

Embedding in Epoxy resin

The shells sectioned were embedded in epoxy resin (combination of epoxy resin to epoxy hardener with the proportion of 2:1) at room temperature for a period of 24 hours. For this purpose, one side of PVC pipe was blocked with selefon tape. The valves were placed into PVC mold with the cut surface facing toward the bottom (Selefon Tabe side). Small volumes (50-75 ml) of mixed epoxy were added into PVC molds to a depth of around 3 cm. To obtain better results during polishing, the valve was pressed to push bubbles from between the cut surface and mold bottom (Figure 3.8).

Grinding

Shell sections were then grounded by hand machine on five sequentially finer grits sizes: 240, 400, 600, 800, and 1200 (Buehler carborundum grits). Wet carborundum paper was used to get a smooth surface on the embedded cut surfaces of the valves. Most of the grinding was done with the 240, 400, 600 grit papers to remove epoxy from the cut surfaces of the valves (Figure 3.9A), the finer grits (800 and 1200) were used to reduce scratches from the coarser grit papers (Figure 3.9B).

Figure ‎3.9: Grinding the cut shell surface sequentially with (A) 300, 600, 800, 1000, and (B) 1200 grade carborundum grits.

Polishing

Cut valve surfaces were polished on a semi automatic polishing machine (FORCIMAT - FORCIPOL 300-1V) in two steps. First, the pad on the plate of the device was soaked with tap water before fixing the plate on the polishing machine. Then, to obtain a shiny surface, aluminum oxide powder was added on the plate. The specimen was connected to the holder in polishing machine and was placed on the rotating plate. Polishing was continued for one hour thereafter the specimen was removed, rinsed in tap water, and dried at room temperature (Figure 3.10).

Etching

Etching was conducted with the aim of leaving the aragonite granules at the surface of valve section that distort the cross section image. Therefore, the polished cut surfaces of the cockles valves were etched by immersing the specimens in the dilute solution of Hydrochloric Acid (0.1% HCl) for one minute. The etched surface were then carefully rinsed with distilled water and dried in room temperature (Figure 3.11).

Observation

The shell cross section was observed with the aid of light microscope–stereo (Olympus SZ61- Olympus Optical Co. Ltd. Tokyo, Japan) at 100X magnification and photographed (Xcam Alpha – The imaging source GmbH). The microgrowth lines were counted and maximum width of each microgrowth increment was measured from the shell margin to 20 or more than 60 increments by using microscopic image analysis software (Analysis Image Processing Version 5.1 - @Olympus soft imaging solutions 1989-2008) (Figure. 3.12).

Environmental parameters

Growth in cockles can be affected by the interactions of various environmental parameters, although food supply is generally the main factor that affects the growth. On the other hand, food availability is influenced by several factors such as temperature, tidal change, salinity, rainfall, pH and water depth (Neves, 2004). Growth studies included laboratory research or field experiments which either manipulate conditions or observe natural changes of these environment factors. Therefore, to determine annual growth rate by means of the growth pattern, it is necessary to examine the daily environmental variations that effect on shell growth using a year-long pattern of daily growth increments.

Daily seawater temperatures

Daily seawater temperature was measured using HOBO Pendant Temp/Light logger fixed to the cage in study area. The logger was calibrated to record hourly seawater temperature in the study site for a period between December 2011 and November 2012. In addition, mean daily seawater temperature was used to determine the effect of daily temperature on growth rate.

Daily seawater salinity

The daily seawater salinity was measured with a hand-held refractometer (RHSN-10ATC BUILT). Before measuring the seawater salinity, the refractometer was calibrated using distilled water. Since distilled water contains no salts, it was used to set the refractometer to a zero reading. A zero offset screw on top of refractometer provided calibration against a known standard (distilled water). Then the daily seawater salinity were measured and recorded at study site.

Rainfall

Rainfall data was provided by the daily measurement taken by Pulau Pinang meteorological station at Bayan Lepas Regional Meteorological Office. The rainfall accumulation measurements were recorded to the nearest 0.1 millimetre, and the rainfall duration was recorded daily from December 2011 to November 2012.

Tidal periodicity

Monthly tide tables of sampling site between December 2011 and November 2012 were obtained from Tide Tables Malaysia (2011-2012) published by National Hydrographica Centre, Royal Malaysia Navy. Total number of daily immersions and emersions were recorded for each site (A, B and C) based on the depth of each point.

Statistical analysis

The SPSS software (Statistical Programme for Social Scientist) version 20.0 was used to carry out statistical analysis of the results obtained in this study. All of the raw data from Microsoft Excel XP was transferred into SPSS software for further analysis.

Linear regression equation

Linear regression was used to deduce relationship between a pair of variables by fitted a linear equation to observed data. One of the two variables was teken to be explanatory variable (X, the independent variable), while the second variable (Y) is a dependent variable. The independent variable X is also called the “predictor” variable while the Y variable is called the “response” variable. The linear regression model relating these variables is given as Y = a + bX,

Where

X is the independent variable

Y is the dependent variable

b is the slope of the line

a is the intercept (the value ofywhenx= 0).

In the current study, relation between weights and lengths of cockles was carried out using a linear regression model.

Pair sample t-test

A paired sample t-test was used to describe whether there was a significant difference between two sets of data values under two different conditions. The number of data in each data set group were similar arranged in pairs, in which there was a specific connection between each two set of data points

Multivariate analysis

Multivariate analysis consists of a collection of methods that can be used when several measurements are made on each individual or object in one or more samples. The measurements were referred as variables and to the individuals or objects as units (research units, sampling units, or experimental units) or observations.

Correlation Matrix

Correlation matrix was used to determine the correlations between all pairs of data sets. In the current study correlation matrix was used to describe correlation between five variables (tidal change, temperature, salinity, rainfall and shell growth). Therefore, it was a square symmetrical 5x5 matrix with a correlation coefficient between each pair of variable. The correlation coefficient varies between –1 to +1, where –1 indicates an inverse perfect relationship, +1 on the other hand shows direct perfect relationship. Correlation coefficient of zero (0) shows that there is no relationship between the variables. Since the correlation of any variable with itself was 1, the diagonal elements of the matrix were all equal to 1 (Hamilton, 1994).

Multiple regression analysis

Multiple regression analysis was used to determine the relationship between several independent or predictor variables and one dependent variable. The dependent variable value was predicted from several independent variables with corresponding coefficients, along with the constant term. Since multiple regression analysis needed several predictor variables, it is known as multiple regression. Thefollowing equationis a multiple regression analysis described by Johnson and Wichern (2002):

Y=a + b₁X₁+ b₂X₂+ b₃X₃

Yis the dependent variable, i.e., predicted or explained

a (Alpha) is the constant term or intercept

b₁ is the Slope (Beta coefficient) for X₁

X₁ is the first independent variable that is explaining the variance in Y

b₂ is the slope (Beta coefficient) for X₂

X₂ is the second independent variable that is explaining the variance in Y

b₃ is the Slope (Beta coefficient) for X₃

X₃ is the third independent variable that is explaining the variance in Y