1.0 INTRODUCTION

1.1 Background to the Study

The Nigerian coastline is characterized by natural sandy and muddy beaches. There are no naturally occurring rocky shores along the Nigerian coast (Edokpayi et al, 2010).

However, between 1908 and 1912, three moles were built seaward to forestall powerful

East- West along shore currents that silt the entrance of Lagos harbour (Awosika, 2001;

Nwankwo, 2004). These three moles at Tarkwa Bay in Lagos provide artificial rocky surfaces for the littoral molluscan communities (Lewis, 1964; Addessi, 1994; Edokpayi et al, 2010). Intertidal rocky shores contain critical habitats which include: migrating route, feeding, nesting, breeding, nursery areas for marine fauna and flora. It also serves as focal points for urban tourism, shell fisheries and scientific research (Asakura and Suzuki,

1987; Nwankwo, 2001; Clarke et al., 2002).

Rocky intertidal communities develop in response to a wide range of interacting factors.

The effect of the daily tidal cycles of submersion and emersion established basic vertical gradients of species richness and biomass (Menge and Daley, 1999; Murray, 2006). The other significant abiotic influences on these communities include the degree of wave action, substrate instability, substrate hardness and heterogeneity, sand inundation, desiccation stress, hydrographic variations i.e currents, upwelling, human induced and natural disturbance (Littler, 1980; Clarke and Grahame, 1999, 2002). The community structure are further and often profoundly, influenced by biotic interactions, especially by the presence of algae, seaweeds, filter feeders, grazing, competition and predation (Wood,

2001; Rose, 2003; Smith, et al., 2008). According to Chapman (2000), habitat, temperature, desiccation, salinity, food, predation and reproduction are the major factors limiting the distribution and abundance of littoral molluscs on global intertidal rocky 1

ecosystems. Coastal area can be regarded as the interface among three habitable media namely earth, air and sea. The ecological importance of the littoral zone in marine ecosystem is widely recognized. The intertidal or littoral portion of the shore, as it is variably described, covers the area between the high and the low tides (Thompson et al.,

2002).

Shores can be classified into three types based on substratum structure: sandy, rocky, and muddy. Rocky shores are more variable than other coastal habitats. Depending on the local geology they may range from steep, overhanging cliffs to wide, gently shelving platforms, from smooth uniform slopes to highly dissected irregular masses or even extensive boulder beaches (Ibe, 1987, 1989, GESAMP, 2001). McQuaid, et al., (1985) documented a decrease in number of species on each shore in an upshore direction probably owing to higher niche heterogeneity on the lower shore coupled with more extreme and less stable conditions at the top of the littoral zone. Littler (1980) observed a variation in the distribution and abundance of organisms on three tidal zones within the southern California bight. The greatest cover of both macrophytes and invertebrates occurred lower in the intertidal zone and decreased upshore direction. Globally, rocky shore ecosystems have been primary research sites for studies of land-sea interactions: morphological, physiological, and life history adaptations, as well as ecological interactions, and the experiments on intertidal shore do not require elaborate oceanographic equipment (Underwood, 2000; Folke, 2004). Information from such studies has been critical to understanding the role of competition, predation, and physical gradient on community dynamics (Wood, 2001; Halpern, et al., 2007; IPCC, 2007; Crain, et al., 2008).

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Artificial rocky shores serve as habitats for preponderant molluscan fauna and flora. They are characterized by high biodiversity, productivity and disturbance in the artificial fractal geometry of the rocky shore assemblages of Tarkwa Bay have been linked to seasonal fluctuations in rainfall, hydrological regime, tides, wave action, desiccation, salinity, shoreline recession and temperature fluctuations (Connell, 1961; Lewis, 1964; Thompson,

1980; Edokpayi and Eruteya, 2012). The physico-chemical characteristics and the algae community of Tarkwa Bay have been described by (Nwankwo, 1993, 2004). The algal community dynamics was reported to depend on seasons, salinity, temperature regimes and depth gradient (Onyema et al., 2009). Intertidal shore animals evolve physiological and behavioural adaptations to withstand the fluctuating nature of the shore environment

(Underwood, 2000; Clarke, et al., 2002; Somero, 2002; Rose, 2003). The wide and rapid changes of temperature and salinity that occur on the shore surface during low tide require high level of eurythermy and euryhalinity in the exposed population (Murray et al., 2006; Murawski, 2007; Riebesell, 2008). They must also be capable of making appropriate adjustments of behaviour in response to changes in their surroundings

(Chapman, 2000). Appropriate changes of activities are required to meet the profoundly different conditions of submergence and exposure to air. Movement, feeding, or reproduction are only possible for many littoral molluscs during the periods when they are covered by waters; and when uncovered, they become more or less inactive (Chesson,

2002; Coleman, et al., 2006). Restriction of movement as the shore dries out during low tides may also help to confine free-living forms to their appropriate zones (Smith, et al.,

2008).

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Some shore animals when removed from the zone, displayed cyclical changes of activity having a tidal frequency, apparently controlled by endogenous rhythms (Underwood,

2000). Wood (2001) reported that a 12 hour-cycle of activities related to the tidal cycle has been observed in shored molluscs. Patella safiana feeds mostly, by scrapping the surface with its long, toothed radular, rasping off the microscopic film of algae which forms a slimy coating on the rocks (Noel, et al, 2009). Marine molluscs often exhibit distinct zonation, with the size of upper intertidal species increasing in an upshore direction, while the size of lower intertidal species decreases in an upshore direction

(Vermeij, 1972, 1973, 1974; Pauly, et al., 2005). It has been reported that the upper limits of marine intertidal molluscs are limited by physical factors, while lower limits are constrained by biological factors (Noel, et al., 2009; Murawski, 2007). Differential growth rates and active migrations have also been proposed to explain size gradients within an intertidal community (Sivadas, et al., 2008). It was suggested that the migratory nature of these species was related to the increased tolerance of larger molluscan species to conditions of increasing desiccation stress (Rose, 2003; Stirling, 2007).

There is dearth of scientific information on the diversity, distributions, growth, feeding, heavy metal distribution, and reproduction of the attached molluscs of the three moles of

Tarkwa Bay. This study has been designed to provide a comparative ecology and taxonomic inventory of the resident molluscan communities of the three moles of Tarkwa

Bay, Lagos, Nigeria.

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1.2 Statement of Problem

There is dearth of scientific information on molluscs worldwide and in particular on the resident molluscan communities on the shores of the three artificial breakwaters of

Tarkwa Bay, thus leaving a gap in our knowledge of the resident molluscs on intertidal shores. It may be difficult to know when the shores are invaded by exotic species from trans-oceanic tankers‟ ballast waters. Intertidal molluscs are important food items of maritime communities in Tarkwa Bay because of their high protein content (Faulkner,

1992). Data on the biology and the general ecology of the molluscan communities of

Tarkwa Bay that are of ecological, economic, and commercial interest that would stimulate research on mass production, sustainable exploitation are sparse. Globally, there is dearth of taxonomic experts, and this has affected the study of molluscs worldwide.

Available literature on how environmental chemistry, and alterations related to human activities affect molluscan dynamic on the global scale (Lewis, 1964; Thompson, 1980;

Edokpayi and Eruteya, 2012).

Tarkwa Bay coast is frequently subjected to multiple sources of stress operating over several spatial and temporal scales (Ukwe, et al., 2003). Exponential population growth and anthropogenically-driven changes affect the molluscan community dynamic on the

Tarkwa Bay shores (Ajao, 1994). Physical alteration and destruction of habitats through land reclamation and landfilling during coastal development, affects water quality.

Changes in sediment morphology brought about by shoreline modifications i.e by dredging of harbour and shipping channels, construction of embayment and marinas as reported by (Ibe, 2005) affect intertidal molluscan population dynamics.

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1.3 Aim:

This study is aimed at investigating the bio-ecology of molluscan fauna of the three moles of Tarkwa Bay.

1.3.1 Objectives:

The following were the specific objectives of the study:

1. Investigate the spatial and temporal variations in physico-chemical parameters of

the three moles of Tarkwa Bay.

2. Determine the composition, abundance, diversity, distribution of the

molluscan communities of the three moles of Tarkwa Bay.

3. Investigate the patterns of growth in molluscs of interest in the laboratory, and

the three different tidal zones on the shores of the study area.

4. Study the temporal variations of algae in the gut content of the selected

intertidal molluscs of the three moles of Tarkwa Bay.

5. Investigate the level of heavy metal concentrations in seawater, seaweeds

and selected intertidal molluscs of the study area;

6. Describe the pattern of reproductive activities in the selected species of molluscs

by investigating temporal changes in Gonad-Somatic Index (GSI), size at

sexual maturity and sex ratio (SR).

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1.4 Significance of the Study

Tarkwa Bay Beach is a popular tourist‟s destination, and supports important socio- economic activities such as aquaculture development, sand and gravel extraction, coastal development, dredging of harbour and shipping channels and construction of harbour protecting structures (Ibe, 1987, 1989; Awosika, 2001). The coastal communities of

Tarkwa Bay rely heavily on the molluscan fauna as source of protein rich diets and income, as such; this study would optimise food security and poverty reduction among the Tarkwa Bay coastal communities. This report would be useful for initiating large scale and long-term programs for monitoring molluscan community and coastal water quality of Tarkwa Bay. The study would provide basic taxonomic inventories and compilation of the resident molluscan communities on the shores of Tarkwa Bay area, which will be useful for future assessments and ecotourism development. Information on water quality, dietary preference and heavy metal concentration will be handy for shellfish industries. Again, the dataset documented in this study would contribute to the advancement of our understanding of the status and the trends of tropical marine ecosystems at regional scale, providing an important support for conservation and management of tropical Bay. The study would establish seasonal influence and reproductive patterns in selected molluscs, which will serve as valuable tools for breeding and conservation of intertidal molluscs.

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1.5 RESEARCH QUESTIONS.

The project was designed to answer the following research questions:

1. What are the effects of seasonality on the physico-chemical parameters of the three moles of Tarkwa Bay?

2. What are the seasonality in the distribution patterns of molluscs along the shorelines of the three moles of Tarkwa Bay?

3. What are the patterns of growth shown by conspecific, interspecific molluscs cultured in the laboratory and under different tidal zones on the shores?

4. What are the correlations between algae and molluscan dynamics in dry and rainy seasons?

5. What are the levels of heavy metal concentrations in seawaters, seaweeds and the selected molluscan species of the study area?

6. What are the effects of seasonality on the reproductive biology of the study species of the three moles of Tarkwa Bay?

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CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Physico-chemical characteristics

The dynamics of the molluscan assemblages in intertidal shores are influenced by physico-chemical parameters of the water masses notably temperature, salinity and dissolved oxygen (Koranteng, 1998). It has been reported by (Awosika, 1990, 2001), that coastal habitats worldwide are responsive to temporal conditions. Seasons bring changes in air, rock, water temperature, salinity, wind frequency, storm and duration of sunlight

(Lewis, 1964; Nkwoji et al, 2010). During rainy season, extra-tropical storms deliver massive amount of precipitation that dilute seawater, produce erosive waves, mobilize sediment, and increase turbidity (Koranteng, 1998; Smith et al, 2008). The complex dynamism in physico-chemical characteristics of coastal waters is related to riverine flow, upwelling, atmospheric deposition, vertical mixing and other anthropogenic sources

(Chukwu and Nwankwo, 2004; Edokpayi and Eruteya, 2012).

Somero (2002) reported that temperature is an important environmental factor influencing all life functions of an organism through changes in the rates of biochemical, physiological processes and in the stability of biomolecules. Adaptation to environmental temperature is recognized as one of the evolutionary mainstreams and is thought to be dependent, to a large extent, on the organism‟s ability for metabolic adjustment on both short-term and evolutionary time scales (Gonor and kemp, 1978; Clarke, 1998).

Metabolic adjustments in response to temperature change are especially crucial for aquatic ecthotherms, whose body temperature fluctuates over the full range of their habitat temperatures (Odiete, 1998, 1999; Somero, 2002). These environmental stresses

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may have synergistic negative effects on survival and performance of intertidal molluscs during prolonged emersion. That is why it could be expected that adaptation to high shore life involves adjustments to several important physiological functions, including characteristics of water economy, temperature resistance and metabolic regulation (Barry,

2001; Clarke et al., 2002).

High shore intertidal molluscs, due to their semi-terrestial mode of life, experience fast and frequent temperature changes, both predictable (i.e associated with the circadian, circatidal and seasonal variations) and unpredictable (i.e irregular short-term changes that are especially pronounced during low tide due to the low thermal buffering capacity of the air (Branch, 1981; Seben, 1985; Newell, 1997; Denny and Wethey, 2001). Besides, foraging times and food abundance are frequently limiting in the intertidal compared with subtidal levels, posing energy constrainsts and requiring a tight matching of energy demand and supply in intertidal inhabitants (Hughes, 1984, 1986; Chapman, 2000;

Thompson, et al., 2002). As a result, adaptation to intertidal life entails high metabolic flexibility and efficient regulation of metabolism in a wide range of environmental temperatures (Britton, 2005; Sivadas, et al., 2008).

Salinity is among the most important environmental factors that exerts various effects on the vitality of marine organisms. It acquires particular importance in marine areas with unstable salinity regimes, such as rivers, estuaries, salt marshes (Underwood, 1979, 1980;

Britton, 2005). Only organisms with effective adaptations to unfavourable salinity can live in such habitats. In this case, the so-called critical phase of development, which is characterized by the smallest adaptive capabilities in respect to the unfavourable environmental factors, often plays a crucial role in the development of stable population of a certain species and their further survival (Workman, 1983; Witman, 1985; Wood,

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2001). As a rule, in most organisms, all the early ontogenetic phases (embryos, larvae, and young) are critical (Murawski, 2007).

2.2 Rocky Shores: Environmental Conditions.

The rocky intertidal shore is among the most physically harsh environments on earth

(Lewis, 1964; Rose, 2003). This marine habitat is a complex, variable and often- unpredictable environment with periodic extreme events such as: flood, storm, wave action, desiccation, temperature, salinity and oxygen deficiency during low tide (Menge and Daley, 1997, 1999; Underwood, 1999, 2000). The degree and duration of environmental stresses increase from low to high shore level (Raffaelli and Hawkins,

1996; Rose, 2003). As a result, the steep physical gradient and spatially condensed community has made the rocky intertidal zone an ideal natural laboratory to study the coupled role of physical and biological factors in determining the abundance and distribution of organisms in nature (Connell, 1994; Ukwe et al, 2003).

2.3 Molluscan Communities and Adaptations

Adaptation to high shore life involves adjustments of several important physiological functions, including characteristics of water economy, temperature resistance and metabolic rate depressions (Denny, 1985, 1989; Somero, 2002; Stirling 2007). Numerous studies have shown that adaptation to high intertidal environments may involve the increased thermal resistance of an organism (Stirling 2007; McMahon 1990; Britton

2005; Rose, 2003). Temperature has played a dominant role in assessing the importance of physical factors in setting the limits of vertical zonation pattern in rocky intertidal communities. The options utilised to buffer the effects of harsh littoral life include: thermo-regulatory, anti-desiccatory behaviours, multi-layered aggregation, extra-visceral

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water loss, reduced tissue temperature by evaporatory cooling are the major strategies for stress reduction (Bustamante et a1., 1995, 1997; McMahon, 1990; Wood, 2001).

2.4 Invertebrate communities of Lagos harbour and Gulf of Guinea.

In Lagos harbour, the distribution of Balanus pallidus stutsburi, Grypha garsar,

Mercierella enigmatica, Hydroides uncinata have been reported to vary according to salinity concentrations, biological competition, season, and the region of the harbour (Hill and Webb, 1958; Edokpayi et al, 2010). Most of these marine forms suffer heavy mortality when salinity is low during the rainy season. It was reported by early workers that the distribution depend mainly on seasonal fluctuation in salinity, biotic predation as temperature remain constant through the year (Mensah and Koranteng, 1988; Oyenekan,

1988; Folke, 2004). The littoral algae reported on the West mole include: Chaetomorpha anteninna, Cladophora prolifera, Bryopsis pennate, Hypnea musciformis (Nwankwo,

2004; Onyema, et al, 2009; Edokpayi et al, 2010).

The plankton communities in the Gulf Guinea have been reviewed: Dinoflagellates

(Peridinium, Ceratium, Prorocentrum, Dinophysis (Longhurst, 1964). Diatom flora:

Skeletonema, Nitzschia and Thalassiosira (Anang, 1979). Zooplankton (Copepoda,

Ostracoda, Cladocera, Larvacea, Thaliacea, Chaetognatha, Copepods were found to outnumber any other taxonomic group of zooplankton (Mensah, 1995). Edmunds (1978) reported the distributions of the following molluscs along the coasts of Gulf of Guinea:

Neritidae (Neritina); Littorinidae (Littorina); Nassaridae (Nassarius); Conidae (Conus);

Muricidae (Murex); Cerithiidae (Cerithium); Patellidae (Patella safiana); Buccinidae

(Buccinum undatum); Calyptraeidae (Crepidula fornicata); Mytilidae (Mytilus edulis).

Koranteng (1998) reported that the invertebrate assemblages in Gulf of Guinea are

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influenced by physico-chemical parameters of the water masses, mainly temperature, salinity and dissolved oxygen.

2.5 The Biology of intertidal molluscs.

2.5.1 Feeding: The diets of intertidal molluscs largely comprises of microalgae, encrusting algae and young stages of erect macro- algae (Branch, 1981; Noel, et al,

2009). It was also reported by early workers (Lewis, 1964; Farina, et al., 2003; Moral, et al, 2007) that feeding activity in intertidal molluscs depends on nature and the types of algae, radula, availability of food on the shore, height of molluscs on the shore, and tidal regime. The duration of the available feed time at a particular height on the shore is likely to affect the feeding rate of intertidal molluscs. The evolutionary success is attributable to the structural and functional plasticity of feeding apparatus (Thompson, 1980; Steneck and Watling, 1982; Norton and William, 1990). The development of molluscs for aquaculture programmes requires a robust scientific knowledge about the algal diets, mollusc´s feeding regime, and consumption rates (Hughes, 1984, 1986; Geller, 1990;

Nair, 1990).

2.5.2 Gut Content Analysis: It is a useful tool for the study of dietary source and trophodynamics within food webs. It provides insight into mechanisms regulating patterns of resource partitioning and co-existence on seasonally controlled tropical shores

(Underwood, 1997; Farina et al., 2003; Noel et al, 2009). It provides a theoretical framework of what food resources, molluscan communities on intertidal shores are capable of exploiting and also, revealing trophic level relationships.

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2.5.3 Growth of intertidal molluscs:

The growth dynamics of intertidal molluscs vary with different habitats, food availability, reproductive activities, and it also correlated with the rate of algal production

(Underwood, 1979; Murray, et al, 2006; Murawski, et al, 2007). The growth rate of shelled marine molluscs is usually measured as an increase in shell length (mm) and a variety of methods have been used to measure growth rates of molluscs. Branch (1981) reported that growth rates in molluscs depend on exogenous factors such as: exposure to wave action, temperature, genetic difference and density.

Growth patterns of mollusc received most attention because of its importance as seafood, ornamental and medicinal use. Most work is done on bivalves as compared to gastropods

(Thompson, et al., 2002; Masefield, 2009). Most of the work on gastropods are related to the descriptive patterns of species and provide information on larval development. The growth pattern is usually estimated through size frequency distribution (Paine, 1980,

1992; Underwood, 2000).

Branch (1981) observed the growth of herbivorous limpets from South Africa, Cape of

Good Hope. The zonation, population, size-frequency and biomass of Nerita undatum, N plicata, N. polita, N. albicilla, N. textilies were investigated by (Sivadas, et al., 2008).

Few references are available relating to allometric growth of gastropod molluscs (Murray, et al., 2006). Generally, desiccation and wave action appear to exert the most influence on the morphological characteristics of intertidal organisms (Johannesson, 1994). Allometric growth, where shell height increases more rapidly than shell length, is common in high- shore molluscs. Shell texture may also play a role in thermoregulation (Somero, 2002).

Molluscs inhabiting areas which are, to a large degree, protected from the sun tend to

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have smooth shells while those exposed to direct sunlight are scultured (Yamada and

Boulding, 1998; Vermeij, 1972, 1973 and 1974). Textured shells increase re-radiation of heat and in doing so, reduce heat stress (Vermeij, 1982).

Many marine molluscs show seasonal variation in growth rates, both within and between species (Vermeij, 1980). Athougth some intra-specific variation may be genetically controlled (Mensah, et al., 1988), exogenous factors such as changes in food availability, waves action and positions on the shores (Branch, 1981; Underwood, 2000; Morton and

Blackmore, 2001), greatly influence growth rate. In addition, intra- and interspecific competition can also affect growth (Branch, 1981).

The growth rates of shelled marine molluscs is usually measured as an increase in shell length and variety methods have been used to estimate the growth rate of intertidal molluscs. These include: periodic monitoring of marked individuals (Gray, 1996), checks in growth as a result of known changes in environmental factors (Underwood, 2000), and cohort analysis (Gray, 1996).

Allometric growth, where shell heigtht (SH) increases more rapidly than shell length

(SL), is common in high-shore limpets (Branch, 1981). The rate of water loss in these animals is lower than molluscs which grow isometrically (i.e shell length increases more rapidly than shell height (Branch, 1981). Variation in the Allometric relationship may occur between sexes, reproductive seasons and changing environmental conditions

(Vermeij, 1980). Allometric shell dimensions are essential for generating useful information for managing resources and understanding changes in environmental conditions and pollution.

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2.5.4 Heavy metal distributions in seawater, seaweeds and selected molluscs.

Tarkwa Bay has suffered from water quality deterioration due to rapid increase in human population and industrialization (Edokpayi et al, 2010). Factors affecting metal toxicity in aquatic environment includes: physico-chemical state, pH, redox potential, salinity, temperature and concentrations of nutrients (nitrate and phosphorus). Several studies have been conducted on heavy metal concentrations of aquatic biota in Lagos harbour, Lagos

Lagoon and estuarine animals, but these types of studies have not been conducted on molluscan communities of Tarkwa Bay. The biological effects of heavy metals range from beneficial stimulation to harmful retardation and death (Usero, 2005). Some metals including copper (Cu), Manganese (Mn), Iron (Fe), Zinc (Zn), Cobalt (Co), and

Vanadium (V) are essential for good health and normal growth; playing important roles in key metabolic activities in plants and animals (Oyewo, 1998). Such essential elements only become toxic when concentrations exceed the the trace amounts required for normal metabolism (Usero, 2005). Other heavy metals like lead (Pb), Candium (Cd), and mercury (Hg) are non-essential to the physiological activities of living of organisms

(Bryan et al., 1980; Bryan and Gibbs, 1983; Rainbow, 1995; Oyewo, 1998).

The persistence of heavy metals in aquatic environments poses a danger to human consumers of seafoods. For example, heavy metals which are non biodegrable, easily accumulate in the tissues of aquatic organisms and their movement through the food chain is further enhanced when a carnivore feeds on metal infested preys and their tissues

"food chain effects" ( Hawkins and Hartnoll, 1983; Usero, et al., 2005). Inspite of regular discharges of heavy metals into aquatic systems from industrial and domestic sources, the observed concentrations are rarely high enough to bring about acute toxicity.

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Therefore, for practical ecological considerations, adequate of knowledge of the harmful effects associated with sub-lethal concentrations are more important for the proper control and management of heavy metal pollution (Bryan and Gibbs, 1983; Smith, et al., 2008).

A number of scientific reports have confirmed that heavy metals at sublethal concentrations can adversely affect metabolic activities reduce reproductive success and cause gross morphological malformations of important organs in some sensitive animal and plant species. The factors that influence the toxicity of heavy metals in water include the presence of chelating agents, for example proteins metallothioneins and metalothioneins-like compounds. Where complexation leads to the sequestration of heavy metals and hence their non-availability, significant reduction in toxicity occurs

(Morton, and Blackmore, 2001).

It is now expedient to carry out (i) a survey of spatial and temporal trends of heavy metal,

(ii) food web approach by analyses of seawaters, seaweeds and molluscs of interest (bio- accumulation of heavy metals) that may pose public health risk to human. Heavy metals have been reported in biota of Bays in other parts of the world to have accumulated in higher concentrations in higher trophic levels of food chain because of biological magnification.

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2.5.5 Reproduction in intertidal molluscs:

Most studies on the reproductive biology of intertidal molluscs focused upon the assessment of the gonadal cycles (Creese, 1980; Fletcher, 1987; Hahn, 1989, 1994).

Reproductive data on intertidal populations are time consuming and costly to obtain, and large gaps exist in our understanding of the reproductive cycles and outputs of molluscan communities of artificial breakwaters of Tarkwa Bay. Food availability is also a factor that influence molluscs‟ reproductive cycle (Rocha-Barreira, 2002). The gonadal cycle is cued to sea surface temperature rise, while spawning may be triggered by rough sea and on-shore winds (Parry, 1982; Underwood, 1997; Dunmore and Schiel, 2000).

Many marine invertebrates which have an annual reproductive cycle show seasonal variation in the timing of gametogenesis and spawning. This variability indicates that reproductive cycles within populations must be synchronised by external environmental factors (Clarke et al., 1999). Wave action, food availability, temperature and daylenght, all influence gonadal development (Foster and Hodgson, 1995). The environmental factors that trigger spawing may, however, be different to those that initiate gonadal growth (Bowman, 1985), phytoplankton booms (Himmelman, 1979), increased wave action and wind speed (Thompson, 1979), sperm suspension (Himmelman, 1979), lunar cycles (Fretter, 1984), hormone, and a combination of these factors.

Both inter- and intraspecific relationship between the reproductive pattern and the geographic distribution of invertebrates may occur. Generally, species from low latitudes have an extended breeding season, while those from higher latitudes have a restricted one

(Fretter, 1984). Very little is known about the reproductive biology of resident molluscs of intertidal rocky shore of Tarkwa Bay.

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2.6 Effect of Physical and Physiological Stress on the Distribution

of Intertidal Molluscs.

The upper distribution of intertidal organisms on rocky shores is thought to be determined by a number of physical factors of which desiccation is considered to be an important factor (Underwood, 1979). It has been recorded that molluscs move upwards on the shore during storms (Thompson, et al, 2005); conversely, limpets move downwards on the shore during hot, dry condition (Murray, et al, 2006). Both short and long-term movements up and down the shore are thought to be related to desiccation (Hutchinson and William, 2003; Murawski, 2007). Wave action and the associated hydrodynamic forces, vary along coastlines and are correlated with prominent changes in community structure on the rocky shores worldwide (Menge and Sutherland, 1987; Mensah and

Koranteng, 1988; Mora, et al, 2007). At large scales, the wave exposure of a particular coastline is determined by the primary wind direction (Denny, 1985, 1988; Newell,

1997). At small scales, bathymetry and shores topography affect wave exposure. On shallow sloping shores, waves will break and form energy dissipating bores far from shorelines, reducing littoral wave exposure. Deep water, wave height, and steepness also affect the properties of breaking waves; a particular shore may experience different types of waves according to the different conditions available (Denny, 1985, 1988; Denny and

Gaylord, 2002). Waves are the most prominent modifiers of tides, which ameliorate temperatures and desiccating conditions. Lewis (1964) notes that the run-up, maximum vertical displacement of wave wash, the maximum horizontal displacement of waves wash associated with wave action are affected by shore topography, coastal bathymetry, wave height, and wave length ((Witman, 1985; Denny, 1988). The magnitude of tides are categorized as microtidal (0- 2m), mesotidal (4 -6m) and megatidal (>6m), (Bolton,

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1990). Tidal magnitude has a direct effect on the size of a littoral zone, but of little implication on the physiological stresses experienced by molluscan fauna, and this depends on the geographical location. Tides may follow diurnal (one cycle per day), semi-diurnal (two cycle per day), or semi-diurnal mixes (two cycle per day), of unequal amplitude (Lewis, 1964). Low tides occurring in the mid-afternoon will precipitate greater temperatures and desiccating conditions than those occurring at night (Thompson,

1980; Waugh, 2000). Denny (1988), affirmed that the duration, timing and patterns of immersion and emersion caused by tides are considered as paramount factors affecting the climate at air-water interface.The environmental stress affecting littoral organisms can be categorized as either physiological or physical (Menge and Sutherland, 1987;

Riebesell, 2008). Physiological stressors directly affect the biochemical and physiological processes carried out within organisms. Molluscs have differential abilities to withstand various types of environmental stress that ultimately affect their distributions in nature

(Menge and Sutherland, 1987).

The most prominent physiological stresses experienced by littoral organisms are extreme temperature, desiccation and extreme solar irradiation. Ocean water acts as a buffer to variations in temperature stress because of its high specific heat capacity 4200J/kg/k

(Denny, 1993). The same cannot be said for air (1000J/kg/k) (Denny, 1993) and especially rock surfaces such as granite (300J/kg/k). Materials with low specific heat capacities change temperature easily with little energy input. As a result rocks are heated to temperature greater than water by solar irradiation. Intertidal molluscan fauna can buffer this stress with large mass, low surface area to mass ratio, reflective colouration

(Denny, 1993) Physiological stress peak during mid-day at low tide, with small waves and clear skies (Sousa, 1979; Denny, 2000). The maximum vertical extent of any littoral

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species population on a coastal is ultimately determined by these factors. High temperature can affect protein stability, heart functions, fluidity, and generally alter biochemical reactions (Somero, 2002). In algae, high temperature can damage the photosynthetic apparatus (Underwood, 2000), and the effects of wave action (Denny,

1985). The magnitude of the variation in thermal stress with shore height is surprisingly understudied. Early interest in the effects of shore height on thermal stress implicated the role of “critical tidal levels” heights on the shores where the duration of aerial emersion shifted markedly. All intertidal species have limited ranges of tolerance towards specific environmental conditions and each species tends to be most abundant at its particular range of optimum temperature (Riebesell, 2008). Most intertidal rocky shore organisms are thermoconformers, which means that they cannot maintain body temperature different from their surrounding environment (Smith, 2008).There is dearth of information on the community structure of the molluscan fauna on the artificial breakwaters of Tarkwa Bay.

2.6.1 Effect of Sea Surface Temperature (SST) on intertidal Molluscs

Temperature is one of the most important factors determining the distribution of marine species on a biogeographical scale (Bolton and Anderson, 1990; Emmanuel, et al., 1992)

Bustamante and Branch, 1996a). Temperature not only governs the species distribution but also controls the rates of metabolism and development and induces many important behavioural and physiological responses such as migration and reproduction (Ray et al.,

1992). Most marine organisms have some acclimatization capacity, an adjustment of thermal tolerance depending on the season, such acclimatization capacity can either be behavioural or physiological (Ray et al., 1992; Little and Kitching, 1996).

The effect of sea temperature on marine intertidal organisms can be either direct or indirect or through a combination of both. The direct influence of temperature could 21

cause changes in the survival, reproductive success and behaviour of species, and may alter dispersal patterns. Larval and juvenile stages often tend to be less tolerant than adult molluscs, and it thus would appear that recruitment may be more than adult mortality in constraining the limits of species with planktonic larval phase (Underwood and Fair-

Weather, 1989). A change in SST will not only influence directly the distribution pattern of species but also may alter the existing strength of biological interactions. Changes in competition, grazing or predation patterns can therefore also affect the molluscan communities of intertidal rocky shores (Beardall et al., 1998). It is also predicted that even a small rise in SST will have significant effect on the life histories, growth and distribution of some microalgae (Beardall et al., 1998). Warm-water species increase in abundance and extends their range during warming, while cold-water species declined or retreated (Barry et al., 1995).

2.6.2 Ecological implications of shore height on intertidal molluscs

Early intertidal studies favoured a major role of physiological adaptations to temperature and desiccation stress in determining patterns of vertical distribution (zonation) commonly found in intertidal organisms on rock shores. It was shown that lethal limits of marine organisms correlated positively with the position of organisms along the physical gradient from the low intertidal zone to the stressful high intertidal zone, especially if differences in microhabitats and wave-exposure were taken into account (Sutherland,

1976, 1987). The physical gradient and spatially diverse community has made the rocky intertidal zone an ideal “natural laboratory” to study the coupled role of physical and biological factors in determining the abundance and distribution of organisms in nature

(Connell, 1961, 1964). Seasonal shifts in vertical distributions are common, especially in wave-swept temperate sites, as are ontogenic shifts in shores height (Newell, 1979;

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Bertness et al., 1994 and Vermeij, 1972, 1974). During the rainy season months snails on wave-swept shores move upshore while large waves splash higher on the shore and then retreat downward during dry season (Bertness et al., 1994; Johannesson, 2003).

The vertical distribution of each species may be derived by several factors, some of which the heat-budget model can be used to explore the effects of solar irradiation on intertidal molluscs. Thermal stress can vary with height on the shore due to the cycling of the tides relative to lower levels due to the frequency of submersion caused by semi- diurnal or mixed semi-diurnal tidal cycles (Denny, 1988; underwood, 2000). While the idea of the primacy of the tides in establishing zones occupied by species with differing tolerances for aerial emersion was intuitively attractive, the ability to rigidly define the extent of zones on a particular shore due solely to the tidal cycle was complicated by plethora of confounding factors, chief among them is the effects of wave, action and biotic interactions such as grazing and predation (Underwood, 1978).

The critical tidal levels are of dubious benefit for describing the vertical limits of most intertidal organisms but certain aspects of the critical tidal level concept have not been wholly discarded. McMahon (1990), concerned with physiological adaptations of high shore snails simplified the concept and proposed that there was one important vertical boundary on the seashore, the height reached by high tides. Above this height, shore is not reliably wet by tides, while the regions, below this mark are submerged daily. As a result, organisms living above the high tide mark must contend with unpredictable and often prolonged periods of aerial emersion, while organisms below can rely on being washed by the tide once within a day.

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2.6.3 Ecological Effects of Shell Size and Shape of Intertidal Molluscs.

The size of an organism will affect the body temperature, to achieve during the course of a hot day (Newell, 1976; Helmuth, 1998, 1999). Large organisms have a larger projected area with which to absorb short-wave radiation, along the substratum and for convection

(Underwood, 2000), all of which can affect body temperature. Larger organisms also have more thermal inertia, resulting in slower heating and cooling rates relative to a smaller organism of the same basic shape (Helmuth, 2002). However, the heat model in the form used here ignores the contribution of stored heat, removing the effect of thermal inertia from the predation of the body temperature. Thermal inertia has only a negligible effect on body temperature. (Denny, 1995; Helmuth, 2002) documented that most molluscs change shape as they grow, a fact that makes simple scaling of empirically measured parameters of the shells in the shore potentially inaccurate. Heat transfer coefficients, projected areas, surface areas, and contact areas all scale non-linearly as the shape of the snail changes throughout its life. The predicted temperatures from the sphere can be used as a standard of comparison allowing us to explore how effectively the shape of the shell and behaviour keep snails cool on hot days.

Littorine snails can be found with varying amounts of sculpturing on the shell, different shell thickness, and different spine heights that affect the overall shape of the shell. These differences have been hypothesized to arise for a number of reasons, such as temperature regulation (Vermeij, 1973) wave action (Currey and Hughes, 1982) and predation pressure (Vermeij, 1982 and Trussell, 2002).

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2.6.1 Ecological Implications of molluscan faunal shell colours.

Denny(1985) noted that species feeding mainly on mussels are white, spirally banded with orange or brown, but those feeding on barnacles are of a white uniform colouration.

Reimchem (1989) has attributed the differences in molluscan shell colours to differences in survival in adverse environmental conditions. The interplay between colours and temperature has received substantial attention. It was long established that dark colours absorbs more short wave radiation, thereby increasing the heat energy influx into the body relative to a lighter colour (Rose, et al., 2003). This concept has ecological implication particularly the ectothermic animals where activity levels are often governed by the body temperature of the intertidal animals (Reichem, 1979, 1980).

The hypotheses explaining shell colours variation in shells and among species have typically centred on the role of colour in determining the body temperature of a snail

(Markel, 1971; Vermeij, 1971; McQuaid, 1992). Reimchem (1979); Heller (1981);

Johannesson and Ekendah (2002) have worked on the role of shell colour in crypsis by providing protection from visual predators. Surge and Walker (2006) stressed that molluscan fauna living on temperate rocky shores especially the Northern Europe, dark brown morphs benefited from faster heating and higher equilibrium body temperature that allowed them to forage more actively during cold period.

The most extensive test of the effect of shell colour on survival in intertidal molluscs was carried out by Etter (1988) on Nucella lapillus from New England. In the laboratory, brown morph, of Nucella lapillus reached temperatures that were on average 2oC warmer than white non-specific when both groups were set out in the sun. Heating rates were also faster in the brown morph. In the field, the results were less clear, with brown morph

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registering temperature up to 30oC warmer than white morphs in specific microhabitats. It was concluded that the combination of higher body temperature, coupled with increase evaporation due to the higher temperature, led to higher mortality in brown morphs on hot shorelines (Rose, 2003) The natural distribution of the white and brown colour morphs followed the pattern of thermal stress present along the environmental gradient from wave-exposed, algae-covered sites to wave-protected, barnacle-dominated sites (Smith et al., 2008). Dark shell colours lead to substantial differences in body temperature during high temperature periods. The differences that could impact the survival of molluscan faunal dark coloured shell provided a benefit by raising body temperature during cold periods, potentially allowing higher activity levels (Garg et al., 2009).

2.7.0 Economic Importance of Intertidal Molluscs

The importance of molluscs in the economy of a country cannot be denied. Molluscan shellfish have long been a source of protein food to the coastal communities worldwide

(Faulkner, 1992). The intertidal rocky shores worldwide provide vast biological store- house of potentially useful molluscs and chemicals for biotechnological industries. Many intertidal molluscs have potential commercial uses, especially in the field of healthcare and nutrition (Masefield, 2009). For example the prosobranch, gastropod; Muricidae is now the basis of antiviral medicine and two anticancer drugs (Faulkner, 1992). Blood drawn from the seahare is now used to detect potentially harmful toxins in drugs, medical devices and water (Wells, 1989).

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Many intertidal molluscs produce biologically active compound that have therapeutic use

(Faulkner, 1992). Extracts from intertidal molluscs yield anti-inflammatory and antibiotic substances (Wells, 1989). Some corals produce antimicrobial compounds and the sea anemones, Anthopleura, provides cardiac stimulant (Faulkner, 1992). Extracts from

Abalone and Oysters act as antibacterial agents and a muscle relaxant has been isolated from the intertidal molluscan fauna (Murex). Thousands of active compounds from marine molluscs have been screened for their anticancer, anti-inflammatory, anti-tumour, immune suppressant and anti-viral possibilities (Waugh, 2001). Using the tools of molecular biology, it is now possible to screen substance rapidly for example to test natural compounds for their effect on enzymes responsible for the growth cancer cells

(Carte et al.1986). Most of the extracts from intertidal molluscs are chemically mediated bioactive compounds that prevent predation and give intertidal animals an advantage in competition for space (Beesley et al., 1998). Faulkner (1992) reviewed that collecting, extracting, identifying and evaluating active natural compound from the molluscs is time consuming and expensive.

The exquisite form and durability of texture of molluscan shells often coupled with pleasing colour patterns have made some of the seashells covetable possessions of man from primitive age to the present day civilizations. The largest utilization of the molluscan shells is for burning them into lime to be used in masonry, constructions and white washing of building (Barry, 2001) In the international market, there is a good demand for molluscan products. In the Far East countries, molluscan products fetch higher prices (Bamabe, 1990). Octopi, cuttle fishes, squid, oysters and mussels have a good market in European countries especially in the Western Europe different species of gastropods are utilized as food, shells for ornamental and medicinal use (Rose, 2003), as

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a diet for other animals like shrimps (Lewis, 1964), mother of pearl for the manufacture of buttons and woods in lays (Lewis, 1964) and becomes the significant external trade in various part of the world like India, Indonesia, Thailand, Australia, Japan and USA.

The cowries are important in various fields, of which the most remarkable is their use as a medium of exchange (replacing the old barter system). This practice was so common in many parts of the globe that it has not yet completely die out. Ornamentaria annulus is used as ornaments. Gambling with cowries, though ancient, is still in use. The total export of fresh and frozen oyster is about 24,000 metric tons (FAO, 2002). Brown mussel fishing is a regular industry of considerable local importance along the coastal area of India. It is a food of great delicacy and liked by all fish eating people (Pauly, et al., 2005). Most intertidal molluscs are used currently for assessing climate change and environmental damage in technologically advanced countries of the world. The intertidal molluscs have broad spectra of activities which are sensitive to subtle environmental changes (Kido,

2002). The various species of intertidal molluscs used as biological indicators are sessile ubitiquous, and are affected by all forms of environmental changes. Some are diadromous species (Godwin, 2006). Species of molluscs such as Neritina espertinus, (Sowerby,

1849), Neritina fluviatius. Linnaeus, 1758, Neritina solidissima (Sowerby, 1849),

Neritina sandirichensis (Reeve, 1855) are frequently used as biological indicators for climate change (Koch, 2004).

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2.3.3 Strategies for Molluscan Conservation and Sustainable Utilization.

The molluscs are heterogeneous group of animals with great diversity. Hundreds of molluscan species have been recorded from various parts of the world (Rose, 2003). In

Nigeria‟s coastal communities; gastropods, cephalopods and bivalve fisheries are used for commercial and consumption purposes by coastal communities, conversely, shells are sources of raw materials for shellcrafts, lime, paints, decorative and industrial purposes.

Commercial exploitation accounts for the greater reduction of molluscan population in nature, pollution and environmental hazards also cause the extinction of molluscs and to a lesser magnitude, the professional shell collection from wild (Claassen, 1998; Islam and

Tanaka, 2004). Indiscriminate fishing from natural bed may lead to depletion of stock of most of the molluscan resources of Tarkwa Bay rocky shores. During the peak-harvesting season, huge numbers of undersize molluscs are being exploited from natural beds along with adult and discarded in the artificial breakwaters of Tarkwa Bay. Instead of discarding these „by-catch‟ they can be re-introduced into the natural environment or sustainably utilized for farming will increase the present production of intertidal marine molluscs manifold. To conserve these resources wisely, the setting up of “Molluscan

Sanctuaries” or “Molluscan Park”, “Breeding Reserves” in these artificial rocky breakwaters of Tarkwa Bay are necessary. The stock level in the wild can be used sustainably by “seasonal closure” for fishing, declaration of some areas of high biodiversity as “prohibited areas” for fishing certain sizes of molluscs of commercial sizes. Furthermore, the artificial seed production (hatcheries) of the particular species identified as overexploited through surveys based on IUCN categorization and sea- ranching can be enhance the wild stock population in future (Masefield, 2009).

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Fisheries management in intertidal rocky shore ecosystem can be enhanced through the participation of local shell fishermen to provide wealth of local indigenous knowledge to supplement scientific information to help monitor the resources, and to improve overall management of molluscan populations in the wild. Strategies for the conservation and sustainable use of molluscs include environmental protection with the emphasis on water quality control, stock assessment. Promotion of small-scale fisheries can be improved through provision of necessary coastal infrastructure at the local level, and dissemination of fisheries information.

Shellfish monitoring programme provides a relatively consistent, long-term dataset which is particularly sensitive to variations in the level of organic contaminations in the marine environment (Rainbow, 1995). Mills (1998) listed the features that make oysters and mussels particularly appealing as bio-monitors. They are inexpensive and easily obtained, they are easy to handle and processed; they are culturally, commercially and ecologically important; their biology is well understood; they are the most frequently used taxa in overseas shellfish monitoring programmes (“America-France Mussel Watch Programme”

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CHAPTER THREE

3.0 MATERIALS AND METHODS

3.1 Descriptions of the Study Area

Tarkwa Bay beach is the only intertidal rocky shores in Nigeria (Figure 1). The three moles of Tarkwa Bay Beach was constructed between 1908-1912 to protect the entrance of the Lagos harbour from excessive siltations from powerful along shore currents (West

- East) drifts (Ibe, 1987 and Nwankwo, 2004). The construction of the 3 moles of Tarkwa

Bay as noted earlier was meant to solve economic problems instead of proffer ecological problems (Nwankwo, 2004).

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Figure 1: Location Map of Tarkwa Bay showing West, Training , East moles, and the 12 sampling stations along the moles. Insert is the Map of Africa showing

Nigeria and the Location of Tarkwa Bay.

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3.1.1 WEST MOLE

It is located geographically on latitude N060 23‟ 54.5‟ and Longitude E 030 23‟ 39.5‟‟. It has an approximate area of 2.26km2 with shore height of approximately 8.20 metres and tidal range of 0.9 metre (Nwankwo and Iginla, 1997). It is an heterogeneous assemblage of rocks, which provides a multiple range of microhabitats that support a great variety of living forms. Human accessibility is limited because the adjacent coastal waters has been declared “ a high risk zone” as a result of intense wave actions and storm surge.

Human activities around the West mole include: swimming, sea surface sliding, fishing and SCUBA diving by tourists. The dominant vegetations at the West mole are

Rhizophora mangle; Avicennia germinans and Laguncularia racemosa are mangrove trees of economic importance. The West mole is currently under rehabilitation and reinforcement (Plate 1). The West mole has also been documented as a control station in this study as a result of minimal human depreciatory impacts.

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Plate 1: West mole.

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3.1.2 TRAINING MOLE.

The Training mole is located between latitude N06° 24‟ 25.5‟‟ and longitude E 03° 23‟

47.2‟‟. The mole bifurcates the East and the West moles. It has an approximate area of

1.74 kilometer square with shore height of about 3.83 metres and tidal height of 0.3 metre. The Training mole is the most stressed of the three moles because human accessibility, low shore height, low tidal range and recreational activities for tourist are prominent. Human activities around the training mole includes: unregulated dumping of untreated human wastes, coastal transportation, fishing, trampling, and swimming by coastal dwellers and diving. Presently, there is no mangrove vegetation along the shoreline of the Training mole to buffer the effect of erosion.

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Plate 2: Training mole

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3.1.3 EAST MOLE

The East artificial breakwater is located near the Victoria Beach (Lagos Bar Beach), with an approximate area of 4.2 kilometres with shore height of 8.5 metres as well as a tidal range of 0.76 metre. The East mole is geographically located on Latitude N06° 23‟ 49.6‟‟ and Longitude E 03° 23‟ 47.1‟‟. The steep gradient of the East mole is responsible for moderate human impact around the shoreline. However, the major anthropogenic activities observed around the East mole include: aggregate dredging, trans-shipment of cargoes in and out of the Lagos harbour and reconstruction activities (Plate 3).

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Plate 3: East mole

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3.2.0 Sampling Design

3.2.1 Site Selections:

Twelve geo-referenced sampling stations were established along the shorelines of the three moles of the study area (Table 1). The three moles were delineated into four sampling stations each, totalling 12 networks sampling stations (Table-1). Ecologically comparable sites (100 metres apart) were selected to avoid confounding results during statistical analyses (autocorrection). GPS, ground-trotting and boat surveying were used for the choice of sampling stations. The co-ordinates of the selected sampling stations were established using global positioning system (Garmin: Etrex 12 channel GPS).

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Table 1: GPS Location of Geo-referenced Sampling Stations and their Co-ordinates

at the three moles of Tarkwa Bay.

Mole SAMPLING STATION CO-ORDINATE STATION CODE North East Latitude Longitude

1 WM 1 060 23' 54.5" 0030 23' 39.5"

2 WM 2 060 23' 49.4" 0030 23' 42.6" WEST 3 WM 3 060 23' 45.9" 0030 23' 45.4"

4 WM 4 060 23' 40.2" 0030 23' 51.3"

5 TM 1 060 24' 25.5" 0030 23' 47.2"

6 TM 2 060 24' 21.3" 0030 23' 49.1" TRAINING 7 TM 3 06024' 17.8" 0030 23' 51.3"

8 TM 4 060 24' 13.7" 0030 23' 51.4"

9 EM 1 060 23' 49.6" 0030 24' 14.2"

10 EM 2 060 23' 56.4" 0030 24' 12.9" EAST 11 EM 3 060 24' 07.8" 0030 24' 11.0"

12 EM 4 060 24'10.5" 0030 24' 6.1"

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Table 2: Ecological features of the sampling stations at the three moles of Tarkwa Bay.

MOLE STATION ECOLOGICAL PLATES FEATURES CODE

WM1 Wave exposure scale of 4, surface roughness, low shore WEST angle, large boulders and pebbles.Presence of tide pool.

Plate 4: WM1

WM2 High aspect ratio, high surface roughness, low human impacts, exposure rating of 3.

Plate 5: WM2

WM3 Topographical heterogeneity, exposure rating of 5 sheltered shore with the 3 tidal elevations present.

Plate 6:WM3

WM4 Exposure scale of 2, low aspect ratio, sand scoured site and presence of 3 tidal zones.

Plate 7: WM4

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Table 2 : Continued.

MOLE STATION ECOLOGICAL PLATES FEATURES CODE

TM1 Topographical heterogeneity, microhabitats and tidal pool TRAINING present. Presence of 3 tidal elevations. Exposure scale of 5.

Plate 8: TM1

TM2 High human interference, low shore, surface roughness, low shore angle and exposure scale of 4.

Plate 9: TM2

TM3 Heterogeneous rock, low shore angle, low degree of

sand/siltinterference. Exposure scale of 3.

Plate 10: TM3

TM4 Low shore gradient, high human interference, presence of microhabitats and low shore angle exposure scale of 4.

Plate 11: TM4

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Table 2: Continued. MOLE STATION ECOLOGICAL PLATES CODE FEATURES EM1 Low shore angle, surface roughness wave exposed, exposure scale of 4. EAST

Plate 12 :EM1 EM2 Topographically heterogeneous, exposure scale of 4. Presence of 3 tidal elevations.

Plate 13:EM2 EM3 Exposure scale of 4, presence of microhabitats. Low shore angle, low human interference

Plate 14 :EM3 EM4 Exposure scale of 2, microhabitats present, low human usage and topographically heterogeneous.

Plate 15 :EM4

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3.2.2 Sample collections:

Water samples for physico-chemical parameters analyses, algae and molluscs were collected monthly for twenty four months (April 2008-March 2010) at the three moles of

Tarkwa Bay. Sample collections were made monthly before noon.

3.2.3 Collection of seawater:

Duplicate water samples for hydro-chemical analysis were collected using a 2.01 non- metallic Hydrobios water sampler, and about 0.5 metres below the water surface, from the boat (75hp Yahama outboard engine length: 7.4m; width: 1.8m Draught: 0.35m) anchored

6m from the shoreline at all sampling stations (Chukwu and Nwankwo, 2004). Water samples were kept in pre-washed and pre-labelled polyethylene bottles for further analyses.

3.2.4 Collection of algal samples:

Algal samples were collected from each sampling station with a scraper from the rock surface facing seaward direction; it was later washed in sea seawater three times, kept in pre-labelled polyethylene bags, later transported to the laboratory for storage in a deep freezer at temperature of 40 C, for further analyses.

3.2.5 Collection of molluscan samples:

Molluscan species were collected at low tide both intertidally and sub-tidally using quadrats (1 metre square). Molluscan samples were collected by an experienced diver using a fixed 1 metre square sub-tidal quadrats along line transects from a fixed point on landward to seaward directions. A quadrat of 1 metre square was used to standardize the sample size (Edokpayi et al, 2010). Molluscs found within the quadrats were sorted,

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counted and identified into taxonomic groups using identification keys of (Edmunds

1978; Oyenekan 1988; Rose 2003).

3.2.6 Choice of study species

Molluscan species selected for further studies were dominant species with culturally, economically and ecologically potentials and available on the shore through the seasons;

Thais callifera, Patella safiana, Nerita senegalensis, Buccinum undatum, and the selected samples were of shell length greater than 5mm (Plate 16 A - D).

A B D C

Plate 16: Study species (A= Thais callifera, B= Patella safiana, C= Nerita senegalensis and D = Buccinum undatum.

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3.2.7 Sample preservation:

Seawater was filtered using a Millipore filtering system (MFS) and stored in 10% formalin solution analytical grade. Algal sample were washed three times in seawater, and later fixed in 4% formalin solution. Molluscan samples were preserved in 4% formalin and stained with Rose Bengal (2g/L) to facilitate sorting in laboratory (APHA

1998; Chukwu and Nwankwo 2004; Nkwoji et al., 2010).

3. 3 SAMPLES ANALYSES

3.3.1 Physico-chemical Analyses:

3.3.2 Air and Water Temperatures:

Temperature was determined in-situ using conventional mercury-in-glass thermometers

(00- 1000C) graduated in 0C.

3.3.3 Rock temperature:

Rock temperature was measured monthly with a multiplex thermocouple/data logger

(Models AM416 and 23X, Campbell Scientific Inc; Logan, Utah, USA).

3.3.4 Salinity

Salinity was determined in-situ in the field using a digital meter (Horiba U-10).

3.3.5 Dissolved Oxygen (DO):

Dissolved Oxygen was assessed in the field using a digital meter (Horiba U-10), cross- checked in the laboratory using standard Winkler‟s procedures (APHA, 1998). Winkler solutions A and B were used to fixed seawater samples collected from the study sites. In the laboratory, the aliquot solution was titrated with sodium thiosulphate solution

(analytical grade). The volume of sodium thiosulphate solution used in the titration is equal the volume of the Dissolved Oxygen in seawater.

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3.3.6 Rainfall Data: was collected from the Federal Department of Meteorological

Services Oshodi, Lagos.

3.4 Laboratory Studies

3.4.1 Nutrient Analyses:

The nutrients contents in the seawater samples were analysed in the laboratory using standard methods described by (APHA, 1998). Phosphate-phosphorus (PO4-P), Nitrate-

-2 Nitrogen (NO3-N) and sulphate (SO4 ), (mg/L) were determined using colorimetric analytical methods.

3.4.2 Heavy Metal Analyses:

The seaweeds collected from the field were oven-dried at 600C for 48 hours, and later pulverized into powder form. 10ml of powder was used for minerals acid digestions and later the digested, and the acidified algal solution was subjected to Atomic Absorption

Spectrophotometer (AAS).

Molluscan samples (25 nos) were deshelled, oven-dried at 600C, for 48 hours, powdered and digested in 4ml of HNO3 (50%) in closed polystyrene crystal tubes in a drying oven at 600C for 48hours. Following acid digestion, all samples were analysed for Cd, Cu, Pb,

Zn, Fe, and Hg using the Atomic Absorption Spectrophotometer (AAS), according to standard procedures (APHA, 1998).

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3.5 STUDIES ON THE BIOLOGY OF INTERTIDAL MOLLUSCS

3.5.1 Feeding rates of Patella safiana and Nerita senegalensis on Algae.

The experiment on feeding was aimed at investigating the consumption rates of intertidal species of herbivorous molluscs under experimental conditions. Equal numbers of adult

(50) and juveniles (50) of test molluscs (Nerita senegalensis, and Patella safiana), were collected at low tide, brought to the laboratory for acclimation for 7 days, and measured with vernier callipers. Rock samples approximate (20cm x 12cm x 4cm) dimension and the seawater were collected from the Training artificial breakwaters (TM3) at low tide and later transported to the laboratory, maintained at air temperature of 28°C for acclimation. The algae used in these experiments were intertidal algae Enteromorpha tubulosa, Cladophora pilulifera and, Ulva lactuca.

3.5.2 Foraging Behaviours of selected intertidal molluscs

Two gently sloping (~ 15°) study stations, about 20 metres apart, were selected at

West mole between 1.2 to 2.3 metres chart datum (CD), which includes the most abundant zone of Patella safiana (~ 1.20 to 1.60 metres above CD). Station A, at the

West mole is about 8.2 metre wide and surrounded by crevices, and large boulder (~ 2 x

1.3 x 1 metre length, width and height), located in the middle shore. Station B is 5 metres also located at West mole surrounded by crevices (~40 cm wide). The crevices and boulders were covered with layer of algae (Ulva lactuca and Enteromorpha tubulosa) during the dry season). The investigations were conducted for 6 hours at low tide and repeated six times during the dry season (Underwood, 2000).

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3.5.3 Gut Content Analysis:

Ten snails of different sizes range (12-22) mm, unspecified ages, were collected monthly from sample pool (April, 2008-March, 2010). They were dissected to remove the digestive contents into a Petri dish. The diluted gut content was pipetted out to identify algal contents into taxonomic groups using light microscope.

3.5.4 Comparative studies on growth of molluscan species at three different tidal zones.

Growth of molluscs under both natural and artificial environments (laboratory) were investigated on the West artificial breakwaters (sampling station-3), at the 3 intertidal zones (low, mid, and high respectively), (-0.2m, +1.6m, +2.2m below/ above seawater level) and laboratory at the Marine science department. Cages used in the experiments were made of metal nettings of 0.5 x 0.5 cm mesh size and were ≈23 x 23 cm, and they enclosed an area of ≈ 500cm2, and were 5cm high. The cages were fastened to the rock by metal screws. All the cages were checked every week when the dead animals were replaced and damage cages repaired.

Three inerts metals cages were fixed firmly to each tidal elevation (low, mid and high shore levels). The species of interest (100Nos of Patella safiana was selected from sample pool, shell length (mm) were measured with vernier calliper (Model: ESAL) monthly for growth measurement for two seasons of rainy and dry (April, 2008 – March,

2010).

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3.5.5 Determination of wet, dry biomass and Ash-free dry weight (AFDW).

Ash-free dry weights (AFDW) were determined for individual molluscs by drying them for 48 hours to constant weight at 650C in a dry oven, and then combusted for 12 hours at

5000C (Underwood, 2000). The dry weights and ash weight of individual molluscs were weighed to nearest 0.01mg using Mettler Micro-balance (Mettler model X1705). The ash- free dry weight (AFDW) was then calculated by subtracting the ash content from the dry weight (Underwood, 2000).

3.5.6 Effects of interspecific competition on molluscs’ growth rate in the

Laboratory.

The experiments were carried out to determine the different growth rates on tidal elevation on selected molluscan species. The experimental molluscs‟ samples were replicated in the laboratory to determine the growth and the effects of interspecific competition on growth rate in artificial environment. Two glass tanks, each with enclosed rock substrates covered with carpets of algal species and sea water which partially submerged the experimental molluscs. Seawater was changed every 48 hours. Ten cohorts of Nerita senegalensis were introduced as treatments into Patella safiana tank to determine the effects of interspecific competition in a controlled environment. The main purpose of these experimental set-ups was to verify the effect of interspecific competition and tidal elevation on the growth rates of Patella safiana.

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3.5.7 Studies on shell dimensions of the selected molluscan fauna.

A total of 204 specimens of matured (Buccinum undatum: 70; Nerita senegalensis: 75 and Thais callifera: 69) were selected randomly from the sample pool from the study area. Samples were first preserved in 10% formalin in seawater, and kept prior to laboratory analysis.The fundamental variables of the shell were measured using a vernier calliper (Model: Esal) to ± 0.01mm accuracy. The measurements included shell length

(SL), shell Height (SH), Shell Width (SW), Aperture Length (AL) and Body whorl (BW)

(Figures 3, 4 and 5) (Grahame and Mill, 1992).The shell, animal and gonadal tissues of

Buccinum undatum were then blotted dried with tissue paper and weighed (wet-weight) to the nearest ± 0.01gm on analytical balance (Mettler model X1705). Sample was oven dried at 600C to a constant weight, and then re-weighed. The sample was further combusted in a muffle furnace at 4500C for 8hrs, and then re-weighed to obtain the ash- free dry-weight (AFDW).The ash-free dry weight (AFDW) was then calculated by subtracting the ash content from the dry weight.

All variables were logarithmically transformed. The relationships of shell length (SL), shell height (SH) to ash-free dry weight were each independently evaluated using regression analysis for Buccinum undatum, Thais callifera, Nerita senegalensis.

3.5.8 Studies on the Reproductive Biology:

Patella safiana, Nerita senegalensis are species of commercial values were investigated using Gonad Somatic Index, (GSI) reproductive effort, and histological techniques.

Mollusc samples length (≈15mm-22mm) were collected from monthly sample pool, and the experimental molluscs were measured with vernier callipers, gonads were separated from somatic tissues and weighed with top loaden electronic balance (Sartorius: model

106MX34600), the gonads were fixed in Bouin's fluid for 48 hours before histological

51

analyses. Ten male and ten female gonads from each monthly sample pool were dehydrated in an alcohol series and embedded in paraffin wax. Longitudinal section was cut through the gonads at 7µm thickness using a Becker rotatory microtome and slides stained with Ehrlich‟s haematoxylin, with eosin as a counterstain (Fletcher, 1987).

Molluscan species for histological studies were stored in 10% formalin solution

(analytical grade). Macroscopic sexing of the experimental molluscs was possible as the mature testis is milky-white in colour while mature ovaries are orange.

3.5.8.1 Assessment of Gonadosomatic Index (GSI)

Gonadosomatic index was used to describe annual cycle of gonadal development. The ratios of gonad weight to total body weight were determined monthly, and mean values were computed.

The gonadosomatic index: was calculated using the formula below:

G.S.I = G.W/T.W (Fletcher, 1987)

Where G.W =Wet weight of the gonad in (g)

T.W = Wet weight of the total body tissues in (g).

The GSI of each sex for each month was analyzed by a two factor (sex and month) analysis of variance and the means tested by an S.N.K test.

52

3.5.8.2 Reproductive Effort (RE)

In this study, the formula adopted for calculating reproductive effort (RE) was:

(R.E) = G.W / S.W (This formula was adopted following (Fletcher, 1987; Dunmore and

Schiel, 2000).

Where G.W = Wet weight of the gonad; and S.W = Wet weight of the somatic tissues

3.5.8.3 Histology of the Gonads of Selected Molluscan Species.

Limpet species (Patella safiana) of size range (19 - 24) mm in shell length and Nerita senegalensis (15-18) mm were randomly selected monthly from the sample pool.

According to (Frank 1982; Murray et al., 2006), limpets at this size are reproductively matured. Four male and female gonads from each monthly sample pool were dehydrated in an alcohol series (70%, 90% and absolute alcohol, analytical grades) and embedded in paraffin wax. Longitudinal sections were cut through the gonads at 7µm thickness using a

Beck rotatory microtome and slides were stained with Ehrlich‟s haematoxylin using eosin as counter stain (Creese, 1980).

Five sections per limpet from the middle of the gonad were examined using a microscope.

The composition of each gonad was recorded at 15 random intervals per section. The females were classified as having mature (post-vitellogenic) or immatured (pre- vitelligenic and maturing) oocytes present while the male were classified as having spermatogonia, spermatocytes or spermatids and spermatozoa present, after the method of

(Creese and Ballantine 1983; .Dunmore and Schiel, 2000). The gonads of the sectioned specimens were sexed

53

3.5.8.4 Sex ratios

All molluscs that were collected from monthly sample pooled were examined macroscopically to determine sex. This was possible through colour variance as the mature testis is milky-white in colour while mature ovaries are orange (Fletcher, 1987).

3.5.8.5 Size at first sexual maturity

The size of first sexual maturity was also estimated from the data collected from the monthly sample pooled. The percentage of individual‟s molluscs with mature gonads in 5 mm size classes was recorded. The size at which the gonad of 50% of molluscs in a given size class contained either spermatozoa or vitellogenic eggs was as index of first maturity

(Fletcher, 1987).

54

3.6.0. Statistical Analysis

All statistical computations were done using PAST (version 2.17). Analysis of Variance

(ANOVA) was used to test differences among sampled stations and comparison of means by Duncan Multiple Range Test was used for significant differences in results obtained for each parameter in all stations at 5% level of significance. One way analysis of variance (ANOVA) and Student Newman-Keuls (SNK) test was used to test for statistical differences (5% level) in heavy metal concentrations in different molluscs‟ body parts

(ANOVA), and between seasons (T-test). Pearson correlation test ( r ) was performed on molluscan shell dimensions to determine the degree of association between paired shell variables. Differences in growth rate among molluscs on three tidal zones on the shore were tested with analysis of variance (ANOVA) and Student Newman-Keuls (SNK) test was used to test for statistical difference (5 % level) in the mean growth rate across the three tidal heights (low, mid and high).

3.6 1. Molluscan Community Data Analysis

Comparative studies of species diversity indices in intertidal molluscan community were computed using Shannon Index of Dominance and Index of Evenness or Equitability in

PAST software version (2.17).

(i) Shannon Index of General Diversity is defined by

Where ni is the importance value for each species

(Number of individuals or biomass). The number of Taxa sampled is S and \N

is ith sum of the important values for a given sample stations.

55

(ii) Index of Dominance is

C=Index of dominance is

Where ni = number of individuals of ith species

N= the total number of individuals for all species (Ogbeibu, 2005).

In contrast, the index of dominance showed the highest values in areas of lowest species diversity indices. This strongly shows l an inverse relationship between the index of

Dominance and the species diversity index.

(iii ) Community Evenness:

The homogeneity of the molluscan communities was computed using Pielou Evenness

1 Index (J ). , Where Hmax is the maximum possible diversity which would be achieved if all species were equally abundant (Pielou 1966; Clark and Warwick,

1994).

56

CHAPTER FOUR

4.0 RESULTS

4.1.0 Physico-chemical characteristics of water samples of Tarkwa Bay.

The results of the physico-chemical parameters of the three moles of Tarkwa Bay are shown in (Tables: 3 and 4). Also indicated are means ± standard deviation values and the maximum and minimum values for each parameter in parentheses. Analysis of variance

(ANOVA) is included to detect a significant difference among the three moles. Based on statistical analysis, there were significant differences between physico-chemical parameters of seawaters in both rainy and dry seasons (t05, 18 =2.10; P < 0.05). Spatially,

ANOVA testing indicated that all the physico-chemical parameters of the three moles are slightly indistinguishable (Mean ± 2; P = 0.05), and this validates the findings of the previous studies (Oyewo et al, 1982 and Edokpayi, et al, 2010).

4.1.1 Temperature

Air, seawater and rock temperatures showed similar seasonal patterns at the three moles of Tarkwa Bay (Tables: 3, 4 and 5, Figures: 2, 3 and 4, Appendices: 1, 2 and 3). During the rainy season, the air, seawater and rock temperatures were recorded between July and

August as following: air (31.8oC); water (29.3oC) and rock (35oC) at the Training mole.

Again, during the dry season months, higher values were recorded for air, seawater and rock temperatures as detailed in (Table 3, Figures: 2 and 3; Appendix: 1).

The West and East moles were found to have maximum temperature of 31oC and the

Training mole 35oC in the dry months of October to December. The minimum values were recorded between October and November for air, seawater and rock temperatures at

57

(28oC, 26oC and 30oC) at the West mole. During the study period, the West mole, water temperature showed positive correlations with air (0.827); rock temperature (0.688) having low correlation with DO (0.315), COD (0.155), salinity (0.247), pH (0.180), sulphate (0.290), Nitrate (0.010) and negatively correlated with conductivity (-0.296); phosphate (-0.056) and BOD (-0.244) (Table 5).

At the Training mole (Table 6) water temperature was positively correlated with Air temperature (0.623); rock temperature (0.295), sulphate (0.682) and lowly correlated with rock temperature (0.295), pH (0.029), salinity (0.021), COD (0.074), DO (0.142) and rainfall (0.262) while negatively correlated with phosphate (-0.015), nitrate (-0.197) and

BOD (-0.025).

At the East mole (Table 7), seawater temperature showed similar patterns. It has positive correlations with air temperature (0.825); rock temperature (0.345) but poorly correlated with salinity (0.034), sulphate (0.251); BOD (0.110), phosphate (0.109) while also negatively correlated with pH (0.112), conductivity (-0.196), nitrate (-0.077), DO (-0.071) and rainfall (0.039).

58

Table 3: Temporal variations in physico-chemical parameters investigated in the dry season at the 3 moles of Tarkwa Bay

WESTMOLE TRAINING MOLE EAST MOLE ANOVA

PARAMETERS MEAN±S.D MIN MAX MEAN±S.D MIN MAX MEAN±S.D MIN MAX P- VALUE

AIR TEMP. (°C) 29.9 ± 0.91 28.00 31.00 30.1 ± 0.45 29.30 30.50 30.3 ± 0.55 29.50 31.00 > 0.05

WATER TEMP.(°C) 27.8 ± 0.93 28.00 31.00 27.6 ± 0.87 25.80 28.30 27.9 ± 0.51 27.30 28.50 > 0.05

ROCK TEMP. (°C) 33.6 ± 1.91 30.00 35.30 34.20 ±0.60 32.80 35.00 33.9 ± 0.99 32.30 35.00 > 0.05

CONDUCTIVITY (μS/cm) 31.0 ± 6.34 26.41 44.10 27.5 ± 1.02 25.80 29.50 27.6 ± 2.08 26.10 33.70 > 0.05

SALINITY (‰) 30.4 ± 2.57 26.13 33.10 30.5 ± 3.03 25.80 33.80 29.7 ± 2.69 25.18 32.50 > 0.05 pH 7.7 ± 0.50 7.12 8.50 7.6 ± 0.38 7.18 8.10 7.61 ± 0.39 7.18 8.08 > 0.05

SULPHATE (mg/L) 24.6 ± 3.08 19.30 27.80 23.4 ± 2.27 20.10 26.70 22.8 ± 2.23 19.80 26.20 > 0.05

PHOSPHATE (mg/L) 1.9 ± 0.32 1.40 2.40 1.8 ± 0.38 1.22 2.30 2.3 ± 0.33 1.47 2.61 > 0.05

NITRATE (mg/L) 6.2 ± 1.85 5.00 11.70 6.2 ± 0.79 5.24 8.03 7.6 ± 1.16 5.80 10.50 > 0.05

COD (mg/L) 10.8 ± 4.73 8.00 25.50 10.8 ± 3.71 7.80 21.80 10.7 ± 5.08 6.80 25.80 > 0.05

DO (mg/L) 5.2 ± 0.55 4.30 6.00 5.6 ± 0.65 4.40 6.30 5.2 ± 0.47 4.50 5.80 > 0.05

BOD5 (mg/L) 9.5 ± 5.09 2.00 19.00 6.8 ± 3.07 3.00 13.00 6.8 ± 2.08 3.00 10.00 < 0.05

±S.D =Standard Deviation; Min = Minimum; Max = Maximum; the results of analysis of variance (ANOVA) computed and P-value indicated

59

Table 4: Temporal variations in physico-chemical parameters investigated during the rainy season at the 3 moles of Tarkwa Bay.

WEST MOLE TRAINING MOLE EAST MOLE ANOVA

PARAMETERS MEAN±S.D MIN MAX MEAN±S.D MIN MAX MEAN±S.D MIN MAX P - VALUE

AIR TEMP. (°C) 29.9 ± 0.87 28.50 31.50 29.9 ± 0.79 28.00 31.80 30.3 ± 0.68 28.80 31.30 > 0.05

WATER TEMP.(°C) 28 ± 0.78 26.80 29.0 27.8 ± 0.93 25.80 29.30 28.3 ± 0.76 26.50 29.50 > 0.05

ROCK TEMP. (°C) 32.3 ± 1.59 29.00 34.50 33.3 ± 1.56 30.30 35.30 32.6 ± 1.81 30.00 35.50 > 0.05

CONDUCTIVITY (μS/cm) 29.3 ± 5.29 22.80 38.70 26.3 ± 2.40 19.70 30.00 26.1 ± 3.74 20.75 32.90 < 0.05

SALINITY (‰) 27.5 ± 3.54 22.00 33.30 29.1 ± 3.47 21.90 33.80 28.0 ± 2.73 24.20 32.40 > 0.05 pH 7.6 ± 0.39 7.06 8.38 7.62 ± 0.34 7.14 8.10 7.4 ± 0.26 7.10 7.90 > 0.05

SULPHATE (mg/L) 24.3 ± 3.42 17.10 28.40 23.4 ± 3.11 17.00 27.30 23.9 ± 3.11 17.90 27.06 > 0.05

PHOSPHATE (mg/L) 2.1 ± 0.62 0.86 3.25 2.2 ± 0.64 1.12 3.48 2.52 ± 0.70 1.56 4.32 > 0.05

NITRATE (mg/L) 7.7 ± 2.83 4.05 12.90 6.7 ± 1.64 4.46 10.00 8.6 ± 2.13 5.15 11.80 < 0.05

COD (mg/L) 11.4 ± 3.84 7.50 20.30 21.8 ± 4.57 7.50 21.80 12.0 ± 3.93 7.50 20.50 < 0.05

DO (mg/L) 5.9 ± 1.00 4.30 7.40 5.6± 0.62 4.40 6.40 6.05 ± 1.03 4.30 7.50 > 0.05

BOD5 (mg/L) 5.2 ± 2.79 1.00 9.00 6.3 ± 2.85 2.00 13.00 5.17 ± 2.25 2.00 9.00 > 0.05 S.D= Standard Deviation, MIN = Minimum and Max= Maximum, the results of analysis of variance (ANOVA) computed and P-value indicated.

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Table 5: Correlation between different physico-chemical parameters of the study stations at the West mole of Tarkwa Bay (April, 2008-

March, 2010)

PARAMETER

WATER WATER TEMP TEMP AIR TEMP ROCK pH SALINITY CONDUCTI VITY SULPHATE PHOSPHAT E NITRATE COD DO BOD RAINFALL WATER TEMP. (OC) 1 AIR TEMP. (OC) 0.827* 1 ROCK TEMP. (OC) 0.688* 0.716* 1 pH 0.180 0.047 0.028 1 SALINITY (‰) 0.242 0.457 0.384 -0.436 1 CONDUCTIVITY (µS/cm) -0.296 -0.199 0.023 0.252 -0.293 1 SULPHATE (Mg/L) 0.290 0.434 0.174 -0.418 0.732* -0.646 1 PHOSPHATE (Mg/L) -0.056 -0.103 -0.184 0.424 -0.181 -0.211 -0.014 1 NITRATE (Mg/L) 0.010 0.152 -0.320 -0.017 0.033 0.227 -0.073 -0.277 1 COD (Mg/L) 0.155 0.127 -0.135 -0.051 0.186 0.234 0.001 -0.336 0.742* 1 DO (Mg/L) 0.315 0.126 -0.194 -0.156 0.135 -0.763 0.470 0.330 -0.067 0.025 1 BOD (Mg/L) -0.244 -0.048 0.130 -0.386 0.441 -0.475 0.484 0.081 -0.553 -0.459 0.142 1 RAINFALL(mm) 0.055 -0.093 0.313 0.065 -0.238 -0.122 0.043 0.110 0.344 0.356 0.382 -0.367 1 *Significant correlation (r2<0.5)

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Table 6: Correlation between different physico-chemical parameters of the study stations at the Training mole Tarkwa Bay (April, 2008-March, 2010).

TI Y

E

PARAMETERS

WATER WATER TEMP AIR TEMP ROCK TEMP pH VITY PHOSPH ATE COD DO BOD SALINIT CONDUC NITRAT SULPHATE RAINFALL WATER TEMP. (OC) 1 AIR TEMP. (OC) 0.623* 1 ROCK TEMP. (OC) 0.295 0.587* 1 pH 0.029 -0.246 -0.262 1 SALINITY (‰) 0.212 0.632 0.554* -0.809 1 CONDUCTIVITY (µS/cm) 0.087 0.438 0.139 -0.131 0.433 1 SULPHATE (Mg/L) 0.685* 0.632 0.509* -0.369 0.520* 0.169 1 PHOSPHATE (Mg/L) -0.015 -0.361 -0.438 0.406 -0.746 -0.513 -0.142 1 NITRATE (Mg/L) -0.197 -0.396 -0.804 0.237 -0.363 0.192 -0.345 0.252 1 COD (Mg/L) 0.074 0.028 -0.407 -0.098 0.198 0.579* 0.055 -0.360 0.581* 1 DO (Mg/L) 0.142 0.199 0.069 -0.459 0.276 0.118 0.467 0.173 -0.001 0.066 1 BOD (Mg/L) -0.025 0.201 0.377 -0.525 0.383 -0.061 0.403 0.045 -0.425 -0.412 0.606 1 RAINFALL(mm) 0.262 -0.146 -0.444 0.022 -0.223 -0.104 0.103 0.324 0.263 0.372 0.166 -0.185 1 *Significant correlation (r2>0.5)

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Table 7: Correlation between different Physico-Chemical parameters of the study stations at the East mole, Tarkwa Bay (April, 2008- March, 2010).

PARAMETERS

pH COD DO BOD WATER TEMP TEMP AIR TEMPROCK SALINITY CONDUCTI VITY SULPHATE PHOSPHAT E NITRATE RAINFALL WATER TEMP. (OC) 1 AIR TEMP. (OC) 0.825* 1 ROCK TEMP. (OC) 0.345 0.439 1 pH -0.112 -0.293 -0.195 1 SALINITY (‰) 0.034 0.362 0.661 -0.492 1 CONDUCTIVITY (µS/cm) -0.196 -0.047 -0.081 0.011 0.488 1 SULPHATE (Mg/L) 0.251 0.224 0.415 -0.195 0.435 0.088 1 PHOSPHATE (Mg/L) 0.109 0.107 -0.177 0.068 -0.392 -0.407 0.260 1 NITRATE (Mg/L) -0.077 -0.118 -0.694 -0.123 -0.167 0.476 -0.394 -0.264 1 COD (Mg/L) -0.133 -0.087 -0.234 -0.097 0.374 0.675 0.132 -0.433 0.614 1 DO (Mg/L) -0.071 -0.215 0.063 -0.266 0.167 -0.004 0.511* 0.141 -0.087 0.270 1 BOD (Mg/L). 0.110 0.233 0.583* 0.013 0.231 -0.348 0.330 0.342 -0.694 -0.497 0.186 1 RAINFALL (mm). -0.039 -0.197 -0.374 -0.254 -0.174 0.014 0.260 -0.051 0.321 0.307 0.411 -0.290 1 *Significant correlation (r2>0.5)

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Figure 2: Temporal variation in air temperature at the 3 moles of Tarkwa Bay (April,

2008- March, 2010).

64

Figure 3: Temporal variations in water temperature at the 3 moles of Tarkwa Bay

(April, 2008- March, 2010).

65

Figure 4: Temporal variations in rock temperature at the 3 moles of Tarkwa Bay

(April, 2008- March, 2010).

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4.1.2 Salinity and rainfall patterns in Tarkwa Bay coast.

The salinity of the 3 moles of the Tarkwa Bay showed a progressive increase from the West to East mole (Figure: 6). The highest readings were recorded at the Training mole (33.8‰) during the dry season. A distinct seasonal pattern was however, recorded in salinity at the

West, Training and the East moles (Tables 3 and 4). The minimum value was recorded at the

East mole (25.18 ‰). The salinity amplitude fluctuated between mean values of 29.7 ±

2.69‰ at the East mole and 30.5 ± 3.03 ‰ at the Training mole during the study period in dry seasons. The salinity values were slighly lower (±3%) during the months of June to

September and high during the dry season months of November to February. During the period of study, in the West mole, salinity showed positive correlation with sulphate (0.732),

BOD5 (0.441) but poorly correlated with DO (0.135), COD (0.186), nitrate (0.033) while also negatively correlated with conductivity (-0.293), phosphate (-0.181), rainfall (-0.238) as shown in (Table 6). In the Training mole, salinity showed similar pattern of positive correlation with conductivity (0.433), sulphate (0.520), air temperature (0.632) and rock temperature (0.554); low correlation with COD (0.198), DO (0.276) and BOD5 (0.383); negatively correlated with phosphate (-0.746), and lowly correlated with nitrate (0.033) and rainfall (-0.223) (Table 7). Similarly in the East mole (Table 7), salinity had low, positive correlation with conductivity (0.488), sulphate (0.435), DO (0.167), BOD5 (0.231); negatively correlated with phosphate (-0.392), nitrate (-0.167), and rainfall (-0.174). The diurnal variations were found to be in phase with tidal cycles, increasing towards the West mole in tune with high tides as reported by (Edokpayi et al, 2010).

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Figure 5: Variation of the number of individuals with salinity and rainfall.

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Figure 6: Temporal variation in salinity at the 3 moles of Tarkwa Bay (April, 2008-

March, 2010).

4.1.3 Hydrogen ion concentrations (pH)

The pH of Tarkwa Bay coastal waters showed a narrow range of 7.06 – 8.50. The pH value did not show significant fluctuation during the present study (Figure 7). The lowest value was recorded in the West mole (7.06) during the rainy season (Table 5) and the highest value was recorded in the West mole (8.50) during the dry season (Table 3). The lowest mean value was obtained in the rainy season (7.40 ± 0.26) in the East mole (Table 4), while the highest mean value (7.70 ± 0.50) was recorded in the West mole during the rainy season. pH was poorly and positively correlated with other physico-chemical parameters (ANOVA; P < 0.05) studied during the period (April, 2008 - March, 2010) (Tables 5, 6 and 7).

69

Figure 7: Temporal variation in pH at the 3 moles of Tarkwa Bay (April, 2008- March,

2010).

4.1.4 Dissolved Oxygen (DO)

The values of Dissolved Oxygen at the three moles of Tarkwa Bay ranged between 4.3 mg/L

– 7.4 mg/L in the rainy season (Table 5). Conversely, in the dry season lower range value was recorded (4.30 mg/L – 6.30 mg/L) (Table 4). No specific discernible trend from West to East mole was observed. Minimum values were recorded during the dry season months while higher values were assessed in the rainy season months (Tables 3, 5 and Figure 8). Dissolved

Oxygen (DO) had a low correlation with water temperature (0.315), air temperature (0.126), salinity (0.135), sulphate (0.474), phosphate (0.330), COD (0.025) and negatively correlated with rock temperature (-0.194), pH (-0.156), conductivity (-0.763), nitrate (-0.07) in the West mole of Tarkwa Bay (Table 6). Similarly in the Training mole DO have a low correlation with water temperature (0.142), Air temperature (0.199) and rock temperature (0.069), salinity (0.276), conductivity (0.118) sulphate (0.467), nitrate (-0.001) (Table 7). Similar 70

patterns were observed at the East mole. Dissolved oxygen was positively correlated with sulphate (0.511), phosphate 0.141), COD (0.270) and rock temperature (0.063) but negatively correlated with water temperature (-0.0710, Air temperature (-0.215), pH (-0.266), conductivity (-0.004) and nitrate (-0.087) (Table 8). There were marked variations in dissolved oxygen (DO) among the different sampling months (ANOVA; P < 0. 05). Analysis of variance result indicated that dissolved values among the three moles were not significant

(P > 0.05). (Figure:8).

Figure 8: Temporal variations in Dissolved Oxygen (DO) at the 3 moles of Tarkwa Bay

(April, 2008- March, 2010).

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4.1.5 Biochemical Oxygen Demand (BOD5)

The values of BOD5 ranged from 1.0 mg/L – 19.0 mg/L in dry season (Tables 4 and 5) throughout the study period. The lowest BOD5 value (1.0 mg/L) was recorded in the rainy season at the West mole and the highest value (19.0mg/L) was recorded at the West mole during the dry season. A temporal pattern of change in BOD5 values was observed at the 3 moles of Tarkwa Bay. In general, mean values were low during the rainy seasons compared to the dry season (Tables 3, 4 and Figure 9). The values were observed to follow temporal patterns during the study period. At the West mole, BOD5 was positively correlated with the salinity (0.441), sulphate (0.484), DO (0.142) and negatively correlated with water temperature, air temperature (-0.048), pH (-0.386), conductivity (-0.475), nitrate (-0.553) and

COD (-0.459) (Table 5).

BOD5 recorded at the Training mole was positively correlated with air temperature (0.201), rock temperature (0.377), salinity (0.383) and DO (0.606) but negatively correlated with pH

(-0.525), conductivity (-0.061), nitrate (-0.425) and COD (-0.412) (Table 6). The BOD5 at the

East mole (Table 7), showed low correlation with seawater temperature (0.110), air temperature (0.233), rock temperature (0.583), salinity (0.231), sulphate (0.330), phosphate

(0.342) and DO (0.186) but negatively correlated with conductivity (-0.348), nitrate (-0.694) and COD (-0.497).

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Figure 9: Temporal variation in Biochemical Oxygen Demand (BOD5) at the 3 moles of Tarkwa Bay (April, 2008- March, 2010).

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4.1.6 Chemical Oxygen Demand (COD) mg/L

Chemical Oxygen Demand (COD) is the amount of oxygen required to achieve a complete oxidation of 1 gramme of chemical wastes (sewage, pesticide, household detergent and fertilizer) in any receiving aquatic environment (Ademoroti, 1998). In the Tarkwa Bay coastal waters, the level of COD varies with seasons. The East mole has maximum and minimum values of 20.5 and 7.5 mg/L respectively. A mean value of (12.0±3.9) mg/L was observed during the rainy season. Similar trends were also observed in Training mole which has a range of 7.5mg/L – 21.8mg/L and a mean value of 21.8±4.57mg/L in rainy season.

In the dry season, the West mole has COD with annual mean value of 10.8± 4.73 mg/L with range between 8mg/L – 25.5 mg/L. Conversely, the East mole has annual mean values of

10.7±5.08 mg/L with a minimum value of 6.8mg/L and a maximum of 25.8mg/L while the

Training mole has annual mean value of 10.8± 3.71mg/L with corresponding minimum and maximum values of 7.8mg/L and 21.8mg/L respectively. The COD values fluctuate within a narrow range in both rainy and dry seasons (Tables 3 and 4; Figure: 10).

In the West mole, COD was positively correlated with nitrate (0.742) ; weakly correlated with water temperature (0.155), air temperature (0.127), salinity (0.186), conductivity

(0.234), sulphate (0.001) and was negatively correlated with rock temperature (-0.135), pH(-

0.051) and phosphate(-0.336) (Table 5)

Similar patterns were observed in the Training mole where COD had average correlations with conductivity (0.579) and Nitrate (0.581). It was poorly correlated with Water temperature (0.074), air temperature (0.028), salinity (0.198) and sulphate (0.055). The COD further had negative correlation with rock temperature (-0.407), pH (-0.098), phosphate (-

0.360) (Table 6).

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The East mole exhibited similar trend with COD, having positive correlations with conductivity (0.675) and nitrate (0.614). But it was observed to be poorly correlated with salinity (0.374) and sulphate (0.132), and negatively correlated with water temperature (-

0.133), air temperature (-0.087), rock temperature (-0.234), pH (-0.097) and phosphate (-

0.433) (Table 7 and figure 10).

Figure 10: Temporal variation in Chemical Oxygen Demand (COD) at the 3 moles of

Tarkwa Bay (April, 2008- March, 2010

75

4.1.7 Conductivity (µS/cm)

The effect of conductivity varies with seasons (Ademoroti, 1998). The level of concentration depends on rainfall, river inflow, evaporation, and the salt contents of the aquatic ecosystem.

The maximum value of (44.1µS/cm) was found in the West during the dry season months with annual mean value of 31.0 ± 6.34. The lowest mean value was recorded in rainy season

(29.3 ± 5.29) and the range (19.7 – 38.7) µS/cm in rainy season (Tables 4, 5 and figure 11).

Figure 11: Temporal variations in Conductivity (μS/cm) at the 3 moles of Tarkwa Bay

(April, 2008- March, 2010)

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4.3.0 Nutrients

4.3.1 Nitrate – Nitrogen (NO3-N)

The spatial distribution of nitrate during the study period varied temporally among the 3 moles of Tarkwa Bay. The nitrate levels showed higher concentrations towards the rainy seasons with a maximum value of 12.9mg/L in the West mole (Table 4 and figure 14). A minimum value of 4.05mg/L was also recorded in the rainy season in the West mole (Table

5). Throughout the study period, the highest mean value (7.71 ± 2.83 mg/L) was recorded in the West mole. The interactions of dissolved nitrate at the 3 moles were observed to have negative correlations with other physico-chemical parameters recorded in the moles

(ANOVA; P>0.05) except water, air temperature, salinity and conductivity (ANOVA; P<

0.05) (Table 5). Nitrate was negatively correlated with other physio-chemical parameters studied in the East mole except conductivity (Table 7). The nitrate value was negatively correlated with other physico-chemical parameters assessed at the Training mole during the study period except with pH, conductivity and phosphate (Table 6). During the study period particularly in the dry season, the entire regions were characterized by low nitrate concentrations at the three artificial breakwaters of Tarkwa Bay (Figure 14).

4.3.2 Phosphorus –phosphate (PO4-P)

The general distributions of phoshorus compound varied with seasons at the three moles of

Tarkwa Bay (Tables 4 and 5). Its range in the rainy season was (0.86 – 3.48) mg/L with highest mean value of 2.52 ± 0.70 mg /L in the East mole. In the dry season, the concentration of phosphate decreased slightly in the range of 1.22 –2.3 mg/L with inter- annual mean value of (1.90 ± 0.32) mg/L for the West mole, 2.3 ± 0.33 mg/L for the East mole and (1.80 ± 0.38) mg/L for the Training mole respectively (Table 4).

77

Phosphorus assessment in Tarkwa Bay coastal waters of the West mole was negatively correlated with the water temperature (-0.056), air temperature (-0.103), salinity (-0.181) conductivity (-0.211), sulphate (-0.014) but it was positively correlated with pH (0.424), in the West mole (Table 6). Similarly, in the Training mole, phosphate had a negative correlation with all the physico-chemical parameters reported except with pH (0.406) (Table

7). In the East mole, phosphate had a low correlation with water and air temperature while pH and sulphate are negatively correlated with rock temperature (-0.177), salinity (-0.392), conductivity (-0.407) as shown in Table 8.This shows the phosphate content in Tarkwa Bay coastal waters were influenced by the dynamics of biological activities under natural conditions.

2= 4.3.3 Sulphate (SO4 )

=2 The sulphate concentration (S04 ) showed a clear persistent variations in the 3 moles of

Tarkwa Bay coastal waters. A highest mean value (24.6 ± 3.08) mg/L was recorded during the dry season in the West mole and it ranged between (19.3 – 27.8 mg/L). In the rainy season, the mean value decreased slightly (24.3 ± 3.42) mg/L and ranged between (17.0 –

28.4 mg/L) in West mole.

In the Training mole, sulphate concentration showed a significant correlation with water temperature (0.685), air temperature (0.632), rock temperature (0.509), and salinity (0.520) and had a low correlation with the conductivity (0.169) as shown in (Table 6; Figure:12).

Conversely, in the West mole, sulphate had a negative correlation with pH (-0.418) and conductivity (-0.646) and a low correlation with pH (-0.418) and conductivity (-0.646) and as well as low correlation with water temperature (0.290), air temperature (0.434), rock

78

temperature (0.174) but significantly correlated with salinity (0.732) (Table 6). In the East mole, sulphate concentration had a low correlations with water temperature (0.251), air temperature (0.224) ,rock temperature (0.415), salinity (0.435) and conductivity (0.088) but it negatively correlated with pH (-0.195) (Table 7).

Figure 12: Temporal variation in nutrient (Sulphate) at the 3 moles of Tarkwa Bay

(April, 2008- March, 2010).

79

Figure 13: Temporal variations in nutrient (Phosphate) at the 3 moles

of Tarkwa Bay (April, 2008-March ,2010).

80

Figure 14: Temporal variations in nutrient (Nitrate) at the 3 moles of Tarkwa Bay

(April, 2008-March, 2010)

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4.4.0 Environmental Fluctuations of three micro-habitats at three different zones on

intertidal shore of Tarkwa Bay.

4.4.1 Temperature fluctuations governed the distribution of intertidal organisms on the shores. Thermal conditions and dessication are severed at supra-littoral pool (+3m) > (+2.6m)

> (+2.2m) above chart datum. The maximum temperature at the 3 rockpools were 30°C

(+3m), 29.4°C (+2.6m) and 28°C (+2.2m). There was a steady increase in ambient temperature from 8am through 3pm and the prevailing temperature later dropped from 3pm to 5pm (Figure 15). The ANOVA results showed that the temperature at the three rockpools varied significantly (p<0.05) and temperature of the three intertidal rock pools fluctuated significantly during the period of investigation (ANOVA, p<0.05). The highest salinity value

(35.3‰) was recorded at 12.30pm in pool (+3m) conversely, the lowest salinity value (29‰) was recorded at 11.30 am at (+3m). The pool at mid-littoral shore (+2.6m) had consistent salinity value compared to supra-littoral tide-pools (Figure 15). The supra-littoral rockpool

(+3m) exhibits fluctuating salinity values throughout the study period. Two-ANOVA results show that salinity variation at the three rock pools were significantly affected by the height of the rock pool on the shore (ANOVA, P<0.05) and the time of salinity measurement (ANOVA, p<0.05).

82

31

C) 30 o 29 28 27 2.2m

Temperature( 26 2.6m 25 3m

Time (Hours)

Figure 15: Diurnal variations in temperature at 3 rockpools of 3 different tidal zones at the West mole of Tarkwa Bay.

83

2.2m 37 2.6m 35 3m 33 31

29 Salinity(‰) 27 25 10am 11am 12am 1pm 2pm 3pm 4pm 5pm 6pm

Figure 16: Diurnal variations in salinity at 3 rockpool of 3 different tidal zones at the

West mole of Tarkwa Bay.

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4.4.2 Thermal variations in air, rockpool, rock surface and limpet foot.

Thermal variations in two microhabitats (rock pool and rock surface), air temperature and foot temperature of the obligate high shore limpet Patella safiana were assessed between

8am through 5 pm (Figure 17). The ambient thermal conditions were governed by solar cycle with opitimum temperature and sharpness of the peak depends on the time of the day (12 noon and 2pm) (Figure 17). Air temperature has the highest temperature range (26OC -

30OC), rock surface (25.6OC – 29.5OC), rockpool (24.8OC-28.3OC) and Patella spp foot temperature (24.3OC - 26.3OC). The distribution and the effect of ambient temperature at the

2 microhabitats, air temperature and the foot of obligate high-shore limpets were noted to depend on factors such as the buffering capacity of the tidal inundation and solar radiation and time of the day (Figure 17). There were significant differences in air temperature, rockpool, limpet foot and rock surface (ANOVA, P<0.05) and in their interactions between particular time of the day when the temperature measurements were taken (ANOVA, P

<0.05).

85

Figure 17: Diurnal variations in air, rockpool, rock surface and limpt foot at

different tidal elevations in the West mole of Tarkwa Bay.

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4.5 Heavy Metal Studies

4.5.1 Heavy metal concentrations in Patella safiana, seaweed and seawater.

The comparison of the heavy metal concentrations of seawater, seaweed and Patella safiana stations (TM3 and WM3) showed that mean concentrations followed the sequence: Fe > Mn

> Zn > Cu > Cd > Co > Cr> Ni> Pb for seaweed (µg.g-1dry.wt); Fe > Cu > Mn > Zn > Cr >

Cd > Ni > Pb for Patella safiana and seawater; Fe > Zn > Mn > Cu > Cd > Co > Cr > Ni >

Pb for rainy and dry seasons respectively. The mean values for all the heavy metals were significantly higher in rainy season compared to the dry season during the study period (t 0.05,

18=2.10; p < 0.05) in seawater. The level of concentrations were significantly higher in

Patella safiana > seaweed> seawater (ANOVA; p < 0.05).This shows that Patella safiana has a higher concentration potentials compared to seaweeds (Table: 8). One way analysis of variance (ANOVA) and Student Newman-Keuls (S-N-K) test was used to test for statistical differences (5% level) in the mean concentrations of heavy metals in seawater, seaweeds and patella safiana.

87

Table 8: Mean Seasonal Concentration of heavy metals in seawater, seaweed and Patella safiana at the Training and West moles of Tarkwa Bay.

Sample Pb Mn Zn Cu Ni

TM WM TM WM TM WM TM WM TM WM

Seawater R 0.19±0.07 0.05±0.02 46.53±4.94 16.97±2.15 48.57±7.49 16.62±1.32 44.26±3.74 12.92±1.07 2.84±0.39 1.04±0.16

(µg/L) D 0.05±0.02 0.03±0.02 35.44±2.10 11.48±2.12 32.69±2.26 10.70±2.67 37.09±1.07 13.02±2.06 2.07±0.09 0.81±0.15

Seaweed R 0.08±0.03 0.07±0.02 29.74±3.44 22.20±1.76 17.35±5.43 23.99±1.16 22.89±3.39 23.66±2.40 0.73±0.50 1.24±0.15

(µg.g-1dry wt) D 0.03±0.01 0.05±0.02 15.82±3.20 21.53±2.27 7.85±0.10 20.64±1.93 12.39±2.59 20.06±1.29 0.04±0.01 2.32±0.40

Patella R 0.62±0.40 0.18±0.06 39.51±5.20 39.54±3.79 32.55±2.71 36.18±1.72 36.00±3.20 45.27±2.80 1.04±0.29 1.45±0.13 safiana (µg.g- D 0.30±0.22 0.05±0.02 18.62±5.03 35.44±2.10 20.65±4.37 32.69±2.26 19.22±7.21 37.09±1.07 0.34±0.10 2.07±0.09 1dry wt)

R = Rainy season; D = Dry season; TM = Training mole; WM = West mole.

88

Table 8 Cont: Mean seasonal concentration of heavy metals in seawater, seaweed and

Patella safiana at the Training and West moles.

Sam Cd Co Cr Fe

ple TM WM TM WM TM WM TM WM

Seaw R 9.89± 2.61± 4.66± 1.32± 1.36± 1.19± 48.75 40.73

ater 2.63 0.44 1.69 0.09 0.17 0.10 ±6.32 ±2.54

(µg/ D 3.28± 1.36± 2.60± 0.61± 0.53± 0.99± 34.25 29.59

L) 0.99 0.53 0.21 0.54 0.38 0.19 ±2.33 ±3.05

Seaw R 4.69± 2.91± 2.58± 0.40± 2.57± 0.18± 46.19 40.28

eed 0.55 0.25 0.68 0.12 0.73 0.05 ±4.56 ±2.98

(µg.g D 2.33± 2.24± 1.15± 0.27± 2.04± 0.32± 30.88 34.73

-1dry 0.35 0.43 0.20 0.09 0.72 0.14 ±3.95 ±2.04

wt)

Patel R 6.38± 5.97± 4.66± 1.70± 6.67± 0.63± 56.40 50.43

la 0.84 1.62 0.66 0.22 0.89 0.24 ±4.28 ±2.68

safia D 2.76± 3.28± 2.26± 2.60± 6.60± 0.54± 54.56 34.25 na 1.39 0.99 0.56 0.21 1.27 0.38 ±1.65 ±2.33 (µg.g

-1dry

wt)

(R=Rainy Season and D=Dry Season)

89

90

4.5.2 Heavy metal concentrations in different body parts of the selected molluscan

species.

The result of the temporal concentrations of heavy metal in various parts of the study molluscs are presented in (Tables: 9 and 10). The effects of seasonality and body parts of the study molluscs on the concentration of heavy metals were evaluated using one-way ANOVA at the significant level of (p<0.05) and comparison of means by Duncan‟ multiple range test

(DMRT) was used test for significant differences in heavy metal concentrations among different body parts. Generally, a different seasonal profile was observed for different metal concentrations in different body parts of the study molluscs during the rainy and dry seasons.

The mean values of heavy metal concentrations decreased in the order: Mn >

Fe>Zn>Cu>Cr>Pb while the level of concentrations of heavy metals in body parts of the molluscs decreased in the order: Body tissues> foot> mantle >shell. The highest metal concentration was recorded in Buccinum undatum (266.6µg/gdry weight for Mn) and lowest concentration was found in Nerita senegalensis (0.01µg/g.wt of Pb).

Temporal patterns were observed in dry season between body parts and heavy metal concentrations. The level of heavy metal concentratons were significantly lower in dry season compared to rainy season (t0.05, 18=2.10; P<0.05). There are clear variance among the body parts for concentration potentials for heavy metals in the aquatic environment (ANOVA; p<0.05). The maximum concentration of Pb (1.94±0.30) was recorded in the mantle of

Buccinum undatum during the dry season compared to a minimum concentration of

0.01±0.001 recorded in the mantle of Nerita senegalensis during the rainy season.

Concentrations of Mn ranged between 266.61±12.60 (body parts of Buccinum undatum during the rainy season) and 7.88±2.10 (shell of Patella safiana during the dry season). Cr concentrations range between 3.01±0.10 and 0.06±0.01 in the foot of Buccinum undatum

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during the rainy season and the mantle of Thais califera respectively. The maximum concentration of Cu was recorded in the body tissue of Buccinum undatum during the dry season (22.14±1.64) compared to a minimum of 0.66±0.01 in the shell of Nerita senegalensis during the dry season. Unlike the other metals, the maximum concentration of Zn

(66.31±8.40) was recorded in the body tissue of Patella safiana during the dry season and a minimum of 0.66±0.01 in the shell of Nerita senegalensis during the dry season. Fe concentration range between 86.40±6.40 in the body tissue of Buccinum undatum during the rainy season and a minimum of 2.17±0.002 recorded in the shell of Nerita senegalensis during the dry season. Histograms and associated distributions of heavy metal concentrations in different molluscan body parts and the corresponding mean standard deviations are expressed as µgg-1dry weight (Table: 9; Figures: 18- 32).

Figure 18: Mean seasonal variations of Manganese in different body parts of Nerita senegalensis.

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Figure 19: Mean seasonal variations of Lead in different body parts of

Nerita senegalensis.

93

Rainy season

Figure 20: Mean seasonal variations of Zinc in different body parts of Nerita senegalensis. 94

Figure 21: Mean seasonal variations of Manganese in different body parts of Thais callifera

95

Figure 22: Mean seasonal variations of Lead in different body parts of Thais callifera

96

Figure 23: Mean seasonal variations of chromium in different body parts of

Thais callifera

97

Figure 24: Mean seasonal variations of Iron in different body parts of Thais callifera

98

Figure 25: Mean seasonals concentrations of Zinc in different body parts of Thais callifera

99

Figure 26: Mean seasonal concentrations of copper in different body parts of

Thais callifera

100

Figure 27: Mean seasonal concentrations of Manganese in different body parts

of Buccinum undatum.

101

Figure: 28 Mean seasonal concentrations of Lead in different body parts of

Buccinum undatum

102

Figure 29: Mean seasonal concentrations of Chromium in different body parts

of Buccinum undatum

103

Figure 30: Mean seasonal concentrations of Iron in different body parts of Buccinum undatum

104

Figure 31: Mean seasonal variations of Zinc in different body parts of Buccinum undatum

105

Figure 32: Mean seasonal concentrations of Copper in different body parts of Buccinum undatum.

106

Table 9: Concentrations of heavy metals in different body parts of selected

molluscs during the rainy season.

Test Species Heavy Body Tissue Mantle Foot Shell Metal µg/g/dry/wt µg/g/dry/wt µ/g/dry/wt µ/g/dry/wt

Nerita Mn 164.10±1.70 86.4±1.30 124.22±1.61 20.34±0.54 senegalensis Pb 0.04±0.01 0.01±0.001 0.08±0.001 1.10±0.01 Cr 1.12±0.51 1.10±0.01 0.07±0.01 0.05±0.001 Fe 42.31±0.41 12.6±0.01 6.40±0.001 3.14±0.002 Zn 15.21±0.46 8.14±1.14 5.31±0.01 2.34±0.004 Cu 3.1±0.09 2.34±0.19 1.40±0.02 0.96±0.001 Patella safiana Mn 186.30±1.64 58.60±1.60 36.16±1.30 9.63±1.10 Pb 1.17±0.004 1.00±0.001 0.80±0.01 0.34±0.002 Cr 2.10±0.001 0.91±0.01 0.76±0.001 0.46±0.001 Fe 49.60±0.01 9.61±0.02 4.74±0.03 2.96±0.02 Zn 56.31±2.2 22.10±1.40 11.34±0.06 6.34±2.31 Cu 6.46±0.81 3.94±1.10 1.96±0.01 1.22±0.04 Thais califera Mn 186.20±2.30 76.14±1.80 87.0±6.14 36.34±7.17 Pb 0.08±0.001 0.02±0.01 0.05±0.0001 0.03±0.001 Cr 1.91±0.001 0.08±0.01 1.10±0.001 0.08±0.002 Fe 63.12±7.10 15.14±0.01 36.15±1.90 12.34±1.13 Zn 66.31±8.40 24.31±1.80 42.31±4.10 9.14±0.90 Cu 12.61±1.20 4.61±0.90 8.12±0.41 5.61±0.12 Buccinum Mn 266.61±12.60 61.41±5.0 86.11±7.61 34.36±2.02 undatum Pb 1.96±0.001 1.10±0.10 1.30±0.10 1.10±0.09 Cr 3.12±0.10 2.10±0.02 3.01±0.10 2.31±0.04 Fe 86.40±6.40 37.10±6.10 48.10± 0.30 15.61±0.16 Zn 59.71±5.14 26.30±5.10 53.16±8.60 22.16±1.30 Cu 22.14±1.64 12.94±1.90 15.31±4.14 9.17±1.19

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Table: 10 Concentrations of heavy metals in different body parts of selected molluscs during the dry season. Species Heavy Body Tissue Mantle Foot Shell Metal µg/g/dry/wt µg/g/dry/wt µg/g/dry/wt µg/g/dry/wt Nerita Mn 122.14±3.41 58.36±2.41 96.64±2.34 16.61±0.86 senegalensis Pb 0.02±0.003 0.01±0.001 0.06±0.001 0.03±0.01 Cr 0.09±0.026 0.06±0.001 0.04±0.001 0.03±0.001 Fe 38.6±1.14 9.14±0.001 5.96±0.002 2.17±0.002 Zn 13.67±1.01 6.36±0.09 3.96±0.001 2.20±0.01 Cu 3.30±1.01 1.96±0.12 1.23±0.010 0.66±0.01 Patella safiana Mn 157.60±1.96 52.94±1.42 31.76±1.96 7.88±2.10 Pb 1.10±0.003 0.92±0.001 0.65±0.002 0.24±0.02 Cr 1.97±0.001 0.71±0.002 0.56±0.003 0.36±0.001 Fe 44.76±1.12 7.76±0.10 3.34±0.04 2.48±0.03 Zn 54.41±2.01 18.96±0.60 9.41±0.10 5.64±1.10 Cu 5.94±0.96 2.94±0.06 1.58±0.20 1.02±0.002 Thais califera Mn 166.4±8.63 66.2±4.40 63.91±5.50 31.96±1.20 Pb 0.06±0.001 0.04±0.001 0.05±0.01 0.035±0.01 Cr 1.86±0.010 0.06±0.001 1.01±0.001 0.06±0.001 Fe 56.4±3.20 12.46±1.01 31.65±1.10 9.56±1.12 Zn 44.93±6.70 23.1±1.21 36.83±3.90 7.96±0.50 Cu 9.64±0.90 3.94±0.10 6.31±0.20 3.72±0.12 Buccinum Mn 248.31±7.10 54.6±5.10 74.14±5.10 31.96±1.01 undatum Pb 1.66±0.11 1.94±0.30 1.29±0.10 0.96±0.01 Cr 1.86±0.01 0.86±1.01 1.76±0.12 1.56±0.02 Fe 77.24±6.10 35.63±3.41 44.80±4.10 8.9±0.17 Zn 58.34±6.14 24.6±4.10 51.20±4.10 20.14±1.10 Cu 19.41±1.23 9.72±1.20 13.14±1.14 7.14±1.12

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4.6.0 Composition, distribution, abundance, diversity, seasonality of molluscan communities of Tarkwa Bay.

The total number of individuals recorded during the study period at the 3 moles of Tarkwa

Bay was 8486 individuals belonging to 69 species from 34 families and 4 classes. A checklist of the molluscan communities of the 3 moles of Tarkwa Bay is presented in Table 11. The distribution of the total individuals recorded were Gastropoda (89.92%), Bivalvia (9.55%),

Cephalopoda (0.33%) and Polyplacophora (0.20%). Gastropoda dominated the 3 moles, and were evenly distributed at the shoreline (Table: 12). Bivalvia had their highest occurrence in the West mole while Polyplacophora and Cephalopoda had their highest occurrence in the

East and West moles respectively (Table 12). Among the Gastropoda the Patella safiana was the most abundant, Arca senilis was the most abundant of the Bivalvia whereas Chiton spp was the only representative of the Polyplacophora while Cephalopoda was dominated by

Sepia officialis. The seasonal abundance of the molluscan species at the 3 moles of Tarkwa

Bay is detailed in Table 12. Kruska-Wallis test were used to test for significant differences in the density and number of abundance of molluscan species among the three moles of Tarkwa

Bay. Mann-Whitney test was used to test for significant difference in the density of molluscan species recorded in the wet and dry seasons.

109

Figure 33: Effect of rainfall on the salinity (‰) at the 3 moles of Tarkwa Bay (April,

2008- March, 2010).

110

Figure 34: Mean number of molluscan species/m2 at West mole (April, 2008- March,

2010).

111

Figure 35: Mean number of molluscan species/m2 at the Training mole of Tarkwa Bay (April, 2008- March, 2010).

112

Figure 36: Mean number of molluscan species/m2 at East mole (April, 2008- March,

2010).

113

Figure 37: Mean number of molluscan Individuals/m2 at West mole (April, 2008-

March, 2010).

114

Figure 38: Mean number of molluscan Individuals /m2 at Training mole (April, 2008-

March, 2010).

115

Figure 39: Mean number of molluscan Individuals /m2 at East mole (April, 2008-

March, 2010)

116

Figure: 40 Temporal variation in Shannon Wiener Index(H1) computed for the three moles of Tarkwa Bay (April, 2008-March, 2010)

117

Figure 41: Temporal variations in Dominance Index (C) computed for the three moles of Tarkwa Bay (April, 2008- March, 2010).

118

Figure 42: Temporal variations in Evenness Index (J1) computed at the three moles of

Tarkwa Bay (April, 2008- March, 2010).

119

The number of species and individuals varied seasonally at the 3 moles of Tarkwa Bay

(Table: 12 and Figures: 34, 35 and 36). The number of species and individuals in each sampling station were higher in the dry season when compared to the rainy season (Tables:

14, and 15 respectively). The maximum number of 11 species was recorded during a particular sampling in EM1 during the dry season while lowest number of 4 species was recorded in TM4. Number of species was lower in the rainy with a minimum of 2 species recorded in WM1, WM2, WM3, WM4, TM1, TM2, EM1 and EM3. A maximum value of 9 species was recorded in TM2 during the rainy season (Table 14 and 15; Appendices:7, 8 and

9).

The number of individuals collected during the dry season constituted 68.3% (5794 individuals), when compared to 31.7% (2692 individuals) during the rainy season.The number of individual in the West mole ranged between 23 individuals (WM2) and 61 individual (WM4) (Tables 12 and 13). In contrast, the Training mole recorded the minimum number of individual (14 individuals) recorded and maximum (54 individuals) were both recorded at TM3 during the dry season. In the East mole, the number of individual molluscs ranged between 20 individuals (EM2) and 65 individuals (EM4) during the dry season. The number of individual recorded during the rainy season ranged between 5 individuals (WM1) and 44 (WM4) in West mole, 7 (TM2) to 41 (TM1) in the Training mole while in the East mole the range was between 4 individuals (EM1) to 36 (EM2) (Tables: 12 and 13; Appendix:

14).

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Table 11: Composition, distribution, abundance, diversity and seasonality of molluscan communities of the intertidal rocky shores of Tarkwa Bay (April, 2008-March, 2010).

DRY SEASON RAINY SEASON TAXA WEST TRAINING EAST WEST TRAINING EAST GASTROPODA Acmaeidae Acmeae saccharina 34 29 24 17 10 12 Acmeae jacquelina 8 10 5 6 3 9 Turbinidae Astrea spp 13 22 3 0 2 0 Astele spp 5 4 4 2 4 0 Aporrhaidae Apporrhais senegalensis 1 2 0 0 0 0 Buccinidae Buccinum undatum 225 275 132 114 143 86 Bullidae Bullia granulosa L 4 7 2 1 0 4 Bullia turrita Gray 0 0 0 0 1 0 Bursidae Bursa marginata 2 8 1 1 2 2 Cerithidae Cerithium atratum Born 4 1 3 0 0 0 Cerithium sinensis 3 0 1 2 0 1

Cerithium genuanus 2 1 7 0 0 0

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Table 11: Cont.

DRY SEASON RAINY SEASON TAXA WEST TRAINING EAST WEST TRAINING EAST GASTROPODA Cassidae Cassis spinosa 3 9 2 0 3 1 Cassis testiculata 14 21 9 3 4 5 Conidae Conus coronatus 4 7 2 1 2 0 Conus genuanus 10 5 1 0 0 0 Conus bilosus 4 10 5 2 7 0 Conus ambiguous 12 16 4 0 0 0 Lottidae Collisella subrugosa 15 22 28 5 0 12 Volutidae Cymbium cymbium_L 3 7 4 12 14 3 Cymbium glans Gmelin 0 6 8 0 1 0 Cypraeidae Cypreae gracili 6 12 21 7 1 3 Cypreae stercoraria L 18 24 36 5 8 9 Cypreae zonata L 2 7 13 4 0 1

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Table 11 : Cont. DRY SEASON RAINY SEASON TAXA WEST TRAINING EAST WEST TRAINING EAST GASTROPODA Fissurellidae Fissurella rosea G 12 21 33 1 6 5 Fissurella nubecula L 42 4 22 10 30 33 Fissurella coarctata 324 212 411 120 127 226 Fasciolariidae Fasciolaria spp 10 6 3 14 3 17 Muricidae Murex cornutus 28 11 7 3 0 4 Murex saxatilis 15 3 26 0 4 9 Murex varius 11 2 9 0 10 2 Thais califera 86 60 54 22 24 15 Thais nodosa 33 41 31 0 9 18 Thais haemastoma 11 21 6 2 4 3 Thais forbesi 6 5 8 1 3 1 Thais rogosa 5 6 7 2 1 5 Drupa nodulosa Adam 1 7 23 9 3 7 Nacidae Natica collaria L 17 10 27 2 1 0 Natica fulminea 13 7 4 5 10 11 Natica marochiensis 1 0 3 1 2 9

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Table 11: Cont.

DRY SEASON RAINY SEASON TAXA WEST TRAINING EAST WEST TRAINING EAST GASTROPODA Nassaridae Nassarius thersites 0 2 1 8 11 5 Nassarius spp 1 0 0 0 0 0 Neritidae Nerita senegalensis 235 436 175 71 115 95 Nerita glabrata 28 31 44 12 9 23 Olividae Oliva acuminate 2 1 3 1 0 6 Patellidae Patella safiana 314 118 351 37 71 45 Littorinidae Littorina littorea 5 8 9 7 6 4 Littorina cingulifera 36 37 6 22 14 5 Littorina punctate 231 331 216 54 87 63 Harpidae Harpa Doris 1 0 1 2 0 0

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Table 11: Cont.

DRY SEASON RAINY SEASON TAXA WEST TRAINING EAST WEST TRAINING EAST BIVALVIA Arcidae Arca senilis 40 22 26 18 34 24 Arca afra Gmelin 4 8 3 12 14 9 Aloididae Aloidis trigonal Hind 1 2 1 21 28 14 Aloidis deutozerberg L 1 0 0 2 6 15 Carditidae Cardium costatum L 3 4 7 26 29 14 Cardium ringens B 1 1 0 0 0 0 Egeria radiate 0 0 0 14 16 7 Iphigenia truncate 1 2 8 12 15 9 Tellinidae Macoma cumana C 0 0 0 2 1 4 Chamidae Chama crenulata 3 0 6 12 8 3 Mytilidae Mytilus perna L 6 8 10 19 4 6 Litophaga spp 3 0 1 2 1 9

Ostreidae Crassostrea gasar 53 11 15 12 9 6

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Table: 11 Cont. DRY SEASON RAINY SEASON TAXA WEST TRAINING EAST WEST TRAINING EAST BIVALVIA Ostridae Ostrea tulipa 12 23 15 18 28 20 Ostrea folium 7 4 10 16 12 14 Donacidae Donax rugosa 2 1 6 9 7 6

POLYPLACOPHORA Chitonidae Chiton spp 2 3 0 4 1 7 CEPHALOPODA Sepiidae Sepia officialis 1 4 6 0 2 4 Octopodidae Octopus vulgaris 2 3 1 2 3 0

126

Table 12: Summary of seasonal variations in the number of individual recorded at the

three moles of Tarkwa Bay.

CLASS DRY SEASON RAINY SEASON

West Training East West Training East

Gastropoda 1860 1874 1795 588 755 759

Bivalvia 97 64 82 195 212 160

Polyplacophora 2 3 0 4 1 7

Cephalopoda 3 7 7 2 5 4

Total 1962 1948 1884 789 973 930

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Table 13: Variation in Number of Species during the dry Season at the 3 moles of Tarkwa Bay (April, 2008 – March, 2010)

WEST MOLE TRAINING MOLE EAST MOLE

WM1 WM2 WM3 WM4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4

N 12 12 12 12 12 12 12 12 12 12 12 12

Min 5 5 5 5 5 6 5 4 4 5 5 5

Max 9 9 10 10 10 9 10 9 11 8 7 10

Mean 6.92 6.5 7.25 7.17 7.5 6.83 7.42 5.92 6.92 7 6.08 6.58

SE 0.36 0.38 0.48 0.44 0.4 0.27 0.47 0.45 0.7 0.35 0.23 0.43

SD 1.24 1.31 1.66 1.53 1.38 0.94 1.62 1.56 2.43 1.21 0.79 1.51

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Table 14: Variation in number of species during the rainy season at the 3 moles of Tarkwa Bay (April, 2008 – March, 2010)

WEST MOLE TRAINING MOLE EAST MOLE

WM1 WM2 WM3 WM4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4

N 12 12 12 12 12 12 12 12 12 12 12 12

Min 2 2 2 2 2 2 3 3 2 3 2 3

Max 6 6 7 7 8 9 7 7 8 7 5 7

Mean 4.08 3.25 3.92 4.25 4.33 4.5 4.75 4.67 4.42 4.92 4.33 4.58

SE 0.29 0.41 0.48 0.37 0.47 0.58 0.41 0.37 0.5 0.38 0.26 0.38

SD 1 1.42 1.68 1.29 1.61 2.02 1.42 1.3 1.73 1.31 0.89 1.31

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4.7.0 Univariate assessement of molluscan communities at the 3 moles of Tarkwa Bay.

4.7.1 Shannon’s Index (H’)

Shannon‟s Index values computed at the 3 moles of Tarkwa Bay varied seasonally with higher values recorded during the dry season (Figure 43; Appendices: 14 and 15). A maximum value of 2.227 (computed in February, 2010) was recorded in WM3 and WM4 of the West mole during the dry season (Table 23). Likewise, in February 2010 the maximum value of Shannon index was 2.181 and 2.170 in WM1 and WM2 respectively. Mean values of

Shannon‟s Index during the dry season in West mole was 1.873±0.174 in WM1, 1.800±0.176 in WM2, 1.900±0.197 in WM3 and 1.888±0.218 in WM4. Values of Shannon‟s Index were lower in the rainy season compared to the dry season with mean value of (1.185±0.457) in

WM2, 1.308±0.376 in WM3 and 1.372±0.320 in WM4. Similarly, the maximum value of

Shannon‟s Index was higher in the dry season compared to the rainy season with the mean value of 2.089 in October, 2009, 1.860 October, 2009, 1.865 May, 2008 and 1.885 May, 2009 in WM1, WM2, WM3 and WM4 respectively. Minimum value for West mole during the rainy and dry season is presented in (Fig 43)

Shannon‟s Index values for the Training mole were similar to the West mole (Figure: 40) with the dry season having higher values when compared to what obtained during rainy season. Minimum value of Shannon‟s Index decreased steadily in the Training from 1.751

(TM1) > 1.679 (TM2)> 1.574 (TM3 and TM4). The maximum value of Shannon‟s index during the dry season was 2.258 in December, 2009 in TM1, 2.133 in January, 2010 in TM2,

2.252 in December, 2008 and 2.155 in December, 2009 in TM4. The highest mean value of

Shannon‟s index during the dry season was 1.983±0.147 in TM1, while mean values of

1.867±0.139, 1.945±0.204), 1.712±0.250 were recorded in TM2, TM3 and TM4 respectively.

Rainy season values of Shannon‟s index ranged between 0.679 in July, 2008 to 1.895 in 130

May, 2008 in TM1, 0.691 September, 2009 to 2.063 May, 2008 in TM2, 0.925 July, 2008 to

1.879 in October, 2008 in TM3 and 1.079 in August, 2008 to 1.880 in October, 2008 in

TM4. Mean value of Shannon‟s Index followed the following patterns TM1 (1.351±0.347) <

TM2 (1.394±0.406) < TM3 (1.434±0.344) < TM4 (1.523±0.272).

Shannon‟s Index values for the East mole were likewise higher in the dry season when compared to what obtained in rainy season (Figure 43). During the dry season Shannon‟s index value ranged between 1.373 in November, 2008 to 2.348 in December, 2008 in EM1,

1.588 in April, 2009 to 2.064 in February, 2010 in EM2, 1.575 in April, 2009 to 1.988 in

November, 2009 in EM3 and 1.586 in March, 2009 to 2.293 in December, 2009 in EM4.

Minimum and maximum values during the rainy season were 0.693 in August, 2008 and

2.013 in May, 2009 in EM1, 1.011 in September, 2008 and 1.896 in May, 2008 in EM2,

0.673 in August, 2008 and 1.768 in October 2009 in TM3, 0.992 in July, 2009 and 1.848

(May,2008) in EM4. Mean values of 1.866±0.318 in EM1, 1.894±0.176 in EM2,

1.773±0.147 in EM3 and 1.850±0.205 in EM4 compared to the lower value when mean value in the rainy season of (1.358±0.376) in EM1, 1.493±0.313 in EM2, 1.423±0.271 in

EM3 and 1.425±0.299 in EM4 (Figure 43).

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Figure 43: Temporal variations in Shannon’s Index at the 12 sampled stations

of the three moles of Tarkwa Bay (April, 2008-March, 2010).

132

4.7.2 Pielou’s Evenness Index

The lowest mean value of evenness index was recorded in the Training mole (TM1) and highest (1.000) in all the sampling stations of the West and East moles (EM1). In the West mole, the rainy season maximum value (1.000) was recorded in WM1 in September, 2009,

WM2 in July, 2009 and in August, 2009, WM3 in August, 2009 and in September, 2009 and

WM4 in July, 2008 and September, 2009 and minimum values of 0.925 in October, 2008, while, 0.863 in August, 2008, and 0.921 in August, 2008 and 0.869 in May, 2008 in WM1,

WM2, WM3 and WM4 respectively in the rainy season(Table 15). Dry season values of evenness in the West mole ranged between 0.925 in March, 2010 and 0.995 February, 2009 for WM1. In WM2 a range between 0.945 in April, 2008, and 0.994 in April, 2009 were recorded in the dry season while a range of between 0.9161 in January, 2009 and 0.992 in

December, 2009 was recorded in WM3. The range of Evenness during the dry season was between 0.951 in February, 2009 and 0.997 in April, 2009 in WM4 (figure: 44).

Evenness values ranged between 0.819 in August, 2008 and 0.985 in May, 2009 in the rainy season in TM1 and between 0.886 in August, 2008 and 0.988 in September, 2009) in TM2

(Table 15). Similarly, during the rainy season evenness values ranged between 0.842 in July,

2008 and 0.997 in May, 2009 in TM3 while a range of between 0.875 in September, 2008 and 0.996 in September, 2009. Dry season values of Evenness ranged between 0.959 in

March, 2010 and 0.994 (February, 2009) in TM1 and between 0.937 in April, 2008 and 0.993 in February, 2010) in TM2. Evenness value in the dry season ranged between 0.933 in April,

2008 and 0.991 in March, 2009 while in TM4 a range of between 0.949 in February, 2009 and 0.998 in February, 2010 was recorded. Across the East mole evenness values ranged between 0.962 in April, 2009 and 0.997 in March, 2010 in EM1 and between 0.995 in April,

2008 to 0.995 in March, 2009 in EM2 in the dry season while the range of evenness values

133

in EM3 and EM4 ranged between 0.920 in April, 2008 to 0.997 in February, 2010 and

0.925 in November, 2009 to 0.997 in February, 2010 respectively in dry season (Table 14).

Evenness values in the rainy season ranged between 0.870 in September, 2008 and 1.000 in

August 2009, and in September, 2009 in EM1 and in EM2 between 0.915 in October, 2009 and 0.987 in October, 2008. In similar manner, in EM3 and EM4 evenness values ranged between 0.936 in May, 2009 and 0.987 in October 2009 and 0.983 in July, 2009 in and 0.997 in August, 2009 in the rainy season (Figure 44; Appendix:20).

134

Figure 44: Temporal variations in Evenness Index at the 12 sampled stations of

the 3 moles of Tarkwa Bay (April, 2008- March, 2010).

135

4.7.3 Simpson Dominance Index

Dominance values at the 3 mole of Tarkwa Bay between April, 2008 and March, 2010 ranged between 0.100 (EM1) and a maximum of 0.592 (WM1). The dominance Index value ranged between 0.114 in February, 2010 to 0.208 in April, 2009 with a mean value of 0.162±0.028 in

WM1 while a minimum value of 0.117 in February, 2010 and Maximum value of 0.205

(March, 2010) was recorded in WM2 with a mean value of 0.172±0.028. Mean value of dominance Index in WM3 0.160±0.028 was similar to WM4 (0.161±0.010) during the dry season. The range of dominance value recorded for WM3 and WM4 ranged between 0.114 in

February, 2010 to 0.029 December, 2008 and 0.114 (February, 2010) to 0.227 (February,

2009) respectively (Figure 45).

The dominance Index values in TM1 ranged between 0.108 (December, 2009) to 0.180

(December, 2008) with a mean value of 0.144±0.021 during the dry season compared to a minimum of 0.173 (May, 2008), maximum of 0.514 (July, 2008) and a mean of

(0.514±0.108) which obtained during the rainy season (Figure: 45). In TM2 dominance value ranged between 0.125 in January, 2010 in and 0.207 in April, 2008 in the dry season compared to a higher minimum, maximum and mean value of 0.144 in May, 2008, 0.501 in

September, 2009 and 0.281±0.105 in the rainy season.

The lowest dominance value of 0.110 in December 2008 and 0.120 in December, 2009 were record during the dry season in TM3 and TM4 respectively when compared to a minimum of

0.165 in October, 2008 in TM3 and 0.160 in October, 2010 in TM4 during the rainy season.

Mean values of dominance also were higher in the rainy season (0.281±0.105) and TM4

(0.272±0.107) when compared to the dry season values of 0.152±0.032 and 0.191±0.013 for

TM3 and TM4 respectively.

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Dominance values at the sampling stations of East mole were similarly higher in the rainy season when compared to dry season value. Minimum values of 0.100 (December, 2008),

0.129 in February, 2010, 0.143 in November, 2009 and 0.102 in December, 2009 were recorded during the dry season corresponds to maximum values of 0.256 in November, 2008,

0.208 in April, 2009, 0.213 in April, 2009 and 0.208 in March, 2009 for EM1, EM2, EM3 and EM4 respectively during the dry season (Figure: 45; Appendix: 19). Mean values of dominance recorded in the East mole during the dry season for at the East mole were

0.168±0.51 (EM1), 0.157±0.028 (EM2), 0.177±0.026 (EM3) and 0.165±0.030 (EM4) respectively. Rainy season values of dominant Index value ranged between 0.141 in May,

2009 to 0.500 in August, 2008 in EM1, 0.157 in May, 2008 to 0.389 in September, 2008 in

EM2, 0.174 in October, 2008 to 0.520 in August, 2008 in EM3 and 0.170 in May, 2008 to

0.398 in July , 2009 in EM4. The mean values of dominant Index values for the in rainy season for EM1, EM2, EM3 and EM4 were 0.285±0.106, 0.245±0.079, 0.260±0.088 and

0.263±0.089 respectively.

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Figure 45: Temporal variations in Simpson’s Dominance Index at the 12 sampled stations of the three moles of Tarkwa Bay (April, 2008- March, 2010)

138

4.7.4 Size-frequency distribution of selected molluscan species sampled at the

three moles of Tarkwa Bay.

4.7.4.1 Patella safiana

The intensity and timing of juvenile recruitment differed among the different ecological, economical and cultural species of intertidal molluscs studied. The size-frequency histograms of Patella safiana are shown in (Figure 46). Patella safiana has a particularly long period of recruitment which last for the whole year except (July, 2008; N=60). The population is polymodal frequency distribution with lowest number of recruits, and higher numbers of adult size of reproductive age (Figure: 46). The largest size range>30mm has lower density as compared with mature adult size rang >15mm. the population of Patella safiana fluctuates with seasons. Higher density of Patella safiana was found in dry season.

4.7.4.2 Nerita senegalensis

The size-frequency histograms of Nerita senegalensis are shown in Figure 47. Cohorts

<10mm which are recruits were poorly represented in the rainy season months (May, June,

July, August and September, 2003), followed by low density present of Nerita senegalensis population on the shores. The largest size class > 30mm was low on the shores throughout the year. Reproductively mature individuals of Nerita senegalensis were present on the shores throughout the seasons but higher density in dry seasons. The histograms of Nerita senegalensis showed polymodal frequency distributions throughout the seasons (Figure 47).

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4.7.4.3 Thais callifera

Different cohorts of Thais callifera appeared to be present on the shores at both seasons

(Figure: 48) reproductively matured individuals >20mm were present on the shores throughout the year (Figure: 48). Numbers of immature individuals were less than mature individuals on the three shores. Individuals of the largest size class were present on the shore in (November, 2008; N=82). The highest number of Thais callifera was recorded on the shores in dry season (December 2008; N=248).

4.7.4.4 Buccinum undatum

Recruitment of juveniles into adult population occurred in dry season months. No recruits were found in rainy season months. The two seasons were characterized with reproductively matured individuals of Buccinum undatum species on the shores (Figure:49). The highest size range class (120-140) mm recorded low frequency on the shores in both rainy and dry seasons. Buccinum undatum population exhibit polymodal frequency distributions throughout the seasons. Reproductively matured individuals (> 20mm) were recorded on the shores throughout the study period. The least density was found in September, 2008; N =96 and highest numbers were recorded in dry season, 2009; N =264).

140

Figure 46: Size frequency distribution of Patella safiana at the three moles of Tarkwa

Bay (May, 2008 - April,2009).

141

Figure 47: Size Frequency distribution of Nerita senegalensis at the three moles of Tarkwa Bay. (May, 2008 - April, 2009)

142

143

Figure 48 : Size frequency distribution of Thais callifera at the three moles of Tarkwa Bay. (May, 2008 - April, 2009).

144

Figure 49: Size frequency distribution of Buccinum undatum at the three moles of Tarkwa Bay. (May, 2008 - April, 2009). 145

4.7.5 BIOLOGY OF INTERTIDAL MOLLUSCS

4.7.5.1 Studies on shell dimensions of selected molluscs.

Shell length and shell height are good predictors of Ash-free dry weights (AFDWs) for the study species (Buccinum undatum, Thais callifera and Nerita senegalensis). Log transformed data showed a strong relationship of AFDW with shell variables (Tables: 15, 16, 17 and 18). .

Table 15: Descriptions of shell variables for Nerita senegalensis, Thais callifera and

Buccinum undatum

Species Log SL Log SW Log AL Log AW Log SH (mm) (mm) (mm) (mm) (mm)

Nerita Min 1.217 1.011 0.875 0.602 senegalensis Max 1.423 1.431 1.114 0.903

Mean 1.331 1.207 1.006 0.752

SE 0.006 0.007 0.007 0.008

SD 0.047 0.056 0.052 0.063

Thais Min 1.279 1.000 1.061 0.699 callifera Max 1.775 1.638 1.537 1.230

Mean 1.520 1.394 1.292 0.957

SE 0.015 0.017 0.016 0.018

SD 0.100 0.113 0.105 0.117

Buccinum Min 1.100 0.954 0.903 0.398 undatum Max 2.104 1.813 1.927 1.646

Mean 1.837 1.566 1.660 1.097

SE 0.032 0.026 0.031 0.032

SD 0.222 0.177 0.217 0.223

(Min= Minimum, Max = Maximum, SD= Standard deviation and SE= Standard Error)

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Shell length (SL) and Shell height (SH) were found to be strongly correlated with ash-free dry weight (AFDW) for the selected molluscan species of Tarkwa Bay rocky shores.

Buccinum undatum (SL: r2 = 0.99, P<0.0001; N =70; SH: r2 = 0.94, P<0.05; N = 70). Shell lengths measured for Buccinum undatum ranged in size from a maximum length of 125.0mm to a minimum length of 53.0mm (Mean= 81.04mm, S.D± 4.08mm, N = 70). The largest shell height documented for Buccinum undatum was 27.5mm and the smallest height was

16.08mm (Mean =19.03mm, S.D±4.64mm, N = 70).

Figure 50: Shell dimensions for Buccinum undatum

147

Thais callifera: (SL: r2= 0.996, P<0.0001; N =69; SH: r2 = 0.93, P<0.0001 N=69). Shell length recorded for Thais callifera ranged (7.40 – 22.30) mm and (Mean=16.30mm, S.D±

3.02mm, N=69). The range for the height of Thais callifera was 5.80mm- 9.60mm

(Mean=7.68mm, S.D±2.04; P<0.05, N=69).

Figure 51: Shell dimensions for Thais callifera

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Nerita senegalensis (SL, r2=0.927; P<0.0001 N=75; SH, r2 =0.862, P<0.0001 N=75). Shell length measured for Nerita senegalensis (Mean=6.76mm, S.D ±2.5; SH=1.63mm; S.D±0.81; range: 4.86mm- 8.51mm; P<0.05, N=75).

Figure 52: Shell dimensions for Nerita senegalensis.

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Table 16: Descriptive Statistics for Ash free Dry and Corresponding Shell length in

Buccinum undatum (N=70).

Variables Shell Length (mm) Ash Free Dry Weight (g)

Min 53 0.92

Max 125 15.67

Mean 81.04 4.83824

Std. error 2.74579 0.534616

Variance 376.968 14.2907

Stand. Dev 19.4157 3.7803

Table: 17 Correlations between log-transformed values of ash-free dry-weight (AFDW) against shell-length (SL) for Buccinum undatum. Re-transformed values of AFDW and

SL are provided in the form of a conventional allometric equation: W = aLb

Equations Expression/ Values

Regression Equation Log AFDW = 3.37SL – 5.8339

Allometric Equation AFDW = 0.0000015SL3.37

R2 0.9989

P <0.0001

150

Figure 53 : Relationship between Log Ash Free Dry Weight (AFDW) and Log Shell Length (SL) in Buccinum undatum

151

Figure 54: Shell variable relationships for shell length Vs Shell width in Buccinum undatum

152

Figure 55: Shell variable relationships for shell length Vs Shell Height in Buccinum undatum 153

Figure 56: Shell variable relationships for shell length Vs Aperture length in Buccinum undatum

154

Figure 57: Shell variable relationships for Aperture Length Vs Aperture width in

Buccinum undatum.

155

Table: 18 Correlations between log-transformed values of ash-free dry-weight (AFDW) against shell-length (SL) for Thais callifera. Retransformed values of AFDW and SL are provided in the form of a conventional allometric equation: W = aLb

Equations Expression/ Values

Regression Equation Log AFDW = 2.963SL – 5.172

Allometric Equation AFDW = 0.00000673SL2.963

R2 0.996

P <0.0001

Figure 58: Relationship between Log Ash Free Dry Weight (AFDW) and Log Shell

Length (SL) in Thais califera.

156

Figure 59: Shell variable relationships for shell length Vs Shell width in Thais callifera

157

Figure 60: Shell variable relationships for shell length Vs Aperture Width in Thais callifera

158

Figure 61: Shell variable relationships for shell length Vs aperture length in Thais callifera.

159

Figure 62: Shell variable relationships for shell length Vs shell height in Thais callifera.

160

Figure 63: Shell variable relationships for Aperture Length vs Aperture Width in Thais callifera.

161

Table: 19 Correlations between log-transformed values of ash-free dry-weight (AFDW) against shell-length (SL) for Nerita senegalensis. Retransformed values of AFDW and

SL are provided in the form of a conventional allometric equation: W = aLb

Equations Expression/ Values

Regression Equation Log AFDW = 2.122L – 4.958

Allometric Equation AFDW = 0.0000110SL2.122

R2 0.927

P <0.0001

Figure 64: Relationship between Log Ash Free Dry Weight (AFDW) and Log Shell

Length (SL) in Nerita senegalensis

162

Figure 65: Shell variable relationships for shell Length vs aperture length in Nerita senegalensis.

163

Figure 66: Shell variable relationships for shell length vs shell height in Nerita senegalensis.

164

Figure 67: Shell variable relationships for shell length vs shell width in Nerita senegalensis.

165

Figure 68: Shell variable relationships for Shell Length vs Aperture Width in Nerita senegalensis.

166

Figure 69: Shell variable relationships for Aperture Length vs Aperture Width in Nerita senegalensis.

167

Table: 20 Laboratory Observations on the Feeding rates of Two Species of Herbivorous Molluscan Fauna.

Herbivorous Shell Wet Dry Feeding Algal Algal Consumption rates (mean ±S.D) Dry Grazers Length Tissue Tissue Area Wet Weight

(mm) Weight Weight (cm2) Weight (g.cm-2) (g) (g) (g.cm-2) g wet algal wt. g dry algal wt. g wet tissue wt-1.day-1 g dry tissue wt-1.day-1 22.2 4.2140 0.2329 14.62 0.0188 0.0078 0.1749 0.2635 21.4 4.9200 0.1164 10.59 0.0264 0.0089 0.1816 0.2704 22.8 0.5234 0.2558 14.75 0.0214 0.0078 0.1669 0.174±0.0074 0.2463 0.260±0.0124 28.9 1.5458 0.3683 24.50 0.0291 0.0059 0.1055 0.1365 Nerita 29.0 1.2805 0.2683 27.66 0.0192 0.0072 0.1500 0.2474 senegalensis 30.1 1.4392 0.3280 41.41 0.0263 0.0054 0.1654 0.140±0.031 0.2339 0.206±0.0605 Patella 21.2 0.2483 0.0649 16.50 0.0089 0.0035 0.0891 0.1374 safiana 21.8 0.2398 0.0732 18.66 0.0103 0.0039 0.1146 0.1648 20.9 0.3361 0.0545 13.85 0.0126 0.0045 0.1099 0.105±0.014 0.1628 0.155±0.0152 31.0 0.6535 0.1764 14.28 0.0291 0.0105 0.0908 0.1223 30.9 0.6596 0.1844 20.66 0.0154 0.0056 0.0693 0.0988 30.7 0.6571 0.1593 19.2 0.0181 0.0076 0.0754 0.078±0.0113 0.0107 0.077±0.0588 Algal Assemblages = Enteromorpha tubulosa, Cladophora pilulifera and Ulva lactuca Duration of laboratory experiment = 7 days Mean salinity value = 31.4‰ Mean laboratory temperature = 28.70C

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4.7.5.2 Gut Content Analysis

Analysis on the gut content shows that the species of algae found in the gut of herbivorous limpets vary during different months of the year. Chlorophyta dominated the algal diets during most of the months (Figure: 70).

Figure 70: Mean Percentage of different Algae and Detritus found in the Gut

content of Limpet species (N=96) from May, 2008 – April, 2009.

169

The mean percentage of Chlorophyta in gut of Limpet spp over the study period was 34.3±7.51% with a range of 18% (July) - 44% (May). Rhodophyta had a minimum percentage gut content of

4% (April) reaching a maximum of 31% (July) with a mean percentage gut content of

14.58±8.43% while the percentage gut content of Crustose- Coralline algae ranged between

18% (December) to 37% (March) and a mean of 27.8±5.59%. Detritus accounted for the remaining gut content with a minimum of 17% (March) and Maximum of 32 % (November) with a mean of 23.7±4.31% (Figure 71).

45

40

35

30

25

20

Percentage Gut content PercentageGut 15

10

5

0

Chloro Rhodo C.Coral Detritus

Figure 71: Box plot showing the minimum, mean and maximum percent gut content

of Limpet spp. (N=96) (Chloro = Chlorophyta, Rhodo = Rodophyta

Crustose and C. Coral = Crustose-Coralline algae).

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4.7.5.3 Foraging Behaviours of Selected Molluscan Species.

The numbers of foraging excursion individuals undertook varied with seasons and tidal conditions, athough in both rainy and dry seasons, there were two foraging windows per day.

Generally, Patella safiana individuals exhibited more foraging excursions in dry season than in rainy season. In this study, individual Patella safiana was noted to undertake one or two foraging excursion daily. The pattern of variation in speed was similar to that of percentage activity: peaks occurred when tides ebbed and ended when the tidal level rose > 1.75m above chart datum and speed were generally faster in dry season than rainy season. Field observations showed that in dry season the speed of Patella safiana were faster during the morning (2.5cm.mm-1) than afternoon foraging window, however usually longer (10 hours) than in the morning foraging window (6 hours). The results of the foraging parameters; total distance travelled, foraging range, maximum speed and activity duration are presented in (Table: 21).

171

Table: 21 Summary of mean values of foraging parameters for Patella safiana during

the dry and rainy seasons.

Foraging Parameters Dry Season Rainy Season (Mean±SD)

(Mean±SD)

Total distance traveled 86.24±5.10 79.61±4.60

(cm)

Foraging Range (cm) 31.26±2.61 26.31±3.12

Maximum Speed 1.10±0.05 0.89±0.01

(cm.min-1)

Activity duration (hours) 1.24±0.01 1.53±0.02

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4.7.5.4 Studies on molluscs’ growth at different tidal zones.

The growth rates (increment in shell length) of Patella safiana and Nerita senegalensis were significantly higher at low tidal mark when compared to the mid and high tidal marks. The growth rates of both Patella safiana and Nerita senegalensis were highly variable at different tidal zones. Juvenile snails (recruites) did, however, grew faster than mature individuals, which appeared to be linked to increased food availability, low environmental stress and low shore height. The result of one- way ANOVA showed that growth in Patella safiana was significantly different across the three tidal zones (ANOVA; p<0.05) and monthly (ANOVA; p<0.05). Similar results were reported in Nerita senegalensis, the growth was significantly different at the tidal zones (ANOVA; p<0.05) and similarly monthly (ANOVA; p<0.05).

14 13 Patella spp 12 11 10

9 Low 8 Mid 7 ShellLength (mm) High 6

5

Jul

Jan

Jun Jun

Oct

Apr Apr

Feb

Sep

Dec

Aug

Nov

Mar

May May

Figure 72: Mean monthly increment in shell length in cohort of Patella safiana

173

Figure 73: Mean monthly increment in shell length in cohort of Nerita senegalensis.

174

4.7.5.5 Effect of Intra-and interspecific Competitions on the growth rate of

selected molluscan species at different environments.

Differences in growth rates were recorded between treatment with the same species of Patella safiana (Tank 1) and with the set-up comprising species of Patella safiana and Nerita senegalensis (Tank 2) (Figure 74). Generally, the growth rate in Tank 1 was significantly higher when compared to Tank 2 (ANOVA, p<0.05). This variance may have resulted from the interspecific competition between Patella safiana and Nerita senegalensis for the available food resources.

Tank 1= Patella spp only Tank 2= Patella spp +Nerita spp

19

17 15 13 11 9 Tank 1 Tank 2

Shell Length (mm) ShellLength 7 5 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 2008 2009

Figure 74: Variation in shell length increment in Tank 1 (Patella safiana) and Tank 2

(Patella safiana + Nerita senegalensis).

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4.7.5.6 Growth rates between males, females and in comparison to a mixed sex population.

Analysis of initial shell length and wet weight data showed that there was no significant difference between treatments of males and females of Patella safiana at the beginning of the experiment (p>0.05 for each criteria). Mean population shell length and wet weight increments obtained after 30 days (1st October – 30th October, 2009) in each treatment are shown in ( Figures:

75 and 76). Statistical tests showed that the mean shell growth increment in the female only group was significantly greater than those for male only and the mixed sex treatments having grown 3.5mm in shell length in comparison to 2.5 mm and 2.6mm respectively (ANOVA;

P<0.05).

Shell growth increment in the mixed sex population was less than the predicted value (derived from mean data for the female and male only treatments indicating slower growth). It was also shown that shell growth increment in the mixed sex group was less than the predicted value

(derivated from mean data for the female and male only treatments), indicating slower growth rate. The data for wet weight increase showed the same significant trend as that of shell length increment (ANOVA; p<0.05,). However there were larger variations about the means for all groups and there was an apparent disparity between wet weight gain and shell length increment.

However, there were larger variations about the means for all groups (ANOVA, p<0.05) and there was an apparent disparity between wet weight gain and shell length increasement.

176

Figure 75: Mean shell length increment in population of Patella safiana.

177

Figure 76: Mean wet weight increment in population of Patella safiana.

178

4.7.6 Biomass studies in mollusc species of economic interest.

4.7.6.1 West mole: Wet Biomass Studies

Temporal changes in the wet biomass of the species of molluscs collected from the West mole of the study area are shown in (Tables: 22 and 23). Three species of the highest percentage total wet biomass (Buccinum undatum, Thais callifera and Littorina punctata) while the remaining seven species (Acmeae saccharina, Nerita senegalensis, Patella safiana, Mytilus edulis, Arca senilis,

Chiton and Fissurella coarctata contributed low percentage biomass to the energy reserved of the

West mole of intertidal rocky shore of Tarkwa Bay. Species of molluscan fauna which were dominant on the West mole of Tarkwa Bay their contributions wet biomass include: Acmeae saccharina (0.95gm/m2, SD ± 0.54gm/m2, range: 0.32gm/m2, - 1.86gm/m2), Nerita senegalensis

(0.75gm/m2, SD ± 0.31gm/m2, range: 0.36gm/m2, - 1.46gm/m2), Littorina punctata (2.95gm/m2,

SD ± 2.95gm/m2, rang: 0.54gm/m2, - 6.01gm/m2), Patella safiana (2.07gm/m2, SD ± 1.07gm/m2, range: 0.71gm/m2, - 3.24gm/m2), Buccinum undatum (10.16gm/m2, SD ± 2.95gm/m2, range:

7.01gm/m2, - 15.01gm/m2), Thais callifera (6.11gm/m2, SD ± 3.57gm/m2, range: 3.04gm/m2, -

14.05gm/m2), Fissurella coarctata. (2.65gm/m2, SD ± 1.33gm/m2, range: 1.22gm/m2, -

4.74gm/m2), Mytilus edulis sp (1.01gm/m2, SD ± 0.39gm/m2, range: 0.76gm/m2, - 2.86gm/m2),

Arca senilis (1.59gm/m2, SD ± 0.63gm/m2, range: 0.76gm/m2, - 2.86gm/m2) and Chiton spp

(2.04gm/m2, SD ± 0.99gm/m2, range: 0.94gm/m2, - 3.09gm/m2). Chiton sp. and Acmeae saccharina were found in all samples but had low biomass.

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4.7.6.2 West mole: Dry Biomass Studies.

The temporal variations in the dry biomass of various species of molluscan fauna from the West temporal is presented in Table 23. Ten species of molluscan fauna contributed to mean average of

30.78mg/m2. The average percentage composition of dry biomass of ten species is Acmaea saccharina (2.72%), Nerita senegalensis (1.72%), Littorina punctata (10.33%), Patella safiana

(6.34%), Buccinum undatum (9.61%), Thais callifera (18.97%), Fissurella coarctata (8.45%), and Mytilus edulis (4.42%), Arca senilis (8.74%) and Chiton spp (5.59%).

Some species like Acmeae saccharina, Nerita senegalensis, Arca senilis have low dry biomass compared their values in wet biomass composition. Some large size species of molluscan fauna represented by few individuals contributed more in the dry biomass for instance Buccinium undatum, Thais callifera, Littorina punctata contributed in dry biomass. Some species are collected in large numbers but have shown low dry biomass such as Fissurella coarctata. Mytilus edulis and Chiton spp. Details of species showing high mean dry biomass are given in (Table 23) mean dry biomass is based on the observations of ten dominant samples collected on monthly sampling during the study period. The mean values of ten molluscan species include: Acmeae saccharina (0.84mg/m2, SD ± 0.53mg/m2, range: 0.28mg/m2 – 1.69mg/m2), Nerita senegalensis

(0.59mg/m2, SD ± 0.32mg/m2, range: 0.27mg/m2 – 1.38mg/m2), Littorina punctata (3.18mg/m2,

SD ± 1.56mg/m2, range: 0.67mg/m2 – 5.69mg/m2), Patella safiana (1.95mg/m2, SD ± 0.90mg/m2, range: 0.66mg/m2 – 2.92mg/m2), Buccinum undatum (10.01mg/m2, SD ± 2.96mg/m2, range:

6.81mg/m2 – 14.81mg/m2), Thais callifera (5.84mg/m2, SD ± 3.22mg/m2, range: 3.01mg/m2 –

13.07mg/m2), Fissurella coarctata (2.60mg/m2, SD ± 1.30mg/m2, range: 1.10mg/m2 –

4.54mg/m2),Mytilus edulis (1.36mg/m2, SD ± 0.76mg/m2, range: 0.48mg/m2, - 1.99mg/m2), Arca senilis (2.69mg/m2, SD ± 0.72mg/m2, range: 1.24mg/m2, - 3.66mg/m2) and Chiton spp

(1.72mg/m2, SD ± 0.98mg/m2, range: 0.59mg/m2, - 3.69mg/m2).

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4.7.6.3 Training mole: Wet Biomass Studies

Values of wet biomass of molluscan faunal dominant species are given in (Table 24). About three species of ten dominant molluscan contributed above 10% of the total contributing value of the ten species wet biomass. The mean wet biomass of abundant species were; Acmeae saccharina

(4.21%) Nerita senegalensis (4.38%), Littorina punctate (11.2%), Patella safiana (8.44%),

Buccinum undatum (31.34%), Thais callifera (10.32%), Fissurella coractata (10.51%), Mytilus edulis (5.46%), Arca senilis (8.30%) and Chiton spp (5.85%).

4.7.6.4 Training mole: Dry Biomass Studies

It was observed that some species of molluscs were present abundantly but have low dry biomass:

Acmeae saccharina, Nerita senegalensis and Chiton, while other species such as Littorina punctata, Buccinum undatum and Thais callifera had high dry biomass although collected in few number Mytilus edulis., Arca senilis and Chiton had low contributions in terms of abundance and dry biomass (Table 25). Molluscan species sampled not only in small numbers but also had low biomass were Chiton, Thais callifera and Fissurella coarctata. The mean dry biomass of ten molluscan fauna species sampled from training mole rocky shore was based to be (35.19mg/m2).

The followingwere the contributions of each species of the ten experimental molluscs: Acmeae saccharina (1.48mg/m2), SD ± (0.59mg/m2), range: (0.48mg/m2 – 2.4mg/m2), Nerita senegalensis (1.54mg/m2), S.D ± 0.67mg/m2, range: (0.56mg/m2 – 3.10mg/m2), Littorina punctata (3.94mg/m2), SD ± 1.77mf/m2), range: (1.16mg/m2 – 7.01mg/m2), Patella safiana

(2.97mg/m2), SD ± 0.99mg/m2, range: 1.10mg/m2 – 4.20mg/m2), Buccinum undatum

(11.03mg/m2, SD ± 3.05mg/m2, range: 7.30mg/m2- 18.10mg/m2), Thais callifera (3.63mg/m2. SD

± 1.24mg/m2, range: 2.10mg/m2 – 6.30mg/m2), Fissurella coarctata (3.70mg/m2, SD ±

1.12mg/m2, range: 2.39mg/m2 – 6.31mg/m2), Mytilus edulis. (1.92mg/m2, SD ± 0.62, range:

181

1.01mg/m2 – 3.46mg/m2), Arca senilis (2.92mg/m2, SD ± 0.63mg/m2, range: 1.5mg/m2 –

4.12mg/m2), Chiton sp. (2.06mg/m2, SD ± 1.03mg/m2, range: 0.86mg/m2 – 3.96mg/m2).

4.7.6.5 East mole: Wet Biomass Studies

Seasonal variations in the wet biomass of molluscs from East mole of the study area is presented in (Table: 26). All species were found to have contributed wet biomass of more than 3%. The average percent composition of wet biomass of the abundant species were : Acmaea saccharina

(3.19%, x = 1.21 ± 0.56 and range = 0.46 – 2.20), Nerita senegalensis (3.51%, x = 1.33 ± 0.78 and range = 0.54 – 3.41), Littorina punctata (10.50%, = 3.98 ± 2.02 and range = 0.88 – 8.01),

Patella safiana (7.84%, = 2.97 ± 0.98 and range = 0.86 – 4.14), Buccinum undatum (30.61%,

= 11.60 ± 3.46 and range = 7.40 – 18.05), Thais callifera (18.10%, = 6.86 ± 3.43 and range

= 3.09 – 14.01), Fissurella coarctata. (9.02%, = 3.42 ± 1.09 and range = 1.94 – 4.94), Mytilus edulis. (5.0%, = 1.88 ± 0.61 and range = 1.22 – 2.40), Arca senilis (7.47%, = 2.83 ± 0.63 and range = 1.64 – 3.86%) and Chiton sp. (4.80%, = 1.82 ± 0.93 and range = 0.86 – 3.92).

Molluscan species like Buccinum undatum, Thais callifera are carnivorous molluscs gastropod having highest wet biomass percentage composition (Table 26) followed by intertidal grazers like

Littorina punctata, Fissurella coarctata, Arca senilis and Patella safiana. The remaining species of molluscs contributed low percentage wet biomass its energy budget of East artificial breakwaters..

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4.7.6.6 East mole: Dry Biomass Studies

The organic dry biomass of molluscan fanua collected from the East mole is shown in (Table 27).

This average percentage composition of species are: Acmaea saccharina (3.73%), Nerita senegalensis (3.94%), Littorina punctata (11.45%), Patella safiana (8.62%), Buccinum undatum

(33.0%), Thais callifera (9.89%), Fissurella spp. (9.85%), Mytilus edulis (5.36%), Arca senilis

(8.47%), Chiton sp. (5.60%). Large size Buccinum undatum dominates East mole both in terms of abundance and in biomass, followed by Thais callifera. Some species had relatively more dry biomass although found in low numbers such as Patella safiana, Fissurella coarctata and Mytilus edulis. The molluscan species occurring rarely and also had negligible biomass were Chiton species and Patella safiana. The mean values of dry biomass of species are given (Table 27).

Acmeae saccharina (1.21mg/m2, SD ± 0.59mg/m2, range: 0.46mg/m2 – 2.08mg/m2), Nerita senegalensis (1.28mg/m2, SD ± 0.71mg/m2, range: 0.46mg/m2 – 2.99mg/m2), Littorina saxatilis

(3.72mg/m2, SD ± 1.82mf/m2, range: 0.69mg/m2 – 7.06mg/m2), Patella safiana (2.80mg/m2, SD ±

0.95mg/m2, range: 1.01mg/m2 – 4.01mg/m2), Buccinum undatum (10.72mg/m2, SD ± 3.32mg/m2, range: 7.20mg/m2 – 17.40mg/m2), Thais callifera (3.24mg/m2, SD ± 1.10mg/m2, range:

2.21mg/m2 – 5.31mg/m2), Mytilus edulis (1.74mg/m2, SD ± 0.64mg/m2, range: 0.01mg/m2, -

3.36mg/m2), Arca senilis (2.75mg/m2, SD ± 0.59mg/m2, range: 1.48mg/m2, - 3.78mg/m2) and

Chiton spp (1.82mg/m2, SD ± 1.00mg/m2, range: 0.69mg/m2, - 3.76mg/m2).

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4.7.6.7 Comparison of wet and dry biomass at the three moles.

The overall mean wet biomass of species were highest at the Training mole (42.36gm/m2) followed by East mole (37.9gm/m2), and West mole (30.23gm/m2), West mole (30.23gm/m2) contained the lowest wet biomass of the three moles sampled. Buccinum undatum dominated all the sampled stations with mean wet biomass of 11.60gm/m2 for East mole, 10.16gm/m2 for the

West mole, and 13.35gm/m2 for Training mole. This was closely followed by Thais callifera, a carnivorous gastropods having average mean value of 6.86gm/m2 at East moles, 6.11mg/m2 at the

West mole.

A comparative study of the mean dry biomass showed that Training mole had the highest mean value of 35.19mg/m2, closely followed by East mole of mean dry biomass of 32.48mg/m2 and the least value was obtained from the West artificial breakwaters (30.78mg/m2). In terms of dry organic mass, Buccinum undatum, Thais nodosa and Littorina punctata has the highest biomass at the three moles.

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Table 22: Temporal variations in wet biomass (gm/m2) studies of ten species of molluscan fauna from West mole (April, 2008-March, 2010).

TAXA 2008 2009 Mean S.D %Comp. Range

MAY JUN JULY AUG SEP OCT NOV DEC JAN FEB MAR APR

Acmeae saccharina 1.45 1.4 0.6 0.32 1.86 0.34 0.44 1.31 0.86 0.34 0.95 1.56 0.95 0.54 3.14 0.32-1.86

Nerita senegalensis 1.02 1.46 0.65 0.66 0.96 0.58 0.64 0.66 0.46 0.54 0.44 0.36 0.7 0.31 2.31 0.36-1.46

Littorina punctata 1.96 4.02 2.01 4.01 5.06 6.01 3.64 1.42 3.14 2.71 0.94 0.54 2.95 1.67 9.76 0.54-6.01

Patella safiana 2.01 3.24 2.94 3.01 1.04 2.06 3.01 3.71 1.01 0.71 1.41 0.74 2.07 1.07 6.85 0.71-3.24

Buccinum undatum 13.11 15.01 7.01 7.12 9.01 8.94 14.71 13.01 8.6 8.45 9.4 7.6 10.16 2.95 33.6 7.01-15.01

Thais callifera 4.22 5.01 3.04 4.04 3.04 3.74 4.04 12.01 14.05 5.5 6.6 8.05 6.11 3.57 20.21 3.04-14.05

Fissurella coarctata 4.74 3.64 2.86 3.41 1.22 4.41 3.86 1.42 2.24 1.34 1.26 1.45 2.65 1.33 8.77 1.22-4.74

Mytilus edulis 0.64 1.46 0.86 0.76 1.02 0.96 0.88 2.02 1.08 1.04 0.77 0.64 1.01 0.39 3.34 0.64-1.47

Arca senelis 1.22 1.43 1.44 0.86 2.46 2.86 1.74 1.44 2.06 0.76 1.66 1.09 1.59 0.63 5.26 0.76-2.86

Chiton 0.94 1.01 0.94 0.96 2.44 1.84 2.33 4.01 3.04 1.99 3.09 1.86 2.04 0.99 6.75 0.94-3.09

(S.D= Standard Deviation, % Comp.= Percentage Composition)

185

Table: 23 Temporal variations in dry biomass (gm/m2) studies of ten species of molluscan fauna from the West mole (April, 2008- March, 2010).

TAXA 2008 2009 Mean S.D %Comp. Range

MAY JUN JULY AUG SEP OCT NOV DEC JAN FEB MAR APR

Acmeae saccharina 1.26 1.28 0.46 0.31 1.69 0.28 0.34 1.29 0.71 0.28 0.74 1.48 0.84 0.53 2.72 0.28-1.69

Nerita senegalensis 0.98 1.38 0.51 0.59 0.78 0.49 0.53 0.48 0.39 0.41 0.28 0.27 0.59 0.32 1.92 0.27-1.38

Littorina punctata 1.74 3.94 1.96 3.94 4.81 5.69 3.51 4.92 1.31 3.01 2.67 0.67 3.18 1.56 10.33 0.67-5.69

Patella safiana 1.99 3.01 2.71 2.92 1.01 2.02 1.94 3.41 0.91 0.66 1.31 1.54 1.95 0.9 6.34 0.66-2.92

Buccinum undatum 13.01 14.81 6.81 7.01 8.66 8.83 14.61 12.91 8.51 8.31 9.28 7.41 10.01 2.96 9.61 6.81-14.81

Thais callifera 4.08 4.91 3.01 4.01 3.01 3.64 4.01 11.1 13.01 5.41 6.41 7.49 5.84 3.22 18.97 3.01-13.01

Fissurella coarctata 4.54 3.44 2.69 3.2 1.1 4.3 3.74 1.31 3.12 1.29 1.09 1.39 2.6 1.3 8.45 1.10-4.54

Mytilus edulis 0.48 1.28 0.76 0.66 0.86 1.1 1.56 3.21 1.99 1.77 1.78 0.89 1.36 0.76 4.42 0.48-1.99

Arca senelis 2.01 2.94 2.68 1.24 2.54 3.1 2.24 2.61 2.72 2.58 3.98 3.66 2.69 0.72 8.74 1.24-3.66

Chiton 1 1.89 0.59 1.17 0.64 2.82 2.13 3.67 2.73 1.76 0.69 1.54 1.72 0.98 5.59 0.59-3.67

(S.D= Standard Deviation, % Comp.= Percentage Composition)

186

Table: 24 Temporal variations in wet biomass (gm/m2) studies of ten species of molluscan fauna from the Training mole (April, 2008- March, 2010).

TAXA 2008 2009 Mean S.D %Comp. Range

MAY JUN JULY AUG SEP OCT NOV DEC JAN FEB MAR APR

Acmeae saccharina 1.79 2.41 0.91 0.62 1.24 1.44 1.77 2.4 1.2 1.1 1.2 1.36 1.45 0.55 3.42 0.62-2.40

Nerita senegalensis 2.26 3.62 1.74 1.36 1.16 1.24 1.1 1.56 1.24 1.24 0.37 1.46 1.53 0.79 3.61 0.37-3.62

Littorina saxatilis 2.32 4.41 3.15 3.14 5.1 8.71 5.2 6.74 5.2 3.56 4.95 1.2 4.47 2.01 10.55 1.20-6.74

Patella vulgata 3.53 3.12 4.52 3.2 2.15 4.1 4.26 3.34 2.82 1.1 1.96 1.32 2.95 1.12 6.96 1.10-4.52

Buccinum undatum 17.12 19.1 17.6 12.76 18.3 14.14 12.2 10.74 8.2 9.2 10.21 10.36 13.35 3.84 31.51 8.20-19.10

Thais nodosa 5.96 5.76 4.76 4.51 4.2 4.31 4.41 12.6 9.64 9.96 9.39 12.12 7.3 3.21 17.23 4.20-9.96

Fissurella rosea 5.1 3.96 3.1 4.61 4.2 5.51 4.2 2.63 3.41 3.51 2.61 2.2 3.75 1.03 8.85 2.20-5.51

Mytilus spp 2.51 2.6 2.1 2.6 1.71 1.46 1.92 3.56 3.24 3.76 2.98 3.1 2.63 0.73 6.21 1.46-3.76

Arca senelis 2.16 2.08 2.7 1.96 2.99 3.72 2.52 2.96 3.29 2.2 3.74 4.12 2.87 0.73 6.78 1.96-3.74

Chiton 1.41 2.2 1.2 1.46 1.24 3.04 3.04 4.1 2.36 1.52 1.23 1.86 2.06 0.92 4.86 1.20-4.10

(S.D= Standard Deviation, % Comp.= Percentage Composition)

187

Table 25: Temporal variation in dry biomass (gm/m2) studies of ten species of molluscan fauna from the Training mole (April, 2008- March, 2010).

TAXA 2008 2009 Mean S.D %Comp. Range

MAY JUN JULY AUG SEP OCT NOV DEC JAN FEB MAR APR

Acmeae saccharina 1.57 2.1 0.56 0.48 1.46 1.32 1.56 2.41 1.12 1.76 1.25 2.14 1.48 0.59 4.21 0.48-2.41

Nerita senegalensis 2.1 3.1 1.74 1.22 1.14 1.76 1.26 1.82 0.96 0.89 0.97 0.56 1.54 0.67 4.38 0.56-3.10

Littorina punctate 2.31 4.12 3.1 3.2 5.14 7.01 4.96 6.64 4.1 3.31 2.2 1.16 3.94 1.77 11.2 1.16-7.01

Patella safiana 3.46 2.96 4.14 3.1 2.2 3.1 4.15 3.1 2.56 4.2 1.56 1.1 2.97 0.99 8.44 1.10-4.20

Buccinum undatum 11.61 18.1 13.7 9.1 8.8 4.1 12.1 8.9 7.3 9.2 9.3 10.12 11.03 3.05 31.34 7.30-18.10

Thais callifera 5.2 4.1 3.1 4.3 3.08 6.3 4.1 3.3 3.2 2.41 2.36 2.1 3.63 1.24 10.32 2.10-6.30

Fissurella coarctata 4.96 4.2 2.81 3.76 3.1 6.31 4.2 3.79 3.3 3.12 2.39 2.46 3.7 1.12 10.51 2.39-6.31

Mytilus edulis 1.44 2.36 1.58 1.92 1.01 1.41 1.71 3.46 2.01 1.76 2.1 2.22 1.92 0.62 5.46 1.01-3.46

Arca senelis 2.31 3.1 2.96 1.56 2.99 3.38 2.34 2.96 3.1 2.96 3.24 4.12 2.92 0.63 8.3 1.56-4.12

Chiton 1.22 2.1 0.86 1.36 0.94 3.1 2.96 2.51 3.96 2.96 0.92 1.86 2.06 1.03 5.85 0.86-3.96

(S.D= Standard Deviation, % Comp.= Percentage Composition)

188

Table 26: Temporal variation in wet biomass (gm/m2) studies of ten species of molluscan fauna from the East mole (April, 2008-March, 2010).

TAXA 2008 2009 Mean S.D %Comp. Range

MAY JUN JULY AUG SEP OCT NOV DEC JAN FEB MAR APR

Acmeae saccharina 1.66 2.01 0.61 0.46 1.08 1.34 1.62 2.2 0.9 0.74 0.74 1.24 1.21 0.56 3.19 0.46-2.20

Nerita senegalensis 2.04 3.41 1.74 1.22 1.04 1.04 0.86 1.44 0.94 0.76 0.96 0.54 1.33 0.78 3.51 0.54-3.41

Littorina punctata 2.14 4.21 3.04 3.04 4.74 8.01 4.94 6.64 4.74 3.46 1.94 0.88 3.98 2.02 10.5 0.88-8.01

Patella safiana 3.44 3.02 4.14 2.9 2.04 3.18 4.12 3.14 2.64 0.86 1.74 1.22 2.97 0.98 7.84 0.86-4.14

Buccinum undatum 16.4 18.05 14.1 9.01 8.45 14.6 12.6 9.74 7.4 8.9 9.74 10.1 11.6 3.46 30.61 7.40-18.05

Thais callifera 5.88 5.64 4.6 4.41 3.09 4.01 4.12 14.01 7.86 7.88 9.1 12.01 6.86 3.43 18.1 3.09-14.01

Fissurella coarctata 4.94 3.82 2.91 4.41 3.22 5.41 3.86 2.44 3.14 2.46 2.45 1.94 3.42 1.09 9.02 1.94-4.94

Mytilus edulis 1.46 2.4 1.74 2.01 1.22 1.44 1.74 3.42 2.11 1.77 2.08 1.22 1.88 0.61 5 1.22-2.40

Arca senelis 2.33 3.04 2.94 1.64 2.98 3.41 2.41 2.86 3.07 2.04 3.4 3.86 2.83 0.63 7.47 1.64-3.86

Chiton 1.14 2.01 0.86 1.34 0.99 3.04 2.41 3.92 2.04 1.44 0.96 1.74 1.82 0.93 4.8 0.86-3.92

(S.D= Standard Deviation, % Comp.= Percentage Composition)

189

Table 27: Temporal variations in dry biomass (gm/m2) studies of ten species of molluscan fauna from the East mole (April, 2008-March, 2010).

TAXA 2008 2009 Mean S.D %Comp. Range

MAY JUN JULY AUG SEP OCT NOV DEC JAN FEB MAR APR

Acmeae saccharina 1.42 1.94 0.46 0.34 1.04 1.22 1.44 2.01 0.86 0.61 1.14 2.08 1.21 0.59 3.73 0.46-2.08

Nerita senegalensis 2.01 2.99 1.65 1.12 1.01 1.02 1.65 1.26 0.63 0.7 0.86 0.46 1.28 0.71 3.94 0.46-2.99

Littorina punctata 2.11 3.99 3.01 2.99 4.34 7.06 4.81 6.41 3.99 3.22 1.88 0.69 3.72 1.82 11.45 0.69-7.06

Patella safiana 3.26 2.94 4.01 2.69 2.01 3.01 3.99 3.04 2.43 3.71 1.44 1.01 2.8 0.95 8.62 1.01-4.01

Buccinum undatum 16.01 17.4 13.6 8.71 8.31 12.4 12.4 8.6 7.2 8.9 8.76 9.9 10.72 3.32 33 7.20-17.40

Thais callifera 4.82 3.71 2.69 4.21 3.04 5.21 3.69 2.32 3.01 2.21 2.26 1.76 3.24 1.1 9.98 2.21-5.31

Fissurella coarctata 4.71 3.61 2.71 3.76 3.01 5.31 3.74 2.21 3.01 2.28 2.36 1.76 3.2 1.06 9.85 2.21-5.31

Mytilus spp 1.34 2.24 1.51 1.84 1.01 1.28 1.69 3.36 2.01 1.64 1.97 1.01 1.74 0.64 5.36 1.01-3.36

Arca senelis 2.12 3 2.71 1.48 2.77 3.28 2.3 2.74 2.98 2.74 3.1 3.78 2.75 0.59 8.47 1.48-3.78

Chiton 1.01 1.98 0.69 1.28 0.76 2.94 2.24 3.76 2.86 1.87 0.72 1.67 1.82 1 5.6 0.69-3.76

(S.D= Standard Deviation, % Comp.= Percentage Composition)

190

4.7.7 Reproduction in selected intertidal molluscan species.

4.7.7.1 Gonadosomatic Index: Patella safiana

Temporal variations in Gonadosomatic Index for both male and female individuals of prosobranch gastropods limpet species of Patella safiana are shown in (Figure 77). The index is based upon experimental molluscan species with shell length >22mm. The total numbers of males and females used in the calculation were 60 and 68, respectively. Both males and females showed a similar gonadal cycle. In 2008, all individuals of Patella safiana were sexually matured and remained so until the index diminished sharply between October 2008 and November 2008. It was noticeable that the population of Patella safiana showed a particular long, post-spawning, resting period, which lasted for about four month from

January, 2009 to April, 2009. The result of the t – test showed that no significant difference in

Gonadosomatic Index between sex (t 0.05, 6 = 2.45; p>0.05), compared to the significant differences in Gonadosomatic Index between months (ANOVA: p<0.05)

Figure 77: Monthly variation in GSI values for male and female Patella safiana

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4.7.7.2 Determination of Sex Ratio in Population of Patella safiana .

A total of 128 individuals of Patella safiana were examined, comprising 60 males and 68

females. Of these, 70 where males and 76 were females, no undetermined were found, this

1:1.13 ratio of males and females is not significantly different from 1:1 (t0.05, 20=2.086; p >

0.05). The proportions of males and females of limpet in the monthly samples from the West

mole are shown in Table 28.

Table 28: The estimated proportion of male and female Patella safiana in monthly samples from the West mole investigated from May, 2008 – May, 2009.

Total Number of INCIDENCE AND PERCENTAGE

Year /Month Individual MALE FEMALE

2008 May 13 4 (30.8%) 9 (69.2 %)

Jun 16 9 (56.3%) 7 (43.7%)

Jul 6 4 (66.7%) 2 (33.3%)

Aug 7 2 (28.6%) 5 (71.4%)

Sep 10 7(70.0%) 3 (30.0%)

Oct 5 1 (5.0%) 4 (80.0%)

Nov 5 4 (80.0%) 1 (20.0%)

Dec 13 2 (15.0%) 8 (61.5%)

2009 Jan 12 6 (50.0%) 6 (50.0%)

Feb 12 4 (33.3%) 5 (41.7%)

Mar 8 3 (37.5%) 5 (62.5%)

Apr 17 9 (52.9%) 8 (47.1%)

May 10 5 (50.0%) 5 (50.1%)

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4.7.7.3 Reproductive Effort (RE): Patella safiana

The reproductive efforts the of male and female of Patella safiana in monthly samples from the West mole is shown in (Table 29). Males of Patella safiana demonstrated greater mean monthly reproductive efforts for most months of the year and a greater annual reproductive effort (0.7048) than female (0.5360). It can be concluded that the life history of Patella safiana is characterized by slow growth, a long life span and a single spawning activity each year. Maturation of the gonads begins in June; the long maturation period suggests that there is regular recruitment of juveniles into adult population, as also suggested by the data presented for this species.

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Table: 29 Monthly reproductive effort of Patella safiana.

MEAN REPRODUCTIVE EFFORT (Patella safiana)

MALE FEMALE

Month Year Wet Weight Range Wet Weight Range (gm) (gm)

May 2008 0.1482 0.1031-0.1907 0.2360 0.0458-0.2958

June 2008 0.1432 0.0934-0.1891 0.1994 0.0967-0.2979

July 2008 0.1980 0.1189-0.3646 0.1979 0.1278-0.2645

Aug 2008 0.2618 0.1974-0.3361 0.2708 0.2323-0.3287

Sep 2008 0.4856 0.3236-0.7018 0.4263 0.2984-0.5136

Oct 2008 0.4332 0.3674-0.4825 0.3897 0.3010-0.5432

Nov 2008 0.5387 0.4907-0.5804 0.4196 0.3546-0.4656

Dec 2008 0.4478 0.3523-0.5986 0.4064 0.2378-0.4982

Jan 2009 0.3510 0.1274-0.5986 0.2549 0.1343-0.3890

2009 0.1148 0.0487-0.2468 0.2457 0.0548-0.2017

Mar 2009 0.0797 0.0673-0.0840 0.1094 0.0861-0.1581

Apr 2009 0.0876 0.0350-0.1143 0.1218 0.0954-0.1452

Mean Annual Reproductive effort; Male = 3.2436; Female= 3.0190

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4.7.7.4 Gonadosomatic Index: Nerita senegalensis.

Variations in the Gonadosomatic index for both male and female individuals of Nerita senegalensis are shown in (Figure: 78). The total number of males and females sampled were

70 and 76 respectively. Both males and females showed a similar gonadal cycle. A major peak in GSI occurred between August and May (spawning took place in April). After spawning, the gonads do not regress completely, and redevelopment begins shortly thereafter.

Mature individuals could thus be found throughout the year. By August 2008, the GSI started to rise again. The population of Nerita senegalensis showed a particularly high GSI value of

10% for most months of the year for both males and females. Maximum values of 34.98% for males and 29.45% for females occurred in February. From November, 2008 to April, 2009

GSI values were >20% for both males and females. The results of the t- test showed that there was no significant difference between males and females ( t 0.05, 18=2.10; P > 0.05) but there was significant difference between months ( ANOVA; p<0.05).

Similarly, GSI values for August 2008, May, June, July and August, 2009 were grouped together with no significant difference between them. There was, however, a significant difference between the two groups of months.

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Figure 78: Monthly variation in GSI values for Male and Female Nerita senegalensis.

4.7.7.5 Sex Ratio: Nerita senegalensis

A total of 146 individuals of Nerita senegalensis were examined for stages of reproductive development. Of these, 70 where males and 76 were females, no undetermined were found.

Thus 1:1.09 ratio of male to female is not significantly differently from 1:1 (t 0.05, 38 =2.02, p

> 0.05). The proportions of males and females of Nerita senegalensis in the monthly samples obtained from the West mole are shown in (Table 30).

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Table 30: The estimated proportion of males and females (Nerita senegalensis) in

monthly samples from the West mole (May, 2008 – May, 2009).

Total Number of INCIDENCE AND PERCENTAGE

Year /Month Individual MALE FEMALE

2008 May 15 4 (26.7%) 11 (73.3%)

Jun 11 7 (63.6%) 4 (36.4%)

Jul 20 9 (45.0%) 11 (55.0%)

Aug 7 2 (28.6%) 5 (71.4%)

Sep 12 5 (41.7%) 7 (58.3%)

Oct 11 5 (45.5%) 6 (54.5%)

Nov 7 4 (57.1%) 3 (42.9%)

Dec 15 7 (46.7%) 8 (33.3%)

2009 Jan 15 8 (53.3%) 7 (46.7%)

Feb 6 3 (50.0%) 3 (50.0%)

Mar 8 5 (62.5%) 3 (37.5%)

Apr 6 3 (50.0%) 3 (50.0%)

May 13 8 (61.5%) 5 (38.5%)

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4.7.7.6 Reproductive Effort (RE): Nerita senegalensis

The reproductive effort of males and females of Nerita senegalensis in monthly samples is shown in (Table 31). Male species of Nerita senegalensis had a greater mean annual reproductive effort (3.2436) than female (3.0190). The proportions of males and females in the population relative to shell length are shown in (Tables: 30 and 31). In Nerita senegalensis the sexes are uniformly distributed throughout all size groups, suggesting an absence of sex reversal in Nerita senegalensis.. The major peak of spawning occurred between April and May, although it is possible that subsidiary spawnings take place at other times of the year.

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Table 31: Mean Reproductive Effort (RE) for Male and Female Nerita

senegalensis from the West of Tarkwa Bay.

MEAN REPRODUCTIVE EFFORT (Nerita spp)

MALE FEMALE

Month Year Wet Weight Range Wet Weight Range (gm) (gm)

May 2008 0.0405 0.0040-0.0493 0.0493 0.010-0.7110

June 2008 0.3401 0.0223-0.460 0.2024 0.1240-0.3240

July 2008 0.2101 0.1431-0.2280 0.2781 0.1421-0.2740

Aug 2008 0.1773 0.1192-0.2346 0.0860 0.2491-0.1590

Sep 2008 0.0074 0.1044-0.0133 0.0118 0.0074-0.0154

Oct 2008 0.0065 0.0193-0.0293 0.0122 0.0072-0.0159

Nov 2008 0.0086 0.0052-0.1250 0.0069 0.0069-0.0070

Dec 2008 0.0093 0.0071-0.0085 0.0043 0.0021-0.0081

Jan 2009 0.0053 0.0041-0.0071 0.0051 0.0042-0.0054

Feb 2009 0.0057 0.0029-0.0082 0.0047 0.0041-0.0072

Mar 2009 0.0168 0.0037-0.0526 0.0056 0.0043-0.0059

Apr 2009 0.0117 0.0028-0.0283 0.0116 0.0041-0.0432

May 2009 0.0381 0.0162-0.0815 0.0451 0.0202-0.0952

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4.7.7.7 Size at sexual Maturiy.

The size at sexual maturity for both intertidal prosobranch gastropods (Patella safiana and

Nerita senegalensis) investigated from monthly sample pool were estimated to be in the ranges of 12mm- 14mm and 8mm-10mm respectively. Macroscopic sexing of experimental molluscs were possible as the mature testis is milky-white in colour while mature ovaries are orange. In most marine molluscs, there are no sexual dimorphisms to ascertain male from female species (Gray, 1996).

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CHAPTER FIVE

5.0 DISCUSSIONS

In this study, the air, sea surface water and rock temperature at the three moles are basically warm with the temperature generally greater than 26oC throughout the study period. The air and sea water temperatures showed the patterns of natural climate regime and that of the solar heights. These variations in air, seawater and rock temperatures are as a result of the overall cooling effect of the Eastern Atlantic and the Gulf of Guinea during rainy season (Longhurst,

1964; Awosika, 2001; Riebesell, 2008; Edokpayi and Eruteya, 2012). The temperature of coastal waters of Tarkwa Bay is similar to that of West Africa climate regime as reported by

(Oyewo et al., 1982). The seasonal variations in Tarkwa Bay Beach temperature depends on the surface heat exchange, wind stress, local and regional air-sea interactions, convective heating over the land of West Africa and inflow of Atlantic waters and the low level of freshwater input during dry season and this report complements the study of (Longhurst,

1964).

The temperature variations amongst the air, seawater and rock also depend on their respective specific heat capacities: air (1000J/kg/k), water (4200J/kg/k) and rock surface (300J/kg/k), this support the work of (Denny, 1993). Materials with low specific heat capacities change temperature with little energy input. As a result, rocks are heated to temperature greater than air; and air is heated to temperature greater than water by solar irradiation. The intertidal organisms can buffer this stress with large mass, low surface area to mass ratio, reflective coloration, behavioural avoidance or multi-layered aggregation (Underwood 1997).

Rainfall is the most important cyclic phenomenon in tropical countries as it brings important changes in the hydrographical characteristics of the marine and coastal waters (Lewis, 1964).

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In this present study, Tarkwa Bay coast experiences a tropical climate consisting of rainy season (April to October) and dry season (November to March). The peak values of rainfall were recorded during the months of June 2008 and July, 2009. Rainfall in Tarkwa Bay coast is largely influenced by Southwest trade wind as reported by early worker (Awosika, 2001).

Molluscan species density on the shores of the three moles of Tarkwa Bay fluctuated temporally from high to low value in rainy season. This decreasing trend in seasonality was in association with the disturbance and stress experienced by molluscan communities during the rainy season (April- October).This present study showed that the molluscan diversity value not only varied seasonally among the three moles, but also varied significantly among the twelve geo-referenced study stations. This report is thus, in accordance with the observations of Littler (1980). The three moles showed a reduction in molluscan composition, abundance, diversity in ascending order: Training< East< West in rainy season, conversely, a reciprocal relation was however, observed in the dry seasons: West > East > Training. The molluscs‟ communities suffer osmotic stress during the rainy season months because some are stenohaline with limited tolerance for osmotics stress caused by refreshening actions of rainfall on saline water of Tarkwa Bay. Similar findings have been reported by (Underwood,

1997; Awosika, 2001; Edokpayi and Eruteya, 2012).

The Sea Surface Salinity of the three moles of Tarkwa Bay, are typical oceanic surface waters of Gulf of Guinea with salinity of about (33.8‰) in dry season. The salinity distribution of

Tarkwa Bay coastal waters is mainly governed by factors such as: thermohaline, coastal circulations, influx of fresh water through rivers, rainfall and evaporation. The basic sea surface salinity which follow the pattern of rainfall regimes in the study area, and this meets the findings of the previous studies (Oyewo et al., 1982; Edokpayi et al., 2010).

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The ecological implications of the temporal variations in salinity are that intertidal organisms are divided into two ecological groups such as stenohaline and euryhaline groups based on the previous reports by (Oyewo et al., 1982; Awosika, 2001; Chukwu and Nwankwo, 2004).

It is possible now to use the dataset in this current report to assess changes due to natural sources (geological sequestrations) and salinity variation mediated by anthropogenic inputs.

However, the mean salinity concentrations recorded among the three moles of Tarkwa Bay exhibited the following descending order: the West > East > Training moles. Similar observations have been given by (Littler, 1980; Stanford, 2002; Britton, 2005).

The pH of water is an important indicator of the chemical conditions of any aquatic environment. The pH of this present study fall within narrow limit (7.06 – 8.50), consequently, the pH did not show any significant variations during the study period. This may be due to extensive buffering capacity of the seawater that maintains the pH within narrow limit in this present study. The processes of primary production, respiration and mineralization of organic matter may alter the pH of coastal waters because these biotic and ecological processes can cause significant changes in oxygen and carbon dioxide concentrations of Tarkwa Bay waters. The result of this present study confirms the researches carried out on other tropical bay in other parts of the world (Oyewo et al., 1982; Ajao, 1989;

Wood, 2001; Britton, 2005).

The variations in the dissolved oxygen content of Tarkwa Bay coastal waters may suggest photosynthetic production of oxygen by aquatic algae, while under saturation indicates its biological utilization for respiration by aquatic fauna and chemical utilization for oxidation processes. Two processes essentially regulate the dissolved oxygen distribution in the sea: physical process, such as exchange across the air-sea water interface, surface water circulation, vertical and horizontal diffusion; freshwater influx and secondly biochemical

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processes, such as photosynthetic productivity and oxidation of organic matter. In the coastal waters of Tarkwa Bay, circulation, upwelling processes, productivity and coastal input of organic matter chiefly regulate the dissolved oxygen distribution.

Generally, dissolved oxygen (DO) increases with the incursion of tidal waters and attains maximum around high tide which later decreased during low tide. Lower values at the

Training mole indicate the level of pollution. At the west mole where tidal flushing is appreciable during high tide, complete ventilations occur at the shore. The Training mole often results in steep (DO) gradient because the oxygen is consumed more by the aquatic animals and oxygen-consuming wastes. Diurnal variations in the dissolved oxygen profiles generally show insignificant variation except during the rainy season and showed marginal decrease in the dry season. This study complements the reports of (Edokpayi and Eruteya,

2012) on the assessment of physico-chemical parameters of Tarkwa Bay coastal waters.

Temporal changes in the mean value of the BOD5 was an indication of the discharged of untreated large volumes of organic wastes that may have their origins from animals and human sources. High values recorded in the Training mole during the dry season could be attributed to allochthanous and extraneous inputs from land-run-off, animal manure from feedlots, dead plants, animals, and ballast water discharge in coastal waters from Trans- oceanic tankers that berth at Lagos harbour. However, it is also possible that restricted circulations in backwaters of the Training mole may also affect the level of DO in seawaters.

Implications of high BOD5 are the same as impacts of low dissolved oxygen; aquatic organisms become stressed, suffocated in anoxic and hypoxia environments as reported in the study by Islam and Tanaka (2004). Dissolved oxygen level is an index for measuring the health-status of any aquatic ecosystem; and the water quality of the study moles are in descending order of West > East > Training moles. At high BOD5 values, low Dissolved

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Oxygen (DO) was recorded, oxygen was used up for the decomposition of organic wastes in the seawater.This current study supports the work of (Edokpayi et al., 2010).

This is an anthropogenically mediated waste from land-based sources such as: pesticides, sewage, household detergent and chemical fertilizers. These chemical wastes are unregulatedly discharged into adjacent coastal waters of Tarkwa Bay during high and low tidal cycles. The low values of COD in some stations were indications of the absence of chemical pollutions in those areas. The waste assimilative capacities of the three moles followed the same trends described by (Ademoroti, 1996). The assessment of the impact of chemical wastewater on the marine environment become easier and reliable, if baseline water quality is known on the marine environment against which the existing conditions can be compared as previously reported by (Ajao, 1994; Ibe, 2005; Edokpayi and Eruteya, 2012).

Conductivity depends largely on the level of dissolved salts in the seawater column. It also depends on the salt contents of the water that varies with seasons. High levels of conductivity were recorded in the dry season in the study area, because of evaporation, and irradiant heat, and this current study supports the previous reports of (Murray, et al., 2006; Edokpayi et al.,

2010). The lowest mean value was recorded during the rainy season because of precipitation, dilution, and riverine inflow. The high suspended ionic salt load in seawater column was associated with the prevailing physical oceanographic conditions of the oceanic water and climate which seems to control the quantum of suspended solid by activation and resuspension and settling cycles in Tarkwa Bay (Ibe, 2005; Edokpayi and Eruteya, 2012).

The negative correlation between nitrate and salinity may be as a result of riverine inflow during the rainy seasons. The highest values were recorded in the West and the Training moles in (April, 2008 and May, 2008) respectively. This may be as a result of localized pollution and persistent discharged of untreated human wastes from informal settlement 205

along the shorelines of the the three moles and sampling stations. The distribution of Nitrate-

Nitrogen (NO3-N) fractions in coastal waters of Tarkwa Bay followed seasonal patterns as described in (Mance, 1987; Nair, et al., 1993; Islam and Tanaka, 2004).

The phosphate content in three moles is influenced by the dynamics of biological activities under natural condition (Barth, 1987; Edokpayi et al, 2010). Phytoplankton blooms normally satisfy their requirement of phosphorus by direct assimilation of organic phosphorus (Seben,

1986; Nambisan et al., 1987). The source of inorganic phosphate as well as organic phosphorus in the three moles was mainly from the sea. Regeneration from the sediments was found to be a major source during the rainy season. Temporal variations in the integrated mean concentration of phosphate, and the peak-value was recorded in the rainy season.

Rainfall was reported to be used as vector for transport of nutrients from continetal land mass into coastal waters (Koranteng, 1998) An inverse relation was reported between the rainy and dry seasons. This report validates the studies of (Ajao, 1994; Ukwe et al., 2003; Ibe, 2005;

Edokpayi and Eruteya, 2010).

Such an inverse relationship has been reported in the coastal waters of the Western English

Channel (Butler et al., 1996). The peak value observed at the East mole was as a result of geological sequestration and localized resuspension from intermittent aggregate dredging of the East mole of Tarkwa Bay for easy navigation of commercial ship into the Lagos harbour based on the previous report of (Awosika, 1990).

Sulphates form an important parameter of phytoplankton distribution and abound in the

Tarkwa Bay coastal waters as reported in the previous studies (Onyema, et al., 2009;

Edokpayi, et al., 2012). The highest and the lowest sulphate concentrations were recorded in the West mole in June, 2009 and the Training mole in January, 2009, and 2010 respectively.

The spatio-temporal variations of sulphate in coastal waters of Tarkwa Bay according to 206

study conducted by (Bultler, et al., 1996) is influenced by several factors, the important being the proportional physical mixing of seawater with freshwater and the adsorption of reactive

2= sulphate anions (SO4 ) into suspended sedimentary particles. Chemical reaction with clay mineral and biological removal by phytoplankton occurs especially with diatoms and flagellates (Lewis, 1964).

The physical environment of rock pools is largely determined by the number of times they are inundated by the tidal regimes. The rockpools at the upper shore experience wider and more prolonged fluctuations in physico-chemical parameters such as: salinity, temperature, pH and oxygen content than those of the lower shore. The organisms at the upper shore rock pool will experience the highest thermal stress as compared to rock pool at the sub littoral shores in the order of tide pool height (+3m) > (+ 2.6m) > (2.2m) above chart datum. The organisms living at such rock pool (+ 3m) are able to evade some of the physical stresses associated with life on the seashore such as desiccation, wind-stress and irradiant heat, but in so doing also encounter additional variables such as pH fluctuations and oxygen depletion which are set up by the relative abundance of animals and plants in the pools as reported by

(Denny, 1985 and 1988).

Salinity and temperature are also affected by evaporation and precipitation, which may result in the pronounced stratifications of the pools. The extrinsic factors such as temperature and salinity exhibit diurnal cycle of fluctuations whose magnitudes are depended upon the tidal level of the pool and the season of the year. This report complements the works on intertidal rocky shores along the Gulf Guinea coast (Mensah, et. al, 1988; Ukwe, et al., 2003; Edokpayi et al, 2010). These factors depend vividly upon the height of the rock pool on the shore, time of the day and seasons. On the lower shore, therefore, where frequent tidal inundation result

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in the low salinity and temperature mean values; the rock pool environment is one which allows typical marine organisms to extend their range upwards into intertidal zones.

There are severe remarkable abiotic conditions which occur in upper shore rock pools result in the occurrence of an increasingly specialized assemblage of organisms. This study confirmed the report of (Lewis, 1964) on the English rocky coast.

The principal environmental features of the intertidal zone are its regular exposure to atmospheric conditions. Its temperature regimes are thus much more complex than those of sub-tidal zones. Some site-specific factors, such as shadings, and cloud covers mask the effect of heat stress to an organism (Patella safiana), whereas others factors, such as evaporation, affect heat efflux from intertidal animals (Denny, 1993). The major source of heat stress in the intertidal zone during low tide is direct solar radiation. Most factors that affect the temperature of exposed rock surface also affect the intertidal molluscs. Molluscs are known to exchange heat with the substratum (Lewis, 1964; Bamabe, 1990). Changes in rock surface temperatures are more drastic during the day and in dry season; because the ultimate source of heat is the solar energy. However, air temperature may be warmer at mid- day and later cool at night. Atmospheric variability also subjects intertidal molluscs on open rock surfaces and in tide pools to frequent salinity and temperature fluctuations. High intertidal pools which are inundated infrequently or receive seawater only from wave splash may become very brackish in rainy season or strongly hyper-saline in hot, dry weather.

The molluscs´ composition abundance, density and distributions at the upper, mid and lower littoral zones of the three shores; were governed by temporal variations in environmental factors. The number of molluscan species found in the upper, mid and lower level definitely contributed to the observed differences among the three moles (West, Training and East). In general, the upper level had a lower diversity and higher dominance of molluscan species 208

distributions. It was also confirmed in this study that the highest species contributing to the dissimilarity among the three zones on the shores are Tectarius granosus Philippi, Littorina cingulifera Dunker, Siphonaria pectinaria, Littorina punctata Gmelin, Nerita senegalensis,

Patella safiana, Littorina saxatilis and Neritina were abundant in the upper-mid-shore levels in the West, Training and East moles respectively, while Fissurella coarctata,

Buccinum undatum, Thais haemastoma, Patella vulgata, Gibbulla, Thais callifera, Thais nodosa, Murex varius, Mytilus spp. and algal species were numerically abundance at the lower shores in three moles of Tarkwa Bay. These results of this study support the vertical distribution patterns described by (Lewis, 1964; Raffaelli, 1976; Rose, 2003; Edokpayi, et al.,

2010). The observed differences among three zones on the shores of Tarkwa Bay, probably related to the effects of substrate heterogeneity, temperature, salinity, rainfall, predation, gradient of food availability coupled with the disturbances associated with boulders which

Sousa (1979) confirms. The abundance of Thais haemastoma on the three shores of Tarkwa

Bay is closely related to the existence of mussel beds on which they feed upon sub-tidally.

Mussel populations also provide shelter for variety of Thais species. In contrast, the

Pulmonate limpet, Siphonaria pectinata decreases in abundance from the West, Training and

East moles.

The Shannon Index fluctuates temporally, throughout the study period. This decreasing trends was, however, associated with disturbance and stress experienced by intertidal molluscan communities during the rainy season (May – August) which probably exceeded an optimal intermediate level of disturbance. Conversely, the intertidal molluscan and algal communities proliferate in dry season months on the three moles of Tarkwa Bay (October,

November, December, January and February). Heavy rainfall, storm surge and estuarization

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processes are the factors that frequently cause defaunation in intertidal shores and coastal marine ecosystems globally, as reported by (Rose, 2003; Edokpayi and Eruteya, 2012).

The present study showed that Shannon Index (Hʹ) values not only varied temporally but also varied from station to station and from shore to shore, in accordance with the study conducted by( Littler 1980) on Californian Rocky Shores.

The evenness or equitability results were in contrast with those of the richness on the three moles of Tarkwa Bay. The Pielou‟s Evenness (J‟) showed seasonal trends at the 3 moles of

Tarkwa Bay. The similar trends from the obtained results may be because of nearness of the three moles to the Atlantic Ocean and they have slight variations in species richness, similar community structures and compositions. Finally the three shores were not heavily polluted.

The values of Simpson‟s Index range from zero to 1 (unity) and are inversely proportional to the species richness (as the Dominance Index, increases, diversity decreases). The reciprocal form of Simpson‟s Index ensures that the value of the Index increases with diversity. The diversity values were significantly different among the three tidal zones on the shores. The present investigation showed that the richness was inversely proportional to the tidal height i.e richness is highest in low tidal zones and decreases on the West, Training and East moles of Tarkwa Bay. The reason for this trend is that environmental stresses are less severe at low tidal levels; these trends are similar to the studies carried out on the California Beach by

(Underwood, 2000).

The analysis of regression co-efficient for various relationships of Buccinium undatum, Thais califera and Nerita senegalensis showed that growth rates of these variables are seasonally controlled. The results of the present study showed that the relationship between shell length(SL)-shell height(SH), shell height(SH) shell width(SW);shell height(SH) dry weight

(DW), shell length (SH) ash-free-dry weight (AFDW) of these study species are linearly 210

correlated. Results of allometric relationships for molluscan species studies by other authors are also linearly correlated and are generally in agreement with the results of the present study (Paine, 1964; Underwood, 2000). AFDW measuremen require the destruction of the experimental molluscan species which is not a suitable methodology for long time monitoring programmes for intertidal molluscan ecological studies. In these studies, a non-destructive measure of growth, such as shell length, shell height and shell width have been recommended as suitable substitutes for ash- free dry weight for maintaining dynamic population of these commercial species of interest in the wild; and can also be utilised for fishery data collection of molluscan species, along with the conventional assessment of shell length growth.

A comparative study of heavy metals in seawater, seaweeds and Patella safiana: Prosobranch gastropod showed a significant difference among the results obtained for different species, stations and seasons. Concentrations of heavy metals in soft-body parts of marine molluscs are primarily influenced, in general by the heavy metal concentrations in seawater, and also by extrinsic and intrinsic factors such as water temperature, salinity, size or weight, age, stage of the reproductive cycle. Temporal variations in level of heavy metal concentrations in the

Tarkwa Bay coastal waters depend on gamentogenesis and changes in availability of food.

This similar report has also been observed in studies by Bryan (1984) and Mance (1987).

Spawning events in intertidal molluscs involve substantial changes in body weight. If the gametes are relatively poor in metals, spawning is associated with an increase in tissue metal concentration based on previous reports documented by (Bryan, 1984).

The results from these reports showed that algae acted as good indicator of Cr, Cu, Fe, and

Mn. Mercury and Nickel were however, found in low concentrations in algae in this present study. The order of the three moles, metal pollution includes: West < East < Training moles.

The data presented here were compared with International guidelines recommended by The

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Food and Safety Regulations (1992) and the defunct FEPA (1992) for heavy metals in shellfish. From the public health point of view, the levels of metal concentrations found in this study, are generally lower when compared to the permitted levels and those of the previous studies at the Lagos harbour and the Lagos lagoon. However, the protection of the

Tarkwa Bay coastal waters from damage due to heavy metals and other chemical pollutants requires an understanding of the sensitivity of aquatic organisms to these substances and their ecological requirements, and it is hoped that the intertidal molluscs Patella safiana will continue to be employed routinely as geochemical marker, for the monitoring programmes for metal pollution in the Tarkwa Bay coast.

It is generally agreed that heavy metal uptake occurs mainly from water, food and sediment

(Crain, et al., 2008). However, effectiveness of metal uptake from these sources may differ in relation to ecological needs and metabolism of the animals and concentrations of the heavy metals in water, food and sediment as well as some other factors such as salinity, temperature, any other interacting agents as documented by (Robinson, 1994). In this study, salinity changes with season, and this caused the salinity level in the Tarkwa coastal waters to fluctuate accordingly, and results in differential rates of heavy metal uptake by biota due to their physiological changes in the linkage of ion fluxes occurring in the body surface of the organisms. The maximum concentration was recorded in the molluscan body tissues and minimum concentration was recorded in molluscan shell. The order of concentration levels of heavy metals in molluscan body parts was observed as: Mn > Fe > Zn > Cu > Cr > Pb. The order of heavy metal concentrations in molluscan body parts include: Body tissue > foot > mantle > shell. Accumulations of such sublethal amount of heavy metals cause toxic reactions along the intertidal food chains.

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The diet of prosobranch intertidal molluscs according to Branch (1981) largely comprises microalgae, macroalgae, encrusting algae and young stages on the rock surface. The consumption rates of littoral molluscan species depend on the duration of available feeding time at a particular height on the shore. Intertidal molluscs are covered for short periods of time at higher levels than those at lower levels. It might be expected therefore, that high shore animals may show some compensation in their rate of feeding to offset the reduced period of immersion at higher levels.

Adaptations of molluscs to feeding at different shore zones in this study showed that high zone molluscs responded more quickly to wetting and secondly that their feeding rate was initially higher than that of lower zone molluscs in respond to wetting and this may play an important role in extending the available feeding period of intertidal animals. This study supplements the reports of (Chapman, 2000; Wood, 2001; Thompson et al, 2002). The effects of limpets on algal communities are varied and complex. This is partly attributable to their feeding mechanisms rather than how much they eat. This experiment was used to estimate food intake under natural conditions to assess the effects of their grazing on intertidal rocky shore and algal community structure. Noel et al (2009) demonstrated this result in similar studies and confirmed a linear relationship between the area grazed and the density of Patella safiana. The knowledge gained from this study can be utilized to formulate algal feeding model for shellfish domestication captive breeding and aquaculture programmes for commercial molluscs. Documented report can also be used to rations algal nutrition to domesticated species and large scale hatchery programmes in the coastal communities in

Nigeria.

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Mollusc‟s competition on the intertidal rocky shore can be complex and often set lower limits of algal communities on the shore. The result of competition often is the elimination of the inferior competitor rather than co-existence. Norton (1991) in a similar study reported that the loser is kept below its compensation point until it enters an irreversible physiological decline or deprived of growth (Carpental 1990), and other studies have also shown that many herbivores do not feed indiscriminately, but consume some algae in preference to others, and such selective removal may determine which species remain to dominate the habitat. A similar scenario is observed in studies by Norton (1991). In this study, Patella safiana cohort growth rate was higher as compared to when the mixed population of Patella spp and Nerita senegalensis were artificially grown together. The differential growth rate between the inter- specific populations was as a result of competition on the algal food resources. This present study will be used as a model for the co-existence of mesograzer species on the shore of

Tarkwa bay. Shellfish growers in coastal communities in Nigeria can also use this model for mixed culture of these species in aqua-culture practices.

Spatial and temporal variations in reproductive parameters occur in both Patella safiana and

Nerita senegalensis. Information about reproductive characteristics is essential both for management of wild stocks and for the development of breeding and hatchery programs for sustainable aquaculture industry. Differences in timing of gametogenesis and response to extrinsic factors revealed dissimilar patterns suggesting variance in reproductive behaviours between Patella safiana and Nerita senegalensis of intertidal rocky shores of Tarkwa Bay.

Patella safiana is a dry season breeder; Nerita senegalensis is a rainy season breeder. The seasonality in Tarkwa Bay rocky coast limits the spawning periods of both species.

Subsidiary spawning in Nerita senegalensis may however, take place at any time between

September and June. The length of the resting phase, and the proportion of individual resting

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at any one time, may be related to local temperature. Spawning periodicity may also appear to be correlated with rough seas and on-shore winds.The spawning stimulus for littoral molluscs has been described according to change in temperature and wave action (Picken and

Allan, 1983). For population of Patella safiana occurring on Tarkwa Bay littoral shores, similar studies on the reproductive cycles of marine molluscs have shown that time for peak maturation, spawning and resting stages can differ markedly in successive years (Dunmore,

2000). The present work shows that Patella safiana has one, clearly defined, annual peak in spawning activity and that a large proportion of the gonad is subsequently spawned out.

Nerita senegalensis has asychronous spawning event; large proportion of gonads are spawned out. There could be occurrence of minor multiple additional spawning periodicities.

The temporal variations in spawning events varied slightly between study mollusc species, males and females, among months and within year in timing and magnitude. These variations may be due to food supply, genetics and environmental factors. These observations are similar to studies carried out by (Parry, 1982; Creese and Ballantine, 1983; Fletchers 1987).

The reproductive effort of individual mollusc within a population was shown to be independent of age as reported by (Huang and Chan, 2000). Energy allocated to reproduction reduces the amount of energy (potentially) available for maintenance and somatic growth and usually, therefore result in an increase in adult mortality rates as reported by (Branch, 1981).

Energy allocated to reproduction will reduce the amount of energy available for somatic growth, accounting for the small size of Nerita senegalensis as documented by Picken

(1980). Reproductive effort has been determined in limpets using the ratio of gonads to body weight by (Branch, 1981). In this study a slight female bias (1:1.3) has been demonstrated for Patella safiana but the ratio is not significantly different from 1:1. Nerita senegalensis has a slightly male biased sex ratio overall (1:1.01), but is male biased as a juvenile (<8mm in

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shell length), (1:1.29). Again, the ratio is not significantly differently different from 1:1 ratio.

Among individuals >7.5mm in shell length, however, females predominate (1:1.09), but the sex ratio does not vary significantly from 1:1. First sexual maturity in both patella safiana and Nerita senegalensis of three moles of Tarkwa Bay occurred at a length between 12mm-

14mm and 8mm-10mm respectively.The age at which marine invertebrates reach sexual may be influenced by a number of factors. Sexual maturities of the intertidal molluscs are strongly influenced by food availability which in turn is related to localised temperature regimes

(Branch, 1981; Fletcher, 1987; Sato, 1999). Due to the nearness of the biogeographical differences among the three study localities (West, Training and the East moles), similar relationship has been described by (Sato, 1999) could be expected between population patella safiana and Nerita senegalensis of Tarkwa Bay coast. It has also be reported by (Gray, 1996;

Foster; 1997) that the sexual maturity is firmly genetically entrenched in these herbivorous species (Gray, 1996). This study can be used in fisheries management to determine the on-set of sexual maturity in marine molluscs as reported by (Fletcher, 1987; Sato, 1999;

Underwood, 2000).

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6.0 SUMMARY AND CONCLUSION

6.1 Summary of Research Findings

1. The physicochemical characteristics of the three moles of Tarkwa Bay fluctuate with

the cycles of rainy and dry seasons.

2 The molluscan communities of the study area were found to be heterogeneously

distributed both horizontally and vertically. The molluscan abundance decreases as

the tidal height increases on the shores of the three moles of the Tarkwa Bay.

3. The mean consumption rates for juvenile species of molluscs were found to be higher

as compared to adults of the same species. The inter-specific competition reduces

growth rate in experimental molluscan species.

4. The algal food preference for the herbivorous molluscan grazers was found in the

following order: Green algae >Red algae >Brown algae> Detritus. This feeding

preference was seasonally dependent.

5. Heavy metal concentration gradients increases in the order: seawaters < seaweeds <

Patella safiana.

6. Study species showed variations in the patterns of reproduction; Patella safiana

spawns in dry seasons, while Nerita senegalensis spawns in rainy season.

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6.2 Recommendations:

The project has the following recommendations:

1. Enactment / enforcement of laws and regulations that will enhance the sustainable

management of the molluscan communities of the three moles of Tarkwa Bay.

2. Identify means of reducing pollution loads from industries, agriculture, domestic and

other sources around the Tarkwa Bay waters.

3. Research into the methods for harvesting and preserving ephemeral green algal food

species to ensure the availability of molluscan feeds at all seasons.

4. Establish a Regional Geographical Information System (GIS) that would be used to input

and analyze data with a view for the establishment of Marine Protected Area (MPA) and

Shoreline Sensitive Index (SSI) in future.

5. The acquisition of the state-of-the–art-technology for efficient harvesting and

transplanting of juvenile molluscs from hotspots region of the artificial shore to

defaunated region of the shore.

6. Development of research agenda for the coastal waters of Tarkwa Bay: Ocean

Acidification; Sea Level and Sea Temperature; Diseases and Invasive species; Algal

blooms and plankton; and molluscan community dynamics.

7. Mangrove conservation research programmes should be encouraged to mitigate

climate change impacts on the molluscan communities of the three moles of Tarkwa

Bay.

8. Taxonomic studies of the molluscan communities of the three moles are urgently needed

to enhance future research activities and conservation programmes.

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9. Database on the mollucsan shellfish communities of the three moles of Tarkwa Bay in

terms of scientific information on their distribution, exploitation, production and stock

assessment that should be stored in Geographical Information System (GIS).

10. This project recommends the introduction of hatchery programmes in aquaculture

activities for mass production of molluscs that would meet the need of local consumption

and export for foreign exchange earning for the coastal communities in Nigeria.

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6.3 Contributions to Knowledge:

This study has made the following contributions to knowledge:

1. This study has generated a checklist for the molluscan communities of the three moles

of Tarkwa Bay which can be used in future to initiate long-time research agenda,

sustainable exploitation, management options and baseline dataset to assess future

change in molluscs‟ community dynamics.

2. The study has documented a robust dataset for selected molluscs of Tarkwa Bay that

can be used as tool for sustainable exploitation and regulatory framework of

molluscan shellfish industries in coastal areas in the Nigeria.

3. The study has documented growth patterns at the three different tidal zones and the

laboratory. These dataset can be utilized for mass-production of molluscan shellfish of

commercial values for the benefits of the Nigerian people

4. The study has established dietary preference (algal diets), and per-capital

consumptions for juvenils and adults commercial species of molluscs that can be used

for feeding models for home aquaria, captive breeding and aquaculture programmes

in coastal communities in Nigeria.

5. Spatio-temporal variations in physico-chemical characteristics and their ecological

effects on intertidal molluscan community dynamics of the three moles of Tarkwa

Bay have been established.

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6.3 Conclusion

General descriptions of the intertidal rocky shores of Tarkwa Bay coast are given in this study to elucidate the context of comparisons of distribution, composition, abundance, diversity of molluscan communities. The study is a quantitative and descriptive study which establishes a useful frame-work of reference in terms of three different zones on the intertidal shores. The assessment of dominant molluscs at different zones of the shore, and biogeographical change of molluscan fauna distributions; such an attempt has never been described for the entire Tarkwa Bay coast. Consequently, this study forms a baseline for measuring the response of molluscan species distributions in term of fluctuating physico- chemical parameters and seasonality. It provides background studies for management and conservation programmes on intertidal rocky shores of Tarkwa Bay.

The relationship between seawater quality parameters and the distribution of intertidal molluscs were analyzed. Accordingly, the physico-chemical changes in water were found to affect the development, composition, and distribution of intertidal molluscan communities of

Tarkwa Bay. The diverse use of intertidal rocky shores of Tarkwa Bay for shell fishing, recreation, education, dredging, research, tourisms, and navigation had locally degenerated significantly into stressed ecosystems of low water qualities. Training mole was strongly influenced by anthropogenic activities and exhibited strong seasonal variations in assemblage structure. The variations in foraging behaviour of intertidal molluscan species of the three moles of Tarkwa Bay during different seasons, combined with seasonal variations in primary productivity, plays an important role in determining seasonal assemblage structure of molluscan species of Tarkwa Bay. The size-frequency histograms, recruitment of new cohorts, emerging of cohort and the disappearance of older cohorts caused variations on population structures of all the study species and these molluscs were explicitly found to be

221

polymodal assemblages.

Studies in this thesis would contribute to the advancement of our understanding of the status and the trends of tropical Bay marine ecosystems at regional scale, providing an important model for molluscan conservation and management of tropical rocky shores locally, regionally and globally. Information on water quality, dietary preference and heavy metal concentrations will be handy for shellfish industries in Nigeria. The study generated a comprehensive checklist of molluscan communities in Tarkwa Bay area, which will be useful for future assessments and ecotourism development.

222

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Appendix 1: Physico-chemical parameters investigated at the West mole of Tarkwa Bay (April, 2008 – March, 2010).

WATER AIR ROCK MONTH TEMP TEMP. TEMP pH SALINITY CONDUCTIVITY SULPHATE PHOSPHATE NITRATE COD DO BOD5 RAINFALL (°C) (°C) (°C) (‰) (µS/cm) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mm) APR08 28.8 31 33.3 7.9 33.13 34.0 25.5 1.64 11.70 25.50 5.5 2 60 MAY 28.6 31.5 33 7.7 33.33 33.43 24.8 1.56 12.90 13.00 5.8 3 130 JUN 28.0 29.8 31.8 7.71 28.50 31.9 24.3 2.00 11.70 20.30 6 3 620 JUL 26.8 28.5 29 7.64 26.06 31.2 23.3 2.00 11.10 17.30 5.9 4 440 AUG 27.3 28.8 31 7.15 22.00 33.54 20.0 0.86 7.60 10.50 4.9 4 130 SEP 27.0 29.3 30.8 7.7 22.68 34.89 21.0 1.78 7.18 10.30 4.5 5 240 OCT 27.0 29.0 33 7.4 25.18 38.67 17.1 2.72 7.40 9.00 4.3 4 140 NOV 28.0 30.3 35.3 8.06 26.13 43.9 19.3 2.10 5.50 10.80 4.4 2 30 DEC 27.5 29.5 33.8 8.5 27.78 44.1 22.1 2.10 5.03 9.75 4.3 4 140 JAN09 26.0 29.0 30.25 7.2 31.48 28.4 25.6 2.40 5.24 8.30 5.8 13 10 FEB 28.0 30.3 34.3 7.12 32.80 29.1 26.8 1.40 6.50 11.00 5.1 16 80 MAR 28.5 30.5 35.3 7.9 32.23 28.32 27.1 1.80 6.23 9.30 4.8 11 50 APR 28.0 30.5 34.5 7.4 31.73 27.82 27.8 1.98 5.73 8.00 5.3 11 125 MAY 28.5 30.5 34.5 7.2 30.78 26.96 28.0 2.06 4.89 9.00 5.4 9 250 JUN 28.8 30.5 33.8 7.06 30.45 22.8 25.9 2.40 4.05 10.80 6.35 15 325 JUL 28.5 30.3 33.5 7.46 29.33 23.49 27.4 2.09 5.85 10.30 7.4 8 450 AUG 29.0 30.3 33.8 7.3 30.83 25.41 28.4 2.10 5.45 11.00 6.9 10 25 SEP 28.5 30.3 31.5 7.7 25.93 24.9 26.0 3.25 6.05 7.50 7.1 9 240 OCT 28.0 30.5 31.8 8.38 24.83 24.1 24.9 2.83 8.45 7.50 6.3 7 140 NOV 28.0 30.3 35.3 7.6 26.41 27.12 17.8 2.40 5.00 9.60 5.7 5 30 DEC 27.5 29.5 33.8 6.9 27.78 26.41 21.0 2.25 5.06 8.95 5.5 6 140 JAN10 26.0 28 30.2 7.2 31.48 28.4 26.0 2.34 5.26 8.6 5.6 6 10 FEB 28.0 30 34.2 7.1 31.78 27.6 26.1 1.48 6.86 10.8 5.4 7 80 MAR 28.5 31 35.1 7.9 32.23 27.3 26 1.76 7.24 9.2 5.5 8 50

248

Appendix 2: Physico-chemical parameters investigated at the Training mole of Tarkwa Bay (April, 2008 – March, 2010)

WATER AIR ROCK MONTH TEMP TEMP. TEMP pH SALINITY CONDUCTIVITY SULPHATE PHOSPHATE NITRATE COD DO BOD5 RAINFALL (°C) (°C) (°C) (‰) (µS/cm) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mm) APR 08 28.3 30.5 32.8 7.68 30.9 29.5 24.8 1.22 8.03 21.8 5.6 3 60 MAY 28.5 30 32.5 7.62 31.83 28.26 24.5 1.12 8.6 21.3 5.3 2 130 JUN 27.8 29.5 31 7.38 28.18 29.6 23 2.4 9.5 20.3 6 3 620 JUL 27.8 29.8 30.8 7.68 27.93 28.2 22 2.61 10 20.5 5.9 4 440 AUG 26.5 28.3 30.3 8.01 26.86 20.76 17 3 9.8 7.5 5.1 4 130 SEP 26.5 28 30.3 8.1 21.95 24.1 18.1 2.8 7.3 10.3 4.9 4 240 OCT 26.5 29.5 32 8 25.55 25.2 17.2 2.5 6.95 9.75 4.6 4 140 NOV 27.5 29.3 35 8.01 25.83 25.9 22 2.2 5.24 7.8 4.5 5 30 DEC 28.3 30.5 34.5 8.08 27.38 26.97 23.7 2.3 6.14 10 4.4 3 140 JAN 09 25.8 30 34 7 32.35 27.74 22.6 1.83 6.43 12 6.12 12 10 FEB 27.8 30 34 7.1 33.75 28.64 26.3 1.51 6.53 11.8 6 13 80 MAR 27.8 30.5 33.8 7.2 32.65 27.12 20.1 1.45 5.9 8.9 5.2 6 50 APR 28 30.5 34.5 7.4 32.05 26.91 26.7 1.55 5.25 9.5 5.1 5 125 MAY 29.3 31.8 35.3 7.9 31.35 25.42 27.3 1.76 4.73 8.9 5.3 6 250 JUN 27.8 29.3 33.8 7.1 30.08 19.68 26 2.38 4.46 8.9 6.14 8 325 JUL 28.8 30 34.3 8.1 30.29 24.45 26.3 2.38 4.68 9.5 6.22 10 450 AUG 28.8 30.8 34.8 7.3 31.88 25.71 27.3 2.93 5.68 7.8 6.3 8 25 SEP 28.5 30.5 31.8 8.1 25.73 26.1 26.1 3.19 6.26 10 6.4 9 240 OCT 28.5 30 32 8.02 25.2 24.9 25.2 3.48 9.05 7.5 6.2 8 140 NOV 27.5 29.3 35 7.3 25.78 26.21 21.3 2.1 6 7.8 6.1 6 30 DEC 28.3 30.5 34.5 7.8 27.38 28.22 22.7 2.3 6.24 9 6.2 7 140 JAN 10 25.8 30.2 34.2 7 31.9 28 23 1.82 6.53 11 6.3 7 10 FEB 27.8 29.8 33.6 7.18 33.23 27.2 24.6 1.62 6.42 10.5 5.7 8 80 MAR 27.8 30.5 34 7.2 33.08 27.4 19.01 1.48 4.86 9.8 5.65 7 50

249

Appendix 3: Physicochemical parameters sampled at the East mole of Tarkwa Bay (April, 2008 – March, 2010)

WATER AIR ROCK MONTH TEMP TEMP. TEMP pH SALINITY CONDUCTIVITY SULPHATE PHOSPHATE NITRATE COD DO BOD5 RAINFALL (°C) (°C) (°C) (‰) (µS/cm) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mm) APR 08 27.8 30.0 33.3 7.64 32.18 33.7 22 1.47 10.45 25.8 5.5 3 60 MAY 29.0 31.3 32.5 7.34 32.37 32.6 23.5 1.56 11.8 20.5 5.8 2 130 JUN 27.8 30.0 31.3 6.9 29.4 32.9 24.5 2.06 11.1 16.5 5.9 2 620 JUL 26.5 28.8 30 7.18 27.53 28.7 24.3 2.25 10.8 16.3 6.5 4 440 AUG 28.0 30.3 30.8 7.28 25 20.75 20.1 2.8 9.24 9.5 4.3 3 130 SEP 28.0 30.0 31.3 7.2 25 23.98 17.9 2.5 9.38 8.5 5.2 5 240 OCT 29.5 31.3 32.8 7.4 26 25.1 19.2 2.2 9.43 7.5 4.8 4 140 NOV 27.8 29.5 33.3 8.2 25.08 26.2 19.8 1.95 8.19 6.8 4.7 4 30 DEC 27.5 30.0 32.3 8.08 27.35 26.9 21.4 2.3 7.42 11.3 4.5 5 140 JAN 09 27.3 30.3 34.3 7.4 31.87 26.9 21.5 2.61 7.11 9.5 5.7 6 10 FEB 28.5 31.0 35.0 7.3 32.53 29.12 24.5 2.4 8.02 11.3 5.1 10 80 MAR 28.5 30.8 34.8 7.7 30.9 28.1 25.2 2.4 6.25 7.5 4.8 8 50 APR 28.5 30.8 34.5 7.4 30.28 27.46 26.2 2.38 5.8 8.5 5.1 8 125 MAY 28.5 30.5 35.5 7.8 29.65 27.2 26.9 2.3 5.15 9.8 5.3 6 250 JUN 28.5 30.0 34.5 7.5 29.45 24.6 25.6 2.3 6.96 12 7.2 6 325 JUL 28.8 30.8 35.0 7 29.84 25.6 26.05 2.2 7.15 13 7.4 8 450 AUG 27.8 29.8 34.5 7.3 31.43 21.4 27.06 2.5 5.6 10.3 7.5 7 25 SEP 28.3 30.5 32.0 7.4 26.02 26.1 24.6 3.26 7.32 8.9 6.4 9 240 OCT 28.8 30.5 31.5 8.1 24.15 25.9 26.5 4.32 8.75 10.8 6.3 6 140 NOV 27.8 29.5 33.3 6.9 26.08 26.1 18 1.8 8.24 7.2 5.5 8 30 DEC 27.5 30.0 32.5 7.1 27.35 26.61 22 2.2 7.38 12.1 5.8 7 140 JAN 10 27.3 30.1 34.5 7.4 31.87 26.6 24 2.71 7.24 9.2 5.8 8 10

FEB 28.5 31.0 34.8 7.3 32.53 26.7 22 2.45 8.21 10.9 5.5 9 80

MAR 28.5 31.0 34.8 7.7 30.7 27.21 24.2 2.51 7.25 8.1 4.7 6 50

250

Appendix 4: Descriptive statistics for number of Individuals collected in dry at the 3 moles of Tarkwa Bay (April, 2008 – March, 2010) Taxa Min Max Sum Mean S.D Acmeae saccharina 24 34 87 29.0 5.0 Acmeae jacquelina 5 10 23 7.7 2.5 Astrea spp 3 22 38 12.7 9.5 Astele spp 4 5 13 4.3 0.6 Apporrhais senegalensis 0 2 3 1.0 1.0 Buccinum undatum 132 275 632 210.7 72.6 Bullia granulose L 2 7 13 4.3 2.5 Bullia turrita Gray 0 0 0 0.0 0 Bursa marginata 1 8 11 3.7 3.8 Cerithium atratum Born 1 4 8 2.7 1.5 Cerithium sinensis 0 3 4 1.3 1.5 Cerithium genuanus 1 7 10 3.3 3.2 Cassis spinosa 2 9 14 4.7 3.8 Cassis testiculata 9 21 44 14.7 6.0 Conus coronatus 2 7 13 4.3 2.5 Conus genuanus 1 10 16 5.3 4.5 Conus bilosus 4 10 19 6.3 3.2 Conus ambiguous 4 16 32 10.7 6..1 Collisella subrugosa 15 28 65 21.7 6.5 Cymbium Cymbium L 3 7 14 4.7 2.1 Cymbium glans Genelin 0 8 14 4.7 4.2 Cypreae gracili 6 21 39 13.0 7.5 Cypreae stercoraria L 18 36 78 26.0 9.2 Cypreae zonata L 2 13 22 7.3 5.5 Drupa nodulosa Adam 1 23 31 10.3 11.4 Fissurella coarctata 12 33 66 22.0 10.5 Fissurella nubecula L 4 42 68 22.7 19.0 Fissurella rosea G 212 411 947 315.7 99.8 Fasciolaria spp 3 10 19 6.3 3.5 Murex cornutus L 7 28 46 15.3 11.2 Murex saxatillis L 3 26 44 14.7 11.5 Murex varius L 2 11 22 7.3 4.7 Natica collaria L 10 27 54 18.0 8.5 Natica fulminea 4 13 24 8.0 4.6 Natica marochiensis 0 3 4 1.3 1.5 Nassarias thersites 0 2 3 1.0 1.0 Nassarius spp 0 1 1 0.3 0.6 Nerita albicilla 175 436 846 282.0 136.7 Nerita glabrata sowerby 28 44 103 34.3 8.5 Oliva acuminate 1 3 6 2.0 1.0 Patella vulgate 118 351 783 261.0 125.2 Littorina punctata 9 22 46 15.3 6.5 Littorina saxatilis 6 26 49 16.3 10.0 Littorina littorea 216 32.7 774 258.0 60.2 251

Appendix 4 Cont: Descriptive statistics for number of Individuals collected at the 3 artificial breakwaters of Tarkwa Bay during the dry season (April, 2008 – March, 2010).

Taxa Min Max Sum Mean S.D Harpa doris 0 1 2 0.7 0.6 Thais nodosa L 28 46 106 35.3 9.5 Thais undata L 6 21 38 12.3 7.6 Thais califera L 31 41 105 35 5.3 Thais forbesi D 5 8 15 5.0 2.6 Thais rogosa 5 11 23 7.7 3.1 Arca senilis 22 40 88 29.3 9.4 Arca afra Gmelin. 3 8 15 5.0 2.6 Aloidis trigonal Hind 1 2 4 1.3 0.6 Aloidis deutezerberg L 0 1 1 0.3 0.6 Cardium costatum L 3 7 14 4.7 2.1 Cardium ringens B 0 1 2 0.7 0.6 Macoma cumana C 0 0 0 0 0 Egeria radiate 0 0 0 0 0 Iphigenia truncate 1 8 11 3.7 3.8 Chama crenulata 0 6 9 3.0 3.0 Mytilus perna L 6 10 24 8.0 2.0 Ostrea tulipa 12 23 50 16.7 5.7 Crassostrea gasar 11 53 79 26.3 23.2 Ostrea folium 4 10 21 7.0 3.0 Donax rugosa 1 6 9 3.0 2.6 Littophaga spp 0 3 4 1.3 1.5 Chiton spp 0 3 5 1.7 1.5 Sepia officialis 1 6 11 3.7 2.5 Octopus vulgaris 1 3 6 2.0 1.0

252

Appendix 5: Temporal variation in euryhaline molluscan species sampled at the 3 moles of Tarkwa Bay (April, 2008 – March, 2010).

Taxa Taxonomic Authority Acmaea Saccharina Forbes 1844 Acmaea tectura unicolour Gmelin 1791 Acmaea jacquelina Risso 1826 Astele spp Linnaeus 1820 Bullia granulose Larmack 1725 Cerithium atratum Brochi 1814 Cerrithium sinesis Risso 1826 Cerithium genuana Philippi 1848 Cassis spinosa Born 1778 Cassis testiculata Tiberi 1863 Coelisella subrugosa Linnueus 1768 Cymbium cymbium Linnaeus 1758 Cymbium glans Gmelin 1791 Cypraea gracilis Gmelin 1790 Cypraea stercoraria Gmelin 1791 Cypraea zanata Linneaus 1820 Fissurella rosea Gmelin 1828 Fasciolaria spp Harmack 1786 Nassarius thersite Allan 1816 Nassarius spp Nsrdo 1846 Nerita albicilla Pfeiffer 1828 Nerita senegalensis Allan 1880 Patella safiana Linnaeus 1758 Patella rustica Linnaeus 1758 Littorina punctata Linnaeus 1758 Littorina Saxatili Gmelin 1791 Littorina Lottorea Risso 1826 Littorina anqulifera Gmelin 1881 Thasis forbesi Philippi 1844 Iphigenia truncate Linnaeus 1822 Mytilus edulis Linnaeus 1819 Donax rugosa Gmelin 1817

253

Appendix 6: Temporal variation in dry season molluscan species sampled at 3 moles of Tarkwa Bay (April, 2008 – March, 2010).

Taxa Taxonomic Authority Astrea spp Linneaus 1767 Apporrhais spp Linnaeus 1890 Bullia turrita G. Linnaeus 1815 Bursa marginata Link 1807 Conus coronate Linnaeus 1678 Conus genuanus harmack 1814 Conus ambiguous Gmelin 1795 Drupa tuberculata Linnaeus 1780 Fissurella Coarctata Linnaeus 1858 Murex cornutus Gmelin 1791 Murex saxatilis Born 1778 Murex varius Da costa 1778 Natica collaria Liunaeus 1821 Natica fulminea Gmelin 1848 Natica marochieus Linnaeus 1888 Oliva acuminate Linnaeus 1879 Harpa dori Oberlin 1971 Thasis rugosa Brocchi 1814 Thasis nodosa Valenciennes 1846 Thasis callifera Linnaeus 1758 Thasis undata Gmeline 1797

254

Appendix 7: Temporal variations in rainy season molluscan species sampled at 3 moles of Tarkwa Bay (April, 2008 – March, 2010).

Taxa Taxonomic Authority

Arca semilis Linnaeus 1871

Arca afra Gmelin 1888

Aloidis trigona Hind 1879

Aloidis spp Deutzerbeg 1818

Cardium coastatum Linnaeus 1758

Cardium ringens Linnaeus 1767

Marcoma acumana Linnaeus 1762

Egeria radiate Allan 1890

Chama genulata harmack 1816

Ostrea tulipa Linnaeus 1826

Ostrea deuticulate Gmelim 1847

Ostrea folium Brocchi 1814

Lithophaga spp Linnaeus 1708

Chiton spp Risso 1826

Sepia officialis Liunaeus 1758

Octopus vulgaris Gmelin 1815

255

Appendix 8: Checklist of common molluscan species of the three moles of Tarkwa Bay (April, 2008 – March, 2010).

Class Family Species Taxonomic Authority Gastropoda Acmaedae Acmeae saccharina Forbes 1844 Gastropoda Buccinidae Buccinum undatum Linnaeus 1858 Gastropoda Cassidae Cassis testiculata Born 1778 Gastropoda Lottidae Collisella subrugasa Linnaeus 1768 Gastropoda Volutidae Cymbium cymbium Linnaeus 1758 Gastropoda Cypraeidae Cypreae stercorana Gmelin 1791 Gastropoda Neritidae Nerita senegalensis Allan 1880 Gastropoda Neritidae Nerita glabrata Pfeiffer 1828 Gastropoda Patellidae Patella Safiana Linnaeus 1758 Gastropoda Littorinidae Littorina Punctata Linnaeus 1854 Gastropoda Littorinidae Littorina cingulifera Gmelin 1791 Bivalvia Arcidae Arca senilis Linnaeus 1871 Bivalvia Arcidae Arca afra Gmelin 1888 Bivalvia Aloididae Aloidis trigonal Hind 1879 Bivalvia Cardidae Cardium Costatum Linnaeus 1758 Bivalvia Cardidae Egeria radiate Allan 1890 Bivalvia Cardidae Iphigenia truncate Linnaeus 1822 Bivalvia Mytilidae Mytilus eduilis Linnaeus 1819 Bivalvia Ostridae Ostrea tulipa Brocchi 1847 Bivalvia Ostridae Ostrea Folium Linnaeus 1814 Polyplacophora Chitonidae Chiston spp Risso 1826 Cephalopoda Sepiidae Sepia officials Linnaeus 1758

256

Appendix 9: Checklist of rare species of molluscan communities of Tarkwa Bay (April, 2008 – March, 2010).

Class Family Taxa Taxonomic Authority Gastropoda Apporhaidae Apporrhais senegalensis Linnaeus 1767 Bullidae Bullia turrita Lnnaeus 1815 Cerithidae Cerithium atratratum Brochi 1814 Conidae Conus coronatus Linnaeus 1678 Volutidae Cymbium glans Gmelin 1791 Nassaridae Nassarius spp Allan 1816 Olividae Oliva acuminate Linnaeus 1879 Harpidae Harpa doris Oberlin 1971 Bivalvia Cardidae Cardium ringeus Linnaeus 1767 Tellinidae Macoma Cumana Linnaeus 1762 Chamidae Chama crenulata Harmack 1816 Mytilidae Lithophaga spp Linnaeus 1718 Donacidae Donax rugosa Gmelin 1817 Cephalopoda Octopodidae Octopus vulgaris Gmelin 1815

257

Appendix 10: Checklist of molluscan ornamental species of the three moles of Tarkwa Bay (April, 2008 – March, 2010).

Class Family Taxa Taxonomic

Authority

Gastropoda Turbinidae Astrea spp Linnaeus 1767

Buccinidae Buccinum unidatum Gmelin 1828

Bursidae Bursa marginata Link 1815

Cassidae Cassis spinosa Born 1778

Lottidae Collisella subrugasa Linnaeus 1768

Cypraeidae Cypreae stercorana Gmelin 1791

Nassaridae Nassarius thersites Allan 1816

Fissurdlidae Fissurella coarctata Gmelin 1828

Fasciolariidae Fasciolaria spp Larmack 1786

Muricidae Murex cornutus Gmelin 1791

Nacidae Natica marochinensis Linnaeus 1888

Bivalvia Ostreidae Ostrea folium Brocchi 1814

Ostreidae Crassostrea gasar Gmelin 1847

Donacidae Donax rugosa Gmelin 1817

Cephalopoda Octopodidae Octopus vulgaris Gmelin 1815

258

Appendix 11: Checklist of species of Aquaculture potentials sampled at the three moles of Tarkwa Bay (April, 2008 – March, 2010).

Class Family Taxa Taxonomic Authority Gastropoda Buccinidae Buccinum undatum Gmelin 1828 Lottidae Colisella subrugosa Linnaeus 1768 Neritidae Nerita Senegalensis Allan 1880 Patellidae Patella safiana Linnaeus 1758 Littorinidae Littorina Littorea Risso 1826 Littorinidae Littorina lingulifera Gmelin 1881 Littorinidae Littorina pundata Linnaeus 1758 Fissurdlidae Fissurella coarctata Linnaeus 1858 Fissurellidae Fissurella rosea Gmelin 1828 Thaididae Thais callifera Linnaeus 1758 Thaididae Thais nodosa Valenciennes 1846 Thaididae Thais forbesi Philippi 1844 Thaididae Thai rugosa Brocchi 1814 Bivalvia Arcidae Arca Senilis Linnaeus 1871 Aloididae Aloidis trigonal Hind 1879 Cardidae Cardium costatum Linnaeus 1758 Ostreidae Crassostrea gasar Gmelin 1817 Mytilidae Mytitus eduilis Linnaeus 1819

259

Appendix 12: Checklist of biofouling species of molluscan communities of Tarkwa Bay (April, 2008 – March, 2010).

Class Family Taxa Taxonomic Authority Gastropoda Acmaeidae Acmaea Saccharina Firbes 1844 Lottidae Collisella subrugosa Linnaeus 1768 Fissurellidae Fissurella rosea Gmelin 1828 Fissurellidae Fissurella nebecula Gmelin 1817 Fissurellidae Fissurella coarctata Linnaeus Fasciolaridae Fasciolaria spp Larmack 1786 Patellidae Patella safiana Linnaeus 1758 Bivalvia Arcidae Aica semilis Linnaeus 1871 Arcidae Arca afra Gmelin 1888 Aloididae Aloidis trigonal Hind 1879 Aloididae Aloidis spp Deutzerber 1818 Cardidae Cardium costatum Linnaeus 1758 Cardidae Cardium ringeus Linnaeus 1767 Chamidae Chaina crenulata Larmack Mytilidae Mytilus eduilis Linnaeus 1819 Mytilidae Lithophaga spp Linnaeus 1918 Ostreidae Crassostrea gasar Ostreola stentina 1826 Ostreidae Ostrea folium Linnaeus 1758

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Appendix 13: Descriptive statistics for number of individuals collected during dry season at the 3 moles of Tarkwa Bay (April, 2008 - March, 2010).

Species Min Max Sum Mean S.D Acmea scccharina 24 34 87 29.0 5.0 Acmeae jacquelina 5 10 23 7.7 2.5 Astrea spp 3 22 38 12.7 9.5 Astele spp 4 5 13 4.3 0.6 Apporrhais senegalensis 0 2 3 1.0 1,0 Buccinum undatum 132 275 632 210.7 72.6 Bullia granulose l 2 7 13 4,3 2.5 Bullia turrita gray 0 0 0 0.0 0 Bursa marginata 1 8 11 3.7 3.8 Certithium atratum born 1 4 8 2.7 1.5 Cerithium sinensis 0 3 4 1.3 1.5 Cerithium genuanus 1 7 10 3.3 3.2 Cassis spinosa 2 9 14 4.7 3.8 Cassis testiculata 9 21 44 14.7 6.0 Conus coronatus 2 7 13 4.3 2.5 Conus genuanus 1 10 16 5.3 4.5 Conus bilosus 4 10 19 6.3 3.2 Conus ambiguous 4 16 32 10.7 6.1 Collisella subrugosa 15 28 65 21.7 6.5 Cymbium cymbium_l 3 7 14 4.7 2.1 Cymbium glans Gmelin 0 8 14 4.7 4.2 Cypreae gracili 6 21 39 !3,0 7.5 Cypreae stercoraria l 18 36 78 26.0 9.2 Cypreae zonata l 2 13 22 7.3 5.5 Drupe nodulosa adam 1 23 31 10.3 11.4 Fissurella coarctata 12 33 66 22.0 10.5 Fissurella nubecula l 4 42 68 22.7 19.0 Fissurella rosea g 212 411 147 315.7 99.8 Faciolaria spp 3 10 19 6.3 3.5 Murex cornutus l 1 28 46 15.3 11.2 Murex saxatilis l 3 26 44 14.7 11.5 Murex varius l 2 11 22 7.3 4.7 Natica collaria l 10 27 54 18.0 8.5 Natica fulminea 4 13 24 8.0 4.6 Natica marochiensis 0 3 4 1.3 1.5 Nassarius thersites 0 2 3 1 0 1.0 Nassarius spp 0 1 1 0,3 0,6 Nerita albicilla 175 436 S46 282.0 136.7 Nerita glabrata sowerby 28 44 103 34.3 8.5 Olive acuminate 1 3 6 2.0 1.0

261

Appendix 13 cont : Descriptive statistics for number of individuals collected at the 3 artificial breakwaters of Tarkwa Bay during the dry season (April, 2008 - March, 2010).

Species Min Max Sum Mean S.D Patella vulgate 18 351 783 261.0 125.2 Littorina punctate 9 22 46 15.3 6.5 Littorina saxatilis 6 26 49 16.3 10.0 Littorina littorea 216 327 774 258.0 60.2 Harpa doris 0 1 2 0.7 0.6 Thais nodosa L 28 46 106 35.3 9.5 Thais califera L 31 41 105 35 5.3 Thais undata L 6 21 38 12.3 7.6 Thais forbesi D 5 3 19 6.3 1.5 Thais rogosa 5 11 23 7.7 3.1 Arca senilis 22 40 88 29.3 0.4 Arca afra Gmelin 3 8 15 5.0 2.6 Aloidis trigonal Hind 1 2 4 1.3 0.6 Aloidis deutozerberg L 0 1 1 0.3 0.6 Cardium consttum L 3 7 14 4.7 2.1 Cardium ringens B 0 1 2 0.7 0.6 Macoma cumana C 0 0 0 0 0 Egeria radiate 0 0 0 0 0 Iphigenia truncate 1 8 11 3.7 3.8 Chama crenulata 0 6 9 3.0 3.0 Mytilus perna L 6 10 24 8.0 2.0 Ostrea tulipa 12 23 50 16.7 5.7 Crassostrea gasar 11 51 79 26.3 23.2 Ostrea folium 4 10 21 7.0 3.0 Donax rugosa 1 6 9 3.0 2.6 Littophaga spp 0 3 4 1.3 1.5 Chiton spp 0 3 5 1.7 1.5 Sepia officialis 1 6 11 3.7 2.5 Octopus vulgaris 1 3 6 2.0 1.0

262

Appendix 14 : Descriptive statistics for number of individuals collected at the 3moles of Tarkwa Bay during the rainy season (April, 2008 -March, 2010).

Species Mm Max Sum Mean S.D Acmea scccharina 10 17 39 13.0 3.6 Acmeae jacquelina 3 9 18 6.0 3.0 Astrea spp 0 2 2 0.7 1.2 Astele spp 0 4 4 2.0 2.0 Apporrhais senegalensis 0 0 0 0 0 Buccinum undatum 86 143 343 114.3 28.5 Bullia granulose L 0 4 5 1.7 2.1 Bullia turrita Gray 0 1 1 0.3 0.6 Bursa marginata 1 2 5 1.7 0.6 Certithium atratum Born 0 0 0 0 0 Cerithium sinensis 0 2 3 1.0 1.0 Cerithium genuanus 0 0 0 0 0 Cassis spinosa 0 3 4 1.3 1.53 Cassis testiculata 3 5 12 4.0 1.0 Conus coronatus 0 2 3 1.0 1.0 Conus genuanus 0 0 0 0 0 Conus bilosus 0 7 9 3.0 3.6 Conus ambiguous 0 0 0 0 0 Collisella subrogosa 0 12 17 5.7 6.0 Cymbium cymbium L 3 4 29 9.7 5.9 Cymbium glans Gmelin 0 1 1 0.3 0.6 Cypreae gracili 1 7 11 3.7 3.1 Cypreae stercoraria L 5 9 22 7.3 2.1 Cypreae zonata L 0 4 5 r.7 2.1 Drupe nodulosa Adam 3 9 19 6.3 3.1 Fissurella coarctata 1 6 12 4,0 2.6 Fissurella nubecula L 10 33 73 24.3 12.5 Fissurella rosea G 120 226 473 157.7 59.3 Faciolaria spp 3 17 34 11.3 7.4 Murex cornutus L 0 4 7 2.3 2.1 Murex saxatilis L 0 9 13 4.3 4.5 Murex varius L 0 10 12 4.0 5.3 Natica collaria L 0 2 3 1.0 1.0 Natica fulminea 5 11 26 8.7 3.2 Natica marochiensis 1 9 12 4.0 4.4 Nassarius thersites 5 11 24 8.0 3,0 Nassarius spp 0 0 0 0 0 Nerita albicilla 71 115 2S1 93.7 22.0 Nerita glabrata sowerby 9 23 44 14.7 7.4 Olive acuminate 0 6 7 2.3 3.2

263

Appendix 14 Cont: Descriptive statistics for number of individuals collected during rainy season at the 3 artificial breakwaters of Tarkwa Bay (April, 2008 -March, 2010).

Species Min Max Sum Mean S.D

Patella vulgate 37 71 153 51.0 17.8

Littorina punctata 4 19 29 9.7 8.1

Littorina saxatilis 5 14 29 9.7 4.5

Littorina littorea 54 S7 204 68.0 17.1

Harpa Doris 0 2 2 0.67 1.2

Thais nodosa L 15 24 61 20.3 4.7

Thais califera L 0 18 27 9.0 9.0

Thais undata L 2 4 9 3.0 1.0

Thais forbesi D 1 3 5 1.7 1.2

264

Appendix15: Seasonal variations in composition, distributions and abundance of molluscan fauna species at the three tidal zones among the 3 moles of Tarkwa Bay (April, 2008 - March, 2010).

TIDAL ELEVATIONS MONTH YEAR HIGH MID LOW APR 2008 68 102 208 MAY 68 88 160 JUN 43 59 98 JUL 35 44 70 AUG 24 32 46 SEP 21 34 56 OCT 63 85 124 NOV 65 97 132 DEC 92 125 222 JAN 2009 116 164 270 Feb 119 164 248 MAR 123 154 242 APR 91 151 211 MAY 69 93 160 JUN 39 59 95 JUL 31 46 72 AUG 22 31 49 SEP 28 34 53 OCT 59 90 125 NOV 52 96 141 DEC 121 172 265 JAN 2010 132 194 275 FEB 141 177 293 MAR 107 157 202 TOTAL 7985 1726 2446 3813

265

Appendix 16: Mean values of Male and Female monthly Gonad Dry Weight (mg) of 3 species of herbivorous gastropods monitored from May, 2008 - December, 2009

MONTH Nerita senegalensis Patella safiana Thais callifera MALE FEMALE MALE MALE FEMALE FEMALE MAY 08 2.07 2.02 4.24 4.51 2.92 2.96 JUN08 2.04 1.74 2.94 2.34 2.38 2.1 JUL08 2.15 1.13 2.82 2.32 176 175 AUG 08 0.96 116 1.34 1.36 1.24 125 SEP 08 1.04 1.96 1.34 3.46 2.56 2.74 OCT 08 1.04 1.04 0.33 0.38 2.15 2.57 NOV 08 1.06 1.02 0.22 0.22 0.1 0.1 DEC 08 1.07 1.03 0.23 0.27 0.15 0.15 JAN 09 0.27 0.1 0.16 0.18 0.12 0.13 FEB 09 0.27 0.44 0.41 0.31 0.14 0.15 MAR 09 0.77 1.64 0.29 0.32 0.17 0.17 APR 09 4.59 4.56 0.67 0.64 0.5 0.49 MAY 09 4.6 4.3 4.46 4.59 2.64 2.15 JUN 09 5.1 4.9 5.43 6.1 4.84 4.98 JUL 09 0.4 0.2 0.56 0.51 4.86 4.63 AUG -9 4.6 4.52 0.96 1.2 6.31 6.19 SEP 09 3.1 2.04 0.34 0.44 0.22 0.24 OCT09 2.61 2.01 0.36 0.22 4.66 444 NOV 09 2.24 2.04 0.91 0.96 2.44 2.46 DEC 09 2.15 1.90 0.86 0.92 1.67 1.94

266

Appendix 17: Seasonal variation in species richness (d) computed for the communities of molluscan fauna sampled at the 3 artificial breakwaters of Tarkwa Bay (April, 2008- March, 2010) MONTH WEST MOLE TRAINING MOL EAST MOLE TOTAL S E WM WM WM WM TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4 MEAN+SD 1 2 3 4 APR 08 1.40 1.67 1.94 1.72 1.73 1.50 1.64 2.00 1.22 1.76 1.50 1.64 1.643+0.21 MAY 1.52 1.64 1.78 1.20 1.89 2.35 1.44 1.17 1.32 1.92 1.32 2.00 1.63+0.37 JUN 1.02 0.72 0.78 1.41 1.56 2.09 1.64 1.67 1.14 1.44 1.44 1.64 1.38+0.40 JUL 1.21 0.46 0.83 1.44 0.40 0.69 0.78 1.14 0.74 1.21 1.11 0.87 0.91+0.32 AUG 1.67 0.51 1.54 1.37 0.96 1.08 1.11 1.03 0.72 0.96 0.62 0.91 0.04+ 0.35 SEP 0.62 1.25 0.83 1.21 1.74 1.03 1.30 1.44 1.03 1.12 1.30 1.67 1.23+0.32 OCT 1.08 1.29 1.28 1.00 1.23 1.86 1.78 1.84 1.94 1.55 1.38 1.34 1.46+0.32 NOV 1.56 1.58 2.08 2.10 1.76 1.64 1.52 1.47 0.99 1.67 1.24 1.64 1.60+0.31 DEC 1.44 1.95 1.34 1.67 1.44 1.65 2.35 0.87 2.71 1.87 1.58 1.39 1.69+ 0.49 JAN 1.83 1.29 2.04 1.28 1.82 1.56 2.01 1.13 1.34 1.84 0.99 1.00 1.51+ 0.39 FEB 1.53 1.32 2.09 1.06 2.05 1.30 1.37 1.53 2.30 1.39 1.40 1.75 1.59+0.38 MAR 1.39 1.05 1.62 1.70 1.70 1.53 1.76 0.84 1.08 1.04 1.39 1.12 1.35+0.32 APRI 1.11 1.08 1.39 1.04 1.58 1.31 1.64 0.89 1.39 1.12 1.17 1.42 1.26+ 0.23 MAY 0.90 1.24 1.69 1.59 1.17 0.93 1.09 1.42 1.99 1.22 1.17 1.14 1.30+0.32 JUN 1.34 0.74 1.14 1.44 0.71 0.91 1.54 1.29 1.11 1.62 1.36 1.18 1.20+0.29 JUL 0.78 1.44 0.81 1.02 0.97 1.21 0.81 1.60 0.97 0.81 1.24 0.76 1.04+0.28 AUG. 1.44 0.43 0.56 0.96 1.24 1.38 0.65 0.66 1.15 0.99 1.00 0.71 0.93+0.33 SEP 1.12 0.51 0.91 0.40 0.76 0.35 1.17 1.36 0.91 1.47 1.04 1.36 0.95+0.38 OCT 2.43 1.73 1.54 1.75 1.56 1.84 1.40 1.41 1.18 1.72 1.40 1.46 1.62+0.32 NOV 2.07 1.55 1.80 1.46 1.62 1.80 1.89 1.45 1.85 1.57 1.84 1.95 1.74+0.20 DEC 1.70 2.04 1.16 2.09 2.24 1.83 2.27 1.96 2.29 1.87 1.64 2.16 1.94+0.33 JAN 10 1.62 1.27 1.83 1.78 12.9 1.93 1.36 1.31 1.97 1.80 1.55 2.03 1.70+0.27 FEB 2.00 1.96 2.24 2.26 1.53 1.65 1.82 1.29 1.59 1.76 1.07 1.31 1.71+0.37 MAR 1.78 1.14 1.39 1.35 2.00 1.49 1.62 1.40 1.09 2.02 1.80 1.11 1.52+0.33

267

Appendix 18: Seasonal variation in Shannon-Weaver Indices (H) computed for the communities of the molluscan fauna at three moles of Tarkwa Bay (April, 2008-March, 2010). MONTH WEST MOLE TRAINING MOLE EAST MOLE TOTAL S WM1 WM2 WM3 WM4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4 MEAN+SD Apr 08 1.77 1.84 2.00 1.91 1.99 1.68 1.82 2.01 1.55 1.86 1.65 1.75 1.82+0.15 May 1.71 1.77 1.87 1.40 1.90 2.06 1.80 1.50 1.46 1.90 1.57 1.84 1.73+0.21 June 1.34 1.10 1.06 1.52 1.55 1.67 1.13 1.71 1.38 1.58 1.54 1.66 1.49+0.22 July 1.31 0.64 1.08 1.38 0.70 1.09 0.92 1.38 1.04 1.36 1.36 1.03 1.16+0.35 Aug. 1.33 0.59 1.28 1.27 0.90 1.23 1.19 1.08 0.69 1.08 0.67 1.06 1.03+0.26 Sept. 0.67 1.34 1.04 1.36 1.51 1.01 1.28 1.21 0.96 1.01 1.37 1.60 1.20+0.27 Oct. 1.28 1.53 1.58 1.33 1.57 1.83 1.88 1.89 1.88 1.77 1.51 1.56 1.63+0.21 Nov. 1.76 1.78 2.00 1.98 1.92 1.73 1.57 1.78 1.37 1.76 1.60 1.76 1.75+0.18 Dec. 1.77 2.03 1.58 1.88 1.75 1.90 2.25 1.36 2.35 2.04 1.93 1.77 1.89+0.27 Jan 09 2.04 1.78 2.01 1.79 2.05 1.93 2.13 1.57 1.77 2.02 1.77 1.93 1.90+0.16 Feb. 2.94 1.79 2.08 1.53 2.13 1.77 1.76 1.85 2.18 1.76 1.72 1.91 1.87+0.19 March 1.76 1.60 1.91 2.07 1.92 1.91 2.06 1.38 1.60 1.60 1.73 1.60 1.76+0.21 April 1.59 1.70 1.74 1.55 1.90 1.77 1.92 1.37 1.66 1.59 1.58 1.77 1.68+0.15 May 0.37 1.58 1.86 1.89 1.59 1.37 1.61 1.73 2.01 1.55 1.51 1.48 1.63+0.20 June 1.56 1.04 1.33 1.46 1.07 1.06 1.73 1.58 1.36 1.73 1.56 1.47 1.41+0.26 July 0.09 1.39 1.08 1.35 1.37 1.33 1.01 1.73 1.33 1.80 1.59 0.99 1.34+0.27 Aug. 1.32 0.69 0.69 0.97 1.56 1.57 1.09 1.09 1.60 1.33 1.30 1.10 1.19+0.31 Sept. 1.10 0.68 1.10 0.69 1.08 0.69 1.23 1.60 1.09 1.76 1.32 1.60 1.16+0.37 Oct. 2.09 1.86 1.75 1.85 1.46 1.83 1.78 1.75 1.48 1.78 1.77 1.72 1.76+0.17 Nov. 2.13 1.72 1.84 1.77 1.89 1.88 1.89 1.75 1.96 1.91 1.99 1.88 1.88+0.11 Dec. 1.81 1.99 1.59 2.12 2.60 2.06 2.22 2.16 2.26 2.03 1.90 2.29 2.09+0.26 Jan. 10 1.92 1.78 2.03 2.06 2.19 2.13 1.76 1.78 2.50 2.05 1.92 2.16 2.02+0.21 Feb. 2.18 2.17 2.23 22 1.93 1.93 2.06 1.79 1.92 2.64 1.61 1.79 3.70+5.80 Mar 1.80 1.59 1.77 1.76 2.00 1.71 1.92 1.75 1.61 2.03 1.88 1.60 1.80+0.15

268

Appendix 19: Seasonal variation in Simpson’s Dominance Index(C) computed for the communities of molluscan fauna at the 3 moles of Tarkwa Bay (April, 2008-March,

2010).

MONTHS WEST TRAINING EAST TOTA L WM1 WM2 WM3 WM4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4 MEAN+SD Apr 08 0.17 0.18 0.14 0.15 0.16 0.21 0.19 0.14 0.22 0.17 0.21 0.18 0.22+0.16 May 0.19 0.17 0.17 0.29 0.17 0.14 0.18 0.23 0.25 0.16 0.22 0.17 0.20+0.04 Jun 0.27 0.33 0.36 0.23 0.22 0.21 0.19 0.20 0.26 0.21 0.23 0.21 0.24+0.05 Jul 0.29 0.56 0.36 0.25 0.51 0.34 0.46 0.26 0.37 0.26 0.26 0.38 0.36+0.11 Aug 0.28 0.59 0.31 0.31 0.47 0.32 0.36 0.35 0.5 0.34 0.52 0.36 0.39+0.10 Sep 0.52 0.27 0.37 0.26 0.24 0.38 0.30 0.34 0.42 0.39 0.26 0.21 0.33+0.09 Oct. 0.31 0.24 0.21 0.28 0.22 0.18 0.17 0.16 0.16 0.18 0.24 0.22 0.21+0.05 Nov 0.18 0.18 0.14 0.15 0.15 0.19 0.21 0.17 0.26 0.18 0.20 0.18 0.18+0.03 Dec 0.18 0.13 0.21 0.16 0.18 0.16 0.11 0.26 0.10 0.13 0.15 0.75 0.21+0.18 Jan 09 0.13 0.17 0.15 0.17 0.13 0.15 0.13 0.13 0.21 0.12 0.14 0.17 0.15+0.02 Feb 0.15 0.17 0.13 0.23 0.13 0.17 0.17 0.16 0.12 0.18 0.19 0.16 0.16+0.03 Mar 0.17 0.21 0.15 0.13 0.14 0.15 0.13 0.25 0.20 0.21 0.18 0.21 0.18+0.04 Apr 0.21 0.20 0.18 0.22 0.16 0.17 0.15 0.26 0.21 0.21 0.21 0.17 0.20+0.03 May 0.26 0.21 0.17 0.16 0.21 0.26 0.20 0.19 0.14 0.22 0.24 0.25 0.21+0.04 Jun 0.22 0.37 0.28 0.27 0.35 0.36 0.19 0.21 0.26 0.19 0.22 0.24 0.26+0.06 Jul 0.34 0.25 0.35 0.29 0.26 0.27 0.39 0.19 0.28 0.35 0.21 0.40 0.30+0.07 Aug 0.28 0.50 0.50 0.41 0.22 0.22 0.34 0.34 0.21 0.28 0.29 0.34 0.33+0.10 Sep 0.33 0.51 0.33 0.50 0.35 0.52 0.33 0.20 0.33 0.18 0.28 0.20 0.34+0.12 Oct 0.14 0.16 0.18 0.18 0.25 0.17 0.16 0.17 0.19 0.24 0.19 0.17 0.18+0.03 Nov 0.13 0.14 0.17 0.17 0.12 0.16 0.16 0.18 0.14 0.15 0.14 0.16 0.16+0.02 Dec 0.17 0.15 0.21 0.13 0.11 0.13 0.11 0.12 0.11 0.14 0.15 0.10 0.14 +0.03 Jan 10 0.15 0.17 0.14 0.13 0.12 0.12 0.18 0.17 0.12 0.13 0.15 0.12 0.14+0.02 Feb 0.11 0.12 0.11 0.11 0.15 0.15 0.13 0.16 0.15 0.13 0.20 0.17 0.14+0.03 Mar 0.19 0.20 0.17 0.18 0.14 0.19 0.15 0.18 0.20 0.14 0.16 0.20 0.18+0.02

269

Appendix 20: Seasonal variations in value of Evenness Indices computed for the communities of molluscan fauna at the 3 moles of Tarkwa Bay (April, 2008-March, 2010). MONT WEST MOLE TRAINING MOLE EAST MOLE TOTA L HS WM WM WM WM TM TM TM TM EM EM EM EM MEAN+SD 1 2 3 4 1 2 3 4 1 2 3 4 Apr 08 0.99 0.95 0.97 0.98 0.96 0.94 0.93 0.96 0.96 0.95 0.92 0.98 0.9575+0.02 May 0.96 0.99 0.96 0.87 0.91 0.94 0.98 0.95 0.91 0.98 0.97 0.95 0.9472+0.03 Jun 0.97 1.00 0.96 0.94 0.96 0.93 0.97 0.96 0.99 0.98 0.96 0.93 0.9625+0.02 Jul 0.94 0.92 0.97 1.00 0.98 0.99 0.84 0.99 0.95 0.97 0.98 0.93 0.955+0.044 Aug 0.96 0.86 0.92 0.92 0.82 0.89 0.86 0.98 1.00 0.98 0.97 0.96 0.926+0.057 Sep 0.97 0.96 0.94 0.98 0.94 0.91 0.92 0.88 0.86 0.92 0.99 0.99 0.938+0.042 Oct 0.92 0.93 0.98 0.96 0.98 0.94 0.96 0.97 0.97 0.99 0.94 0.97 0.959+0.021 Nov 0.98 0.99 0.96 0.95 0.99 0.97 0.98 0.99 0.99 0.98 0.99 0.98 0.979+0.013 Dec 0.99 0.97 0.98 0.96 0.98 0.98 0.98 0.99 0.98 0.98 0.99 0.99 0.980+0009 Jan 09 0.98 0.99 0.91 1.00 0.99 0.99 0.96 0.98 0.98 0.97 0.99 0.96 0.975+0.023 Feb 0.99 0.99 0.94 0.95 0.97 0.99 0.98 0.94 0.94 0.98 0.96 0.98 0.9675+0.02 Mar 0.98 0.97 0.98 0.99 0.98 0.97 0.99 0.99 0.99 0.99 0.96 0.99 0.981+0.010 Apr 0.99 0.98 0.99 0.97 0.96 0.97 0.98 0.98 0.99 0.93 0.99 0.98 0.976+0.017 May 0.98 0.98 0.95 0.96 0.98 0.99 0.99 0.96 0.97 0.96 0.93 0.92 0.9641+0.02 Jun 0.96 0.95 0.96 0.90 0.97 0.97 0.96 0.98 0.98 0.96 0.96 0.91 0.95+.0.025 Jul 0.99 1.00 0.98 0.97 0.98 0.95 0.92 0.97 0.95 0.98 0.99 0.90 0.967+0.030 Aug 0.95 1.00 1.00 0.88 0.97 0.97 0.99 0.99 0.99 0.96 0.94 0.99 0.969+0.034 Sep 1.00 0.99 1.00 1.00 0.98 0.99 0.89 0.99 1.00 0.98 0.95 0.99 0.98+0.0316 Oct 0.95 0.96 0.97 0.95 0.90 0.94 0.99 0.98 0.92 0.92 0.99 0.96 0.952+0.031 Nov 0.97 0.95 0.94 0.99 0.97 0.96 0.96 0.98 0.95 0.98 0.96 0.91 0.96+0.0213 Dec 0.93 0.94 0.99 0.96 0.98 0.99 0.96 0.98 0.98 0.97 0.97 0.99 0.97+0.0195 Jan 10 0.99 0.99 0.97 0.99 0.99 0.97 0.98 0.99 0.98 0.98 0.98 0.98 0.9825+0.00 Feb 0.99 0.98 0.96 0.97 0.99 0.99 0.99 1.00 0.98 0.99 0.99 0.99 0.985+0.011 Mar 0.92 0.99 0.97 0.98 0.96 0.95 0.98 0.97 0.99 0.97 0.96 0.94 0.965+0.021

270

Appendix 21: Seasonal variation in density (total number of individuals/m2) of different species of molluscan fauna collected at the 3 moles of Tarkwa Bay (April, 2008-March, 2010).

MONTH WEST MOLE TRAINING MOLE EAST MOLE TOTA L S W1 W2 WM3 WM4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4 MEAN+SD Apr 08 36 36 37 33 32 28 39 33 27 30 28 21 31.67+ 5.12 May 27 21 29 28 41 30 32 31 21 23 21 20 21.00 +6.21 Jun 19 16 13 17 13 11 21 20 14 16 16 21 16.42+3.32 Jul 12 9 11 8 12 18 13 14 15 12 15 10 12.42+2.81 Aug 6 7 7 9 8 16 15 7 4 8 5 9 8.42+3.63 Sep 5 11 11 12 10 7 10 8 7 6 10 11 9.00+2.30 Oct 16 22 23 20 26 25 29 26 22 25 18 20 22.67+4.75 Nov 28 23 29 28 30 21 14 30 21 20 25 21 24.17+4.99 Dec 32 36 34 36 32 38 46 31 40 42 45 37 37.42+5.00 Jan 09 46 49 51 50 46 47 54 34 41 45 41 50 46.17+5.44 Feb 51 48 46 43 50 47 39 51 50 37 37 31 44.17+6.69 Mar 37 45 41 61 34 50 54 36 41 47 37 36 43.25+8.38 April 37 41 37 40 45 45 45 29 37 36 31 34 38.80+5.33 May 28 24 35 44 31 25 39 34 35 27 31 33 32.17+5.81 June 20 15 14 16 17 9 26 22 15 22 19 309 18.75+5.71 July 13 8 12 19 22 12 12 23 22 12 25 14 16.17+5.65 Aug. 8 10 6 8 25 18 21 21 32 21 20 17 17.25+7.85 Sept. 6 7 9 12 14 17 13 19 9 30 18 19 14.42+6.72 Oct. 27 32 26 31 13 26 36 35 30 33 36 31 29.67+6.33 Nov. 48 25 28 31 41 28 24 31 44 46 45 36 35.58+8.82 Dec. 34 31 32 46 56 46 53 59 51 42 39 65 46.17+11.01 Jan. 41 52 46 51 62 64 40 46 58 49 47 52 50.67+7.57 Feb. 55 59 56 56 51 38 49 49 44 54 42 46 49.92+6.44 March 29 53 37 41 33 29 41 36 39 32 28 370 36.2+5.98 TOTAL 661 680 650 740 744 695 763 725 719 715 689 701 8,486

271

Appendix 22: Seasonal variations in number of individual molluscan fauna (Nos/m2) sampled at three tidal zones at 3 moles of Tarkwa Bay (April, 2008-March, 2010).

MON TIDAL WEST MOLE TRAINING MOLE EAST MOLE TOTA L MARK WM WM WM WM TM1 TM TM TM4 EM EM EM EM 1 2 3 4 2 3 1 2 3 4 Apr High 6 4 7 6 3 7 9 6 3 5 8 4 68 2008 Mid. 11 7 12 5 9 4 12 13 8 7 6 8 102 Low 19 25 18 22 20 17 18 14 16 18 14 9 208 May High 7 3 8 6 4 6 7 6 3 4 6 7 68 2008 Mid. 8 6 9 5 13 9 9 10 6 7 4 5 88 Low 12 12 12 17 24 15 16 15 12 12 11 8 160 Jun High 4 4 2 4 2 2 4 3 2 3 4 7 43 2008 Mid. 6 5 4 5 4 5 7 5 4 5 3 6 59 Low 9 8 7 8 7 4 10 12 8 8 9 8 98 Jul High 2 1 4 1 3 3 4 3 5 2 4 3 35 2008 Mid. 3 3 2 3 4 5 3 4 6 4 5 2 44 Low 7 5 5 4 5 10 7 7 4 6 6 5 70 Aug High 1 2 2 2 1 4 1 1 1 3 1 3 24 2008 Mid. 2 2 3 5 3 5 2 2 1 1 1 2 32 Low 3 3 2 2 5 7 4 4 2 4 3 4 46 Sep High 1 2 1 2 1 2 2 3 2 1 2 1 21 2008 Mid. 1 5 4 4 12 1 3 2 2 2 3 4 34 Low 3 4 6 6 7 14 5 3 3 3 5 6 56 Oct High 3 5 5 6 8 5 6 5 5 6 4 5 63 2008 Mid. 6 7 7 5 6 8 9 8 7 9 6 7 85 Low 7 10 11 9 12 12 14 13 10 10 8 8 124 Nov High 6 5 8 7 8 4 2 6 4 3 6 4 65 2008 Mid. 9 8 9 9 9 7 5 8 7 7 10 7 97 Low 13 10 12 12 13 10 7 16 10 10 9 10 132 Dec High 6 7 5 9 6 8 10 6 10 8 9 8 92 2008 Mid. 10 9 8 7 9 10 16 9 13 13 13 11 125 Low 16 20 21 20 16 18 20 16 17 21 23 18 222 Jan High 9 10 11 9 8 10 10 5 9 10 12 9 116 2009 Mid. 14 14 16 12 16 14 19 12 13 14 19 15 164 Low 23 25 24 29 22 23 25 19 19 21 20 26 270 Feb High 11 10 9 10 14 9 6 12 10 7 8 6 119 2009 Mid. 18 17 16 14 10 13 11 19 18 12 13 9 164 Low 22 21 21 19 26 25 22 20 22 18 16 16 248 Mar High 7 11 8 14 10 11 134 9 9 9 8 9 119 2009 Mid. 11 13 12 21 10 13 16 11 14 12 11 16 154 Low 19 21 21 26 14 26 25 16 18 26 18 17 242

272

Appendix 22 Cont: Seasonal variations in number of individual molluscan fauna (Nos/m2) sampled at three tidal levels at 3 moles of Tarkwa Bay (April, 2008-March, 2010)

Tidal W1 W2 WM3 W4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4 Total mark Apr High 7 9 8 10 11 10 8 5 6 5 3 6 91 2009 Mid. 11 14 10 14 20 16 10 6 10 12 8 10 151 Low 19 18 19 16 14 19 20 18 21 19 20 18 211 May High 5 4 8 7 5 4 9 7 18 3 5 7 69 2009 Mid. 8 5 6 6 10 7 12 11 18 6 10 11 93 Low 15 15 15 22 16 14 18 16 19 18 16 15 160 Jun High 4 3 1 3 5 1 7 4 3 3 4 6 39 2009 Mid. 7 4 5 4 2 2 8 8 5 9 5 8 59 Low 9 8 8 9 10 6 11 10 7 10 10 16 95 Jul High 1 4 1 5 3 2 1 3 4 2 3 2 31 2009 Mid. 4 7 3 6 9 3 4 6 4 4 10 5 46 Low 9 2 8 8 10 7 7 12 14 6 12 7 72 Aug High 1 1 0 2 3 1 3 3 11 1 2 3 22 2009 Mid. 3 3 2 2 12 3 8 9 12 8 6 6 31 Low 4 6 4 4 10 14 10 9 13 12 12 8 49 Sep High 1 0 1 4 2 3 3 3 2 1 2 0 28 2009 Mid. 2 2 4 3 3 5 2 6 2 10 7 4 31 Low 3 5 4 5 9 9 8 10 5 19 9 15 49 Oct High 3 4 5 4 3 6 5 10 4 7 7 3 59 2009 Mid. 10 7 7 6 4 9 12 11 11 12 11 7 90 Low 19 21 14 21 6 11 8 14 15 14 18 21 125 Nov High 3 5 5 4 5 4 3 6 5 3 7 5 52 2009 Mid. 17 6 8 12 10 7 5 10 15 16 12 12 96 Low 28 14 15 15 26 17 16 15 24 27 26 19 141 Dec High 4 4 5 9 14 9 12 12 13 9 6 14 111 2009 Mid. 10 8 9 12 18 16 18 18 18 12 14 23 172 Low 20 19 18 25 24 21 23 29 20 21 19 28 265 Jan High 8 13 7 13 14 9 8 11 12 11 10 9 132 2010 Mid. 13 17 17 12 23 26 12 15 20 15 14 13 194 Low 20 22 22 26 25 29 20 20 26 23 23 28 275 Feb High 12 13 9 14 11 6 11 11 10 12 8 12 132 2010 Mid. 15 16 17 18 17 16 15 12 11 14 12 16 177 Low 28 30 29 24 23 16 21 26 23 28 22 18 293 Mar High 6 13 7 11 8 6 10 7 8 5 4 7 197 2010 Mid. 9 17 12 12 11 9 14 10 19 8 9 11 157 Low 14 23 18 18 14 14 17 19 12 19 15 19 202 Total 630 666 672 706 698 667 721 666 655 640 596 625

273

Appendix 23: Seasonal variation in the number of species (S) computed for the community of molluscan fauna sampled at the three moles of Tarkwa Bay (April, 2008- March, 2010)

MONTH WESTBREAKWATERS TRAINING BREAK. EAST BREAKWATERS WATERS WM1 WM2 WM3 WM4 TM1 TM2 TM3 TM4 EM1 EM2 EM3 EM4

Apr-08 6 7 8 7 7 6 7 8 5 7 6 6 May-08 6 6 7 5 3 9 6 5 5 7 5 7 Jun-08 4 3 3 5 5 6 6 6 4 5 5 6 Jul-08 4 2 3 4 2 3 3 4 3 4 4 3 Aug-08 4 2 4 4 3 4 4 3 2 3 2 3 Sep-08 2 4 3 4 5 3 4 4 3 3 4 5 Oct-08 4 5 5 4 5 7 7 7 7 6 5 5 Nov-08 6 6 8 8 7 6 5 6 4 6 5 6 Dec-08 6 S 5 7 6 7 10 4 11 8 7 6 Jan-09 8 6 9 6 8 7 9 5 6 8 6 7. Feb-09 7 6 9 5 9 6 6 7 10 6 6 7 Mar-09 6 5 7 8 7 7 S 4 5 5 6 5 Apr-09 5 5 6 5 7 6 7 4 6 5 5 6 May-09 4 5 7 7 5 4 5 6 8 5 5 5 Jun-09 5 3 4 5 3 3 6 5 4 6 5 5 July-09 5 3 4 5 3 3 6 5 4 6 5 5 Aug-09 4 2 2 3 5 5 3 3 5 4 4 3 Sep-09 4 2 2 3 A 5 3 3 5 4 4 3 Oct-09 3 2 3 2 3 2 4 5 3 6 4 5 Nov-09 9 7 6 7 5 7 6 6 5 7 6 6 Dec-09 7 8 5 9 10 8 10 9 10 8 7 10 Jan – 09 7 6 8 8 9 9 6 6 9 8 7 9

274

Appendix 24: Studies on growth of Patella spp in natural and artificial environments investigated at the East moles of Tarkwa Bay (May, 2008 - July 2009).

NATURAL ENVIRONMENT (EAST MOLE) ARTIFICIAL (LABORATORY)

MONTH Patella spp (only) Patella spp + Nerita spp Patella spp (only) Patella spp + Nerita spp TIDAL LEVEL TIDAL LEVEL HIGH LOW MID HIGH LOW MI)D TANK 1 TANK 2 MAY 2008 564 5.56 5.52 5.61 5.53 5.04 6.13 5.86 JUNE 6.40 6.10 5.93 5.83 5.90 5.53 7.03 5.63 JUL 6.50 6.30 6.01 5.98 6.10 5.86 8.54 7.75 AUG 6.90 6.54 6.28 6.50 6.26 5.90 9.68 3.61 SEPT 7.20 6.90 6.85 6.90 6.56 6.36 10.54 9.58 OCT 7.80 7.20 7.10 7.26 6. 94 6.70 11.24 10.12 NOV 8.40 7.40 7.30 7.87 7.10 701 12.03 11.63 DEC 8.60 7.70 8.10 S.20 7.30 7,90 12.74 12.2 JAN 2009 9.20 8.30 8.60 8.90 7.96 8,20 13.65 13.30 FEB 9.56 8.89 9.10 9.30 8.30 S.70 14.31 14.10 MAR 10.10 9.41 9.30 9.70 8.90 9.10 15.02 14.85 APR 10.50 9.86 9.70 10.30 9.46 9.30 15.64 15.51 MAY 11.10 10.50 10.20 10.60 9.94 9.80 16.02 15.80 JUN 1140 11.10 10.80 11.10 10.48 10.50 16.51 16.20 JUL 11.90 11.64 13.40 11 30 11.10 11.60 17.10 16.91

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Appendix 25: Mean seasonal variations of heavy metal (µ g/g dry Weight) in different body parts of selected molluscan species investigated in dry season at the West mole of Tarkwa Bay (April, 2008-March, 2009) SPECIES HEAVY METAL BODY TISSUE MANTLE FOOT SHELL SEAWATER Nerita senegalensis Mn 164.1+1.70 86.40±1.30 124.22±1.61 20.34+0.54 186.4±6.14 Pb 0.04+0.01 0.0±0.001 0.08±0.001 1.10±0.01 2.14+0.001 Cr 1.12±0.51 1.10±0.01 0.07±0.01 0.05±0.001 3.12+0.001 Fe 42.3+0.41 12.60±0.01 6.40±0.001 3.14±0.002 68.14+3.16 Zn 15.21+ 0.46 8.14±1.14 5.31±0.01 2.34±0.004 15.12+1.41 Cu 3.1±0.09 234±0.19 1 .48±0.02 0.96±0.001 22.20+1.90 Patella safiana Mn 186.3±1.64 58.6±1.6 36.16±1.30 9.63±1.10 224+6.43 Pb 1.17±0.06 1.0±0.001 0.80±0.01 0.34±0.002 2.0±0.001 Cr 2.10±0.001 0.90±0.01 0.76±0.001 0.46±0.001 2.88+0.02 Fe 49.60±0.01 9.61±0.02 4.74±0.03 2.9fct0.03 59.61+7.11 Zn 56.31±2.20 22.10±1.4 11.34±0.06 6.34+2.31 64.73±5.20 Cu 6.46±0.80 3.94±1.10 1.96±0.01 1 .22±0.04 12.68+0.01 Thais callifera Mn 186.20±2.30 76.14±1.80 87±6.14 36.34±7.17 241.01+6.14 Pb 0.08±0.03 0.02±0.01 0.05±0.0001 0.03±0.001 1.10+0.04 Cr 1.9±0.04 0.08±0.01 1.10±0.001 0.0S+0.002 2.44+0.01 Fe 63.12±7.10 15.14±0.0± 1 36.15±1.90 12.34+L13 156.74+0.12 Zn 66.3±8.40 24.31±1.80 42.3±4.10 9.14+0.90 121.14+2.80 Cu 12.6±1.20 4.61±0.90 8.12±0.41 5.61±0.12 44.60+1.33 Buccinum undatum Mn 266.61±12.60 61.4±5.0 86.11 ±7.61 34.36+2.02 286.4±8.60 Pb 1.96±0.08 1.10±0.10 1.30±0.10 1.10+0.09 2.12+0.10 Cr 3.12±0.10 2.10±0.02 3.01±0.10 2.31+0.04 4.43+0.04 Fe 86.14±6.40 37.10±6.10 48.10±0.30 15.6±0.16 124.60±6.18 Zn 59.7±5.14 26.30+5.10 5±.16±8.60 22.16±1.30 156.74+0.12 Cu 22.14± 1.64 12.94±1.90 15.31± 4.14 9.17+1.19 56.76±4.18

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Appendix 26: Mean seasonal variations of heavy metal (µ g/g Dry Weight) in different body parts of selected molluscan species at the West mole of Tarkwa Bay (April, 2008-March 2009). SPECIES HEAVY METAL BODY TISSUE MANTLE FOOT SHELL SEAWATER Nerita senegalensis Mn 122.14±3.41 58.36±2.41 96.64±234 16.61 ±0.86 163.6±7.1 Pb 0.02±0.003 0.0±0.001 0.06±0.001 0.03±0.01 2.01±0.001 Cr 0.09±0.026 0.06±0.001 0.04±0.001 0.03±0.001 2.14±0.01 Fe 38.60±1.14 9.14±0.001 5.96±0.002 2.17±0.002 56.14±2.01 Zn 13.67±1.01 6.36±0.09 3.96±0.001 2.20±0.01 13.61 ±1.20 Cu 3.30±1.01 3.96±0.12 1.23±0.010 0.66±0.01 18.96±1.40 Patella safiana Mn 157.60±1.96 52.94±1.42 31.76±1.96 7.88±2.10 198.6±9.90 Pb 1.10±0.003 0.92±0.001 0.65±0.002 0.24±0.02 1.96±0.04 Cr 1.97±0.001 0.71±0.002 0.56±0.003 0.36±0.001 2.20±0.03 Fe 44.76±1.12 7.76±0.10 3.34±0.04 2.48±0.03 56.34±1.20 Zn 54.41±2.01 18.96±0.60 9.4l±0.±0 5.64±1.10 60.14±1.60 Cu 5.94±0.96 2.94±0.06 1.58±0.20 1.02±0.002 9.93±1.10 Thais callifera Mg 166.4±8.63 66.20±.40 63.91±5.50 31.96±1.20 221.0±8.0 Pb 0.06±0.001 0.04±0.001 0.05±0.01 0.035±0.01 0.9±0.001 Cr 1.86±0.010 0.06±0.001 1.01±0.001 0.06±0.001 2.0±0.01 Fe 56.4±3.20 12.46±1.01 31.65±1.10 9.56±1.12 152.74±8.1 Zn 44.93±6.70 23.10±1.21 36.83±3.90 7.96±0.50 114.60±8.70 Cu 9.64±0.90 3.94±0.10 6.31±0.20 3.72±0.12 41.30±1.70 Buccinum undatum Mg 248.3 1±7.10 54.60±5.10 74.14±5.10 31.96±1.01 261.61±9.10 Pb 1.66±0.10 1.94±0.30 1.29±0.10 0.96±0.01 1.96±0.10 Cr 1.86±1.10 0.86±1.01 1.76±0.12 1.56±0.02 3.30±0.10 Fe 77.24±6.10 35.63±3.41 44.80±4.10 8.90-L0.17 1143±1.70 Zn 58.34±6.14 24.60±4.10 51.20±4.10 20.14±1.10 76.10±1.40 Cu 19.43=1.23 9.72±1.20 13.14±1.14 7.14±1.12 53.76±2.00

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Appendix 27: Mean concentrations of heavy metals in seawater, seaweed and selected molluscan species investigated in dry season at the 3 moles of Tarkwa Bay.

Mole HEAVY METAL CONCENTRATION (µ g/g dry weight)

SAMPLE Cd Co Cr Fe Pb Mn Zn Cu Hg Ni

WEST SEA 0.34± 0.02 2.30± 0.06 0.43± 0.002 24.2± 0.08 0.40± 0.30 83.26± 0.31 9.10± 0.31 9.12± 0.20 0.01± 0.001 0.07± 0.01 SURFACE WATER

SEAWEED 0.88± 0.37 7.52± 0.15 2.56± 0.03 39.25± 0.13 0.09± 0.01 175.88± 0.54 132.45± 1.92 24.40±192 0.20± 0.05 0.1 2± 0.001

Patella safiana 1.16± 0.04 11.50± 0.17 12.23± 0.14 57.35± 0.31 0.18± 0.02 361.61± 0.34 144.85±1.71 119.10± 0.36 0.24± 0.05 0.82± 0.02

TRAINING SEA 0.1 5± 0.01 2.18± 0.05 0.4± 0.01 0.34± 0.02 0.14± 0.02 63.3± 1.80 94.87± 1.82 13.6± 0.36 0.04± 0.006 0.02± 0.008 SURFACE WATER

SEAWEED 0.73± 0.01 7.25± 0.13 2.50± 0.06 22.63± 0.17 0.43± 0.02 142.10± 0.92 125.68± 0.82 48.38± 0.52 0.1 2± 0.02 0.24± 0.06

Patella safiana 1.61± 0.06 11.53± 0.17 8.05± 0.11 38.8± 0.62 0.58± 0.12 294. 1± 7.50 255.73± 6.07 126.3±2.41 0.20± 0.001 0.74± 0.01

EAST SEA 0.87± 0.05 4.16± 0.13 0.53 ± 0.03 2.40 ± 0.001 0.14± 0.04 11 2.0± 1.33 114.0± L40 36.30± 0.33 0.04± 0.001 0.06± 0.001 SURFACE WATER

SEAWEED 142±0.01 10.20± 0.01 4.82± 0.10 20.84± 0.10 0.24± 0.05 124.0± l.S0 133.75± 1.51 65.25± ±0.34 0.1 6± 0.05 0.13± 0.01

Patella safiana 2.40± 0.13 16.3± 0.08 24.4± 0.29 32.38± 0.36 0.73± 0.02 363.0± 1.25 213.73± 1.20 116.2± 1.10 0.43± 0.03 0.94± 0.01

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Appendix 28: Mean concentration of heavy metals in seawater, seaweed and selected molluscan species investigated in dry season at the 3 moles of Tarkwa Bay in dry season.

BREAKWATERS HEAVY METAL CONCENTRATION (µ g/g dry weight)

SAMPLE Cd Co Cr Fe Pb Mn Zn Cu Hg Ni

WEST SEA SURFACE 0.34± 0.02 2.30± 0.06 0.43± 0.002 24.2± 0.08 0.40± 0.30 83.26± 0.31 9.10± 0.31 9.12± 0.20 0.01± 0.001 0.07± 0.01 WATER

SEAWEED 0.88± 0.37 7.52± 0.15 2.56± 0.03 39.25± 0.13 0.09± 0.01 175.88± 0.54 132.45± 1.92 24.40±192 0.20± 0.05 0.1 2± 0.001

Patella safiana 1.16± 0.04 11.50± 0.17 12.23± 0.14 57.35± 0.31 0.18± 0.02 361.61± 0.34 144.85±1.71 119.10± 0.36 0.24± 0.05 0.82± 0.02

TRAINING SEA SURFACE 0.1 5± 2.18± 0.05 0.4± 0.01 0.34± 0.02 0.14± 0.02 63.3± 1.80 94.87± 1.82 13.6± 0.36 0.04± 0.006 0.02± WATER 0.01 0.008

SEAWEED 0.73± 0.01 7.25± 0.13 2.50± 0.06 22.63± 0.17 0.43± 0.02 142.10± 0.92 125.68± 0.82 48.38± 0.52 0.1 2± 0.02 0.24± 0.06

Patella safiana 1.61± 0.06 11.53± 0.17 8.05± 0.11 38.8± 0.62 0.58± 0.12 294. 1± 7.50 255.73± 6.07 126.3±2.41 0.20± 0.001 0.74± 0.01

EAST SEA SURFACE 0.87± 0.05 4.16± 0.13 0.53 ± 0.03 2.40 ± 0.001 0.14± 0.04 11 2.0± 1.33 114.0± L40 36.30± 0.33 0.04± 0.001 0.06± WATER 0.001

SEAWEED 142±0.01 10.20± 0.01 4.82± 0.10 20.84± 0.10 0.24± 0.05 124.0± l.S0 133.75± 1.51 65.25± ±0.34 0.1 6± 0.05 0.13± 0.01

Patella safiana 2.40± 0.13 16.3± 0.08 24.4± 0.29 32.38± 0.36 0.73± 0.02 363.0± 1.25 213.73± 1.20 116.2± 1.10 0.43± 0.03 0.94± 0.01

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Appendix 29: Mean concentration of heavy metals in seawater, seaweed and selected molluscan species investigated in rainy season at the 3 moles of Tarkwa Bay.

MOLE HEAVY METAL CONCENTRATION (µ g/g dry weight) SAMPLE Cd Co Cr Fe Pb Mn Zn Cu Hg Ni WEST Sea surface 2.63± 0.15 1.30± 0.09 1.14± 0.05 39.23± 0.20 0.05± 0.005 18.45± 0.34 16.35± 0.23 14.72± 0.46 N.D 0.94± 0.04 water. Seaweed 6.15± 0.11 3.80± 0.06 3.16± 0.17 54.34± 0.18 0J0± 0.09 36.08± 1.14 22.03± 1.2 26.40± 0.18 0.12± 0.07 1.14± 0.06 Patella 9.07± 0.22 5.0± 0.36 8.73± 0.18 82.05± 0.32 0.1 2± 0.02 43.91± 0.66 36.14± 0.04 41.04± 0.85 0.03±0.004 1.47± 0.06 safiana TRAINING Sea surface 3.07± 0.15 0.48± 0.09 0.14± 0.04 41.56± 0.54 0.09± 0.01 22. 0± 0.43 24.0 1± 0.31 22.03± 0.68 0.01±0.004 1.11± 0.02 water Seaweed 7.43± 0.16 1.81± 0.11 0.64± 0.06 57.68± 0.49 0.1 7±0.02 48.68± 0.45 37.00± 0.63 55.90± 0.49 0.03± 0.01 1.43± 0.05 Patella 11.23± 0.84 4.17± 0.13 1.09± 0.03 65.32± 1.15 0.27± 0.02 63.48± 0.43 49.06± 0.97 59.08 ± 0.8 0.08±0.008 2.18± 0.14 safiana EAST Sea surface 3.73± 0.72 1.39± 033 0.38± 0.11 34.23± 1.96 0.32± 0.14 31.00± 0.71 14.65± 0.69 29.83± 0.86 0.02± 0.01 1.74± 0.10 water Seaweed 11 .68± 0.35 3.48± 0.08 0.89± 0.10 53.95±1.27 0.25± 0.04 53.73± 0.29 68.40± 1.29 33.90± 0.91 0.03± 0.01 4.98± 0.99 Patella 16.01± 0.65 6.50± 0.43 1.48d±0.18 77.02±2.29 0.36± 0.03 64.60± 1.42 111.2± 4.78 41.20± 1.02 0.06± 0.03 7.21± 0.07 safiana

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