V * j ( U 8 . (  S S i  h i  THE BALME LIBRARY
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G370418 3 0692 1000  3471 7
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UNIVERSITY OF GHANA
THE POPULATION PARAMETERS, FOOD HABITS AND 
PHYSICOCHEMICAL ENVIRONMENT OF THREE CICHLID SPECIES IN 
THE SOUTHWESTERN SECTOR OF THE KETA LAGOON
A THESIS
SUBMITTED TO THE DEPARTMENT OF OCEANOGRAPHY AND FISHERIES
BY
SELORM DZAKO ABABIO B.Sc. (HONS)
(10031643)
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF A 
MASTER OF PHILOSOPHY DEGREE IN FISHERY SCIENCE
DECEMBER 2001
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This thesis is the result of research work undertaken by me in the Department 
of Oceanography and Fisheries, University of Ghana, under the supervision of 
Professor C. J. Vanderpuye and Mr. A. K. Armah.
DECLARATION
(Selorm Dzako Ababio) 
Student
(Professor C. J. Vanderpuye 
Supervisor
..........
(Mr. A. K. Armah) 
Supervisor
External Examiner
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DEDICATION
This work is dedicated to my mother, Angele R. Ababio and my father, Obed 
K. Ababio for educating me to this level, and to Yayra, my fiancee, for giving 
me a new focus in life.
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ACKNOWLEDGEMENT
I would like to acknowledge the immense help of Professor C. J. Vanderpuye 
and Mr. A. K. Armah in this study, and especially the latter for mobilizing funds 
for the research work and guiding me though the entire study.
I would like to say a big thank you to the following who ably assisted me in my 
field and laboratory studies: Messrs. E. Klubi, E. Lamptey, E. Armah, K. Obiri 
and Gameli. I would also like to thank all members of staff of the Department 
of Oceanography and Fisheries, especially driver O. Koney, for their help 
during my work.
I would like to say a special thank you to Messrs. Sam Addo, G. Darpaah, F. 
K. E. Nunoo and G. Wiafe for their constructive criticisms and suggestions 
during the writing of this thesis.
I would also like to acknowledge Environmental Solutions Ltd. of Ghana and 
Resource Planning Inc. of South Carolina for sponsoring the field aspect of 
this work and for allowing me to use their equipment during the study.
Finally, I would like to thank my brothers and sisters and all my friends for 
being there for me in times of need and want. May God richly bless you all.
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TABLE OF CONTENTS
Declaration
Page No. 
ii
Dedication iii
Acknowledgement iv
Table of Content v
List of Tables vii
List of Figures viii
Abstract xii
Chapter 1: Introduction 1
Chapter 2: Literature Review 6
2.1 The Keta lagoon 6
2.2 The lagoonal fishery 9
2.3 The cichlids 10
2.4 Growth model and parameters 12
2.5 Sediment and benthic fauna 16
Chapter 3: Materials and Methods 18
3.1 Study site 18
3.2 Description of sampling stations 19
3.3 Sampling 20
3.4 Laboratory analysis 23
Chapter 4: Results 27
4.1 Water physical and chemical parameters 27
4.2 Sediment grain size distribution 44
V
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4.3 Sediment organic (detrital) matter content 48
Page No.
4.4 Benthic fauna diversity 49
4.5 Population parameters of major fishery 53
4.6 Food habit studies 65
Chapter 5: Discussion 69
5.1 Water physicochemical parameters 69
5.2 Benthic studies 73
5.3 Fishery studies 76
Chapter 6: Conclusions and Recommendations 80
6.1 Conclusion 80
6.2 Recommendations 83
References 85
Appendix 96
Appendix A: Water physicochemical parameters 97
Appendix B: Sediment grain size distribution 99
Appendix C: Sediment organic matter content 100
Appendix D: Diversity indices 101
Appendix E: Length-frequency distribution of fish 102
Appendix F: Plates 103
vi
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LIST OF TABLES
Table No.
Table 2.0
Table 2.1
Table 3.0 
Table 4.0
Table 4.1
Table 4.2
Table 4.3
Table 4.4
Table 4.5
Description
Population parameters for S. melanotheron
melanotheron, T. guineensis and H. fasciatus (from 
Fishbase)
Population parameters for S. melanotheron
melanotheron from the Keta lagoon (Ofori-Danson 
etal., 1999)
Coordinates of sampling stations in study area 
Benthic macrofauna presence/absence data for 
stations sampled
Benthic macrofauna presence/absence data for 
months sampled
Population parameters estimated for the fish
species
Longevity and growth performance index for the 
three cichlid species
Mortality parameters and exploitation ratio estimated
for the three cichlid species
Food items of the three Cichlid species
vii
Page No.
13
14 
19
50
50
57
60
63
65
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LIST OF FIGURES
Figure No.
Figure 1.0 
Figure 3.0 
Figure 4.0
Figure 4.1
Figure 4.2 
Figure 4.3 
Figure 4.4 
Figure 4.5 
Figure 4.6
Figure 4.7
Description
Map of the Keta lagoon
Map of the study area showing sampling stations 
Mean monthly salinity and conductivity distribution 
with standard deviation bars for the study area 
Mean monthly total dissolved solids (TDS) 
distribution with standard deviation bars for the 
study area
Mean station values of salinity and conductivity 
with standard deviation bars for the study area 
Mean station values of total dissolved solids (TDS) 
with standard deviation bars for the study area 
Mean monthly pH distribution with standard 
deviation bars for the study area 
Mean station values of pH with standard deviation 
bars for the study area
Mean monthly dissolved oxygen (DO) and water 
temperature distribution with standard deviation 
bars for the study area
Mean monthly values of dissolved oxygen (DO) 
and water temperature with standard deviation 
bars for the study area
viii
Page No.
2
20
27
28 
29
29
30
31
32 
32
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Figure 4.8
Figure 4.9 
Figure 4.10 
Figure 4.11 
Figure 4.12 
Figure 4.13 
Figure 4.14 
Figure 4.15 
Figure 4.16
Figure 4.17
Figure 4.18
Figure No.
Mean monthly nitrate distribution with standard
deviation bars for the study area
Mean station values of nitrate with standard
deviation bars for the study area
Mean monthly phosphate distribution with
standard deviation bars for the study area
Mean station values of phosphate with standard
deviation bars for the study area
Mean monthly sulphate distribution with standard
deviation bars for the study area
Mean station values of sulphate with standard
deviation bars for the study area
Mean monthly silicate distribution with standard
deviation bars for the study area
Mean station values of silicate with standard
deviation bars for the study area
Mean monthly total suspended solids (TSS) and
turbidity distribution with standard deviation bars
for the study area
Mean station values of suspended solids (TSS) 
and turbidity with standard deviation bars for the 
study area
Cluster analysis (Bray-Curtis) of the water 
physicochemical parameters
Description
ix
33
Page No.
34
35
35
36
37
38
38
39
40
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Figure 4.19 MDS plot of water physicochemical parameters 43
Figure 4.20 Spatial distribution of sediment in study area 44
Figure 4.21 Temporal distribution of sediment in study area 45
Figure 4.22 Cluster analysis (Bray-Curtis) dendrogram for
grain size distribution in study area 47
Figure 4.23 MDS plot of grain size distribution in study area 47
Figure 4.24 Spatial distribution of sediment organic matter
content in study area 48
Figure 4.25 Temporal distribution of sediment organic matter
content in study area 49
Figure 4.26 Spatial distribution of diversity indices for study
area 52
Figure 4.27 Temporal distribution of diversity indices for study
area 53
Figure 4.28 Length-frequency distribution for S. melanotheron
melanotheron in study area 54
Figure 4.29 Length-frequency distribution for T. guineensis in
study area 55
Figure 4.30 Length-frequency distribution for H. fasciatus in
study area 55
Figure 4.31 Length-weight relationship for S. melanotheron
melanotheron in study area 56
Figure 4.32 Length-weight relationship for T. guineensis in
study area 56
Figure No. Description Page No.
x
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Figure 4.33 Length-weight relationship for H. fasciatus in study
area 57
Figure 4.37 Derived growth curve for S. melanotheron
melanotheron in study area 58
Figure 4.38 Derived growth curve for T. guineensis in study
area 59
Figure 4.39 Derived growth curve for H. fasciatus in study area 59
Figure 4.40 Length-converted catch curve for S. melanotheron
melanotheron 61
Figure 4.41 Length-converted catch curve for T. guineensis 61
Figure 4.42 Length-converted catch curve for H. fasciatus 62
Figure 4.43 Recruitment pattern for S. melanotheron
melanotheron 63
Figure 4.44 Recruitment pattern for T. guineensis 64
Figure 4.45 Recruitment pattern for H. fasciatus 64
Figure 4.46 Feeding strategy and prey importance for S.
melanotheron melanotheron 66
Figure 4.47 Feeding strategy and prey importance for T.
guineensis 66
Figure 4.48 Feeding strategy and prey importance for H.
fasciatus 67
Figure No. Description Page No.
xi
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ABSTRACT
The study was carried out in the southwestern sector of the Keta lagoon, a 
closed coastal lagoon located in the southeastern part of Ghana. The study 
was aimed at studying the population parameters and the feeding habits of 
the major fish species (in terms of catch) in the lagoon in relation to the 
prevailing physicochemical parameters and the benthic macrofauna of the 
area.
The water physicochemical parameters studied included the electrochemical 
and the optical properties of the water as well as the nutrients available for 
production. Macrobenthic fauna studies were also carried out, in relation to 
sediment grain size distribution and organic matter content, as an index of the 
ecological state of the area. The findings from the study indicate that the 
seasonal precipitation pattern of the area was mainly responsible for 
fluctuations in the lagoon water physicochemical regime during the period of 
the study. The benthic fauna diversity did not indicate any effect of any 
external perturbation on the lagoonal environment, except salinity changes.
The study on the fishery resource of the lagoon indicated that even though the 
resource is highly exploited, it is able to maintain itself by rapid reproduction at 
an early age. However, if exploitation is maintained at or above the current 
rate, its effect, coupled with that of the stressful environment could result in 
diminishing catches, with catches comprising mainly of small-bodied fishes.
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1CHAPTER ONE 
INTRODUCTION
The Keta lagoon is a closed lagoon located in the southeastern corner of the 
Republic of Ghana (Figure 1.0). It stretches for about 40 km along the 
coastline, and covers an approximate area of 350 km2. The lagoon serves as 
a major source of finfish and other fishery products (e.g. shrimps, crabs) to its 
fringing communities, among which are Anloga, Woe, Keta , Kedzi, Anyako, 
Alakple, Atiavi and Fiahor.
The fishery of the Keta lagoon covers diverse groups of organisms including 
several finfish species, gastropods and crustaceans. However, the dominant 
species caught belong to the Family Cichlidae. These include Sarotherodon 
melanotheron melanotheron, Tilapia guineensis, and Hemichromis fasciatus 
(Addo, 2000; Ofori-Danson et al., 1999; Shenker et at., 1998; Armah et al., 
1997). This cichlid fishery is of cardinal importance to the fringing 
communities since it serves as a major source of dietary protein, employment 
and revenue generation; the fishes caught from the lagoon are either used for 
food domestically or are processed and sold.
Access to the lagoonal fishery is not restricted though certain riparian 
communities, such as Atiavi, have imposed taboo days when fishing is 
prohibited. Such prohibitions, however, are of local effect and do not prevent 
fishing in the lagoon as a whole. Consequently, the fishery is exploited 
continually throughout the year.
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Figure 1.0: Map of the Keta lagoon showing the Study Area
O'SO' roo '
'Anyako Agavedzi
KETA
LAGOON
Havedzi
W Vodza
Ozelul
KETA
Study Area
GULF OF GUINEA
ape Saint Paul
□  WETLANDS
s 
0
KILOMETERS
0°50‘ 0°55' 1*00'
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3The other uses of the lagoon include salt mining during the dry seasons and 
water transport. Some of the aquatic plants are harvested for mat making 
(Cyperus articulatus) and for fish processing (Sesuvium sp., Phylloxerus sp.). 
Shallots (Allium ascalonicum) and other short duration annuals such as 
maize, pepper and cassava are extensively cultivated on the sandbar 
separating the lagoon from the sea (Armah et al, 1997). The Keta lagoon is 
also important as an avifauna site and a Ramsar site. It is home to over 46 
species of waterfowls comprising terns, herons, egrets and waders with peak 
counts in excess of 40,000 birds (Piersma and Ntiamoa-Baidu, 1995).
Tropical coastal lagoons generally experience widely fluctuating salinity 
regimes and water levels that induce an immense stress on the lagoonal 
ecosystem (Barnes, 1980). The synergistic effect of this stress, coupled with a 
high and unsustainable fishing pressure puts a severe stress on the lagoonal 
fishery, resulting in stunted fish populations (Blay and Asabere-Ameyaw,
1993) and a potential for a collapsed fishery (Pauly et al, 1989). However, due 
to the unavailability of historic data for most tropical coastal lagoons, it is 
difficult determining the effects stresses of this nature may have on the 
fishery. As a result, devising management strategies and plans for the 
sustainable utilization of the lagoonal fisheries resource is not easily 
achievable.
Historical work done on the fishery of the Keta lagoon is rather limited, 
principal among which are those of Shenker et al. (1998), Ofori-Danson et al.
(1999) and Addo (2000). The work done by Shenker et al. (1998) and Ofori-
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Danson et al. (1999) formed part of the environmental baseline studies for the 
Ghana Coastal Wetlands Management Project and covered relatively short 
durations; their focus was on a narrow range of physicochemical parameters. 
The various authors recommended an extensive study/monitoring of the 
fishery over a long-term period, especially in relation to population parameters 
of the fishery. Work done by Addo (2000) focused primarily on the Acadja 
fishery of the Keta lagoon and determined some population parameters and 
fecundity indices of the major cichlids in the lagoon.
The current study was carried out in the southwestern sector or the Anloga 
end of the lagoon. This area is heterogeneous and consists of identifiable 
habitats such as vegetated areas, open waters, muddy and sandy bottoms 
reminiscent of the entire lagoon. It is also reported by the local fishers to be 
the most productive part of the lagoon in terms offish catch.
The research was aimed at studying the population parameters and the 
feeding habits of the major fish species of the lagoon in relation to the 
prevailing physicochemical parameters and the benthic macrofauna of the 
area. The specific objectives of the study were to:
• Determine the von Bertalanffy growth and mortality parameters 
of the major cichlid species from length-frequency data, as an 
index of the ecological state of the fishery.
• Determine the recruitment pattern and the level of exploitation of 
the fishery from length-frequency data and the population 
parameters.
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5• Study the benthic macrofauna as an index of the ecological 
state (health) of the area, and its role in the fishery of the 
lagoon.
• Study the physicochemical parameters of the water and 
sediment in the study area and determine how they impact on 
the benthic fauna and fishery.
The rest of the thesis is organized into five chapters. Chapter two is a review 
of current and relevant literature on the study, including literature on the 
methodologies adopted during research and data analyses. Chapter three 
discusses the methods employed in sampling design, sample collection and 
analyses both in the field and in the laboratory. Chapter four is the results 
obtained from the study. Chapter five discusses the finding of the study in 
relation to the set objectives and other published findings of similar subject. 
Chapter six contains the conclusions from the study and relevant 
recommendations for management considerations.
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6CHAPTER TWO 
LITERATURE REVIEW
2.1 The Keta Lagoon
The lagoon is located within the coordinates of longitudes 0°48’E and 1°01’E, 
and latitudes 5°48’N and 6°03’N. The climate of the region is tropical with two 
rainy seasons, a major season and a minor season, separated by a relatively 
short dry period occurring between late July and September. The major 
season occurs from March/April to July while the minor season is from 
September to November. This is followed by a second and longer dry period 
lasting until February. The average rainfall of the region is about 700 mm per 
annum. The mean ambient temperature is 27.5°C, the average relative 
humidity above 80% with a 15% seasonal variation. The mean hours of 
insolation is 6.9 hours, ranging from a low of 4.8 hours in June to a high of 8.4 
hours in November (Finlayson et al., 2000).
Geological evidence (Akpati, 1978) shows that the lagoon was formed in the 
Keta basin, a coastal geological subsidence which occurred in the late 
Precambriam era, during the separation of South America from Africa. The 
basal landform is mainly made up of gravel, sand, siltstone, shale and clay 
with layers of fossiliferous limestone (Armah etal., 1997; Akpati, 1978).
The lagoon stretches for about 40 km along the coastline (Piersma and 
Ntiamoa-Baidu, 1995) and, with its associated wetlands, covers an area of 
about 702 km2 (Armah et al., 1997). The open water of the lagoon, however,
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covers an approximate area of 300 km2 with the surface area varying with the 
seasons and water levels (Piersma and Ntiamoa-Baidu, 1995). The mean 
water depth is about 0.8 m (0.6 m -  1.0 m; Biney, 1984) with a maximum 
depth of about 3 m. Bathymetrically, the lagoon floor is plate-like with a gentle 
landward slope (Finlayson et al., 2000).
The salinity regimes prevailing in the lagoon vary considerably with location 
(within the lagoon) and period of year. Piersma and Ntiamoa-Baidu (1995) 
estimated the salinity of the lagoon in a study conducted in late October 1994 
as ranging from less than 40%o (near Woe and Anloga) to greater than 60%o 
(Fiahor). Biney (1984) reported the following physicochemical values for the 
lagoon: water temperature: 32.3°C, pH: 8.1, dissolved oxygen: 7.22 mg/L, 
phosphates: 0.023 mg/L, nitrates: 0.173 mg/L. Biney (1984) summarized the 
lagoon water quality as ‘slightly polluted or of doubtful quality’, as a result of 
fecal and domestic waste which contaminates it at its fringes. Finlayson et al.
(2000) reported that the physicochemical properties of the lagoonal water 
were within the expected range for coastal lagoons in Ghana.
Entsua-Mensah and Dankwa (1997) chronicled three sources of water inflow 
into the Keta lagoon though there are probably more. The following sources 
have been identified (Armah et al., 1997; Entsua-Mensah and Dankwa, 1997; 
Piersma and Ntiamoa-Baidu, 1995; A. K. Armah, pers com):
i. Runoff from the Tordzie River which enters and fills the Avu 
lagoon during the rainy season and overflows into the Keta
7
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lagoon via the Aglor and Agbatsivi lagoons and other smaller 
streams.
ii. Runoff from the Aka and Belikpa streams which enter the lagoon 
directly from the north.
iii. Overwash from the sea across the sandbar at the Havedzi end 
of the lagoon during high tides.
iv. Hydrostatic induced flow of seawater through the sandbar 
separating the lagoon from the sea.
v. Direct precipitation from the atmosphere into the lagoon.
vi. Interflow between the lagoon and the Volta estuary through the 
Anyanui creek.
The sixth source, which was very important prior to the construction of the 
Akosombo and Kpong dams, is currently not very significant as a source of 
inflow to the lagoon (Piersma and Ntiamoa-Baidu, 1995). This phenomenon 
was also observed during a recent study (in which the author participated and 
which is yet to be published) which showed that the tidal force experienced in 
the Volta estuary was not strong enough to move fresh water through the 
Anyanui creek into the lagoon. This has resulted in increased deposition and 
siltation along the canal, further decreasing in the flow rate through the creek. 
The net result is an oscillation of the same parcel of water in the creek 
between tidal minima and maxima.
The only identifiable source of water loss from the lagoon is by evaporation 
(Piersma and Ntiamoa-Baidu, 1995). The freshwater inflow to the lagoon is
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greatly reduced during the dry season resulting in a drastically increased 
salinity in the lagoon during such periods (Piersma and Ntiamoa-Baidu, 1995).
2.2 The Lagoonal Fishery
The Keta lagoon supports a large fishery with the cichlid Sarotherodon 
melanotheron melanotheron dominating the catch (Addo, 2000; Armah et al., 
1997). The other major fishes caught in the lagoon include Tilapia guineensis 
and Hemichromis fasciatus (Addo, 2000; Ofori-Danson et al., 1999). Ofori- 
Danson et al. (1999) have also identified 15 finfish species in addition to two 
crustacean species (Callinectes aminocola and Penaeus sp.) and some 
molluscan species as the fishery resource of the lagoon.
Generally, the fishery resource of the lagoon may be considered in three 
groups consisting of different species (A. K. Armah, pers com). These are:
i. Freshwater species that swim into the lagoon via the streams 
discharging water into the lagoon.
ii. Juvenile forms of marine fishes washed over the sandbar into 
the lagoon from the sea.
iii. Permanent residents, which are indigenous to the lagoon.
The Keta lagoon is fished extensively for its shellfish and finfish resources. 
Crafts used for fishing in the lagoon are mainly canoes made of wooden 
planks (Dankwa and Entsua-Mensah, 1995), though most fishers wade in the 
lagoon for their fishing activities. Fishing methods and gears used in the 
lagoon are reported in Dankwa and Entsua-Mensah (1995); the major ones
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were castnets, gillnets, drag/seine nets, fish weirs, acadja and the tekali 
systems of fishing. Dankwa and Entsua-Mensah (1995) also report that most 
of the gears/methods employed were not sustainable and have the potential 
to negatively impact on the fishery and the ecosystem.
2.3 The Cichlids
The three fish species, S. melanotheron melanotheron, T. guineensis and H. 
fasciatus that form the main focus of this study belong to the fish family 
Cichlidae, Subfamily Pseudocrenilabrinae, Order Perciformes and Class 
Actinopterygii (Carroll, 1988). Cichlids are reported as the largest family of 
fishes while the order Perciformes is also reported as the largest fish order 
(Helfman et a!., 1997; Nelson, 1994). Perciformes occur in marine, freshwater 
and brackishwater environments, and are cosmopolitan in distribution 
(Helfman etal., 1997; Nelson, 1994).
2.3.1 Sarotherodon melanotheron melanotheron
2.3.1.1 Geographic Distribution
Sarotherodon melanotheron melanotheron Ruppell 1852 is indigenous to 
West Africa from Senegal to southern Cameroon. It has, however, been 
introduced into several countries in Asia, Europe and the USA (Trewavas and 
Teugels, 1991).
2.3.1.2 Ecology
The melanic areas in the adult are usually present on the lower parts of the 
head (hence its common name, the blackchin tilapia), the cleithrum and on
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the apices of the caudal and soft dorsal fins. Occasional irregular and 
asymmetrical spots may be observed on the flanks in the form of bands. The 
fish aggregates in schools and is mainly nocturnal with intermittent daytime 
feeding; its food consists of aufwuchs and detritus (Trewavas, 1983) as well 
as bivalves and zooplankton (Diouf, 1996). It is demersal and occurs in 
lagoons and lower reaches of streams (Page and Burr, 1991; Trewavas and 
Teugels, 1991). It is found in freshwater and brackishwater and can tolerate 
wide salinity ranges (Page and Burr, 1991; Trewavas and Teugels, 1991). Its 
optimal pH range is between 7.0 and 8.0 while its depth range is up to 3 m 
(Trewavas and Teugels, 1991).
2.3.2 Tilapia guineensis
2.3.2.1 Geographic Distribution
Tilapia guineensis (Gunther, 1862) is also indigenous to West African coastal 
waters, from the mouth of the Senegal River to the mouth of the Cuanza River 
in Angola (Teugels and Thys van den Audenaerde, 1991).
2.3.2.2 Ecology
It is benthopelagic and feeds on shrimps, bivalves, plankton and detritus 
(Diouf, 1996). It is commonly found in fresh or brackish water but it also 
tolerates high salinities (Teugels and Thys van den Audenaerde, 1991).
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2.3.3 Hemichromis fasciatus
2.3.3.1 Geographic Distribution
Hemichromis fasciatus Peters, 1858, also known as the banded jewelfish, is 
found throughout Africa. Its distribution is reported from Senegal to the Nile 
basin, from Lake Chad to the Congo basin and Upper Zambezi and from Cote 
d’Ivoire and Ghana (Teugels et al., 1988). It is however believed to be widely 
distributed in West Africa (Teugels, 1992). The species occurs in both forest 
and savannah biotopes (Daget and Teugels, 1991) in littoral riverine habitats 
and permanent floodplain lagoons with clear water (Teugels, 1992).
2.3.3.2 Ecology
It is demersal and feeds on shrimps, insects and small fish (Teugels, 1992). It 
is a nesting substrate spawner; the parents guard the nest and larvae (Regan, 
1912).
These three species are indigenous to the Keta lagoon where they are 
harvested in appreciable quantities (Addo, 2000; Ofori-Danson et al., 1999; 
Shenker et al., 1998).
2.4 Growth Model and Parameters
Though several growth models are in existence for the description of fish 
growth (Beverton and Holt, 1957; Gulland, 1983; Pauly, 1984; Pauly and 
Morgan, 1987), the von Bertalanffy growth model is preferred for this study, 
the main reasons being its wide acceptability and use in several complex
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models describing fish population dynamics. The von Bertalanffy model 
describes the body length of fish as a function of time by the equation
L t = L  (1  - e ‘K(t‘t0))
where L t is the length of a fish at time (age) t ,  usually measured in 
years,
L  is the asymptotic length of the fish, usually measured as total
length in centimeters
K is the growth constant of the fish
t 0 is the theoretical age when the fish has zero length and
e is the natural log base.
Other parameters that describe various properties of a fish population are 
estimated from these basic parameters. The growth parameters differ from 
species to species and also among stocks of the same species (FAO,1989). 
Table 2.0 shows some von Bertalanffy population parameters for the three 
species from Fishbase (Froese and Pauly, 2001), a web-based electronic 
library on the fishes of the world.
Table 2.0: Population parameters for S. melanotheron melanotheron, T. 
guineensis and H. fasciatus (Froese and Pauly, 2001).
L (cm) K (yr1) O’ M (yr1) to (yr) tmax (yr)
S. melanotheron 26.1 1.25 2.93 2.17 -0.1 2.3
T. guineensis 20.7 0.85 2.56 1.72 -0.2 3.3
H. fasciatus 21.4 1.20 2.74 2.21 -0.1 2.4
where <D’ (phi prime) is the growth performance index
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M is the natural mortality coefficient estimate
tmax is the lifespan or longevity of the fish (Alagaraja, 1984).
The growth performance index O’ (Pauly and Munroe, 1984; Munroe and 
Pauly, 1983) is a test of the resilience of the growth model (hence 
parameters) estimated for a fish stock. It is calculated from the equation
O’ = InK + 2(lnL )
Unlike the other growth parameters, it is fairly constant with little variability for 
a fish species, irrespective of where it is obtained (FAO, 1989).
The study by Ofori-Danson et al. (1999) on the fishery of the Keta lagoon was 
focused on S. melanotheron melanotheron. Table 2.1 presents some of the 
parameters they estimated.
Table 2.1: Population parameters for S. melanotheron melanotheron from the 
Keta lagoon (Ofori-Danson eta i ,  1999).
L
(cm)
K
(yr-1)
O’ Z
(yr-1)
M
(yr-1)
F
(yr-1)
E
S. melanotheron 17.5 1.1 2.53 5.02 2.21 2.81 0.56
where Z is the total instantaineous mortality 
F is the fishing mortality ,
E is the level of exploitation and
all other parameter retain their previous definitions.
Though no yield data was available for the lagoon, Ofori-Danson et al. (1999) 
reported that experimental fishing yielded 791,3g and 332.Og of S. 
melanotheron melanotheron and T. guineensis per man-hour respectively
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Ofori-Danson et al. (1999) however did not estimate the population 
parameters of the other major fishes they identified in the Keta lagoon. Their 
study also did not include the food and feeding habits of the fishes or the 
environmental integrity of the lagoon.
S. melanotheron melanotheron is reported as the dominant fish in catches in 
studies on other coastal lagoons in Ghana (Koranteng et al., 2000; Koranteng 
et al., 1998; Blay and Asabere-Ameyaw, 1993; Pauly, 1976). Studies on the 
Muni lagoon, Densu-Delta and Sakumo II lagoon (Koranteng, et al., 2000; 
Koranteng et al., 1998) all indicate S. melanotheron melanotheron as 
dominating the catch, accounting for 99.9% (by weight) of catch in the Muni 
lagoon, 96.4% in the Sakumo II lagoon and 85.6% in the Densu-delta. Some 
population parameters estimated for S. melanotheron melanotheron from the 
Muni lagoon (Koranteng et al., 2000) are:
L =12.5 cm (SL),
K = 0.71 y r1, 
t0 = -0.01 yr and 
tmax = 4.2 yr
Pauly (1976) reported that the Sakumo I lagoon yielded 50 kg of fish per day 
while Blay and Asabere-Ameyaw (1993) reported annual yields of between 
452 -  664 kg/ha of fish for the Fosu lagoon.
The study by Shenker et al. (1998) focused mainly on the gonado-somatic 
index and length-weight relationship as well as size/sex relationship and
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mean abundance of species in the Keta lagoon. They however did not 
estimate population parameters of the fishes they studied. Addo (2000) whose 
main focus was on the Acadja fishery of the Keta lagoon determined the 
gonado-somatic index and the feeding habits of the major cichlids in the Keta 
lagoon.
2.5 Sediment and Benthic Fauna
Though Armah et al. (1997) reported on the sediment of the Keta lagoon, the 
only comprehensive study so far to have been carried out on the lagoonal 
sediment was by Finlayson et al. (2000), who studied the spatial distribution of 
the sediment grain size and the benthic macrofauna of the lagoon. Their 
findings indicate that the lagoonal sediment is basically clayey, but contains a 
large proportion of fine sand and silt elements. The larger particles were 
usually shell fragments or shell relics (Finlayson et al., 2000). They however 
did not comment on the temporal dynamics of the sediment distribution.
The benthic fauna of the lagoon, as reported by Finlayson et al. (2000), was 
made up of 10 species of annelids, 13 species of molluscs and 9 species of 
crustaceans. According to the authors, the most encountered species was the 
bivalve Tivela tripla followed by the gastropod Tympanotonus fuscata. They 
however did not relate sediment properties with benthic faunal distribution.
The relation between sediment properties and the distribution of infaunal 
invertebrates has been a subject of numerous studies (Snelgrove and 
Butman, 1994). This has however not produced a universally accepted
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animal-sediment’ model (Seidererand Newell, 1999; Snelgrove and Butman, 
1994). The current school of thought is that ‘animal-sediment’ relations may 
be influenced by other factors such as bottom boundary-layer flow (Miller and 
Sternberg, 1988; Butman, 1987; Nowell and Jumars, 1984; Palmer, 1983), 
hydrodynamics and sediment transport processes (Cacchione and Drake, 
1990; Butman, 1987; Grant and Madsen, 1986; Nowell, 1983). However some 
evidence exists in support of sediment grain size distribution as being a factor 
in infauna distribution (Palacin et al., 1991; Ishikawa, 1989; Nichols, 1970; 
Cassie and Michael, 1968; Sanders, 1958; Thorson, 1957).
The organic content of benthic sediment is considered by some authors (Gray 
et al., 1990; Pearson and Rosenberg, 1978) as a more likely factor in 
determining infauna distributions. This is because organic matter in sediment 
is a major source of food supply for deposit feeders (Snelgrove and Butman,
1994).
The current study was focused on the Anloga end of the lagoon. This area 
was selected since, according to the local fisherfolk, it is the most productive 
part of the lagoon. In terms of biotopes also, the area is more or less a 
microcosm of the entire lagoon.
Sampling covered a period of nine months enabling the effects of seasons on 
the environment and the fishery to be determined. Environmental parameters 
and benthic faunal surveys were carried out in addition to the fishery studies 
in order to determine the effects of the environment on the fishery.
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CHAPTER THREE 
MATERIALS AND METHODS
3.1 Study Site
The study site is the southwestern corner or the Anloga end of the lagoon 
(Figure 1.0). It is located within the coordinates of latitude 05°52’N and 
05°42’N and longitude 00°52’E and 00°56’E, covering an approximate area of 
35 km2. The principal factors taken into consideration in the location of 
sampling stations was salinity, vegetation cover, water depth and sediment 
structure.
A preliminary survey was carried out in the first week of January 2000 in the 
study area to design a sampling strategy that will address the objectives of the 
study and to locate sampling stations, taking into account the identifiable 
biotopes in the area. It was realized that the salinity values in the study area 
increased northwards (towards Fiahor) away from the sea. Preliminary 
analysis also indicated that the sediment, while being muddy generally, had 
more sand content at the northward (Fiahor) end of the study area than at the 
seaward end. No clear pattern was observed in the depth of the water column 
in the study area, the water depth being shallow. Vegetation however was 
more concentrated close to Anloga with open water near Fiahor.
Based on these considerations, the sampling stations were located along a 
belt transect in identifiable habitats from Anioga to Fiahor (Figure 3.0). The
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study area is approximately 35 km2. Seven sampling stations were located in 
all, at about a kilometer apart (Table 3.0).
Table 3.0: Coordinates of Sampling Stations in the study area.
Station Latitude Longitude
A 05°47’58” 00°54’16”
B 05°48’27” 00°54’15”
C 05°48’57” 00°54'25”
D 05°49’27” 00°54’12”
E 05°49’57” 00°54’05”
F 05°50’22” 00°54’07”
G 05°50’48” 00°53’55”
The sampling stations were located with a handheld Magellan 4000X 
Geosatelite Positioning System (GPS) receiver.
3.2 Description of Sampling Stations
The sampling stations were lettered A to G. Stations A, B and C were located 
close to Anloga, and were mainly in vegetated areas. Stations A and B were 
located in densely vegetated areas while station C was in a relatively sparsely 
vegetated area. Station D was located at the edge of the vegetated area while 
Stations E and F were located in open water devoid of any vegetation. Station 
G was located close to Fiahor, also without vegetation.
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Figure 3.0: Map of the Study area showing sampling stations along belt
transect
•  A Sampling stations
_J_______________________!_______________________ L
O^O’ 0°55‘ 1*01
Cape Saint Paul
3.3 Sampling
Sampling was carried out from January to September 2000, a period of nine 
months. This period was chosen because it was possible to observe the effect 
of season on the iagoon.
Sampling was carried out for the following:
• Water physicochemical parameters
• Sediment grain size distribution and total organic (detrital) 
content
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21
• Macrobenthic fauna
• Fish
Samples for the water physicochemical parameters and fish studies were 
taken at monthly intervals while bi-monthly samples were taken for the 
sediment grain size analysis, organic content and benthic fauna. Sample 
collection usually took place during the last week of a month. The samples 
were collected between 6:00 hours and 11:00 hours. The same sequence of 
sample collection was adopted so that samples were collected at 
approximately the same time each month.
3.3.1 Water Physicochemical Parameters
The physicochemical parameters of the water which were measured were 
salinity, conductivity, total dissolved solids, pH, dissolved oxygen, nitrates, 
phosphates, sulphates, silicates, water temperature, total suspended solids 
and turbidity. The lagoon water was sampled employing a tight closing 250 ml 
plastic bottle. The bottles were washed and rinsed with deionised water in the 
laboratory to remove any contaminant. Just before samples were taken, a 
small amount of the water at the station was used in rinsing the sample bottle 
in order to get rid of any other contamination that may have occurred during 
transportation or handling. The sample bottle was then dipped below the 
water surface to about 0.5 m to collect subsurface water sample. The sample 
bottle was tightly closed while still below the surface of the water; a precaution 
taken to ensure that no air bubble entered or was trapped in the bottle. The 
occlusion of air from the bottle was done to reduce to a minimum any
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biochemical activity occurring in the bottle. This was further ensured by 
placing the water sample in a thermos chest containing ice cubes.
The dissolved oxygen content of the water and water temperature were, 
however, measured in situ employing a hand held YSI 55 dissolved oxygen 
meter with a built-in thermometer. The other parameters were determined in 
the laboratory soon on arrival from the field.
3.3.2 Sediment and Macrobenthic Fauna
The sediment was sampled employing a 3-inch diameter PVC pipe corer with 
a fitted plunger. During sampling six inches of the corer was pushed into the 
sediment and the trapped sediment taken. The plunger was used in pushing 
out the trapped sediment. Four replicate samples were taken per station for 
the benthic fauna study. Each sample was washed in a box sieve of 0.5 mm 
mesh size in order to get rid of excess silt and clay components in the sample 
while retaining the benthic macrofauna. The residual sample was then placed 
in a tight-closing plastic container and preserved with 10% buffered 
formaldehyde solution. A few drops of Rose Bengal stain was added to each 
sample container to make the identification of living tissue easier.
One additional sediment sample per station was taken for sediment grain size 
and total organic content analysis. The sample was taken in the same way as 
that for the benthic fauna, except that after coring, the sample was not sieved 
but was rather placed whole in a container. No preservative or stain was 
added to it.
22
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23
3.3.3 Fish
The fish samples were obtained from the fishermen fishing in the study area. 
Care was taken that the fish so obtained was:
• caught in the study area and
• not sorted into samples of different sizes, as usually occured 
before they were sold on the market.
In order to meet the above requirements, the fish samples were bought from 
the fishermen while they were still at work on the lagoon.
The gut contents of the fish samples were then fixed in situ by injecting a 4% 
buffered formaldehyde solution into the gut. They were then placed in a 
thermos chest containing ice to aid in their preservation. On arrival in the 
laboratory, the fish samples were transferred to a deep freezer and kept there 
till they were analyzed.
3.4 Laboratory Analyses
3.4.1 Water Physicochemical Parameters
The nutrients (i.e. nitrates, phosphates, sulphates and silicates) were 
analyzed using a Hach DR2010 direct-reading spectrophotometer and Hach 
prepackaged reagents. The protocols followed was as outlined in the Hach 
DR2010 user manual (Hach, 2000a) and the Hach water quality analysis 
handbook (Hach, 2000b), supplied with the spectrophotometer. These 
involved the addition of the prepackaged specific reagents to an aliquot of the 
water to be analyzed. This produces compounds of varying color or turbidity,
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24
which is then measured with the spectrophotometer. The optical properties of 
the water (i.e. turbidity and total suspended solids) were also analyzed using 
the Hach DR2010 spectrophotometer, following protocols outlined in the user 
manual and handbooks (Hach, 2000a, Hach, 2000b).
The electro-chemical properties of the water (i.e. salinity, conductivity and 
total dissolved solids) were measured using a Hach portable salinity, 
conductivity and total dissolved solids meter with a built-in automatic 
temperature compensation facility. The pH was measured using a Hach pH 
meter with a built-in automatic temperature compensation facility. The 
protocols followed, as before, were those outlined in the Hach user manual 
and methods books (Hach, 2000a, Hach 2000b).
3.4.2 Sediment
In the laboratory, the sediment samples for the benthic fauna analysis were 
washed with tap water in a stainless steel 500 pm mesh-size precision sieve 
to get rid of the fixative. It was then spread on an examination tray in which 
grids had been drawn to facilitate examination. The sample was then 
examined carefully and organisms present were picked out and placed in a 
70% alcohol-glycerol preservative. Identification and counting were done 
under a dissecting microscope with samples identified to the species level.
Sediment grain-size distribution was determined by taking 130 g of the core 
sample and washing it in a 63 |jm mesh-size precision sieve to remove the silt 
and clay component. The residual was heated in an oven at 60°C for 6 hours,
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and reweighed to obtain the mass of the silt and clay fraction. It was then 
treated with 1% sodium hydroxide solution to destroy any organic component 
and to prevent clumping. The sodium hydroxide solution was washed out of 
the sediment and the sediment was reheated at 60°C for 6 hours to obtain a 
constant weight. 100 g of this treated sediment was then placed on the 
uppermost sieve of a nest of 7 sieves of mesh sizes 2 mm 1 mm 0.75 mm, 0.5 
mm 0.355 mm, 0.25 mm and 0.063 mm. The nest of sieves was agitated 
using an Endecot sieve shaker at an amplitude of 7 mm for 10 minutes. This 
resulted in the separation of the sediment components into various grain-size 
classes in the sieves. Each component so trapped was weighed to determine 
the weight contribution of that class of grain size to the sediment in whole.
The total organic (detrital) content of the sediment was also determined. 
During this analysis, 30 g of the sediment was treated in a beaker with 10% 
hydrochloric acid solution to remove excess carbonates due to shells. The 
residual was heated at 60°C to a constant weight. Approximately 20 grams of 
this was then placed in a muffle furnace and heated at 600°C for 6 hours for 
the organic content to burn. After ashing, the residual was then weighed 
again, the difference being the organic (detrital) content of the sediment.
3.4.3 Fish
The fish samples were identified to species level and analyzed for length- 
weight data and gut content. The total length was measured to the nearest 0.1 
cm employing a fish measuring board. The weight was measured on a Mettler
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26
Toledo balance to the nearest 0.01 g. The gut content was then removed and 
preserved in a 70% alcohol-glycerol solution till it was analyzed.
For the gut content analysis, the preserved gut was cut open and the content 
washed out into a petri dish. The food items in the gut were identified and 
analyzed as percentage composition by weight and occurrence. A Costello 
analysis (Costello, 1990) was carried out on this data to determine the feeding 
strategy of each species and the importance of each food item to a species. 
This involved plotting the percent weight of food found in the gut of the fish 
against its percent occurrence.
Multivariate analyses on the water physicochemical parameters, sediment 
data and benthic macrofauna diversity index were carried out employing the 
PRIMER (Plymouth Routines in Multivariate Ecological Research) software 
package developed at the Plymouth Marine Laboratory, United Kingdom 
(Carr, 1996). The fish population parameter estimation was done employing 
the FiSAT (Fish Stock Assessment Tools) software package developed jointly 
by ICLARM (International Center for Living Aquatic Resource Management) 
and FAO (Gayanilo et al., 1995). All other data analysis and graphing was 
performed using Microsoft Excel Spreadsheet software developed by 
Microsoft Corporation.
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27
CHAPTER FOUR 
RESULTS
4.1 Water Physical and Chemical Parameters
4.1.1 Salinity, Conductivity and Total Dissolved Solids (TDS)
The mean monthly salinity, conductivity and total dissolved solids (TDS) 
values for the study area are presented in Figures 4.0 and 4.1. Salinity, 
conductivity (Figure 4.0) and total dissolved solids (Figure 4.1) values 
generally increased from January to September with a slight depression 
observed in April and May. There was more variation between values towards 
the end of the year with September values showing more deviation than 
January values.
Figure 4.0: Mean monthly salinity and conductivity 
distribution with standard deviation bars for the study area
50
Jan Feb Mar Apr May Jun Jul Aug Sep
Month
HI Sa lin ity  ■ C o n d u c t iv i ty  (m S /cm )
V    /
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28
Figure 4.1: Mean monthly total dissolved solids (TDS) 
distribution with standard deviation bars for the study
area
35000 --------------------------------------------------------------------
30000 - j
25000 - T
_j 20000
Jan Feb Mar Apr May Jun Jul Aug Sep 
Month
0 T o ta l d is s o lv e d  so lid s  (m g /L )
v.__________________________________________________________ J
Figures 4.2 and 4.3 show the mean salinity, conductivity and total dissolved 
solids values for the stations sampled. There was a general increase in the 
values from Station A to Station G, i.e. an increase in the values northwards, 
away from the sea. Stations F and G recorded the highest values for the three 
parameters on the average. There was more variation in the values for 
Stations E, F and G than the other stations, as seen in their standard 
deviation bars.
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29
Figure 4.2: Mean station values of salinity and conductivity 
with standard deviation bars for the study area
0  Salinity ■  Conductivity (mS/cm )
Figure 4.3: Mean station values of total dissolved solids 
(TDS) with standard deviation bars for the study area
30000
25000
20000
o>
£  15000
(0Q
■“  10000 
5000 
0
Station
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4.1.2 pH
The mean pH values with their deviations for each month and for each station 
are presented in Figures 4.4 and 4.5. The mean values were quite constant 
across the months (Figure 4.4) and showed little variation within each month, 
as seen in the very short standard deviation bars.
30
Figure 4.4: Mean monthly pH distribution with standard 
deviation bars for the study area
14 
12 
10 
8
X  Q.
6 
4 
2 
0
Jan Feb Mar Apr May Jun Jul Aug Sep
Month
^______________________________________________________________
The mean pH values per station were also constant and showed little variation 
within each station.
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31
/
Figure 4.5: Mean station values of pH with standard 
deviation bars for study area
14 1-------------------------------------------------------------------------------------
12
10
4.1.3 Dissolved Oxygen (DO) and Water Temperature
Figures 4.6 and 4.7 show the dissolved oxygen (DO) and water temperature 
distribution for the study area during the period of study. The DO values were 
similar for the stations sampled (Figure 4.6) and for the months sampled 
(Figure 4.7). The values also showed little variation within station and month, 
as evidenced by the short deviation bars.
The mean water temperature dipped slightly between May and August (Figure 
4.6) but was generally constant between stations (Figure 4.7). Little variation 
was also observed within month and station values.
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32
Figure 4.6: Mean monthly dissolved oxygen (DO) and water 
temperature distribution with standard deviation bars for 
the study area
Jan Feb Mar Apr May Jun
Month
Jul Aug Sep
El DO (mg/L) ■  Water temperature
A
Figure 4.7: Mean station values of dissolved oxygen (DO) 
and water temperature with standard deviation bars for the
study area
a> 50 
2 45
|  35 
® 30 
i  25
O 0 UJUJj
IH DO (mg/L) ■  Water temperature
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33
4.1.4 Inorganic Nutrients
The nutrients measured during the study were nitrates (N032 ), phosphates 
(P043'), sulphates (S023 ) and silicates (Si02').
4.1.4.1 Nitrates ( N O 32')
The mean monthly nitrate distribution for the study area is shown in Figures 
4.8 and 4.9. The mean monthly values were higher for January and February 
than the other months (Figure 4.8). Low values were recorded in March, April, 
May and July. The variations in monthly samples were highest in February but 
were generally lower than variations in station samples.
Figure 4.8: Mean monthly nitrate distribution with standard 
deviation bars for the study area
1.6
1.4
1.2
Jan Feb Mar Apr May Jun Jul Aug Sep
Month
V.
The mean spatial distribution generally decreased from Station A to Station G, 
though a slight increase was observed at Station F (Figure 4.9). The standard
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deviation within the station values were, however, appreciably higher than the 
monthly averages.
4.1.4.2 Phosphates (P043')
Figures 4.10 and 4.11 shows the mean phosphate distributions for the study 
area. The mean monthly distribution (Figure 4.10) shows a bi-modal pattern of 
distribution with first and second peaks obtained in February and July. Low 
values were recorded in May and June. The standard deviation values were 
also very large, indicating high variation in values of samples within each 
month.
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35
Figure 4.10: Mean monthly phosphate distribution with 
standard deviation bars for study area
2.0
1.5
a
£  0.5
0.0
III 1 r
I 1.... s i . . .  i * i  !1 I i
Jan Feb Mar Apr May Jun
Month
Jul Aug Sep
Figure 4.11: Mean station values of phosphate with standard 
deviation bars for the study area
2.0
d  15 o>
E
©
15 10 £  a  <o o
0.5
0.0
1
•r
■ 1Lilli 1 I
C D E
Station
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Spatially, there was a gradual increase in phosphate levels from Station A to 
Station G (Figure 4.11). The standard deviations were also large indicating, in 
this case also, large variations in phosphate values within stations.
4.1.4.3 Sulphates (S023')
Figures 4.12 and 4.13 shows the sulphate values recorded for the study. The 
mean monthly values (Figure 4.12) were bi-modal with peaks in March and 
July and low values occurring in April and May. The value for January showed 
the least variation with the shortest standard deviation bar, with the values in 
March and April showing the most variation.
Figure 4.12: Mean monthly sulphate distribution with 
standard deviation bars for the study area
2500
2000
Jan Feb Mar Apr May Jun 
Month
Jul Aug Sep
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The spatial values showed an increase from Station A to Station G, though 
Station B had the least value (Figure 4.13). There was more variation in the 
values for Station B with Station E having the least variation.
37
Figure 4.13: Mean station values of sulphate with standard 
deviation bars for the study area
2500 ----------------------------------------------------------------------------------------
2000  -
4.1.4.4 Silicates (SiO20
Figures 4.14 and 4.15 shows the silicate distribution for the study. The mean 
temporal distribution (Figure 4.14) shows two peaks occurring in February and 
September, with a low value occurring in July. The deviations in the monthly 
values were small in February and May with the largest calculated value being 
for April. The mean spatial distribution was similar between the stations 
though it decreased slightly from Station A to Station G (Figure 4.15). The 
deviation in the station values were also similar but were higher for Station D.
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38
Figure 4.15: Mean station values of silicate with standard 
deviation bars for the study area
D E
Station
v J
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39
4.1.5 Total Suspended Solids (TSS) and Turbidity
Figures 4.16 and 4.17 shows the TSS and turbidity values for the study. The 
temporal distribution values (Figure 4.16) show two peaks, one occurring in 
March and the second in July for both TSS and turbidity. Low values were 
recorded in January, February, April and May. The values also showed 
relative large deviations for each month sampled.
Figure 4.16: Mean monthly total suspended solids (TSS) and 
turbidity distribution with standard deviation bars for the
study area
300
250
| 200
•ac(0
(On
150
100
50
Jan
111 i l l  s i . S l J
Feb Mar Apr May Jun Jul Aug Sep 
Month
13TSS (mg/L) ■  Turbidity (FAU)
0
The mean values for the stations were lower for Stations B, C, D and G 
(Figure 4.17) and highest for Station A. The deviations per station in this were 
large instance also.
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40
Figure 4.17: Mean station values of total suspended solids 
(TSS) and turbidity with standard deviation bars for the 
study area
300
p 250
'■5
3  200 
L .3
«  150U
I  10°
(0
H 50 
0
A B C D E F G
Station
I El TSS  (mg/L) ■Turb id ity  (FAU)
___________________________________________________________________V
4.1.6 Similarity analysis
A similarity analysis was conducted to test for significant spatial and temporal 
differences in the water physicochemical parameters. The methods adopted 
were those of Bray and Curtis (Everitt, 1980; Cormack, 1971; Bray and Curtis, 
1957) and Kruskal and Wish (1978). In the methods, a similarity matrix was 
generated on the physicochemical data set after standardization. A cluster 
analysis (Everitt, 1980; Cormack, 1971; Bray and Curtis, 1957) and a multi­
dimensional scaling (MDS) (Kruskal and Wish, 1978) are performed on the 
similarity matrix. The output was a dendrogram (for the cluster analysis) and 
an MDS plot (for the MDS analysis) showing data sets of similar nature 
clustering together from dissimilar ones. These were then used as an index of 
the degree of similarity in the data sets. The PRIMER software, which 
includes these methods, was used for the analysis.
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41
Figure 4.18 shows the dendrogram of the Bray-Curtis similarity analysis of the 
physicochemical parameters. This shows all the samples clustering together 
above 80% similarity and 93.7% of the samples clustering above 90% 
similarity.
The MDS plot (Figure 4.19) of the similarity matrix shows a major aggregation 
of the samples into three groups (unbroken ellipse), which coincides with 94% 
similarity and a sub-aggregation into four groups (broken ellipse) coinciding 
with 95% similarity on the dendrogram.
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Figuie 4,18: Cluster analysis (Bray-Cuflis] of the  
water physicochemical parameters
r
£ siII
r m
-  f a
JS.
rC§
k 3
80 85 90 95 100
Bray-Curtis similarity
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Flgure4.19: MDS plot of water physicochemical 
---------------- parameters (stress =  0.01)----------------
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4.2 Sediment Grain Size Distribution
The phi (CD) scale (Barnes, 1980) is computed for the sediment grain size 
using the relationship:
<D = -log2d
Where d (in millimeters) is the diameter of a sediment grain particle.
4.2.1 Spatial distribution
Figure 4.20 is a percentage stacked column graph comparing the average 
percentage each grain size category contributed to the Station average.
44
I
Figure 4.20: Spatial distribution of sediment in study area
100%
80%
60%
40%
20%
0%
Jan Mar May Jul Sepl
■  04> ■0.5<t> n  1<t> EE31 -5et> m2d> E|3<t> *4 0 ) □>44>
1
1
r  i1 1
H 1
1E B ■ ■ I  l
No distinct spatial distribution pattern was observed between the stations 
during the study period. From the graph (Figure 4.20), Station D and F had 
the least and largest percentage respectively of very fine (>4<t>) grain size
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components. Station D however had the highest amount of coarse (^10) 
grains. The mean grain size ranged from 1.760 (Station D) to 2.510 (Station 
F), indicating that fine sand predominates in the study area.
4.2.2 Temporal Distribution
The percentage stacked column graph comparing the average percentage 
each grain size category contributes to the monthly average is presented in 
Figure 4.21. Generally the grain size distribution remained fairly constant 
during the study period, indicating little sediment movement. The mean 
coarse sand percentage however increased slightly towards September. This 
is probably due to a reduction in the percent of fine sediments transported to 
the study area.
■  00 ■  0.50 B 1 <t> I1 1.50 ■  20 m 30 B 40  □  >40
80%
0%
A B c D E F G
I
100%
Figure 4.21 Temporal distribution of sediment in study 
area
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The dendrogram (Figure 4.22) and the MDS plot (Kruskal and Wish, 1978) 
constructed from a cluster analysis of a Bray-Curtis similarity matrix (Everitt, 
1980; Cormack, 1971; Bray and Curtis, 1957) of the grain size distribution of 
the area shows a major aggregation of the samples into six groups (unbroken 
ellipse), coinciding with 85% similarity on the dendrogram and a sub 
aggregation into eleven groups (broken ellipse) coinciding with 90% similarity 
(Figure 4.23).
46
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Figure 4.22: Cluster analysis (Bray-Curtis) dendogram for 
grain size in study area
r - t f
75 80 85 90
—Mar€
—UarG 
— JaoG 
— W
— JliA
— JtfC  
— JanC 
— MarA—Rar? 
— JiXF
—$mA 
— May€ 
— MayA 
—
— JanF 
— JjnA  
— «i*>4 
— MayG 
— MarB 
— JulG
—  SopG
—  Mayf 
— W O  
— '-.±Q  
— SspO
= ; r
— JanO 
— A /8  
— Uayfi 
— Sep8 
— SepC 
— -W-tyC
100
Bray-Curtis similarity
Figure 4.23: MDS plot of grain size in study area 
(stress = 0.11)
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4.3 Sediment Organic (Detrital) Matter Content
Figure 4.24 and 4.25 show the spatial and temporal distribution (with error 
bars) of the organic content over the study period. No clear distribution pattern 
was observed in the sediment organic matter content during the study period.
48
Figure 4.24: Spatial distribution of sediment organic matter 
in study area
2.0   -  -    -  -  ...
~  1.5
A  B C  D  E F  G
Station
Spatially, Stations A and G (Figure 4.24) had the lowest organic matter levels 
while Station C had the highest. The mean temporal values were fairly 
consistent over the study period (Figure 4.25). the mean values however have 
large deviations suggesting wide variability in values obtained per month.
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49
I
Figure 4.25: Temporal distribution of sediment organic 
matter in study area
2.0 i .................... -....... -.....................iI
Jan Mar May Jul Sep
4.4 Benthic Fauna Diversity
Sixteen benthic faunal species were encountered during the study. They were 
made up of 8 annelids, 4 molluscs and 4 crustaceans. Tables 4.0 and 4.1 
show their distributions (presence/absence) temporally and spatially. The 
dominant species in almost all the stations (counts per species) was Nereis 
sp.
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Table 4.0. Benthic macrofauna presence/absence data for stations sampled
Species
Nerieis sp.
Notomastus sp.
Capittelid
Eunicid
Corbula trigona
Pena sp.
Ischyrouerus sp.
Polychaete indet A
Orbinid sp.
Nermetine
Spionid
Polychaete indet B
Neanthes sp.
Tellina nymphalis
Tympanotonus sp.
Amphipod
Key: Presence Absence
Table 4.1. Benthic macrofauna presence/absence data for months sampled
Januai March September
Nerieis sp
Notomastus sp,
Capittelid
Eunicid
Corbula trigona
Pena sp
Ischyrocerus sp
Polychaete indet A
Orbinid sp
Nermetine
Spionid
Polychaete indet B
Neanthes sp.
Tellina nymphalis
Tympanotonus sp,
Amphipod
Key: Presence Absence
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Four diversity indices were estimated for the benthic fauna from the study 
area (Magurran, 1991; Heip etal, 1988; Pielou, 1975). These are:
1. Margalef s index of species richness
2. Shannon-Wiener diversity index
3. Pielou’s evenness index, and
4. Simpson’s dominance index
The diversity indices were calculated from the species abundance (counts per 
species) data (Appendix E) employing the PRIMER software. A fourth-root 
transformation was carried out on the data to weigh the contribution of 
common and rate species in the data.
4.4.1 Spatial Distribution
Figure 4.26 shows the spatial distribution of the diversity indices for the study 
area. Station C on the average had the highest diversity index (Shannon- 
Wiener) while Station B had the lowest, though the species richness 
(Margalef) was highest for Station G and lowest for Station B. Station A had 
the highest species evenness (Pielou) index while Station D had the lowest. 
Station A on the other hand had the lowest species dominance indices 
(Simpson) while Station D had he highest.
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@ Richness a  Shannon m Evenness □  Simpson
Figure 4.26: Spatial distribution of dive rsity Ind i ce.s, for 
study area
C D E
Stations
4.4.2 Temporal Distribution
The temporal distribution graph is presented in Figure 4.27. The month of 
March, on the average, recorded the highest values for species richness and 
evenness and the lowest value for dominance. Species diversity and richness 
were also low for the month of January, and this was correlated with a high 
dominance index. This suggests that a few species which were able to 
withstand the stressful conditions encountered during January became 
dominant in the environment. Dominance was lowest in September with a 
correspondingly high evenness, suggesting an equitable distribution of 
species in the study area during that month.
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53
^Richness BShannon 0Evenness □  Simpson
r~ --------------------------------------------------------------------------------  x
Figure 4.27: Temporal distribution of diversity 
indices.' for study area
Mar May Jul Sep
Months
4.5 Population Parameter of Major Fishery
The population parameter estimated were growth, mortality and recruitment 
from length-frequency and weight-frequency data. A von Bertallanfy growth 
pattern was assumed for the species.
4.5.1 Growth Parameters
The fish samples obtained measured between 4.4 cm and 18.2 cm with a 
median class of 8.0 cm for S. melanotheron melanotheron, 4.3 cm and 15.2 
cm with a median class of 9.5 cm for T. guineensis and 4.7 cm and 20.6 cm 
with a median class of 12.5 cm for H. fasciatus (Figures 4.28, 4.29 and 2.30).
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Figure 4.28: Length-frequency distribution of S. 
melanotheron from Study Area
140 
120 
100
of 60 
Li.
40
20
0
4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5 12.5 13.5 14.5 15.5 16.5 17.5 18.5
Length
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Figure 4.29: Length-frequency distribution o f T. 
guineenis from the Study Area
140
120
100
c 80 0)
^  60£
40 
20 -  
0
4.5 5 .5 6.5
Figure 4.30: Length-frequency distribution of H. 
fasciatus from the Study Area
160 
140 - 
120 -
>> 100
ca>3cro
80
60
40
20
0
:
V
.
-
■ :
: :
:
4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5 12.5 13.5 14.5 15.5 16.5 17.5 18.5 19.5
Length
9.5 10.5
Length
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Figures 4.31, 4.32 and 4.33 show the power regression function relating fish 
length and weight for each species.
Figure 4.31: Length-weight relationship of 
Sarotherodon melanotheron melanotheron from the
Total length (cm)
_____________________________________
Figure 4.32: Length-weight relationship for Tilapia 
guineensis from the Study Area
Total length (cm)
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Figure 4.33: Length-weight relationship for 
Hemichromis fasciatus from the Study Area
Total length (cm)
A length progression analysis was generated with the FiSAT software, using 
monthly length frequency data, from which was obtained estimates of the 
asymptotic length (Loo) and the growth constant (K ) for each species. From 
these parameters, the theoretical length (t0) when the fish is zero years old is 
estimated from Pauly’s equation
Log-io (-to)= -0.3922-0.2752Log10Loo-1.038Logi0K 
The result for each species is presented in table 4.2 below.
Table 4.2: Population parameters estimated for the fish species
Fish species Loo K to
S. melanotheron 21.40 0.78 -0.225
T. guineensis 19.10 0.85 -0.213
H. fasciatus 19.29 1.50 -0.369
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Substituting the parameters into the von Berttalanfy growth function for fish
Lt=Loo(1-e-K(t-to))
Where Lt is the length of a fish at age t years, we obtain the derived growth 
function for each fish species (Figures 4.37, 4.38 and 4.39).
Figure 4.37: Derived growth  curve of Saro therodon  
m elano theron  m elanotheron  from  the Study area
Age (years )
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The maximum attainable age (longevity) of each species, t m a x , is computed 
from the relationship
t m a x = 3 / K
The growth performance index, O’ (phi prime), (Pauly and Munroe, 1984; 
Munroe and Pauly, 1983) is given by the relationship
O’ =LogioK+2LogioLoo 
The growth performance index, unlike the other population parameters is 
species specific and is to a very small extent influenced by the environment. 
Hence it serves as a test of the robustness of the other parameter estimated.
Table 4.3 shows the longevity (tmax) and growth performance index (O’) 
computed for each species.
Table 4.3: Longevity and growth performance index estimated for the fishes
Fish species tmax O’
S. melanotheron 3.85 2.55
T. guineensis 3.53 2.49
H. fasciatus 2.00 2.74
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4.5.2 Mortality Parameters
The length-converted catch curve (Figures 4.40, 4.41 and 4.42) is used in 
computing the total mortality coefficient Z for each species.
Figure 4.40: Length-converted catch curve for S. 
melanotheron melanotheron from the Keta lagoon
10 
8
_  6
0 1 2  3
Absolute age (years)
Figure 4.41: Length-converted catch curve for Tilapia 
guineensis from the Keta lagoon
10
8
_  6
z
cf
~  4 -
2 -
Z = 4.51vr~
1
Absolute age (years)
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Figure 4.42: Length-converted catch curve for Hemichromis 
fasciatus from the Keta lagoon
Absolute age (years)
The natural mortality coefficient M is calculated from Pauly’s M-equation as 
lnM=-0.0152-0.279lnL°o+0.6543lnK+0.463lnT
where T is the average water temperature in degrees Celsius (°C).
From the relationship Z=F+M, we obtain the fishing mortality for each species 
as the difference between the total mortality Z and the natural mortality M. 
The level of exploitation of the fishery, or the exploitation ratio, E, is computed 
as E=F/Z. Table 4.4 shows the morality parameters and the exploitation ratio 
computed for the species.
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Table 4.4: Mortality parameters and exploitation ratio estimated for the fishes
Fish species Z M F E
S. melanotheron 3.79 1.74 2.05 0.54
T. guineensis 4.51 1.90 2.61 0.58
H. fasciatus 5.04 2.75 2.29 0.45
4.5.3 Recruitment Pattern
Figures 4.43, 4.44 and 4.45 show the recruitment patterns for S. 
melanotheron, T. guineensis and H. fasciatus respectively.
Figure 4.43: Recruitment pattern for S. melanotheron
Month
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Figure 4.44: Recruitment pattern fo r Tilapia 
guineensis from the Study Area
Month
V y
/
Figure 4,45: Recruitment pattern for Hemichromis 
fasciatus from the Study Area
Month
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The broken portion of the curves indicates periods for which data was 
estimated. A bimodal recruitment pattern was observed for all the three 
species, one during the dry season and a second during the wet season. 
However, it was obvious that recruitment generally continued throughout the 
year for the species. S. melanotheron melanotheron had its maximum 
recruitment peak between December and January and a minor peak between 
May and June. The recruitment pattern for T. guineensis peaked in 
September with a second smaller peak in February. For H. fasciatus, the 
recruitment peaks were more clearly defined, and generally very similar in 
value. The peaks occurred first in December, then in June.
4.6 Food Habit Studies
The food items found in the gut of the fish species studies were plant 
materials, mud/debris, benthos, gastropods, aufwuchs/diatoms and juvenile 
forms of fishes. The benthos refers to benthic organisms with the exception of 
gastropods found in the guts. The fishes found in the guts were mainly 
juvenile forms of either cichlids or gobies, which could not be clearly identified 
due to their advanced stated of decomposition. The table below (Table 4.5) 
shows the presence (shaded portions) of each of the aforementioned food 
items in the gut of the different species.
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Table 4.5: Food items in gut of fishes studied
Fish species Mud/
debris
Plant
material
Benthos Gastropods Aufwuchs
/diatoms
Juvenile
fishes
S. melanotheron .
T. guineensis r  ;
H. fasciatus
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Generally, plant materials dominated the food in the gut of S. melanotheron and 
T. guineensis while fish was only present in the gut of H. fasciatus. A Costello 
graphical analysis (Marshall and Elliott, 1997,Costello, 1990) performed to 
investigate the feeding strategies and the importance of each food item to the fish 
species is presented in Figures 4.46, 4.47 and 4.48.
Figure 4.46: Feeding strategy and prey importance 
fo r S. melanotheron in the study area
100
80
-Co> 60
1 40 -
o'*
20
0 -
plant material •
benthos* mud/debris 0
gastropods
aufwuchs/diatoms
20 40 60
% Qccurnce
80 100
Figure 4.47: Feeding strategy and prey importance 
fo r T. guineensis in the study area
100 
80 
o> 60 
5  40
20
plant material^
autwuchs/diatoms*
benthos*
mud/debris «
20 40 60
% Occur nee
80 100
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Figure 4.48: Feeding strategy and prey importance 
for H. fasciatus in study area
100
80 fish Quveniie) •
40 -
gastropods*
20 - benthos •mud/debris* plant material •
0
0 20 40 60 80 100
% Occur nee
From the analysis, each species does not show any specialization for a 
particular food type, the dominant food for both S. melanotheron 
melanotheron and T. guineensis was plant material indicating that they 
probably grazed on plant for food. However, with mud and debris occurring as 
a generalized food type, it may be concluded that they also feed on benthic 
organisms, probably sifting through the mud/detritus in search of food. This is 
evident in the presence of some benthic organisms such as gastropods and 
polychaetes in their guts. The analysis also shows the benthos as being 
infrequent in their diet. Inference to this, however, must be drawn with caution 
taking cognizance of the fact that most benthic organisms, being soft bodied 
tend to digest rather readily in the gut offish.
Hemichromis fasciatus, on the other hand, had fish dominating its diet with 
plant material occurring generally. Benthos and mud/debris was rare in the 
diet while gastropods occurred midway between the four feeding strategies.
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The inference here is that H. fasciatus, though carnivorous also feeds on 
benthic organisms. The plant materials present in its gut may be mainly as a 
result of the fishes browsing on aquatic plants for food.
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5.1.2 Spatial distribution
The spatial distribution describes the mean values obtained per station and 
gives an insight into the variations obtained at each sampling station over the 
sampling period. Salinity, conductivity and TDS values were increasingly 
higher in a northwards direction along the transect as one moves between 
stations A and G. This can be attributed to the fact that inflowing fresh water 
to the lagoon mixes with and dilutes lagoonal water close to station A than 
close to station G. The spatial distribution of dissolved oxygen, water 
temperature and pH values were fairly constant for the stations sampled 
during the sampling period, implying that they were not affected by inflowing 
fresh water or rainfall into the lagoon. No definite pattern was observed in the 
spatial distribution of nutrients in the study area.
Turbidity and TSS distribution was higher at stations A, B, E and F than at the 
other stations. The values at stations A and B are thought to be influenced by 
inflowing water into the lagoon while those at station E and F were as a result 
of re-suspension of sediments under the influence of strong winds and the 
activities of fishers.
5.1.3 Similarity analysis
The similarity analysis conducted on the water physicochemical parameters 
showed that the various stations located in the lagoon were generally 
homogenous in terms of water quality, and are clustered close together. This 
is seen in the dendrogram where 82.5% of all the samples were clustered 
above the 95% similarity (Bray-Curtis) index. From the MDS plot, the samples
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can be clustered into three main groups coinciding with about 94% similarity 
(on the dendrogram), and further clustered into four subgroups, greater than 
95% similarity. Comparing the results of the similarity analysis with the 
sample graphs, the major factors responsible for the sample aggregations 
were salinity and turbidity. This is evidenced by the fact that the four stations 
clustered separately (July A, August A, September A and September B) had 
the lowest salinity and highest turbidity values.
5.2 Benthic Studies
5.2.1 Sediment analysis
The sediment grain size analysis showed that the lagoon sediment in the 
study area over the period studied was basically clayey, with about 50% 
sediment composition being clay or very fine sand. The other half was mainly 
made up of fine sand, some coarse sand and shells/shell fragments.
5.2.1.1 Temporal distribution
A slight increase in the percentage composition of coarse sand was observed 
in May and July, with a concurrent decrease in very fine sand composition. No 
clear reason could be assigned for this, however it is possible that this 
percentage shift was as a result of re-suspension of fine sediment during 
these periods.
The sediment organic matter content was fairly constant over the period 
studied with slight depressions observed in May and in September. It is 
inferred that the organic matter content is mainly generated internally in the
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lagoon, and is influenced to a very small extent by external factors. The 
standard deviation bars however suggest that there is much variation 
observed for the samples taken each month.
5.2.1.2 Spatial distribution
Stations B, C and D had the highest percentage of coarse sediment in the 
study area while Station D had the lowest very fine sand composition. No 
clear spatial pattern was observed in the sediment grain size distribution. 
Stations A, B and C, which were vegetated had high clay/very fine sand 
components. This could be attributed to the vegetation entrapping fine 
suspended sediment matter in solution, causing them to settle. However, 
Stations E and G, which were not vegetated, also had a high clay/very fine 
sand component. It is thought that the clay/very fine sediment at these 
stations may have originated from surface runoff from land.
The high sediment organic matter content observed at Station A, B and C was 
thought to be influenced by decaying matter from dead vegetation in those 
area, which could increase the sediment organic matter content. Stations D 
and G, which are devoid of vegetation, showed low organic matter content. 
Stations E and F on the other hand, though devoid of vegetation exhibited 
high organic matter content. It is thought that the increased sediment organic 
matter observed could have been derived from other areas of the lagoon, or 
from land-based sources.
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5.2.1.3 Cluster analysis
Results from the cluster analysis showed a high similarity between the 
samples. Six main groupings were observed above the 85% similarity (Bray- 
Curtis) index while eleven sub-groups were observed above 90% similarity. 
Some aggregation of samples based on their location in the lagoon was 
observed form the cluster analysis. This clustering is however not considered 
significant enough as to warrant an inference of some strong heterogeneity 
between the stations sampled, based on grain size distribution. It is rather 
inferred from the analysis that very little sediment movement occurred in the 
study area during the study period, accounting for some form of higher 
aggregation of samples from the same stations. Comparing the cluster 
analysis to the sediment graphs, it is deduced that the main factor controlling 
the spatio-temporal distribution of sediment in the study area was the 
presence of clay/very fine sediment.
5.2.2 Benthic fauna analysis
The benthic fauna diversity for the study area was low, compared with studies 
by Finlayson et al. (2000) which recorded higher number of species for the 
entire lagoon. It is however surmised that since Finlayson et al. (2000) worked 
in the entire lagoon, they may have encountered species at other locations in 
the lagoon which were localized to those area and hence were not 
encountered in this study.
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5.2.2.1 Temporal distribution
The temporal distribution of the benthic faunal diversity, with the exception of 
the dominance index, showed a pattern reminiscent of the salinity distribution. 
The Shannon-Wienner index, which incorporates the other diversity indices 
was lowest in January and highest in March and September. This pattern is 
similar to the salinity, TDS and conductivity distribution for the area. The 
species dominance index was the inverse of the evenness index distribution.
5.2.2.2 Spatial distribution
The benthic faunal diversity was highest for Stations C, G and A in decreasing 
order of magnitude. No clear reason could be adduced for this spatial 
distribution since the pattern compares weakly with the water physicochemical 
and sediment property distributions. The distribution pattern can however be 
compared to the sediment organic matter contend distribution, though the 
similarity is rather weak.
5.3 Fishery Studies
5.3.1 Growth, mortality and recruitment
The study on the fish populations indicates that fish catches responded to the 
physicochemical regimes prevailing in the lagoon with periods of high salinity 
recording lower catches. This was inferred from communications with the 
fishers on the lagoon who indicated that they tend to obtain low catches at 
periods coinciding with high salinity. It was hence concluded that salinity 
influenced catches in the lagoon.
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Fish growth can be described by the exponential function of the form relating 
length (y) to weight (x) as follows:
y = axb
The fish growth is said to be isometric if the exponent b = 3 (King, 1995). 
From the length-weight relationships estimated, the following exponents (b) 
was obtained for the cichlids studied:
• S. melanotheron melanotheron = 2.6105
• T. guineensis = 3.0184
• H. fasciatus = 2.9516
This leads to the conclusion of isometric growth for the cichlids studied. The 
growth constant K for the fishes studied, which is an index of the rate of 
growth, were found to compare with values from Fishbase (Froese and Pauly, 
2001) and with previous results obtained in the same lagoon (Ofori-Danson et 
al., 1999). The asymptotic lengths of the cichlids studied were however found 
to be lower than those from Fishbase (Froese and Pauly, 2001) though that 
for S. melanotheron melanotheron was found to be higher than that estimated 
by Ofori-Danson et al. (1999) in the same lagoon. The longevity or lifespan of 
the cichlids, compared to those from Fishbase (Froese and Pauly, 2001), was 
shorter for H. fasciatus but longer for S. melanotheron melanotheron and T. 
guineensis.
The estimated ages of the largest fishes captured were 3 years, 2 years and
2.5 years for S. melanotheron melanotheron, T. guineensis and H. fasciatus 
respectively. The lengths and age of these fishes indicate that they were 
closer to the asymptotic length and their maximum lifespan in the lagoon.
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However, the median length of the fishes caught were 8.0 cm, 9.5 cm and 125 
cm for S. melanotheron melanotheron, T. guineensis and H. fasciatus 
respectively, indicating that they were caught within their first year in the 
lagoon. The inference is that more juvenile fishes are being caught in the 
lagoon, which could result in a high rate of growth overfishing (Pauly et al, 
1989; Beverton and Holt, 1957) occurring in the lagoon. Growth overfishing 
generally results in stunted populations of fish since the exploitation pressure 
would result in premature reproduction by the fishes to regain a balance in 
their populations.
The mortality parameters estimated for the species show that H. fasciatus is 
currestly expoited at optimal levels while S. melanotheron melanotheron and 
T. guineensis are being exploited above the optimal level. The fishery is, 
hence, currently able to maintain itself due to the high recruitment of juveniles 
into the fishery as a result of their high growth rates despite the growth 
overfishing being experienced. This recruitment is evident in a continuous 
recruitment pattern throughout the year with peaks occurring both in the dry 
and wet seasons for the species. Generally, the species studied exhibited a 
bimodal recruitment pattern during a year with H. fasciatus having the most 
distinct modes. The import of this is that there will be several juveniles to 
repopulate the system during the raining season when conditions are less 
stressful.
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5.3.2 Food habits
The result from the food studies indicates that plant material and detritus play 
important roles in the diet of S. melanotheron melanotheron and T. 
guineensis, whereas H. fasciatus is basically a piscivorous predator. The 
fishes did not exhibit any form of specialized feeding during the study period. 
Benthos was rare in the diet of H. fasciatus and not very abundant in the diet 
of the other species. However, this is seen in the light of the fact that benthic 
organisms, being soft-bodied, may be digested faster in the gut of the fishes, 
hence their under-representation in the diet. Hence benthic fauna may well be 
more important, especially in the diets of S. melanotheron melanotheron and 
T. guineensis than was shown in the analysis. This is seen also in the 
presence of large amounts of mud/detritus in the gut of these fishes. It is 
inferred that the fishes sift through the mud for benthic fauna, hence the 
presence of mud in their gut.
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CHAPTER SIX 
CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusion
The study sought to find out the water physicochemical regime, the sediment 
grain size distribution and organic matter content, the benthic macrofauna 
diversity and some population parameters of the major cichlid fishery in the 
study area. The findings indicate that the seasonal precipitation pattern of the 
area was mainly responsible for changes in the lagoon water physicochemical 
regime during the period of the study. The effect is most observed in the 
salinity, conductivity and total dissolved solids (TDS) values, and to some 
extent in the turbidity, total suspended solids (TDS) and nutrient values. The 
suspended matter responsible for turbidity changes are thought to be mainly 
from an external source; carried into the lagoon by the inflowing waters that 
feed the lagoon. The dissolved oxygen (DO) content of the water, the water 
pH and temperature, however, were fairly stable during the period studied. 
However periodic fluctuations observed could cause severe stresses for the 
lagoon biota. The similarity analysis, however, indicate that the samples were 
largely similar between and within stations for the period studied, with minor 
fluctuations under the influence of the seasons. These leads to the conclusion 
that the lagoon water is of a good-enough quality in terms of supporting 
aquatic life.
Several studies (Seiderer and Newell, 1999; Snelgrove and Butman, 1994; 
Palacin etal., 1991; Cacchione and Drake, 1990; Gray etal., 1990; Ishikawa,
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1989; Miller and Sternberg, 1988; Butman, 1987; Grant and Madsen, 1986; 
Nowell and Jumars, 1984; Nowell, 1983; Palmer, 1983; Pearson and 
Rosenberg, 1978; Nichols, 1970; Cassie and Michael, 1968; Sanders, 1958; 
Thorson, 1957) correlating benthic faunal diversity with sediment grain size 
distribution have been carried out with varying results. It is now generally 
accepted that other interactions, in addition to grain size distribution, may be 
responsible for benthic faunal distribution. This study also does not show a 
clear spatio-temporal effect of sediment distribution on benthic faunal 
diversity. However salinity and sediment organic matter content rather 
showed some level of correlation with benthic faunal diversity distribution in 
the study area.
Generally, no major spatio-temporal dynamics could be shown for the 
sediment grain size distribution in the study area. Further, no clear-cut 
dissimilarity could also be proved for the grain size distribution among the 
stations sampled. Hence it is possible that the effect of these factors on the 
benthic sediment diversity could be masked in the study area by other factors 
such as the hydrodynamics of the sediment-water interface and bottom 
boundary-layer flow effects.
The benthic fauna diversity did not indicate any effect of any external 
perturbation on the benthic environment, except salinity changes. Hence it is 
expected that periods of increased salinity could result in a lowered benthic 
fauna diversity. Indeed increased salinity would select for species which are 
able to tolerate such stress, leading to increases in the species dominance
81
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82
index and a reduction in diversity. Since the fishes studied rely to some extent 
on benthic organisms for food, such a stress could affect their nutrition and, 
consequently, their production in the lagoon.
The study on the major fishery resource of the lagoon indicated that even 
though the resource is highly exploited, it is able to maintain itself by rapid 
reproduction at an early age. The reproduction also occurs throughout the 
year. However, if exploitation is maintained at or above the current rate, its 
effect, coupled with that of the stressful environment could result in 
diminishing catches, with catches comprising mainly of small-bodied fishes. In 
the absence of any restriction on fishing or fishing gear, there is a high 
potential for ‘Malthusian’ overfishing (Pauly et al., 1989) resulting in the 
eventual collapse of the fishery and the degradation of the environment itself.
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6.2 Recommendations
The following recommendations are made for management considerations 
and for a more full understanding of the dynamics of the lagoon towards a 
sustainable exploitation and utilization of the lagoon.
• Existing rules and legislation governing the exploitation of the lagoonal 
resource should be strengthened and enforced. This is particularly 
essential with regards to mesh-size restrictions and destructive fishing 
methods so that the fishery does not suffer unduly from the use of 
illegal and unapproved gears and methods. The harmonization and 
strengthening of traditional regulations such as the imposition of no­
fishing days would also help to reduce the stress on the fishery.
• A frame survey should be conducted to estimate the current fishing 
effort in the lagoon, and hence to determine the yield of the lagoon. 
This survey should include a socio-economic component to identify the 
potential effects rules and regulations enforcement would have on the 
riparian communities which depend on the lagoonal resource for their 
sustenance.
• A time-series data should be collected on the lagoonal 
physicochemical state as well as fishery and other resource through 
regular monitoring of the lagoon. This should be done, at least, on 
quarterly basis. The data so obtained should be modeled such that it 
would serve as an early warning system indicative of any major stress 
which could cause damage to the lagoon ecology.
• Alternate sources of livelihood should be made available to the riparian 
communities to reduce the current pressure on the lagoonal fishery
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resource. This could include the encouragement of eco-tourism in the 
lagoon, and the redirection of income generating activities to fishing in 
the adjacent sea and farming on the sandbar through the provision of 
necessary logistics.
84
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85
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APPENDIX
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Appendix A  
Water physicochemical parameters
January: Preliminary studies______________________________________
January
j S ta tio n SAL CON TD S PH DO n o 3_ PO43- S 0 42 S I0 2 Tem p (W ) TS S turbidityI
A 12 22.10 12600 7.74 5.7 1.0 0.25 1500 7.8 30.60 7 11
B 11 18.69 10600 8.09 4.35 0.8 0.19 1300 10.9 31.20 7 11
C 10 18.12 10300 8.05 6.65 0.8 0.83 1300 11.6 33.00 9 11
D g 17.99 10200 8.00 6.55 0.8 0.82 1300 8.4 30.80 15 24
E 10 18.10 10300 8.12 6.6 0.6 0.48 1520 11.0 34.52 5 12
F 10 18.53 10500 7.98 5.85 0.7 1.46 1350 10.9 34.80 5 9
G 10 18.23 10400 7.99 7.25 0.7 2.08 1350 11.2 33.40 4 8
February
■ S ta tio n SAL CON TD S PH DO NOj" P 0 43 SO„J‘ S i0 2 Tem p (W ) TS S turbidityI
A 15 25.40 14300 7.54 4.6 1.6 0.92 1350 12.3 34.60 8 11
B 13 21.90 12400 7.48 5.1 1.3 2.11 1400 10.8 33.50 5 4
C 13 21.10 11900 7.91 7.0 0.8 0.51 1350 12.4 34.20 5 4
D 12 19.44 11100 7.77 6.4 0.9 1.56 1400 10.4 34.00 10 17
E 12 20.30 11500 7.84 6.6 1.1 0.60 1450 12.7 34.10 6 10
F 13 20.80 11800 7.78 6.4 0.9 0.73 1450 11.1 33.70 7 10
G 13 21.00 11900 7.58 6.6 0.9 1.76 2350 11.1 34.50 6 10
March
" S ta t io n S A L C O N T D S PH D O N O 3- P O 43- so42' S i0 2‘ T e m p (W ) T S S turbidityI
A 11 19.04 10800 9.27 5.4 0.5 0.1 1000 12.3 33.90 182 261
B 12 20.1 11400 7.95 5.62 0.2 0.27 2300 11.6 31.20 10 18
C 13 22.1 12500 8.26 5.92 0.3 0.32 1450 12.2 31.90 22 20
D 14 23.2 13200 8.24 5.82 0.4 1.35 1550 8.6 29.80 20 26
E 14 23.7 13400 8.33 6.12 0.4 0.46 1700 10.9 31.10 29 44
F 14 23.9 13500 8.37 5.52 0.4 1.73 1550 9.8 31.20 23 38
G 16 25.5 14600 8.4 8.52 0.4 0.59 2650 11.2 31.30 13 21
April
| Station SAL CON TDS PH DO no3‘ PO43- S042- Si02' Temp(W) TSS tu r b id it y I
A 7 11.4 6320 7.9 6.0 0.5 0.50 550 10.6 31.10 28 22
B 7 12.2 6800 8.07 6.1 0.4 0.50 350 10.7 31.30 11 8
C 11 18.8 10700 8.09 6.2 0.2 0.45 1200 6.7 31.50 14 29
D 18 29.4 16400 8.18 6.1 0.2 0.24 1550 18.4 31.70 10 15
E 16 26.4 14900 8.35 6.3 0.2 0.68 1650 10.7 32.30 21 33
F 17 27.7 15700 8.35 6.2 0.1 1.80 1700 10.1 32.50 21 25
G 14 23.6 13200 8.43 6.3 0.1 2.17 1700 9.4 35.30 26 33
S ta tio n  SA L  CO N  T D S  PH  DO  N 0 3' P O /  SO 4 S i 0 2‘ T em p (W ) T S S  TU R B ID IT Y
10 21.50 12200 7.60 8.0
13 18.17 10300 7.16 3.8
10 17.31 9790 7.82 7.5
12 17.37 9820 7.76 8.3
13 18.13 10200 7.76 8.4
13 18.37 10500 7.88 7.5
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1 Station SAL CON TD S PH DO NO," PO„3' so42 Si02 Tem p (W ) TS S TU RB ID IT Y  I
A 9 14.7 8290 7.78 5.0 0.4 0.16 650 7.5 28.40 7 31
B 8 14.2 7970 7.72 6.05 0.3 0.11 600 8.3 29.00 4 12
C 11 19.0 10800 7.98 6.09 0.3 0.13 1050 10.0 29.30 2 7
D 13 21.5 12200 8.09 5.84 0.1 0.20 1150 9.7 29.40 5 13
E 14 23.8 13500 8.26 8.44 0.2 0.13 1600 8.0 30.40 23 42
F 15 25.4 14400 8.24 3.08 0.6 0.11 1500 7.5 30.50 18 32
G 17 27.3 15400 8.27 4.17 0.2 0.16 1900 7.6 31.20 15 25
June
I S ta tion SA L CON TD S PH DO n o 3‘ p o 43' SO„2' S i0 2 Tem p (W ) TS S t u r b i d i t y I
A 8 13.7 7710 8 6.74 0.7 0.1 1400 7.2 31.50 24 23
B 8 14.6 8220 8.01 6.41 0.7 0.16 850 6.8 31.50 24 30
C 14 23.8 13500 8.14 6.45 0.7 0.06 1300 9.0 30.20 28 32
D 16 26.2 14900 8.53 7.98 0.5 0.02 1550 8.4 27.20 11 5
E 17 28.1 15700 8.31 6.96 0.4 0.07 1650 6.9 28.50 125 186
F 17 30 16800 8.46 6.54 0.7 0.11 1800 5.8 27.90 44 64
G 18 29.7 16700 8.38 6.12 0.8 0.06 1700 5.5 28.30 34 50
| S ta tion SA L CON TD S PH DO n o 3 P 0 43'
OCO S i0 2 T em p (W ) TSS t u r b i d i t y I
A 6 10.8 6000 7.92 6.68 0.2 0.39 550 6.0 27.70 202 295
B 6 10.1 5570 7.87 4.49 0.2 0.13 600 4.3 27.60 99 148
C 18 28.7 16200 8.30 5.31 0.1 0.14 1550 7.0 26.90 28 48
D 21 33.7 19100 8.39 4.87 0.1 0.20 2100 7.9 25.70 51 80
E 12 19.44 1100 8.45 9.18 0.1 1.79 1100 5.0 25.10 128 187
F 20 33.4 18900 8.39 4.94 0.1 0.30 2150 2.7 24.80 196 276
G 23 35.7 23396 8.16 9.31 0.1 0.15 2400 4.2 24.50 51 79
August
5 Station SA L CON TD S PH DO n o 3‘ p o 43- S 0 42- S i0 2‘ T em p (W ) TS S T U R B ID IT Y I
A 5 9.2 5050 7.64 5.2 0.7 0.6 5 5 0 9.5 28 90 65 96
B 5 9.3 5020 7.64 5.4 0.5 0.16 950 7.6 28.90 18 26
C 17 28.0 1600 8.00 6.2 0.4 0.14 1950 5.6 28.70 19 28
D 22 34.1 19500 8.24 6.4 0.4 0.31 1850 6.9 29.60 21 31
E 15 24.2 24297 8.54 6.12 0.5 0.62 2400 4.0 30.00 59 86
F 25 40.1 26197 8.24 5.3 0.6 0.12 2700 10.5 27.80 118 169
G 24 39.6 24497 8.20 8.52 0.5 0.82 2400 4.2 28.00 21 33
September
' S ta tio n SA L CON TD S PH DO n o 3- PO„3' W O A ^ S i0 2" Tem p (W ) T S S t u r b i d i t y I
A 3 5.6 2920 7.45 6.63 0.7 0.3 350 12.7 32.20 63 98.00
B 3 5.6 2950 7.47 6.87 0.7 0.50 400 10.8 31.40 56 81.00
C 18 28.5 16000 7.8 7.08 0.5 0.47 1850 9.7 31.20 12 18.00
D 21 34.0 19300 8.17 7.6 0.3 0.27 1600 6.0 30.70 18 30.00
E 28 44.0 28494 7.98 6.6 0.6 0.27 2900 6.3 28.00 61 87.00
F 30 45.5 29590 8 6.61 0.6 0.29 3300 7.1 27.40 35 53.00
G 28 44.0 29097 8 7.26 0.5 0.22 3200 5.9 27.80 15 22.00
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99
Appendix B 
Sediment grain size distribution
January
1 Station 1 .0 0 0m m 0 .7 5 0 m m 0 .5 0 0 m m 0 .3 5 5m m 0 .2 5 0m m 0 .1 2 5 m m 0 .0 6 3m m > 0 .0 6 3 m m  I
A 1.16.6 3.4828 7.3281 12.0782 19.0508 24.5219 1 8 .4 8 4 3 13.8623
B 2.4776 4.8630 8.3581 11.1599 14.9013 22.4299 21.5597 14.2505
C 2.2312 4.3067 7.3255 9.7842 13.8139 23.0150 14.5176 24.9393
D 1.5073 5.7784 13.3559 17.2802 20.0077 23.5723 6.9671 11.5311
E 0.6164 2.3396 5.9864 10.5428 18.5677 35.9248 15.8692 10.1532
F 1.8438 4.4078 7.9684 11.5014 17.3101 25.6153 17.1232 14.2291
G 0.8746 2.0251 5.2059 8.6118 13.3507 38.1396 12.4158 19.3765
March
|  Station 1 .0 0 0m m 0 .7 5 0 m m 0 .5 0 0 m m 0 .3 5 5 m m 0 .2 5 0m m 0 .1 2 5 m m 0 .0 6 3m m > 0 .0 6 3 m m  1
A 1.4862 3.5074 6.8271 10.7223 16.6332 20.5341 14.4456 2L .3441
B 1.4536 5.0816 9.3348 12.6616 19.2116 31.2762 14.4242 6.5565
C 1.9952 4.8326 9.2429 13.7538 20.1970 24.8650 9.6889 15.4246
D 2.8944 7.9837 15.2125 18.5924 18.3223 18.3231 7.1908 11.4809
E 1.1591 2.6031 5.2986 9.0335 17.4892 34.8735 15.7364 13.8066
F 2.7851 4.0932 6.7176 9.9371 15.7191 29.4606 10.0911 21.1963
G 0.6098 1.8951 5.1243 8.6137 14.2290 34.8752 13.7986 20.8544
May
I  Station 1 .0 0 0m m 0 .7 5 0 m m 0 .5 0 0 m m 0 .3 5 5m m 0 .2 5 0m m 0 .1 2 5 m m 0 .0 6 3 m m > 0 .0 6 3m m  |
A 2.3347 4.9601 d.9Ub-t 1 3 .5 8 6 7 19.4662 22.4547 14.2301 14.0579
B 7.3499 9.0234 11.6870 12.6412 14.1660 19.6259 15.2361 10.2707
C 4.1774 7.9481 11.7909 14.0216 15.3629 21.6239 11.2295 13.8457
D 5.6235 11.0174 17.4325 19.1027 18.0982 16.8649 3.9199 7.9410
E 1.1390 2.9806 9.3361 15.9409 20.4102 22.5592 16.1599 11.4742
F 1.4464 3.1492 6.0709 9.5246 13.4553 27.5765 31.0754 7.7017
G 1.3402 5.3467 9.6379 12.3121 19.6175 31.7026 13.7692 6.2738
July
11 Station 1 .0 0 0 m m 0 .7 5 0 m m 0 .5 0 0 m m 0 .35 5m m 0 .2 5 0 m m 0 .1 2 5 m m 0 .0 6 3m m > 0 .0 6 3 m m  |
A 1 .0 5 9 5 2.3182 4.3844 7.030b 14.1765 28.1714 22.3784 20.4811
B 7.1907 8.5941 11.1737 12.7329 15.0996 19.5413 14.2031 11.4647
C 3.8073 6.0223 8.6741 9.7854 13.7298 21.7352 14.2193 22.0266
D 4.6119 8.9999 14.5176 17.0514 18.9703 20.0827 4.4077 11.3585
E 2.8823 6.8459 12.7315 15.5316 21.7700 24.2038 6.4836 9.5513
F 3.1101 5.4643 10.8984 8.5995 13.0028 23.4910 18.0852 17.3487
G 0.8001 4.2168 10.1364 14.1232 20.9407 21.5930 13.2825 4.9073
Seotember
I Station 1 .0 0 0m m 0 .7 5 0 m m 0 .5 0 0m m 0 .35 5m m 0 .2 5 0m m 0 .1 2 5m m 0 .0 6 3m m > 0 .0 6 3 m m  I
A z : : o . 7 5.1923 10.0743 14.9648 21.4278 23.3202 13.4247 9.2982
B 7.2638 8.2233 9.9895 11.1017 13.0339 19.6222 20.2696 10.4961
C 5.5105 8.4518 12.4257 13.9226 14.9510 20.3607 10.4344 13.9432
D 4.7169 10.5220 16.9065 18.7212 18.8660 19.0591 4.2262 6.9820
E 0.3933 1.3912 3.9744 7.9735 14.3251 32.5336 23.3152 16.1037
F 3.0424 4.1763 6.2325 8.7158 11.8757 20.6182 23.0215 22.3176
G 0.5738 2.7897 7.3656 12.1537 19.9725 33.4412 15.7265 6.9771
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Appendix C
Sediment organic (detrital) matter content (mg/g)
Station Jan Mar May Jul Sep
A 0.9530 0.b940 0.5840 1.3910 0.6180
B 0.9970 1.9470 0.7280 0.8260 0.7330
C 2.1290 0.8340 1.2420 1.5640 0.9800
D 0.5730 0.8590 0.7010 0.5580 0.5150
E 0.6650 1.3780 1.4510 0.9750 1.0920
F 1.1590 0.7730 0.2850 1.3530 1.8260
G 0.2710 0.4320 0.5350 0.3660 0.5740
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Appendix D 
Mean diversity indecies
January
I S ta tio n R ich n ess Shannon Evenn ess S im p son  1
A 1.08 1.21 0.8b 0.30
B 0.48 0.56 0.81 0.57
C 0.54 1.08 0.98 0.33
D 0.42 0.53 0.48 0.74
E 1.04 1.37 0.77 0.30
F 0.68 0.89 0.64 0.50
G 1.00 0.73 0.41 0.67
March
1 S ta tio n R ic h n e s s Shannon E venness S im p son  1
A 1.44 1.39 1.00 0.14
B 1.03 1.45 0.90 0.24
C 1.03 1.43 0.89 0.25
D 1.25 1.43 0.73 0.30
E 1.28 1.59 0.89 0.23
F 0.76 0.74 0.46 0.63
G 1.42 1.54 0.70 0.27
May
' S ta tio n R ichn ess Shannon E venness S im p son  I
A 0.87 1.28 0.93 0.28
B 0.87 1.22 0.88 0.30
C 1.10 1.33 0.83 0.30
D 0.88 0.72 0.52 0.64
E 0.75 0.68 0.49 0.67
F 1.14 1.15 0.83 0.34
G 1.39 1.35 0.65 0.34
July
S ta tio n R ichn ess Shannon E venness S im pson  |
A 0.69 1.06 0.97 0.32
B 0.91 0.75 0.47 0.65
C 1.52 1.74 0.89 0.19
D 0.96 1.64 0.92 0.20
E 1.06 1.08 0.61 0.47
F 0.64 1.02 0.74 0.42
G 1.22 1.58 0.81 0.25
September
1 S ta tio n R ichn ess Shannon E venness S im pson
A 0.96 1 .0 4 0.95 0.29
B 0.65 1.25 0.90 0.32
C 1.27 1.44 0.81 0.28
D 1.51 1.48 0.67 0.30
E 0.67 1.03 0.74 0.40
F 1.04 1.51 0.94 0.22
G 0.93 1.52 0.78 0.26
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Appendix E
Length-frequency distribution offish samples (grouped data)
Sarothprodon melanotheron melanotheron
| Mid class Jan Feb Mar Apr May Jun Jul Aug Sep
4.5 6 1 2
5.5 2 16 4 6 10
6 .5 4 18 7 6 2 13 19 3
7 .5 5 2 14 30 12 6 26 13 10
8.5 6 6 9 11 14 23 16 9 16
9.5 8 11 5 9 9 18 7 7 8
10.5 14 16 2 23 5 9 5 8 8
11.5 20 12 1 7 9 2 0 5 5
12.5 12 5 2 2 1 1 0 2 3
13.5 6 4 1 1 0 2
14.5 4 6 1 1
15.5 1 12 1
16.5 6
17.5 2
18.5 2
19 .5
20 .5
Tilapia guineensis
Mid class jan Feb Mar Apr May Jun Jul Aug Sep
4 .5 1
5 .5 1 3 1 3 2
6.5 4 2 2 4 4 2 5 3
7.5 9 6 4 3 9 3 9 5 6
8.5 19 14 8 12 18 7 7 6 9
9.5 28 16 6 16 17 12 11 6 12
10.5 11 21 10 8 5 15 21 11 17
11.5 7 10 15 6 3 9 16 18 22
12.5 3 4 4 3 1 8 5 9 10
13.5 1 2 3 2 5 6
14.5 2 2 1 3
15.5 1
16.5
17.5
18.5
19.5
20 .5
Hemichromis fasciatus
1 Mid class Jan Feb Mar ADr May Jun Jul Aug Sep
4 .5
5.5 5 1
6.5 2 4 3 2 0
7.5 6 3 2 4 9 8 3 2
8.5 8 2 2 7 8 14 3 5
9.5 16 4 3 4 6 10 14 8 5
10.5 18 13 4 5 10 23 11 14 6
11.5 14 12 3 11 25 14 16 16 13
12.5 9 16 12 25 16 9 24 17 19
13.5 4 8 18 15 8 9 10 16 21
14.5 3 3 10 9 3 4 8 23 11
15.5 2 4 0 2 7 12 3
16.5 4 6 3 6 4
17.5 5 6 2 6 3
18.5 3 2 4 0
19.5 1 0
20.5 1
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Appendix F: Plates
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A gill net: A fishing gear used in the Keta lagoon
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Using a GPS receiver to locate stations in the lagoon (near Fiahor)
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Taking in situ  water parameters (DO)
Taking sediment samples with a PVC corer
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A densely vegetated portion of the lagoon, close to Station B
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A scene at the Anloga landing
Fish catches at the Anloga landing
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