Journal of Environmental Protection, 2011, 2, 304-315
doi:10.4236/jep.2011.23034 Published Online May 2011 (
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of
Three Tropical Lakes
Benedict Obeten Offem, Ezekiel Olatunji Ayotunde, Gabriel Ujong Ikpi, F. B. Ada,
Steven Ncha Ochang
Department of Fisheries and Aquatic Sciences, Cross River University of Technology Obubra Campus, Obubra, Nigeria.
Received January 5th, 2011; revised February 19th, 2011; accepted March 31st, 2011.
In developing countries, lakes being important sources of water supply and fishing are vulnerable to anthropogenic
impact, yet knowledge of their troph ic state in relation to chang es in species composition , and environmental variab les,
are limited. This study is aimed at assessing the tro phic status of la kes by monthly samplin g of three la kes loca ted along
the floodplain of Cross River, Nigeria between January 2008 and December 2009. Samples were analyzed for water
quality parameters , zooplankton and phytoplankton composition and distribution. Results were subjected to community
structure analysis using trophic state index, species richness and diversity indexes. Essential primary productivity nu-
trients, nitrates, sulphates and phosphates were highest in Ejagham Lake, and lowest in Ikot Okpora Lake. Dominant
phytoplankton species Oscillatoria lacustria (Cyanophyceae), Cyclotella operculata (Bacilliarophyceae) and zoo-
plankton Keratella tropica, Keratella quadrata , Filinia longiseta , Branchionus anguillaris and Trich ocerca pusilla (ro-
tifers) all typical of eutrophic communities were recorded in high densities in Ejagham Lake in both dry and wet sea-
sons while Cladocerans, Bosmina longirostris and Moina micrura and copepods considered indicators of oligotrophy
and mesotrophy were reco rded in large numbers in Iko t Okpora and Obubra Lakes respectively. High er values of spe-
cies richness, Evenness and Shannon- Wiener diversity index for both ph ytoplankton a nd zooplan kton, were recorded in
Ejagham Lake during the dry season than wet. Also values of the Trophic state index were generally highest at the
Ejagham Lake in the savanna region of the floodplain and lowest at Ikot Okpora in the forest region of the floodplain.
Forest region is therefore a limiting factor in the productivity of lakes in the tropics.
Keywords: Zooplankton, Phytopl an kton, Trophic Stat e I ndex, Diversity Indices, Species Richness
1. Introduction
Biological approaches to evaluating water quality in-
volve assessing communities of organisms. “The basis
for this approach is that different species have varying
tolerances to environmental stressors” [1]. Fish produc-
tivity of water bodies is connected to primary production
by many intermediate trophic links. The four groups of
organisms that appear in The European Water Frame-
work Directives WFD (Phytoplankton, Zooplankton,
Fish and macrophytes), represent water ecological struc-
ture over a range of temporal and spatial scales and func-
tional roles. It was recommended that the above biologi-
cal indicators and, in addition to a range of supporting
hydro-morphological and physico-chemical elements
should form the core of any monitoring program on lakes
[2]. Seasonal changes in mean temperature, radiations,
hydrology and nutrient availability are the most impor-
tant variables which determine plankton abundance [3].
Also the qualitative and quantitative estimates of the
plankton provide good indices of quality and productive
capacity of water.
The estimation of phytoplankton density, productivity
and trophic status of lakes is very important for fisheries
management especially in Nigeria because of dominant
tilapia fish culture. The trophic status of a water body is
usually estimated by values of primary production meas-
ured for the growing season. Classification of lakes
based on quantitative trophic indicators such as phos-
phorus (P) concentration, chlorophyll-a and transparency
also allow the trophic status of lakes on a large gradient
to be defined [4]. However, these parameters are not al-
ways relevant for short-term evolution within any given
lake, especially when variations in phosphorus concen-
tration are low. The values of chlorophyll-a (μg·l1) are
mostly used as the basic criteria, because it is relatively
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes 305
easy and inexpensive to measure and it is a generally
used biological measure of phytoplankton biomass and
relatively few measurements are needed to get reliable
mean value [5]. Carlson’s Trophic State Index (TSI)
classification [6] can be used to provide a single trophic
criterion for the purpose of classifying and ranking water
bodies in complex multi-wetland systems. Secchi depth
is a much debated and used variable in lake management.
Secchi disk transparency is a standard indicator of water
clarity, which is strongly correlated with biomass and
annual productivity of suspended algae. This is also
closely related to the amount of sandy clay, detritus and
organic and inorganic suspended and dissolved matter in
water [7].
The use of zooplankton community structure as indi-
cator of the wellbeing of water body dates back to 1879-
1910 [8]. Zooplankton is an important component of the
trophic food webs of lakes because of its particular posi-
tion at the crossroads of carbon and energy flows from
the lower levels of food chains to fish. Zooplankton
biomass which is part of secondary production of lakes is
bottom-up regulated by the availability of bacteria and
phytoplankton as food and top-down controlled by pre-
dation from fish etc. [9]. The composition of zooplank-
ton especially in relation to filter feeders depends on the
quality of nutrient supply. So some zooplankton species
(mainly rotifers, branchiopods and copepods) could be
used as indicators of lakes trophic status [10] because
their composition is affected by any of the several envi-
ronmental parameters e.g. pH or alkalinity and salinity
and other biological parameters [11-13]. Zooplankton
abundance is usually closely related to phytoplankton
concentration and species composition and increases
with increasing nutrients concentrations [14].
Biodiversity is also one of the promising ecological
criteria that could be added to lake monitoring pro-
grammes. Plankton richness within lakes appears to be
largely controlled by factors related to productivity, wa-
ter quality and fish predation levels. Diversity indices,
such as Shannon-Weaner index appeared to detect sig-
nificant differences in the structure of the communities.
Around the world several researches have been carried
out using phytoplankton and zooplankton to investigate
pollution [15-19] because they are relatively easy to
identify, particularly when community sensitivity can be
detected based on plankton body sizes or gross taxo-
nomic classifications. Eastern Nigerian lakes in particu-
lar being important sources of water for drinking, fishing
and domestic use are vulnerable to anthropogenic impact,
yet there is limited water quality data [20,21]. This is the
first-ever baseline study of the condition of the nation’s
akes in eastern Nigeria using statistically valid approach.
It will help the government of the region implement lake
monitoring and assessment programs, establish a base-
line for lake condition that can be used for future trend
assessment. It is focused on studying plankton diversity
and evaluating trophic status of some wetlands of East-
ern Nigeria for the first time.
2. Materials and Methods
2.1. Study Site
The Cross River, a floodplain river in south-eastern Ni-
geria between latitude 4˚25' - 7˚00'N and longitude 7˚15'-
9˚30'E, is bounded in the south by the Atlantic Ocean,
east by the Republic of Cameroun and the Nigerian states
of Benue in the north, Ebonyi and Abia in the west and
Akwa Ibom in the south-west (Figure 1). The climate of
the study area comprises a wet season (April- October)
characterized by high precipitation (3050 ± 230 mm) and
a dry season (November - March) marked by low pre-
cipitation (300 ± 23 mm) [22]. Temperatures range from
15.5˚C ± 7.6˚C in the wet season to 32.6˚C ± 5.4˚C in the
dry season [20]. Along the floodplain of Cross River are
located series of wetlands consisting of lakes, ponds and
swamps. The main source of water for these lakes is
rainfall and flood water from the river. For the purpose
of this study, three lakes were randomly selected along
the floodplain of The Cross River, one each from upper
section of the floodplain (Ejagham lake), middle portion
(Obubra Lake) and down section (Ikot Okpora Lake).
Ikot Okpora Lake covers an area of 4 hectares and has
maximum depth of 8m with a muddy substratum. The
lake is used mainly for fishing and has a shoreline
thickly shaded by rainforest preventing the effect of di-
rect sunlight rays on the lake water. The lake was almost
covered by water hyacinth at the peak of wet season.
Bamboo (Bambusa bambusa), Palm trees (E. guinensis)
and some other trees characteristics of typical rainforest
were present. There was palm oil processing mill near
the station and common human activities included
drinking, bathing, washing and fishing. Obubra Lake had
a rocky, gravel and sandy substratum and covers 4 hec-
tares with maximum depth of 6 m with shoreline sparsely
shaded by forest and savanna grassland. Ejagham Lake,
has a sandy and silt dominated substratum opened to
direct effect of sunlight ray and shoreline dominated by
dense macro-flora Ipomoea pestigridis, Monechma
ciliatum, Eragrostic p ilosa and Setaria pallid e-fusia. The
most visible human activities and excavation of sand.
2.2. Sampling Techniques
Monthly sampling of the three lakes was carried out from
anuary 2008 to December 2009 at the middle of every J
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes
Copyright © 2011 SciRes. JEP
Figure 1. Map of Cross River State showing sampling sites (Source: Cross Riv er State Ministry of lands and survey).
month, between 8 a.m. and 11 a.m. every sampling day.
2.3. Water Quality Parameters
Temperature values were recorded from a mercury-in
glass thermometer graduated in units of ˚C by immersing
the thermometer slightly under the surface of water (2
cm) for 5 minutes until mercury stood at one place). Pye
Unicam Model 7065 electronic metre at 25˚C after stan-
dardization with buffer solution at pH 4, 7 and 9 was
used for pH. Dissolved oxygen concentration of the wa-
ter samples was determined with a Jen-way 9071 digital
oxygen analyzer. Water transparency was measured by
use of Secchi disc [23]. The disc was lowered into water
and the depth at which it became invisible was recorded.
It was then gradually withdrawn from the water and the
depth at which it became visible was noted. The trans-
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes 307
parency of the water at that station was the mean of the
two readings. For the total dissolved solids (TDS), the
Hach TDS meter was put on, the reading zeroed and then
the electrode dipped into the water sample and the read-
ing taken. Conductivity was assessed by putting on the
Suntex conductivity meter, adjusting the reading portion
and dipping the meter into the water sample and ap-
proximate reading taken. Total hardness, free Carbon
dioxide, Acidity, Chemical Oxygen Demand, was ob-
tained by titrimetric method [24]. Biological Oxygen
Demand was determined by difference between initial
and final dissolved oxygen after incubation for 5 days at
room temperature of (20˚C). Total alkalinity was meas-
ured by titrating water samples with sulphuric acid stan-
dard solution, using a drop of phenolphthalein solution
and one sachet of bromcresol green-methyl red as indi-
cator, until the sample changed from blue green to pink.
Total alkalinity which is expressed in mg/L is the total
number of drops of sulphuric acid solution used multi-
plied by 17.1 (Fish Farmers’ Water Quality Testing Kit
Manual, 1990). Nitrate and Phosphate were measured
with brucine and Ascorbic acid methods respectively.
Salinity was determined using hand held refractometer
(S/mill-E 0-100%). Bicarbonate ion was measured with
pH electrode dipped into the tip of the conical container.
Sample water was passed through until a constant read-
ing was obtained and a marble powder was added, to
completely cover the electrode ball. After about 2 min-
utes, the pH was read again. The temperature of the mar-
ble was monitored with thermometer during measure-
ment. Carbonate ions was determine by placing hydro-
chloric acid, between 2 and 10 ml of water sample in a
gas generator and insert tube filled with 20 ml hydro-
chloric acid (10%). After connecting to the apparatus, the
graduated tube was filled by raising the level container.
The gas generator was then tilted so that the hydrochloric
acid makes contact with the floor. A pressure compensa-
tion was attained by sinking the container so that, after
about 10 minutes the gas volume can be read. Color was
determine by assembling Filter apparatus (membrane
filter, filter holder, aspirator and folter flask) and allowed
about 50 ml of dematerialized water to pass through to
rinse the unit. Discard rinse water. Approximately 50 ml
of water sample was filtered and 25 ml poured into an-
other clean cell. The dematerialized water was placed in
a cell holder and sample compartment door was closed.
The demineralization was used to set the zero concentra-
tion point.
2.4. Phytoplankton
Planktons were collected in sterilized, one-litre wide
mouth dark colour plastic bottles at each sampling sta-
tion, reduced to 10 ml by decanting the supernatant ali-
quot and preserved with Lugol’s solution. Samples were
shifted to laboratory where they were identified after
Prescott [25], Edmondson [26] and John et al. [27]. For
Chlorophyll-a analysis 100 ml water sample were filtered
through Millipore micro filters (47 mm; 45 μm pores).
Concentration of Chlorophyll-a in supernatant was de-
termined by spectrophotometer, with absorbance at 665
nm and 750 nm [28].
2.5. Zooplankton
Zooplankton was collected by towing a-55µ mesh-sized
plankton net against the current flow at the subsurface
level for two minutes [29]. The filtered samples were
washed into the sterilized collecting bottles and immedi-
ately fixed in 4% formalin. The percentage relative
abundance of the specimen was estimated by irect count.
Each quantitative sample was concentrated to 10 ml and
from this; 1 ml of sample was taken and all individual
taxa present were counted. Relative abundance was cal-
culated as the number of individuals per liter of water
filtered though the net. They were identified with an
Olympus Vanox Research Microscope (mag X60) Model
230485 using keys given by Kadiri [30] and Kemdirim
2.6. Community Structure Analysis
Trophic state index based on Secchi Depth TSI (SD) and
Trophic state index based on Chlorophyll-a, TSI (Chl-a)
and that based on phosphorus, TSI(TP) were calculated
after Carlson [32] using the following equations:
TSI (Secchi Disk) = 60 14.1 In (SD) where SD is Secchi
Disk in meters(m)
TSI (Chlorophyll a) = 9.81(In Chl-a) + 30.6 where Chl a
is mean chlorophyll a in μg·l1 TSI (Total Phosphorus) =
14.41 ln (TP) + 4.15 where TP is mean total phosphorus
in μg·l1.
Diversity indices used were species diversity (H
species richness (d) and species evenness. Shan-
non-Weaner diversity function was used to calculate het-
erogeneity for each site. This index takes into account the
total number of species present as well as their respective
abundance thus providing a more convenient means of
comparing differences between ecological communities.
These changes in the environment are reflected in the
types and number of organisms.
Richness index was expressed using Margelef’s rich-
ness index. This measure relies only on the number of
taxa. Richness increases when abundance is spread over
a greater number of categories but does not take into
account the evenness of the distribution. Also between
two samples with the same S, richness will be higher in
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes
Copyright © 2011 SciRes. JEP
the one with lower abundance. Evenness Index, which
expresses the degree of uniformity in the distribution of
individual among the taxa in the collection [33] was also
were least in Ejagham Lake. Other variables showed no
significant spatial differences (p > 0.05).
3.2. Phytoplankton
 
S1logNEquation 1d  A total of 46 planktonic algae from 5 taxa were recorded:
17 Bacillariophyceae, 19 Chlorophyceae, 8 Cyanophy-
ceae, 1 Chrysophyceae and 1 Euglanaphyceae (Table 2).
There was significant seasonal and spatial variation in
the phytoplankton abundance and distribution. Apart
from Rhyzosolenia longiseta, Melosera varians,
Cyclotella operculata, Chlorococcum humicolum, Clos-
teridum lanceolatum Golonotozygon aculeatum,
Sphaerocystis species, Raphidiopsis species, Epithermal
zebra, Chlamydomonas atactogam, Closteriopsis long-
issinna, Golonotozygon aculeatum Schizoponium praisi-
ola, Tetrahedron species, Spirulina substilissinna, Co-
lactum cyclopicola, Closterium junoidum and Golo-
notozygon aculeatum that had higher wet season counts,
all other species in the three lakes had higher dry season
counts. The highest number of algal counts was recorded
in the Ejagham Lake while the least occurred in Ikot
Okporo. Cocconeis dimunuta, Oscilatoria Lacustria and
Dinobryon species were however completely absent
from the Ejagham Lake. The observed dominant species
in the Ejagham Lake, during both wet and dry seasons
was Oscillatoria lacustria (Cyanophyceae) closely fol-
lowed by Cyclotella operculata (Bacilliarophyceae) while
Splog p Equation
H SEEquitabilityE=
d = Margalef’s richness index and H' = Shanon-Wiener
Diversity Function
S = total species number
pi = proportion of each species in each sample,
besides the application of diversity indices, inter-stations
comparison were carried out to test for significant dif-
ferences in faunal abundance using one-way analysis of
variance (ANOVA) [34].
3. Result
3.1. Environmental Conditions
As shown in Table 1, significant spatial variation with
higher values (p < 0.05) was observed for air temperature,
surface temperature, turbidity, alkalinity, conductivity,
BOD, phosphates, sulphates, chlorides, calcium, magne-
sium, silicon, total hardness, total solids and total dis-
solved solids in the Ejagham Lake than Obubra and Ikot
Okpora Lakes while Dissolved Oxygen and alkalinity
Table 1. Mean (± SD) values of some physical and chemical characteristics of the three lakes (Ikot Okpora, Obubra and
Parameters Ikot Okpora Obubra Ejagham
Total Storage (m3) 638a 1099b 1236b
Lake Area (ha) 45.4 ± 8.76a 51.3 ± 5.66a 76.4 ± 12.34b
Mean Depth (m) 8.2 ± 2.81 a 7.6 ± 3.23 a 8.9 ± 2.45a
Air Temperature (°C ) 30.9 ± 2.23 a 32.5 ± 1.84 a 34.4 ± 3.42b
Surface Temperature (°C) 27.7 ± 1.71 a 29.4 ± 2.11 a 33. 8 ± 2.89 b
Turbidity(NTU) 12.5 ± 2.23 a 66.9 ± 6.33b 132.4 ± 23.34c
Ph 6.5 ± 0.66a 7.2 ± 1.12a 6.8.5 ± 1.81a
Dissolved Oxygen(mg·l1) 3.2 ± 1.21a 2.7 ± 0.89b 2.3 ± 0.76c
Alkalinity (mg·l1) 53.2 ± 4.42a 40.8 ± 5.43b 67.4 ± 12.98c
Conductivity (μS·cm1) 22.4 ± 14.78a 87.6 ± 10.32b 102.8 ± 16.78c
BOD (mg·l1) 1.4 ± 1.66a 2.6 ± 0.87b 4.5 ± 1.64c
Phosphates (mg/l) 0.5 ± 0.01a 1.5 ± 0.04b 2.5 ± 0.23c
Calcium (Ca2+) 10.4 ± 3.4a 9.3 ± 2.87a 19.4 ± 4.83b
Magnesium (Mg2+) 1.8 ± 0.22a 2.1 ± 0.54a 3.2 ± 0.99b
Total iron 1.4 ± 0.56a 0.7 ± 0.43a 1.9 ± 0.36a
Silicon (SiO2) 38.9 ± 2.89a 28.4 ± 5.34b 56.8 ± 9.65c
Sulphates (SO4) 11.4 ± 1.23a 14.8 ± 2.88a 19.8 ± 7.81b
Nitrates (NO3) 0.2 ± 0.78a 0.4 ± 0.34b 0.8 ± 0.56a
Chlorides (Cl) 13.6 ± 5.99a 11.6 ± 3.21a 18.8 ± 6.77b
Total hardness 57.5 ± 8.88a 94.3 ± 6.54b 143.5 ± 23.56c
Total solids (mg/l) 68.9 ± 12.34a 187.6 ± 8.76b 208.3 ± 54.50c
Total Dissolved solids (mg/l) 59.8 ± 6.54a 178.5 ± 6.66b 222.8 ± 65.44c
Values in the same rows with the same superscript are not significantly different (p > 0.05).
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes 309
Table 2. Phytoplankton of Ikot Okpora, Obubra and Ejagham Lake s dur ing we t (W) and dr y (D) seasons.
Season .Okpora WD Obubra W D Ejagham W D
Phytoplankton Species No/ml No/ml No/ml No/ml No/ml No/ml
Tabellaria Flocculosa 34 49 87 192 134 234
Synedra Cyclopum 00 65 09 87 26 198
Suriellia Spiralis 00 50 00 76 00 86
Rhyzosolenia Longis e t a 122 36 156 48 222 433
Melosera Varians 134 88 223 176 320 482
Navicula Rostellata 00 98 102 267 243 543
Nitzschia Closterium 89 101 112 344 176 410
Cytosigma Attenuatum 67 45 136 233 267 309
Flagilaria Intermedia 94 222 87 342 120 654
Epithermal Zebra 34 98 243 132 298 499
Cocconeis Dimunuta 00 76 00 67 00 00
Cymatopleura Solea 65 98 98 200 110 222
Cyclotella Glomerata 76 118 99 199 230 349
Cyclotella Comta 00 223 87 322 167 276
Cyclotella Operculata 816 1464 511 1389 624 1195
Amphora Ovalis 222 553 87 627 187 299
Amphilpleura Pellicuda 98 112 202 322 324 562
Spirogyra sp 223 655 127 498 242 576
Chlorococcum Humicolum 232 98 299 456 342 399
Chlamydomonas Atactogam 67 633 276 202 433 00
Closteriopsis Longissinna 87 87 123 00 234 488
Codiolum Gregarii 99 211 97 110 178 876
Closterium Jennen 77 199 88 290 134 489
Drapamidia Species 00 120 155 388 209 119
Neomens Dumetosa 72 432 87 282 198 198
Charales Fragilis 00 87 54 389 123 467
Shroeederia Setigera 39 108 98 98 176 198
Closterium Junoidum 00 56 63 187 233 67
Closteridum Lanceolatu m 95 73 59 78 00 78
Golonotozygon Aculeatum 66 18 167 56 234 378
Schizoponium Praisiola 101 193 91 21 145 576
Serastrium Spinolosum 56 198 66 134 133 366
Spirotaenna Condensate 78 97 102 167 187 266
Volvox Aurus 39 67 23 101 43 102
Sphaerocystis Spe c ie s 100 44 00 122 00 736
Tetrahedron Species 00 194 233 65 129 234
Oscilatoria Lacustria 12 23 54 32 1878 2842
Pharmidium Species 101 134 55 71 134 1120
Spirulina Substilissinna 00 134 129 76 489 1564
Rivularia Plankton 81 234 31 92 87 342
Anabaena Species 0 67 78 102 110 1290
Microcystis Species 230 1222 188 981 1558 2733
Anabaenopsis Species 0 26 83 233 134 556
Raphidiopsis Speci es 33 0 45 00 987 1234
Dinobryon Species 1 2 0 12 0 0
Colactum Cyclopicola 00 32 34 0 78 324
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes
Copyright © 2011 SciRes. JEP
Table 3. Seasonal variation of phytoplankton diversity indices in Ikot Okpora, Obubra and Ejagham Lakes.
Lakes Phytoplankton Seasons Dorminance Evenness Margalef Shan non
Bacillariophyceae Wet
0.17 ± 0.03a
0.43 ± 0.02b
0.76 ± 0.13a
0.56 ± 0.34b
3.24 ± 0.12a
3.97 ± 0.23a
0.45 ± 0.17a
0.95 ± 0.22b
Chlorophyceae Wet
0.22 ± 0.01a
0.48 ± 0.02b
0.66 ± 0.04a
0.58 ± 0.11b
3.45 ± 0.21a
3.89 ± 0.33a
0.59 ± 0.14a
0.89 ± 0.28b
Cyanophyceae Wet
0.13 ± 0.15a
0.35 ± 0.11b
0.81 ± 0.13a
0.61 ± 0.23b
2.31 ± 0.19a
2.81 ± 0.26a
0.36 ± 0.19a
0.66 ± 0.28a
Chrysophyceae Wet
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
Ikot Okpora
Euglenaphyceae Wet
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ±0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
Bacillariophyceae Wet
0.12 ± 0.01a
0.18 ± 0.03b
0.91 ± 0.10a
0.89 ± 0.19b
3.76 ± 0.17a
3.97 ± 0.29 a
1.03 ± 0.15a
1.76 ± 0.21b
Chlorophyceae Wet
0.29 ± 0.05a
0.17 ± 0.11b
0.66 ± 0.21a
0.79 ± 0.11b
3.91 ± 0.19a
4.11± 0.26a
1.05 ± 0.33a
1.88 ± 0.29b
Cyanophyceae Wet
0.23 ± 0.06 a
0.44 ± 0.13b
0.82 ± 0.17a
0.54 ± 0.29b
3.11 ± 0.22a
3.88 ± 0.16a
0.68 ± 0.16a
1.22 ± 0.19b
Chrysophyceae Wet
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
Euglenaphyceae Wet
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
Bacillariophyceae Wet
0.23 ± 0.16a
0.36 ± 0.21b
0.84 ± 0.18a
0.54 ± 0.32b
3.85 ± 0.25a
4.32 ± 0.28a
1.69 ± 0.33a
2.88 ± 0.21b
Chlorophyceae Wet
0.18 ± 0.05a
0.64 ± 0.29b
0.95 ± 0.22a
0.42 ± 0.17b
4.21 ± 0.14a
4.87 ± 0.21a
1.55 ± 0.14a
2.97 ± 0.43b
Cyanophyceae Wet
0.540 ± 0.07a
0.86 ± 0.16b
0.44 ± 0.14a
0.29 ± 0.23b
2.88 ± 0.24a
3.07 ± 0.18a
1.69 ± 0.22a
1.92 ± 0.19a
Chrysophyceae Wet
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
Euglenaphyceae Wet
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
0.00 ± 0.00
Means with the same superscript are not significantly different (p>0.05).
the least species recorded was Dinobryon species
(Chrysophyceae).There were significant seasonal varia-
tions of species diversity indices for all phytoplankton
taxa (p < 0.05) except Margalef index none for all the
species from the three lakes (Table 3).
3.3. Zooplankton
A total of 26 zooplankton species consisting of 4 taxa
were recorded (Table 4). Rotifers (9) and Cladocerans (8)
had the highest representation by species followed by
Copepoda (5) while Decapods were least represented (4).
Among the rotifers, Keratella tropica, Keratella quad-
rata, Filinia longiseta, Branchionus anguillaris and
Trichocerca pusilla and cladocerans, Ceriodaphnia cor-
nuta, Chydorus sphaericus and Diaphanosoma excisum
were common in Ejagham Lake. Rotifers like Synchaeta
longipes and Conochilus dossuarius and Cladocera,
Bosmina longirostris and Moina micrura were recorded
in high densities in Ikot Okpora Lake. Cyclopoid cope-
podids and nauphlii increased the population of Cope-
poda particularly in Ikot Okpora Lake during dry season
while the numerical abundance reduced drastically in
Ejagham Lake.
Seasonal variation of species diversity indices for zoo-
plankton were significant (p < 0.05) for all 3 lakes (Ta-
ble 5). However, seasonal variation of Margalef index
was not significant for all species in the 3 lakes. Higher
values of species richness, Evenness and Shannon-Wie-
ner diversity index were recorded during the dry season
than the wet.
3.4. Trophic State Index
In the three lakes studied chlorophyll-a concentration
increased in dry season and decrease in the wet. Trophic
State Index dry season values based on Chlorophyll-a,
Secchi Disk and Phosporus were generally highest at the
Ejagham (57.02, 77.22 and 74.40) Lake and lowest at
Ikot Okpora (41.21, 49.52 and 60.9) respectively (Table
6). In all the lakes Trophic Index value based on total
phosphorus; TSI (TP) is higher (60.9, 63.12, 74.4) than
the values by Chlorophyll-a; TSI (Chl-a) (41.21, 52.43,
56.01) and Secchi disk; TSI (SD) (49.52, 51.11 77.22)
4. Discussion
4.1. Physico-Chemistry
Essential primary productivity nutrients, nitrates, sul-
phates and phosphates were highest in Ejagham Lake,
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes 311
Table 4. Zooplankton of Ikot Okpora, Obubra and Ejagham Lakes during wet (W) and dry (D) seasons.
Species W D W D W D
Alona rectangula 59 185 23 40 7 23
Ceriodaphnia cornuta 34 149 87 83 12 13
Chydorus sphaericus 29 254 74 88 3 28
Diaphanosoma excisu m 40 176 2 94 23 13
Simocephalus 0 113 15 56 24 89
Moina micrura 65 198 24 33 12 44
Bosmina longirostris 69 123 30 11 0 0
Macrothrix spinosa 65 12 56 0 122 67
Copepoda 34
Ectocyclops phaleratus 92 178 34 56 41
Mesocyclop notius 85 177 33 57 0 48
Merocyclop 118 184 19 56 0 10
Metacyclops minutus 11 0 8 12 23 45
Microcyclops 85 13 23 34 57 78
Decapoda 84
Lucifer hansenii 45 87 76 124 176
Bipinnaria larva 18 34 34 76 32 45
Mysid larvae 23 45 34 56 45 121
Diphanosoma excisum 43 87 12 111 98 101
Rotifera 12 56 23 54 34 333
Keratella tropica 22 44 12 84 23 176
Keratella quadrata 0 0 7 56 23 66
Epiphanes macronna 59 123 43 58 13 83
Trycocerca similis 62 165 28 42 22 18
Synchaeta longipes 112 98 29 66 2 6
Conochilus dossuarius 122 101 34 55 3 8
Trichocerca pusilla 10 12 8 34 23 98
Branchionus anguillar is 23 34 23 56 98 178
Filinia longiseta 9 45 39 65 67 234
surrounded by the savanna vegetation and lowest in Ikot
Okpora Lake; the forest portion of the floodplain. Forest
ecosystem readily immobilise these nutrients [35], which
explains its limiting inputs into the water body in the
forest area. The levels of nutrients are fundamental to the
eutrophic nature of the lakes. Evidence for high produc-
tion is also seen in the lakes oxygen profile which went
down low (2.3 mg/L) at the Ejagham Lake, a condition
which contributes to the increase of lake phosphorus
through the release of phosphorus by deoxidized iron in
the sediments. The concentrations of calcium and mag-
nesium salts combined with various anions (usually car-
bonates) that constitute the total hardness of water were
high in Ejagham Lake indicating hard water lake. The
lower values of these parameters in Ikot Okpora lake and
Obubra showed the soft water nature of these lakes. Lake
water was clearer at Ikot Okpora than other lakes due to
lower values of turbidity at this forest lake.
4.2. Phytoplankton
Although Bacillariophyta and Chlorophyta were domi-
nant in respect to species number, Cyanophyta type
phytoplankton were more in terms of population density
in Ejagham Lake. Oscilatoria lacustria Microcystis spe-
cies, Spirulina substilissinna, Raphidiopsis species were
dominant and sub-dominant organisms in certain seasons.
Cyanophyta dominance, and sometimes bloom formation
are among the most visible symptoms of accelerated
euthrophication of lakes and reservoirs [36-38]. Also the
permanent dominance of Oscillatoria species during dry
and wet seasons has often been reported for eutrophic
lakes in Central Europe [39]. The observed dominant
species, Cyclotella operculata (Bacillariophyta) by
Nwankwo [40] and Microcystis by Silva [18] in both wet
and dry season was reported to be as a result of physio-
logical and behavioural flexibility of these species which
can accommodate environmental stresses better than
most fast growing species.
4.3. Zooplankton
Numerous species of rotifers and crustaceans considered
good indicators of the trophic state of lakes were found
in the zooplankton community. Rotifers recorded fre-
quently in the Ikot Okpora Lake, Synchaeta longipes and
Conochilus dossuarius are typical of oligotrophic to
mesotrophic systems [41]. However, the regularly most
dominant species in the Ejagham Lake like Keratella
tropica, Keratella quadrata, Filinia longiseta, Bran
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes
chionus anguillaris and Trichocerca pusilla are consid-
ered indicators of advanced lake trophy [10]. The crus-
tacean zooplankton community was made up of clado-
cerans and copepods. Copepod abundance in Ikot Ok-
pora and Obubra lakes was driven by the increase of Ec-
tocyclops, Mesocyclops, merocyclops, Microcyclops
which are indicative of higher water quality signifying
oligotrophic status. Crustacean abundance increases only
between mesotrophic and meso-eutrophic [42]. Also
dominant cladocerans, Alona rectangular, Ceriodaphnia
cornuta, Chydorus sphaericus, Diaphanosoma excisum,
Simocephalus sp., Moina micrura and Bosmina longi-
rostris represented in most samples in the Ikot Okpora
Lake are well recorded by Sendacz et al. [43] and Swier-
zowski et al. [44] in oligotrophic and mesooligotrophic
systems. Generally increase in the abundance of zoo-
plankton in the Ejagham Lake further confirms the eu-
trophic status of the lake since zooplankton abundance
increases with increasing nutrient concentration [14] and
decreases with decreasing nutrient concentration.
Table 5. Seasonal variation of zooplankton diversity indices in Ikot Okpora, Obubra and Ejagham Lakes.
Lakes Zooplankton Seasons Dominance Evenness Margelef Shannon
Wet Season 0.44 ± 0.07 a 0.56 ± 0.12a 3.56 ± 0.17a 0.55 ± 0.05a
Cladocera Dry Season 0.29 ± 0.11b 0.96 ± 0.16b 4.87 ± 0.21a 0.73 ± 0.19b
Wet Season 0.63 ± 0.09a 0.51 ± 0.07a 2.11 ± 0.15a 0.47 ± 0.18a
Copepoda Dry Season 0.32 ± 0.22b 0.87 ± 0.10b 2.99 ± 0.03a 0.88 ± 0.14b
Wet Season 0.58 ± 0.06a 0.44 ± 0.26a 1.68 ± 0.22a 0.23 ± 0.18a
Decapoda Dry Season 0.20 ± 0.15b 0.79 ± 0.15b 1.94 ± 0.18a 0.44 ± 0.11b
Wet Season 0.76 ± 0.23a 0.25 ± 0.08a 1.66 ± 0.11a 0.36 ± 0.26a
Ikot Okpora
Rotifera Dry Season 0.51 ± 0.22b 0.55 ± 0.01b 1.23 ± 0.20a 0.69 ± 0.18b
Wet Season 0.75 ± 0.19a 0.25 ± 0.11a 4.81 ± 0.34a 0.45 ±0.08a
Dry Season 0.46 ± 0.12b 0.50 ± 0.02b 4.33 ± 0.16a 0.86 ± 0.43b
Wet Season 0.955 ± 0.18a 0.11 ± 0.11a 3.22 ± 0.16a 0.42 ± 0.22a
Copepoda Dry Season 0.57 ± 0.19b 0.43 ± 0.05b 3.89 ± 0.20a 0.87 ± 0.43b
Wet Season 0.64 ± 0.10a 0.41 ± 0.19a 2.20 ± 0.14a 0.46 ± 0.17a
Decapoda Dry Season 0.35 ± 0.08b 0.88 ± 0.16b 2.88 ± 0.10a 0.75 ± 0.21b
Wet Season 0.75 ± 0.12a 0.64 ± 0.13a 1.58 ± 0.28a 0.48 ± 0.11a
Rotifera Dry Season 0.39 ± 0.11b 0.30 ± 0.22b 1.68 ± 0.18a 0.88 ± 0.27b
Wet Season 0.86 ± 0.22a 0.24 ± 0.12a 5.34 ± 0.21a 0.87 ± 0.13a
Cladocera Dry Season 0.47 ± 0.13b 0.55 ± 0.11b 4.99 ± 0.31a 0.48 ± 0.11b
Wet Season 0.86 ± 0.10a 0.242 ± 0.15a 4.34 ± 0.24a 0.59 ± 0.22a
Copepoda Dry Season 0.45 ± 0.25b 0.64 ± 0.14b 4.33 ± 0.3a 0.97 ± 0.33b
Wet Season 0.75 ± 0.15a 0.22 ± 0.19a 3.12 ± 0.22a 0.46 ± 0.13a
Decapoda Dry Season 0.32 ± 0.12b 0.52 ± 0.08b 3.55 ± 0.12a 0.86 ± 0.32b
Wet Season 0.82 ± 0.18a 0.20 ± 0.18a 1.88 ± 0.32a 0.52 ± 0.21a
Rotifera Dry Season 0.54 ± 0.21b 0.50 ± 0.16b 2.44 ± 0.21a 0.97 ± 0.17b
Table 6. Trophic state index due to chlorophyl-a, se cchi disk and total phosphorus.
Mean Values Trophic Points Classification
Lakes Parameter W D W D W D
Chlorophyll-a (µg/L) 1.77 2.54 31.11 41.21 Oligotrophy Mesotrophy
Secchi Disk (m) 2.16 1.17 34.23 45.52 Mesotrophy Mesotrophy
Ikot Okpora
Total Phosphorus (µg/L) 0.05 0.18 51.25 60.9 Eutrophy Eutrophy
Chlorophyll-a (µg/L) 2.24 2.89 42.31 52.43 Mesotrophy Eutrophy
Secchi Disk (m) 2.85 1.78 42.27 51.11 Mesotrophy Eutrophy
Total Phosphorus (µg/L) 0.05 0.06 57.34 63.12 Eutrophy Eutrophy
Chlorophyll-a (µg/L) 3.42 4.08 50.78 57.02 Eutrophy Eutrophy
Secchi Disk (m) 1.34 0.95 54.3 77.22 Hypereutrophy Eutrophy
Total Phosphorus (µg/L) 0.09 0.11 70.21 74.4 Hypereutrophy Hypereutrophy
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes 313
4.4. Diversity
Species diversity measured by Shannon Weaner index is
directly proportional to the number of species in the
sample and the uniformity of the species distribution in
the total abundance [45]. In the three lakes species diver-
sity was relatively high, which indicates good environ-
mental conditions conducive to the development of many
species, and according to Kajak [46] - moderate trophy
of waters. It was only in wet season samples that values
were much lower which was reflected by the lowest re-
corded number of species in the zooplankton community
[47] as well as by the domination of single species, ac-
companied by low proportions of other taxa. This indi-
cated poor lake conditions. This hypothesis that decrease
in lake condition followed by community structure sim-
plification was also confirmed by Rogozin [48].
4.5. Trophic State Index (Tsi)
Chlorophyll-a is used by all phytoplankton to capture
sunlight for photosynthesis. Chlorophyll (Chl-a) concen-
tration is a uniquely algal trait of the water column and
function as a reliable measure of phytoplankton biomass
[49]. Secchi depth is generally a good indicator of chlo-
rophyll-a concentration and reported to be negatively
related to chlorophyll-a concentration [50]. In Ejagham
Lake, when minimum Secchi depth was observed, the
highest chlorophyll-a value was recorded. However sec-
chi disk visibility may not always be acceptable as an
index of high productivity as some regions are affected
by non-algal turbidity. In Ejagham and Obubra lakes,
TSI (Chl-a) was found to be 70.02 and 52.43 respectively
while TSI (SD) was 57.22 and 51.11 respectively and
TSI value greater than 50 is usually associated with eu-
tophy or high productivity [5]. For lakes that have a few
rooted aquatic plants and little non-algal turbidity, the
TSI (SD) and TSI (Chl-a) are approximately the same [6]
as was observed in the Ikot Okpora and Obubra Lakes.
Therefore, TSI (SD) is only useful to those lakes where
turbidity is as a result of algal biomass [51]. In this study
non algal turbidity was observed in Ejagham lake where
the TSI (SD) was highest. Many factors are known to
influence Secchi depth. The most important factors in-
clude primary production, the amount of resuspended
material and the amount of coloured matter in the lake.
Secchi depth do not depend solely on autochthonous lake
production but also very much on allochthonous influ-
ences and resuspension [5]. So it is not correct to classify
Ejagham lake as hypereutrophic on basis of secchi depth
measurements. Same difference between TSI (SD) and
TSI (Chl) values has been found for Sri Lankan reser-
voirs [52] and TSI (Chl) has been found to be a reliable
means for quantifying trophic state at least for fisheries
management purposes. Lake Ejagham can be character-
ized as eutrophic during both seasons on the basis of
Chlorophyll-a concentration while Obubra Lake is eu-
trophic and mesotrophic during dry and wet seasons re-
spectively. The Ikot Okpora Lake, however, show
mesotrophic and oligotrophic characteristics in dry and
wet seasons respectively. Oligotrophic lake generally
host very little or no vegetation and is relatively clear
while eutrophic lakes tend to host large quantities of or-
ganisms, including algal bloom. Each trophic class sup-
ports different types of fish and other organisms. If the
algal biomass in a lake reaches very high level (> 80)
fish kills occur as decomposing biomass deoxygenate the
water. A lake situated in nutrient rich area may be natu-
rally eutrophic. Nutrients carried into water bodies from
non-point sources such as agricultural run-offs, residen-
tial fertilizers and sewage, will all increase biomass and
can cause oligotrophic lake to become hypereutrophic.
The three lakes are at different stages of development
and are influenced by season and location. Lake located
at the savannah area of the floodplain eutrophies faster
than lake at the forest section due to higher intensity of
direct sunlight penetration and temperatures which in-
creases photosynthesis and biodegradation respectively,
in the former. The forest helps limit eutrophication due
to the absence of anthropogenic inputs. The dry season
trophic state of the tropical lakes seems to be more ad-
vanced because of the dilution factor by rain water. Lake
Ikot Okpora may be recommended for an unfiltered wa-
ter supply particularly during the wet season and is suit-
able for fisheries and recreation in all seasons. Obubra
Lake may be suitable for fisheries but dominated mostly
by tolerant species, Clariidae and Cichlidae families
during the wet season while Ejagham Lake maybe have
very few tolerant fish species and not suitable for recrea-
[1] S. Kroeger, E. Fensin, K. Lynch and M. V. Borgh,
“United State Water Programs that Use Algae as Bio-
logical Assessment Tool,” Technical Guidance Document:
EPA 007-841, 1999.
[2] D. F. Westlake, “The Functioning of the Freshwater
Ecosystem,” International Biological Programme, Cam-
bridge University Press, London, Vol. 122, 2003, pp.
[3] A. Payne, “Ecology of Tropical Lakes and Rivers,” John
Wiley and Sons, New York, 1986.
[4] G. M. Sechi and A. Sulis, “Multi-Reservoir System Op-
timization Using Chlorophyll-A Trophic Indexes,” Water
Resources Managemnet, Vol. 21, No. 5, 2007, pp.
849-860. doi:10.1007/s11269-006-9114-3
[5] L. Håkanson and V. V. Boulion, “Regularities in Primary
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes
Production, Secchi Depth and Fish Yield and a New Sys-
tem to Define Trophic and Humic State Indices for Lake
Ecosystems,” International Review Hydrobiology, Vol.
86, 2001, pp. 23-62.
[6] R. E. Carlson and J. Simpson, “A Coordinator’s Guide to
Volunteer Lake Monitoring Methods,” North American
Lake Management Society, Madison, 1996.
[7] L. Sifa and X. Senlin, “Culture and Capture of Fish in
Chinese Reservoirs,” IDRC, Ottawa, 1995.
[8] D. G. Frey, “Wisconsin: Birge-Juday Era,” In: D. G. Frey
Ed., Limnology in North America, The University of
Wisconsin Press, Madison, 1963.
[9] S. D. Peckham, J. W. Chipman, T. M. Lillesand and S. I.
Dodson, “Alternate Stable States and the Shape of the
Lake Trophic Distribution,” Hydrobiologia, Vol. 571, No.
1, 2006, pp. 401-407. doi:10.1007/s10750-006-0221-1
[10] I. C. Duggan, J. D. Green and R. J. Shiel, “Distribution of
Rotifers in North Island, New Zealand, and Their Poten-
tial Use as Bioindicators of Lake Trophic State,” Hydro-
biologia, Vol. 446-447, No. 1, 2003, pp. 155-157.
[11] S. Guess, D. Albrecht, H. J. Krambeck, D. C. Muel-
ler-Navarra and H. Mumm, “Impact of Weather on Lake
Ecosystem, Assessed by Cyclo-Stationary MCCA of
Long-Term Observations,” Ecology, Vol. 81, No. 6, 2003,
pp. 1720-1730.
[12] K. O. Coyle and A. I. Pinchuk, “Climate-Related Differ-
ences in Zooplankton Density and Growth on the Inner
Shelf of the South-Eastern Bering Sea,” Progress in
Oceanography, Vol. 55, No. 1-2, 2002, pp. 177-179.
[13] A. Hobaek, M. Manca and T. Anderson, “Factors Influ-
encing Species Richness Lacustrine Zooplankton,” Acta
Oecologica, Vol. 23, No. 3, 2002, pp. 155-165.
[14] G. Balvay, “Evolution du Zooplacton du Leman,” Cam-
pagne 1999, Rapp. Comm. int. prot. Eaux. Leman conte
pollut (CIPEL), 2000.
[15] M. G. Nogueira, “Phytoplankton Composition, Domi-
nance and Abundance as Indicators of Environmental
Compartmentalization in Jurumirim Reservoir (Parana-
panema River),” Hydrobiologia, São Paulo, Vol. 431, No.
2-3, 2000, pp. 115-128.
[16] C. C. Figueredo and A. Giani, “Seasonal Variation in the
Diversity and Species Richness of Phytoplankton in a
Tropical Eutrophic Reservoir,” Hydrobiologia, Vol. 445,
No. 3, 2001, pp. 165-174. doi:10.1023/A:1017513731393
[17] C. S. Pedrozo and O. Rocha, “Zooplankton and Water
Quality of Lakes of the Northern Coast of Rio Grande Do
Sul State, Brazil,” Acta Limnologica Brasiliensia, Vol. 17,
No. 4, 2005, pp. 445-459.
[18] E. I. L. Silva, “Ecology of Phytoplankton in Tropical
Waters: Introduction to the Topic and Ecosystem
Changes from Sri Lanka,” Asian Journal of Water Envi-
ronmental Pollution, Vol. 4, No. 1, 2005, pp. 25-35.
[19] D. Zorka, V. Mitrovic-Tutundzic, Z. Markovic and I.
Zivic, “Monitoring Water Quality Using Zooplankton
Organisms as Bioindicators at the Dubica Fish Farm,
Serbia,” Archives of Biological Sciences, Vol. 58, No. 4,
2006, pp. 245-248. doi:10.2298/ABS0604245D
[20] B. O. Offem and E. O. Ayotunde, “Toxicity of Lead to
Freshwater Invertebrates. Waterfleas; Daphnia magna and
Cyclop sp) in Fish Ponds in a Tropical Floodplain,” Water
Air Soil Pollution, Vol. 192, No. 1-4, 2008, pp. 39-46.
[21] B. O. Offem, Y. Akegbejo-Samsons, I. T. Omoniyi and G.
U. Ikpi, “Dynamics of the Limnological Features and
Diversity of Zooplankton Populations of the Cross River
System SE Nigeria,” Knowledge and Management of
Aquatic Ecosystems, Vol. 393, No. 2, 2009, pp. 2-19.
[22] U. I. Enin, “The Artisanal Shrimp Fishery of the Outer
Cross River Estuary, Nigeria,” Ph. D. Thesis, University
of Calabar, Calabar, 1994.
[23] H. I. Golterman, “Methods for Chemical Analysis of
Freshwater,” International Biological Programme, Hand-
book & Oxford, Blackwell Scientific Publications, Ox-
ford, 1969.
[24] American Public Health Association (APHA), “Standard
Methods for the Examination of Water and Waste Wa-
ter,” 20th Edition, Washington DC, 1998.
[25] G. W. Prescott, “Algae of the Western Great Lakes
Area,” Brown Publishers, Dubuque, 1951.
[26] W. T. Edmondson, “Fresh Water Biology,” 2nd Edition,
John Wiley & Sons Inc., New York, 1959.
[27] D. M. John, B. A. Whitton and A. J. Brook, “The Fresh-
water Algal Flora of the British Isles: An Identification
Guide to Freshwater and Terrestrial Algae,” 1st Edition,
Cambridge University Press, Cambridge, 2002.
[28] R. A. Vollenweider, “A Manual on Methods for Measur-
ing Primary Production in Aquatic Environments,” 2nd
Edition, Blackwell Scientific Publications, Oxford, 1974.
[29] C. E. Boyd, “Water Quality in Warm Water Fish Ponds,”
Auburn University Publishers, Auburn, 1981.
[30] M. O. Kadiri, “Seasonal Changes in the Phytoplankton
Biomass of Shallow Tropical Reservoir, Nigeria,” Jour-
nal of Botany, Vol. 6, 1988, pp. 167-173.
[31] E. C. Kemdirim, “Checklist of Phytoplankton of Shedam
Reservoir in Plateau State, Nigeria,” Journal of Aquatic
Sciences, Vol. 16, 2001, pp. 61-66.
[32] E. R. Akpan and J. O. Offem, “Seasonal Variation in the
Water Quality of Cross River, Nigeria,” Hydrobiologia,
Vol. 26, No. 2, 1993, pp. 95-98.
[33] A. E. Magurran, “Ecological Diversity and Its Measure-
ment,” Cambridge University Press, Cambridge, 1988.
[34] J. H. Zar, “Biostatistical Analysis,” Pretice-Hall Interna-
tional, London, 1984.
[35] J. A. Downing and E. Mccauley, “The Nitrogen: Phos-
phorus Relationship in Lakes,” Limnology Oceangraphy,
Vol. 37, 1992. pp. 936-977.
Copyright © 2011 SciRes. JEP
Plankton-Based Assessment of the Trophic State of Three Tropical Lakes
Copyright © 2011 SciRes. JEP
[36] B. Moss, J. Madgwick and G. Phillips, “A Guide to the
Restoration of Nutrients-Enrich Shallow Lakes,” W. W.
Hawes, Suffolk, 1997.
[37] J. Padisak and C. S. Reynolds, “Selection of Phytoplank-
ton Associations in Lake Balaton, Hungary in Response
to Eutrophication and Restoration Measures, with Special
Reference to the Cyanoprokaryotes,” Hydrobiologia, Vol.
384, 1998, pp. 41-53. doi:10.1023/A:1003255529403
[38] M. P. Stoyneva, “Steady-State Phytoplankton Assem-
blage in Shallow Bulgarian Wetlands,” Hydrobiologia,
Vol. 502, No. 1-3, 2003, pp. 169-177.
[39] C. Berger and H. E. Sweers, “Ijsselmeer and Its Phyto-
plankton with Special Attention to the Suitability of the
Lake as a Habitat for Oscillatoria Agardhii Gom,” Jour-
nal of Plankton Research, Vol. 10, No. 4, 1988, pp.
579-586. doi:10.1093/plankt/10.4.579
[40] D. I. Nwankwo, K. Onyema and T. A. Adesah, “A Sur-
vey of Harmful Algae in Coastal Waters of South West-
ern Nigeria,” Journal of Nigerian Environmental Society,
Vol. 1, No. 2, 2003, pp. 241-246.
[41] J. Hall, J. B. Catharine and W. Carolyn, “Environmental
Gradient and Zooplankton Distribution, in a Shallow,
Tidal Lake,” Archives of Hydrobiologia, Vol. 154, No. 3,
2002, pp. 485-490.
[42] A. Karabin, “Pelagic Zooplankton (Rotatoria and Crusta-
cea) Variation in the Process of Lake Eutrophication. II.
Modifying Effect of Biotic Agents,” Polish Journal of
Ecology, Vol. 33, No. 4, 1985b, pp. 567-589.
[43] S. Sendacz, E. Kubo and M. A. Cestarolli, “Limnologia
de Reservatios do Estado do Sao Paulo, Brasil, VIII Zoo-
plankton,” Boletim do Instituto de Saúde, Vol. 12, 1985,
pp. 145-176
[44] A. Swierzoski, M. Godlewska and T. Poltorak, “The Re-
lationship between the Spatial Distribution of Fish, Zoo-
plankton and Other Environmental Parameters in the
Solina Reservoir, Poland,” Aquatic Living Resources, Vol.
13, 2000, pp. 373-387.
[45] C. J. Krebs, “Ecology: The Experimental Analysis of
Distribution and Abundance,” Harper Intel, Lectual Edi-
tion, New York, 1996.
[46] Z. Kajak, “Ecological Characteristics of Lakes in
North-Eastern Poland versus Their Trophic Gradient,”
Polish Journal of Ecology, Vol. 31, 1983, pp. 495-510.
[47] K. Irvine, M. T. Bales, B. Moss, J. H. Stanfield and D.
Snook, “Trophic Relations in Hickling Broad—A Shal-
low and Brackish Eutrophic Lake,” Verhandlungen des
Internationalen Verein Limnologie, Vol. 24, 1990, pp.
[48] A. G. Rogozin, “Specific Structural Features of Zoo-
plankton in Lakes Differing in Trophic Status: Species
Population,” Ekologia, Moscow, Vol. 6, 2000, pp.
[49] M. J. Behrenfeld and E. Boss, “Beam Attenuation and
Chlorophyll Concentration as Alternative Optical Indices
of Phytoplankton Biomass,” Journal of Marine Research,
Vol. 64, 2006, pp. 431-451.
[50] G. Almazan and C. E. Boyd, “An Evaluation of Secchi
Disk Visibility for Estimating Plankton Density in Fish
Ponds,” Hydrobiologia, Vol. 61, No. 3, 1978, pp. 601-
608. doi:10.1007/BF00044446
[51] U. A. D. Jayasinghe, U. S. Amarasinghe and S. S. De
Silva, “Trophic Classification of Non-Perennial Reser-
voirs Utilized for the Development of Culture-Based
Fisheries, Sri Lanka,” International Review of Hydro-
biology, Vol. 90, No. 2, 2005, pp. 209-222.
[52] F. Dominique, G. Hans, L. Malgorzata, C. Lawrence and
K. Andoline, “Integrated Water Resource Management
for Important Deep European Lakes and Their Catchment
Areas,” Eurolakes, Vol. 36, 2003, pp. 56-67.