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A Peer Reviewed International Journal of Asian
Academic Research Associates
AARJMD
ASIAN ACADEMIC RESEARCH
JOURNAL OF MULTIDISCIPLINARY
LIMNOLOGICAL STUDIES AND ALGAL DIVERSITY, A USEFUL TOOL FOR
ASSESSMENT OF FISH POND WATER QUALITY.
NWEZE, N.O*;
MAHMOUD, L.B**;AISHA M. I.***
*Department of Plant science and Biotechnology,
University of Nigeria, Nsukka.
**Department of Plant science and Biotechnology,
University of Nigeria, Nsukka.
***Federal College of Education, Yola Nigeria.
Abstract
Algal species diversity and their relationship with physico-chemical parameters of a fish pond in
Yola, North-Eastern Nigeria were investigated from (July 2011 – April, 2012). Water samples
were collected, preserved and analyzed, using standard methods. The results showed that the
limnological parameters influenced the species distribution in the pond over time. Oscillatoria
and Anabaena species (Cyanobacteria) were observed in the pond water which was characterized
by low transparency, total dissolved solids (TDS) and poor dissolved Oxygen (DO). The
relationship between Cyanophyta / Desmidiales and chloroccales / Desmidiales was used as early
Phytoplankton indices to characterize the trophic status of aquatic ecosystem. Green algae
Mougeotia, Spirogyra, Chlorella specie and species of desmids Microasterias, Closterium and
Cosmarium were equally encountered in the pond. The results showed that both Chlorophycean
and Myxophycean indices were <1.
Keywords: water quality, bioindicators, desmid, Cyanobacteria.
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INTRODUCTION
Pond fishery is practiced in the north-eastern part of Nigeria on a large scale for
augmentation of fish product and hence makes an interesting biotope for physico-chemical and
biological studies. The anthropogenic inputs of complex mixtures from neighboring communities
and agricultural waste such as runoff of manures and fertilizers could lead to alteration of water
quality (Mustapha, 2006; Garg, et al., 2009). The primary concern of these anthropogenic
activities is its effects on the water quality and aquatic life. Water quality monitoring is of
immense importance in the use of water bodies for the management of fisheries (Mustapha,
2006, Nweze, 2009a).
Phytoplankton are of great ecological significance as primary producers in the aquatic
environment (Nweze, 2003; Barinova et al., 2008, Bellinger and Sigee, 2010). Human activities
such as, pond fertilization with fertilizers, obnoxious fishing practice; Fertilizer application,
pesticides and herbicides, used in agriculture and forestry are the commonest sources of human-
induced water pollution that bring about eutrophication, hypoxia, fish kill, disruption of food
web and changes in the community ecosystem (Mustapha, 2006; Garg et al., 2006b; Chia et al.,
2011).
In natural waters dissolved solids are composed mainly of carbonates, bicarbonates,
chlorides, sulphates, phosphates, nitrates, calcium, magnesium, sodium, potassium, lead and
manganese, (Esmail and Johal, 2005; Garg et al., 2006a). The change in physical and chemical
parameters, calcium, sulphide, dissolved oxygen, phosphate, zinc, and water temperature, with
time could be attributed to dilution effects of rainfall (Biswas, 1992; Kadiri, 1993). The extent to
which microalgal species can tolerate trace metals make them potential indicators for the
presence and levels of these metals. Trace elements act as micronutrients at low concentrations,
while at high concentration they become toxic. For example Chlorococcus sp. is sensitive to Zinc
and Copper (Chia et al., 2011).
The use of biotic component of an ecosystem to assess periodic changes is a valuable
assessment tool that is receiving increased attention in water quality monitoring programmes
(Kenish, 1992; Ramachandra and Solanki, 2007). The growth of phytoplankton, is dependent on
sunlight and nutrient concentrations. Their short life cycle and sensitivity to changes earn micro
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algae the potential for monitoring water quality of aquatic ecosystem (Kenish, 1992; De Lange,
1994; Ekpenyong and Adeniyi, 1996; Radojevic and Bashkin, 1999; Ramachandra and Solanki,
2007, Bellinger and Sigee, 2010). USEPA (2002) reported that algae can be used for
environmental monitoring against pollution.
Some algal species and taxonomic group show clear preference for particular conditions
and this can be potential bioindicators. In broad comparisons of oligotrophic versus eutrophic
waters, desmids (green algae) tend to occur mainly in low nutrient waters while colonial blue
green algae are more typical of eutrophic waters. Small newly forms ponds are often dominated
by rapidly growing Chlorococcales (green algae) and euglenoids. The later are particularly
prominent to high levels of soluble organics. Some of the most hypertrophic and ecologically
unstable waters are represented by artificially fertilized fish ponds Potapova and Charles (2005).
In addition to individual species taxonomic grouping (assemblage) may also be useful
environmental indicators. Reynolds (1980) considered species assemblage in relation to seasonal
changes and trophic status, with some groupings typical of oligotrophic (Cyclotella
comensis/Rhizosolenia) eutrophic (Anabaena/Aphanizomeno/Gloeotrichia) and hypertrophic
(Pediastrum/Coelastrum/Oocystis) states. The use of algae and other organisms for monitoring
organic pollution was originally pioneered by Kolkwitz and Marson (1908). Palmer (1969)
assessed the tolerance of algal species to organic pollution, and incorporates data into organic
pollution index for rating water quantity.
Thunmark (1945), Nygaard (1949) and Stockner (1974) used major taxonomic groups in
determining early phytoplankton indices of Oligotrophic (particularly desmids) or Eutrophic
(chlorococcales, blue green, euglenoids) condition. The proportions of eutrophic/oligotrophic
species generated a ratio that could be used to designate trophic status of a water body. Accordi
to Bellinger and Sigee (2010) Algae groups rather than individual species result to quantitative
analysis and determination of trophic levels.
The objective of the research is to identify various algal species that can be use as
bioindicators, for monitoring various aquatic ecosystems and determine the trophic level using
standard indices.
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MATERIALS AND METHODS
Gesedaddo Farms is located in Yola South Local Government Area, Adamawa State, Nigeria.
The farm is located in Sudan savannah. Data captured using an e trek trip Mgr V5 map source
model revealed that the farm is located on latitudes 9.2o and longitudes 12.3
oE. Pond points are
on 144 and 142 latitudes 9.2oN and longitudes12.3
oE on points 137 and 143.
The temperature, dissolve oxygen (DO), pH, and conductivity were determined on the spot,
using portable dissolved oxygen analyzer (Model JPB-607, a PHS-25 pH, temperature meter and
DDS-307 conductivity meter. Transparency was measured using Secchi disc.
The calcium, magnesium, sodium, potassium, was determined titrimetrically following
standards methods of APHA (1995), and Radojevic and Bashkin (1999). The nitrates, sulphates
and phosphates were equally determined using atomic absorption spectrophotometer (AAS) at
Centre of Excellence FCE Yola following standard method of APHA (1995), Radojevic and
Bashkin (1999).
Wet mounts was prepared from fresh samples and examined using a compound
microscope, Swift (SA) No78c4018 model under x10, x40 and x100 objective lenses supplied by
Philip Harris Shenstone England. Dichotomous keys were used for identification of algae
following the methods of Prescott (1962,), Belcher & Swale (1976), Bellinger and Sigee (2010)
and the internet Photomicrographs were taken using a digital camera (Samsung camera 12.2
mega pixels.5X optical zoom).
RESULTS AND DISCUSSION
The highest Temperature of 40oC encountered during April and lowered to 25
oC in
January (harmattan season) is a characteristic of seasonal variation of the northern parts of
Nigeria, as observed by Ekpenyong and Adeniyi (1996). Solar radiation was equally higher in
March (238.56 M/W/Cm2)
and lowest in August (162.95M/W/Cm2). Low relative humidity and
high wind speed were observed in the dry season. This climatic trend was equally observed by
(Nweze and Chumboh, 2006). The high weather factors coincide with the lowest dissolved
oxygen (DO), 4.0 mg/litre. These conditions favour the growth of phtoplankton that deplete
nutrients and dissolved oxygen and when this happens fish suffocate and as they are constrained
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in pond and cannot escape to a more oxygenated water. This can be a serious problem in
aquaculture (Chowdhury and Al Mamun , 2006).
Correlation among the physicochemical parameters during the period of investigation at
P=0.05 revealed that there is positive correlation between the water temperatures and nitrates
(NO3), calcium (Ca), iron (Fe), and bio oxygen demand (BOD) and Water temperatures
positively correlated with Sodium, (Na), Copper, (Cu) and total hardness and negatively
correlated with manganese (Mn), zinc,(Zn) and potassium,(K). Similarly Phosphates (PO4),
Sulphates (SO4) correlate positively with sodium (Na) and total hardness, and negatively with
magnese (Mn) and zinc (Zn). Whereas transparency, conductivity and TDS correlate positively
with Na, PO4, and total hardness.
Table 1: Comparing (Mean + S.E) of Algal count by Ponds.
Algae spp Pond 1 Pond 2 Pond 3
Chrococcus 42+9.87 22+6.11 23+10.33
Anabaena 15.5+4.74 16.5+3.3 46+9.91
Oscillatoria 45+9.57 29+6.74 27+5.38
Microcystis 1+1.00 0 17+10.33
Merismopedia 2+1.33 1.4+01.03 0
Spirulina 10+3.65 5.2+1.61 9+4.58
Dactylococopsis
fusicularia
0 0 1+1.0
Spirogyra 8+5.92 10+3.65 11+3.78
Mougeotia 44+21.76 12+3.59 12+3.26
Chlorella 107+19.61 29+6.40 48+9.40
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Cosmarium 48+10.93 31.60+7.73 18+5.92
Closterium 16+7.48 31+6.22 13+6.50
Desmo-desmus 8+6.11 3+1.52 6+2.66
Micrasterias 0 3+1.52 0
Scenedesmus 1+1.0 4+3.05 0
Oedogonium 32+8.53 15+3.72 21+6.57
Eudorina 3+3 27+8.17 2+1.33
Navicula 91+22.82 36+7.02 60+12.20
Nitzschia 21+9.48 17+6.15 23+9.19
Cyclotella 1+1.0 5+4.01 3+3.0
Ankistrodesmus 1.0+1.0 1.0+1.0 0
Gyrosigma 4+2.21 8+2.90 10+4.71
Synendra 13+6.15 10.5+4.50 13+5.97`
Correlation between physico-chemical parameters and algal species revealed a negative
relation between Closterium, Trahelomonas, and TDS, and positively with Zn. In Table 2,
Closterium correlated positively with Desmodesmus and Synedra species, Chrococcus, Navicula
species. and Oscillatoria species negatively correlated with Chlorella and Spirogyra species.
This finding also agreed with Turner et al (1991) that Mougeotia sp. forms substantial growth in
acid water and is widely regarded as an early indicator of environmental change. Chlorella sp.
has a pollution index of 3 and acts as a biocleanser (Palmer, 1969). Some factors that favour the
presence of desmids include pH value of 6.0-6.44 (Kadiri, 2007).
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The positive correlation between conductivity, transparency, DO, with phosphates (PO4),
nitrates (NO3), iron (Fe), copper (Cu), and total hardness and negatively with potassium (K),
manganese (Mn) may be linked to the climatic conditions, solubility, and agricultural activities
around the catchment areas which range from surface runoff of fertilizers and Pesticides. These
agreed with the findings of ( Chia et al., 2009a, 2010).These complex mixtures alter the water
quality (Mustapha 2006; Garg et al., 2009).The introduction of cow dungs, fertilizers during
manuring/fertigation of fish ponds to encourage algal growth to serve as producers and
subsequent fish feeding. This agrees with the findings of (Nweze 2003; Barinova et al., 2008;
and Bellinger and Sigee 2010) that phytoplankton are of ecological significance comprising the
major producers in the aquatic ecosystem.
The algal composition during the ten month study period belongs to four (4) divisions,
Cyanophyta: Blue green algae (BGA), Chlorophyta, Bacillariophyta and Euglenophyta.The
cyanophytes were Anabaena circinalis (Borge), Microcystis pseudo filamentosa, M aeroginosa
(Kuetz), Chrococcus (Naegeli), Merismopedia spp. and Oscillatoria annae (Vaucher).
Chlorophyta (green algae) were represented by Eudorina elegans (Ehr.), Chlorella vulgaris.
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(Beyerinck), Oedogonium capillare Him Tiffany, Spirogyra fluviatalis (Hilse) Mougeotia spp.
(Hassall) and Desmidiaceae, Closterium setaceum (Her & Ralf. C. calosporum Wittrock and
Closterium diane (Willie) Schroeder.
Correlation between algal species and physico-chemical parameters in the pond showed
that Micrasterias sp a desmid correlated positively with Zn and Closterium sp negatively with
TDS and Eudorina sp –vely with conductivity .This agreed with the findings of Chia et al
(2011) where Closterium sp and Rhizoclonium hookerii Kuetz were positively associated with
concentration of Fe and negatively correlated (sensitive) to TDS and Conductivity.
In this research, the mean total population of Chlorococcales was 37 individual per ml
comprising of (Ankistrodesmus (1), Chlorella (29), Scenedesmus perforata (4), Desmo desmo
(3). Desmidiaceae had a mean total of 95 made up of (Closterium sp. (31), Cosmarium sp. (31)
and Microasterias sp. (33).The Chlorophycean index is the ratio of Chlorococcales
/Desmidiaceae was 0.389 which was less than 1. This implies that the fish pond was
Oligotrophic. The result agreed with Chlorophycean index of USEPA (1976) and Bellinger and
Sigee (2010).
Myxophycean index, the mean total population of Cyanophyta was 83 individual per ml
comprising of (Chroococcus sp. (22), Anabaena sp. (16), Oscillatoria (29), Merismopedia sp.
(1), and Spirulina sp. (5). The ratio of Cyanophyta/Desmidiaceae was 0.873 which is less than 1.
This implied that the fish pond is Oligotrophic and the result agreed with Nygaard (1949).
Bellinger and Sigee (2010).
Conclusion
Analysis of water samples from three Ponds in Yola revealed the presence of a variety of
phytoplankton representing major division of Cyanophyta, Chlorophyta, Euglenophyta and
Bacillariophyta. Some of which are toxic species. Qualitative and quantitative study of algae is
important biomarkers for biomonitoring of an aquatic ecosystem. They provide early signals for
timely intervention for the control of water pollution and conservation of biodiversity. The
relationship between physico-chemical parameters and algal – algal relationship, Cyanophycean
and Myxophycean indices for the water body investigated indicated the pond being Oligotrophic,
and henced suggested their usage as biomarkers. Thus frequent monitoring of ponds will
minimize threats to the fish and other aquatic organisms.
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