Phytoplankton Abundance and Distribution of Fish Earthen Ponds in Lagos, Nigeria

: The study investigated phytoplankton abundance and distribution under different pond management to determine the effect of some physicochemical parameters on the community structure of three on-research fish earthen ponds of Nigerian Institute for Oceanography and Marine Research, Badore, Lagos. Samples were taken every week using standard procedure. Water quality parameters; temperature, dissolved oxygen, turbidity, salinity and pH were measured and found to be within the optimal ranges for phytoplankton productivity. Seventeen (17) phytoplankton species belonging to family Chlorophyceae, Bacillariophyceae, Cyanophyceae and Euglenophyceae were identified. Densities of the phytoplankton ranged from 01.85 x 10 3 cells L -3 to 25.90 x 10 3 cells L -3 in the ponds; Chlorophyceae being the most abundant. Mean cell densities of the phytoplankton were significantly different ( P <0.05). Few phytoplankton species were present in all the Ponds. The spatial distribution of Bacillariophyceae in ponds 1, 2 and 3 were 41.7%, 41.7% and 16.8%, while those of Euglenophyceae were 50%, 50% and 0% respectively. Shannon Wiener diversity index was 1.263 in Pond 1, 1.265 in pond 2 and 1.078 in Pond 3. Pond 1 had the highest phytoplankton percentage (94.11%). Correlation coefficients were calculated for abundance with pH, DO and temperature. Abundance was positively correlated with the temperature variations and levels of DO but negatively correlated with the pH. Results of phytoplankton abundance of the three ponds clearly showed the influences of the physicochemical factors on diversity, distribution and abundance of phytoplankton which indirectly affects aquaculture potentials.

The plankton community comprises of the phytoplankton and zooplankton. Phytoplankton is important organisms which act as producers of the primary food supply in any aquatic ecosystem (Battish, 1992). They are the initial biological components from which energy is transferred to higher organisms through the food chain (Tiwari and Chauhan, 2006, Babatunde, 2014and Saifullah, 2014. Phytoplankton significantly contributes to the dynamic and succession of zooplankton in aquatic ecosystems and without them the diversity and abundance of aquatic life would be impossible (Suzie, 2015). Dynamics and changes in phytoplankton biomass are the result of a complex interplay of physical, chemical and biological processes. The physicochemical and biological features largely control the plankton production and biology of the cultured organisms. Availability of nutrients also plays a key role in determining the phytoplankton population density (Grenz et al, 2002;Elliott et al, 2002). The term "Water quality" refers for the physical, chemical and biological parameters of water and directly or indirectly influences the survival and production of aquaculture species (Kohinoor, 2000). Environmental factors in aquatic habitats include various physical properties of water such as solubility of gases and solids, penetration of light, temperature, and density. Chemical factors such as salinity, pH, hardness, phosphates and nitrates are also very important for growth and density of phytoplankton on which zooplankton depend (Roy, 2014). Phytoplankton species are used as indicators of water quality because their sensitivity can be a dynamic response to changes in the surrounding environment (Siddika, 2012).
Qualitative and quantitative abundance of phytoplankton indicate the productive status of a water body (Chowdhury et al, 2008), thus a thorough knowledge of abundance of phytoplankton and its quality in time and space in relation to environmental conditions is a prerequisite for fish production. Several studies carried out in Lagos, Nigeria were concentrated on the taxonomic identification of different phytoplankton genera and were very confined to the specific regions of Lagos lagoon. There is dearth of information on the composition of phytoplankton in fish earthen ponds in Lagos, Nigeria. This study focuses on the Phytoplankton Abundance and Distribution of Fish….. CHUKWU, MN; AFOLABI, ES measurement of some physicochemical parameters such as temperature, transparency, dissolved oxygen and pH to checklist the phytoplankton abundance and distribution in fish earthen ponds in the Nigerian Institute for Oceanography and Marine Research, Badore, Lagos.

MATERIALS AND METHODS
Study Area: Three on-farm research fish ponds in the Nigeria Institute for Oceanography and Marine Research Badore, Lagos, were selected. The station is located off Ado -Badore road and lies between 719917.527mN 566343.226mE and 719187.784mN 566933.382mE off the coast of Lagos (Figure 1). The sampling ponds were 50 m apart and underground water was the main source of water for the ponds.
The ponds were free from any shading and had adequate sunlight throughout the day. The size of the ponds, their respective capacities and culture system were shown in Table 1.

Sampling techniques:
Physicochemical and biological water quality variables were measured from the sample ponds' water. Samples were taken from each pond once a week, between 09.00 a.m. and 10.00 a.m. in duplicate for a period of eight weeks; from September to October, 2016. The pH, salinity, dissolved oxygen, temperature and water transparency was measured in-situ. A mercury in glass thermometer was used to measure the temperature ( o C), while transparency (m) was measured with Secchi disc, 20 cm diameters (LaMotte-0171). Digital electronic meter (JPB-607A) was used to measure the dissolved oxygen (DO) (mgL -l ). The pH of samples was measured using hand held electronic probe (pH-98108) and salinity with RHW-25Brix (ATC).
Phytoplankton sampling and analysis: Samples for phytoplankton analysis were collected from four sampling points using a cone shaped, silk bolting cloth plankton net with a 50 ml concentrate bottles. The concentrates were transferred to separately labeled 100 ml glass jars and fixed immediately with 5% formalin, which served as a fixative. Fixed samples were allowed to settle in the Laboratory for 24 hours and the supernatant carefully discarded until concentration of 40 ml was obtained. Phytoplankton species were examined, identified and counted using Trinocular Olympus microscope quipped with digital scope photo (×9) and computer system window 2000. Drop count method as described by (Ramachandra and Malvikaa, 2007) was modified for the counting while identification of phytoplankton up to generic level was made according to (Apha, 1998).

Utilize Index and Statistical Analysis: Shannon
Wiener diversity index was used to determine the plankton species composition and their diversity across the different ponds sampled. Physicochemical parameters and phytoplankton parameters were analyzed using one-way ANOVA and Post-hoc comparisons using Duncan test (P>0.05) while Pearson's Correlation coefficient was used to determine the association between abundance and physicochemical parameters.

RESULTS AND DISCUSSION
Most physicochemical parameters of the sampled ponds fell within the standard range and thus were favorable for the growth of phytoplankton and fish culture. The only shift from this trend is in the turbidity and pH of the ponds' water which were variable (Table 2 and Fig.2). Pond 3 water with high transparency of 0.89m and slightly low pH (4.81 ± 0.51) would be harmful to the non-tolerant phytoplankton, hence low phytoplankton abundance in the pond.
There is no significant difference in the average water air temperature and dissolved oxygen (DO)   hytoplankton enumeration and relative abundance rankings: x =1-15 cells/ml -1 (sparsely abundant), xx =16-63 cells/ml -1 (fairly abundant) xxx = 64-255 cells/ml -1 (very abundant), a = species absent, not encountered in entire enumeration. Phytoplankton density was variable among the ponds investigated. The highest total density of phytoplankton was observed in pond 1. The lowest phytoplankton density in pond 3 was due to the treatment of ponds 1 and 2 with manure which influenced their pH and nutrient availability thus increasing the phytoplankton communities. Shannon -Weaver species diversity index was relatively high in ponds 2 and 1 and low in pond 3 (Table 3). This portrayed more species diversity in ponds 1 and 2 compared to pond 3; order of diversity being P2>P1>P3 (Table 4). There was a significant difference in the mean phytoplankton density of the three ponds (P < 0.05). Similar observations were made by (Elliott et al, 2002) in various pond habitats. The effect of the negative correlation between phytoplankton abundance and pH range in the ponds characterized with acidic water resulted in low phytoplankton density and diversification (Table 5). This is in agreement with the findings of (Asha, 2015) that water resources with strong acidic water may sustain only acidic species. The spatial distribution (%) varied for the family of Cyanophyceae (Fig  4a-c). The spatial distribution for Bacillariophyceae in ponds 1, 2 and 3 were 41.7%, 41.7% and 16.8% respectively while those for the Euglenophyceae were 50%, 50% and 0% in ponds 1, 2 and 3 respectively (Fig.4a-c). Pearson's correlation coefficients showed that water transparency is inversely proportional to the abundance of phytoplankton; hence an increase in plankton will reduce transparency of water and increase avail ample food availability to fishes for high productivity  Conclusion: It is evident that the occurrence and abundance of phytoplankton species in these ponds were closely related to their physicochemical characteristics. The physicochemical parameters influenced the distribution and abundance of the phytoplankton and zooplankton. In view of the quantity, quality and the phytoplankton abundance and distribution in the ponds; there is a need to employ a measure to improve the quality of the ponds' water for sustainability of the cultured fishes.