Greener Journal of Biological Sciences

Vol. 11(2), pp. 45-53, 2021

ISSN: 2276-7762

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Planktonic Fauna Distribution and Abundance in Relation to Physico-Chemical Properties of Pindiga Lake, Gombe, Nigeria.

¹Umar, D. M.; ²Abbati, M. A.

¹Department of Biological Sciences, Gombe State University, Gombe, Nigeria.

²Department of Biological Sciences, Federal University of Kashere, Gombe, Nigeria.

ARTICLE INFO	ABSTRACT
*Article No.:* 080721073 *Type: Research*	Planktonic Fauna Distribution and abundance in relation to Physico-chemical properties of Pindiga Lake, Gombe State were evaluated. Four sampling sites (A, B, C, and D) with distance of 500 meters apart were selected. Zooplankton samples were collected using plankton net of 55µm mesh size by hauling horizontally for five meters. The collected samples were preserved in 4% formalin and 3 drops of lugols iodine solution and transported to the Gombe State University, Biological Sciences laboratory for counting and identification. Physico-chemical properties were measured and planktonic fauna sampled fortnightly for a period of six months (March-August, 2019). Planktonic fauna collected were identified using taxonomic keys. Shannon Weiner diversity index was employed for estimation of abundance and distribution. Results of the physico-chemical characteristics showed the ranges of Air temperature, Water temperature, Water pH, Electrical Conductivity, Total Dissolved Solid, Turbidity, Dissolved Oxygen, Biochemical Oxygen Demand, Nitrate and Phosphate were 30.38-38.20C, 21.56-28.880C, 7.11-7.49, 264.5-321.25µS/cm, 132.25-160.75mg/L, 16.88-22.75mg/L, 3.6-5.74mg/L, 1.89-3.18mg/L, 8.79-10.98mg/L and 2.49-3.89 mg/L respectively. The planktonic fauna results revealed a total of 1542 individual species of zooplankton in 28 genera among the three zooplankton taxa of Cladocera, Copepoda and Rotifera. The genera abundance of Pindiga Lake arranged in dwindling trend as Copepoda>Rotifera> Cladocera, with respective total zooplankton values of 44.94%, 32.23%, and 22.82%. Copepod, Cladocera and Rotifera were negatively interrelated to Air temperature, Water temperature, Electrical conductivity, Total dissolved solid, nitrate and phosphate while positively concurrent to Dissolved Oxygen and Biochemical Oxygen Demand. Outcome of the investigation point out that physicochemical properties were within the range value recommended for most tropical water bodies and profusion of zooplankton is exceedingly elating compare to other water bodies. Subsequently, the lake is suitable to sustain the proliferation, continued existence and development of aquatic organisms predominantly fish. The research showed that there is abundance of zooplankton, which will serve as a food to fish, hence there is need to stock a fish into the water body in order to maintain the stability of the ecosystem.
*Accepted:* 07/08/2021 *Published:* 31/08/2021
Corresponding Author Abbati* MA *E-mail:* danladiumar97@ gmail.com
*Keywords: Planktonic fauna; physicochemical properties; Pindiga Lake.*

INTRODUCTION

Water is the most crucial assets and general solvent that all living creatures depend on for their existence, growth and reproduction (Samuel, et al., 2015). Without water living organisms are expected not to survived, growth and reproduced since it’s the portion of life. Good water quality is requisite in conserving the composition of aquatic flora and fauna, deterioration of the water quality can cause turn down in productivity and biodiversity of aquatic biota (Faithful and Finlayson, 2005). The quality of water is ascertained by its physical and chemical properties. Due to intensifying population growth and anthropogenic processes, water quality is dwindling each day (Alrumman et al., 2016). Decline of lentic water quality has been linked to both biogenic and anthropogenic activities, including volcanic eruptions, earthquake, climate change, precipitation, agricultural land use and sewage discharge.

Water necessities in all living organisms are intensifying day after day, but the source of water for drinking is a decisive issue, as all water supplies have got to the point of predicament due to urbanization and industrial revolution (Bibbi et al., 2016). Pollution of water occurred when there is alteration in the physical, chemical or biological condition in the ecosystem which disastrously affects the treasure of human life together with other fauna and flora (Ojitiku et al., 2018). The density and diversity of the planktons are greatly influenced by the different physicochemical parameters of water (Krishna et al., 2014). Zooplanktons are minute drifting and suspended organisms floating at the surface of the water body, which are essential components of water food web, as they have a say to the productivity of freshwater ecosystems. They are also very prone to changing ecosystem; therefore, they compose perfect indicator organisms. Zooplanktons are the important aquatic organisms occurring profusely in all sorts of aquatic habitats, and they play a crucial role in energy transfer of aquatic ecosystem (Siddique and Kale, 2018). The aimed of the research is to investigate the zooplankton as a fish feed and physicochemical properties as a condition for fish growth, survival and reproduction in Pindiga lake.

MATERIALS AND METHODS

3.1 Study Area

Pindiga Lake is an artificial and perennial small water body that receives its water directly from rain. It’s located in the eastern part of Pindiga about 1km to Pindiga Village in Akko Local Government Area of Gombe State. The lake lies between latitude 10.13°15N and longitude 11.11°19E (Fig. 1). It has the surface area of 513m by 502m. The activities carried out around the water body include washing, bathing, livestock consumption and car washing.

Sampling Stations

Zooplankton abundance and distribution of Pindiga Lake, Gombe State were evaluated. Four sampling stations (A, B, C, and D) with distance of 500 meters apart were selected and replicated samples were collected at each point throughout the study period. Water samples were collected from four different locations on the lake and mean values of the four stations were worked out and recorded. The sampling was conducted fortnightly between March to August, 2019. Sampling was done between 8.00am and 10.00am.

Physicochemical Properties

Temperature (°C) of the air was determined in situ by exposing a bulb mercury in glass thermometer in the air at each sampling station for about 1-2 minutes and the readings were recorded in degree Celsius (APHA, 2005). Water temperature was determined in situ by dipping mercury in glass thermometer into the water at each station for about 1-2 minutes and readings were recorded (APHA, 2005). pH was measured using Hanna pH meter (Model H199107), the tip of the pH meter was immersed into the 100ml beaker containing water sample for 2-3 minutes and readings were recorded (APHA, 2005). Electrical conductivity was measured with Hanna conductivity meter (Model EC 215), the Water samples was drawn in a wide mouthed beaker and the tip of the conductivity meter was dipped into a beaker for a period of 2-3 minute to permit constant reading (APHA, 2005).Total Dissolved Solid was determined with Hanna TDS meter microprocessor (Model H215), the water samples were drawn in a 100ml beaker and the tip of the TDS meter was dipped into a beaker for a period of 2-3 minute to permit constant reading (APHA, 2005).Turbidity was measured with black-white secchi disc. Turbidity was measured by gradually lowering the Secchi disc at respective sampling points. The depth at which it disappears in the water (X1) and reappears (X2) was noted and estimated as the average of points of disappearance and reappearance (APHA, 2005). Hanna Dissolved Oxygen microprocessor (Model HI 98186) was used to measure the dissolved oxygen. Sample of the water was collected in 100ml beaker; the electrode of dissolved oxygen microprocessor was dipped into the beaker that contains the sample water for about 2-3 minutes. The reading was recorded in mg/l (APHA, 2005). Hanna Dissolved Oxygen microprocessor (Model HI 98186) was used to determine the biochemical oxygen demand, 100ml part of the sample collected was incubated for five days in dark cupboard at room temperature and dissolved oxygen was determined after five days of incubation, the difference between the initial value of dissolved oxygen and the value after five days of incubation was used as value of biochemical oxygen demand in the water sample (APHA, 2005. The Palintest multiparameter (Model 7100) colorimeter was used to determine the nitrate using the nitra ver. 5 nitrate reactivo reagent. The reagent was added to the sample collected in a 20ml colorimeter vial and placed in a colorimeter compartment and then closed with the colorimeter cover and allowed for a period of time sufficient to permit constant reading. The value obtained was recorded in mgl^-1(APHA, 2005). The Palintest multiparameter (Model 7100) colorimeter was used to determine the phosphate using the Armstrong reagent. The reagent was added to the sample collected in a 20ml colorimeter vial and placed in a colorimeter compartment and then closed with the colorimeter cover and allowed for a period of time sufficient to permit constant reading. The value obtained was recorded in mgl^-1(APHA, 2005).

Zooplankton sampling, counting and Identification

Zooplankton samples were collected using plankton net of 55µm mesh size by hauling horizontally for five meters. The collected samples were preserved in 4% formalin and 3 drops of lugols iodine solution and transported to the Gombe State University, Biological Sciences laboratory for counting and identification (Saidu et al., 2016 and Isah et al., 2018).

The resultant concentrated zooplankton sample was transferred into plastic container and preserved with 4% formalin and 3 drop of lugol’s iodine solution according to the method used by Isah et al., (2018). The samples were labelled with the date, time of sampling, study area-lake name, sampling site name and the volume measured and pasted on the containers (Umar, 2014). All collected samples were transported in a cool box containing ice to the laboratory for analysis. In the laboratory the 20ml out of 100ml in each sample collected was filtered using the Whitman’s filter paper and the 1ml of the resultant concentrate was collected for identification and counting. 1ml of filtered sample was spread on to a slide and counted the individual present in number per ml. Zooplankton counts were made by shaking each sample to share out organisms uniformly and one drop was put on top of a clean glass slide by the use of pipette. This was then watchfully covered with a cover slip and brought under Olympus binocular microscope at 400× and 1000× magnification for further taxonomic analysis. The zooplankton was identified using applicable standard zooplankton keys like Graham (2007), Witty (2004), Petersen, (2018) and Phan et al., (2015). The Zooplankton distribution and abundance were analyzed and presented using Excel Microsoft and Minitab software. Shannon Weiner diversity index was employed to estimate the monthly abundance of zooplankton.

Data Analysis

One-way Analysis of variance was used to test the significant differences in mean of physico-chemical properties among months and Fisher Least Significance Difference (FLSD) was used to separate the means of significant differences where exist. Correlation was employed to test the relationship between the physicochemical properties and zooplankton abundance and distribution at P<0.05 level of significance using Minitab19.2020 software.

RESULT AND DISCUSSION

The results of the physicochemical properties were presented in table 1. The ranges of Water temperature (21.6-28.9⁰C) recorded in Pindiga lake was slightly lower than the ranges reported by Abubakar et al., (2015) conducted in Dadin Kowa reservoir, Gombe State, Saidu et al., (2016) conducted in Balanga dam, Dimowo, (2013) conducted in river Ogun, Abeokuta, Ogun State and higher than the range reported by Usman and Yerima, (2017) in Ajiwa reservoir, Katsina State. The difference was might be due to differences in location, altitude and other factors such as cloud cover, vegetation and level of penetration of sunlight.

Water pH ranges between (7.11-7.49), The pH ranges recorded during the study period was higher than the ranges reported by Otene et al., (2019) in a research conducted at Okamini Stream, Port Harcourt and lower than the ranges reported by Abubakar et al., (2015) conducted in Dadin kowa, Usman and Yerima, (2017) conducted in Ajiwa river, Katsina State. Dimowo, (2013) conducted a field research in River Ogun, Abeokuta, Ogun State, Ekpo, (2013) conducted in tropical rain forest river in Niger Delta, Nigeria, Azuka et al., (2018) conducted at Ikpoba river. The differences might be due to the amount of decomposition and inflow of inorganic nutrient into the water bodies.

Electrical Conductivity (264.5-321.3µm/S) Electrical conductivity had its highest mean value during the month of April and lowest mean value during the month of July agreed with the findings of Usman and Yerima, (2017) in a field research conducted in Ajiwa river, Katsina State, who reported the highest electrical conductivity during the month of April and lowest value recorded during the month of August. The low value of Electrical conductivity in July might be due to low concentration of ions due to dilution effect of rainfall and highest in April was due to high concentration of ions in the water body. The range mean value of conductivity in Pindiga Lake was higher than the electrical conductivity range reported by Abubakar et al., (2015) conducted in Dadin Kowa reservoir, Gombe State, Esenowo et al., (2017) conducted in Nwaniba, River state, Isah et al., (2018) conducted in Dadin kowa Dam, Gombe State and lower than the range reported by Usman et al., (2019) conducted in Kashimbila river, Takum, Taraba State. The differences might be to the level of inflow of ions into the water body and variation caused by the topography.

Total Dissolved Solid (132.25-160.8mg/L) Total dissolved solid had its highest mean value of during the month of April and lowest mean value of during the month of July agreed with the findings of Usman and Yerima, (2017) in a field research conducted in Ajiwa river, Katsina State, who reported the highest Total dissolved solid during the month of April and lowest value recorded during the month of August. The low value of Total dissolved solid in July might be due to low solubility of solid and low inflow of water into the system and highest in April was due to low water in the lake which may increase the concentration of solute in the water body.

The range mean value of Total dissolved solid in Pindiga Lake was higher than the Total dissolved solid range reported by Abubakar et al., (2015) conducted in Dadin Kowa reservoir, Gombe State, Esenowo et al., (2017) conducted in Nwaniba, River state, Isah et al., (2018) conducted in Dadin kowa Dam, Gombe State and lower than the range reported by Usman et al., (2019) conducted in Kashimbila river, Takum, Taraba State. The differences might be to the nature of the water body and variation caused by the topography. Total dissolved solids which mostly consist of organic and inorganic substances dissolved and washed into the lakes by runoffs are very essentials in the survival, growth and reproduction of aquatic organisms (Umar, 2014).

Table 1: Mean±SEM of physico-chemical properties throughout the study period (March-August, 2019) in Pindiga Lake, Gombe, Nigeria.

			Months
Physicochemical	March	April	May	June	July	August	Range
Air temp. (⁰C)	38.2±0.8^a	36.6±0.6^b	36.75±0.3^b	32.74±0.2^c	30.4±1.03^d	32.1±0.75^c	30.4-38.2
Water temp. (⁰C)	28.9±1.01^a	25.6±0.28^b	26.5±0.48^b	23.3±0.26^c	21.6±0.52^d	22.1±0.88^d	21.6-28.9
pH	7.1±0.35^a	7.3±0.11^a	7.5±0.17^ab	7.4±0.05^abc	7.2±0.17^bcd	7.5±0.03^cd	7.1-7.49
E.C(µS/cm)	301.5±16.2^a	321.3±2.5^b	318±5.2^b	278.3±1.5^c	264.5±2.7^c	292.8±2.5^d	264.5-321.3
TDS (mg/L)	151±8.3^a	160.75±1.2^b	159±2.6^b	139.1±0.75^c	132.3±1.3^c	146.38±1.3^a	132.3-160.8
Turbidity (cm)	22.8±1.19^a	20.3±2.4^b	16.9±2.39^c	18.8±0.65^bc	19.9±1.3	20.9±0.75^abd	16.9-22.8
DO (mg/L)	3.6±1.03^c	3.98±0.36^bc	4.3±0.12^b	5.07±0.12^a	5.53±0.1^a	5.74±0.19^a	3.6-5.74
BOD (mg/L)	1.99±0.65^bc	1.9±0.29^bc	2.07±0.06^b	2.24±0.09^b	3.18±0.13^a	2.96±0.1^a	1.9-3.18
Nitrate (mg/L)	9.22±2.12^bc	10.66±1.2^ab	10.98±0.3^a	9.91±0.41^abc	8.79±0.21^c	10.94±0.14^a	8.79-10.98
Phosphate (mg/L)	2.49±0.32^d	3.05±0.15^b	2.93±0.17^bc	2.73±0.17^cd	2.8±0.09^bc	3.89±0.17^a	2.49-3.89

Mean value with same superscripts are not significant difference (p≤0.05), Key: pH= Percentage of hydrogen, E.C= Electrical Conductivity, D. O=Dissolved Oxygen; BOD= Biochemical Oxygen Demand

Turbidity (16.9-22.8cm) Turbidity had its highest mean value during the month of March and lowest mean value of during the month of July and May contrary to the findings of Usman and Yerima, (2017) in a field research conducted in Ajiwa river, Katsina State, who reported the highest Turbidity during the month of August and lowest value recorded during the month of May. The low value of Turbidity in July and May might be due to high transparency and low turbulences of water caused by excessive usage of the inhabitant and highest in April was due to high water usage in the lake which may increase the turbulence and upset the water body. The range mean value of Turbidity in Pindiga Lake was similar to the range reported by Abubakar et al., (2015) conducted in Dadin Kowa reservoir, Gombe State, Esenowo et al., (2017) conducted in Nwaniba, River state, Isah et al., (2018) conducted in Dadin kowa Dam, Gombe State and lower than the range reported by Usman et al., (2019) conducted in Kashimbila river, Takum, Taraba State.

Dissolved Oxygen (3.6-5.8mg/L) The Dissolved oxygen range recorded during the study period was similar to the ranges reported by Otene et al., (2019) in a research conducted at Okamini Stream, Port Harcourt, Abubakar et al., (2015) conducted in Dadin kowa, Isah et al., (2018) at Dadin kowa Reservoir and slightly lower than the ranges reported by Usman and Yerima, (2017) conducted in Ajiwa river, Katsina State, Dimowo, (2013) conducted a field research in River Ogun, Abeokuta, Ogun State, Imaobong, (2013) conducted in tropical rain forest river in Niger Delta, Nigeria, Azuka et al., (2018) conducted at Ikpoba river.

The differences might be due to differences in temperature and solubility of gases. Therefore, the dissolved oxygen of Pindiga Lake is within the required range of good water quality. The highest dissolved oxygen was recorded during the month of August which agreed with the finding of Usman and Yerima, (2017) reported in a field research conducted at Ajiwa river, Katsina State and Similar to the findings of Abubakar et al., (2015). High dissolved oxygen observed during the month of August was caused as a result of low temperature and high solubility of gases. Dissolved oxygen is an essential factor that facilitates the survival, growth and reproduction of aquatic organisms. The dissolved oxygen concentrations ranged 3.6mg/l to 5.7mg/l and hence, the concentrations were within the required range. The amount of dissolved oxygen in water has been reported not static but dynamics, depending on temperature, depth, wind and extent of living organisms such as decomposition (Indabawa, 2009). Low dissolved oxygen affects the growth of many organisms and enhances the rate of metabolic activities (Charles, 2003); therefore, adequate dissolved oxygen is essential for all living organisms. The lower the dissolved oxygen the poorer will be the water quality (Umar, 2014).

Biochemical Oxygen Demand (1.9-3.2mg/L), Biochemical oxygen demand range recorded during the study period was similar to the ranges reported by Abubakar et al., (2015) conducted in Dadin kowa reservoir, Gombe State, Isah et al., (2018) at Dadin kowa Reservoir, Gombe State, Otene et al., (2019) in a research conducted at Okamini Stream, Port Harcourt and slightly lower than the ranges reported by Dimowo, (2013) conducted a field research in River Ogun, Abeokuta, Ogun State; Imaobong, (2013) conducted in tropical rain forest river in Niger Delta, Nigeria; Usman and Yerima, (2017) conducted in Ajiwa river, Katsina State, Azuka et al., (2018) conducted at Ikpoba river.

Phosphate ranged between (2.5-3.9mg/L), the range mean value of phosphate value in Pindiga Lake was higher than the phosphate range reported by Abubakar et al., (2015) conducted in Dadin Kowa reservoir, Gombe State, Esenowo et al., (2017) conducted in Nwaniba, River state, Isah et al., (2018) conducted in Dadin kowa Dam, Gombe State and lower than the range reported by Usman et al., (2019) conducted in Kashimbila river, Takum, Taraba State. The variation might be due to the nature of the water body as a close system and variation caused by the topography. Phosphorus plays an important role in the determination of the productivity of an ecosystem, which in turn can affect the number of trophic level in a food web and its stability. The presence of nutrients and plant biomass formation in water body exhibit a complex dynamic relationship in tropical aquatic ecosystem due to various physico-chemical and biological characteristic (Siddique and Kale,2018).

Nitrate ranges between (8.8-10.1mg/L), the range mean value of Nitrate in Pindiga Lake was higher than the range of Nitrate reported by Esenowo et al., (2017) conducted in Nwaniba, River state, Abubakar et al., (2015) conducted in Dadin Kowa reservoir, Gombe State, Isah et al., (2018) conducted in Dadin kowa Dam, Gombe State and lower than the range reported by Usman et al., (2019) conducted in Kashimbila river, Takum, Taraba State.

Planktonic fauna distribution and abundance

Result of zooplankton in Pindiga lake is contrary to the research conducted by Usman and Yerima, (2017) who reported four different taxa of zooplankton in Ajiwa river, Katsina State and agreed with the finding of Emmanuel et al., (2008) who reported three taxa of Zooplankton in Calabar river. The Copepods were the most abundant zooplankton taxon of the zooplankton abundance. Likewise, results have been reported by Erondu and Solomon (2017) in Behind Girls hostel, University of Abuja and Emmanuel et al., (2008) in Calaba river, Nigeria. Their abundance was may be due to their acclimatization to altering ecological condition and capability to bear up varying ecological hassle (Emmanuel et al., 2008). The abundant of Copepoda is also dependent on availability of sufficient nutrients and favorable temperature (Sharma et al., 2013).

The second most abundant taxon was Cladocera of the total zooplankton abundance this finding is in disagreement with the findings of Abba et al., (2016) who stated that cladoceran were least zooplankton species in Kpata lake, Lokoja, Nigeria. Their abundance would be attributed to their capability to undergo upright movement, which lessens competition through niche exploitation and food utilization (Usman and Yerima, 2017). Cladocera have widely been used as biological indicators in studies due to their sensitivity to various levels of water quality characteristics (Radix, et al., 2002).

Rotifera is the least abundant zooplankton in the study area similar to the statement of Forro (2010) who reported that Rotifera are the least abundant zooplankton in freshwater and contrary to the finding of Abba et al., (2016) who reported that rotifer is the second most abundant zooplankton in Kpata Lake, Lokoja, Nigeria. The result also shows that copepod has a total number of 13 genera contrary to the report of Ekpo, (2013) in a field research conducted in a tropical rain forest river in Niger Delta, Nigeria, who reported the number of species fall under copepod as 9 species Cladocera consisting of 7 genera and Rotifera comprises 8 genera of species richness, consequently, Copepoda is the richest of all zooplankton taxa followed by Rotifera then Cladocera.

The percentage of copepods in Pindiga lake was closely similar to the finding of Solomon and Erondo, (2018) who reported almost the same percentage of copepods in a field research conducted at behind girl’s hostel, university of Abuja on Identification of planktons (zooplankton and phytoplankton), contrary to the finding of Usman and Yerima, (2017) who reported lower percentage of copepods in a field research conducted on ecological investigation of zooplankton abundance in Ajiwa reservoir, Katsina State, Nigeria, as the most least abundance zooplankton taxon in the water body. The variation may be as result of anthropogenic activities carried out around the water body.

Table 2: Monthly zooplankton abundance and distribution in Pindiga Lake, Gombe State, Nigeria

			Months
Taxa	March	April	May	June	July	August
Copepoda	47.32	47.78	46.89	43.87	41.36	45.29
Skistodiaphthamus sp.	6.25	4.93	6.7	5.2	4.94	5.86
Leptodiaphthamus sp.	5.36	0.99	5.74	4.46	3.7	4.93
Macrocyclops sp.	6.25	7.39	4.31	5.2	4.32	3.76
Paracyclops sp.	2.68	8.37	5.26	2.97	3.4	5.63
Senecella sp.	2.68	4.93	7.66	6.69	4.94	5.16
Acanthocyclops sp	1.79	2.96	2.87	2.23	1.85	5.16
Limnocalanus sp.	4.46	0	0.96	1.12	0.62	3.29
Tropocyclops sp.	8.93	8.37	3.35	1.86	2.16	3.05
Nauplius sp	0	0	1.44	8.92	8.64	3.29
Cathocamptus sp.	0	3.94	2.87	2.23	1.85	3.05
Diacyclops sp.	4.46	3.94	3.82	2.97	4.94	2.11
Aglaodiaphthamus sp.	4.46	0.99	1.91	0	0	0
Mesocyclops sp.	0	0.99	0	0	0	0
Cladocera	24.11	22.66	22.01	36.43	34.26	39.67
Bosmina sp.	4.46	2.46	3.35	6.69	4.63	8.22
Diaphanosoma sp.	0	0	0	3.72	7.41	0
Eubosmina sp.	0	0	0	4.46	0	7.04
Daphnia sp.	8.04	2.46	3.35	7.43	4.94	5.63
Ceriodaphnia sp.	0	1.97	2.39	4.83	4.01	5.63
Macrothrix sp	6.25	8.87	2.87	4.46	5.86	5.4
Moina sp.	5.36	6.89	10.05	4.83	7.41	7.75
Rotifera	28.57	29.56	31.1	19.7	24.38	15.02
Asplanchna sp.	4.46	4.43	8.13	2.23	3.4	2.58
Brachianus sp.	2.68	9.36	2.87	5.95	6.79	2.82
Keratella sp.	6.25	3.45	7.66	1.49	2.47	2.82
Polyarthra sp.	8.96	7.88	4.31	2.6	5.56	3.52
Trichocerca sp.	0	0.99	3.35	1.12	6.17	0.47
Synchaeta sp.	2.68	2.96	4.78	6.32	0	2.82
Hexarthra sp.	0	0.49	0	0	0	0
Anuraepsis sp.	3.57	0	0	0	0	0
Shannon index(H)	3.44	4.26	4.74	5.57	5.87	6.86
Evenness (E)	1.15	1.38	1.50	1.75	1.89	2.19

Table 3: Correlation matrix showing relationship between Zooplankton taxa and Physico-chemical characteristics in Pindiga Lake, 2019.

Properties

Air temp

temp

E.C

TDS

Turbi.

BOD

Nitrate

Phos

Cop

Clado

Rotif

Water temp

0.973

Water pH

-0.11

-0.28

E.C

0.837

0.692

0.323

TDS

0.841

0.697

0.316

Turbidity

0.138

0.212

-0.619

-0.109

-0.101

-0.954

-0.956

0.337

-0.713

-0.718

-0.191

BOD

-0.891

-0.838

-0.017

-0.758

-0.76

0.066

0.895

Nitrate

0.249

0.044

0.897

0.684

0.678

-0.423

-0.016

-0.289

Phosphate

-0.366

-0.517

0.676

0.098

0.094

-0.009

0.573

0.451

0.656

Copepod

-0.787

-0.868

0.553

-0.4

-0.405

-0.129

0.913

0.775

0.32

0.855

Cladocera

-0.854

-0.884

0.395

-0.587

-0.591

0.01

0.95

0.838

0.115

0.742

0.966

Rotifera

-0.689

-0.758

0.311

-0.305

-0.311

-0.538

0.677

0.654

0.118

0.412

0.63

0.514

Bold font indicated that correlation is significant at (p<0.05)

The result of zooplankton throughout the months revealed that all the months were highly rich in the assemblage of zooplankton with almost all representatives of species. This could be as a result of favorable environmental conditions. This agreed with Alexander, (2012) who suggested that the abundance of zooplankton depends on a number of factors such as climatic change, habitat physico-chemical characteristics and biotic factors.

CONCLUSION

Outcome of the research indicated that physicochemical properties were within the range value suggested for most tropical water bodies and abundance of zooplankton is highly exhilarating compare to other water bodies. Consequently, the lake is suitable to sustain the proliferation, continued existence and development of aquatic organisms predominantly fish.

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