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Plankton are sensitive to their environment and are used to monitor anthropogenic impacts. A South-eastern Nigeria River was studied from December 2017 to November 2018 in 6 stations; to assess the plankton community, water quality and anthropogenic impacts. The river was subjected to intense sand mining activities among other activities. The plankton was sampled with filtration method while water was collected and analysed using standard methods. A total of 36 phytoplankton species and 27 zooplankton species were recorded with Chlorophyceae and Rotifers being the most abundant groups. The most abundant species - Melosira granulata (phytoplankton) and Daphnia pulex (zooplankton) are pollution indicators. Some of the physicochemical parameters showed that the river was perturbed by the anthropogenic activities in the watershed. However, the plankton assemblage and community structure gave an indication of a stable environment; though the zooplankton fauna showed some level of stress. The impacts of sand mining activities on water quality and plankton were more in the downstream stations (4–6) where sand mining was intense while perturbation from swimming children and related activities were observed in station 1 especially during the dry season. The presence of eutrophic indicators and tolerant species showed that the river was tending towards eutrophication. Sand mining activities contributed to the nutrient enrichment of the river. CCA showed the major water quality parameters that influenced the plankton community structure. There is need to regulate illegal sand mining activities in the river. Conservation Biology Environmental Policy Plankton Diversity anthropogenic bioindicator water quality sand mining Figures Figure 1 Figure 2 Figure 3 Introduction Rivers support diverse and large number of flora and fauna; making some of them the most productive ecosystems on the earth and biodiversity hotspots. Freshwater bodies across the world are subjected to intense human activities which has degraded the quality and utility of the water [ 1 ]. Researchers have predicted the quality of the aquatic ecosystem and ecological effects of human activities by the assessment of its biological communities [ 2 , 3 ]. Planktons are one of the essential biological communities found in lotic freshwater ecosystems [ 4 , 5 ]. Regular monitoring of planktons is the cheapest and easy method of assessing the quality of water in developing countries [ 6 ]. Planktons (phytoplankton and zooplankton) are essentially microscopic, non-motile or weak swimming organisms floating in the water column and drift with it; making them susceptible to changes in the water [ 7 ]. Mathivanan et al [ 8 ] reported that due the sensitivity of planktons to their environments, changes in the environment will affect the tolerance, abundance, diversity and dominance of the plankton communities in the habitat. They are highly sensitive to fluctuations in nutrient levels, temperature, pollution, levels of light and increase in predation [ 9 , 10 ]. Plankton directly or indirectly controls all the secondary productions in the aquatic ecosystems [ 11 , 12 ]. According to Bellinger and Sigee [ 13 ], phytoplankton are the micro-plant organisms without distinct roots, stems and leaves. The phytoplankton community plays a key role in aquatic ecosystems as bioindicators and primary producers; providing for carbon fixation, oxygen and food production [ 14 ]. Phytoplankton species are able to survive and develop in diverse aquatic habitats but each species is restricted to a defined niche based on their physiological requirements and environmental limitations [ 15 ]. Zooplankton are microscopic animals that are essential components of aquatic food webs; an important link in the conversion of energy from producers to consumers [ 16 , 17 ]. Schmidt et al [ 18 ] described zooplankton as a key biological group that is very important to the functioning of the ecosystem. They respond strongly to environmental changes and are used to assess the conditions in aquatic ecosystems [ 18 , 19 ]. Temporal and spatial variations of physico-chemical environmental conditions often result in dramatic and rapid changes in zooplankton because of their short life span and fast regeneration [ 20 ]. The trophic transfer efficiencies from phytoplankton to zooplankton and from zooplankton to fish are largely dependent on the taxa of zooplankton available in an aquatic ecosystem [ 21 , 22 ]. The composition of macroinvertebrate predator and fish species can be influenced by the pattern of changes in the zooplankton species composition within the same space [ 23 ]. In aquatic ecosystems, decline in zooplankton diversity will ultimately affect higher trophic levels; resulting in loss of species, habitat or even ecosystems and ecosystem services, if the trend was not abated [ 24 ]. Eme River was subjected to a number of anthropogenic activities, of which illegal and indiscriminate sand mining was the major one. The objective of this study was therefore to assess the water quality and plankton diversity in relation to anthropogenic activities. Study Area Eme River took its source from Uzoakoli in Abia State, Nigeria; flowing through many communities before discharging into Imo River at Onuimo. The section of Eme River studied was between Ofeme and Umudiawa across the Port Harcourt - Enugu expressway in Umuahia, Abia State; about 3.25km in length (Fig. 1). It lies between latitude 5°38’ and 5°37’N and Longitude 7°25’ and 7°26’E. The study area falls within the sub-equatorial zone with mean annual rainfall of about 4000mm per annum. It is characterized by high relative humidity of over 70% and high temperature of about 29-31 o C. It is also characterized by two seasons - wet (June to November) and dry (December to May) and double maxima rainfall peaks in July and September with a short period of dryness between the peaks known as the August break. The river was divided into six stations, which were within the dredged section except station 1. Station 1, located within Ofeme community at Mbato, was upstream and the control station. The major human activities observed were including laundry and extraction of drinking water in the dry season. Large number of children was also observed swimming during the dry season up to early rains because easy accessibility and low water depths. The substrate is muddy. Station 2, located on the out sketch at Eme - Ihite, about 1.84km downstream of Station 1. It was a less active sand mining site and minimal laundry, swimming and extraction of drinking water were observed during the dry season. The substrate is mixture of sand and stones. Station 3, also located in Eme - Ihite, by the expressway, about 419.67m downstream of Station 2. No activities were observed except periodic boat movements. The substrate is made up of large clayey boulders. Station 4, located in Umudiawa Community across the expressway, about 490.26m downstream of Station 3. It was also downstream to an intensive sand mining and two sand landing sites. The substrate was sandy. Station 5, within Umudiawa Community was about 200.22m downstream of Station 4. The substrate was sandy and sand mining activities was also observed. Station 6, within Umudiawa Community was about 300.14m downstream of Station 5. The substrate was sandy and sand mining activities occur within the water channel and around the shores. Samples collection and analyses Water Samples Water samples were collected from Eme River, Umuahia, monthly between December 2017 and November 2018. The samples were collected with 1-litre water sampler, stored in sterilized 1litre plastic bottles and then taken to the laboratory for analysis. Some physicochemical parameters (Water Temperature, Flow Velocity, Turbidity, pH, Electrical Conductivity and Total Dissolved Solids) were determined in-situ while Dissolved Oxygen, Biochemical Oxygen Demand, Nitrate and Phosphate were determined in the laboratory using standards methods described by American Public Health Association (APHA) [25]. Plankton Samples Plankton samples were collected from undisturbed areas of the River as the water samples. The sampling was carried out using the quantitative method. A composite sample of 100 litres of water was filtered through 55um Hydro-Bios plankton net (with the aid of a 10 litres of bucket drawn 10 times at each station). The net content was washed out into plankton bottles of 250ml size and preserved in 4% formalin solution after a proper labelling. In the laboratory, one ml of the preserved sample was taken as a sub sample using a pipette. The collected sample was put on the Sedgwick-rafter counting chamber and viewed under a light binocular microscope (Nikon 400 binocular microscope) using a low magnification of x10. Planktons were sorted into different groups and the cells per ml were counted. Identification work was done using key literatures by Jeje and Fernando [26]; Janse van Vuuren et al [27] and Dang et al [28]. The identification was made to lowest practicable taxonomic. Statistical Analysis The data were summarised using Descriptive Statistic Package of Microsoft Excel while one-way ANOVA was used to test for statistical differences among the stations and Tukey’s pairwise comparisons test was performed to determine the location of significant difference (P<0.05). The community structures of the plankton were determined using Margalef (D), Shannon-weiner (H) Evenness (E) indices. Canonical correspondence analysis (CCA) was used to evaluate relationships between the plankton groups and environmental variables with PAST statistical package [29]. Results Water Quality Aspects of the physicochemical parameters of Eme River are presented in Table 1 . Surface water temperature ranged from 22.0 o C to 28.5 o C. The lowest value was recorded in station 1 in May 2018 while the highest was recorded in station 6 in April 2018. The temperature values were within acceptable limits. Flow velocity values were moderate; ranging between 0.21 and 0.85 m/s. The lowest flow velocity was recorded in station 1 in April 2018 while the highest was recorded in station 3 in December 2017. Stations 2 and 3 were significantly higher (F = 31.59; P < 0.05) than the other stations. Turbidity ranged between 0.5 and 9.4 NTU. The lowest and highest values were recorded in station 4 in March and February 2018 respectively. Stations 4–6 recorded relatively higher turbidity values especially between May and October, 2018. Some of the values exceeded the 5 NTU limit set by FMEnv [ 30 ] in all the stations. All the pH values recorded were acidic and lower than the acceptable limit (6.5–8.5); ranging from 4.3 to 6.3. The lowest pH was recorded in station 2 in June 2018 while the highest value was recorded in station 1 in September 2018. The electrical conductivity (EC) values ranged between 45.2 and 168.4 µS/cm. The lowest and values highest were recorded in stations 2 and 5 in March and January 2018 respectively. The downstream stations (4–6) were significantly higher (F = 29.59; p 6mg/L) set by FMEnv [ 30 ]. The lowest value was recorded in station 4 in November 2018 while highest was recorded in stations 3 (January 2018) and 4 (February 2018). Biochemical oxygen demand (BOD) values ranged between 0.8 and 4.3 mg/L. The lowest and highest values were recorded in November 2018 and February 2018 respectively in station 4. Some of the values exceeded the acceptable limit (3 mg/L) especially in Stations 4–6. Station 4 was significantly higher than stations 2 and 3 (F = 3.43; p < 0.05). Nitrate values were all within acceptable limit and ranged from 1.1 to 5.6 mg/L; though station 4 was significantly (F = 14.62; p < 0.05) higher than the other stations. The lowest value was recorded in station 3 (June 2018) while the highest was recorded in station 4 (February 2018). Phosphate values ranged between 0.4 and 4.6 mg/L. The lowest value was recorded in station 3 (June and July 2018) while the highest was recorded in station 4 (September 2018). Stations 4–6 recorded values that exceeded the acceptable limit and were significantly different (F = 56.71; p < 0.05) from stations 1–3. Table 1 Summary of Physico-chemical Parameters of Eme River, Umuahia, Abia State. Parameter Stn 1 X ± SEM Stn 2 X ± SEM Stn 3 X ± SEM Stn 4 X ± SEM Stn 5 X ± SEM Stn 6 X ± SEM P-value FMEnv. Water Temperature ( o C) 24.8 ± 0.59 (22.0–28.0) 24.9 ± 0.54 (22.5–28.2) 24.8 ± 0.53 (23.0-28.2) 24.9 ± 0.51 (23.2–28.4) 24.4 ± 0.53 (23.0-28.3) 24.8 ± 0.53 (22.9–28.5) P > 0.05 0.05 5 Flow Velocity (m/s) 0.35 ± 0.02 a (0.21–0.49) 0.56 ± 0.04 b (0.37–0.80) 0.71 ± 0.02 c (0.63–0.85) 0.36 ± 0.02 a (0.24–0.46) 0.37 ± 0.02 a (0.28–0.50) 0.45 ± 0.0 a (0.26–0.58) P 0.05 6.5–8.5 Electrical Conductivity (µS/cm) 86.0 ± 4.40 a (55.6-115.8) 71.3 ± 4.43 a (45.2–95.4) 65.7 ± 3.50 a (49.6–88.7) 130.4 ± 5.86 b (90.3-160.2) 115.4 ± 6.04 b (88.5-168.4) 119.6 ± 5.38 b (87.1-148.4) P < 0.05 - Total Dissolved Solids (Mg/l) 43.0 ± 2.17 a (27.5–56.9) 35.8 ± 2.25 a (22.6–47.7) 33.1 ± 1.86 a (24.8–46.5) 65.3 ± 2.81 b (46.9–80.1) 57.9 ± 3.03 b (44.7–85.2) 60.0 ± 2.69 b (43.2–74.2) P 0.05 6 Biochemical Oxygen Demand (Mg/l) 1.7 ± 0.14 ab (1.0-2.5) 1.5 ± 0.08 b (1.1–1.9) 1.7 ± 0.12 b (1.1–2.4) 2.6 ± 0.37 ac (0.8–4.3) 1.9 ± 0.20 ab (1.0-3.2) 2.1 ± 0.25 ab (0.9–3.9) P < 0.05 3 Nitrate (Mg/l) 2.9 ± 0.30 b (1.8–4.9) 2.2 ± 0.17 b (1.3–3.2) 1.6 ± 0.12 a (1.1–2.4) 4.5 ± 0.20 c (3.4–5.6) 2.6 ± 0.37 ab (1.2–5.3) 2.9 ± 0.27 b (1.9–5.2) P < 0.05 9.1 Phosphate (Mg/l) 1.3 ± 0.08 a (1.0-1.9) 0.8 ± 0.10 a (0.5–1.7) 0.7 ± 0.07 a (0.4–1.2) 3.4 ± 0.18 b (2.8–4.6) 2.8 ± 0.22 bc (1.9–4.3) 2.9 ± 0.21 bc (2.0-4.5) P < 0.05 3.5 a, b, c, d, e = Means with different superscripts across the rows are significantly different at p < 0.05; SEM = Standard Error of Mean; FMEnv. National Environmental (Surface and Groundwater Quality Control) Regulations (2011). Plankton composition, abundance and distribution Phytoplankton The species composition of phytoplankton in the stations of Eme River, Umuahia was presented in Table 2 . A total of 5213 phytoplankton individuals were recorded, out of which the most abundant group was Chlorophyceae (1776 or 34.1%), followed by Bacillariophyceae (1234 or 23.7%). Other phytoplankton taxa recorded were Cyanophyceae (838 or 16.1%), Euglenophyceae (835 or 16.0%) and Pyrrophyceae (530 or 10.2%). One-way ANOVA showed that Cyanophyceae, Euglenophyceae and Pyrrophyceae were significantly (F = 18.0, p < 0.05) lower than Chlorophyceae and Bacillariophyceae in terms of abundance. Spatially, station 3 recorded the most abundant individuals (1108 individuals/L or 21.3%), followed by station 2 (1007 individuals/L or 19.3%) while station 1 (748 individuals/L or 14.3%) was the least. One-way ANOVA showed that stations 2 and 3 were significantly (F = 10.3, p < 0.05) higher than stations 1, 4–6 in terms of abundance. The most abundant phytoplankton species recorded was Melosira granulata (Bacillariophyceae) with 190 individuals (3.64 % of the total phytoplankton abundance), followed by Planktosphaeria gelatinosa (Chlorophyceae) with 180 individuals/L (3.45% of the total phytoplankton abundance) and the least was Peridinium depressum (Pyrophyceae) with 101 individuals/L (1.94% of the total phytoplankton abundance). Table 2 Species composition, abundance and distribution of phytoplankton in Eme River, Umuahia, Nigeria. Group Taxa Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Total RA (%) Cyanophyceae Anabaena affins 14 29 26 30 36 35 170 3.26 A. spiroides 12 36 31 14 21 19 133 2.55 Oscilatoria laccustris 14 21 35 21 30 30 151 2.90 Spirulina substilissinia 18 24 29 26 14 14 125 2.40 Microcystis weswenbergii 11 23 24 25 18 32 133 2.55 Coelosphaerium pallidum 10 27 20 24 22 23 126 2.41 Euglenophyceae Euglena candata 13 35 20 15 42 32 157 3.01 E. acus 20 24 25 15 12 34 130 2.59 E. proxima 27 20 28 25 26 12 138 2.65 Phacus longicanda 23 29 37 31 20 19 159 3.05 P. caudata 24 30 23 15 24 10 126 2.42 Trachelomonas aramata 33 14 30 20 28 0 125 2.40 Bacillariophyceae Amphoria ovaris 24 28 32 40 21 16 161 3.09 Melosira granulata 25 30 32 42 22 39 190 3.64 M varians 25 29 23 15 19 20 131 2.51 Synedra acus 32 28 23 19 19 13 134 2.57 S. ulna 25 29 19 35 18 25 151 2.90 S. affins 20 31 28 39 28 30 176 3.38 Cyclotella glomerata 33 30 27 23 20 13 146 2.80 Tragilaria crotonesis 15 22 32 21 33 22 145 2.78 Chlorophyceae Pediastrum clathratum 19 27 28 31 20 20 145 2.78 P. simplex 26 21 43 15 24 31 160 3.07 P. dublex 4 39 28 21 26 27 145 2.78 Closterium moniliferum 31 32 38 17 14 21 153 2.93 C. parvulum 20 26 29 22 22 21 140 2.69 C. macilentum 1 25 34 16 19 23 118 2.26 Cosmarium amoerum 2 29 42 11 30 25 139 2.67 Mougeotia scalaris 32 29 34 17 18 16 146 2.80 Volvox aureus 26 21 38 17 22 30 154 2.95 Chlamydomonas Atactogam 26 31 40 9 21 16 143 2.74 Planktosphaeria Gelatinosa 28 43 48 19 24 18 180 3.45 Scenedesmus quardriacauda 11 34 29 17 26 36 153 2.93 Pyrophyceae Ceratium candelabum 30 31 45 16 6 19 147 2.82 C. hirudenella 23 29 34 25 9 25 145 2.78 Peridinium depressum 23 18 31 8 9 12 101 1.94 P. latum 28 33 23 25 20 8 137 2.63 Total 748 1007 1108 781 783 786 5213 Phytoplankton Community Structure The number of taxa (species) recorded were 36 in all the station except station 6 with 35 (Table 3 ). The number of individuals ranged from 748 (station 1) to 1108 (station 3). Shannon-weiner diversity index (H) varied from 3.477 (station 1) to 3.562 (station 2). Margalef Species Richness, on the hand was highest in station 1 (5.289) and station 3 had the least (4.993).The Evenness Index (E) was highest in station 2 (0.9785) and least in station 1 (0.8987). Table 3 Community Structure of Phytoplankton in Eme River, Umuahia, Nigeria. Biodiversity Indices Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Taxa (S) 36 36 36 36 36 35 Individuals 748 1007 1108 781 783 786 Shannon-Weiner (H) 3.477 3.562 3.557 3.514 3.526 3.490 Evenness (E) 0.8987 0.9785 0.9740 0.9327 0.9441 0.9371 Margalef 5.289 5.062 4.993 5.255 5.253 5.100 Relationship between Phytoplankton Groups and Environmental Variables The Canonical Correspondence Analysis (CCA) showed that electrical conductivity and phosphate exerted a greater positive influence on the relative abundance of the phytoplankton groups compared to the higher negative influence exerted by pH and temperature (Fig. 2). Biochemical oxygen demand, electrical conductivity and phosphate exerted positive influence on cyanophyceae and flow velocity on euglenophyceae and chlorophyceae. On the other hand, turbidity and nitrate exerted negative influence on bacillariophyceae and temperature on Pyrrophyceae. Spatially, pH and flow velocity exerted negative influence respectively in stations 1 and 3 while turbidity and nitrate exerted negative influence in station 4. Zooplankton The overall species composition, abundance and distribution of zooplankton in the stations of Eme River, Umuahia are presented in Table 4 . A total of 3382 zooplankton individuals were recorded in this study. Of these, the most abundant group was Rotifer (1064 individuals/L or 31.5%) followed by Cladocera (961 individuals/L or 28.4%), Protozoa (741 individuals/L or 21.9%) and Copepod (616 individuals/L or 18.2%). Spatially, Station 2 recorded the most abundant individuals (619 individuals/L or 18.3%), followed by Station 6 (614 individuals/L or 18.2%), Station 3 (577 individuals/L or 17.1%), Station 5 (511 individuals/L or 15.1%) and station 4 (498 individuals/L or 14.7%). The most abundant zooplankton recorded was Daphnia pulex (Cladocera) with175 individuals/L (5.17% of the total zooplankton abundance). Table 4 Species composition, abundance and distribution of phytoplankton in Eme River, Umuahia, Nigeria. Group Taxa Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Total RA (%) Copepoda Campthocamptus staphylinus 26 21 14 33 22 22 138 4.08 Eucyclops speratus 10 22 39 29 12 32 144 4.26 Microcyclops varicans 21 27 22 11 16 21 118 3.49 Sinodiatomus sarsi 23 20 20 0 3 22 88 2.6 Mesochra suifunensis 24 18 26 16 10 34 128 3.78 Cladocera Alona affins 12 19 25 27 34 13 130 3.84 Daphnia longis 20 26 23 10 20 35 134 3.96 D. pulex 25 25 35 27 37 26 175 5.17 D. magna 26 26 25 12 22 28 139 4.11 Moina dubia 44 22 19 20 26 35 166 4.91 M. micrura 11 18 22 20 22 15 108 3.19 Diaphanosoma Brachyurum 21 15 19 27 20 7 109 3.22 Rotifera Keratella cochlearis 20 20 21 14 15 14 104 3.08 Brachionus capsuliflorus 20 26 12 25 23 35 141 4.17 Asplanchna priodontra 27 19 25 27 31 22 151 4.47 Notholca labis 15 36 14 11 33 22 131 3.87 Synchaeta pectinata 26 23 30 23 21 29 152 4.49 Conochilus umcormis 25 23 25 21 6 28 128 3.79 Ascomorpha ecaudis 29 30 20 13 17 18 127 3.76 B. plicatilis 16 24 18 25 17 30 130 3.84 Protozoa Paramecium candatum 15 21 13 12 24 20 105 3.11 Difflugia candatum 14 18 22 15 17 7 93 2.75 Didinium bolbanic 26 25 22 8 8 14 103 3.05 Tintinnopsis lacustris 17 27 12 20 23 25 124 3.67 Amoeba radiosa 11 17 12 13 11 23 87 2.57 Vorticella radians 20 30 17 24 18 32 141 4.17 Arcella nitrata 19 21 25 15 3 5 88 2.60 Total 563 619 577 498 511 614 3382 Zooplankton Community Structure The number of taxa (species) recorded were 27 in all the station except station 4 with 26 (Table 5 ). The number of individuals ranged from 498 (station 4) to 619 (station 2). Shannon-weiner diversity index (H) varied from 3.178 (station 5) to 3.276 (station 2). Margalef Species Richness, on the hand was highest in station 5 (4.169) and station 4 had the least (4.025).The Evenness Index (E) was highest in station 2 (0.9806) and least in station 5 (0.8885). Table 5 Community Structure of Zooplankton in Eme River, Umuahia. Biodiversity Indices Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Taxa (S) 27 27 27 26 27 27 Individuals 563 619 577 498 511 614 Shannon-weiner (H) 3.241 3.276 3.250 3.192 3.178 3.212 Evenness (E) 0.9464 0.9806 0.9554 0.936 0.8885 0.9197 Margalef 4.105 4.045 4.089 4.025 4.169 4.050 Relationship between Zooplankton Groups and Environmental Variables The Canonical Correspondence Analysis (CCA) showed that water temperature, flow velocity and dissolved oxygen exerted a greater positive influence on the relative abundance of the zooplankton groups compared to the higher negative influence exerted by electrical conductivity, phosphate and turbidity (Fig. 3). Flow velocity exerted positive influence on copepod while Biochemical oxygen demand exerted negative influence on rotifer and cladocera. Spatially, dissolved oxygen exerted positive influence on stations 3 and 6 while electrical conductivity, phosphate and turbidity exerted negative influence in stations 1 and 4. Discussion Rivers are natural resources that offer a wide range of ecosystem services from drinking to water utilities in industry, agriculture, transportation and recreation [ 31 , 32 ]. Rivers need have a healthy ecosystem and a good water quality in order to provide these services. The surface water temperatures were within acceptable limits and were influenced by season and sampling times. The lowest value was recorded after an early rain in May 2018 while the highest was during the dry season in April 2018. Surface water temperatures are strongly influenced by air temperatures [ 33 ]. Dugdale et al [ 34 ] reported water temperature as a critical factor in biotic and abiotic processes; capable of affecting the amount of dissolved matter, organic/inorganic pollutants, nutrients, microbacterial concentrations, the behavior of fish and invertebrates in the aquatic environment. Flow velocity values were moderate though Stations 2 and 3 were significantly higher. The ability of a waterbody to assimilate and transport pollutants can be significantly affected by flow velocity [ 35 ]. It can also affect the composition, abundance and distribution of aquatic biota. Low algal population may be associated with high water velocity while algal population growth is stimulated by low velocity among other things [ 36 ]. This study was different; the highest phytoplankton and zooplankton abundance were recorded respectively in Stations 3 and 2 with high flow velocities but little or no human activities. CCA also showed that flow velocity was a strong negative factor especially in Station 3; increased river discharge and flow velocity, especially during the wet season, has been reported to be responsible for low species composition and abundance in rivers due to low time of residency [ 37 , 38 ]. The standard limit for turbidity was exceeded by some values recorded in all the stations especially between December 2017 and March 2018, which could be attributed to cumulative effect of receding flood and anthropogenic activities. Swimming by large number of children, bathing, washing and extraction of water for drinking were high during the dry season and affected turbidity in Station 1. However, Stations 4–6 had relatively higher values between May and November 2018; attributed to the effect of sand mining activities which increased with the rains [ 31 , 39 , 40 ]. This was more remarkable in Station 4 that was immediately downstream of sand mining and landing sites and steadily declined further downstream [ 41 , 42 ]. CCA also showed that turbidity had negative effect in station 4 for both phytoplankton and zooplankton. Aquatic lives are affected by high turbidity [ 43 , 44 ]. All the pH values did not comply with acceptable limit because of acidity. This is attributed to both geogenic [ 45 ] and anthropogenic influences [ 46 , 47 ]. Sand mining lowers the pH of water bodies [ 42 ]. Extremes of pH are unsuitable for most aquatic organisms. Kale [ 44 ] reported the extreme sensitivity of aquatic organisms to pH levels below 5 and death may arise at these low pH values. CCA showed a strong negative influence of pH on phytoplankton. The total dissolved solids (TDS) and electrical conductivity (EC) values of the water were moderate though downstream stations (4–6) were significantly higher than the upstream stations (1–3). This could be attributed to effects of sand mining activities. Sand mining activities can increase the levels of TDS and EC in surface water [ 46 , 48 ] and water pollution usually increase with increasing EC [ 49 ]. The TDS and EC values recorded in Station 1 were relatively higher compared to Stations 2 and 3; this could be attributed to perturbation from large number of children swimming during the dry season and allochthonous input from increased runoff during the wet season. The TDS levels recorded were below 600mg/l and cannot reduce light penetration to inhibit phytoplankton growth [ 50 ]. Most of the Dissolved Oxygen values were not up to the acceptable limit especially in station 4; which could be attributed to anthropogenic impact. Rao et al [ 51 ] reported that some consequences of sand mining activities like addition of nutrients, changing the flow of water, raising the water temperature and the addition of chemicals can contribute to oxygen depletion in water. Dissolved oxygen (DO) is one of the major parameters used in the determination of water quality [ 32 ] and the level is critical to support aquatic biodiversity. CCA showed that dissolved oxygen was one of the major positive factors influencing the zooplankton community. Dissolved oxygen levels > 5 mg/L is essential to support aquatic life and good fish production [ 52 ]. Biochemical Oxygen Demand (BOD) is an important parameter of water indicating the health and self-purification status of freshwater bodies. Some of the BOD values; especially in Stations 4–6 were higher than the acceptable limit. This could be attributed to sand mining activities. Akankali et al [ 46 ] observed that sand mining activities considerably enhance the release and circulation of organic matters from the sediments into the water column which can increase the BOD levels. High BOD level is a pointer to potential pollution problems because it is capable of adversely depleting dissolved oxygen to the detriment of aquatic biota [ 53 ]. Nitrate, a common form of nitrogen occurs naturally in many environments in moderate levels [ 54 ]. The nitrate values were all within acceptable limit though higher values were recorded in Stations 4–6; attributable to sand mining activities. In Okoro Nsit stream South-south Nigeria; subjected to intense sand mining activities, Akankali et al [ 46 ] recorded a range of 10.7 to 12.4 mg/l. The relatively higher values recorded in Station 1 compared to Stations 2 and 3 could be attributed to the effect of large number of children swimming during the dry season and rain during the wet season. Water with nitrate values higher than 5.0 mg/L is considered poor because naturally the range is often between 0.01 and 3.0 mg/L [ 55 ]. Nitrates have negative impact on the environment; noted for contamination of ground and surface waters due to its high solubility [ 54 ]. The nutrient levels and eutrophication of the river system can be identified by the concentrations of phosphate in the river [ 56 ]. Some of the phosphate values exceeded acceptable limit especially in Stations 4–6 and could be attributable to sand mining activities. Akankali et al [ 46 ] recorded a range of 2.5 to 3.6 mg/l in Okoro Nsit stream in Akwa Ibom State in Nigeria. Relatively higher values were also recorded in Station 1 attributed to perturbation from large number of children swimming during the dry season and increased allochthonous input during the wet season. Phosphate values are usually 0.005 to 0.020 mg/L in most natural surface waters; high concentrations can pollution and are mainly responsible for eutrophication [ 35 ]. Nutrients such as nitrogen and phosphates compounds in water stimulate the growth of algae and other photosynthetic aquatic life [ 57 ]. Biomonitoring provides for temporal integration of all impacts and allows the integrated analysis of different factors and their complex interactions in a reliable and cost-effective way. This is because aquatic organisms spend most part of their life under the specific conditions of the site [ 58 ]. Studies have documented the use of plankton as bioindicators of water quality [ 59 , 60 ]. The composition and abundance of phytoplankton and zooplankton of the water body is a clear indication of the health status of the water body [ 61 ]. The high phytoplankton abundance in this study could be attributed to nutrient enrichment and low zooplankton abundance. Lehman [ 62 ] reported that zooplankton are major recyclers of nitrogen and phosphorus which frequently limit phytoplankton growth rate, therefore low zooplankton abundance contribute to increased enrichment and phytoplankton development. The phytoplankton was dominated by Chlorophyceae followed by Bacillariophyceae as reported by Kshirsagar et al [ 63 ] and Bwala [ 64 ]. Chlorophyceae was also reported as the dominant in Odot Stream by Ekpo et al [ 65 ] while the dominance of Bacillariophyceae was reported in Ikpa River by Ekwu and Udo [ 38 ], Idumayo River by Nwonumara [ 66 ] both in Southeast Nigeria, River Kaduna in North Central Nigeria by Arimoro et al [ 9 ] and Orashi River, South-South Nigeria by Davies et al [ 67 ]. The growth and development of Chlorophyceae is controlled by parameters like transparency, water temperature, dissolved oxygen, pH and nutrients [ 68 , 69 , 70 ] while low level of DO and high BOD, nitrate and phosphate, favor the growth of diatoms [ 63 ]. High abundance of diatoms is attributed to high levels of silicates in the water, resulting from sand mining activities [ 38 ] and also suggests perturbation and organic pollution [ 67 ]. The composition of the phytoplankton was dominated cosmopolitan and pollution tolerant species [64, 66, 67, 71). The most abundant species were Melosira granulata and Planktosphaeria gelatinosa . Other common tolerant species include Anabaena affins (Cyanophyceae), Euglena candata, Phacus longicanda (Euglenophyceae), Amphoria ovaris, Synedra affins (Bacillariophyceae) and Pediastrum simplex (Chlorophyceae). Phytoplankton species have been used as indicators of organic pollution [ 66 , 72 , 73 ] Some of the taxa recorded like Euglena , Ceratium , Peridinium , Anabaena , Closterium , Scenedesmus and Pediastrum were indicative of eutrophic condition [ 72 ]. Spatially, stations 2 and 3 had the highest number of individuals despite their high velocities; this could be due to little or human activities in the stations [ 74 ]. Stations 1, 4–6 were significantly lower with station 1 being the lowest. Stations 4–6 were subjected to intense sand mining activities. Sand mining adversely affects both physical and biological environments, often extending beyond the mining sites [ 43 ]. Apart from constant agitation of the water, it increases turbidity levels and reduces light penetration which hinders the photosynthetic activity, productivity and growth of plankton [ 75 ]. The low abundance recorded in station 1 could be attributed to perturbation from large number of children swimming in the station. This was observed throughout the dry season sampling period, which also reflected in the levels of some physicochemical parameters. The effect of rains also could be responsible during the wet season. Plankton abundance usually decrease as the amount of rainfall increase; attributed to high turbidity and high flow velocity [ 9 , 66 , 72 ]. The composition of the zooplankton group was dominated by Rotifer followed by Cladocera, Protozoa and Copepod as observed by Kamboj and Kamboj [ 76 ] in the mining-impacted stretch of Ganga River, India. Rotifer was also reported as the dominant group in Ikpa and Odot Streams in South-South Nigeria that is subjected to intense sand mining [ 38 , 65 ]. Rotifers especially Keratella, Brachionus, Asplanchna and Notholca have been reported to dominate freshwater zooplankton in Nigeria [ 38 , 77 , 78 ]. Small size, parthenogenesis and rapid reproduction of rotifers under favourable conditions (nutrient-enriched water) could be responsible for their high abundance [ 79 ]. Other factors include their morphological variations and adaptations [ 80 ] as well as their diverse feeding habits [ 78 ]. Rotifers minimize competition through niche exploitation and food utilization because of their ability to migrate vertically, which could also be responsible for their dominance [ 65 ]. The relatively low zooplankton abundance could be attributed to anthropogenic and seasonal influences. The most abundant zooplankton species was Daphnia pulex (Cladocera). Daphnia pulex is the most common cladoceran found almost in all permanent and eutrophic freshwater environments [ 81 ]. The large body sizes of Daphnia makes it possible for them to graze on large quantities and diverse forms of phytoplankton; contributing to their predominance of among the cladocerans [ 78 ] and their composition and abundance is also dependent on food supply [ 81 ]. Spatially, little or no human activities was responsible for the high zooplankton abundance in Station 2 while sand mining activities was responsible the low abundance in Station 4. Station 6 showed signs of recovery after the impacts. Ko et al [ 82 ] reported a significant recovery in the number of species and individuals after dredging operations. High flow velocity could be responsible for the relatively lower abundance in Station 3. Plankton development is usually affected by flowing water because they are continually washed downstream [ 83 ]. Diversity indices have an important application in plankton studies especially in relation to assessment of pollution and waterbody productivity. The ShannonWeiner diversity indices for phytoplankton and zooplankton were all greater than 3 indicating ecosystem stability. Stations 2 and 3 were relatively higher for the phytoplankton while upstream stations (1–3) were relatively higher for the zooplankton. According to Wilm and Dorris [ 84 ], water bodies with algal ShannonWeiner diversity Index 3 for clean water and stable environment. Margalef indices were high for both phytoplankton and zooplankton. In aquatic community, It is generally accepted that species diversity and richness decrease when under stress conditions; though some tolerant species usually break out [ 85 ]. Evenness values were relatively higher in stations 2 and 3 in both phytoplankton and zooplankton indicating the effect of the anthropogenic activities in the other stations. Evenness index is an indication of whether all species are equally abundant in a sample [ 86 ]. This means that species evenness will decrease as the plankton population size increase. Among the phytoplankton, the evenness of Station 3 with more abundance was lower than that of Station 2. Conclusion Some of the physicochemical parameters showed that the river was perturbed by the anthropogenic activities in the watershed especially in the downstream stations where sand mining was intense. However, the plankton assemblage and community structure gave an indication of a stable environment; though the zooplankton fauna showed some level of stress from the anthropogenic activities. The presence of eutrophic indicators and tolerant species showed that the river was tending towards eutrophication. Sand mining activities contributed to the nutrient enrichment of the river. There is need to regulate illegal sand mining activities in the river. Abbreviations FMEnv Federal Ministry of Environment Declarations Acknowledgements Thanks to Mr. Emeka Nwachukwu for assistance with the sample collections, Mr. Emmanuel Irozuru for assisting in identification of the plankton samples and Mr. Chinedu Ogbodo for producing the study map. Authors’ contributions EDA and SNU designed the research. EDA and OGA conducted the field research, analyzed the data, and interpreted the results. All the authors contributed in writing the manuscript, reading and approving the final manuscript. Funding This research and publication is not funded by any agency. Availability of data and materials Please contact the corresponding author for data requests. Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. References Amah-Jerry EB, Anyanwu ED, Avoaja DA. Anthropogenic impacts on the water quality of Aba River, Southeast Nigeria. Ethiop J Environ Stud Manage. 2017;10(3):299–314. Doi: https://dx.doi.org/10.4314/ejesm.v10i3.3 Aliu OO, Akindele EO, Adeniyi IF. Biological assessment of the Headwater Rivers of Opa Reservoir, Ile-Ife, Nigeria, using ecological methods. J Basic Appl Zool. 2020;81:11. https://doi.org/10.1186/s41936-020-00151-5 Santos JM, Ferreira MT. Use of Aquatic Biota to Detect Ecological Changes in Freshwater: Current Status and Future Directions. Water. 2020;12:1611. Komala HP, Nanjundaswamy L, Devi Prasad AG. An assessment of Plankton diversity and abundance of Arkavathi River with reference to pollution. Adv Appl Sci Res. 2013;4 ( 2 ) :320–324. Sharma SK. An assessment of plankton diversity and climate change relationship in physico-chemical environment of Son River in Bhojpur area of Bihar, India. Res J Recent Sci. 2018;7 ( 2 ) :6–11. Ovie SI, Bwala R, Ajayi O. Preliminary study on Limnological stock assessment, productivity and potential fish yield of Omi dam, Nigeria. Afr J Environ Sci Tech. 2011;5(11):956–963. Suthers IM, Rissik D. (Eds). Plankton: A guide to their ecology and monitoring for water quality. Australia: CSIRO Publishing, Collingwood, Vic: 2009. Mathivanan V, Vijayan P, Sabhanayakam S, Jeyachitra O. An assessment of plankton population of Cauvery River with reference to pollution. J Environ Biol. 2007; 28(2):523–526. Arimoro FO, Olisa HE, Keke UN, Ayanwale AV, Chukwuemeka VI. Exploring spatio-temporal patterns of plankton diversity and community structure as correlates of water quality in a tropical stream. Acta Ecol Sin. 2018;38: 216–223 Striebel, M. Plankton Dynamics: the influence of light; nutrients and diversity. PhD Dissertation, Faculty of Biology, Ludwig Maximilians University, Munich, Germany. 2008;168pp. Conde D, Bonita S, Aubriot L, De Leon R, Pintos W. Relative contribution of planktonic and benthic microalgae production in a Eutrophic Coastal Lagoon of South America. J Limnol. 2007;78:207–212. Contreras JJ, Sarma SSS, Merino-Ibarra M, Nandini S. Seasonal changes in the rotifer (Rotifera) diversity from a tropical high altitude reservoir (Valle de Bravo, Mexico). J Environ Biol. 2009;30:191–195. Bellinger EG, Sigee PC. Freshwater algae: Identification and use as bioindicator. John Wiley and Sons, Ltd: 2010;40pp. Yusuf ZH. Phytoplankton as bioindicators of water quality in Nasarawa reservoir, Katsina State Nigeria. Acta Limnol Bra. 2020;32:e4. https://doi.org/10.1590/S2179-975X3319 Parmar TK, Rawtani D, Agrawal Y. Bioindicators: The natural indicator of environmental pollution. J. Frontiers Life Sci. 2016;9(11):110–118. Sousa W, Attayde JL, da Silva Rocha E, Eskinazi-Sant'Anna EM. The response of zooplankton assemblages to variations in the water quality of four man-made lakes in semi-arid northeastern Brazil. – J Plank Res. 2008;30:699–708. Sharma S, Siddique A, Singh K, Chouhan M, Vyas A, Solnki CM, Sharma D, Nair S, Sengupta T. Population dynamics and seasonal abundance of zooplankton community in Narmada River (India). Researcher. 2010;2(9):1–9. Schmidt J, Andrade PDB, Padial AA. Zooplankton trajectory before, during and after a hydropower dam construction. Acta Limnol Bra. 2020;32:e18. Primo A, Kimmel D, Marques S, Martinho F, Azeiteiro U, Pardal M. Zooplankton community responses to regional-scale weather variability: a synoptic climatology approach. Climate Res. 2015;62(3):189–198. Rajagopal T, Thangamani A, Sevarkodiyone S, Sekar M, Archunan G. Zooplankton diversity and physico-chemical conditions in three perennial ponds of Virudhunagar district, Tamilnadu. J Environ Biol. 2010;31(3):265–272. Pace ML, Orcutt JD. The relative importance of protozoans, rotifers, and crustaceans in a freshwater zooplankton community. Limnol Oceanogr. 1981;26(5):822–830. Hairston Jr NG, Hairston Sr N.G. Cause-effect relationships in energy flow, trophic structure, and interspecific interactions. Ame Naturalist.1993;142(3):379–411. Das P, Kar S, Das U, Bimola M, Kar D, Aditya G. Day time variations of zooplankton species composition: observations from the wetlands of Assam, India. Acta Limnol Bra. 2020;32:e10. https://doi.org/10.1590/S2179-975X1418 Gaygusuz Ö, Dorak Z. Species Composition and Diversity of the Zooplankton Fauna of Darlik Stream (İstanbul-Turkey) and its Tributaries. J Fisher Sci. 2013;7(4):329–343. Doi: 10.3153/jfscom.2013037 APHA. Standard Methods for the Analysis of Water and Wastewater, 23rd Edition. Washington D.C: American Public Health Association; 2012. Jeje CY, Fernando CH. A practical guide to the identification of Nigerian zooplankton. Kainji, Nigeria: Kainji Lake Research Institute Press; 1986. Janse van Vuuren S, Taylor J, Gerber A, van Ginkel C. Easy identification of the most common freshwater algae. A guide for the identification of microscopic algae in South African freshwaters. School of Environmental Sciences and Development: Botany, North-West University (Potchefstroom Campus), Potchefstroom 2520, South Africa; 2006. Dang PD, Khoi NV, Nga LN, Thanh DN, Hai HT. Identification Handbook of Freshwater Zooplankton of the Mekong River and its Tributaries. Vientiane: Mekong River Commission. 2015;207pp. Hammer ØH, Harper DAT, Ryan PD. Past: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontol Electron. 2001;4(1) art. 4: 9pp. FMEnv. National Environmental (Surface and Groundwater Quality Control) Regulations, S.I. No. 22 , Gazette No. 49, Vol. 98 of 24th May, 2011. Federal Ministry of Environment, Abuja, Nigeria; 2011. Anyanwu ED, Umeham SN. Identification of waterbody status in Nigeria using predictive index assessment tools: a case study of Eme River, Umuahia, Nigeria. Int J Energ Water Res. 2020;4:271–279. https://doi.org/10.1007/s42108-020-00066-5 Aydin H, Ustaoğlu F, Tepe Y, Soylu EN. Assessment of water quality of streams in northeast Turkey by water quality index and multiple statistical methods, Environ Forensics. 2021;22(1–2:270–287. Doi: 10.1080/15275922.2020.1836074 Park J, Kim K, Cho C, Kang M, Kim B. Spatio-temporal characteristics of air and water temperature change in the middle reach of the Nakdong River. J Environ Policy Admin. 2016;9:233–253. Dugdale SJ, Allen Curry R, St-Hilaire A, Andrews SN. Impact of future climate change on water temperature and thermal habitat for keystone fishes in the Lower Saint John River. Water Res Manage. 2018;32(15):4853–4878. Chapman D. (ed.). Water Quality Assessment. A Guide to the use of Biota, Sediments and Water in Environmental Monitoring (2nd Edition). Taylor and Francis: London and New York; 1996. Verma S, Tiwari D, Verma A. Algal Dynamics of River Pandu in Relation to Ambient Environment. ECOPRINT. 2013;20:9–17. Anyanwu ED, Ikomi RB, Arimoro FO. Water quality and zooplankton of the Ogba River, Benin City, Nigeria. Afr J Aquat Sci. 2013;38(2):193–199. Ekwu AO, Udo ND. Plankton Communities of Ikpa River, Southeast Nigeria Exposed to Sand-dredging Activities. J Fisher Aquat Sci. 2014;9(5):345–351. Peck Yen T, Rohasliney H. Status of Water Quality Subject to Sand Mining in the Kelantan River, Kelantan. Trop Life Sci Res. 2013;24 ( 1 ) :19–34. Anyanwu ED, Umeham SN. An index approach to heavy metal pollution assessment of Eme River, Umuahia, Nigeria. Sustain, Agri, Food Environ Res. 2020;8(X). http://dx.doi.org/10.7770/safer-V0N0-art2067 . Ashraf MA, Maah MJ, Yusoff I, Wajid A, Mahmood K. Sand mining effects, causes and concerns: A case study from Bestari Jaya, Selangor, Peninsular Malaysia. Sci Res Essays. 2011;6(6):1216–1231. Seiyaboh E, Ogamba EN, Utibe DI. Impact of Dredging on the water quality of Igbedi Creek, Upper Nun River, Niger Delta, Nigeria. IOSR J Environ Sci Toxicol Food Tech. 2013;7(5):51–56. Sheeba S. Biotic Environment and Sand Mining - A Case Study from Ithikkara River, South West Coast of India. J Ind Pollut Contr.2009;25(2):133–138. Kale VS. Consequence of Temperature, pH, Turbidity and Dissolved Oxygen Water Quality Parameters. Int Adv Res J Sci Engr Tech. 2016;3 ( 8 ) :186–190. Anyanwu ED, Emeka CS. Application of water quality index in the drinking water quality assessment of a southeastern Nigeria river. Food Environ Safe. 2019;XVIII(4):308–314. Akankali JA, Idongesit AS, Akpan PE. Effects of sand mining activities on water quality of Okoro Nsit stream, Nsit Atai Local Government Area, Akwa Ibom State, Nigeria. Int J Dev Sustain. 2017;6:451–462. Anyanwu ED, Ukaegbu AB. Index approach to water quality assessment of a south eastern Nigerian river. Int J Fisher Aquat Stud. 2019;7(1): 153–159. Rehman M, Yousuf AR, Balkhi MH, Rather MI, Shahi N, Meraj M, Hassan K. Dredging induced changes in zooplankton community and water quality in Dal Lake, Kashmir, India. Afr J Environ Sci Tech. 2016;10(5):141–149. Doi: 10.5897/AJEST2016.2096 Dorak Z. Zooplankton abundance in the lower Sakarya River Basin (Turkey): Impact of environmental variables. J Black Sea/Mediter Environ. 2013;19: 1–22. Ashiru OR, Adegbile MO, Ayeku PO. Assessment of the Effect of Anthropogenic Activities on Aquatic Life in Ugbo-Aiyetoro Water-way, Southwestern Nigeria. Int J Oceanogr Mar Ecol Sys. 2017;6:9–22. Rao AS, Marshall S, Gubbi J, Palaniswami M, Sinnott R, Pettigrove V. Design of Low-Cost Autonomous Water Quality Monitoring System. International Conference on Advances in Computing, Communications and Informatics (ICACCI), Mysore, 22–25, August 2013;14–19. Bhatnagar A, Jana SN, Garg SK, Patra BC, Singh G, Barman UK. Water quality management in Aquaculture. In: Course manual of Summer School on Development of sustainable Aquaculture technology in fresh and saline water. CS Hagyana Agricultural Hisar (India). 2004;203–210. Al-Sulaiman AM, Khudair BH. Correlation between BOD5 and COD for Al-Diwaniyah Wastewater Treatment Plants to obtain the Biodigrability Indices. Pak J Biotech. 2018;15(2):423–427. Patel RK. Nitrates-its generation and impact on environment from mines: A Review. National Conference on Sustainable Mining Practice, 2–3, December 2016, India. 2016. Lehigh Environmental Initiative (n.d). Nitrates. Enviro Sci Inquiry. http://www.ei.lehigh.edu/envirosci/watershed/wq/wqbackground/nitratesbg.html . Christensen VG, Lee KE, McLees JM, Niemela SL. Relations between retired agricultural land, water quality, and aquatic-community health, Minnesota River basin. J Environ Quality. 2011;41:1459–1472. Dubey VK, Sarkar UK, Kumar RS, Mir JI, Pandey A, Lakra WS. Length-weight relationships (LWRs) of 12 Indian freshwater fish species from an un-impacted tropical river of Central India (River Ken). J Appl Ichthyol. 2012;28, 854–856. Valdecasas AG, Baltanás A. Jacknife and bootstrap estimation of biological index of water quality. Water Res. 1990;24:1279–1283. Vaidya SR. Use of zooplankton as bioindicators for the management of aquatic diversity: A review. Int J Biol Res. 2017;2 ( 1 ) :14–15. Igwe DO, Igboji PO, Mbagwu GI. Use of Plankton as Bioindicators in Water Quality Management for Sustainable Use in Fishery Production: A Review. Elixir Agri. 2019;134:53593–53597. Kutama RM, Abubakar MM, Balarabe ML. The Plankton as Indicators of Water Quality in Kusalla Reservoir: A Shallow Man Made Lake. IOSR J Pharm Biol Sci. 2014;9(3):12–15. Lehman JT. Release and cycling of nutrients between planktonic algae and herbivores. Limnol Oceanogr. 1980;25:620–632. Kshirsagar AD, Ahire ML, Gunale VR. Phytoplankton Diversity Related to Pollution from Mula River at Pune City. Terrest Aquat Environ Toxicol. 2012;6(2):136–142 Bwala MN. The Abundance of Phytoplankton In River Nggada and River Ngadda-Bul, Maiduguri Metropolis, Borno State, Nigeria. Global Edu Res J. 2019;7(7):820–829. Ekpo IE, Essien-Ibok MA, Duncan AO. Densities, spatial distribution and community structure of plankton of Odot Stream. J Ecol Nat Environ. 2015;7(6):180–187. Nwonumara GN. Water Quality and Phytoplankton as Indicators of Pollution in a Tropical River. Proceedings of 6th NSCB Biodiversity Conference, Uniuyo 2018; 83– 89. Davies OA, Otene BB, Amachree D, Nwose FA. Phytoplankton Community of Upper Reaches of Orashi River, Rivers State, Nigeria. Specialty J Biol Sci. 2019;5(3):1–12. Rajagopal T, Thangamani A, Archunan G. Comparison of physico-chemical parameters and phytoplankton species diversity of two perennial ponds in Sattur area, Tamil Nadu. J Environ Biol. 2010;31:787–794. Rao GMN, Pragada PM. Seasonal abundance of micro algae in Pandi Back waters of Godavari Estuary, Andra Pradesh, India. Not Sci Biol. 2010;2:26–29. Verma P, Gupta UC, Adiyecha PR, Solanki HA. Seasonal variation in the phytoplankton biodiversity of Chandlodia lake. Int J Inno Res Sci Engr Tech. 2014;3(1):1–6. Palmer CM. A composite rating of algae tolerating organic pollution. J Phycol. 1969;5: 78–82. Okogwu OI, Ugwumba AO. Seasonal dynamics of phytoplankton in two tropical rivers of varying size and human impact in Southeast Nigeria. Rev Biol Trop. 2103;61 (4):1827–1840 Salem Z, Ghobara M, El Nahrawy AA. 2017. Spatio-temporal evaluation of the surface water quality in the middle Nile Delta using Palmer’s algal pollution index. Egypt J Basic Appl Sci. 2017;4:219–226. http://dx.doi.org/10.1016/j.ejbas.2017.05.003 Arimoro FO, Oganah AO. Zooplankton community responses in a perturbed tropical stream in Niger Delta, Nigeria. Open Environ Biol Monit J. 2010;3:1–11. Tanimu Y, Bako SP, Adakole JA, Tanimu, J. Phytoplankton as bioindicators of water quality in Saminaka reservoir, Northern Nigeria. In: International Symposium on Environmental Science and Technology. Dongguan, Guangdong Province, China; Environmental Science and Technology. 2011;83–87. Kamboj V, Kamboj N. Spatial and temporal variation of zooplankton assemblage in the mining-impacted stretch of Ganga River, Uttarakhand, India. Environ Sci Pollut Res. 2020;27:27135–27146 Akin-Oriola GA. Zooplankton Association and Environmental Factors in Ogunpa and Ona Rivers, Nigeria. Rev Biol Trop. 2003;51(2):391–398. Mustapha MK. Zooplankton assemblage of Oyun Reservoir, Offa, Nigeria Rev Biol Trop. 2009;57(4):1027–1047. Levine SN, Borchardt MA, Braner M, Shambaugh AD. The Impact of Zooplankton Grazing on Phytoplankton Species Composition and Biomass in Lake Champlain (USA-Canada). J. Great Lakes Res. 1999;25(1):61–77 Wetzel RG. Limnology: Lake and River Ecosystems (3rd ed.) San Diego, C.A.: Academic Press. 2001. Miller C. Daphnia pulex (On-line), Animal Diversity Web. Accessed February 04, 2021 at https://animaldiversity.org/accounts/Daphnia_pulex/ . 2000. Ko EJ, Kim D-K, Jung E-S, Heo Y-J, Joo, G-J, Kim, H-W. Comparison of Zooplankton Community Patterns in Relation to Sediment Disturbances by Dredging in the Guemho River, Korea. Water. 2020;12: 3434. Doi: 10.3390/w12123434 Redden AM, Kobayashi T, Suthers I, Bowling L, Rissik D, Newton G. Chapter 2: Plankton processes and the environment. In: Suthers IM, Rissik D. (Eds). Plankton: A guide to their ecology and monitoring for water quality . CSIRO Publishing, Collingwood, Vic, Australia. 2009;15–38 Wilm JL, Dorris TC. Species diversity of benthic macroinvertebrates in a stream receiving domestic and oil refinery effluents. In: Islam SM. Phytoplankton diversity index with reference to mucalinda serovar Bodh-Gaya, 12th World Lake Conference. Taal, India. Ame Midland Naturalist. 2007;427–449. Xu MQ, Cao H, Xie P, Deng DG, Feng WS, Xu J. The temporal and spatial distribution, composition and abundance of planktonic protozoa, with special relation to eutrophication in the Chaohu Lake, China. Eur J Protistol. 2005;41:183–192. Kaparapu J, Geddada MNR. Seasonal Distribution of Phytoplankton in Riwada Reservoir, Visakhapatnam, Andhra Pradesh, India. Not Sci Biol. 2013;5(3):290–295 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-281949","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":14791583,"identity":"75e051e1-1d3f-40dc-b194-1663cb497ec5","order_by":0,"name":"Emeka Donald Anyanwu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYDACHgYGCQYGGzBJkpY00rUcJkELP8/hhzc+7jif2D+7+eADhhqbaIJaJHvbjC1nnrmdOOPOsWQDhmNpuQ2EtBicZzCT5m27ndhwI8dMgrHhMGEt9ufZvwG1nEucT7QWA94ekC0HEjcQrUXizJliy5ltycYbb6QlGyQQ4xf+nvSNNz622cnOu5F88MGHGhvCWmDAEawygVjlIGBPiuJRMApGwSgYYQAAFaNAz0wdJRsAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-8593-6865","institution":"Michael Okpara University of Agriculture","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Emeka","middleName":"Donald","lastName":"Anyanwu","suffix":""},{"id":14791584,"identity":"fa16d782-9829-4bf3-9699-ba42abd18686","order_by":1,"name":"Onyinyechi Gladys Adetunji","email":"","orcid":"","institution":"Michael Okpara University of Agriculture","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Onyinyechi","middleName":"Gladys","lastName":"Adetunji","suffix":""},{"id":14791585,"identity":"b962f31f-29b4-4498-a244-1a26325b4ae8","order_by":2,"name":"Solomon Nnanna Umeham","email":"","orcid":"","institution":"Abia State University Faculty of Biological and Physical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Solomon","middleName":"Nnanna","lastName":"Umeham","suffix":""}],"badges":[],"createdAt":"2021-02-27 05:51:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-281949/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-281949/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":6871472,"identity":"166bbf41-bded-4ee3-8056-e3bbed3bae5e","added_by":"auto","created_at":"2021-03-12 00:36:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":398268,"visible":true,"origin":"","legend":"Map of Umuahia, Abia State, Nigeria showing the sampling Stations of Eme River","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-281949/v1/ed887167107857877395eec7.png"},{"id":6871271,"identity":"28ccd652-b57e-4b20-9450-8feb374dc647","added_by":"auto","created_at":"2021-03-12 00:33:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53844,"visible":true,"origin":"","legend":"Canonical correspondence analysis (CCA) ordination showing relationships between phytoplankton groups, stations and environmental variables. (BOD – biochemical oxygen demand, DO - dissolved oxygen, Turb - turbidity, Temp - water temperature, NO3 – nitrates, PO4 - phosphates, EC – electrical conductivity, FVel – flow velocity, CYA – cyanophyceae, BAC – bacillariophyceae, CHL – chlorophyceae, EUG – euglenophyceae and PYR – Pyrrophyceae)","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-281949/v1/9d80b0ebee429d9f21ffb8ce.png"},{"id":6871473,"identity":"ec5096d6-5317-4431-9cf8-db4a14950c8d","added_by":"auto","created_at":"2021-03-12 00:36:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54240,"visible":true,"origin":"","legend":"Canonical correspondence analysis (CCA) ordination showing relationships between phytoplankton groups, stations and environmental variables. (BOD – biochemical oxygen demand, DO - dissolved oxygen, Turb - turbidity, Temp - water temperature, NO3 – nitrates, PO4 - phosphates, EC – electrical conductivity, FVel – flow velocity, ROT – rotifer, COP – copepod, CLA – cladocera and PRO – protozoa)","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-281949/v1/4cb67381aae22f95a66e4809.png"},{"id":13946985,"identity":"ac3b20bb-5c89-48b7-94d7-fd88092c5653","added_by":"auto","created_at":"2021-09-24 12:39:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1079079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-281949/v1/0eb32fdf-bc39-4350-9c3c-6d5874946aba.pdf"}],"financialInterests":"","formattedTitle":"Water Quality and Plankton Assessment of Eme River, Umuahia, Southeast Nigeria","fulltext":[{"header":"Introduction","content":" \u003cp\u003eRivers support diverse and large number of flora and fauna; making some of them the most productive ecosystems on the earth and biodiversity hotspots. Freshwater bodies across the world are subjected to intense human activities which has degraded the quality and utility of the water [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Researchers have predicted the quality of the aquatic ecosystem and ecological effects of human activities by the assessment of its biological communities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Planktons are one of the essential biological communities found in lotic freshwater ecosystems [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Regular monitoring of planktons is the cheapest and easy method of assessing the quality of water in developing countries [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Planktons (phytoplankton and zooplankton) are essentially microscopic, non-motile or weak swimming organisms floating in the water column and drift with it; making them susceptible to changes in the water [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMathivanan et al [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] reported that due the sensitivity of planktons to their environments, changes in the environment will affect the tolerance, abundance, diversity and dominance of the plankton communities in the habitat. They are highly sensitive to fluctuations in nutrient levels, temperature, pollution, levels of light and increase in predation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Plankton directly or indirectly controls all the secondary productions in the aquatic ecosystems [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to Bellinger and Sigee [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], phytoplankton are the micro-plant organisms without distinct roots, stems and leaves. The phytoplankton community plays a key role in aquatic ecosystems as bioindicators and primary producers; providing for carbon fixation, oxygen and food production [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Phytoplankton species are able to survive and develop in diverse aquatic habitats but each species is restricted to a defined niche based on their physiological requirements and environmental limitations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eZooplankton are microscopic animals that are essential components of aquatic food webs; an important link in the conversion of energy from producers to consumers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Schmidt et al [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] described zooplankton as a key biological group that is very important to the functioning of the ecosystem. They respond strongly to environmental changes and are used to assess the conditions in aquatic ecosystems [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Temporal and spatial variations of physico-chemical environmental conditions often result in dramatic and rapid changes in zooplankton because of their short life span and fast regeneration [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe trophic transfer efficiencies from phytoplankton to zooplankton and from zooplankton to fish are largely dependent on the taxa of zooplankton available in an aquatic ecosystem [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The composition of macroinvertebrate predator and fish species can be influenced by the pattern of changes in the zooplankton species composition within the same space [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In aquatic ecosystems, decline in zooplankton diversity will ultimately affect higher trophic levels; resulting in loss of species, habitat or even ecosystems and ecosystem services, if the trend was not abated [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Eme River was subjected to a number of anthropogenic activities, of which illegal and indiscriminate sand mining was the major one. The objective of this study was therefore to assess the water quality and plankton diversity in relation to anthropogenic activities.\u003c/p\u003e "},{"header":"Study Area","content":"\u003cp\u003eEme River took its source from Uzoakoli in Abia State, Nigeria; flowing through many communities before discharging into Imo River at Onuimo. The section of Eme River studied was between Ofeme and Umudiawa across the Port Harcourt - Enugu expressway in Umuahia, Abia State; about 3.25km in length (Fig. 1). It lies between latitude 5\u0026deg;38\u0026rsquo; and 5\u0026deg;37\u0026rsquo;N and Longitude 7\u0026deg;25\u0026rsquo; and 7\u0026deg;26\u0026rsquo;E. The study area falls within the sub-equatorial zone with mean annual rainfall of about 4000mm per annum. It is characterized by high relative humidity of over 70% and high temperature of about 29-31\u003csup\u003eo\u003c/sup\u003eC. It is also characterized by two seasons - wet (June to November) and dry (December to May) and double maxima rainfall peaks in July and September with a short period of dryness between the peaks known as the August break. The river was divided into six stations, which were within the dredged section except station 1. Station 1, located within Ofeme community at Mbato, was upstream and the control station. The major human activities observed were including laundry and extraction of drinking water in the dry season. Large number of children was also observed swimming during the dry season up to early rains because easy accessibility and low water depths. The substrate is muddy. Station 2, located on the out sketch at Eme - Ihite, about 1.84km downstream of Station 1. It was a less active sand mining site and minimal laundry, swimming and extraction of drinking water were observed during the dry season. The substrate is mixture of sand and stones. Station 3, also located in Eme - Ihite, by the expressway, about 419.67m downstream of Station 2. No activities were observed except periodic boat movements. The substrate is made up of large clayey boulders. Station 4, located in Umudiawa Community across the expressway, about 490.26m downstream of Station 3. It was also downstream to an intensive sand mining and two sand landing sites. The substrate was sandy. Station 5, within Umudiawa Community was about 200.22m downstream of Station 4. The substrate was sandy and sand mining activities was also observed. Station 6, within Umudiawa Community was about 300.14m downstream of Station 5. The substrate was sandy and sand mining activities occur within the water channel and around the shores.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSamples collection and analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWater Samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWater samples were collected from Eme River, Umuahia, monthly between December 2017 and November 2018. The samples were collected with 1-litre water sampler, stored in sterilized 1litre plastic bottles and then taken to the laboratory for analysis. Some physicochemical parameters (Water Temperature, Flow Velocity, Turbidity, pH, Electrical Conductivity and Total Dissolved Solids) were determined \u003cem\u003ein-situ\u003c/em\u003e while Dissolved Oxygen, Biochemical Oxygen Demand, Nitrate and Phosphate were determined in the laboratory using standards methods described by American Public Health Association (APHA) [25].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlankton Samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlankton samples were collected from undisturbed areas of the River as the water samples. The sampling was carried out using the quantitative method. A composite sample of 100 litres of water was filtered through 55um Hydro-Bios plankton net (with the aid of a 10 litres of bucket drawn 10 times at each station). The net content was washed out into plankton bottles of 250ml size and preserved in 4% formalin solution after a proper labelling. In the laboratory, one ml of the preserved sample was taken as a sub sample using a pipette. The collected sample was put on the Sedgwick-rafter counting chamber and viewed under a light binocular microscope (Nikon 400 binocular microscope) using a low magnification of x10. Planktons were sorted into different groups and the cells per ml were counted. Identification work was done using key literatures by Jeje and Fernando [26]; Janse van Vuuren et al [27] and Dang et al [28]. The identification was made to lowest practicable taxonomic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were summarised using Descriptive Statistic Package of Microsoft Excel while one-way ANOVA was used to test for statistical differences among the stations and Tukey\u0026rsquo;s pairwise comparisons test was performed to determine the location of significant difference (P\u0026lt;0.05). The community structures of the plankton were determined using Margalef (D), Shannon-weiner (H) Evenness (E) indices. Canonical correspondence analysis (CCA) was used to evaluate relationships between the plankton groups and environmental variables with PAST statistical package [29].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003cp\u003e\u003cstrong\u003eWater Quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAspects of the physicochemical parameters of Eme River are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Surface water temperature ranged from 22.0\u003csup\u003eo\u003c/sup\u003eC to 28.5\u003csup\u003eo\u003c/sup\u003eC. The lowest value was recorded in station 1 in May 2018 while the highest was recorded in station 6 in April 2018. The temperature values were within acceptable limits. Flow velocity values were moderate; ranging between 0.21 and 0.85 m/s. The lowest flow velocity was recorded in station 1 in April 2018 while the highest was recorded in station 3 in December 2017. Stations 2 and 3 were significantly higher (F\u0026thinsp;=\u0026thinsp;31.59; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than the other stations. Turbidity ranged between 0.5 and 9.4 NTU. The lowest and highest values were recorded in station 4 in March and February 2018 respectively. Stations 4\u0026ndash;6 recorded relatively higher turbidity values especially between May and October, 2018. Some of the values exceeded the 5 NTU limit set by FMEnv [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e] in all the stations. All the pH values recorded were acidic and lower than the acceptable limit (6.5\u0026ndash;8.5); ranging from 4.3 to 6.3. The lowest pH was recorded in station 2 in June 2018 while the highest value was recorded in station 1 in September 2018. The electrical conductivity (EC) values ranged between 45.2 and 168.4 \u0026micro;S/cm. The lowest and values highest were recorded in stations 2 and 5 in March and January 2018 respectively. The downstream stations (4\u0026ndash;6) were significantly higher (F\u0026thinsp;=\u0026thinsp;29.59; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) than the upstream stations (1\u0026ndash;3). The dissolved oxygen (DO) values ranged from 1.6 to 6.1 mg/L; all the DO values except two were below the acceptable limit (\u0026gt;\u0026thinsp;6mg/L) set by FMEnv [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. The lowest value was recorded in station 4 in November 2018 while highest was recorded in stations 3 (January 2018) and 4 (February 2018). Biochemical oxygen demand (BOD) values ranged between 0.8 and 4.3 mg/L. The lowest and highest values were recorded in November 2018 and February 2018 respectively in station 4. Some of the values exceeded the acceptable limit (3 mg/L) especially in Stations 4\u0026ndash;6. Station 4 was significantly higher than stations 2 and 3 (F\u0026thinsp;=\u0026thinsp;3.43; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Nitrate values were all within acceptable limit and ranged from 1.1 to 5.6 mg/L; though station 4 was significantly (F\u0026thinsp;=\u0026thinsp;14.62; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher than the other stations. The lowest value was recorded in station 3 (June 2018) while the highest was recorded in station 4 (February 2018). Phosphate values ranged between 0.4 and 4.6 mg/L. The lowest value was recorded in station 3 (June and July 2018) while the highest was recorded in station 4 (September 2018). Stations 4\u0026ndash;6 recorded values that exceeded the acceptable limit and were significantly different (F\u0026thinsp;=\u0026thinsp;56.71; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) from stations 1\u0026ndash;3.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" style=\"height: 817px;\" border=\"1\" width=\"836\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSummary of Physico-chemical Parameters of Eme River, Umuahia, Abia State.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003eStn 1\u003c/p\u003e\n\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eStn 2\u003c/p\u003e\n\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eStn 3\u003c/p\u003e\n\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003eStn 4\u003c/p\u003e\n\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003eStn 5\u003c/p\u003e\n\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003eStn 6\u003c/p\u003e\n\u003cp\u003eX\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eFMEnv.\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eWater Temperature (\u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e\n\u003cp\u003e(22.0\u0026ndash;28.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e24.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\n\u003cp\u003e(22.5\u0026ndash;28.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\n\u003cp\u003e(23.0-28.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e24.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e\n\u003cp\u003e(23.2\u0026ndash;28.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\n\u003cp\u003e(23.0-28.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\n\u003cp\u003e(22.9\u0026ndash;28.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eTurbidity ( NTU)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e\n\u003cp\u003e(1.5\u0026ndash;9.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e\n\u003cp\u003e(1.3\u0026ndash;8.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n\u003cp\u003e(0.6\u0026ndash;5.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n\u003cp\u003e(0.5\u0026ndash;9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e\n\u003cp\u003e(0.7\u0026ndash;7.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\n\u003cp\u003e(0.9\u0026ndash;6.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eFlow Velocity (m/s)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.21\u0026ndash;0.49)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.37\u0026ndash;0.80)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.63\u0026ndash;0.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.24\u0026ndash;0.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.28\u0026ndash;0.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.26\u0026ndash;0.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003epH\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e5.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\n\u003cp\u003e(5.0\u0026ndash;6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e5.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\n\u003cp\u003e(4.3\u0026ndash;5.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e5.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n\u003cp\u003e(4.9\u0026ndash;6.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n\u003cp\u003e(5.0\u0026ndash;6.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e5.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n\u003cp\u003e(5.1\u0026ndash;6.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e5.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\n\u003cp\u003e(5.1\u0026ndash;6.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e6.5\u0026ndash;8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eElectrical Conductivity (\u0026micro;S/cm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e86.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.40\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(55.6-115.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e71.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(45.2\u0026ndash;95.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e65.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(49.6\u0026ndash;88.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e130.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.86\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(90.3-160.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e115.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(88.5-168.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e119.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(87.1-148.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eTotal Dissolved Solids (Mg/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(27.5\u0026ndash;56.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(22.6\u0026ndash;47.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(24.8\u0026ndash;46.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e65.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(46.9\u0026ndash;80.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e57.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(44.7\u0026ndash;85.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e60.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.69\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(43.2\u0026ndash;74.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eDissolved Oxygen (Mg/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\n\u003cp\u003e(2.3\u0026ndash;5.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 76px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\n\u003cp\u003e(2.2\u0026ndash;5.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 77px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\n\u003cp\u003e(1.8\u0026ndash;6.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e3.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n\u003cp\u003e(1.6\u0026ndash;6.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\n\u003cp\u003e(2.0-5.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e\n\u003cp\u003e(1.8\u0026ndash;5.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eBiochemical Oxygen\u003c/p\u003e\n\u003cp\u003eDemand (Mg/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.0-2.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 69px;\" align=\"left\"\u003e\n\u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.1\u0026ndash;1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 6px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 72px;\" align=\"left\"\u003e\n\u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.1\u0026ndash;2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003eac\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.8\u0026ndash;4.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.0-3.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.9\u0026ndash;3.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003eNitrate (Mg/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.8\u0026ndash;4.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 69px;\" align=\"left\"\u003e\n\u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.3\u0026ndash;3.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 6px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 72px;\" align=\"left\"\u003e\n\u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.1\u0026ndash;2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(3.4\u0026ndash;5.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.2\u0026ndash;5.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.9\u0026ndash;5.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e9.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 188px;\" align=\"left\"\u003e\n\u003cp\u003ePhosphate (Mg/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 78px;\" align=\"left\"\u003e\n\u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.0-1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 69px;\" align=\"left\"\u003e\n\u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.5\u0026ndash;1.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 6px;\" colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"width: 72px;\" align=\"left\"\u003e\n\u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(0.4\u0026ndash;1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(2.8\u0026ndash;4.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(1.9\u0026ndash;4.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 85px;\" align=\"left\"\u003e\n\u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(2.0-4.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 52px;\" align=\"left\"\u003e\n\u003cp\u003e3.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 826px;\" colspan=\"11\"\u003e\u003cstrong\u003ea, b, c, d, e\u0026thinsp;=\u0026thinsp;Means with different superscripts across the rows are significantly different at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; SEM\u0026thinsp;=\u0026thinsp;Standard Error of Mean; FMEnv. National Environmental (Surface and Groundwater Quality Control) Regulations (2011).\u003c/strong\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlankton composition, abundance and distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhytoplankton\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe species composition of phytoplankton in the stations of Eme River, Umuahia was presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. A total of 5213 phytoplankton individuals were recorded, out of which the most abundant group was Chlorophyceae (1776 or 34.1%), followed by Bacillariophyceae (1234 or 23.7%). Other phytoplankton taxa recorded were Cyanophyceae (838 or 16.1%), Euglenophyceae (835 or 16.0%) and Pyrrophyceae (530 or 10.2%). One-way ANOVA showed that Cyanophyceae, Euglenophyceae and Pyrrophyceae were significantly (F\u0026thinsp;=\u0026thinsp;18.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) lower than Chlorophyceae and Bacillariophyceae in terms of abundance. Spatially, station 3 recorded the most abundant individuals (1108 individuals/L or 21.3%), followed by station 2 (1007 individuals/L or 19.3%) while station 1 (748 individuals/L or 14.3%) was the least. One-way ANOVA showed that stations 2 and 3 were significantly (F\u0026thinsp;=\u0026thinsp;10.3, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) higher than stations 1, 4\u0026ndash;6 in terms of abundance. The most abundant phytoplankton species recorded was \u003cem\u003eMelosira granulata\u003c/em\u003e (Bacillariophyceae) with 190 individuals (3.64 % of the total phytoplankton abundance), followed by \u003cem\u003ePlanktosphaeria gelatinosa\u003c/em\u003e (Chlorophyceae) with 180 individuals/L (3.45% of the total phytoplankton abundance) and the least was \u003cem\u003ePeridinium depressum\u003c/em\u003e (Pyrophyceae) with 101 individuals/L (1.94% of the total phytoplankton abundance).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSpecies composition, abundance and distribution of phytoplankton in Eme River, Umuahia, Nigeria.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTaxa\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 6\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRA (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCyanophyceae\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAnabaena affins\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e170\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eA. spiroides\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.55\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eOscilatoria laccustris\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e151\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSpirulina substilissinia\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.40\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eMicrocystis weswenbergii\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.55\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eCoelosphaerium pallidum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.41\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEuglenophyceae\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eEuglena candata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e157\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.01\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eE. acus\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.59\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eE. proxima\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ePhacus longicanda\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e159\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.05\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP. caudata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.42\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTrachelomonas aramata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.40\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBacillariophyceae\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAmphoria ovaris\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e161\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.09\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eMelosira granulata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e190\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eM varians\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.51\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSynedra acus\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e134\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.57\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eS. ulna\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e151\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eS. affins\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.38\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eCyclotella glomerata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e146\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.80\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTragilaria crotonesis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChlorophyceae\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ePediastrum clathratum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP. simplex\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e160\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP. dublex\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eClosterium moniliferum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e153\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eC. parvulum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e140\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.69\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eC. macilentum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eCosmarium amoerum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eMougeotia scalaris\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e146\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.80\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eVolvox aureus\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e154\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eChlamydomonas Atactogam\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e143\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.74\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ePlanktosphaeria Gelatinosa\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e180\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.45\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eScenedesmus quardriacauda\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e153\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePyrophyceae\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eCeratium candelabum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e147\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eC. hirudenella\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ePeridinium depressum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e101\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.94\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP. latum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e137\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.63\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e748\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1007\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1108\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e781\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e783\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e786\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e5213\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhytoplankton Community Structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe number of taxa (species) recorded were 36 in all the station except station 6 with 35 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The number of individuals ranged from 748 (station 1) to 1108 (station 3). Shannon-weiner diversity index (H) varied from 3.477 (station 1) to 3.562 (station 2). Margalef Species Richness, on the hand was highest in station 1 (5.289) and station 3 had the least (4.993).The Evenness Index (E) was highest in station 2 (0.9785) and least in station 1 (0.8987).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCommunity Structure of Phytoplankton in Eme River, Umuahia, Nigeria.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBiodiversity Indices\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation\u003c/p\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation\u003c/p\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation\u003c/p\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation\u003c/p\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation\u003c/p\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation\u003c/p\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaxa (S)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndividuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e748\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1007\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1108\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e781\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e783\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e786\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShannon-Weiner (H)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.477\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.562\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.557\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.514\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.526\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.490\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEvenness (E)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8987\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9785\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9740\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9327\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9441\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9371\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMargalef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.289\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.062\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.993\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.255\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.253\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.100\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between Phytoplankton Groups and Environmental Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Canonical Correspondence Analysis (CCA) showed that electrical conductivity and phosphate exerted a greater positive influence on the relative abundance of the phytoplankton groups compared to the higher negative influence exerted by pH and temperature (Fig. 2). Biochemical oxygen demand, electrical conductivity and phosphate exerted positive influence on cyanophyceae and flow velocity on euglenophyceae and chlorophyceae. On the other hand, turbidity and nitrate exerted negative influence on bacillariophyceae and temperature on Pyrrophyceae. Spatially, pH and flow velocity exerted negative influence respectively in stations 1 and 3 while turbidity and nitrate exerted negative influence in station 4.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZooplankton\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall species composition, abundance and distribution of zooplankton in the stations of Eme River, Umuahia are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. A total of 3382 zooplankton individuals were recorded in this study. Of these, the most abundant group was Rotifer (1064 individuals/L or 31.5%) followed by Cladocera (961 individuals/L or 28.4%), Protozoa (741 individuals/L or 21.9%) and Copepod (616 individuals/L or 18.2%). Spatially, Station 2 recorded the most abundant individuals (619 individuals/L or 18.3%), followed by Station 6 (614 individuals/L or 18.2%), Station 3 (577 individuals/L or 17.1%), Station 5 (511 individuals/L or 15.1%) and station 4 (498 individuals/L or 14.7%). The most abundant zooplankton recorded was \u003cem\u003eDaphnia pulex\u003c/em\u003e (Cladocera) with175 individuals/L (5.17% of the total zooplankton abundance).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSpecies composition, abundance and distribution of phytoplankton in Eme River, Umuahia, Nigeria.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTaxa\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 6\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRA (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCopepoda\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eCampthocamptus staphylinus\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.08\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eEucyclops speratus\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e144\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eMicrocyclops varicans\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.49\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSinodiatomus sarsi\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eMesochra suifunensis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e128\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.78\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCladocera\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAlona affins\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.84\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eDaphnia longis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e134\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.96\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eD. pulex\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e175\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.17\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eD. magna\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eMoina dubia\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e166\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.91\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eM. micrura\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e108\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.19\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eDiaphanosoma Brachyurum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.22\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRotifera\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eKeratella cochlearis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.08\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eBrachionus capsuliflorus\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e141\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.17\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAsplanchna priodontra\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e151\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eNotholca labis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.87\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSynchaeta pectinata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.49\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eConochilus umcormis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e128\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.79\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAscomorpha ecaudis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e127\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.76\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eB. plicatilis\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e130\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.84\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProtozoa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eParamecium candatum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eDifflugia candatum\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eDidinium bolbanic\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e103\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.05\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTintinnopsis lacustris\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.67\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAmoeba radiosa\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.57\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eVorticella radians\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e141\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.17\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eArcella nitrata\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.60\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e563\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e619\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e577\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e498\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e511\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e614\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e3382\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZooplankton Community Structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe number of taxa (species) recorded were 27 in all the station except station 4 with 26 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). The number of individuals ranged from 498 (station 4) to 619 (station 2). Shannon-weiner diversity index (H) varied from 3.178 (station 5) to 3.276 (station 2). Margalef Species Richness, on the hand was highest in station 5 (4.169) and station 4 had the least (4.025).The Evenness Index (E) was highest in station 2 (0.9806) and least in station 5 (0.8885).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCommunity Structure of Zooplankton in Eme River, Umuahia.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBiodiversity Indices\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStation 6\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaxa (S)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndividuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e563\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e619\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e577\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e498\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e511\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e614\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShannon-weiner (H)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.241\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.276\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.250\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.192\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.178\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.212\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEvenness (E)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9464\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9806\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9554\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.936\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8885\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9197\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMargalef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.045\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.089\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.025\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.169\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.050\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between Zooplankton Groups and Environmental Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Canonical Correspondence Analysis (CCA) showed that water temperature, flow velocity and dissolved oxygen exerted a greater positive influence on the relative abundance of the zooplankton groups compared to the higher negative\u0026nbsp; influence exerted by electrical \u0026nbsp;conductivity, phosphate and turbidity (Fig. 3). Flow velocity exerted positive influence on copepod while Biochemical oxygen demand exerted negative influence on rotifer and cladocera. Spatially, dissolved oxygen exerted positive influence on stations 3 and 6 while electrical conductivity, phosphate and turbidity exerted negative influence in stations 1 and 4.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eRivers are natural resources that offer a wide range of ecosystem services from drinking to water utilities in industry, agriculture, transportation and recreation [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Rivers need have a healthy ecosystem and a good water quality in order to provide these services. The surface water temperatures were within acceptable limits and were influenced by season and sampling times. The lowest value was recorded after an early rain in May 2018 while the highest was during the dry season in April 2018. Surface water temperatures are strongly influenced by air temperatures [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Dugdale et al [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] reported water temperature as a critical factor in biotic and abiotic processes; capable of affecting the amount of dissolved matter, organic/inorganic pollutants, nutrients, microbacterial concentrations, the behavior of fish and invertebrates in the aquatic environment.\u003c/p\u003e \u003cp\u003eFlow velocity values were moderate though Stations 2 and 3 were significantly higher. The ability of a waterbody to assimilate and transport pollutants can be significantly affected by flow velocity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It can also affect the composition, abundance and distribution of aquatic biota. Low algal population may be associated with high water velocity while algal population growth is stimulated by low velocity among other things [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This study was different; the highest phytoplankton and zooplankton abundance were recorded respectively in Stations 3 and 2 with high flow velocities but little or no human activities. CCA also showed that flow velocity was a strong negative factor especially in Station 3; increased river discharge and flow velocity, especially during the wet season, has been reported to be responsible for low species composition and abundance in rivers due to low time of residency [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe standard limit for turbidity was exceeded by some values recorded in all the stations especially between December 2017 and March 2018, which could be attributed to cumulative effect of receding flood and anthropogenic activities. Swimming by large number of children, bathing, washing and extraction of water for drinking were high during the dry season and affected turbidity in Station 1. However, Stations 4\u0026ndash;6 had relatively higher values between May and November 2018; attributed to the effect of sand mining activities which increased with the rains [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This was more remarkable in Station 4 that was immediately downstream of sand mining and landing sites and steadily declined further downstream [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. CCA also showed that turbidity had negative effect in station 4 for both phytoplankton and zooplankton. Aquatic lives are affected by high turbidity [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll the pH values did not comply with acceptable limit because of acidity. This is attributed to both geogenic [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and anthropogenic influences [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Sand mining lowers the pH of water bodies [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Extremes of pH are unsuitable for most aquatic organisms. Kale [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] reported the extreme sensitivity of aquatic organisms to pH levels below 5 and death may arise at these low pH values. CCA showed a strong negative influence of pH on phytoplankton.\u003c/p\u003e \u003cp\u003eThe total dissolved solids (TDS) and electrical conductivity (EC) values of the water were moderate though downstream stations (4\u0026ndash;6) were significantly higher than the upstream stations (1\u0026ndash;3). This could be attributed to effects of sand mining activities. Sand mining activities can increase the levels of TDS and EC in surface water [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] and water pollution usually increase with increasing EC [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The TDS and EC values recorded in Station 1 were relatively higher compared to Stations 2 and 3; this could be attributed to perturbation from large number of children swimming during the dry season and allochthonous input from increased runoff during the wet season. The TDS levels recorded were below 600mg/l and cannot reduce light penetration to inhibit phytoplankton growth [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMost of the Dissolved Oxygen values were not up to the acceptable limit especially in station 4; which could be attributed to anthropogenic impact. Rao et al [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] reported that some consequences of sand mining activities like addition of nutrients, changing the flow of water, raising the water temperature and the addition of chemicals can contribute to oxygen depletion in water. Dissolved oxygen (DO) is one of the major parameters used in the determination of water quality [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and the level is critical to support aquatic biodiversity. CCA showed that dissolved oxygen was one of the major positive factors influencing the zooplankton community. Dissolved oxygen levels\u0026thinsp;\u0026gt;\u0026thinsp;5 mg/L is essential to support aquatic life and good fish production [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBiochemical Oxygen Demand (BOD) is an important parameter of water indicating the health and self-purification status of freshwater bodies. Some of the BOD values; especially in Stations 4\u0026ndash;6 were higher than the acceptable limit. This could be attributed to sand mining activities. Akankali et al [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] observed that sand mining activities considerably enhance the release and circulation of organic matters from the sediments into the water column which can increase the BOD levels. High BOD level is a pointer to potential pollution problems because it is capable of adversely depleting dissolved oxygen to the detriment of aquatic biota [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNitrate, a common form of nitrogen occurs naturally in many environments in moderate levels [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The nitrate values were all within acceptable limit though higher values were recorded in Stations 4\u0026ndash;6; attributable to sand mining activities. In Okoro Nsit stream South-south Nigeria; subjected to intense sand mining activities, Akankali et al [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] recorded a range of 10.7 to 12.4 mg/l. The relatively higher values recorded in Station 1 compared to Stations 2 and 3 could be attributed to the effect of large number of children swimming during the dry season and rain during the wet season. Water with nitrate values higher than 5.0 mg/L is considered poor because naturally the range is often between 0.01 and 3.0 mg/L [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Nitrates have negative impact on the environment; noted for contamination of ground and surface waters due to its high solubility [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe nutrient levels and eutrophication of the river system can be identified by the concentrations of phosphate in the river [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Some of the phosphate values exceeded acceptable limit especially in Stations 4\u0026ndash;6 and could be attributable to sand mining activities. Akankali et al [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] recorded a range of 2.5 to 3.6 mg/l in Okoro Nsit stream in Akwa Ibom State in Nigeria. Relatively higher values were also recorded in Station 1 attributed to perturbation from large number of children swimming during the dry season and increased allochthonous input during the wet season. Phosphate values are usually 0.005 to 0.020 mg/L in most natural surface waters; high concentrations can pollution and are mainly responsible for eutrophication [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Nutrients such as nitrogen and phosphates compounds in water stimulate the growth of algae and other photosynthetic aquatic life [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBiomonitoring provides for temporal integration of all impacts and allows the integrated analysis of different factors and their complex interactions in a reliable and cost-effective way. This is because aquatic organisms spend most part of their life under the specific conditions of the site [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Studies have documented the use of plankton as bioindicators of water quality [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The composition and abundance of phytoplankton and zooplankton of the water body is a clear indication of the health status of the water body [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe high phytoplankton abundance in this study could be attributed to nutrient enrichment and low zooplankton abundance. Lehman [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e] reported that zooplankton are major recyclers of nitrogen and phosphorus which frequently limit phytoplankton growth rate, therefore low zooplankton abundance contribute to increased enrichment and phytoplankton development. The phytoplankton was dominated by Chlorophyceae followed by Bacillariophyceae as reported by Kshirsagar et al [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] and Bwala [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Chlorophyceae was also reported as the dominant in Odot Stream by Ekpo et al [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] while the dominance of Bacillariophyceae was reported in Ikpa River by Ekwu and Udo [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], Idumayo River by Nwonumara [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] both in Southeast Nigeria, River Kaduna in North Central Nigeria by Arimoro et al [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and Orashi River, South-South Nigeria by Davies et al [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The growth and development of Chlorophyceae is controlled by parameters like transparency, water temperature, dissolved oxygen, pH and nutrients [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] while low level of DO and high BOD, nitrate and phosphate, favor the growth of diatoms [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. High abundance of diatoms is attributed to high levels of silicates in the water, resulting from sand mining activities [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and also suggests perturbation and organic pollution [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe composition of the phytoplankton was dominated cosmopolitan and pollution tolerant species [64, 66, 67, 71). The most abundant species were \u003cem\u003eMelosira granulata and Planktosphaeria gelatinosa\u003c/em\u003e. Other common tolerant species include \u003cem\u003eAnabaena affins\u003c/em\u003e (Cyanophyceae), \u003cem\u003eEuglena candata, Phacus longicanda\u003c/em\u003e (Euglenophyceae), \u003cem\u003eAmphoria ovaris, Synedra affins\u003c/em\u003e (Bacillariophyceae) and \u003cem\u003ePediastrum simplex\u003c/em\u003e (Chlorophyceae). Phytoplankton species have been used as indicators of organic pollution [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] Some of the taxa recorded like \u003cem\u003eEuglena\u003c/em\u003e, \u003cem\u003eCeratium\u003c/em\u003e, \u003cem\u003ePeridinium\u003c/em\u003e, \u003cem\u003eAnabaena\u003c/em\u003e, \u003cem\u003eClosterium\u003c/em\u003e, \u003cem\u003eScenedesmus\u003c/em\u003e and \u003cem\u003ePediastrum\u003c/em\u003e were indicative of eutrophic condition [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpatially, stations 2 and 3 had the highest number of individuals despite their high velocities; this could be due to little or human activities in the stations [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Stations 1, 4\u0026ndash;6 were significantly lower with station 1 being the lowest. Stations 4\u0026ndash;6 were subjected to intense sand mining activities. Sand mining adversely affects both physical and biological environments, often extending beyond the mining sites [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Apart from constant agitation of the water, it increases turbidity levels and reduces light penetration which hinders the photosynthetic activity, productivity and growth of plankton [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. The low abundance recorded in station 1 could be attributed to perturbation from large number of children swimming in the station. This was observed throughout the dry season sampling period, which also reflected in the levels of some physicochemical parameters. The effect of rains also could be responsible during the wet season. Plankton abundance usually decrease as the amount of rainfall increase; attributed to high turbidity and high flow velocity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe composition of the zooplankton group was dominated by Rotifer followed by Cladocera, Protozoa and Copepod as observed by Kamboj and Kamboj [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] in the mining-impacted stretch of Ganga River, India. Rotifer was also reported as the dominant group in Ikpa and Odot Streams in South-South Nigeria that is subjected to intense sand mining [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Rotifers especially \u003cem\u003eKeratella, Brachionus, Asplanchna\u003c/em\u003e and \u003cem\u003eNotholca\u003c/em\u003e have been reported to dominate freshwater zooplankton in Nigeria [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. Small size, parthenogenesis and rapid reproduction of rotifers under favourable conditions (nutrient-enriched water) could be responsible for their high abundance [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Other factors include their morphological variations and adaptations [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e] as well as their diverse feeding habits [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. Rotifers minimize competition through niche exploitation and food utilization because of their ability to migrate vertically, which could also be responsible for their dominance [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe relatively low zooplankton abundance could be attributed to anthropogenic and seasonal influences. The most abundant zooplankton species was \u003cem\u003eDaphnia pulex\u003c/em\u003e (Cladocera). \u003cem\u003eDaphnia pulex\u003c/em\u003e is the most common cladoceran found almost in all permanent and eutrophic freshwater environments [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. The large body sizes of \u003cem\u003eDaphnia\u003c/em\u003e makes it possible for them to graze on large quantities and diverse forms of phytoplankton; contributing to their predominance of among the cladocerans [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] and their composition and abundance is also dependent on food supply [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpatially, little or no human activities was responsible for the high zooplankton abundance in Station 2 while sand mining activities was responsible the low abundance in Station 4. Station 6 showed signs of recovery after the impacts. Ko et al [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e] reported a significant recovery in the number of species and individuals after dredging operations. High flow velocity could be responsible for the relatively lower abundance in Station 3. Plankton development is usually affected by flowing water because they are continually washed downstream [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiversity indices have an important application in plankton studies especially in relation to assessment of pollution and waterbody productivity. The ShannonWeiner diversity indices for phytoplankton and zooplankton were all greater than 3 indicating ecosystem stability. Stations 2 and 3 were relatively higher for the phytoplankton while upstream stations (1\u0026ndash;3) were relatively higher for the zooplankton. According to Wilm and Dorris [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e], water bodies with algal ShannonWeiner diversity Index\u0026thinsp;\u0026lt;\u0026thinsp;1 are classified as being heavily polluted while 1\u0026ndash;3 is for moderately polluted and \u0026gt;\u0026thinsp;3 for clean water and stable environment. Margalef indices were high for both phytoplankton and zooplankton. In aquatic community, It is generally accepted that species diversity and richness decrease when under stress conditions; though some tolerant species usually break out [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Evenness values were relatively higher in stations 2 and 3 in both phytoplankton and zooplankton indicating the effect of the anthropogenic activities in the other stations. Evenness index is an indication of whether all species are equally abundant in a sample [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. This means that species evenness will decrease as the plankton population size increase. Among the phytoplankton, the evenness of Station 3 with more abundance was lower than that of Station 2.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eSome of the physicochemical parameters showed that the river was perturbed by the anthropogenic activities in the watershed especially in the downstream stations where sand mining was intense. However, the plankton assemblage and community structure gave an indication of a stable environment; though the zooplankton fauna showed some level of stress from the anthropogenic activities. The presence of eutrophic indicators and tolerant species showed that the river was tending towards eutrophication. Sand mining activities contributed to the nutrient enrichment of the river. There is need to regulate illegal sand mining activities in the river.\u003c/p\u003e "},{"header":"Abbreviations","content":" \u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFMEnv\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFederal Ministry of Environment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThanks to Mr. Emeka Nwachukwu for assistance with the sample collections, Mr. Emmanuel Irozuru for assisting in identification of the plankton samples and Mr. Chinedu Ogbodo for producing the study map.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEDA and SNU designed the research. EDA and OGA conducted the field research, analyzed the data, and interpreted the results. All the authors contributed in writing the manuscript, reading and approving the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research and publication is not funded by any agency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlease contact the corresponding author for data requests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmah-Jerry EB, Anyanwu ED, Avoaja DA. Anthropogenic impacts on the water quality of Aba River, Southeast Nigeria. Ethiop J Environ Stud Manage. 2017;10(3):299\u0026ndash;314. Doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dx.doi.org/10.4314/ejesm.v10i3.3\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAliu OO, Akindele EO, Adeniyi IF. Biological assessment of the Headwater Rivers of Opa Reservoir, Ile-Ife, Nigeria, using ecological methods. J Basic Appl Zool. 2020;81:11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s41936-020-00151-5\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos JM, Ferreira MT. Use of Aquatic Biota to Detect Ecological Changes in Freshwater: Current Status and Future Directions. Water. 2020;12:1611.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKomala HP, Nanjundaswamy L, Devi Prasad AG. An assessment of Plankton diversity and abundance of Arkavathi River with reference to pollution. Adv Appl Sci Res. 2013;4\u003cem\u003e(\u003c/em\u003e2\u003cem\u003e)\u003c/em\u003e:320\u0026ndash;324.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma SK. An assessment of plankton diversity and climate change relationship in physico-chemical environment of Son River in Bhojpur area of Bihar, India. Res J Recent Sci. 2018;7\u003cem\u003e(\u003c/em\u003e2\u003cem\u003e)\u003c/em\u003e:6\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOvie SI, Bwala R, Ajayi O. Preliminary study on Limnological stock assessment, productivity and potential fish yield of Omi dam, Nigeria. Afr J Environ Sci Tech. 2011;5(11):956\u0026ndash;963.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuthers IM, Rissik D. (Eds). Plankton: A guide to their ecology and monitoring for water quality. Australia: CSIRO Publishing, Collingwood, Vic: 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMathivanan V, Vijayan P, Sabhanayakam S, Jeyachitra O. An assessment of plankton population of Cauvery River with reference to pollution. J Environ Biol. 2007; 28(2):523\u0026ndash;526.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArimoro FO, Olisa HE, Keke UN, Ayanwale AV, Chukwuemeka VI. Exploring spatio-temporal patterns of plankton diversity and community structure as correlates of water quality in a tropical stream. Acta Ecol Sin. 2018;38: 216\u0026ndash;223\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStriebel, M. Plankton Dynamics: the influence of light; nutrients and diversity. PhD Dissertation, Faculty of Biology, Ludwig Maximilians University, Munich, Germany. 2008;168pp.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConde D, Bonita S, Aubriot L, De Leon R, Pintos W. Relative contribution of planktonic and benthic microalgae production in a Eutrophic Coastal Lagoon of South America. J Limnol. 2007;78:207\u0026ndash;212.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eContreras JJ, Sarma SSS, Merino-Ibarra M, Nandini S. Seasonal changes in the rotifer (Rotifera) diversity from a tropical high altitude reservoir (Valle de Bravo, Mexico). J Environ Biol. 2009;30:191\u0026ndash;195.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBellinger EG, Sigee PC. Freshwater algae: Identification and use as bioindicator. John Wiley and Sons, Ltd: 2010;40pp.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYusuf ZH. Phytoplankton as bioindicators of water quality in Nasarawa reservoir, Katsina State Nigeria. Acta Limnol Bra. 2020;32:e4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S2179-975X3319\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParmar TK, Rawtani D, Agrawal Y. Bioindicators: The natural indicator of environmental pollution. J. Frontiers Life Sci. 2016;9(11):110\u0026ndash;118.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSousa W, Attayde JL, da Silva Rocha E, Eskinazi-Sant'Anna EM. The response of zooplankton assemblages to variations in the water quality of four man-made lakes in semi-arid northeastern Brazil. \u0026ndash; J Plank Res. 2008;30:699\u0026ndash;708.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma S, Siddique A, Singh K, Chouhan M, Vyas A, Solnki CM, Sharma D, Nair S, Sengupta T. Population dynamics and seasonal abundance of zooplankton community in Narmada River (India). Researcher. 2010;2(9):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmidt J, Andrade PDB, Padial AA. Zooplankton trajectory before, during and after a hydropower dam construction. Acta Limnol Bra. 2020;32:e18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrimo A, Kimmel D, Marques S, Martinho F, Azeiteiro U, Pardal M. Zooplankton community responses to regional-scale weather variability: a synoptic climatology approach. Climate Res. 2015;62(3):189\u0026ndash;198.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRajagopal T, Thangamani A, Sevarkodiyone S, Sekar M, Archunan G. Zooplankton diversity and physico-chemical conditions in three perennial ponds of Virudhunagar district, Tamilnadu. J Environ Biol. 2010;31(3):265\u0026ndash;272.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePace ML, Orcutt JD. The relative importance of protozoans, rotifers, and crustaceans in a freshwater zooplankton community. Limnol Oceanogr. 1981;26(5):822\u0026ndash;830.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHairston Jr NG, Hairston Sr N.G. Cause-effect relationships in energy flow, trophic structure, and interspecific interactions. Ame Naturalist.1993;142(3):379\u0026ndash;411.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDas P, Kar S, Das U, Bimola M, Kar D, Aditya G. Day time variations of zooplankton species composition: observations from the wetlands of Assam, India. Acta Limnol Bra. 2020;32:e10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/S2179-975X1418\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaygusuz \u0026Ouml;, Dorak Z. Species Composition and Diversity of the Zooplankton Fauna of Darlik Stream (İstanbul-Turkey) and its Tributaries. J Fisher Sci. 2013;7(4):329\u0026ndash;343. Doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3153/jfscom.2013037\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAPHA. Standard Methods for the Analysis of Water and Wastewater, 23rd Edition. Washington D.C: American Public Health Association; 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeje CY, Fernando CH. A practical guide to the identification of Nigerian zooplankton. Kainji, Nigeria: Kainji Lake Research Institute Press; 1986.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJanse van Vuuren S, Taylor J, Gerber A, van Ginkel C. Easy identification of the most common freshwater algae. A guide for the identification of microscopic algae in South African freshwaters. School of Environmental Sciences and Development: Botany, North-West University (Potchefstroom Campus), Potchefstroom 2520, South Africa; 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDang PD, Khoi NV, Nga LN, Thanh DN, Hai HT. Identification Handbook of Freshwater Zooplankton of the Mekong River and its Tributaries. Vientiane: Mekong River Commission. 2015;207pp.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHammer \u0026Oslash;H, Harper DAT, Ryan PD. Past: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontol Electron. 2001;4(1) art. 4: 9pp.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFMEnv. \u003cem\u003eNational Environmental (Surface and Groundwater Quality Control) Regulations, S.I. No. 22\u003c/em\u003e, Gazette No. 49, Vol.\u0026nbsp;98 of 24th May, 2011. Federal Ministry of Environment, Abuja, Nigeria; 2011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyanwu ED, Umeham SN. Identification of waterbody status in Nigeria using predictive index assessment tools: a case study of Eme River, Umuahia, Nigeria. Int J Energ Water Res. 2020;4:271\u0026ndash;279. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s42108-020-00066-5\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAydin H, Ustaoğlu F, Tepe Y, Soylu EN. Assessment of water quality of streams in northeast Turkey by water quality index and multiple statistical methods, Environ Forensics. 2021;22(1\u0026ndash;2:270\u0026ndash;287. Doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/15275922.2020.1836074\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark J, Kim K, Cho C, Kang M, Kim B. Spatio-temporal characteristics of air and water temperature change in the middle reach of the Nakdong River. J Environ Policy Admin. 2016;9:233\u0026ndash;253.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDugdale SJ, Allen Curry R, St-Hilaire A, Andrews SN. Impact of future climate change on water temperature and thermal habitat for keystone fishes in the Lower Saint John River. Water Res Manage. 2018;32(15):4853\u0026ndash;4878.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapman D. (ed.). Water Quality Assessment. A Guide to the use of Biota, Sediments and Water in Environmental Monitoring (2nd Edition). Taylor and Francis: London and New York; 1996.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerma S, Tiwari D, Verma A. Algal Dynamics of River Pandu in Relation to Ambient Environment. ECOPRINT. 2013;20:9\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyanwu ED, Ikomi RB, Arimoro FO. Water quality and zooplankton of the Ogba River, Benin City, Nigeria. Afr J Aquat Sci. 2013;38(2):193\u0026ndash;199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEkwu AO, Udo ND. Plankton Communities of Ikpa River, Southeast Nigeria Exposed to Sand-dredging Activities. J Fisher Aquat Sci. 2014;9(5):345\u0026ndash;351.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeck Yen T, Rohasliney H. Status of Water Quality Subject to Sand Mining in the Kelantan River, Kelantan. Trop Life Sci Res. 2013;24\u003cem\u003e(\u003c/em\u003e1\u003cem\u003e)\u003c/em\u003e:19\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyanwu ED, Umeham SN. An index approach to heavy metal pollution assessment of Eme River, Umuahia, Nigeria. Sustain, Agri, Food Environ Res. 2020;8(X). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.7770/safer-V0N0-art2067\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshraf MA, Maah MJ, Yusoff I, Wajid A, Mahmood K. Sand mining effects, causes and concerns: A case study from Bestari Jaya, Selangor, Peninsular Malaysia. Sci Res Essays. 2011;6(6):1216\u0026ndash;1231.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeiyaboh E, Ogamba EN, Utibe DI. Impact of Dredging on the water quality of Igbedi Creek, Upper Nun River, Niger Delta, Nigeria. IOSR J Environ Sci Toxicol Food Tech. 2013;7(5):51\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheeba S. Biotic Environment and Sand Mining - A Case Study from Ithikkara River, South West Coast of India. \u0026lt;background-color:#CCFF99;vertical-align:baseline;\u0026gt;J Ind Pollut Contr\u0026lt;/background-color:#CCFF99;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;.\u0026lt;/vertical-align:baseline;\u0026gt;\u0026lt;ivertical-align:baseline;\u0026gt;\u0026lt;/ivertical-align:baseline;\u0026gt;2009;\u0026lt;background-color:#FFCC66;vertical-align:baseline;\u0026gt;25\u0026lt;/background-color:#FFCC66;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;(\u0026lt;/vertical-align:baseline;\u0026gt;\u0026lt;background-color:#C8BE84;vertical-align:baseline;\u0026gt;2\u0026lt;/background-color:#C8BE84;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;)\u0026lt;/vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;:\u0026lt;/vertical-align:baseline;\u0026gt;\u0026lt;background-color:#D279FF;vertical-align:baseline;\u0026gt;133\u0026ndash;138\u0026lt;/background-color:#D279FF;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;.\u0026lt;/vertical-align:baseline;\u0026gt;\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKale VS. Consequence of Temperature, pH, Turbidity and Dissolved Oxygen Water Quality Parameters. Int Adv Res J Sci Engr Tech. 2016;3\u003cem\u003e(\u003c/em\u003e8\u003cem\u003e)\u003c/em\u003e:186\u0026ndash;190.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyanwu ED, Emeka CS. Application of water quality index in the drinking water quality assessment of a southeastern Nigeria river. Food Environ Safe. 2019;XVIII(4):308\u0026ndash;314.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkankali JA, Idongesit AS, Akpan PE. Effects of sand mining activities on water quality of Okoro Nsit stream, Nsit Atai Local Government Area, Akwa Ibom State, Nigeria. Int J Dev Sustain. 2017;6:451\u0026ndash;462.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyanwu ED, Ukaegbu AB. Index approach to water quality assessment of a south eastern Nigerian river. Int J Fisher Aquat Stud. 2019;7(1): 153\u0026ndash;159.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRehman M, Yousuf AR, Balkhi MH, Rather MI, Shahi N, Meraj M, Hassan K. Dredging induced changes in zooplankton community and water quality in Dal Lake, Kashmir, India. Afr J Environ Sci Tech. 2016;10(5):141\u0026ndash;149. Doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5897/AJEST2016.2096\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDorak Z. Zooplankton abundance in the lower Sakarya River Basin (Turkey): Impact of environmental variables. J Black Sea/Mediter Environ. 2013;19: 1\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshiru OR, Adegbile MO, Ayeku PO. Assessment of the Effect of Anthropogenic Activities on Aquatic Life in Ugbo-Aiyetoro Water-way, Southwestern Nigeria. Int J Oceanogr Mar Ecol Sys. 2017;6:9\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao AS, Marshall S, Gubbi J, Palaniswami M, Sinnott R, Pettigrove V. Design of Low-Cost Autonomous Water Quality Monitoring System. International Conference on Advances in Computing, Communications and Informatics (ICACCI), Mysore, 22\u0026ndash;25, August 2013;14\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhatnagar A, Jana SN, Garg SK, Patra BC, Singh G, Barman UK. Water quality management in Aquaculture. In: Course manual of Summer School on Development of sustainable Aquaculture technology in fresh and saline water. CS Hagyana Agricultural Hisar (India). 2004;203\u0026ndash;210.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Sulaiman AM, Khudair BH. Correlation between BOD5 and COD for Al-Diwaniyah Wastewater Treatment Plants to obtain the Biodigrability Indices. Pak J Biotech. 2018;15(2):423\u0026ndash;427.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatel RK. Nitrates-its generation and impact on environment from mines: A Review. National Conference on Sustainable Mining Practice, 2\u0026ndash;3, December 2016, India. 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLehigh Environmental Initiative (n.d). Nitrates. Enviro Sci Inquiry. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ei.lehigh.edu/envirosci/watershed/wq/wqbackground/nitratesbg.html\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChristensen VG, Lee KE, McLees JM, Niemela SL. Relations between retired agricultural land, water quality, and aquatic-community health, Minnesota River basin. J Environ Quality. 2011;41:1459\u0026ndash;1472.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubey VK, Sarkar UK, Kumar RS, Mir JI, Pandey A, Lakra WS. Length-weight relationships (LWRs) of 12 Indian freshwater fish species from an un-impacted tropical river of Central India (River Ken). J Appl Ichthyol. 2012;28, 854\u0026ndash;856.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValdecasas AG, Baltan\u0026aacute;s A. Jacknife and bootstrap estimation of biological index of water quality. Water Res. 1990;24:1279\u0026ndash;1283.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaidya SR. Use of zooplankton as bioindicators for the management of aquatic diversity: A review. Int J Biol Res. 2017;2\u003cem\u003e(\u003c/em\u003e1\u003cem\u003e)\u003c/em\u003e:14\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIgwe DO, Igboji PO, Mbagwu GI. Use of Plankton as Bioindicators in Water Quality Management for Sustainable Use in Fishery Production: A Review. \u003cem\u003eElixir Agri.\u003c/em\u003e 2019;134:53593\u0026ndash;53597.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKutama RM, Abubakar MM, Balarabe ML. The Plankton as Indicators of Water Quality in Kusalla Reservoir: A Shallow Man Made Lake. IOSR J Pharm Biol Sci. 2014;9(3):12\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLehman JT. Release and cycling of nutrients between planktonic algae and herbivores. Limnol Oceanogr. 1980;25:620\u0026ndash;632.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKshirsagar AD, Ahire ML, Gunale VR. Phytoplankton Diversity Related to Pollution from Mula River at Pune City. Terrest Aquat Environ Toxicol. 2012;\u0026lt;background-color:#FFCC66;vertical-align:baseline;\u0026gt;6\u0026lt;/background-color:#FFCC66;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;\u0026lt;/vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;(\u0026lt;/vertical-align:baseline;\u0026gt;\u0026lt;background-color:#C8BE84;vertical-align:baseline;\u0026gt;2\u0026lt;/background-color:#C8BE84;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;)\u0026lt;/vertical-align:baseline;\u0026gt;:136\u0026ndash;142\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBwala MN. The Abundance of Phytoplankton In River Nggada and River Ngadda-Bul, Maiduguri Metropolis, Borno State, Nigeria. Global Edu Res J. 2019;7(7):820\u0026ndash;829.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEkpo IE, Essien-Ibok MA, Duncan AO. Densities, spatial distribution and community structure of plankton of Odot Stream. J Ecol Nat Environ. 2015;7(6):180\u0026ndash;187.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNwonumara GN. \u003cem\u003eWater Quality and Phytoplankton as Indicators of Pollution in a Tropical River.\u003c/em\u003e\u0026lt;bvertical-align:super;\u0026gt; \u0026lt;/bvertical-align:super;\u0026gt;\u003cem\u003eProceedings of 6th NSCB Biodiversity Conference, Uniuyo\u003c/em\u003e 2018;\u003cem\u003e83\u0026ndash; 89.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavies OA, Otene BB, Amachree D, Nwose FA. Phytoplankton Community of Upper Reaches of Orashi River, Rivers State, Nigeria. Specialty J Biol Sci. 2019;5(3):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRajagopal T, Thangamani A, Archunan G. Comparison of physico-chemical parameters and phytoplankton species diversity of two perennial ponds in Sattur area, Tamil Nadu. J Environ Biol. 2010;31:787\u0026ndash;794.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao GMN, Pragada PM. Seasonal abundance of micro algae in Pandi Back waters of Godavari Estuary, Andra Pradesh, India. Not Sci Biol. 2010;2:26\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerma P, Gupta UC, Adiyecha PR, Solanki HA. Seasonal variation in the phytoplankton biodiversity of Chandlodia lake. Int J Inno Res Sci Engr Tech. 2014;3(1):1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalmer CM. A composite rating of algae tolerating organic pollution. J Phycol. 1969;5: 78\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkogwu OI, Ugwumba AO. Seasonal dynamics of phytoplankton in two tropical rivers of varying size and human impact in Southeast Nigeria. Rev Biol Trop. 2103;61 (4):1827\u0026ndash;1840\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalem Z, Ghobara M, El Nahrawy AA. 2017. Spatio-temporal evaluation of the surface water quality in the middle Nile Delta using Palmer\u0026rsquo;s algal pollution index. Egypt J Basic Appl Sci. 2017;4:219\u0026ndash;226. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.ejbas.2017.05.003\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArimoro FO, Oganah AO. Zooplankton community responses in a perturbed tropical stream in Niger Delta, Nigeria. \u0026lt;background-color:#CCFF99;vertical-align:baseline;\u0026gt;Open Environ Biol Monit J\u0026lt;/background-color:#CCFF99;vertical-align:baseline;\u0026gt;\u0026lt;vertical-align:baseline;\u0026gt;.\u0026lt;/vertical-align:baseline;\u0026gt; 2010;3:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanimu Y, Bako SP, Adakole JA, Tanimu, J. Phytoplankton as bioindicators of water quality in Saminaka reservoir, Northern Nigeria. In: \u003cem\u003eInternational Symposium on Environmental Science and Technology.\u003c/em\u003e Dongguan, Guangdong Province, China; Environmental Science and Technology. 2011;83\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamboj V, Kamboj N. Spatial and temporal variation of zooplankton assemblage in the mining-impacted stretch of Ganga River, Uttarakhand, India. Environ Sci Pollut Res. 2020;27:27135\u0026ndash;27146\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkin-Oriola GA. Zooplankton Association and Environmental Factors in Ogunpa and Ona Rivers, Nigeria. Rev Biol Trop. 2003;51(2):391\u0026ndash;398.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMustapha MK. Zooplankton assemblage of Oyun Reservoir, Offa, Nigeria Rev Biol Trop. 2009;57(4):1027\u0026ndash;1047.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevine SN, Borchardt MA, Braner M, Shambaugh AD. The Impact of Zooplankton Grazing on Phytoplankton Species Composition and Biomass in Lake Champlain (USA-Canada). J. Great Lakes Res. 1999;25(1):61\u0026ndash;77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWetzel RG. Limnology: Lake and River Ecosystems (3rd ed.) San Diego, C.A.: Academic Press. 2001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller C. \u003cem\u003eDaphnia pulex\u003c/em\u003e (On-line), Animal Diversity Web. Accessed February 04, 2021 at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://animaldiversity.org/accounts/Daphnia_pulex/\u003c/span\u003e\u003c/span\u003e. 2000.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKo EJ, Kim D-K, Jung E-S, Heo Y-J, Joo, G-J, Kim, H-W. Comparison of Zooplankton Community Patterns in Relation to Sediment Disturbances by Dredging in the Guemho River, Korea. Water. 2020;12: 3434. Doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/w12123434\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRedden AM, Kobayashi T, Suthers I, Bowling L, Rissik D, Newton G. Chapter 2: Plankton processes and the environment. In: Suthers IM, Rissik D. (Eds). \u003cem\u003ePlankton: A guide to their ecology and monitoring for water quality\u003c/em\u003e. CSIRO Publishing, Collingwood, Vic, Australia. 2009;15\u0026ndash;38\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilm JL, Dorris TC. Species diversity of benthic macroinvertebrates in a stream receiving domestic and oil refinery effluents. In: Islam SM. \u003cem\u003ePhytoplankton diversity index with reference to mucalinda serovar Bodh-Gaya, 12th World Lake Conference.\u003c/em\u003e Taal, India. Ame Midland Naturalist. 2007;427\u0026ndash;449.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu MQ, Cao H, Xie P, Deng DG, Feng WS, Xu J. The temporal and spatial distribution, composition and abundance of planktonic protozoa, with special relation to eutrophication in the Chaohu Lake, China. Eur J Protistol. 2005;41:183\u0026ndash;192.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaparapu J, Geddada MNR. Seasonal Distribution of Phytoplankton in Riwada Reservoir, Visakhapatnam, Andhra Pradesh, India. Not Sci Biol. 2013;5(3):290\u0026ndash;295\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"
[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Plankton, Diversity, anthropogenic, bioindicator, water quality, sand mining","lastPublishedDoi":"10.21203/rs.3.rs-281949/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-281949/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCertain anthropogenic activities have negative impacts on the aquatic ecosystems. Plankton are sensitive to their environment and are used to monitor anthropogenic impacts. A South-eastern Nigeria River was studied from December 2017 to November 2018 in 6 stations; to assess the plankton community, water quality and anthropogenic impacts. The river was subjected to intense sand mining activities among other activities. The plankton was sampled with filtration method while water was collected and analysed using standard methods. A total of 36 phytoplankton species and 27 zooplankton species were recorded with Chlorophyceae and Rotifers being the most abundant groups. The most abundant species - \u003cem\u003eMelosira granulata\u003c/em\u003e (phytoplankton) and \u003cem\u003eDaphnia pulex\u003c/em\u003e (zooplankton) are pollution indicators. Some of the physicochemical parameters showed that the river was perturbed by the anthropogenic activities in the watershed. However, the plankton assemblage and community structure gave an indication of a stable environment; though the zooplankton fauna showed some level of stress. The impacts of sand mining activities on water quality and plankton were more in the downstream stations (4\u0026ndash;6) where sand mining was intense while perturbation from swimming children and related activities were observed in station 1 especially during the dry season. The presence of eutrophic indicators and tolerant species showed that the river was tending towards eutrophication. Sand mining activities contributed to the nutrient enrichment of the river. CCA showed the major water quality parameters that influenced the plankton community structure. There is need to regulate illegal sand mining activities in the river.\u003c/p\u003e","manuscriptTitle":"Water Quality and Plankton Assessment of Eme River, Umuahia, Southeast Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-03-12 00:33:31","doi":"10.21203/rs.3.rs-281949/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"
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