Water Quality and Plankton Assessment of Eme River, Umuahia, Southeast Nigeria

Certain 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 ltration 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 inuenced the plankton community structure. There is need to regulate illegal sand mining activities in the river.

The trophic transfer e ciencies from phytoplankton to zooplankton and from zooplankton to sh are largely dependent on the taxa of zooplankton available in an aquatic ecosystem [21,22]. The composition of macroinvertebrate predator and sh species can be in uenced 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; owing 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 [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 ltered 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 magni cation of x10. Planktons were sorted into different groups and the cells per ml were counted. Identi cation work was done using key literatures by Jeje and Fernando [26]; Janse van Vuuren et al [27] and Dang et al [28]. The identi cation 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 signi cant 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].

Water Quality
Aspects of the physicochemical parameters of Eme River are presented in Table 1. Surface water temperature ranged from  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 signi cantly (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 signi cantly (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). 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). exerted by pH and temperature (Fig. 2). Biochemical oxygen demand, electrical conductivity and phosphate exerted positive in uence on cyanophyceae and ow velocity on euglenophyceae and chlorophyceae. On the other hand, turbidity and nitrate exerted negative in uence on bacillariophyceae and temperature on Pyrrophyceae. Spatially, pH and ow velocity exerted negative in uence respectively in stations 1 and 3 while turbidity and nitrate exerted negative in uence 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 (  The number of taxa (species) recorded were 27 in all the station except station 4 with 26 (

Relationship between Zooplankton Groups and Environmental Variables
The Canonical Correspondence Analysis (CCA) showed that water temperature, ow velocity and dissolved oxygen exerted a greater positive in uence on the relative abundance of the zooplankton groups compared to the higher negative in uence exerted by electrical conductivity, phosphate and turbidity (Fig. 3).

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 in uenced 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 in uenced 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 sh and invertebrates in the aquatic environment.
Flow velocity values were moderate though Stations 2 and 3 were signi cantly higher. The ability of a waterbody to assimilate and transport pollutants can be signi cantly affected by ow 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 ow velocities but little or no human activities. CCA also showed that ow velocity was a strong negative factor especially in Station 3; increased river discharge and ow 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 ood 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 in uences [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 in uence 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 signi cantly higher than the upstream stations (1)(2)(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 ow 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 in uencing the zooplankton community. Dissolved oxygen levels > 5 mg/L is essential to support aquatic life and good sh production [52].
Biochemical Oxygen Demand (BOD) is an important parameter of water indicating the health and self-puri cation 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 identi ed 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 speci c 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].
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 signi cantly 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 re ected 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 ow 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 in uences. 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 signi cant recovery in the number of species and individuals after dredging operations. High ow velocity could be responsible for the relatively lower abundance in Station 3. Plankton development is usually affected by owing 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 < 1 are classi ed as being heavily polluted while 1-3 is for moderately polluted and > 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