UMYU Journal of Microbiology Research

E-ISSN: 2814 – 1822; P-ISSN: 2616 – 0668

ORIGINAL RESEARCH ARTICLE

Assessment of Surface Water Quality using Phytoplankton as Base-line Indicator Organisms in Ilorin, Kwara State, Nigeria

^1*Aborisade, W. T. , ¹Ajao, A. T. and ²Sadiq, A. I.

¹Department of Microbiology, Kwara State University, Malete, Nigeria.

²Department of Microbiology, Kwara State Polytechnic, Ilorin, Nigeria.

*Corresponding Author’s Email: wakili.aborisade@kwasu.edu.ng; +2348034195063

Abstract

Timely and accurate water quality monitoring is crucial to ensure their sustainable use and safeguard public health. Therefore, this study assessed surface water quality in Mubo River (SP1) and Sobi Dam (SP2) in Ilorin, using phytoplankton as base-line indicator organisms. Water samples were collected on July 20th (rain season) and December 20th (dry season), 2023, at 0.3 meters from the mid-water column. The physicochemical parameters of the water samples were determined using standard methods. The standard microscopic techniques were used to enumerate and identify phytoplankton genera. The findings showed that the pH and DO (mg/l) levels were within the permissible limit stipulated by the National Environmental Standard and Regulation Enforcement Agency for Surface Water in Nigeria (NESREA). The BOD (mg/l) and COD (mg/l) levels were above the permissible limit for SP1 for both seasons. The 8 genera of pollution-tolerant phytoplankton recorded were Cyclotella, Chlorella, Closterium, Chlamydomonas, Micractinium, Microcystis, Euglena, and Phacus, with Chlorella having the highest abundance percentage in all the sampling sites. The Shannon diversity indices values indicate lower phytoplankton species diversity (H ≤ 1.99) in all the water samples. The Palmer’s pollution index (PPI) scores ranged from 14 to 18 in the sampling sites. Palmer's index suggests likely high organic pollution in Mubo Rivers' in both sampling periods. A notable high level of organic pollution was recorded in Sobi Dam only during the rainy season. The relatively high turbidity, BOD (mg/l), and COD (mg/l) values support the index pollution scores and confirm the suitability of phytoplankton as baseline indicators for organic pollution assessment in surface water.

Keywords: Phytoplankton, Surface water, Palmer’s index, Pollution-tolerant, Chlorella

INTRODUCTION

Surface waters, like rivers, lakes, and streams, are important components of the environment, supporting ecosystem functioning, human communities, vital economic activities, and environmental sustainability. However, these invaluable resources are increasingly threatened by various forms of pollution and environmental degradation (Aborisade et al., 2023). Assessing the quality of water systems in a timely and accurate manner is crucial for ensuring their sustainable use and safeguarding public health (Onu et al., 2023). Assessing surface water quality using phytoplankton as baseline indicators could provide a rapid and standard technique crucial for environmental monitoring and management (Nguyen and Huynh, 2023).

Phytoplankton are an ecological group of microalgae adapted to live in the well-illuminated surface part of the aquatic environment (Tambaru et al., 2021; Naselli-Flores and Padisak, 2023). They are oxygenic photosynthetic organisms and play a fundamental role in aquatic ecosystems (Enawgaw and Wagaw, 2023). They are the primary producers and facilitate the process of carbon fixation through photosynthesis, thereby serving as primary energy sources within aquatic food ecosystems (Okere et al., 2020). The sensitivity of phytoplankton to environmental changes makes them ideal bioindicators for monitoring water quality (Gabyshev et al., 2022). Likewise, phytoplankton responds rapidly to nutrient level fluctuation, pH, temperature, and other environmental factors (Filiz et al., 2020). Their characteristically short life cycles and rapid population response to environmental changes could provide timely insights into water quality variations. Their ubiquitous nature also offers comprehensive coverage for monitoring water quality across diverse ecosystems (Grob et al., 2021). With numerous species exhibiting distinct features, their presence and abundance can reveal specific pollutants or environmental stresses (Okoye and Ogbebor, 2023).

Water quality assessment involves the evaluation of physicochemical parameters (inorganic nutrients, organic pollutants, heavy metals, acidity, and salinity) in water samples (Boudeffa et al., 2020; Roy et al., 2021). While regular evaluation of water quality based on physicochemical characteristics is preferable, biological monitoring that uses phytoplankton evaluation can offer a quicker, more reliable, and cost-effective method for pollution monitoring in aquatic environments. It can reflect the overall quality of water and offer direct insights into the ecological effects of environmental conditions on aquatic life.

Water quality monitoring is important because of the link between the overall quality of water and people's health (Luvhimbi et al., 2022). Maintaining high-quality water is a global necessity. Contaminants such as hazardous chemicals and pathogenic microorganisms can cause waterborne illnesses, emphasizing the importance of protecting water sources and maintaining effective system monitoring (Nguyen and Huynh, 2023).

The comprehensive evaluation of phytoplankton could serve as an indispensable tool for evaluating water quality. Evaluating the community composition of phytoplankton may provide clear insights into water pollution levels, their impacts on aquatic communities, and the resilience of aquatic ecosystems. The initial attempt to utilize the phytoplankton species for water pollution assessment was made by Palmer (Salem et al., 2017; Ray et al., 2023). Subsequently, along with other indices, Palmer pollution indices are being used to monitor organic and inorganic pollution because it is thought to be a rapid, dependable, and cost-effective method of evaluating pollution levels in aquatic ecosystems (Labib et al., 2023).

Employing phytoplankton as reference indicators to assess surface water quality represents a multifaceted approach essential for preserving aquatic ecosystems, protecting public health, and promoting sustainable resource management (Enawgaw and Wagaw, 2023). Evaluating surface water quality using phytoplankton can provide a swift and cost-effective tool to safeguard our water resources. By integrating phytoplankton analysis with other water quality parameters and adhering to rigorous scientific methodologies, a holistic and comprehensive understanding of the health of aquatic ecosystems can be attained. Therefore, this study assesses surface water quality using phytoplankton as baseline indicator organisms.

MATERIALS AND METHODS

Study Site

The selected surface waters used for the study were Mubo River and Sobi Dam. Mubo River is a part of Asa River that flows through Royal Valley Estate and lies within the latitude 8° 30' North and longitude 4° 34' East (Aborisade et al., 2023). While the Sobi Dam is located on River Moro and lies within a latitude 9^o 58’ North and longitude 8° 25' East (Ogunkunle et al., 2016).

Water Samples Analysis

Water samples were aseptically collected from the mid-water column at a depth of 0.3m below the water surface. The samples were collected into 1000 ml screwed cap amber-colored sampling bottles and immediately transported to the laboratory for analysis. The water samples were collected on July 20th and December 20th, 2023, to account for the wet and dry season periods of the year. Three samples each were collected from the sampling point, making a total of 12 samples for the sampling period.

The dissolved oxygen (DO) and the pH variables of the samples were determined on-site with a water multiparameter analyzer (Model YSI-Pro1020). The biological oxygen demand (BOD) was evaluated from the differences in the first-day DO value and the fifth-day DO (DO₁ – DO₅) values (Aborisade et al., 2023). The chemical oxygen demand (COD) was determined through the oxidation of organic matter contents of the water with potassium dichromate (K₂Cr₂O₇) and catalyzed by Ag₂SO₄. The turbidity of water samples was determined in the laboratory with a benchtop turbidity meter (Infitek BEP-TB4000E Model).

The samples were analyzed for heavy metals content (cadmium, chromium, copper, zinc, and lead) spectrophotometrically with an atomic absorption spectrophotometer (AAS_Agilent 200AA model).

Enumeration and Identification of Phytoplankton

The standard microscopic technique using a conventional hemocytometer counting method of the UNESCO-Intergovernmental Oceanographic Commission, as described by Isichei et al. (2020) with slight modifications, was used to enumerate phytoplankton contents of the water samples. Each sample was agitated to distribute organisms evenly, and 1 ml was placed on a hemocytometer with a dropping pipette and examined under a microscope. The phytoplankton was counted, and the identification was based on morphological features in line with the identification keys by Janse-van et al. (2006).

Data Analysis

The data were subjected to descriptive analysis on IBM SPSS version 25. The means and standard errors of the data were presented in Table format.

The mean value of physicochemical parameters was compared with the standard permissible limit of the National Environmental Standards and Regulation Enforcement Agency for Nigeria’s fisheries and recreation surface water quality (NESREA, 2011). Shannon-Weiner diversity index (H) was used to estimate the diversity of phytoplankton on an online Statology calculator (https://www.statology.org/shannon-diversity-index-calculator/). The water pollution status was classified based on Palmer’s index.

RESULTS

Physiochemical Parameters of the Water Samples.

The results for the physicochemical parameters of the surface water samples are presented in Table 1.

The average pH values of the surface water samples were 6.62 and 6.97 (SP1) and 7.02 and 6.69 (SP2) for the rain and dry seasons, respectively. The average dissolved oxygen values DO (mg/l) were 6.83 and 6.49 (SP1) and 6.99 and 6.65 (SP2) for the rainy and dry seasons, respectively. The mean turbidity values (NTU) were 13.05 and 9.03 (SP1) and 11.12 and 5.67 (SP2) for the rain and dry season, respectively. The mean BOD (mg/l) values were 8.23 and 5.24 (SP1) and 4.49 and 3.62 (SP2) for the rainy and dry seasons, respectively. The average COD (mg/l) was 50.03 and 38.05 (SP1) and 35.62 and 23.83 (SP2) for the rainy and dry seasons, respectively.

The cadmium (mg/l) and chromium (mg/l) were below the detectable limit (BDL) of the analytical instrument used for SPI and SP2, respectively. The average copper (mg/l) content values were 0.058 and 0.047 for the rain and dry seasons, respectively, at SP1. The Zinc content (mg/l) values were 0.004 and 0.003 for the rain and dry seasons, respectively, at SP1. The average Pb (mg/l) contents values were 0.007 and 0.002 for the rain and dry seasons, respectively, at SP1. At the sampling site2 (SP2), the Cu (mg/l), Zn (mg/l), and Pb (mg/l) were below the detectable limit (BDL).

The pH and DO (mg/l) values for the sampling sites (SP1 and SP2, respectively) do not exceed the specified standard range of the National Environmental Standard and Regulations Enforcement Agency (NESREA) for fisheries and recreation surface water standards (Table 1).

The turbidity values (NTU) during the rainy season for SP1 and SP2 were higher than the standard value recommended by NESREA (Table 1). The BOD (mg/l) and COD (mg/l) values at sampling point 1 (SP1) in both rainy and dry seasons were higher than the specified limit values of NESREA (Table 1).

The heavy metals (Cd (mg/l), Cr (mg/l), Cu (mg/l), Zn (mg/l), and Pb (mg/l)) were within the recommended safe range of NESREA for surface water quality (Table 1).

Relative Abundance of Phytoplankton from Surface Water Samples

The relative abundance of phytoplankton genera observed from the surface water samples is presented in Table 2. A total of 8 phytoplankton genera (Chlamydomonas, Chlorella, Closterium, Cyclotella, Euglena, Micractinium, Microcystis, and Phacus) were recorded in the sample sites (Table 2). Chlorella had the highest abundance percentage in all the sampling sites (Table 2).

Palmer’s Pollution Index Scores of Surface Water Samples

Palmer’s pollution index of phytoplankton genera of all the 8 observed algal genera (Chlamydomonas, Chlorella, Closterium, Cyclotella, Euglena, Micractinium, Microcystis, and Phacus) were considered as pollution tolerant and Palmer’s pollution index scores were assigned (Table 2).

The total scores recorded in surface water samples from sample site 1 (SP1) were 18 and 17 for the rain and dry season, respectively. (Table 3). At sample site 2 (SP2), the total scores recorded were 17 and 14 for the rain and dry season, respectively (Table 3).

Palmer’s pollution classification index scores for SP1 are probably high organic pollution for the rainy and dry seasons (Table 3). For SP2, the pollution classification was probable high organic and moderate organic pollution for the rainy and dry seasons, respectively (Table 3).

Table 1: Physicochemical Parameters and Heavy Metals Content of Water Samples

Key: All the values were presented in mean plus or minus standard error of the mean; The values with an asterisk (*) are not within the NESREA surface water’s standard for fisheries and recreation, NSEREA is the National Environmental Standard and Regulation Enforcement Agency; BDL is below the detection limit of 0.00003 mg/l; SP1 is Mubo water; SP2 is Sobi Dam.

Table 2: Relative Abundance of Phytoplankton in the Study Sites

Key: H is Shannon's diversity index; If H value ≥ 3.50 indicates Very high; H value 3.00 – 3.49 High; H value 2.50 – 2.99 indicates moderate; H value 2.00 – 2.49 indicates low; H value ≤ 1.99 indicates Very low diversity (Baliton et al., 2020).

Table 3: Palmer’s Pollution Index Scores of Surface Water Samples

Key: PPI score values between A: 0-10 = lack of organic pollution, B: 10-15 = moderate pollution, C: 15-20 = probable high organic pollution, and D: ≥ 20 = confirmed high organic pollution (Zaky et al., 2018).

DISCUSSIONS

Timely and accurate monitoring of water quality is crucial to ensure its sustainable use and safeguard public health (Onu et al., 2023). Therefore, this study assesses the quality of Mubo and Sobi Dam surface water using phytoplankton as baseline indicator organisms.

The findings showed that the pH and DO (mg/l) levels were within the permissible limit stipulated by Nigeria's National Environmental Standard and Regulation Enforcement Agency for surface water (NESREA, 2011). The pH, a measure of the concentration of protons in the water, has been reported to have a major impact on the toxicity and solubility levels of chemicals and heavy metals in aquatic environments (Mishra et al., 2023). Research has shown that pH could disrupt the photosynthetic activities of phytoplankton communities by affecting their inherent physiological carbon uptake (Masuda et al., 2021; Liu et al., 2022).

The biological oxygen demand is one of the crucial indicators that could indicate the level of organic pollution in the aquatic environment (Mishra et al., 2023). It measures the amount of dissolved oxygen necessary for the biodegradation of organic matter in the water system (Lemessa et al., 2023). The BOD (mg/l) levels for Mubo River were higher than the recommended range for both sampling periods. While at the Sobi Dam sampling sites, the BOD (mg/l) and the COD (mg/l) were within the permissible values (NESREA, 2011). The higher BOD (mg/l) and COD (mg/l) values recorded in the free-flowing Mubo River compared to the comparatively static Sobi Dam could be attributed to several factors, including its higher flow rate, shorter residence time for organic matters and susceptibility to non-point pollution sources (Moses et al., 2019).

Turbidity is one of the effective indicators of water quality monitoring because a sudden change in turbidity has been ascribed to the presence of a new pollution source in the water system (Zaghloul et al., 2019; Kusari et al., 2022). Therefore, the higher turbidity levels above the permissible limit of NESREA recorded in the rainy season in this study could be ascribed to the non-point sources of surface water pollution from flood water during the rainy season. However, the water quality turbidity level was within the recommended limit in the dry season.

The high levels of heavy metals in aquatic environments are considered harmful due to their hazardous and toxic effects on aquatic organisms and the human community (Zhang et al., 2023). However, the heavy metals evaluated in this study (Cd (mg/l), Cr (mg/l), Cu (mg/l), Zn (mg/l), and Pb (mg/l)) were within the recommended safe range of NESREA for surface water quality (NESREA, 2011).

The eight genera of phytoplankton recorded from the surface water under investigation belong to four major divisions of algae group; viz, Bacillariophyta (Cyclotella), Chlorophyta (Chlorella, Closterium, Chlamydomonas and Micractinium), Cyanophyta (Microcystis) and Euglenophyta (Euglena and Phacus) (Janse-van et al., 2006). The Shannon Diversity Index (H) is widely used in evaluating the community species diversity status as influenced by environmental pollution levels. According to Al-Tamimi and Al-Jumaily (2021), there is a clear correlation between aquatic ecosystems' species richness and pollution levels, with a lower diversity index indicating highly polluted water. The diversity of phytoplankton in the surface water samples under investigation was very low (H ≤ 1.99) following the Shannon diversity index classification (Baliton et al., 2020). This affirmed the work of Nwonumara et al. (2022), who reported that Shannon-Weiner diversity indices within the range of 1.50-3.40 signify low diversity richness. This implies a relatively high pollution level of the surface waters under investigation, which might account for the dominance and proliferation of a few phytoplankton species adapted to such conditions.

According to Palmer's index, surface water samples from the free-flowing Mubo Rivers were estimated to probably contain high levels of organic pollution during the two sampling periods (Zaky et al., 2018). However, only in the rainy season did Sobi Dam exhibit notable levels of organic pollution. This is corroborated by the physicochemical analysis of the water, which showed high levels of BOD (mg/l) and COD (mg/l) to indicate a probable high level of organic pollution level (Aguilar-Torrejon et al., 2023).

CONCLUSION

The Shannon diversity index and Palmers’ pollution index scores for phytoplankton assessment of the surface waters’ pollution status showed that the water samples from the free-flowing Mubo Rivers contained high levels of organic pollution in both sampling periods. While the relatively static Sobi Dam exhibits notable levels of organic pollution only during the rainy season. The relatively high turbidity, BOD (mg/l), and COD (mg/l) values support the index pollution scores and confirm the suitability of phytoplankton as baseline indicators for organic pollution in water.

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