Crude oil pollution indices and microbial sustainability protocol in the Iko River estuary

The terrain in Nigeria's Niger Delta has become severely polluted as a result of the expanding operations of petroleum firms. This region contains over 80% of the country's total crude oil reserves. Over time, the upstream and downstream operations of oil corporations in this area have resulted in the production of various pollutants, which have almost entirely ruined the terrestrial and marine habitats (Unimke et al. 2021). These pollutants include sewage, solid wastes, industrial effluents, gaseous emissions, and oil spills from the upstream and downstream operations of the petroleum industry.

The microbial community's ability to tolerate contamination by toxic substances has changed significantly as a result of the introduction of these petroleum-derived pollutants and other related industrial pollutants, such as plastics and hazardous metals (Grégoire et al. 2021). Microorganisms in the environment may be used to easily detect fluctuations and variations as any sudden changes in the physical or chemical environment are identified. This leads to an early phase that enables the population of the microbial community to adapt to changes in the environment (Varó et al. 2021). This first phase, also referred to as the ‘lag period’, allows the microbes to acquire the vital metabolic and physiological traits essential to their survival (Bijlani et al. 2021). This is a practical concept in diverse ecosystems (Irerhievwie et al. 2020).

In order to survive in harsh environments and generate new compounds that are uncommon in bacteria of terrestrial origin, marine microorganisms have evolved special metabolic and physiological capacities (Hassanshahian 2014). Estuaries as an ecosystem are threatened by a variety of human activities, including overfishing, pollution from extensive oil extraction, particularly in the Niger Delta, and other human endeavors. Sewage, coastal settlement, land removal, and many other factors pose a threat to them as well (Unimke et al. 2020). Estuaries concentrate things like pollution and sediments and are impacted by events that occur far upstream. Rivers receive land runoff, industrial, agricultural, and household garbage, which is then released into estuaries (Kaiser 2005). Contaminants such as plastics, pesticides, furans, dioxins, phenols, and heavy metals that do not disintegrate rapidly in the marine environment are often introduced.

A crucial component of biogeochemical cycles, energy flow, and microbial food webs is the water and sediment microbial community, particularly in an extensive productive ecosystem such as the Iko River estuary. Variability in physicochemistry and other biotic variables, which represent the innate environmental conditions, considerably influence the biodiversity of these microbial groupings (Urakawa et al. 1999; Zhang et al. 2008). As a result, both abrupt and slow changes in the pollutant profiles and nutrient availability in benthic–pelagic ecosystems can have an impact on the organization of the microbial community, which can then have an impact on the nutrient cycles and other populations that are connected. Both natural and man-made gradients, such as climate change, contamination from many sources, such as heavy metals and petroleum hydrocarbons, and enrichment, can significantly alter microbial communities. For example, coastal pollution has a significant impact on the growth of different microbial communities since it might restrict their processes.

In the aquatic ecosystem, microorganisms share resources such as food, housing, and microhabitat with other biotic elements. Innovations in gen-based techniques that provide detailed information about the phylogeny and distribution of unculturable microbial populations have greatly increased our understanding of the structure of microbial communities and the overall population dynamics in the aquatic environment (Enaigbe et al. 2020). Our understanding of the true composition, roles, and population dynamics of a given ecosystem's microbial community has significantly increased because of these molecular techniques.

Nigeria's oil industry's growth has resulted in significant environmental problems that have contaminated numerous habitats. Even while unintentional oil spills are uncommon, they have recently drawn a lot of attention and raised public concern. These accidents have the potential to kill living entities while seriously polluting the ocean and shoreline habitats. Acceptable techniques for managing oil pollution in terrestrial and aquatic ecosystems have been developed and used as a result of multiple oil leak occurrences in the Niger Delta. These techniques include biological techniques, which have been the focus of much discussion and some study in recent years, as well as physical and chemical techniques, which are pretty well established (Ekanem et al. 2023a, b). Biological methods can involve a variety of technologies, such as using plant material or straw as an oil absorbent, cleaning oiled surfaces with biosurfactants, coating surfaces with biological polymers to stop oil adhesion, and adding materials to promote the microbiological biodegradation of oil. Hydrocarbon degradation pathways must be understood in order to create bioremediation systems (Unimke et al. 2024).

The evaluation of crude oil, physicochemical, and microbiological pollution indicators in the Iko River estuary, as well as the striving for ecosystem sustainability methodologies, are the objectives of this study.

The Iko River estuary, which is located between latitudes 4°30°N and 4°45°N and between longitudes 7°30°E and 8°45°E, was the study research site. Three sampling sites within a 3-km radius were considered: Okoro, Kampa, and Emeroke. Southeast Nigeria's Eastern Obolo region has an open connection to the Atlantic Ocean. It is among the largest fishing villages along the Nigerian coast. It is situated in the mangrove forest zone of the Nigerian Niger Delta. The significant degree of environmental deterioration resulting mostly from petroleum activities and other related anthropogenic factors can be attributed to the area's extensive oil exploration.

In compliance with the site-specific health and safety plan, a general site survey was conducted at the study site before admission. All of the sampling sites and points were marked and identified using stakes, flagging, and buoys. Several site parameters were taken into account while choosing sampling locations and points, including flow regime, basin morphometry, sediment properties, depth of the underlying aqueous layer, pollutant source, and amount and type of contamination. Surface impediments, property boundaries, and site access were taken into consideration while adjusting the suggested positions. Tidal and intertidal water samples were aseptically collected using a water sampler and placed into sterile plastic bottles. The holding bottles were rinsed before collection (Benson et al. 2023). With a decontaminated sampling grab, the desired thickness and volume of the benthic sediment samples from the sampling locations were obtained. Samples were collected from three different stations: upstream (Okoro), midstream (Kampa), and downstream (Emeroke).

After being collected, the sediment samples were placed in plastic bags for trace element analysis, in paper and deep-frozen aluminum boxes, and in cleaned aluminum boxes for organic analysis. Aseptically obtained water samples from intertidal and tidal regions were put in sterile plastic bottles and allowed to remain frozen for a long time. Following collection, the samples were taken to the laboratory and chilled at around 4 °C to avoid bacterial degradation in the event of petroleum hydrocarbon analysis and other microbial activities.

An aliquot was taken from the bulk sample prior to analysis, and the samples were thoroughly homogenized before the 10 g aliquot (for organic) or the 1–2 g aliquot (for trace metal) was collected for extraction in order to ensure that the results were representative of the total. Using recognized procedures, composite samples of benthic sediment and tidal and intertidal water collected from several sampling sites were examined for hazardous metals and physicochemical traits.

The soil and water samples were collected, transported, stored, and analyzed using standard microbiological techniques. Within 24–48 h of collection, analysis was completed (Unimke et al. 2021).

Standard microbiological methods, media, and reagents were employed in the survey of the different microbial components from the various stations and microhabitats (Unimke et al. 2021). These were:

• (a) total heterotrophic bacteria (THB),

• (b) total fungi (TF),

• (c) crude oil-utilizing bacteria (CUB), and

• (d) crude oil-utilizing fungi (CUF).

The media employed in the investigation of the different microbial physiological groups were: nutrient agar (NA), Sabouraud dextrose agar (SDA), mineral salt medium (MSM), and other related media used primarily for preliminary investigations. The preparation of each medium was done according to its manufacturer's instructions and directives.

Pour plate techniques were used to survey the proliferation of the various microbial groups (Enaigbe et al. 2020). To stop fungal contaminants from growing, 50 μg mL⁻¹ of nystatin was added to the NA medium. Using the pour plate technique and SDA, a fungal survey was conducted. Approximately 50 μg mL⁻¹ of streptomycin was added to the solution to stop the bacteria from growing (Ekanem et al. 2023a, b). The number of microbial colonies was counted after the infected plates had been sufficiently incubated. NA plates were incubated at 28 °C for 24 h, while SDA plates were incubated for 3 days at room temperature.

After the proper incubation period as described previously, outstanding colonies were subjected to further investigations. Repeated sub-culturing was carried out on bacteria colonies before stocking. SDA was used for sub-culturing the fungal isolates.

A pour plate technique was used to survey the microorganisms that break down crude oil utilizing the vapor-phase transfer method using MSM (Unimke et al. 2020; Ekanem et al. 2023a, b). Antibiotics were sufficiently added to the conditions for the survey of both bacteria and fungi that use crude oil in order to stop each organism under investigation from growing backward. Millipore filtering was used to sterilize the crude oil used in the survey. Prior to evaluation, the plates used in this study were incubated for 5 days at room temperature.

The various bacteria species were identified and characterized using molecular microbiological techniques (Enaigbe et al. 2020).

Many physicochemical parameters (fast changing parameters) of the sediment and water samples such as temperature, pH, and conductivity were determined in situ.

Temperature was measured in situ, using a thermometer and thermostat by means of a thermocouple electrode calibrated in 0.2 °C units from 0 to 100 °C. The pH of water samples was determined through direct reading using a pH meter, while a glass electrode pH meter was applied in the determination of the pH of the sediment samples (Grégoire et al. 2021).

Percentage salinity of the water samples was determined from silver thiourea (AgTu) extracts and 0.1 M silver nitrate (AgNO₃) titration using potassium chromate as an indicator and calculated as total water-soluble salts (chloride and sulfates) (Keskinen et al. 2024) and also by direct reading using a salinity meter.

Using a dissolved oxygen (DO) meter, the amount of DO in the water samples was directly measured. A conductivity meter was used to detect the electrical conductivity (EC) of water samples on site, and a conductivity bridge was used to evaluate the electrical conductivity of sediments in the extract made from sediment:water suspension (Quan et al. 2022; Coggon et al. 2024). Using a glass fiber ‘GF/C’ grade filter and a total dissolved solids (TDS) meter, the total dissolved solids were directly measured. However, a DO meter was also used to directly measure biological oxygen demand (BOD), for confirmation.

The methods proposed by Rana et al. (2021) were used to examine the amount of phosphorus that was available. These steps involved measuring 25 mL of water samples into 50 mL volumetric flasks, adding 10 mL of varadatemelybdate reagent, and diluting it to volume with deionized water. In a 50 mL volumetric flask, 20 mL of reagent was made up to volume to create a reagent blank. For color development, the solutions were combined and left to stand for roughly 10 m. The absorbance was then read at 470 nm using a visible spectrophotometer. Total nitrogen was determined by the microkjeldahl digestion and distillation method as described by Rana et al. (2021) in which 10 mL of the water sample was transferred into different 25 mL standard flasks and 2 mL of Brucine reagent was added, then 10 mL of concentrated H₂SO₄ was added rapidly. Mixing was done for about 30 s and allowed to stand for 5 m. The flasks were then set in cold water for about 5 m and filled up to volume with deionized water. The absorbance was read at 470 nm using a visible spectrophotometer.

The bases were extracted with neutral NH₄OAO. Calcium and magnesium were determined in the extract by EDTA titration, and potassium and sodium, by the use of flame photometer.

The hydrometer method, as outlined by Chapuis (2023) and Joseph et al. (2024), was used to determine the particle size distribution of the sediment samples. Particles larger than 63 μm were evaluated after sufficient sifting, while those smaller than that were examined using a hydrometer and calgon as a displacing agent. The following protocols were used:

• i. The hydrometer value for 40 s indicated the amount of silt and clay in suspension since the sand settled to the bottom of the cylinder in that time.

• ii. By deducting the corrected hydrometer value from the sample's total weight, the weight of the sand was determined:

  

• iii. To determine the percentage clay in the sample, the suspension was re-shaken and the hydrometer reading taken at the end of 2 h, and corrected.

• iv. The corrected hydrometer reading therefore represents the gram of clay in the sample:

  
• v. The percent silt in the sample was obtained by difference as follows:

  

Infrared (IR) spectroscopy was used to assess the total petroleum hydrocarbon (TPH) content and its fractions, PAH and BTEX. FTIR spectrometer-equipped IR spectroscopy experiment: Deuterated triglycine sulfate (DTGS) was detected using a PerkinElmer Spectrum 2 with a wavelength of approximately 4,000–400 cm⁻¹ and a resolution of 4 cm⁻¹. Attenuated total reflectance (ATR) crystals were used to analyze a few microliters of the samples, with 16 scans per sample. A blank scan of a clean ATR crystal was used for background scanning, and automated software was used for baseline correction.

The atomic absorption spectrophotometer (Model UNICAM 939) was used to analyze the amounts of heavy metals in the different samples from the various microhabitats at a wavelength range of 248.3 to 324.8 nm. To prevent precipitation, samples were acidified with 2% v/v concentrated nitric acid after being diluted with deionized water, and the flow rate was adjusted in accordance with manufacturer guidelines. When matrix interference was substantial, chemical modifiers such as magnesium nitrate or palladium were employed. Analyte concentrations ranging from 1 to 10 ppm were used for standard calibrations, and the instrument's software was used to confirm the detection limit.

DNA extraction and Blast was performed at the Department of Medical Laboratory Science, College of Medicine University of Lagos, Nigeria. Sanger Sequencing was done at Iqbaba Biotech/South Africa.

Bacteria DNA was extracted from bacterial colonies sub-cultured on sterile nutrient broth. DNA extraction from broth samples was performed using a NORGEN DNA extraction kit (Model 24700, NORGEN CANADA) according to the manufacturer's instructions. This method extracts quality DNA from bacteria, fungi, and Archea (methanogens). The genomic DNA was extracted using 200 μL of broth sample (containing approximately 3 × 10⁶ cells) and transferred using a micropipette in an aseptic condition into a 1.5 μL tube. The tube was centrifuged at 200 × g (approximately 2,000 RPM) for 10 min. The supernatant was discarded. This was followed by the addition of 200 μL Digestion Buffer A to cell pellets, then mixed gently with the addition of RNase to the cell suspension. Following this, 12 μL of Proteinase K was also added to the suspension. The mixture was vortexed gently to homogenize the contents.

The suspension was then incubated at 55 °C for 1 h. After incubation, 200 μL of Buffer K was added to the lysate, followed by another process of mixing by vortexing. Then, 100% ethanol was added and the solution was further mixed before DNA binding to the column. Exactly 800 μL of the mixture from above was added to a spin column in a collection tube and centrifuged at 14,000 × g for 2 min. Flow through from the collection tube was discarded and this particular step was repeated with the remaining filtrate. Then, 500 μL of Wash Solution A was thereafter added to the spin column in a new collection tube and centrifuged again at 14,000 × g for 1 min after which 500 μL of the same Wash Solution A was added to the spin column and centrifuged at 10,000 × g for 1 min in order to completely dry the column. The spin column was transferred into a clean 1.7 mL elution tube and 200 μL of DNA Elution Buffer B was added directly to the center of the resin bed, which was centrifuged at 14,000 × g for 2 m to elute the DNA. The template DNA was then used for PCR and DNA sequencing.

The PCR reaction was performed on the extracted DNA samples using Universal Degenerate Primers 27F.1 Forward 5′AGRGTTTGATCMTGGCTCAG 3 and 1492R reverse 5′GGTTACCTTGTTACGACTT3′ (Pacific Biosciences, California Inc, USA) that amplifies the entire 16s variable region at annealing temperature of 58. Similarly, universal degenerate primers were used to amplify the ribosomal internal transcribed spacer (ITS). The primer sequences were ITS1: 5′TCC GTA GGT GAA CCT TGC GG 3 and ITS4 5′TCC TCC GCT TAT TGA TAT GC 3′.

All the replicate readings for the various treatments and analyses were subjected to one-way factor analysis of variance (ANOVA). The results were presented as mean plus or minus standard deviation (Mean ± SD). Mean values with a probability index less than 0.05 (p < 0.05) were considered significant at a 95% level of significance while those greater than 0.05 were non-significant (p > 0.05).

From the results obtained, the mean values of microbial counts for the various parameters and microhabitats were 8.0 ± 0.98 (×10⁷), 2.34 ± 0.10 (×10⁷), and 2.36 ± 0.92 (×10⁷) – THB, 1.46 ± 0.18 (×10⁶), 1.56 ± 0.10 (×10⁶), and 1.76 ± 0.2 (×10⁶) – CUB, 1.39 ± 0.18 (×10⁶), 1.62 ± 0.10 (×10⁶), and 1.69 ± 0.18 (×10⁶) – TF, and 1.03 ± 0.50 (×10⁵), 5.2 ± 0.54 (×10⁴), and 1.24 ± 0.18 (×10⁵) – CUF for tidal water, respectively, as shown in Table 1. For intertidal water samples, the mean counts were 2.46 ± 0.19 (×10⁷), 2.35 ± 0.58 (×10⁷), and 2.31 ± 0.22 (×10⁷) – THB, 1.51 ± 0.22 (×10⁶), 1.57 ± 0.50 (×10⁶), and 1.51 ± 0.12 (×10⁶) – CUB, 1.21 ± 0.92 (×10⁶), 1.73 ± 0.64 (×10⁶), and 1.52 ± 0.28 (×10⁶) – TF, and 1.19 ± 0.16 (×10⁵), 5.4 ± 0.56 (×10⁴), and 6.7 ± 0.44 (×10⁴) – CUF, respectively.

The physicochemical parameters analyzed for tidal and intertidal water samples were temperature (°C), pH, electrical conductivity (μS/cm), DO (mg/L), BOD (mg/L), total dissolved solids (mg/L), salinity (ppt), turbidity (NTU), total hardness, phosphate (mg/L), calcium (mg/L), magnesium (mg/L), sodium (mg/L), potassium (mg/L), acidity (mg/L), sulfate (mg/L), nitrate (mg/L), nitrite (mg/L), chloride (mg/L), ammonium (mg/L), and total petroleum hydrocarbon (mg/L). The results showed that there was no significant difference (p > 0.05) in the mean values of each parameter within a given microhabitat. However, significant differences in mean values were observed from one microhabitat to the other.

From the results obtained, the range of the mean values of physicochemical parameters in the tidal and intertidal water samples were temperature 23.1–24. 9, pH 5.5–6.6, electrical conductivity 1,800–2,500, total dissolved solids 1,200–2,300, DO 5.7–14.0, BOD 3.1–22.8, salinity 910–4,300, turbidity 16.9–18.8, and total hardness 103.5–107.5. Others were phosphate 5.4–10.8, Ca 82.3–86.2. Mg 22.8–46.2, Na 752–776, K 188–104, acidity 1.9–2.6, sulfate 159–175, nitrate 23.1–24.9, nitrite 0.21–0.41, chloride 496–588, and NH₄ 0.21–0.24, while total petroleum content ranged from 36.9 to 41.8, as presented in Table 2.

The range of the mean values of physicochemical parameters obtained in the benthic sediment were pH 5.9–6.9, electrical conductivity 1,200–1,300, total dissolved solids 500–700, available phosphorus 1.5–3.1, and total nitrogen 0.4–0.5. The mean ranges for exchangeable bases were calcium (Ca) 4.5–5.9, magnesium (Mg) 3.1–4.7, sodium (Na) 0.51–0.58, and potassium (K) 0.41–0.47. Other parameters were total organic carbon (TOC) 1.2–1.5, sulfide 1.1–1.5, exchangeable acidity (EA) 2.4–2.5, effective cation exchange capacity (ECEC) 11.0–13.0, and base saturation 77–79, as shown in Table 3. However, the range of the particle size distribution was sand 70–75, silt 12–20, and clay 5–10, while total hydrocarbon content ranged from 250 to 300.

Table 4 displays the findings from this investigation about the hydrocarbon and heavy metal analyses of the soil and water samples. Copper (Cu), cobalt (Co), manganese (Mn), nickel (Ni), lead (Pb), arsenic (As), zinc (Zn), chromium (Cr), and vanadium (V) were the heavy metals examined, and TPH, PAH, and BTEX were the hydrocarbon fractions. The study results for the tidal and intertidal water samples showed that there was no significant difference (p > 0.05) in the mean values of any parameter within a particular microhabitat; however, Table 4 indicates that there was a significant difference (p < 0.05) in the mean values between microhabitats. By contrast, the mean values of benthic sediment samples were substantially (p < 0.05) greater than those of tidal and intertidal water samples.

From the results obtained in the study, the mean values of heavy metals and hydrocarbons content in the tidal water, intertidal water, and benthic sediment samples range as follows: Cu 0.19–1.08, Co 0.04–0.59, Mn 0.01–0.03, Ni 1.01–1.04, Pb 0.01–0.05, As 0.11–0.13, Zn 1.14–2.11, Cr 0.06–0.88, and V 0.03–0.18, while hydrocarbon fractions were TPH 36.9–296.1, PAH 21.6–188.4, and BTEX 12.9–115.4 (Table 4). The ANOVA for the mean values of heavy metals and hydrocarbon fractions are shown in Figures 4–6 and 7–9 respectively.

As the current work has shown, these varied microbial diversities and the related dynamics in contaminated ecosystems, such as the Iko River estuary, present a significant possibility for bioremediation solutions.

Additionally, the study found that compared with tidal and intertidal water samples, sediment samples from all sites produced considerably (p < 0.05) higher THB counts. Comparable patterns were noted for CUB, TF, and CUF, in that order. Regarding the mean values of upstream, midstream, and downstream, respectively, there was no significant difference (p > 0.05). The densities of microorganisms that use crude oil were found to be considerably (p < 0.05) lower in all microhabitats and stations when compared with the overall heterotrophic counts. Additionally, the mean counts of THB, CUB, TF, and CUF within a microhabitat did not differ significantly (p > 0.05). The total fungal counts in relation to the THB counts were significantly (p < 0.05) low.

Generally, the high level of microbial proliferation in the estuary was mainly due to the constant inflow of petroleum-based contaminants and other industrial polluting agents resulting in an enriched microbial ecosystem with the required capabilities of surviving toxic and stressed environments.

The average density of heterotrophic and crude oil-consuming microorganisms in the sediment is generally higher than that of water. This could be as noted by Bussmann et al. (2024) and Ngamcharungchit et al. (2023), microorganisms prefer to cling to and grow on the surface of sediments, acting as a sink. Additionally, according to Bussmann et al. (2024), humic compounds and other components in the sediment phase may act as nutrition for microbes, promoting their proliferation. The average density of heterotrophic and crude oil-using microorganisms in the sediment is generally higher than that of water. According to Bonnineau et al. (2021) and Booth et al. (2023), microorganisms have a tendency to adhere to and proliferate on the surface of sediments, which may be the cause of this. The humic materials and other components in the sediment phase may act as nutrition for microorganisms, promoting their proliferation, according to Deng et al. (2023). The increased concentrations of hydrocarbonoclastic microorganisms in sediments as opposed to water may be due to the presence of crude oil in the microhabitat and the low heterotrophic activity of these oil degraders. It indicates that the sediments harbor a high degree of culturable microbial populations with low potential for oil degradation or high preference for other substrates.

Both riverine and marine elements, such as freshwater flows and sediments, as well as saline water inflows and outflows, have an impact on estuaries. Between river habitats and the open ocean, they act as a transitory zone.

Water bodies undergo temperature fluctuations in addition to the typical weather cycles. The soil samples, intertidal water, and tidal water all had mesophilic temperature levels, per Qin & Tao's (2022) study. pH is a measure of the amount of free hydrogen ions in water and is also known as the negative logarithm of the hydrogen ion concentration in a certain sample or medium. Throughout the study, all of the microhabitats in the Iko River estuary had somewhat acidic pH values. The study's findings demonstrated the estuary's level of pollution, with the sediments being the most contaminated microhabitat. The fact that sediments function as sinks in the marine environment is reflected in this outcome. These pH readings fall between the 6.5 and 8.5 range that the WHO recommends, and they also concur with the Shen et al. (2020) assessment on the Niger Delta mangrove environment. Since pH affects the activity of almost all enzymes, hormones, and proteins that regulate every facet of metabolism, growth, and development, it is crucial to the activity and biodiversity of aquatic life.

The findings showed that both the tidal and intertidal water's conductivity levels were comparatively high and comparable. This indicates that the environment contains significant concentrations of main ions and total dissolved solids. The measured conductivity levels are consistent with the findings of the Gindorf report (2020), which states that most bodies of water have conductivities between 10 and 1,000 μS/cm; however, they can go above 1,000 μS/cm in certain cases, such as contaminated waters or those that get a lot of land runoff.

The findings show considerably higher mean amounts of nutritional salts (p < 0.05). This could be explained by the amount of pollution caused by crude oil, which has been linked to an increase in the salinity and nutritional salts in aquatic systems. It may also be attributed to the diversity of the estuarine ecosystem and the allocthonous sources of nutrients into the estuaries (Bussmann et al. 2024).

A significant drop in oxygen concentration, occasionally leading to anoxia, can occur when untreated household or industrial wastes that include a lot of organic matter are dumped into rivers (Rana et al. 2021). The results of this study showed that there were substantial (p < 0.05) differences in the amounts of organic matter in the sediment between stations and microhabitats. TOC was another metric used to quantify organic materials. Because the levels are below 12% w/w of sediments (levels above 12% indicate that the sediment materials are from decomposed organic sources), the results showed that the sediment materials are produced from mineral sources. Location has a substantial (p < 0.05) impact on the concentrations of exchangeable bases (Ca, Mg, K, and Na) in sediment samples across all stations and microhabitats. Since these bases are found in sediment, it is likely that they are significant suppliers of micronutrients. The micronutrients Ca, Mg, K, and Na are abundant natural elements that are essential for preserving the ideal primary and secondary productivity of the marine and brackish ecosystems (Lainela et al. 2024). The current study's findings appear to support the report of Rajkaran et al. (2020), which states that a variety of factors contribute to the degradation of estuaries, including eutrophication from excessive nutrients from sewage and animal wastes, pollutants such as heavy metals, radionuclides, and hydrocarbons, sedimentation from soil erosion, deforestation, overgrazing, overfishing, drainage, and filling of wetlands.

At p < 0.01, the mean amounts of heavy metals found in the benthic sediment were substantially greater than those found in the tidal and intertidal water samples. All of the heavy metals under investigation were found at some point during the investigation.

In comparison to tidal and intertidal water samples, sediments had relatively higher quantities of heavy metals. The sediment samples used in this study had extremely substantial levels of TPH. Despite a significant fluctuation in TPH found in tidal and intertidal water samples, there is no appreciable change in the amounts. A material concentration resulting from a drop in water volume may be the cause of this. Similar patterns were found in the TPH component analysis results (PAH and BTEX), with sediments containing significantly higher quantities than tidal and intertidal water samples.

Sediment samples from all sites produced significantly (p < 0.05) higher THB counts than tidal and intertidal water samples, the study found. For CUB, TF, and CUF, in that order, comparable trends were seen. Upstream, midstream, and downstream mean values did not differ significantly (p > 0.05), although there were substantial (p < 0.05) differences between locations. The results indicated that the mean counts of THB, CUB, TF, and CUF were significantly different (p < 0.05) from the wet season to the dry season, but not significantly different (p > 0.05) within each month of a season. The densities of crude oil-utilizing microorganisms were significantly (p < 0.05) low in comparison to total heterotrophic counts in all microhabitats and stations. The total fungal counts in relation to the THB counts were significantly (p < 0.05) low.

In general, the continuous input of pollutants derived from petroleum and other industrial pollutants was the primary cause of the high degree of microbial proliferation in the estuary. This led to an enriched microbial ecology that possessed the necessary attributes to survive in a toxic and stressful environment. When their chemical or physical surroundings are abruptly changed, microorganisms are susceptible to changes and variations. As a result, the microbial community takes some time to adjust to the new circumstances. From this work, the development of a standardized microbiological and physicochemical reference material in the Iko River estuary has demonstrated that the area's anthropogenic activities, including oil exploration and exploitation as well as other industrial and navigational processes, are the primary cause of the heavy metal and petroleum hydrocarbon pollution in the estuary. This research has evaluated the microbial community structure, resilience and adaptation to environmental changes, and sustainability and microbial cooperation resulting in collective metabolism toward bioremediation of the marine environment during stress periods such as petroleum pollution.

From the research, a standardized microbiological and physicochemical relationship has been established revealing the anthropogenic and natural influences in the estuary such as oil exploration and exploitation and other navigational and industrial processes.

The authors declare that funds, grants, and other support were received during the preparation of this paper.

Conceptualization: A.A.U. Both authors (A.A.U. and A.A.I.) contributed fully to the literature search, experimental design, analysis, and writing of the first draft. Each author handled a specific section in the paper. A.A.I. supervised the work. Preparation, proofreading, and revision were handled by A.A.U.

Tertiary Education Trust Fund (TetFund) sponsored this research.

We sincerely appreciate all authors and other support staff and various institutions who contributed immensely toward the success of this research.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.