Abundance and diversity of benthic macroinvertebrates as bioindicators of water quality in KuliyaRiver at Areka town southern Ethiopia

doi:10.21203/rs.3.rs-8275690/v1

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Abundance and diversity of benthic macroinvertebrates as bioindicators of water quality in KuliyaRiver at Areka town southern Ethiopia

https://doi.org/10.21203/rs.3.rs-8275690/v1

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In most aquatic environments, macroinvertebrates are used as biological tools to assess the impact of anthropogenic activities and pollutant levels. The present investigate was conductedon Kuliya River of Areka town in the southern Ethiopia between January to June 2023 to study thequality of water by using the distribution and abundance of benthic macroinvertebrates along with their physico chemical parameters.Three sampling sites were selected across the river, each differ from the other at least by 5 km apart based on their anthropogenic activities. Water samples were collected for both benthic macroinvertebratesby using kick and multi-habitat sampling methodswhereasselected physicochemical parameters including DO, temperature, pH, TDS, phosphates, nitrates, nitrites BOD, COD were measured according to protocols. Most of the selected physicochemical parameters except ammonia and ammonium showed a significant difference.A total of 1082 macroinvertebrate individuals, belonging to 18 families, 7 orders, and 1 class were identified. The 533 families from the pollution-tolerant order Diptera were found at site 3 indicating they were highly abundant there. In contrast, 244 families from the EPT (Ephemeroptera, Plecoptera, and Trichoptera) order were found at site 1, suggesting they were more abundant at site 1 than at site 3. This indicates that site 3 was highly impacted by anthropogenic activities. The Hilsenhoff Family biotic index values were 3.80, 7.04, and 8.18 at sites 1, 2, and 3, respectively, indicating possible slight organic pollution, significant organic pollution, and highly significant organic pollution. The distribution of macroinvertebrates had showed a significant difference. Similarly, the Shannon-Wiener diversity index values were 2.35, 1.72, and 0.99 at Sites 1, 2, and 3.The association between macroinvertebrates and physicochemical parameters was demonstrated by canonical correspondence analysis showing a negative correlation with most-pollution sensitive macroinvertebrates. This indicated that the Kuliya River is under anthropogenic stress for whichproper water quality management and continuous monitoring is to be made.

Abundance

Areka

Bioindicators

Kuliya River

Macroinvertebrates

physicochemical parameters

Water quality

Benthic macroinvertebrates perform important functions, including the decomposition of organic matter, forming the basis of many aquatic food chains, and they are capable of living in any freshwater ecosystem as long as the water is not deep and not extremely polluted (Chamia and Kutuny, 2022). Their abundance and distribution of macroinvertebrates change with prevailing pollution stress and can be used as a biological criterion for assessing the effects of anthropogenic activities on the quality of aquatic ecosystem (Iyiola and Asiedu, 2020).

In Africa degradation of aquatic ecosystems has also been reported through various studies undertaken to restore them (Nyambura and Abuyeka, 2023). Freshwater pollution by human activities is becoming a matter of urgent concern, threatening environmental productivity, sustainability, and further social and economic development in sub Saharan Africa (Liman, 2021). Pollution and other human activities are degrading South African rivers, impacting macroinvertebrate natural habitats and resulting in a decrease in species diversity and abundance (Matlou et al., 2017; Rasifudi et al., 2018). In East Africa, population growth is increasing, and this is leads to accelerated deforestation, urbanization, industrial expansion, and commercial irrigation or agricultural activities that threaten freshwater bodies.Like other developing East African countries, Ethiopia is experiencing the deterioration of its river quality more and more, which hurts people's health, raises the cost of water treatment, and reduces river fisheries' yields (Misgana Dabessa et al., 2021).The practice of using benthic macroinvertebrates for the assessment and monitoring of freshwater ecosystem conditions is mostly uncommon throughout East Africa, including Ethiopia(Workiye Worie et al., 2020). The Kuliya River is one of the many rivers in south Ethiopia that have been impacted by the various anthropogenic activities. However, no previous research has been conducted to assess the status of this river using benthic macroinvertebrates as bioindicators of water quality.

Description of the study area

Present study was carried outbetween January to May 2023 on a perennial River Kuliyain the Areka town ofWolaita zone under southern Ethiopiasituated between 7°4'08" N Latitude and 37°42'41" E Longitude with an elevation of 1774 meters (Table 1). The mean annual temperature is around 20–21, with cooler nights and warmer daytime conditions. The annual rainfall of the town ranges between 1300 and 1900mm most of which occurs from April to August, while December and January are typically the driest months. Originating from the highland areas of Damota Mountain and passing through GurumoWoyde and GurumoKoysha localities, River Kuliyafacing a lot of stress due to heavy anthropogenic activities including unsafe agricultural practices like unsafe irrigation activities directly releasing nitrates and phosphates from the farmland to the river, deposits from slaughterhouses, washing of vehicles, release of municipal garbage, sand mining and clearance of riparian vegetation around the river. The map of the study area is shown in below in the Fig. 1.

Table 1

Descriptions of the sampling sites
Sampling sites	Coordinates	Descriptions of the sampling sites
Site1 (\|Ukara site): the upstream one	7°2'59"N and 37°42'30"E	Less population density, less contaminant, good water shading, rich riparian vegetation cover, lack of urbanization and no industrial influence with wide forest areas located at 1770 msl.
Site 2 (Dubomeshageriya site) or the mid-stream	7°2'59"N and 37°42'30"E	Agricultural activities close to the river, excessive grazing, bathing, and solid waste disposal from the town. Livestock watering and heavy washing activities with an altitude of 1751 msl.
Site 3 (Kera site) or the down stream	7°4'40"N and 37°42'6"E	The disposal of leftover organic waste, washing of vehicles in the river and in town, liquid residues from slaughterhouses, domestic waste municipal runoff at an altitude of 1723 msl.

Physico-chemical parameters

Analysis of selected physicochemical parameters such as temperature (WT), dissolved oxygen (DO), hydrogen ion concentration (pH) and total dissolved solids (TDS) were tested in situ, whereas for the remaining parameters namelybiological oxygen demand (BOD), chemical oxygen demand (COD), phosphates (PO₄³⁻), electrical conductivity (EC), turbidity (Turb.), ammonia (NH₃), ammonium (NH₄⁺), nitrite (NO₂⁻), nitrate (NO₃⁻), total alkalinity (TA)water samples were carried to the laboratory following appropriate procedures (APHA, 2005). Nitrate and phosphate were tested using the Wagtech photometer (Model 7100). Reagents such as Nitra test tablets and Nitra test powder were used to test nitrate. The reagents used to test phosphate were Phosphate No. 1 LR (lower range) and Phosphate No. 2 LR (lower range) tablets. Other parameters, like TA, were tested with Alkaphot tablets, and NH₃ was tested with ammonia No. 1 and No.2 tablets using a Wagtech International photometer (Model 7100). BOD and COD were tested using the Palin test method with permanganate value tablets. Parameters such as EC, turbidity, and pH were measured using a conductivity meter from Wagtech International (Model 1573720), a turbidity meter (Model T-100), and a pH meter (Model pHS 250W), respectively. The DO test was conducted using the Winkler method on site and the remaining steps were completed using the titration method in the laboratory.

Plankton sampling

Collection of water samples for the benthic macroinvertebrates was done using a D-frame net with a mesh size of 500µm with a diameter of 30 x 28 cmin the littoral and sub-littoral area. Water was collected facing in the opposite direction of the water current from all three sampling sites by using the kick sampling method extending up to 100m along the river. The species were then passed through a sieve of 300µm mesh size, rinsed well to remove the contaminants later placed on white trays for identification. Those that were clearly visible were identified, counted, and recorded whereas the smaller ones were identified using a dissecting microscope (EU-1926182-2019 model).Their taxonomic identification was then made to the family level using standard keys (Bouchard et al., 2004; Gerber and Gabriel, 2002; Gooderham and Tsyrlin, 2002; Voshell, 2002). After identification and recording, the species were preserved in a bottle containing 70% ethanol.

Data analysis

The collected data related to macroinvertebrates and the physicochemical parameters were statistically analyzed using SPSS software version 21, PAST software version 4.13, and Microsoft Excel 2010. One way ANOVA (with post hoc in Tukey HSD test) was used to test the significance of differences in values of physicochemical parameters and distribution patterns of benthic macroinvertebrates. Canonical correspondence analysis (CCA) was used to study the interaction between species abundance and parameters by using PAST version 4.13 software. The benthic macroinvertebrate community structure was analyzed using biodiversity indices like Shannon-Wiener diversity index (H'), Simpson diversity index (D′), Margalef diversity index (dMg), evenness index (J), dominance index (D), and Hilsenhoff Family-Biotic Index (H-FBI).The index values of H-FBI were classified into seven categories, as indicated by Hilsenhoff, 1987 (Table 2).

Table 2

Range for of H - FBI value
Biotic index	water quality	Degree in organic pollution
0.00-3.50	Excellent	No apparent pollution
3.51–4.50	Very good	slight organic pollution
4.51–5.50	Good	Some organic pollution
5.51–6.50	Fair	Fair level of organic pollution
6.51–7.50	Fairly poor	Significant pollution
7.51–8.50	Poor	Very high pollution
8.51-10.00	Very poor	Strong organic pollution

Physicochemical parameters

The recorded mean values of all the physic chemical parameters are shown in the Table 3 along with respected figures and histograms in following pages. Mean temperatures for site 1(S 1), Site 2(S2), and Site 3(S3) were 19.27 ± 1.03°C, 21.7 ± 0.87°C, and 23.02 ± 0.57°C, respectively. The recorded electrical conductivity (EC) values in the Kuliya River ranged from 134.77 ± 3.28 µS/cm at s-1 to 236.47 ± 0.57 µS/cm at s-3, (P < 0.05). the lowest EC value (134.77 ± 3.28 µS/cm) was recorded at site 1, while the significantly highest value (236.47 ± 0.57 µS/cm) was observed at site 3.The recorded mean value of dissolved oxygen (DO) between 7.07 ± 0.17 mg/l at site 1 to 4.07 ± 0.44 mg/l at site 3. The measured values of DO in the Kuliya River decreased from the upstream to downstream site (P < 0.05).

The total dissolved solids (TDS) ranged from 88.90 ± 2.18 mg/l at site 1 to 156.02 ± 0.36 mg/l at site 3, (P < 0.05). The recorded pH values ranged from 7.05 ± 0.03 at site 1 to 8.87 ± 0.03 at site 3, (P < 0.05). The recorded values of NH₃ in Kuliya River ranged from 0.42 ± 0.15mg/l at site 1 to 0.55 ± 0.19 mg/l at site 3, (P > 0.05). Similarly, the recorded values of NH₄⁺ ranged from 0.45 ± 0.16 mg/l at Site 1 to 0.60 ± 0.21 mg/l at site 3; (P > 0.05).The recorded value of BOD ranged from 92.5 ± 4.08 mg/l at site 1 to 156.87 ± 4.26 mg/l at site 3, (P < 0.05). The value of COD ranged from 185 ± 8.16 mg/l at site 1 to 313.75 ± 8.53 mg/l at site 3, (P < 0.05).The distribution of macroinvertebrate species recorded at the study sites (Table 3).

Nutrients such as phosphates, nitrites, and nitrates generally increased from upstream sites to downstream sites, (P < 0.05) (Table 3). The highest recorded values of nitrites and nitrates (2.21 ± 0.02 mg/l and 8.82 ± 0.07 mg/l) were observed at site 3, followed by 1.35 ± 0.03 mg/l and 7.47 ± 0.11 mg/l at site 2, and the lowest values of 1.24 ± 0.017 mg/l and 5.22 ± 0.05 mg/l at site 1, respectively (Table 3). A significantly high value of total alkalinity (TA) of 292 ± 6.37 mg/l was recorded at site 3 as shown in Table 3.In the Kuliya River, relatively low mean values of physicochemical parameters were recoded, including turbidity, total dissolved solids (TDS), and electrical conductivity (EC) at the less disturbed upstream site compared to downstream sites. In more disturbed sites like the midstream and downstream areas, there were generally higher levels of turbidity, TDS, and EC values (Table 3).

Table 3

showing mean values of physicochemical parameters
Parameters	Units	Site 1	Site 2	Site 3	WHO Standards
pH	-	7.05 ± 0.03^a	7.96 ± 0.02^b	8.87 ± 0.03^ac	6.5–8.5
WT	⁰C	19.27 ± 1.03^b	21.7 ± 0.87^ac	23.02 ± 0.57^a	15–35
EC	µS/cm	134.77 ± 3.28^a	222.02 ± 1.13^ab	236.47 ± 0.57^ac	500
Turb.	NTU	20.62 ± 2.86^a	30.45 ± 1.03^b	35.15 ± 0.89^c	7
TDS	mg/l	88.9 ± 2.18^ac	146.5 ± 0.76^a	156.02 ± 0.36^b	500
DO	mg/l	7.07 ± 0.17^ab	5.75 ± 0.26^a	4.075 ± 0.44^c	5
BOD	mg/l	92.5 ± 4.08^a	136.87 ± 4.26^ac	156.87 ± 4.26^c	-
COD	mg/l	185 ± 8.16^ab	273.75 ± 8.53^ac	313.75 ± 8.53^b	-
TA	mg/l	128.75 ± 13.45^a	210 ± 8.64^ab	292 ± 6.37^ac	75
NO₂⁻	mg/l	1.24 ± 0.017^b	1.35 ± 0.03^ac	2.21 ± 0.02^a	3
NO₃⁻	mg/l	5.22 ± 0.05^a	7.47 ± 0.11^ab	8.82 ± 0.07^b	50
PO₄³⁻	mg/l	0.45 ± 0.03^a	0.60 ± 0.02^ac	0.99 ± 0.02^b	0.54
NH₃	mg/l	0.42 ± 0.15^a	0.46 ± 0.20^a	0.55 ± 0.19^a	0.5
NH₄⁺	mg/l	0.45 ± 0.16^a	0.50 ± 0.22^a	0.60 ± 0.21^a	0.5

Distribution of macroinvertebrates

The benthic macroinvertebrate species were categorized according to the presence or absence of specific species in the study sites. The distribution of macroinvertebrate species recorded at the study sites as shown in Table 4.

Table 4

Distribution pattern of macroinvertebrates in the sampling sites.
Taxon	Family name	Site-1	Site-2			P-value
Coleoptera	Gyrinidae	+	+	-	6.700	.017
	Elmidae	+	+	-	7.588	.012
Diptera	Chironomidae	+	+	+	5.042	.034
	Muscidae	+	+	+	6.045	.022
	Syrphidae	-	-	+	22.091	.000
Ephemeroptera	Baetidae	+	+	-	7.066	.014
	Caenidae	+	+	+	5.723	.025
	Heptageniidae	+	+	-	6.513	.018
	Leptophlebiidae	+	-	-	123.429	.000
Hemiptera	Naucoridae	+	+	-	7.696	.011
	Nepidae	+	+	+	5.864	.023
	Notonectidae	-	+	+	6.767	.016
Odonata	Asheniidae	+	-	-	29.270	.000
	Coenagrionidae	-	+	+	7.000	.015
	Gomphidae	+	-	-	129.960	.000
Plecoptera	Perlidae	+	-	-	154.0831	.000
Trichoptera	Hydropsychidae	+	+	-	7.545	.012
Hirudinea	Hirudinidae	-	-	+	24.000	.000
Total		14	12	8

Note: (+): indicates the presence and (-): indicates absence of species

Relative abundance of the macroinvertebrates

Among all the families collected from sampling sites in Kuliya River, Chironomidae showed the highest relative abundance (45.10%) followed by Baetidae (7.86%), Gomphidae (5.26%), Leptophlebiidae (4.44%), Heptageniidae (4.16%), Perlidae (3.97%), Naucoridae (3.88%) and Nepidae (3.70%) (Fig. 2). The remaining families such as Aeshnidae (3.51%), Muscidae(3.33%), Hydropsychidae (3.14%), Coenagrionidae (2.77%), Caenidae (2.13%), Elmidae(1.94%), Notonectidae (1.76%), Gyrinidae (1.48%), Syrphidae (0.83%), and Hirudinea (0.74%), were relatively less abundant (Fig. 2).

Table 5

Abundance of macroinvertebrates at three sampling sites in Kuliya River
Taxon		Family	Site 1	Site 2	Site 3	Total
Coleoptera		Gyrinidae	7	9	0	16
		Elmidae	8	13	0	21
Diptera		Chironomidae	71	187	230	488
		Muscidae	8	25	3	36
		Syrphidae	0	0	9	9
Ephemeroptera		Baetidae	77	8	0	85
		Caenidae	15	5	3	23
		Heptageniidae	28	17	0	45
		Leptophlebiidae	48	0	0	48
Hemiptera		Naucoridae	15	27	0	42
		Nepidae	3	14	23	40
		Notonectidae	0	8	11	19
Odonata		Asheniidae	38	0	0	38
		Coenagrionidae	0	12	18	30
		Gomphidae	57	0	0	57
Plecoptera		Perlidae	43	0	0	43
Trichoptera		Hydropsychidae	21	13	0	34
Hirudinea		Hirudinidae	0	0	8	8
	Total individuals		439	338	305	1082
	Total taxa per site		14	12	8	34

Abundance of macroinvertebrates Kuliya River

A total of 1082 benthic macroinvertebrate species belonging to 18 families, 7 orders, and 1 class were collected from the Kuliya River; (Table 5). Site 1 had 439 individuals, followed by Site 2 with 338 and Site 3 with 305; (Table 5). Families like Baetidae, Caenidae, Heptageniidae, Leptophleblidae, Perlidae, and Hydropsychidae were abundant at Site 1, but less so at Site 3; however, Chironomidae, Coenagrionidae, Nepidae, and Hirudinea were more abundant at Site 3.

Community Composition

The site 3 (Kera site) was highly dominated by the species belonging to diptera compared to the other two sites.The upstream river site (site 1) was dominated by the Ephemeropteran, Plecopteran, and Trichopteran orders, while the least number of dipterans were recorded. Among the species belonging to Odonata, family Aeshnidae and Gomphidae were sensitive to pollution.In the midstream site the EPT families were low comparing to downstream site that is due to good environmental condition in this site comparing to downstream (Kera site).

Percent EPT

Percent EPT represents the Ephemeroptera (Mayflies), Plecoptera(Stoneflies), and Trichoptera (Caddisflies). In this study, the percentage of EPT decreased as the water quality decreased downstream. The highest value (52.84%) of EPT was recorded at site 1, followed by site 2 (12.73%), and the lowest recording (0.98%) was observed at site 3, as shown in Figs. 3, 4, and 5, respectively.

Percent Dipterans

The highest percentage (79.34%) of Diptera was recorded at the affected site 3, followed by 62.72%at site 2, while the lowest percentage (18.00%) was recorded at site 1.

Diversity of benthic macroinvertebrates

The richness value was the highest for the Site1 (14) and the lowest at Site 3 (8). The Shannon-Wiener diversity index value (H') was ranged between 2.35 at site 1 to 0.99 recorded at site 3(Table 6). The highest Simpsons diversity index (0.88) wasobserved at the site 1, while the lowest (0.42) was at the site 3. The recorded values of the Margalef richness index varied from 1.22 to 2.13, the highest at site 1 while the lowest (1.22) at the site 3 (Table 6).

Table 6

Macroinvertebrate diversity indices value of Kuliya River
Diversity indices	Site 1	Site 2				Site 3
Taxa	14 439 0.11 0.88 2.35 2.13 0.89 3.80				12			8
Individuals				338			305
Dominance (D) Simpson-(1-D)				0.32			0.57
Dominance (D) Simpson-(1-D)				0.67			0.42
Shannon_H			1.72				0.99
Margalef			1.88				1.22
Evenness – J H-FBI				0.69			0.47
Evenness – J H-FBI		7.04				8.18

Correlation (CCA) between macroinvertebrates and physicochemical parameters

The CCA illustrates the dynamics of three elements: the sampling stations, physicochemical parameters, and benthic macroinvertebrates in two dimensions; (Fig. 6). The first dimension, Axis 1 (Y- axis), accounted for 93.83% of inertia (with eigen value 0.10572, Table 7), and the second dimension, Axis 2 (X-axis), accounted for 6.17% of inertia (with eigen value 0.0069562, Table 7). Collectively these two axes accounted for 100.00% of variations in the distribution and a positive correlation was found between dissolved oxygen (DO) at the upstream sites and less tolerant macroinvertebrate taxa, including Caenidae, Hydropsychidae, Heptageniidae, Baetidae, Gomphidae, andAeshnidae; (Fig. 6). In axis 1 physicochemical parameters such as electrical conductivity, turbidity, total dissolved solids, nitrites, nitrates, phosphates, total alkalinity, biological oxygen demand, and chemical oxygen demand were negatively correlated with axis 1;while there was a positive correlation with dissolved oxygen and temperature; (Fig. 6). In the first axis, physicochemical parameters such as conductivity, turbidity, total dissolved solids, nitrites, nitrates, phosphates, total alkalinity, biological oxygen demand, and chemical oxygen demand were positively correlated with Coenagrionidae, Notonectidae, Nepidae, Syrphidae, Muscidae, Chironomidae, andHirudinea (Fig. 6).

Table 7

Eigen values and total inertia or variation
Axis				Eigen value				Total inertia (%)
Axis 1 (Y- axis)				0.10572				93.83
Axis 2 (X- axis)				0.0069562				6.17

The variation in temperature from site 1 to site 3 could be due to the presence or absence of vegetation cover, shading effect along the river and water depth. The recorded mean values of temperature in this study were consistent with those reported by (Tesfaye Muluye et al., 2024) for the Awash River, showing an increase in water temperature from upstream to downstream sites. The significantly highest EC value in site 3 was possibly due to soil erosion, runoff from farmland surfaces containing fertilizers, and dumping of domestic waste in ionized form. The downstream site was highly affected by anthropogenic activities, with a significantly low value of DO (4.07 ± 0.44 mg/l) and high measurements of electrical conductivity (EC) (236.47 ± 0.57 µS/cm) similar downstream site of the Awash River as reported by (Tesfaye Muluye et al., 2024).The most likely causes for the decrement of dissolved oxygen (DO) were due to the discharge of various organic wastes from Areka town into the river, the infiltration of pollutants from household sewage from the town.

According to Dessalegn Geleta and Worku Firomsa, 2022, DO concentration below 5 mg/l may harmthe functioning and survival of biological communities in the aquatic ecosystem. Additionally, the dissolved oxygen concentration in the present study was lower than the recommended level of 5 mg/l by the World Health Organization (WHO) for dissolved oxygen content in river water, particularly at Site 3, which is optimal for the survival and normal functioning of biological communities (Misgana Dabessa et al., 2021).The turbidity value exceeded the WHO guideline value for drinking water in all three sites of the Kuliya River, indicating that the river was affected by various anthropogenic activities. Anthropogenic activities such as waste discharged from Areka town, agricultural activities near the river, poor sanitation practices in the riparian communities, and municipal sewage, as well as residues released from the Kera/slaughter house, have led to high turbidity in the river. Significantly high EC, TDS, and turbidity values in the midstream and downstream sites are probably due to increased runoff from washing, bathing, agriculture, and the release of domestic waste to these sites. This may be explained by turbid waters carrying domestic and non-domestic waste, organic materials, and inorganic material discharges. This result is consistent with a similar study conducted in the Olifants River in South Africa (Rasifudi et al., 2018), where a high load of organic matter indicates pollution in the aquatic environment.

The pH values at site 1 and site 2 were within the permissible limit range of the WHO standard value (6.5–8.5), but the pH at site 3 exceeded the WHO standard limit. This shows that the nature of Kuliya River water is in an alkaline condition, which can result in an unpleasant taste, corrosion, and toxicity for drinking purposes and aquatic biota as indicated by (Begum et al., 2023).In this study, the recorded value of ammonium is less than the recorded value in the Brahmaputra River in India due to the difference in levels of anthropogenic activities (Begum et al., 2023). The exceeded levels of phosphate at site 2 and site 3 could be due to the discharge of detergents, contaminated sewage, runoff from fertilizers, and pesticides from agricultural activities into the river, as indicated by (Anyanwu et al., 2019). The recorded values of nitrites and nitrates exhibited statistically significant differences at sampling sites in the Kuliya River (P < 0.05) (Table 3). The significantly highest recorded values at site 2 and site 3 were possibly caused by urban runoff containing household domestic wastes, human sewage, car and motorcycle washing activities, and dumping of organic debris in and near the river. Surface runoff from farmlands containing high concentrations of inorganic fertilizers and livestock husbandry, untreated sewage, disposal sites, agriculture and fertilizer runoff, along with other point and nonpoint sources of pollution, might have contributed to the high load of nitrate and nitrite in these sites.

Diversity and distribution of macroinvertebrates

The community diversity and abundance of macroinvertebrate were known to be fluctuatingalong with various human-induced activities in all these ecosystems.Furthermore, the site 1 (Yukara site) can be used as a reference site having high occurrence of less tolerant species including Baetidae, Heptageniidae, Hydropsychidae, Perlidae, andAeshnidae. The distribution of highly tolerant species in site 3 (Kera site) indicated that the water quality had a direct effect on the distribution on the species composition. Therefore, it can be established that the differences in the distribution of benthic macroinvertebrate species could be caused by spatial variation in accordance to water quality at the study sites. EPT orders were comparatively high distribution at the reference site (site 1) and this suggests that this site was impacted less by different anthropogenic activities compared to the midstream and downstream sites.Numerous families of highly tolerant organisms were usually indicative of poor water quality according to Etemiet al2020. This might be due to human activities and pollutants deposited into streams, leading to an increase in nutrient levels causing BOD and COD.

Macroinvertebrate families such as Chironomidae, Nepidae, Coenagrionidae, Notonectidae, and Hirudinea were significantly highly distributed at the Kera site (Site 3) and have a high tolerance ability to adapt to affected environments (Table 4). This may indicate that the site was impacted by various anthropogenic activities. The distribution pattern of these species in the Kuliya River indicates that water quality had an effect on the distribution of benthic macroinvertebrates. Therefore, it can be established that the differences in the distribution of benthic macroinvertebrate species could be caused by spatial variation in water quality at the study sites.

Intolerant macroinvertebrate orders, such as EPT, were the most widely distributed species at the reference site (Site 1) (Table 4). This suggests that the site was less impacted by different anthropogenic activities occurring in the river compared to the midstream and downstream sites At the Kera site, the distribution of macroinvertebrates has decreased due to high pollution levels from various anthropogenic factors. Currently, the site is represented by 8 families with; the majority of them are being pollution-tolerant families that are significantly highly distributed, such as Chironomidae, Coenagrionidae, Hirudinea, Nepidae, and Notonectidae(Table 4).

Coming to the abundance of species, in the present study 7 orders and 18 families were recorded from the sampling sites similar to the findings ofYadesaChibsaet al 2022, GurmessaTessema and AgumassieTesfahun2018 (6 orders and 11 families). EPT orders were more abundant at site 1 and less abundant at sites 2 and 3might be due to theirchoice for better river environments with less pollution similar to the findings of GedaKebedeet al., 2020 on the upper Awash River and SisayMisganaw, 2019. The rich abundance of Chironomidae at site 2 (187) as well as site 3 (230) indicating high organic pollution and nutrient enrichment deposited in to the river from agriculture lands and sewage an observation similar to MisganaDabessaet al2021. In this study, the total abundance of individuals showed a decreasing pattern from upstream sites to downstream site andthis might be due to the high influence of anthropogenic activities at the downstream sites, such as farming, sand mining, slaughterhouse residues, and the addition of organic wastes that affect the physicochemical parameters in the river.

The EPT taxa were highly abundant at site 1 also be related to significantly higher dissolved oxygen (DO) and significantly lower total dissolved solids (TDS), temperature, turbidity and alkalinity compared to the midstream and downstream sites. According to Mzungu, 2023, undisturbed or reference parts of the river had a higher abundance of macroinvertebrates than downstream areas because of relatively favorable physicochemical parameters found at the reference site. Throughout the study period, Chironomidae were the most commonly encountered and dominant taxon site 3 supporting the widely held belief that in streams and rivers that have been impaired, tolerant species increase(Aschalew Lakew and Moog, 2015). The River was highly dominated by the dipteran family compared to Syrphidae and Hirudinea might be because of high tolerance to pollution and anthropogenic activities.In addition, the EPT taxa were relatively more abundant at the upstream site, a finding supported by Tyagi et al., 2006, which stated that benthic communities with a high abundance of pollution sensitive organisms are typically associated with good water quality, while a large proportion of pollution-tolerant organisms indicates water pollution from organic wastes.According to the study conducted by Abnet et al 2018, there are four classes of pollution status based on the value of the Shannon Wiener diversity index (H'). In their scale, H'<1 indicates heavy pollution, 1–2 indicates moderate pollution, 2 < 3 indicates light pollution, and H > 3 indicates slight pollution or unpolluted water. Based on these criteria, site 1 showed light pollution, site 2 was categorized as moderate pollution, and site 3 was classified as heavy pollution level. According to Izzati et al 2022the evenness value was divided into three categories with the value < 0.4 was low, 0.4–0.6 was moderate and > 0.6 was high. Based on these criteria, site 1 and site 2 had high evenness however,site 3 had moderate. The variation in evenness values might be due tothe pollution levels in the sampling sites of the river. The highest Simpsons diversity index (0.88) observed at the site 1, while the lowest (0.42) was at the site 3 (Table 6). According to Mandeville, 2002), the Simpson Index values vary from 0 to 1, where 0 indicates low diversity and 1 indicates a high level of diversity. The recorded value of Simpson’s diversity index in the present study indicated a relatively good level of diversity at the site 3 compared to other downstream sites.

This result of the study is consistent with Masresha Birara et al 2022who stated that stable environments have high diversity, while unstable communities have low diversity.The highest H-FBI value at site 3 might be due to the presence of significant organic pollution caused by diffused organic matter.

The dumping of organic debris traditionally and household wastes in to the river may have a large impact on the production of organic pollution as well as difference in water quality with the upstream site showing minimal ecological impairment, the middle showing intermediate while the downstream showing poor ecological status.DO showed positive correlation with pollution sensitive species, and this could be a sign of their biological preference for low levels of organic pollutants and high dissolved oxygen concentrations(Tesfaye Muluye et al., 2024). According to Osimen et al., 2021, families Baetidae and Caenidae were negatively correlated with temperature, total alkalinity, and nutrients in the South African river system and a positive correlation was observed with DO in Ojirami Reservoir, Nigeria (Akamagwuna et al., 2023).

The present study is an assessment to understand the water quality level in the Kuliya River using macroinvertebrates and physicochemical parameters as indicators to measure their responses to various anthropogenic stresses. Physicochemical parameters tested at the Kuliya River indicated a high load of anthropogenic impacts in midstream and downstream sites, affecting the river quality. The distribution, abundance, diversity outputs of macroinvertebrates revealed a pollution gradient along the course of the river. The presence of a high diversity and abundance of pollution-sensitive taxa in the upstream confirms relatively good water quality at the site1. In contrast, the presence of lower diversity and abundance of pollution-sensitive taxa in the midstream and downstream sites indicate that the river is in impairment. Correlation analysis in this study indicated that the association between most of pollution-sensitive benthic macroinvertebrates and physicochemical parameters showed a negative correlation at the midstream and downstream sites. Finally, the presence of high pollution tolerant macroinvertebrates taxa together with the load of physicochemical parameters indicatesthat the Kuliya River is under stress and needs utmost attention for its rejuvenation.

Author Contribution

1. Legesse Minota: The primary researcher, author and contributor of data2. Abnet Woldesenbet: The Primary advisor and central idea3. Prof.B.Sairam Pattnaik: The chief interpreter of data, compiler and editor4. Zebdiyos Yosef: field work and lab assistance5. Yigrem Deneke: Technical support and cross verification of document

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No competing interests reported.

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Abundance and diversity of benthic macroinvertebrates as bioindicators of water quality in KuliyaRiver at Areka town southern Ethiopia

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Abstract

Figures

INTRODUCTION

METHODOLOGY

Description of the study area

Physico-chemical parameters

Plankton sampling

Data analysis

RESULTS

Physicochemical parameters

Distribution of macroinvertebrates

Relative abundance of the macroinvertebrates

Abundance of macroinvertebrates Kuliya River

Community Composition

Diversity of benthic macroinvertebrates

Correlation (CCA) between macroinvertebrates and physicochemical parameters

DISCUSSION

Diversity and distribution of macroinvertebrates

Conclusion

Declarations

Author Contribution

References

Additional Declarations

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