Evaluation of Menala River Water Quality Based on Benthic Macroinvertebrate as Bioindicator to Support Tourism in
Sumbawa Island, Indonesia
Zainul Muttaqin Sany
1, Endang Arisoesilaningsih
2, Catur Retnaningdyah
2*1Master Program of Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia
2Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia Abstract
The aquatic ecosystem in the Menala River has been degraded due to anthropogenic activities. The purpose of this study was to evaluate the water quality in the Menala River based on water physicochemical and benthic macroinvertebrates as bioindicators. Water quality was evaluated at seven stations based on anthropogenic activities in the surrounding. The physicochemical parameters measured included water temperature, turbidity, electrical conductivity, pH, DO, TDS, BOD, nitrate, and total phosphate. Benthic macroinvertebrate data were used to determine the importance value index (IVI), Shannon-Wiener diversity index (H'), evenness index (E), Simpson dominance index (C), the average score per taxon index (ASPT), and family biotic index (FBI). The data were analyzed by one-way ANOVA, biplot, and correlation test using PCA. The research result indicated that the concentration of DO (5.97 – 11.7 mg.L-1) at each station only fulfilled in class 3 of water quality, BOD (2.83 – 4.03 mg.L-1) in class 2, and Total phosphate (0.03 – 0.23 mg.L-1) only meets class 3. Based on the H', FBI, and ASPT index, the first station was categorized as clean water, the second to fourth stations were categorized as good to fairly poor, and the fifth to seventh stations were categorized as lightly polluted to probable severe pollution.
Keywords: Benthic Macroinvertebrates, Menala River, physicochemical parameters, water quality.
INTRODUCTION*
Sumbawa Island is a tourist destination. The main tourist attraction on Sumbawa Island is freshwater areas like waterfalls flowing into rivers. For example, in the Brang Rea River, with a length of ± 21.55 km, ecotourism is expected to help the social economy in the communities around the river [1]. Besides, many other rivers, such as the Menala River, are used for tourism.
Therefore, to keep attracting tourists, it is necessary to evaluate the water quality of the Menala River so that future management can be more targeted.
Aquatic ecosystems are usually influenced by the surrounding environment from upstream to downstream. One of the causes of river ecosystem disruption is anthropogenic activities which range from residential activities, agriculture, and industry, to urbanization [2]. For example, the Menala River on Sumbawa Island, West Nusa Tenggara Province, is also facing the problem of decreasing river water quality due to anthropogenic activities ranging from domestic (bathing, washing, toilets), plantations, agriculture, animal husbandry, entrepreneurial activities (motorcycle/car wash areas, cafes,
* Correspondence Address:
Catur Retnaningdyah E-mail : [email protected]
Address : Dept. Biology, Universitas Brawijaya, Veteran Malang, 65145.
supermarkets, places to eat, tourist attractions, and pharmacies), as well as urbanization [3]. On the other hand, the community still uses degraded river water for drinking. Degradation of river water quality results from high pollution pressure but low environmental sanitation efforts [4].
Human activities can disrupt the abiotic and biotic factors of the Menala River waters, so it is necessary to evaluate the water quality.
Evaluation of water quality can be conducted in two ways. The first evaluation is monitoring the physicochemical water quality. Previous water physicochemical monitoring studies in the Bolivian watershed from 1991 to 2017 stated that anthropogenic waste could reduce DO, while detergents from domestic waste contribute to phosphate pollutants [5]. The second evaluation is benthic macroinvertebrate communities as bioindicators. It has been done in Genjong River, which was classified as lightly to moderately polluted with toxic materials and slightly polluted by organic matter. A decrease in water quality was indicated by a decrease in FBI and ASPT values [3]. Water physicochemical measurements are used to support biotic index data in showing accuracy. Therefore, combining biotic indices and physicochemical parameters can provide an accurate picture of the river ecosystems' condition [4].
Benthic macroinvertebrates have different sensitivities to pollutant loads entering rivers, so that they can be used as water quality bioindicators. The tolerance range of benthic macroinvertebrates has different levels depending on the habitat and environmental disturbances [6]. Studies using benthic macroinvertebrates as bioindicators of river water quality have been widely used and have shown their accuracy [7].
Using benthic macroinvertebrates as bioindicators for assessing water quality has been widely applied in tropical countries. The advantages of using benthic macroinvertebrate communities as bioindicators are low costs, easy sampling, easy to show interactions with water physicochemical. Some live only in clean waters, and some are cosmopolitan [8]. However, research on benthic macroinvertebrate bioindicators as an assessor of the water quality has yet to be available on Sumbawa Island, especially in the Menala River. Therefore, it is essential to conduct this study to assess and evaluate the quality of the Menala River water ecosystem using benthic macroinvertebrate bioindicators and physicochemical water parameters.
MATERIAL AND METHOD Study Area
This research was conducted in the Menala River, West Sumbawa Regency, West Nusa Tenggara Province, Indonesia. The Menala River has a tropical climate, flows from 120 m asl, has a drainage area of 162.69 m2, and flows from south to north towards Taliwang City (Fig. 1). The total annual precipitation is about 176.89 mm.year-1 (June – December), and the average annual temperature is 28.08°C. The river flows through many residential, plantation, and agricultural areas and urbanization (Table 1). The research area was conducted along the Menala River for 5 km covering the river's upstream, midstream, and downstream parts. This research was conducted from January to November 2022.
Data Collection
Sampling was conducted at seven stations with three repetitions from upstream to downstream (Fig. 1). The selection of sampling stations was based on the possible pollutant load. Each sampling station was estimated to have a different quality due to human activities around it (Table 1).
Benthic macroinvertebrate samples were collected from rocky, sandy, and muddy
substrates using a Surber net (first to the fifth station) and a grab sampler (sixth to seventh).
Then, the collected benthic macroinvertebrates were rinsed with water, separated from the sediment, and preserved in 70% alcohol. All samples were identified to the family or species level using appropriate references [3].
Figure 1. Sampling locations of benthic macro- invertebrates and water quality parameters (Source: Google Earth Pro 7.3 Modification, build date on June 7th, 2022).
Table 1. Detailed information on sampling stations Sampling
Station
Geographical
location Surrounding Activities
1 8°46.41′S
116°50.50′E
Natural and drinking water ingredients
2 8°46.56′S
116°51.09′E
Plantation and drinking water raw materials
3-5 8°46.03′S 116°51.22′E
Domestic activities (raw materials for drinking water, bathing, washing, and toilets), fruit plantations, agriculture, cattle breeding, and transportation routes
6-7 8°45.28′S 116°51.10′E
Domestic activities (bathing, washing, and toilet), agriculture, cattle breeding, transportation routes, urbanization, and entrepreneurial activities (motorcycle/car washes, cafes, supermarkets, places to eat, tourist attractions, and pharmacies)
Water physicochemical quality was measured at each sampling location, including temperature, current velocity, turbidity, electrical conductivity (EC), pH, dissolved oxygen (DO), total dissolved solids (TDS), biochemical oxygen demand (BOD), nitrate and total phosphate (TP). In addition, the composition of the aquatic substrate at each station was also observed. BOD, nitrate, and TP measurements were conducted in the laboratory, while other physicochemical parameters of water were conducted in situ. The physicochemical
measurement method of water was based on the standard method of water examination [9].
Dataanalysis
After identifying the benthic macroinvertebrate samples, the importance value index (IVI), Shannon-Wiener diversity index (H), evenness index (E), dominance index (C), the average score per taxon index (ASPT), and family biotic index (FBI) were calculated. The importance value index (IVI) was calculated below [10].
𝐼𝑉𝐼 = 𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 + 𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 Description:
Relative density =𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 𝑡𝑜𝑡𝑎𝑙 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 × 100 Relative frequency = 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦
𝑡𝑜𝑡𝑎𝑙 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 × 100
The following equation calculated the Shannon-Wiener diversity index (H') [4]. Next, the evenness index (E) and Simpson dominance index (C) were calculated [4]. The average score per taxon index (ASPT) was calculated by the following formula [11], as well as the family biotic index (FBI) [11].
𝐻′= − 𝑃𝑖ln 𝑃𝑖, 𝑃𝑖 =𝑛𝑖 𝑁 Description:
ni = the number of individuals of species i, N = the total number of individuals, ln = the natural log,
Σ = the number of counts
The H index is classified into four categories [12]:
>2 : not polluted 1.5-2 : lightly polluted 1-1.5 : moderately polluted 0-1.0 : heavily polluted
𝐸 = 𝐻′
𝐻 𝑚𝑎𝑥 , 𝐻 𝑚𝑎𝑥 = ln 𝑆 𝐶 = 𝑃𝑖2 , 𝑃𝑖=𝑛𝑖
𝑁 Description:
H' = Shannon–Wiener diversity index
ln S = natural log of the total number of species recorded
𝐴𝑆𝑃𝑇 𝐼𝑛𝑑𝑒𝑥 = 𝐵𝑀𝑊𝑃 𝑠𝑐𝑜𝑟𝑒 × 𝑛 𝑛 𝐹𝐵𝐼 = 𝑋𝑖𝑡𝑖
𝑛 Description:
BMWP = Biological Monitoring Working Party (BMWP) n = number of families represented in the sample xi = number of individuals belonging to family i ti = tolerance score of family i
n = total number of individuals collected
The index values for ASPT are classified into four categories:
>6 : clean water 5–6 : doubtful water
4–5 : probable moderate pollution <4 : probable severe pollution
FBI scores are classified into seven categories:
0.00-3.75 : excellent 3.76-4.25 : very good 4.26-5.00 : good 5.00-5.75 : fair 5.76-6.50 : fairly poor 6.51-7.25 : poor 7.26-10.00 : very poor
While the results of the measurements of the physicochemical parameters were analyzed using one-way ANOVA followed by Tukey HSD or Games-Howell using SPSS version 8.0. The relationship between the biotic factor, abiotic factor, and sampling station was analyzed using the Pearson correlation test and biplot (PCA) using PAST 4.05.
RESULT AND DISCUSSION
Water Physicochemical Quality Profile along the Menala River, Sumbawa Island
Based on the physicochemical measurements of water in the Menala River, the quality of water at the seven sampling locations has fulfilled the quality standard of class 3 based on Indonesian Government Regulation No. 22 of 2021, which can be used as a source of water for agricultural activities (Table 2).
The water temperature in the Menala River showed an increasing value starting from the upstream 24.43°C to the downstream 29.87°C.
This water temperature has met class 1. The high water temperature value downstream of Menala River was caused by decreasing altitude from 120 to 11 m asl [13]. The current velocity downstream of Menala River also decreased compared to upstream, which reached 0.31 ms- 1, while downstream, it was only 0.17 ms-1. The highest current velocity was found at the first station, 91.7% of the rocky substrate. In contrast, the lowest current velocity was found at the seventh station, with a substrate composition dominated by mud (Fig. 2). This decrease in river current velocity was due to changes in the percentage composition of the river substrate and the decreasing altitude [14]. The TDS value at station one was the highest (579.33 ppm), while the lowest was found at the third station, which was 402 ppm. The high value of TDS at the first station was due to the high water discharge, which carries dissolved mineral salts and sediment or phytoplankton [15].
Table 2. Physicochemical parameter on sampling stations
Parameter Station 1 Station 2 Station 3 Station 4 Station 5 Station 6 Station 7
Quality standard class-based Indonesia Government Regulation No. 22, 2021 1st 2nd 3rd 4th T (°C) 24.43±0.64a 29.07±0.58b 28.97±0.25b 29.80 ± 1.18b 29.33±0.58b 29.40±1.04b 29.87±0.32b --- Dev 3 ---
CV (ms-1) 0.31±0.08c 0.10±0.03a 0.29±0.04bc 0.30 ± 0.03c 0.18±0.02ab 0.15±0.03a 0.17±0.03a - - - -
Turb. Clear Clear Bit turbid Bit turbid Bit turbid Bit turbid Turbid - - - -
EC (ms.cm-1) 0.733±0.06 0.767±0.06 0.500±0.00 0.533 ± 0.06 0.600±0.00 0.567±0.06 0.600±0.00 - - - - pH 6.95±0.16a 6.65±0.03ab 6.38±0.07c 6.88 ± 0.04bc 6.99±0.01bc 6.91±0.08abc 6.90±0.06c --- 6-9 --- DO (mg.L-1) 11.17±1.04d 7.33±1.16abcd 7.17 ± 0.49abcd 8.03 ± 0.21cd 8.47±0.55d 6.97±0.15d 5.97±0.60abc 6 4 3 0 TDS (ppm) 556.00±3.46e 579.33±5.13f 402.00±1.00a 418.00 ± 3.61b 440.33±2.52c 439.67±3.79c 457.67±0.58d --- 1000--- BOD (mg.L-1) 4.03±0.61a 3.23±0.23a 2.83±0.83a 3.23 ± 1.22a 4.70±0.80a 4.17±0.23a 3.23±0.92a 2 3 6 12
NO3 (mg.L-1) 0.003±0.01 0.000 0.000 0.000 0.007±0.01 0.000 0.010±0.01 10 10 20 20
TP (mg.L-1) 0.39±0.12a 0.51±0.46a 0.29±0.03a 0.67 ± 0.13a 0.89±0.57a 0.65±0.15a 0.71±0.23a 0.2 0.2 1 5
Notes: T = Temperature, CV = current velocity, Turb.= Turbidity, EC = Electrical conductivity, NO3 = nitrate, TP = total phosphate, Dev 3= The difference between the water temperature and the air temperature above the water surface.
However, the TDS in the Menala River meets class 1 of water quality standards because it has a value of less than 1000 ppm. A low TDS indicated a low concentration of particles in the water body.
The turbidity of the downstream was the most turbid compared to the stations in the upstream to mid-stream. The increase of turbidity in the Menala River was caused by a decreasing current velocity resulting in sediment accumulation in the downstream section. It was because organic wastes were carried from the upstream/middle to the downstream [16]. At all stations, DO only met class 3 water quality standards. The downstream DO concentration was lower than the upstream. The highest DO concentration was found at the first station (11.17 mg.L-1), while the lowest DO was found at the seventh station, which was 5.97 mg.L-1. The decrease in DO levels in Menala River was caused by increased human activity, starting from domestic activities, plantations, agriculture, cattle farm, and urbanization. Human activities such as waste disposal can cause a decrease in dissolved oxygen concentrations [3]. BOD at all stations ranges from 3.23-4.70 mg.L-1, so it met class 3 of water quality. Agricultural waste, plantation waste, cattle farms, and domestic waste caused the high concentration of BOD. An increase in BOD is indicated by a high level of organic pollution in water [17].
The pH at all stations ranged from 6.38 – 6.99, meeting the class 1 standard water quality. The pH value along the river did not show a significant difference because the pollution impact from washing activities using detergents was still at a low intensity, so it will not disturb the pH value in the river. An increase in detergent concentration in the river was indicated by an increase in pH value, which ranges from 10 to 11 [16]. Electrical conductivity (EC) has a decreasing value starting from the
upstream to the downstream. The highest EC was shown at the first station (0.73 ms.cm-1), while the lowest EC was found at the seventh station, 0.6 ms.cm-1. Even though the EC has a different value at each station, the EC in the Menala River was classified as good water. It was in accordance with previous literature, which stated that EC values of 0.5-5 ms.cm-1 were included in the type of distilled water [18]. Nitrate content along the river showed a low value (0.003-0.010 mg.L-1), fulfilling class 1 of the water quality standard. Even though the nitrate content was low, the TP level had a high value, namely 0.39- 0.89 mg.L-1, so it only met class 3 of the water quality standard. Based on the Indonesian Minister of Environment Regulation No. 28 of 2009, the total phosphate, which exceeds 0.1 mg.L-1, indicates that the Menala River was included in the category of hypertrophic water.
The increase in TP levels is directly proportional to the increase in BOD concentration, so the increase in TP levels in the Menala River was caused by high organic waste [16,19].
Figure 2. Substrate composition of each sampling station.
The type of substrate at each station varies from rocky, sandy, to muddy (Fig. 2). The highest percentage of rock substrate composition was found upstream, that was, at the first station.
The highest percentage of sand substrate composition was found in the mid-stream, which was at the third station. The muddy substrate
composition found downstream, precisely at the seventh station, had the highest percentage. The rocky substrate at the first station had the coldest water temperature, 24.43°C. The current velocity at the first station has the highest value of 0.31 ms-1, so it can increase DO to 11.17 mg.L-1 (Table 2). It will support the diversity of benthic macroinvertebrates, including those with a low tolerance for environmental changes. Colder river flows were generally dominated by rocky substrates, which have a more variable current velocity to remove fine sediments from the river and were dominated by arthropods [8]. In contrast to the seventh station, which has a muddy substrate with a warmer temperature of 29.87°C, the seventh station has the lowest current velocity of 0.17 m.s-1 due to the lower altitude compared to the upstream, and the DO value decreased to 5.97 mg.L-1 due to accumulation of pollution along the river.
Annelids and mollusks mainly inhabited the muddy substrate at the seventh station [20,21].
Profile of Benthic Macroinvertebrate Community Structure along the Menala River, Sumbawa Island
Based on the benthic macroinvertebrate communities found in the Menala River, the first station had the highest TR (18 taxa) but had a low abundance (320.96 ind.m2). In contrast, the seventh station had the lowest TR (8 taxa) with a high abundance of 722.43 ind.m2 (Fig. 3). The decreasing value of taxa richness was influenced by the intensity of environmental changes, especially due to contaminants that disrupt the physicochemical of water that supports benthic macroinvertebrate communities, for example, the DO level at the first station was much higher than the seventh station. Low dissolved oxygen levels affect the community of benthic macroinvertebrates because they depend on oxygen availability [22].
Figure 3. The abundance and taxa richness of benthic macroinvertebrates at each station.
The benthic macroinvertebrate abundance of the first station had a lower value than the seventh station. The low abundance at the first station was affected by the lowest nitrate and phosphate levels compared to the other stations.
Low levels of nitrate and phosphate reduce nutrients in the water, then reduce biological productivity so that the abundance of benthic macroinvertebrates becomes low. Low nitrate and phosphate levels also indicate low primary and biomass productivity [23].
The importance value index (IVI) of each species is presented in Figure 4. We found some co-dominant taxa of benthic macroinvertebrates at first to fifth stations, namely Leptophlebiidae (29.79%) and Baetidae (44.97%) at the first station; Chironomidae (31.18%), Leptophlebiidae (19.65%), and Baetidae (29.88%) at station two;
Caenidae (55.58%) and Chironomidae (52%) at the third station; Caenidae (34.87%), Chironomidae (21.18%), Leptophlebiidae (22.72%), and Baetidae (33.72%) at the fourth station; Melanoides tuberculata (39.15%) and Chironomidae (35.73%) at the fifth station. While at the sixth and seventh stations, we found the dominance of M. tuberculata, namely 50.17%
and 72.89% (Fig. 4). The co-dominant taxa from the Order of Ephemeroptera (Baetidae, Caenidae, Leptophlebiidae) indicated that the waters classified as unpolluted waters because they were sensitive to pollution [24]. Taxa of Diptera (Chironomidae) indicated the quality of moderately to heavily polluted waters. Taxa of Mollusca (M. tuberculata) indicated the quality of waters that were heavily polluted because M.
Tuberculata has a high tolerance level for decreasing the water's physicochemical quality and can be opportunistic [4,25].
Figure 4. Importance Value Index (IVI) of each benthic macroinvertebrate taxa at each station.
Water Quality along the Menala River Based on Benthic Macroinvertebrates as Bioindicators
Based on the calculation of the Shannon- Wiener diversity index (H'), it showed a decrease in water quality from the first station to the seventh station (Fig. 5). The highest H' index value was found at the second station (3.10), while the lowest H' index value was found at the seventh station, which was 1.81. The first station to the sixth station was classified into the same category, namely unpolluted. In contrast, the seventh station had a lower value (1.81), so it had a different category: slightly polluted. The seventh station was categorized as slightly polluted because it has the highest pollutant load compared to other stations, for example, domestic waste. The physical changes of the seventh station to be channelized river made the microhabitat less suitable for macroinvertebrates to live. The benthic macroinvertebrates that can live were only a high tolerance taxa for environmental changes, such as Annelida and Molluscs [21,26].
Figure 5. Shannon-Wiener diversity index (H') for each station. Description: ___ classification H'.
Based on the Evenness Index (E) calculation, the evenness value varies at each station. The highest evenness was at the fifth station (0.9), while the lowest was found at the seventh station (0.6) (Fig. 6). The first to sixth stations had a high evenness category (> 0.6 – 1), while the seventh station had a medium category (> 0.4 – 0.6). A high evenness value indicates that the benthic macroinvertebrate community is evenly distributed in the waters [27].
The highest Simpson dominance index (C) value was found at the seventh station (0.4), while the lowest C index value was at the second station (0.1) (Fig. 6). The first to seventh stations have low dominance because they have a value of < 0.5. The low dominance index value of benthic macroinvertebrates was influenced by high diversity and evenness [28].
Figure 6. Evenness (E) and Simpson dominance index (C) benthic macroinvertebrates at each station.
Based on the FBI score, the first, second, and fourth stations were classified as good-quality waters (4.26–5.00) with possible organic contamination (Figure 7). The third station was classified as fair waters with the possibility of substantial organic contamination. It is influenced by families with a high tolerance range, as indicated by the tolerance value caused by organic pollution. Orders Ephemeroptera, Plecoptera, and Trichoptera usually have a low tolerance range, so they were very sensitive to the physicochemical changes of water [29]. The fifth station was classified as poor waters with a very high probability of pollution. The sixth and seventh stations were classified as very poor waters with the possibility of severe organic pollution. The sixth and seventh stations were downstream, a place for accumulating pollutants from the mid-stream. In addition, the anthropogenic activities downstream of the river were increasing, and a channel alteration was found. The category of very poor waters indicated that the benthic macroinvertebrate communities in these waters were very tolerant of decreasing water quality. It was evidenced by the fact that mollusks only dominated the benthic macroinvertebrates in the sixth and seventh stations. Mollusks are taxa that have a high tolerance range [30].
Figure 7. FBI values at each station. Description: ___ water quality classification based on FBI value.
Based on the ASPT index value, it can be seen that there was a decrease in water quality downstream (Fig. 8). First, third, and fourth stations were classified as clean water. The second station was classified as waters of questionable quality because of domestic activities. The fifth, sixth, and seventh stations were classified as probable severe pollution because these stations have undergone many changes and become accumulations of organic and domestic waste. It is also indicated by some taxa of benthic macroinvertebrates, which are indicators of poor quality, such as Chironomidae, Tubificidae, Planorbidae, and Lymnaeidae [31].
Figure 8. ASPT index at each station. Description: ___
classification of water quality based on ASPT index values.
Tourism Effect on Menala River Water Quality The Menala River is a tourist area, both domestic and non-domestic. Tourists who visit usually do nature viewing activities around the river, recreation, eating, and bathing. The use of soap when bathing causes toxic materials that cause a decrease in water quality based on the biotic index H', ASPT, and FBI [5].
Based on the correlation test, DO, EC, and turbidity had a significant effect on the quality of benthic macroinvertebrate diversity as bioindicators as reflected in the TR, H' index, FBI, and ASPT index (p-value <0.01 – 0.05) (Fig. 9). DO and EC had positively affected to TR, index H', and ASPT. An increase in DO can increase TR, H' index, and ASPT index but reduce FBI. Thus, it shows a good increase in water quality. Turbidity negatively affects the quality of macroinvertebrate diversity as indicated by TR, H' index, and ASPT, but it has a positive correlation with FBI. The higher the turbidity will increase the FBI, which shows the quality of the waters was getting worse. Therefore, the higher the DO, EC, TR, H' index, and ASPT index, and the lower the turbidity and FBI, show the better the quality of benthic macroinvertebrate diversity as a bioindicator of clean water [8,32,33].
Figure 9. Correlation between water physicochemical parameters, benthic macroinvertebrate community structure, and biotic index at each station using PAST 4.05 2022 application.
Description: **p value <0.01, *p-value 0.01- 0.05.
The results of biplot analysis using PCA showed that there was a shift in water quality in the downstream area (Fig. 10). The water quality of the Menala River decreased as indicated by higher TP levels, higher turbidity, higher FBI values, lower TR, lower H' index, lower ASPT index, lower DO, and lower EC. Based on PCA analysis, the first to fourth stations were in the one group categorized as good water quality, marked by high TR values, H' index, ASPT index, DO, and EC. It was consistent with previous research, which stated that the oxygen concentration in the water had a positive correlation (p <0.01 significance) with the biotic index H'. In comparison, the ASPT index had a negative correlation (p <0.01 significance) with The FBI biotic index [34].
The fifth to seventh stations had poor water quality, with high FBI, TP, and turbidity values. It was due to the high intensity of tourists arriving, so the river ecosystem is unable to remediate the waters. The function of riparian habitats as pollutant filters was also reduced due to land conversion to residential areas and agricultural land. The decrease in water quality, which was marked by a decrease in the benthic macroinvertebrate community quality, needs to be managed, especially at the fifth to seventh stations, such as limiting the number of tourists per day to minimize pollutant impacts and returning riparian habitat as a pollutant filter by planting riparian tree vegetation along the Menala River [35,36]. Waste from tourist facilities (such as human waste and detergents) that are discharged into rivers can seriously threaten environmental health. Discharged waste into the river can pollute water and damage aquatic ecosystems [37]. A centralized waste disposal system (such as a septic tank) can help reduce domestic waste entering the river.
Figure 10. Classification of water quality in the Menala River based on biplot analysis using PCA.
Additionally, waste management using riparian vegetation along the riverbanks can effectively address residual waste from toilets or other facilities that flow into the river. Riparian vegetation is a natural filter that can clean the water flow from harmful chemicals, excessive nutrients, and organic waste, thus benefiting biodiversity, improving water quality, and preventing erosion [38].
CONCLUSION
The physicochemical quality of the water at the seven sampling locations only met the class 3 water quality standard due to the low DO, then high BOD and TP. The results of benthic macroinvertebrates calculation showed that stations 1-5 were dominated by the taxa Ephemeroptera (Baetidae, Caenidae, Leptophlebiidae) and Diptera (Chironomidae), while M. tuberculata dominated stations 6 and 7.
The calculation results of the biotic index (H', E, C, FBI, ASPT) showed that the first station was not polluted, the second to fifth stations were not polluted to slightly polluted, and the fifth to seventh stations were lightly polluted to heavily polluted. Thus, it is necessary to manage the surrounding human activities and land covering to support tourism in the ecosystem of the Menala River.
ACKNOWLEDGEMENT
Writers would like to appreciate the Laboratory of Ecology, Brawijaya University, and Purnomo for providing the research tools; Jihadil Akbar, who has helped survey the research site;
Baiq Regina Silva, who helped with identification;
and Faisal Ansyarif, who has accompanied Benthic macroinvertebrates and physicochemical water sampling, and Satria Cahya Febriansyah who has helped in preliminary article concept.
REFERENCES
[1] Fatmalia, E., and J. Efendi. 2021. Studi kelayakan Daerah Aliran Sungai Rea, Kecamatan Taliwang Kabupaten Sumbawa Barat dalam pengembangan ekowisata.
Jurnal Sanitasi dan Lingkungan 2(1), 139- 145.
[2] Chetty, S., and L. Pillay. 2019. Assessing the influence of human activities on river health: A case for two South African Rivers with Differing Pollutant Sources.
Environmental Monitoring And Assessment 191(3), 1-11. DOI: 10.1007/s10661-019- 7308-4.
[3] Wimbaningrum, R., S. Indriyani, C.
Retnaningdyah, and E. Arisoesilaningsih.
2016. Monitoring water quality using biotic indices of benthic macroinvertebrates along surfaces water ecosystems in some tourism areas in East Java, Indonesia. Journal of Indonesian Tourism and Development Studies 4(2), 81-91.
[4] Patang, F., A. Soegianto, S. Hariyanto. 2018.
Benthic macroinvertebrates diversity as bioindicator of water quality of some rivers in East Kalimantan, Indonesia. International Journal of Ecology 1(1), 1-11. DOI: 10.1155/
2018/5129421.
[5] Gossweiler, B., I. Wesström, I. Messing, A.
M. Romero, and A. Joel. 2019. Spatial and
temporal variations in water quality and land use in a semi-arid catchment in Bolivia.
Water 11(11), 2227. DOI: 10.3390/
w11112227.
[6] Herawati, H., E. Patria, H. Hamdani, and A.
Rizal. 2020. Macrozoobenthos diversity as a bioindicator for the pollution status of Citarik River, West Java. IOP Conference Series: Earth and Environmental Science 535(1), 1-8. DOI: 10.1088/1755-1315/535/
1/012008.
[7] Chazanah, N., B. S. Muntalif, R. A.
Rahmayani, and P. Sudjono. 2020.
Macrozoobentos distribution as a bioindicator of water quality in the upstream of the citarum river. Journal of Ecological Engineering 21(3), 10-17. DOI:
10.12911/22998993/116335.
[8] Izzati, F. N., C. Retnaningdyah. 2022.
Evaluation of river water quality based on biotic index of benthic macroinvertebrate as bioindicator (case study in Genjong River Wlingi Blitar East Java, Indonesia).
Biotropika: Journal of Tropical Biology 10(2), 117-125. DOI: 10.21776/ub.
biotropika.2022.010.02.05.
[9] Baird, R. B., A. D. Eaton, and L. S. Clesceri.
2012. Standard methods for the examination of water and wastewater, Vol.
10. In: Rice, E. W. (Ed). American public Health Association. Washington, DC.
[10] Jost, L. 2010. The relation between evenness and diversity. Diversity 2(2), 207- 232. DOI: 10.3390/d2020207.
[11] Mandaville, S. M. 2002. Benthic macroinvertebrates in freshwaters: Taxa tolerance values, metrics, and protocols, Vol. 128. Soil & Water Conservation Society of Metro Halifax, Nova Scotia.
[12] Shukla, A. K., C. S. P. Ojha, A. Mijic, W.
Buytaert, S. Pathak, R. D. Garg, and S.
Shukla. 2018. Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin. Hydrology and Earth System Sciences 22(9), 4745-4770.
[13] Danladi Bello, A. A., N. B. Hashim, and M. R.
Mohd Haniffah. 2017. Predicting impact of climate change on water temperature and dissolved oxygen in tropical rivers. Climate 5(3), 1-24. DOI: 10.3390/cli5030058.
[14] Groll, M., A. Thomas, L. Jungermann, and K.
Schäfer. 2016. Typology of Riverbed Structures and Habitats (TRiSHa)–A new
method for a high resolution characterization of the spatial distribution and temporal dynamic of riverbed substrates and microhabitats. Ecological indicators 61(2), 219-233. DOI: 10.1016/
j.ecolind.2015.09.019.
[15] Vasistha, P., and R. Ganguly. 2020. Water quality assessment of natural lakes and its importance: an overview. Materials Today:
Proceedings 32, 544-552. DOI: 10.1016/
j.matpr.2020.02.092.
[16] Syandri, H., A. Azrita, and A. Mardiah. 2020.
Water quality status and pollution waste load from floating net cages at Maninjau Lake, West Sumatera Indonesia. IOP Conference Series: Earth and Environmental Science 43(1), 1-9. DOI: 10.1088/1755- 1315/430/1/012031.
[17] Heerema, C. J., P. J. Talling, M. J. Cartigny, C.
K. Paull, L. Bailey, S. M. Simmons, et al.
2020. What determines the downstream evolution of turbidity currents?. Earth and Planetary Science Letters 532(1), 116023.
DOI: 10.1016/j.epsl.2019.116023.
[18] Schück, M., and M. Greger. 2020. Screening the capacity of 34 wetland plant species to remove heavy metals from water.
International Journal of Environmental Research and Public Health 17(13), 4623.
DOI: 10.3390/ijerph17134623.
[19] Mahmudi, M., E. D. Lusiana, S. Arsad, N. R.
Buwono, A. Darmawan, T. W. Nisya, and G.
A. Gurinda. 2019. A study on phosphorus- based carrying capacity and trophic status index of floating net cages area in Ranu Grati, Indonesia. Aquaculture, Aquarium, Conservation and Legislation 12(5), 1902- 1908.
[20] Abe, H., T., Takeuchi, M. Taru, W. Sato- Okoshi, and K. Okoshi. 2019. Habitat availability determines distribution patterns of spionid polychaetes (Annelida:
Spionidae) around Tokyo Bay. Marine Biodiversity Records 12(1), 1-12. DOI:
10.1186/s41200-019-0167-4.
[21] Heath, M. W., S. A. Wood, K. A. Brasell, R.
G. Young, and K. G. Ryan. 2015.
Development of habitat suitability criteria and in‐stream habitat assessment for the benthic cyanobacteria Phormidium. River Research and Applications 31(1), 98-108.
DOI: 10.1002/rra.2722.
[22] Musonge, P. S., P. Boets, K. Lock, and P. L.
Goethals. 2020. Drivers of benthic macroinvertebrate assemblages in
equatorial alpine rivers of the Rwenzoris (Uganda). Water 12(6), 1-21. DOI: 10.3390/
w12061668.
[23] Stefanidis, K., Y. Panagopoulos, and M.
Mimikou. 2016. Impact assessment of agricultural driven stressors on benthic macroinvertebrates using simulated data.
Science of the Total Environment 540(11), 32-42.
[24] Miserendino, M. L., and C. Brand. 2009.
Environmental effects of urbanization on streams and rivers in Patagonia (Argentina):
the use of macroinvertebrates in monitoring. Advances in Environmental Research 6, 183-220.
[25] Abdelhady, A. A., M. M. Khalil, E. Ismail, J.
Fan, S. Zhang, and J. Xiao. 2019. Water chemistry and substrate type as major determinants of molluscan feeding habit and life–mode in lagoon sediments.
Estuarine, Coastal and Shelf Science 220, 120-130. DOI: 10.1016/j.ecss.2019.02.019.
[26] Karrouch, L., A. Chahlaoui, and A. Essahale.
2017. Anthropogenic impacts on the distribution and biodiversity of benthic macroinvertebrates and water quality of the Boufekrane River, Meknes, Morocco.
Journal of Geoscience and Environment Protection 5(07), 173-196. DOI: 10.4236/
gep.2017.57014.
[27] Hamid, A., S. U. Bhat, and A. Jehangir. 2021.
Assessment of ecological characteristics of macroinvertebrate communities and their relationship with environmental factors in a stream ecosystem. Chemistry and Ecology 37(9-10), 746-766. DOI: 10.1080/02757540.
2021.1987419.
[28] Krisanti, M., Y. Wardiatno, and Y. M. Anzani.
2017. Assessing the ecological status of the Cisadane River’s headwaters using benthic macroinvertebrates. IOP Conference Series:
Earth and Environmental Science 54(1). 1-7.
DOI: 10.1088/1755-1315/54/1/012023.
[29] Raburu, P. O., F. O. Masese, and K. S.
Tonderski. 2017. Use of macroinvertebrate assemblages for assessing performance of stabilization ponds treating effluents from sugarcane and molasses processing.
Environmental monitoring and assessment, 189(2), 1-15. DOI: 10.1007/s10661-017- 5786-9.
[30] Lopes-Lima, M., N. Riccardi, M. Urbanska, F.
Köhler, M. Vinarski, A. E. Bogan, and R.
Sousa. 2021. Major shortfalls impairing knowledge and conservation of freshwater
molluscs. Hydrobiologia 848(12), 2831- 2867. DOI: 10.1007/s10750-021-04622-w.
[31] Kamal, S., and R. S. Kumar. 2021.
Assessment of biological water quality based on functional feeding groups of benthic macroinvertebrates: A case study of Pampa River. Indian Journal of Ecology, 48(3), 837-841.
[32] Kebede, G., D. Mushi, R. B. Linke, O. Dereje, A. Lakew, D. S. Hayes, et al. 2020.
Macroinvertebrate indices versus microbial fecal pollution characteristics for water quality monitoring reveals contrasting results for an Ethiopian river. Ecological Indicators 108(105733), 1-10. DOI:
10.1016/j.ecolind.2019.105733.
[33] Yang, Y., Y. Yi, Y. Zhou, X. Wang, S. Zhang, and Z. Yang. 2020. Spatio-temporal variations of benthic macroinvertebrates and the driving environmental variables in a shallow lake. Ecological Indicators, 110 (105948), 1-11. DOI: 10.1016/j.ecolind.
2019.105948
[34] Etemi, F. Z., P. Bytyçi, M. Ismaili, O. Fetoshi, P. Ymeri, A. Shala–Abazi, et al. 2020. The use of macroinvertebrate based biotic indices and diversity indices to evaluate the water quality of Lepenci river basin in Kosovo. Journal of Environmental Science and Health, Part A 55(6), 748-758. DOI:
10.1080/10934529.2020.1738172
[35] Lozanovska, I., M. T. Ferreira, and F. C.
Aguiar. 2018. Functional diversity assessment in riparian forests–multiple approaches and trends: a review. Ecological Indicators 95, 781-793.
[36] Roche, P. K., and C. S. Campagne. 2017.
From ecosystem integrity to ecosystem condition: a continuity of concepts supporting different aspects of ecosystem sustainability. Current Opinion in Environmental Sustainability 29, 63-68.
[37] Bukola, D., A. Zaid, E. I. Olalekan, and A.
Falilu. 2015. Consequences of anthropogenic activities on fish and the aquatic environment. Poultry, Fisheries &
Wildlife Sciences 3(2), 1-12. DOI:
10.4172/2375-446X.1000138.
[38] Opoku‐Kwanowaa, Y., R. K. Furaha, L. Yan, and D. Wei. 2020. Effects of planting field on groundwater and surface water pollution in China. CLEAN–Soil, Air, Water
48(5-6), 1900452. DOI:
10.1002/clen.201900452.
