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Article

Klina River Water Quality Assessment Based on Diatom Algae

by
Osman Fetoshi
1,
Romina Koto
2,
Albona Shala
3,*,
Fatbardh Sallaku
2,
Pajtim Bytyçi
1,
Demokrat Nuha
1,
Bojan Đurin
4,*,
Rozeta Hasalliu
5,
Arbëri Bytyçi
6,
Upaka Rathnayake
7 and
Dragana Dogančić
8
1
Food Science and Biotechnology, UBT-Higher Education Institution, 10000 Prishtina, Kosovo
2
Faculty of Agriculture and Environment, Agricultural University of Tirana, Str. Pajsi Vodica, Koder Kamez, 1029 Tirana, Albania
3
Faculty of Management in Tourism, Hotels, and the Environment, University “Haxhi Zeka”, 30000 Pejë, Kosovo
4
Department of Civil Engineering, University North, 42000 Varaždin, Croatia
5
Faculty of Biotechnology and Food, Agricultural University of Tirana, Str. Pajsi Vodica, Koder Kamez, 1029 Tirana, Albania
6
Ministry of Environment Spatial and Planning, 10000 Prishtina, Kosovo
7
Department of Civil Engineering and Construction, Faculty of Engineering and Design, Atlantic Technological University, F91 YW50 Sligo, Ireland
8
Faculty of Geotechnical Engineering, University of Zagreb, Hallerova aleja 7, 42000 Varaždin, Croatia
*
Authors to whom correspondence should be addressed.
Ecologies 2025, 6(1), 15; https://doi.org/10.3390/ecologies6010015
Submission received: 27 November 2024 / Revised: 17 January 2025 / Accepted: 21 January 2025 / Published: 8 February 2025
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Abstract

:
Benthic diatoms are being used as indicators to assess the biological quality of surface waters in Kosovo. The Klina River is the left tributary of the White Drin River Basin, with a length of 69 km. The study assessed the level of surface water quality in the Klina River using 12 diatomic indices calculated with the Omnidia program. For this purpose, three stations monitored the river Klina in the autumn of 2021 to conform to international standards. A total of 88 diatom taxa were identified, with the dominant species being Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot, Gyrosigma acuminatum (Kützing) Rabenhorst, Cocconeis placenula Ehrenberg, Gomphonema minutum (Ag.) Agardh f. minutum, Gomphonema clavatum Ehr, Meridion circulare (Greville) C.A. Agardh, Cocconeis pediculus Ehrenberg, Diatoma vulgaris Bory, and Nitzschia dissipata (Kützing) Grunow ssp. dissipata etc. This study assessed the surface water quality in the Klina River using diatom indices, indicating that the river is in good to moderate ecological condition. Environmental variables such as hydrogen ion concentration (pH) and dissolved oxygen (DO) had significant positive correlations (<0.01) with the biological diatom index (IBD), Descy’s pollution metric (Descy), Sladeček’s pollution metric (SLA), the European index (CEE), and Watanabe’s Index (WAT), while the total suspended solids (TSS) also showed a strong negative significant correlation (<0.01) with the generic diatom index (IDG), Indice Diatomique Artois Picardie (IDAP), the eutrophication pollution index (EPI-D), the trophic diatom index (TDI), the Pampean diatom index (IDP), and Steinberg and Schiefele’s index (SHE). Total phosphorus (TP), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) presented a significant negative correlation (<0.05) with the IBD, Descy, SLA, CEE, and WAT indices. Our findings provide insights for organizations dealing with the state of the environment and water protection in Kosovo, and these results can be used as a starting point for assessing the ecological quality of water and monitoring environmental pollution in the Kosovo region.

1. Introduction

In recent decades, the problem with water pollution and growing concern for water quality has been evident all over the globe [1,2,3,4]. Meanwhile, joint efforts by the scientific community and policy-makers continue to find and implement solutions for the conservation and protection of water resources [5,6]. Many studies have shown that the situation is alarming, resulting from the lack of water or the pollution of drinking water [7]. These are the main reasons for the spread of many diseases in less developed countries [8]. According to World Health Organization (WHO) data, every year, close to 500 million people get sick from waterborne diseases, and around 10 million people die from polluted water daily [9]. One can state with certainty that the main problem of human society nowadays is water [10].
Diatoms are widely used due to their high diversity and abundance compared to other groups; they are widespread in aquatic ecosystems and are of great importance due to their unique composition of the silica cell wall and the important applied aspects of their relationship with physicochemical parameters [11,12].
Recent research has proven that diatoms have crucial roles in the assessment of surface waters [13,14,15]. Biological assessment using diatoms is also a requirement of the European Water Framework Directive [16], as they are excellent indicators of water quality. Diatoms provide detailed insight into the health of aquatic ecosystems and respond quickly to environmental changes [17]. Due to their rapid response and sensitivity to the environment, diatoms serve as a valuable tool for monitoring and managing surface waters, including rivers and lakes, helping to preserve healthy and sustainable ecosystems, improve water resource management, and contribute to the development of policies for the protection and management of surface waters [15,18,19,20].
For biological assessment purposes, many European countries use diatom algae [21,22,23,24,25], where, according to some data, after benthic macroinvertebrates, which are the most applied in biological assessment, diatom algae are also included in proportions of up to 54% [19,26,27]. Even in Kosovo, according to research so far, the most applied species in biological assessment have been macroinvertebrates, followed by macrophytes, fish, and diatoms, which have been used in some rivers [1,28,29,30,31,32,33,34,35,36,37].
Given the alarming pollution of river basins in recent years in Kosovo [1,38,39], river basin management plans have recently been approved, which also foresee biological monitoring based on the biological component, including diatom algae.
The Klina River is located in Kosovo and flows entirely through Kosovo’s territory. This river has several branches from forest streams and is influenced by anthropogenic activities, especially when it passes through the cities of Skenderaj and Klina. This study of the algae community, applying diatom indices, reflects the ecological condition of the Klina River and the impact of anthropogenic activities. In this study, based on the quality research data, we examined the applicability of 12 diatom indices to determine the ecological status and analyzed the correlation between diatom index values and environmental variables using Spearmen’s correlation. The objectives of this study were to identify the number of diatom algae species in the Klina River, assess the ecological quality of the Klina River based on diatom algae, and investigate the relationship between diatom indices and environmental variables.

2. Materials and Methods

2.1. Study Area

The Klina River is the left branch of the Drini i Bardhë River (Figure 1). It lies between coordinates 42°40′00″ and 42°50′00″ N and 20°30′00″ and 20°50′00″ E and has a catchment area of 477 km2 [40]. According to the “Report: The state of water in Kosovo 2020” [40,41], its average annual inflows are 2.8 m3s−1, its flow coefficient is 0.22, and its flow module is 4.92 dm3s−1km−2. According to the topographic map on a scale of 1:25,000 for the territory of Kosovo [40,42], the altitude of the watershed ranges from 375 m to 1751 m (Mount Radopole Neck). The minimum rainfall was 571.70 mm, 1081.90 mm, and 880.98 mm, while the average annual temperature was 10 °C [43]. Rock formations from the Paleozoic to the Quaternary take part in the geological construction of the Klinë river basin [42]. The area of the basin is covered with forests and bushes (60.20%), pastures, meadows, and plant areas (22.60%), and others (14.15%) [40] (Figure 1) and (Table 1).
To analyze and determine diatoms, samples were collected from three different sampling locations along the Klina River in 2021. Samples were taken in periphyton and on stones, tree branches, or other existing substrates in the Klina River basin, according to the standard [44].
The samples were placed in glass bottles, while their preservation and fixation were performed in 4% formalin [44]. The preparations were made in the laboratory according to the steps below. For diatom analysis, 5 mL of samples was placed in the test tubes. The supernatant water was removed from the algal material, which had settled on the bottom of the tubes (Figure 2). Then, 10 mL of H2O2 was added to all the samples in the test tubes, and the tubes were placed in a water bath at a temperature of 90 °C for 2–3 h. Then, 1M HCl 37% was added to the samples rich in organic matter to dissolve the carbonates [45,46,47]. After completing this stage, test tubes were placed in the centrifuge for 3–4 min, and the supernatant was removed. After this step, 4 mL of distilled water was added to the test tubes, and the samples were centrifuged 4 times with distilled water until they were thoroughly cleaned. Then, 1–2 drops of formalin were added to ensure preservation. Microscopic slides were made from the obtained material, and a thorough algological analysis of the samples was performed using an optical microscope (Figure 2). The determination of species was based on the keys provided in [48,49,50,51]. During the study, 200 to 400 individuals were counted at each sampling site, and the abundance of species was determined based on these counts. The OMNIDIA 5 program [52] was used to calculate twelve diatom-based indicators (Table 2), which are commonly used to analyze ecological conditions.
In addition to the samples for diatom analysis, samples were also taken for physical-chemical analysis of the water in the Klina River in the exact 3 locations. Samples were used to accurately assess the water quality and prove the correlations between the physicochemical and diatomic parameters.
Physicochemical parameter analyses were performed according to ISO 5667–6 [66]. Water samples for analysis were collected simultaneously with diatom samples. Environmental factors, including pH, water temperature, and dissolved oxygen (DO), were analyzed directly in the field and determined using the portable multiparameter meter HI98194. This multiprobe meter was calibrated before field sampling. Total phosphorus (TP), nitrite (NO2-), and total suspended solids (TSS) were determined using an ultraviolet-visible spectrophotometer, chemical oxygen demand (COD) was analyzed based on protocol NF T90-101, and biochemical oxygen demand (BOD5) was analyzed based on SS by the gravimetry (NF EN 872) parameter; all these were analyzed in the laboratory [66].

2.2. Statistical Analysis

Spearmen’s correlation analysis was used to analyze the correlation between various environmental factors and the assessment of the diatom index; PCA was also used to determine the relationship between environmental variables, while CCA was used to identify the main environmental factors that affect species abundance.
In this study, SPSS 24 was used to analyze Spearmen’s correlation. In contrast, PCA (principal component analysis) and CCA (canonical correlation analysis) were analyzed through the Past 5.0 program.

3. Results and Discussion

During this research, the state of water quality in the Klina River was assessed using diatoms in the three locations, L-1, L-2, and L-3; in addition to this, in these three locations, physicochemical parameters, such as temperature, total suspended solids, pH, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, total phosphorus, and nitrites, were analyzed to assess the quality of the water more accurately. The obtained results for diatoms and physicochemical parameters were compared with the values determined by the recommendations of international standards for monitoring surface waters.
Temperature is one of the most basic physical parameters and should always be measured. The development of aquatic life depends on oxygen. Since the oxygen concentration in water is temperature-dependent, a high water temperature lowers the oxygen solubility, thus limiting the development of the aquatic world. Slight differences in the temperature values were observed at locations L-1, L-2, and L-3. L-1 had a temperature of 13.1 °C, L-2 had a temperature of 16.3 °C, and L-3 had a temperature of 17.1 °C (Figure 3). Based on the temperature values, the water quality belongs to class I.
Total suspended solids (TSS) refer to the concentration (mg/L) of inorganic and organic matter in waters of streams, rivers, lakes, etc. Total suspended solids usually consist of fine particles with a diameter of less than 62 µm [67]. The results of the Klina River analyses were as follows: L-1 had a concentration of total suspended solids of 15 mg/L, L-2 had 47 mg/L, and L-3 had 4 mg/L (Figure 3). According to the results, the first and second locations (L-1 and L-2)) were found to have a higher load of total suspended solids. As a result, damage to the biota can occur. Looking at macrophytes and algae, elevated values of the total suspended solids can reduce 3–13% of the primary productivity, and in phytoplankton, it reduces biomass production by up to 40% [67,68,69].
Dissolved oxygen is essential to sustaining higher forms of biological life. Fish of the Salmonidae family (trout, salmon) require O2 levels of at least 5 mg/L. Other fish will not survive at O2 levels lower than 2 mg/L. Based on the analysis of the Klina River, the following results were obtained: in L-1, the dissolved O2 was 5.35 mg/L; in L-2, it was 3.17 mg/L; and in L-3, it was 4.6 mg/L (Figure 3). The first location belongs to class III of water quality, and the second and third locations belong to class IV based on the classification standard [70]. The water quality based on dissolved oxygen is worse than in the [71] research in Morava e Binqes, while better water quality is reported than in the [72] research in some locations of the Sitnica River in Kosovo.
Chemical oxygen demand (COD) is the amount of oxygen spent oxidizing organic and inorganic substances expressed in mg/L. It measures the total amount of organic and inorganic pollution in polluted waters [73]. According to the Classification of the Environmental Quality of Freshwater in Norway, L-1 belongs to class I, L-2 belongs to class V, and L-3 belongs to class IV (Figure 3). The water quality values of the Klina River compared to previous research [71] are better, except for location 2, where industrial activity is evident, which affects the poor water quality.
The water pH level is one of the leading chemical parameters since many physicochemical reactions in water are controlled by pH. The pH of water affects both biological and chemical processes. pH values below 4.5 and above 9.5 are usually lethal to aquatic organisms. pH affects the solubility of organic compounds, metals, and salts. In highly acidic waters, certain minerals can dissolve and release metals and other chemicals into the water. Most organic pollutants are weak organic acids and are more likely to enter organisms at low pH. The pH values in the Klina River were 7.92 in L-1, 7.56 in L-2, and 7.72 in L-3 (Figure 3). These results conclude that the pH values are within the recommended values required according to Directive 75/440.
Biochemical oxygen demand (BOD5) is one of the pollution indicators used to determine the impacts of wastewater on water quality. Microorganisms decompose organic matter in water, consuming oxygen. Variations in BOD5 in the Klina River were visible. L-1 had BOD5 values of 1.6 mg/L, L-2 showed 23.1 mg/L, and L-3 displayed 9.6 mg/L (Figure 3). Location L-1 has not been under anthropogenic industrial and urban influence and belongs to the first category [73]. In contrast, based on the above results, the other two locations (L-2 and L-3) have higher BOD5 values and belong to the V category. A similar situation regarding BOD and category V water quality is also presented in [74] research on the Topluha River branch, a branch of the same basin as the Klina River.
Phosphorus is a common constituent of agricultural manure, organic manure, and organic waste. Also, it can be found in higher concentrations in wastewater and industrial effluents [75]. It is an essential element for plant life, but when there is too much of it in water, it can accelerate eutrophication. The results of the analyses in the present research indicate high values of total phosphorus in the water. The total phosphorus concentration in the first location (L-1) was 0.047 mg/L, in L-2, it was 0.658 mg/L, and in L-3, it was 0.329 mg/L (Figure 3). The water taken from L-2 and L-3 can be classified as hypertrophic, while the water at L-1 is eutrophic [75,76] (Figure 3). Hypertrophic similarity of the water quality in locations L2 and L3 based on total phosphorus is also presented in the research of [36] in the Nerodime River.
From principal component analysis (PCA) (Figure 4) and the correlation coefficient between physical and chemical parameters (Table 3), it can be seen that there is a relationship between total phosphorus, biochemical and chemical oxygen demand, and total suspended solids (TSS). An increase in total suspended solids and a simultaneous increase in the number of total phosphorus particles can have an impact on the growth of phytoplankton, which causes an increase in the biochemical and chemical oxygen demand and a decrease in dissolved oxygen [77,78,79], while the total phosphorus suggests an increase in organic pollution, which increased the chemical expenditure of oxygen [77,80]. These parameters are closely related and can impact aquatic habitats, resulting in decreased water quality and potentially dangerous conditions for the living things that live there [81,82]. It has also been discovered that the oxygen concentration correlates negatively with the biochemical and chemical consumption of oxygen and total phosphorus. This results from microbial pollution caused by organic contamination, which influences the increase in biochemical oxygen demand and decrease in dissolved oxygen. Anthropogenic causes, including wastewater from residences, livestock, and industrial operations in the Klina River basin, cause this contamination. Similar findings were reported in [83,84,85] investigations in Europe and Asia.
Figure 4 and Table 4 demonstrate a positive association between temperature and NO2−. NO2− levels drop with lower temperatures while increasing with higher temperatures. Higher water temperatures increase microbial activity and reduce nitrates (NO3−) to nitrites (NO2−), explaining the positive association. Higher temperatures accelerate the activity of microorganisms in the nitrogen cycle, leading to a rise in NO2− concentration in water [87].
Table 5, Table 6 and Table 7 present the analysis of diatoms in three locations. Eighty-eight types of diatoms were identified during the research in the Klina River.
A total of 32 species of diatoms were identified in the Kuçicë location (L-1). The species with the highest abundance are Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot at 23.5%, Gyrosigma acuminatum (Kützing) Rabenhorst at 13.4%, Gomphonema minutum (Ag.) Agardh f. minutum at 9.6%, Meridion circulare (Greville) C.A.Agardh at 9.1%, Cocconeis pediculus Ehrenberg at 4.8%, and Gomphonema clavatum Ehr. At 3.2% (Table 5).
Based on the values of the IBD, IPS, IDG, Descy, IDAP, EPID, CEE, WAT, and SHE indices, the water quality is good and belongs to the second class (II) and the oligo-mesotroph trophic level (Table 8).
However, according to the SLA, TDI, and PDI indices, the water quality is moderate and belongs to the third class (III) and the trophic-mesotrophic level. According to the Rott TI index, the water quality belongs to the fourth class, the bad category, and the eutrophic trophic level. Globally, the genus Rhoicosphenia is commonly reported in brackish freshwater and marine ecosystems and can be found on every continent [88].
A total of 37 species of diatoms were identified in the Tushilë location (L-2). The species with the highest abundance are Nitzschia dissipata (Kützing) Grunow ssp. dissipata at 5.8%, Gomphonema parvulum (Kützing) Kützing at 5.8%, Nitzschia palea (Kützing) W. Smith at 5.6%, Craticula ambigua (Ehrenberg) Mann at 4.7%, Gomphonema c.g. Ehrenberg at 4.7%, Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot at 5.0%, Gomphonema subclavatum Grunow at 3.8%, and Gomphonema clavatum Ehr. At 3.8% (Table 6).
According to the values of the IBDBDI, IPS, IDG, Sla, IDAP, CEE, WAT, IDP, and SHE indices, the water quality is moderate and belongs to the third class (III) and the mesotrophic trophic level (Table 7). Based on the Descy index, the water quality is good, belonging to the second class (II) and the oligo-mesotrophic trophic level.
According to the TDI index values, the water quality is poor and belongs to the fourth class (IV) and the trophic eutrophic level (Table 8).
In the location of Klina (L-3), there were 52 species of diatoms. The species with the highest abundance were Cocconeis placenula Ehrenberg at 9.0%, Diatoma vulgaris Bory at 7.4%, Cocconeis placenula Ehrenberg var. euglypta (Ehr.) Grunow at 7.4%, Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot at 6.8%, Amphora ovalis (Kützing) Kützing at 6.8%, and Gomphonema clavatum Ehr. at 3.9% (Table 6).
The water quality is good according to the indexed values of IBD, IPS, IDG, IDAP, EPI-D, CEE, WAT, and SHE. It belongs to the second class (II) and oligo-mesotrophic trophic level. According to the Descy index, the water quality is high, belonging to the first class (I) and the oligotrophic trophic level (Table 7).
According to the SLA index values, the water quality is moderate and belongs to the third class (III) and the trophic-mesotrophic level. However, according to the TDI index, the water analysis is poor and belongs to the fourth category (IV) and the trophic eutrophic level. (Table 7)
Species of the genera Nitzschia and Navicula predominated in three localities. They are cosmopolitan diatoms that prefer alkalophilic environments (pH > 7) and eutrophic waters. Navicula lanceolata prefers electrolyte waters. Regarding pH, the three localities of our research have shown basic pH values related to the preference of the genera Navicula and Nitzschia [89].
Other research in Kosovo used the same diatom indices and biological water quality assessment methods. In a previous study in Kosovo [13], which analyzed the water from the Lepence River basin based on the diatomic indices, the river was classified into good and moderate categories, similar to this research. While the results obtained in this research are comparable to the research of [28] in Kosovo’s Ibar River basin, the water quality based on diatom indices in their studies is high, good, and poor. In contrast, the results in the Klina River show no index falling in the category of poor water quality. Our results, compared to the macroinvertebrate indices from the study of [37] based on the biological assessment of water, show that the Kuçicë site has a similar good ecological status. Likewise, based on the macrophyte indices as bioindicators for ecological water assessments [29], similar results indicating a good ecological status were observed at the Kuçicë and Klina sites. The Klina River has 88 species in total, but the Llapi River has 52 species, according to previous [90] research. This is a good number of species, and according to this study, there are similarities because both water bodies fall into the second ecological category. A similar number of species was also presented in previous [91] research in the Nerodime River, where 70 species of diatoms exist. Still, compared to this river, the Klina River has better water quality. Also, comparing the Klina River flow with the main flow of the Drini Bardhe River, where 77 species are present [92]. It can be said that the Klina River, which is part of this basin, also has many species and similarities in the categorization of water quality. Compared to the flow of the Krena River, where, according to research [93], 28 species of diatoms dominate, the Klina River has a more significant number of species and better water quality. Compared to the countries in the region, like Albania, according to research by [94], the results of this research have similarities according to the Index of Pollution Sensitivity, where it has good and average ecological statuses. Also, compared to the Vjosa River in Albania [95], we have similarities in terms of ecological status. Similarities in the number of species and water quality are also found in research [96] on the Gjirokastra River in Albania. Compared to research in the neighboring country of Macedonia [97,98,99], research in Kosovo is more limited and scarce regarding the monitoring and diversity of diatom algae.
In recent years, much effort has been devoted to understanding ecosystem and species responses to environmental variability and its impact on ecosystem function [100,101,102].
The ordination of species in (Figure 5) showed that GMIN, CPED, RABB, and MCIR were mainly associated with Ph and dissolved oxygen (DO) and were more abundant in sites where Ph and Do were higher. Likewise, species such as NPAD, NDIS, GPAR, CEUG, ESBM, GOMP, and CAMB show a relationship with T°C, BOD, COD, PT, and NO2—the higher the value of the parameters, the greater the abundance of the species. Meanwhile, TSS presents a clear connection to the species CPLE, CPLA, APED, AOVA, TVUL, ESLE, and ADMI.
Previous research indicated [103] that the correlation between diatom indices and environmental variables varies by region, possibly due to differences in the environmental parameters or nutrient gradients utilized to generate each index.
Table 9 shows Spearman’s correlation of the physicochemical parameters and diatomic indices of the river Klina. Total suspended solids (TSS) present a strong negative significant correlation (<0.01) with the IDG, IDAP, EPI-D, TDI, IDP, and SHE indices (Table 9). Because an increase in total suspended solids (TSS) contributes to the rise in eutrophication [104]. This study also finds a negative association between the TSS, IDG, IDAP, EPI-D, TDI, IDP, and SHE indexes (Table 9). The negative correlation between TSS and these indicators is because TSS obstructs light penetration in water, affecting photosynthesis [105] and resulting in poorer health of diatom algae. pH was significantly correlated (<0.01) with IBD, Descy, Sla, CEE, and Wat indices. Similar results regarding pH and the diatomic index are also presented in previous research [15]. Dissolved oxygen presents a significant positive correlation (<0.01) with the IBD, Descy, SLA, CEE, and WAT indexes (Table 9). A similar positive correlation between BOD and the IBD, Descy, SLA, CEE, and WAT indexes was also reported in previous research [103,106] in Turkey. Different countries use IDAP to evaluate the impacts of agriculture, industry, and urban development [64], and based on this context, the river Klina is polluted by urban pollution, which comes from the cities of Skenderaj and Klina and the industries and agricultural activities located in this region. Also, earlier research [29] on the Klina River, based on the assessment of macrophytes as bioindicators of organic pollution, reported the same situation in this river. The biochemical and chemical oxygen expenditures present a significant negative correlation with the indices IBD, Descy, Sla, CEE and Wat (Table 9), similar results were also reported in the research of [106] in Turkey. Since the IBD, Descy, Sla, CEE, and Wat indexes aim to measure the levels of general pollution, organic pollution, and eutrophication [58,63], the increase in biochemical costs indicates a high level of eutrophication; therefore, there was a negative correlation between BOD, COD, and the IBD, Descy, Sla, CEE, and Wat indexes, where the monitoring points that had higher values of biochemistry and oxygen expenditure had lower values in the IBD, Descy, Sla, CEE, and Wat indexes and average ecological status.
Total phosphorus presents a significant negative correlation (<0.05) with the IBD, Descy, Sla, CEE, and Wat indexes (Table 9), similar correlation values were also presented in previous authors’ research [106,107,108]. High levels of total phosphorus affect the growth of biomass of algae, including other types of algae, which can affect the development of diatoms, oxygen reductions and increases in biochemical and chemical oxygen consumption, which can also affect the eutrophication of waters and their acidification [109,110,111]. Therefore, the negative correlation of this parameter should be of great concern as it also shows the high presence of organic pollution from the activities carried out around the Klina River.
Environmental stresses that affect the diatom community and water quality indices of diatom algae in the Klinë River include industrial activities along the river’s course, sewage discharge, anthropogenic pollution, and agricultural activities. Various studies [112] report similar stressors, including climate change, and recommend continuing international efforts to develop more effective tools and strategies for biomonitoring based on biological components, including diatom metrics, in the context of environmental variables.

4. Conclusions

In this study, we investigated the water quality in the Klina River based on the composition of diatoms in 2020. We selected twelve diatom indices, IBD, IPS, IDG, Descy, SLA, IDAP, EPI-D, CEE, WAT, TDI, IDP, and SHE, to observe the quality and ecological status in the Klina River.
This study found that diatom indices were related to environmental factors. pH and DO show strong positive relationships (p < 0.01) with IBD, Descy, SLA, CEE, and WAT indices. TSS had a high negative connection (p < 0.01) with IDG, IDAP, EPI-D, TDI, IDP, and SHE indexes. TP, BOD, and COD had a significant negative correlation (p < 0.05) with the IBD, Deascy, Sla, CEE, and Wat indices.
Based on the results, the Klina River belongs to the second- and third-class water quality categories and falls in the good and moderate ecological categories based on diatomic indices.
Also, based on the physical and chemical parameters, the first location (L-1) had higher water quality, with lower levels of total suspended solids (TSS), biochemical oxygen demand (BOD), and total phosphorus. In contrast, the second (L-2) and third (L-3) locations showed greater pollution levels, most likely due to industrial and urban discharges, pollution from agriculture, improper waste management, and household wastewater flows, as seen by the heightened TSS, BOD, and TP concentrations. These results indicate the necessity of initiatives that should be undertaken to preserve surface water ecosystems, especially in areas with high levels of pollution, to protect and improve the ecological integrity of the Klina River. To ensure sustainable management of this surface water resource, future research should focus on long-term monitoring and the application and setting of reference values for biological water monitoring to address the identified sources of pollution.

Author Contributions

Conceptualization, O.F., R.K. and A.S.; methodology, O.F. and A.S.; software, D.N., F.S. and P.B.; validation, P.B., B.Đ., R.H. and D.N.; formal analysis, R.K. and F.S.; investigation, O.F. and D.D.; resources, P.B.; data curation, O.F., D.D. and B.Đ.; writing—original draft preparation, O.F., A.S., P.B., R.K. and D.D.; writing—review and editing, O.F. and A.B.; visualization, D.D., U.R. and R.H.; supervision, U.R. and B.Đ. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

All data available upon the reasonable request from the corresponding authors.

Acknowledgments

The authors also thank University North, Croatia, for helping with the scientific project, “Hydrological and geodetic analysis of the watercourse”, from 2024.

Conflicts of Interest

The authors declare no conflicts of interest.

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Ecologies 06 00015 g001
Figure 1. Sampling locations and investigation areas.
Figure 1. Sampling locations and investigation areas.
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Figure 2. The methodology of determination of diatom.
Figure 2. The methodology of determination of diatom.
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Figure 3. Results of physicochemical analysis in Klina River.
Figure 3. Results of physicochemical analysis in Klina River.
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Figure 4. Ordination plot of principal components analysis (PCA) of physicochemical parameters.
Figure 4. Ordination plot of principal components analysis (PCA) of physicochemical parameters.
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Figure 5. Canonical correspondence analysis (CCA) diagram showing environmental variables and the species of diatoms that were the most abundant.
Figure 5. Canonical correspondence analysis (CCA) diagram showing environmental variables and the species of diatoms that were the most abundant.
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Table 1. The sampling sites with geographic coordinates and hydromorphological features.
Table 1. The sampling sites with geographic coordinates and hydromorphological features.
Sampling StationsLatitude (N) Longitude(E) Altitude (m a.s.l.)Hydro Morphology
L1Kuçicë42°37′8″ N
20°53′49″ E
1200		Natural habitat: mountainous source area with a flow velocity exceeding 2.5 m per second.
L2Tushilë44°42′43″ N
20°45′39″ E
561		The river is influenced by various agricultural and industrial activities, with no impact on the riverbed and a slow flow velocity of over 1 m per second.
L3Klinë42°61′52.56″ N
20°57′57.35″ E
381		The riverbed is concreted on all sides and is affected by urban waters, industrial discharges, and agricultural activities. Its flow velocity is 1.5 m per second.
Table 2. List of diatom indices calculated for the current investigation.
Table 2. List of diatom indices calculated for the current investigation.
Index ReferencesStressor Type Sensibility
IBD (Biological diatom index) [53]General pollution
IPS (Index of Pollution Sensitivity) [54,55]Pollution sensitivity index
IDG (Generic diatom index) [56]General pollution
Descy (Descy’s pollution metric) [52]General pollution
SLA (Sladeček’s pollution metric) [57,58]Saprobity (BOD)
IDAP (Indece Diatomique Artois Picardie)[59]General pollution
EPI-D (Eutrophication pollution index) [60]Pollution-Trophic status
CEE (European index) [61]General pollution
WAT (Watanabe’s Index) [62]Saprobity (BOD)
TDI (Trophic diatom index) [63]Trophic status
IDP (Pampean diatom index) [64]Organic pollution/eutrophication
SHE (Steinberg and Schiefele’s index) [63,65]Pollution-Trophic status
Table 3. Determination of quality, ecological status, and trophic status based on diatom index values [86].
Table 3. Determination of quality, ecological status, and trophic status based on diatom index values [86].
Water Quality ClassesEcological StatusIBD, IPS, IDG, DESCY, SLA, IPI-D, CEE, WAT, TDI, IDP, SHETrophic Status
IHigh17–20oligotrophic
IIGood13–16oligo-mesotrophic
IIIAverage9–12mesotrophic
IVPoor5–8eutrophic
VBad1–4hypertrophic
Table 4. Correlation between physicochemical parameters.
Table 4. Correlation between physicochemical parameters.
T°CTSSpHDOBODCODPTNO2−
T°C1
TSS0.0787771
pH−0.79274−0.670111
DO−0.62337−0.82860.9708021
BOD0.6477260.810532−0.97789−0.99951
COD0.5902690.851198−0.95997−0.999130.9973221
PT0.722110.746514−0.99413−0.991060.9947770.9846471
NO2−0.9890650.224937−0.87397−0.731870.7530030.7028610.8162371
Table 5. Results of diatoms at Kuçicë location (L-1).
Table 5. Results of diatoms at Kuçicë location (L-1).
No.CodeAbd.%Taxon Name
1AOVA21.1Amphora ovalis (Kützing) Kützing
2AVEN10.5Amphora veneta Kützing
3AUDI10.5Aulacoseira distans (Ehr.)Simonsen
4CPED94.8Cocconeis pediculus Ehrenberg
5CPLA63.2Cocconeis placentula Ehrenberg
6CPLE52.7Cocconeis placentula Ehrenberg var.euglypta (Ehr.) Grunow
7CPLI63.2Cocconeis placentula Ehrenberg var.lineata (Ehr.) Van Heurck
8COPL10.5Cocconeis pseudolineata (Geitler) Lange-Bertalot
9DOBL10.5Diploneis oblongella (Naegeli) Cleve-Euler
10GDEC10.5Geissleria decussis(Ostrup) Lange-Bertalot & Metzeltin
11GCLA63.2Gomphonema clavatum Ehr.
12GGRA31.6Gomphonema gracile Ehrenberg
13GMIN189.6Gomphonema minutum (Ag.) Agardh f. minutum
14GOLI10.5Gomphonema olivaceum (Hornemann) Brébisson
15GPUM52.7Gomphonema pumilum (Grunow) Reichardt & Lange-Bertalot
16GSCL52.7Gomphonema subclavatum Grunow
17GYAC2513.4Gyrosigma acuminatum (Kützing) Rabenhorst
18GYAT52.7Gyrosigma attenuatum (Kützing) Rabenhorst
19HARC31.6Hannaea arcus (Ehr.) Patrick
20MCIR179.1Meridion circulare (Greville) C.A.Agardh
21NERI10.5Navicula erifuga Lange-Bertalot in Krammer & Lange-Bertalot
22NHIN42.1Navicula hintzii Lange-Bertalot
23NREI10.5Navicula reinhardtii (Grunow) Grunow in Cl. & Möller
24NTPT10.5Navicula tripunctata (O.F.Müller) Bory
25NVIR52.7Navicula viridula (Kützing) Ehrenberg
26NVUL10.5Navicula vulpina Kützing
27NEDU10.5Neidium dubium (Ehrenberg) Cleve
28NAMP10.5Nitzschia amphibia Grunow
29NLIN10.5Nitzschia linearis (Agardh) W.M.Smith
30NPAL52.7Nitzschia palea (Kützing) W.Smith
31RABB4423.5Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot
32TFLO10.5Tabellaria flocculosa (Roth) Kützing
Table 6. Results of diatoms in the Tushilë location (L-2).
Table 6. Results of diatoms in the Tushilë location (L-2).
No.CodeAbd.%Taxon Name
1AAEQ61.8Amphora aequalis Krammer
2CEUG144.1Cocconeis euglypta Ehrenberg emend Romero & Jahn
3CPLE144.1Cocconeis placentula Ehrenberg var.euglypta (Ehr.) Grunow
4COPL82.3Cocconeis pseudolineata (Geitler) Lange-Bertalot
5CAMB164.7Craticula ambigua (Ehrenberg) Mann
6CCUH10.3Craticula cuspidata Kützing var.heribaudii M.Peragallo
7CMEN113.2Cyclotella meneghiniana Kützing
8CMIN92.6Cymbella minuta Hilse ex Rabenhorst
9CNAV61.8Cymbella naviculiformis Auerswald ex Heiberg
10EPRO30.9Encyonema prostratum (Berkeley) Kützing
11ENV141.2Encyonema ventricosum (Agardh) Grunow morphotype 1 in Krammer
12ESBM164.7Eolimna subminuscula (Manguin) Moser Lange-Bertalot & Metzeltin
13GOMP164.7GOMPHONEMA C.G. Ehrenberg
14GCLA133.8Gomphonema clavatum Ehr.
15GEXL10.3Gomphonema exilissimum (Grun.) Lange-Bertalot & Reichardt
16GGRA20.6Gomphonema gracile Ehrenberg
17GITA41.2Gomphonema italicum Kützing
18GMIN30.9Gomphonema minutum (Ag.) Agardh f. minutum
19GPAR205.8Gomphonema parvulum (Kützing) Kützing
20GSCL133.8Gomphonema subclavatum Grunow
21MCIR123.5Meridion circulare (Greville) C.A.Agardh
22NAMB72.0Navicula amabilis Hustedt
23NCTE123.5Navicula cryptotenella Lange-Bertalot
24NHIN61.8Navicula hintzii Lange-Bertalot
25NRAD20.6Navicula radiosa Kützing
26NRCH61.8Navicula reichardtiana Lange-Bertalot
27NROS61.8Navicula rostellata Kützing
28NDIS205.8Nitzschia dissipata (Kützing) Grunow ssp.dissipata
29NLIN51.5Nitzschia linearis (Agardh) W.M.Smith
30NPAL175.0Nitzschia palea (Kützing) W.Smith
31NPAD195.6Nitzschia palea (Kützing) W.Smith var.debilis(Kützing)Grunow in Cleve & Grunow
32NSOC72.0Nitzschia sociabilis Hustedt
33RABB175.0Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot
34SBRE61.8Surirella brebissonii Krammer & Lange-Bertalot
35SULN92.6Synedra ulna (Nitzsch.)Ehr.
36TFLO20.6Tabellaria flocculosa (Roth) Kützing
37UULN92.6Ulnaria ulna (Nitzsch) Compère
Table 7. Results of diatoms at the Klinë location (L-3).
Table 7. Results of diatoms at the Klinë location (L-3).
No.CodeAbd.%Taxon Name
1ADMI173.5Achnanthidium minutissimum (Kützing) Czarnecki
2ADBI61.2Achnanthidium biasolettianum (Grunow in Cl. & Grun.) Lange-Bertalot
3AMNU20.4Amphora minutissima W. Smith
4APED153.1Amphora pediculus (Kützing) Grunow
5AOVA336.8Amphora ovalis (Kützing) Kützing
6ALIB20.4Amphora libyca Ehr.
7AVEN30.6Amphora veneta Kützing
8CPED81.6Cocconeis pediculus Ehrenberg
9CPLE367.4Cocconeis placentula Ehrenberg var.euglypta (Ehr.) Grunow
10CPLA449.0Cocconeis placentula Ehrenberg
11CPLI234.7Cocconeis placentula Ehrenberg var.lineata (Ehr.)Van Heurck
12COPL132.7Cocconeis pseudolineata (Geitler) Lange-Bertalot
13CLAN61.2Cymbella lanceolata (Agardh ?)Agardh
14DMON193.9Diatoma moniliformis Kützing ssp.moniliformis (moniliforme?)
15DVUL367.4Diatoma vulgaris Bory
16EMNT91.8Encyonema minutum (Hilse in Rabh.) D.G. Mann morphotype 2
17ESLE142.9Encyonema silesiacum (Bleisch in Rabh.) D.G. Mann
18EPRO10.2Encyonema prostratum (Berkeley) Kützing
19GMIN81.6Gomphonema minutum (Ag.) Agardh f. minutum
20GCLA193.9Gomphonema clavatum Ehr.
21GSCL10.2Gomphonema subclavatum Grunow
22GOLI20.4Gomphonema olivaceum (Hornemann) Brébisson
23GPAR102.0Gomphonema parvulum (Kützing) Kützing
24GPRB91.8Gomphonema pumilum (Grunow) Reichardt & Lange-Bertalot var. rigidum Reichardt & Lange-Bertalot f.biseriatum Morales & Vis
25GTEA61.2Gomphonema tergestinum Fricke f. anormale
26MAAT10.2Mayamaea atomus (Kützing) Lange-Bertalot
27MVAR30.6Melosira varians Agardh
28NANT112.3Navicula antonii Lange-Bertalot
29NCPR132.7Navicula capitatoradiata Germain
30NHIN40.8Navicula hintzii Lange-Bertalot
31NCTE40.8Navicula cryptotenella Lange-Bertalot
32NGRE20.4Navicula gregaria Donkin
33NLLT10.2Navicula lanceolata (Agardh) Kützing
34NTPT61.2Navicula tripunctata (O.F.Müller) Bory
35NVEN51.0Navicula veneta Kützing
36NVMA20.4Navicula vulpina Kützing var.mascarenae Coste & Ricard
37NEDU10.2Neidium dubium (Ehrenberg)Cleve
38NACI20.4Nitzschia acicularis Kützing) W.M.Smith
39NAMP10.2Nitzschia amphibia Grunow
40NCPL10.2Nitzschia capitellata Hustedt in A.Schmidt & al.
41NDIS153.1Nitzschia dissipata (Kützing) Grunow ssp.dissipata
42NFON30.6Nitzschia fonticola Grunow in Cleve et Möller
43NRAD40.8Navicula radiosa Kützing
44RABB336.8Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot
45SNEG20.4Surirella neglecta Reichardt
46SLIN40.8Surirella linearis W.M.Smith in Schmidt & al.
47UULN10.2Ulnaria ulna (Nitzsch) Compère
48LGOE10.2Luticola goeppertiana (Bleisch in Rabenhorst) D.G.Mann in Round Crawford & Mann
49LVEN10.2Luticola ventricosa (Kützing) D.G. Mann in Round Crawford & Mann
50FCVA40.8Fragilaria capucina Desmazieres var.vaucheriae (Kützing) Lange-Bertalot
51FCAP71.4Fragilaria capucina Desmazieres
52MCIR142.9Meridion circulare (Greville) C.A.Agardh
Table 8. Values of diatoms indices in the Klina River.
Table 8. Values of diatoms indices in the Klina River.
No.Diatom IndexL-1 (Kuçicë)L-2 (Tushillë)L-3 (Klinë)
1IBD (Biological diatom index)15.512.715.2
2IPS (Index of Pollution Sensitivity)14.511.514.5
3IDG (Generic diatom index)13.411.313.7
4Descy (Descy’s pollution metric) 17.213.316.3
5SLA (Sladeček’s pollution metric) 12.611.912.3
6IDAP (Indece Diatomique Artois-Picardie) 13.512.114.5
7EPI-D (Eutrophication pollution index) 13.311.413.4
8CEE (European index)15.210.114.1
9WAT (Watanabe’s Index)16.310.915.4
10TDI (Trophic diatom index)8.77.09.9
11IDP (Pampean diatom index)11.810.212.3
12SHE (Steinberg and Schiefele’s index)13.812.413.9
Table 9. The Spearmen’s correlation between physicochemical parameters and diatoms indices.
Table 9. The Spearmen’s correlation between physicochemical parameters and diatoms indices.
Correlations
IBDIPSIDGDescySLAIDAPEPI-DCEEWATTDIIDPSHE
Spearman’s rhoT°CCorrelation Coefficient−0.5000.0000.500−0.500−0.5000.5000.500−0.500−0.5000.5000.5000.500
Sig. (2-tailed)0.6671.0000.6670.6670.6670.6670.6670.6670.6670.6670.6670.667
N333333333333
TSSCorrelation Coefficient−0.500−0.866−1.000 **−0.500−0.500−1.000 **−1.000 **−0.500−0.500−1.000 **−1.000 **−1.000 **
Sig. (2-tailed)0.6670.333 0.6670.667 0.6670.667
N333333333333
pHCorrelation Coefficient1.000 **0.8660.5001.000 **1.000 **0.5000.5001.000 **1.000 **0.5000.5000.500
Sig. (2-tailed) 0.3330.667 0.6670.667 0.6670.6670.667
N333333333333
Dissolved oxygen (DO)Correlation Coefficient1.000 **0.8660.5001.000 **1.000 **0.5000.5001.000 **1.000 **0.5000.5000.500
Sig. (2-tailed) 0.3330.667 0.6670.667 0.6670.6670.667
N333333333333
BODCorrelation Coefficient−1.000 **−0.866−0.500−1.000 **−1.000 **−0.500−0.500−1.000 **−1.000 **−0.500−0.500−0.500
Sig. (2-tailed) 0.3330.667 0.6670.667 0.6670.6670.667
N333333333333
CODCorrelation Coefficient−1.000 **−0.866−0.500−1.000 **−1.000 **−0.500−0.500−1.000 **−1.000 **−0.500−0.500−0.500
Sig. (2-tailed) 0.3330.667 0.6670.667 0.6670.6670.667
N333333333333
PTCorrelation Coefficient−1.000 **−0.866−0.500−1.000 **−1.000 **−0.500−0.500−1.000 **−1.000 **−0.500−0.500−0.500
Sig. (2-tailed) 0.3330.667 0.6670.667 0.6670.6670.667
N333333333333
NO2−Correlation Coefficient−0.5000.0000.500−0.500−0.5000.5000.500−0.500−0.5000.5000.5000.500
Sig. (2-tailed)0.6671.0000.6670.6670.6670.6670.6670.6670.6670.6670.6670.667
N333333333333
** Correlation is significant at the 0.01 level (2-tailed).
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Fetoshi, O.; Koto, R.; Shala, A.; Sallaku, F.; Bytyçi, P.; Nuha, D.; Đurin, B.; Hasalliu, R.; Bytyçi, A.; Rathnayake, U.; et al. Klina River Water Quality Assessment Based on Diatom Algae. Ecologies 2025, 6, 15. https://doi.org/10.3390/ecologies6010015

AMA Style

Fetoshi O, Koto R, Shala A, Sallaku F, Bytyçi P, Nuha D, Đurin B, Hasalliu R, Bytyçi A, Rathnayake U, et al. Klina River Water Quality Assessment Based on Diatom Algae. Ecologies. 2025; 6(1):15. https://doi.org/10.3390/ecologies6010015

Chicago/Turabian Style

Fetoshi, Osman, Romina Koto, Albona Shala, Fatbardh Sallaku, Pajtim Bytyçi, Demokrat Nuha, Bojan Đurin, Rozeta Hasalliu, Arbëri Bytyçi, Upaka Rathnayake, and et al. 2025. "Klina River Water Quality Assessment Based on Diatom Algae" Ecologies 6, no. 1: 15. https://doi.org/10.3390/ecologies6010015

APA Style

Fetoshi, O., Koto, R., Shala, A., Sallaku, F., Bytyçi, P., Nuha, D., Đurin, B., Hasalliu, R., Bytyçi, A., Rathnayake, U., & Dogančić, D. (2025). Klina River Water Quality Assessment Based on Diatom Algae. Ecologies, 6(1), 15. https://doi.org/10.3390/ecologies6010015

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