Wetlands serve as critical interfaces between terrestrial and aquatic ecosystems, offering ecological, hydrological, and social benefits, including biodiversity conservation, water filtration, nutrient cycling, and habitat provision (Blackwell, 2011). Periphyton, a key component of freshwater ecosystems composed of bacteria, fungi, algae, and protozoa, plays a vital role in aquatic food webs by driving primary productivity, nutrient dynamics, and water quality (Gulzar and Agric, 2017; Kumar, 2017; Rojo et al., 2017; Saxena et al., 2024; Singh and Singh, 2024). Found in diverse aquatic habitats, from oligotrophic to eutrophic systems, Periphyton acts as a sensitive bioindicator of ecological health and trophic states (Rojo et al., 2017; Baluni et al., 2019). Its density and diversity are influenced by physicochemical factors such as temperature, pH, nutrients, dissolved oxygen, and turbidity, with disruptions potentially impacting ecosystem balance (Tariq et al., 2021). Elevated nutrient levels, particularly nitrogen and phosphorus, can cause eutrophication and algal blooms, while stable conditions promote diverse periphyton communities and ecological integrity (Pastorino et al., 2024).

The Asan Wetland, located in Uttarakhand’s Dehradun district, is a Ramsar site of global ecological importance, known for its rich biodiversity and as a critical stopover for migratory birds (Khanna and Natural, 2013; Pathak et al., 2024). However, anthropogenic pressures such as agricultural runoff, pollution, habitat modification, tourism, and boating are threatening its ecological health and water quality (Kumar et al., 2018; Rai et al., 2024). Despite its significance, there is a lack of focused research on the wetland’s periphytic communities, which serve as crucial bioindicators of water quality (Sabater and Admiraal, 2005). Although a substantial body of literature exists on limnology at the international and national level (Lai et al., 2018). studied the diatom communities to describe their relationships with environmental variables and to evaluate the impact of an extreme flash flood (Ruggiero et al., 2004). examines the Inter- and intra-annual variation of water chemistry and phytoplankton biomass were addressed. High species richness, diversity, and evenness were found both in epiphytic and epilithic assemblages (Beauger et al., 2020; Tanuja and Nautiyal, 2023) investigated the diatom flora from mineral springs in Auvergne (France) in which a total of 58 taxa were found (Gaiser, 2009; Kaonga and Monjerezi, 2012; Vis et al., 2016)., studied the diatom assemblage in different river basins (Hill et al., 2000; Sabater and Admiraal, 2005; Montuelle et al., 2010; DeNicola and Kelly, 2014) studied the role of periphyton assemblage and their role as an indicator (Wetzel, 1983), recommendations for future work on periphyton (Trbojević et al., 2017), studied the periphyton assemblage in an urban reservoir (Goldsborough et al., 2005)., investigates the periphyton in lakes and wetlands (Wetzel, 2005), also demonstrates the role of periphytons and their management.

In other studies that were carried out in other parts on different rivers and streams on diatom assemblage, their role, as indicators were carried out by (Kelly et al., 1995; Stevenson et al., 2010; Hill et al., 2001; Feio et al., 2007; Kelly et al., 2009; Rimet, 2012; Lavoie et al., 2014; Lobo et al., 2016; Newton et al., 2020; Bartwal and Nautiyal, 2023). Studies on the wetlands were carried out by (Kennish, 2002; Lone et al., 2012; Alam et al., 2017; Mengesha, 2017; Newton et al., 2020; Asgher et al., 2021; Zainulabdeen and Nagaraj, 2022), studied the streams of kashmir himalaya and Arunachal pradesh (Haq et al., 2023; Mustfa et al., 2023; Singh and Himalaya, 2024), studied the periphyton community in uttarakhand (SAGIR and AK Dobriyal, 2020; Gogoi et al., 2021), studied the periphyton community in ponds (Kumar et al., 2013; Mustfa et al., 2023; Vivek Santhiya and Athithan, 2024), studied the periphyton of manipur (Lobo et al., 2016; Trbojević et al., 2017; Alikhani et al., 2023).

Research on periphyton in Uttarakhand state, especially in the regions of the Himalayas. Notable contributions in this area include the works of (Baluni et al., 2018) studied ecological characteristics and the periphytic algal community of the Khankra stream of Garhwal Himalaya, found that the periphytic algal community of Khankra is represented by 21 taxa belonging to 3 major classes (Chauhan and Sharma, 2016; Bahuguna et al., 2021). Found that 19 genera represented the periphytic algal diversity of the Mal Gad stream (Rashid et al., 2013). studied the Periphytic Algal Community of Doodh Ganga and Khansha-Mansha Streams of Yusmarg Forests (Mustfa et al., 2023; SAGIR and AK Dobriyal, 2020). studied the periphyton community of the Nayar River and its tributaries indicated that all these physicochemical parameters were favourable for periphyton growth during the winter season (Badoni et al., 1997; Nautiyal and Kumar, 2001; Nautiyal et al., 2014; Bisht et al., 2019). studied the algal and faunal communities of the Garhwal Himalayas (Lohani and Pant, B, 2017; Yadav et al., 2018) studied the abundance and seasonal variation of Bhimtal Lake and river Ganga (Tariq et al., 2021). investigate the distribution patterns, density, diversity and ecology of the periphyton community in the Balkhila stream, which is a glacier-fed tributary of the Alaknanda River in the Chamoli district of Uttarakhand (Gupta et al., 2008). examines the bio-physical chemical parameters of the Motrowala swamp.

These studies show that periphyton is very sensitive to changes in water quality factors and can show signs of ecological damage early on. The objective of this study is to address the knowledge deficit about the ecological status of the Asan Wetland and its resilience to environmental pressures by evaluating the periphyton density and diversity.

The objectives of this study are to:

• Quantify the density and diversity of periphyton communities in the Asan Wetland,

This study investigates the interactions between periphytic communities and environmental factors to develop sustainable management strategies for conserving and restoring the Asan Wetland ecosystem, emphasizing the importance of periphyton in maintaining ecological functions. The findings will provide a basis for future research on periphyton’s role in wetland conservation and offer valuable insights into the health of the Asan Wetland.

The paper is structured as follows: Section 2 details the study area, sampling procedures, and statistical methods; Section 3 presents the results through graphs and figures; and Section 4 discusses the findings, supported by comparisons with previous research.

For a better understanding of the overall water quality and environmental conditions in the Asan Wetland, we examined periphytons and other physicochemical factors at three different sites (S1, S2, and S3) from November 2021 to October 2023. The average monthly fluctuations in physicochemical parameters S1, S2, and S3) in the Asan Wetland are illustrated in Tables 2–4, respectively. The cumulative analysis of the three tables provides a detailed overview of ecological variations among the three different sites within the Asan Wetland. Water temperatures at all locations exhibited analogous trends, with the lowest temperatures observed in January (11.80°C ± 0.43°C at S1, 12.25°C ± 0.22°C at S2, and 11.35°C ± 0.22°C at S3), while peak temperatures were noted in June (26.2°C ± 0.15°C at S1, 25.9°C ± 0.22°C at S2, and 26.0°C ± 0.08°C at S3). The pH was consistently recorded as slightly alkaline across all three sites, with the highest values (8.55 ± 0.08 at S1, 8.35 ± 0.15 at S2, 8.75 ± 0.08 at S3) generally occurring in January, while lower values (7.15 ± 0.08 at S1, 7.25 ± 0.08 at S2, 7.30 ± 0.15 at S3) were noted in July-August. Turbidity levels were lowest in December (29.5 ± 0.71 NTU at S1, 24.5 ± 0.71 NTU at S2) and in January at S3 (20.5 ± 0.71 NTU), with a significant rise observed in July (211 ± 1.42 NTU at S1, 201 ± 1.42 NTU at S2, 203.5 ± 2.13 NTU at S3). Transparency exhibited an inverse correlation with turbidity, with the highest transparency recorded in January across all locations (60.6 ± 0.43 cm at S1, 57.2 ± 1.42 cm at S2, 63.6 ± 0.29 cm at S3) and the lowest transparency occurring during the monsoon in August (19.05 ± 1.35 cm at S1, 18.65 ± 0.64 cm at S2, 20.9 ± 0.85 cm at S3). The total dissolved solids (TDS) levels were minimal in January (164 ± 5.66 mg/L at S1, 173.5 ± 2.13 mg/L at S2, 178 ± 2.83 mg/L at S3) and escalated during the monsoon, reaching a maximum in August (308.5 ± 4.95 mg/L at S1, 311 ± 4.25 mg/L at S2, 272 ± 4.25 mg/L at S3). Electrical conductivity mirrored the trends of total dissolved solids (TDS), with peak values of 240.9 ± 1.98 m/cm at S1, 250.75 ± 0.78 m/cm at S2, and 262.4 ± 4.11 m/cm at S3 during the monsoon months of August, with the lowest values recorded in January (122.4 ± 2.55 m/cm at S1, 122.85 ± 0.64 m/cm at S2 and 126.05 ± 1.35 m/cm at S3). Higher conductivity during the monsoon reflects increased ionic content in the water due to runoff and mineral dissolution. Dissolved oxygen levels were highest in January with values (10.2 ± 0.57 mg/L at S1, 10.6 ± 0.22 mg/L at S2, and 10.4 ± 0.08 mg/L at S3) while lower values were recorded during the warmer and monsoon month, especially in August (7.6 ± 0.36 mg/L at S1, 7.7 ± 0.15 mg/L at S2, 7.4 ± 0.08 mg/L at S3). Total hardness at all sites was generally higher in December (178.5 ± 0.71 mg/L at S1, 181.5 ± 0.71 mg/L at S2 and 184 ± 1.42 mg/L at S3) and dropped during the monsoon season, with values (141 ± 2.83 mg/L at S1, 127 ± 5.66 mg/L at S2, 146 ± 1.42 mg/L at S3) in July and August. Total Alkanity was found to be maximum in January at all sites (129.5 ± 2.13 mg/L at S1, 125.5 ± 0.71 mg/L at S2, 131.5 ± 2.13 mg/L at S3) while minimum values were observed in July and August (76 ± 8.49 mg/L at S1, 78 ± 2.83 mg/L at S2 and 85 ± 7.08 mg/L at S3). BOD and COD values were found to be higher in August (3.50 ± 0.29 mg/L at S1, 3.60 ± 0.00 mg/L at S2, 3.75 ± 0.22 mg/L at S3) and (4.75 ± 0.08 mg/L at S1, 4.85 ± 0.08 mg/L at S2 and 4.80 ± 0.15 mg/L at s3) respectively while lowest in January with values of BOD (1.65 ± 0.08 mg/L at S1, 1.80 ± 0.15 mg/L at S2, 1.90 ± 0.15 mg/L at S3) and COD (2.40 ± 0.15 mg/L at S1, 2.95 ± 0.08 mg/L at S2, 2.45 ± 0.08 mg/L at S3).

Phosphorus is a key nutrient that promotes algal growth and is often a limiting factor in freshwater systems. The phosphorus levels at all three sites indicate a moderate to high nutrient load, with almost similar values that were found to be higher in August (1.20 ± 0.15 mg/L at S1, 1.25 ± 0.08 mg/L at S2, 1.20 ± 0.15 mg/L at S3) while fall in January with values (0.65 ± 0.22 mg/L at S1, 0.45 ± 0.08 mg/L at S2, 0.35 ± 0.08 mg/L at S3. Nitrate levels across all three sites are moderate, with relatively similar nitrate concentrations at all sites with values higher in December (1.50 ± 0.15 mg/L at S1, 1.55 ± 0.08 mg/L at S2, 1.40 ± 0.15 mg/L at S3) and lower in July (0.35 ± 0.04 mg/L at S1, 0.25 ± 0.08 mg/L at S2, 0.33 ± 0.03 mg/L at S3).

Potassium is a vital element for plant growth; however, it is less prone to induce eutrophication than nitrogen and phosphorus. Although there is no explicit regulatory limit for potassium in aquatic environments, potassium concentrations in natural waters generally vary from 0 to 10 mg/L. Potassium concentrations were measured at 2.73 ± 0.02 mg/L at S1, 2.50 ± 0.15 mg/L at S2, and 2.85 ± 0.08 mg/L at S3, while Sodium levels were recorded at 4.65 ± 0.78 mg/L at S1, 4.10 ± 0.15 mg/L at S2, and 4.05 ± 0.06 mg/L at S3. Both elements exhibited elevated levels in July and August, followed by a decline in January and February, with Sodium values of 2.52 ± 0.04 mg/L at S1, 2.70 ± 0.05 mg/L at S2, and 2.60 ± 0.02 mg/L at S3, and Potassium values of 1.69 ± 0.08 mg/L at S1, 1.69 ± 0.03 mg/L at S2, and 1.69 ± 0.02 mg/L at S3.

Free CO₂ in water results from the breathing of aquatic organisms and the breakdown of organic waste. It is a crucial element for photosynthesis in aquatic flora and algae. Free CO₂ concentrations were nearly uniform across all sites, peaking in February (2.93 ± 0.25 mg/L at S1, 2.35 ± 0.22 mg/L at S2, 2.55 ± 0.08 mg/L at S3) and declining in September (1.10 ± 0.15 mg/L at S1, 0.80 ± 0.15 mg/L at S2, 0.75 ± 0.08 mg/L at S3).

The periphyton was represented in this study by 18 different periphytic taxa that belong to three different classes. These classes include Bacillariophyceae (Cymbella, Navicula, Nitzschia, Fragilaria Meridion, Synedra, Gomphonema, Tabellaria, and Diatoma). Ulothrix, Spirogyra, Cosmarium, Microspora, Chlorella, Oedogomium, Zygnema, and Cladophora are members of the Chlorophyceae family, while Phormidium is a member of the Cyanophyceae. The average monthly variations in the density of periphyton distributed in three classes at sites S1, S2, and S3 of the Asan Wetland over a 2-year study period (November 2021 to October 2023) are illustrated in Table 5.

The total density of all classes at sites S1, S2, and S3, as well as the overall density of the Asan wetland throughout the 2-year study period from November 2021 to October 2023, is given in Table 6. The peak periphytic density (individuals/cm²) recorded was 322.67 ± 89.08 × 10³ in January, with all three classes exhibiting maximum values at S3: Bacillariophyceae (197 ± 1.42 × 10³ at S1, 310 ± 25.46 × 10³ at S2, 332 ± 2.83 × 10³ at S3), Chlorophyceae (20 ± 11.32 × 10³ at S1, 42 ± 2.83 × 10³ at S2, 44 ± 11.32 × 10³ at S3) and Cyanophyceae (4 ± 2.83 × 10³ at S1, 8 ± 0.00 × 103 at S2, 11 ± 1.42 × 10³ at S3. The monsoon months (June to August) had the lowest densities, most likely as a result of increased sedimentation and water turbidity, which hinder light penetration and have an impact on periphyton growth. The minimum periphytic density (individuals/cm²) recorded was 18 ± 5.57 × 10³ in August, with Bacillariophyceae values of 5 ± 4.25 × 10³ at S1, 12 ± 5.66 × 10³ at S2, and 20 ± 2.83 × 10³ at S3; Chlorophyceae values of 1 ± 1.42 × 10³ at S1, 2 ± 2.83 × 10³ at S2, and 0 ± 0 × 10³ at S3; and no Cyanophyceae detected at any site.

The current study illustrates the annual percentage composition of periphytic flora in the Asan wetland over 2 years, as depicted in Figure 2, indicating that Bacillariophyceae constituted the predominant group (89%–90%), succeeded by Chlorophyceae (7%–9%) and Cyanophyceae or Myxophyceae (1%–4%) across various sites.

An annual percentage composition illustrates the proportion of various species or groups within a community over 1 year, presented as a percentage of the total community. This type of analysis is commonly used in ecological studies to understand the relative abundance and dominance of different species or taxonomic groups (e.g., classes, genera) throughout the year.

The Sorensen Similarity Index illustrates the pairwise similarity values between months, which are determined by periphyton community data or ecological conditions at various times of the year. Table 7 shows the average values of the Sorenson similarity index during the 2 years of the study period at S1. Monthly values approaching one imply similar periphyton communities or environmental conditions. The December (D) and January (J) communities are quite similar, with a similarity score of 0.814815. February (F) and March (M), with 0.818182, may have similar species composition and environmental conditions affecting periphyton. Moderate Similarity Scores (0.5–0.8) Values in this range indicate moderate community or condition overlap between months. The similarity index is 0.608696 in March (M) and July (J), suggesting some common species but presumably influenced by environmental changes. Low Similarity is Almost 0. Seasonal changes in periphyton diversity and abundance may cause broader differences in community composition or ecological circumstances. The winter months (e.g., December, January, and February) exhibit a high degree of similarity, suggesting that the cold-season conditions are stable and conducive to the growth of specific periphyton communities. The summer or pre-monsoon months (e.g., April, May) are also comparable, which is likely attributable to the stable temperatures and nutrient levels that occur prior to monsoon disruption, rainfall and fertilizer runoff cause ecological alterations. Hence, monsoon and post-monsoon months (July, August, September) have lower similarity scores than winter months.

The average values of the Sorenson similarity index during the 2 years of the study period at S2 are presented in Table 8. The ecological conditions of November (N) and January (J) are similar, as evidenced by their similarity of 0.909091. A similarity of 0.965517 is observed between December (D) and March (M), indicating a significant degree of similarity in the periphyton community or water quality between these months. As an illustration, the similarity between April (A) and August (A) is 0.75, suggesting that there are seasonal fluctuations. A value of 0.8 in June (J) and September (S) indicates that there is an overlap in conditions, which may be associated with late summer or post-monsoon outcomes.

Potentially due to seasonal fluctuations or environmental transitions, lower values suggest more pronounced disparities between the months. For instance, August (A) and May (M) have a low similarity of 0.4, indicating varying biological circumstances due to monsoon influences. The similarity between August (A) and February (F) is 0.56, suggesting that monsoon conditions may induce modifications in periphyton or other ecological characteristics.

The average values of the Sorenson similarity index during the 2 years of the study period at S3 are presented in Table 9. In winter (November–February), Winter months have high similarity ratings, indicating consistent winter conditions and similar periphyton ecosystems. The similarity between January (J) and December (D) is 0.909091, showing no substantial ecological changes. Months May, June, and July show moderate similarities due to biological changes caused by warming and increased precipitation, which can alter periphyton composition. Monsoon and post-monsoon values are comparable due to settling runoff and ecological stabilization. The maximum similarity was found between the winter months at all the sites.

The values of the Shannon–Wiener diversity index during both study years are presented in Figure 3 for the year 2021–22 & 2022–23 respectively. The Shannon–Wiener diversity index values at all sites were high during both years in winter in January (2.427 at S1, 2.495 at S2, 2.562 at S3) and (2.29 at S1, 2.435 at S2, 2.467 at S3) during 2021–22 & 2022–23 respectively while minimum in the monsoon season (1.099 at S1, 1.099 at S2, 1.676 at S3) in 2021–22 and (1.311 at S1, 1.834 at S2, 1.594 at S3) in 2022–23.

The values of the Margelef index during 2021–22 and 2022–23 are presented in Figure 4. The Margalef Diversity Index measures species richness in a community by counting species and individuals. It is especially beneficial for comprehending the diversity of biological communities, such as periphyton, in aquatic ecosystems. The higher Margalef Index values suggest that the community has a greater diversity of species. Poor numbers indicate poor species richness. In both years, the highest values were found in January (2.763 at S1,2.694 at S2, 2.84 at S3) in 2021–22 (2.05 at S1, 2.745 at S2, 2.867 at S3) in 2022–23. The lowest values (1.116 at S1, 1.11 at S2, 1.573 at S3) in 2021–22 and (1.038 at S1, 1.447 at S2, 1.417 at S3) in 2022–23. were in the monsoon months. Hence, The maximum similarity was found between the winter months at all the sites.

In both years of the investigation, the canonical correspondence analysis (CCA) of periphyton among various sites is illustrated in Figure 5. Multivariate Canonical Correspondence Analysis (CCA) is used to investigate and illustrate species composition (or community structure) and environmental variables. CCA helps ecological researchers determine how environmental gradients (temperature, pH, nutrient levels) affect species distribution and abundance. CCA suggested that S3 was more diverse than S1 and S2. Results show that Axes one and two represented 64.93% and 35.07% of the variance with eigenvalues of 0.01794 and 0.00968, respectively. The dominant genera found at Site one included Synedra, Cladophora, Nithchia, Oedogonium, Fragillaria, and Ulothrix.

These genera are typically more tolerant of higher turbidity, free CO₂ and nutrient conditions like total nitrogen, total phosphorous, chlorides, sodium, and potassium. These environmental conditions favour periphyton species that are tolerant of fluctuating and often challenging water quality conditions. Algal populations such as Spirogyra, Diatoma, and Cosmorium were connected with S2, which DO, TDS, COD, and BOD govern. The presence of Cosmarium (a desmid) indicates favourable growth conditions, such as slightly alkaline pH and good light availability. S3 was associated with most of the genera Genera such as Cymbella, Phormidium, Gomphonema, Navicula, Tabellaria, Microspora, Meridion, Chlorella, Zygnema was governed by factors such as electrical conductivity, water temperature, pH, Total Alkalinity, transparency, Total hardness.

The multivariate cluster analysis in Figure 6 shows periphyton similarity at three sites during the 2-year study period. The dendrogram formed thus suggested that sites S2 and S3 were similar, while S1 showed a different group. S3 is different from these similar groups. The difference in S3 compared to the other groups in Figure 7 is primarily due to its higher abundance of periphyton, whereas S2 has some genera present but shows a lower abundance. This contrast arises from the varying levels of disturbance in these areas; S3 experiences significant boating and tourism-related disturbances, which influence its community structure. Despite these differences, the similarities between S2 and S3 are due to shared genera and comparable environmental impacts. In contrast, S1 forms the outgroup because it has the least abundance of periphyton populations, likely due to minimal anthropogenic disturbances.

The principal component analysis (PCA) of periphyton among different sites during both years of the study is presented in Figure 7. Here, PCA suggested that PC1 and PC2 were represented by 93.98% and 6.015% of the variance with eigenvalues 279.149 and 17.8675, respectively. Results show that SITE-1 is not directly associated with any of the genera clustered near the centre, suggesting that the environmental conditions at this site are not conducive to the growth of most of the periphyton genera. Instead, it suggests that SITE-1 is likely to be characterized by highly disturbed or extreme conditions such as high turbidity or nutrient contamination.

The genera Fragilaria (FRAG), Ulothrix (ULOT), Nitzschia (NIT), Diatoma (DIA), Cosmarium (cos), Spirogyra (spi), and Oedogoni-um (oed) are all closer to SITE-2. This shows that these taxa have adapted adequately to the SITE-2 environmental conditions. These genera are close to SITE-2, indicating that they provide ideal conditions, including stable substrates, moderate nutrition levels, and sufficient dissolved oxygen.

Many genera are linked to SITE-3, including Cladophora (Clad) Microspora(Micro), Meridion(Mer), Phormidium(Phor), Zygnema(Zyg), Synedra(Syn), and Tabellaria(Tab). Other genera include Gomphonema (GOMPHO), Navicula (NAV), and Chlorella (CHLO). These genes usually indicate steady, clear water that is well-oxygenated, has adequate light penetration and has balanced nutrition levels.

One-way ANOVA of periphytic at S1, S2, and S3 in the Asan wetland during the study period (November 2021–October 2022). is represented by Table 10. The p-value thus obtained (0.0796) indicates that there is no significant difference between the three sites in the density of periphyton.

This study fills a gap in our knowledge of the Asan Wetland’s ecological health by analyzing periphyton populations and a number of physicochemical characteristics across three selected sites (S1, S2, and S3) from November 2021 to October 2023. The findings emphasize site-specific environmental factors and monthly fluctuations and their impact on periphyton density and diversity.

The findings reveal significant ecological fluctuations among the three sites, influenced by variations in water quality parameters such as temperature, pH, turbidity, total dissolved solids (TDS), transparency, dissolved oxygen (DO), electrical conductivity, total alkalinity, total hardness, BOD, COD, and nutrients.

This research sheds light on the periphyton communities’ relationship with physicochemical characteristics and the ecological variability of the Asan Wetland across the three sites (S1, S2, and S3). The novelty of this research lies in its comprehensive analysis of periphyton diversity in conjunction with detailed physicochemical profiling, which provides a unique insight into unexamined relationships between environmental factors and periphyton dynamics in this wetland. Site 3 demonstrated optimal conditions for diverse periphyton growth, while Site one faced ecological stress due to high turbidity and nutrient enrichment. Site two supported moderate ecological conditions and mixed periphyton populations. Seasonal changes in water quality, such as fluctuations in temperature, pH, turbidity, and dissolved oxygen, were closely tied to periphyton density and diversity. Winter months showed higher periphyton densities, while monsoon months experienced reductions due to turbidity and nutrient runoff. Elevated phosphorus levels, particularly during the monsoon, underline the need for nutrient management to prevent eutrophication. Statistical analyses identified strong correlations between environmental factors and periphyton genera, reinforcing the necessity for site-specific management strategies. Addressing turbidity, nutrient inputs, and sedimentation is essential to maintain ecological balance.

The findings of this study emphasize the need for targeted management strategies to maintain the ecological health of the Asan Wetland. The distinct differences in environmental conditions and periphyton diversity among the three sites highlight the importance of controlling external inputs such as nutrient runoff and sedimentation. Reducing turbidity levels and managing nutrient sources are critical to preventing further degradation of water quality and ensuring the sustainability of the wetland ecosystem.