Intermittency as an Environmental Filter: Diatom Traits and Water Quality Indicators in a Hydrodynamic Context
by
, , , and
Alexander G. Rusanov
1,2,3
,
Zsuzsa Trábert
2,3,
Keve T. Kiss
2,3,
János L. Korponai
2,3
,
Mikhail Y. Kolobov
4,5,
Tibor Bíró
3,4,6,
Edit Vadkerti
2 and
Éva Ács
2,3,*
1
St. Petersburg Research Center RAS, Institute of Limnology of the Russian Academy of Sciences, 196105 St. Petersburg, Russia
2
Department of Aquatic Environmental Sciences, Faculty of Water Sciences, Ludovika University of Public Service, H-1083 Budapest, Hungary
3
National Laboratory for Water Science and Water Security, H-1083 Budapest, Hungary
4
A.N. Severtsov Institute of Ecology and Evolution of the Russian Academy of Sciences, 119071 Moscow, Russia
5
Faculty of Biology, Lomonosov Moscow State University, 119991 Moscow, Russia
6
Department of Regional Water Management, Faculty of Water Sciences, Ludovika University of Public Service, H-1083 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Hydrology 2025, 12(8), 213; https://doi.org/10.3390/hydrology12080213
Submission received: 30 May 2025
/
Revised: 15 July 2025
/
Accepted: 31 July 2025
/
Published: 13 August 2025
(This article belongs to the Special Issue Hydrodynamics and Water Quality of Rivers and Lakes)
Abstract
Global climate changes have led to dramatic increases in drought durations in previously permanent streams, impacting the biodiversity and functioning of river ecosystems. However, the response of benthic diatom communities to hydrological intermittency remains poorly understood. In this study, we compared the taxonomic and functional compositions of the diatom communities between permanent and intermittent sections in two hilly stream systems in southwestern Hungary. Our results showed that both the taxonomic and functional compositions of diatom communities were significantly affected by changes in the hydrological regime, leading to a decline in species richness and diversity and functional richness in intermittent sections. Functional richness and dispersion decreased significantly with declining taxonomic richness, likely as a consequence of species loss driven by flow intermittency. Aquatic–subaerial diatoms with moderate oxygen requirements were indicative of intermittent sections, while large, occasionally aerophilic and oxybiontic diatoms characterized permanent sections. The relative abundance of low-profile diatoms increased in intermittent sections, indicating that the natural successional process of communities was disrupted due to streambed drying. Furthermore, intermittent sections were marked by elevated abundances of α-mesosaprobous and α-meso-polysaprobous diatoms, indicating a reduced self-purification capacity under intermittent-flow conditions. These findings provide detailed insight into the responses of diatom communities to drought and water scarcity in intermittent streams, which are becoming increasingly common in warm temperate regions.
1. Introduction
Aquatic ecosystems, especially lotic systems, are under increasing pressure from a combination of anthropogenic stressors, including agricultural intensification, urban expansion, and industrial pollution. Climate change and the proliferation of invasive species exacerbate these impacts, further posing complex challenges to ecosystem integrity and biodiversity [1]. Among the most critical consequences is the alteration of natural flow regimes, particularly the increased prevalence of stream intermittency, which can significantly disrupt ecological functioning.
Flow intermittency reduces hydrological connectivity, leading to disrupted transport and transformation of nutrients and organic matter across both local stream segments and entire catchments. These changes affect the biogeochemical functioning of streams and the structure of their biological communities. Benthic diatoms are among the most sensitive indicators of such alterations. Desiccation events, even when brief, induce osmotic and physiological stress in diatoms, resulting in reduced species richness and an altered taxonomic and trait community structure [2,3,4].
Globally, studies have demonstrated that intermittent flow conditions affect the functional composition, diversity, and bioindicator performance of diatom assemblages [5,6]. In Mediterranean and Alpine streams, altered hydrodynamics due to seasonal droughts have led to shifts in dominant life-forms and ecological traits [6,7]. In this view, flow intermittency can be considered as a strong environmental filter in the context of community assembly processes, affecting the traits of species rather than the species themselves [8]. However, the functional responses of benthic diatoms to hydrological intermittency under variable precipitation regimes remain understudied in central European hilly streams. Moreover, while the routine water quality diatom indices used in Hungary effectively detect nutrient-related impacts, their sensitivity to hydrological disturbances, such as drying, is uncertain [9,10,11].
In this study, we investigated the response of benthic diatom communities to recurrent drying in two hilly stream systems in southwestern Hungary: Bükkösdi and Völgységi. These systems share similar geomorphological characteristics (a moderate gradient, calcareous bedrock, medium–fine substrates) but differ in their annual precipitation levels during the sampling years. The Bükkösdi system was sampled in 2019 under normal precipitation, while the Völgységi system was sampled in 2021 under low precipitation. This natural contrast enabled us to examine the combined effects of intermittency, seasonality, and climatic variability on diatom community structure and function.
Specifically, we tested the following hypotheses: (1) Recurrent desiccation significantly alters the taxonomic and functional composition of diatom communities, reducing taxonomic and functional diversity. (2) Drought-induced hydrological intermittency has stronger ecological effects under low-precipitation conditions, as expected in the Völgységi system. (3) The chlorophyll-a content of the phytobenthos is lower in intermittent sections. (4) The routine water quality diatom indices used in Hungary may not adequately reflect the ecological differences between permanent and intermittent reaches.
2. Materials and Methods
2.1. The Study Area
In the southern part of the Hungarian sub-basin of the Danube, within the Mecsek Mountains, a total of 54 diatom samples were collected in 2019 and 2021 from two stream systems: the Bükkösdi stream system located in the western Mecsek near Pécs, and the Völgységi stream system located in the eastern Mecsek near Bonyhád (Figure 1, Appendix A Table A1). According to the Hungarian national typology, both stream systems belong to the same hydromorphological type: a small catchment area (approximately 10–100 km2), a hilly region, mid-altitude (200–800 m), calcareous, with coarse to medium bed material. Both water systems consist of several small watercourses, including both perennial and intermittent branches. Based on the data collected in previous years, we selected intermittent and perennial sites in each stream system. Bükkösdi had 4 intermittent and 6 permanent sites, whereas Völgységi had 7 intermittent and 5 permanent sites (Table A1). In each stream system, diatom samples were collected during spring, summer, and autumn (Table A1).
In this study, stream reaches were categorized as either “permanent” or “intermittent” based on field observations and historical hydrological data collected during the sampling years. Permanent sections maintained continuous surface flow throughout all sampling seasons and exhibited no signs of channel desiccation. Intermittent sections, in contrast, experienced at least one documented flow cessation event per year, resulting in partial or complete channel drying during certain seasons (primarily summer or autumn). While no quantitative flow threshold (e.g., discharge rate or specific hydrological index) was used, the classification reflected the observable presence of surface water and flow continuity across seasons.
The sampling years differed substantially in their precipitation levels: 2019 (the sampling year in the Bükkösdi system) was characterized by a normal precipitation level, while 2021 (the sampling year in the Völgységi system) was a low-precipitation year (Table 1).
2.2. Environmental Parameters and Chlorophyll-a
In the case of the Völgység stream system, at the diatom sampling sites, a total of 8 physical and chemical parameters were measured. Dissolved oxygen (DO, mg L−1), electrical conductivity (Cond, mS cm−1), pH and turbidity (FNU) were measured in the field using a portable-multi-parameter digital meter (YSI EXO2). Total organic carbon (TOC, mg L−1), ammonium (NH4+, mg L−1), nitrate (NO3−, mg L−1) and total phosphorus (TP, mg L−1) were measured in the laboratory. We complemented the environmental sampling by measuring the chlorophyll-a content of the phytobenthos. Chlorophyll-a (total Chl-a and diatom Chl-a) was measured in the field using a Bentho-Torch (bbe Moldaenke® Schwentinental, Germany) on the surface of five randomly selected stones (unfortunately, we were not able to use this method for the Bükkösdi stream system, as the device was not yet available to us at that time).
2.3. Sampling and Processing the Diatoms
The diatom samples were collected from the submerged parts of stones, with five replicates, in both stream systems (Bükkösdi and Völgységi). The phytobenthos was scrubbed from the substrate on- site using a toothbrush, and the samples were fixed with formaldehyde (final concentration: 4%). For the digestion of organic matter, we applied the hot hydrogen peroxide method, and the cleaned frustules were mounted in Naphrax mounting medium [12]. At least 400 valves per sample were counted and identified to the lowest possible taxonomic level (species and variety). Identification was carried out at 1500× magnification using an Olympus BX50 microscope (Olympus Corporation®, Tokyo, Japan) equipped with differential interference contrast (DIC) optics. The identification of the diatoms was carried out using the following literature: [13,14,15,16,17,18,19,20].
We assigned 305 identified diatom taxa to 7 traits with 32 trait categories, including cell size according to Berthon et al. [21]; guilds according to Passy [22] and Rimet & Bouchez [23]; spreading capacity according to Rimet & Bouchez [23]; and preferences for moisture, oxygen saturation, saprobity, and trophic state according to van Dam et al. [24] and [25] (Table 2).
To assess the ecological status of the sampling sites, we used four diatom water quality indices (the specific oollution sensitivity index (IPS, Coste in [26]), Rott’s trophic index (TI [27]), Rott’s saprobic index (SI [28]), and the Hungarian phytobenthos metric (IPSITI [29]). The IPS, TI and SI were calculated by means of OMNIDIA (ver. 6.1.7) software [30], while the IPSITI was the arithmetic average of these three indices.
Three site-specific diversity measures, namely species richness, Shannon’s diversity, and Pielou’s evenness, were calculated using the ‘vegan’ (ver. 2.6–6.1) package [31] written for the R (ver. 4.4.3) statistical programming environment (R Core Team 2025). The three functional diversity (FD) indices from Villéger et al. [32]—functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv)—as well functional dispersion (FDis; [33]) were calculated using the ‘FD’ (ver. 1.0–12.3) package [34,35]. The FD indices represent (i) the amount of niche space occupied by the taxa (FRic), (ii) the evenness of the abundance distribution in the occupied niche space (FEve), (iii) the position of clusters of taxa function in the niche space (FDiv), and (iv) the main distance of all taxa from the abundance-weighted centroid of traits in the trait space (FDis). To calculate the four FD indices, we used all 7 functional traits, treated as nominal (guilds), binary (spreading), and ordinal (cell size, moisture preference, oxygen demand, saprobity, and trophic state) variables.
2.4. Data Analysis
To identify significant changes in the diatom’s taxonomic and functional structure associated with the aquatic regimes, river systems, and sampling periods, we used a distance-based redundancy analysis (db-RDA [36]) performed in ‘vegan’. Bray–Curtis and Euclidean dissimilarity were used as the distance metrics for taxonomic and functional structure, respectively. The relative abundance of diatom taxa were arcsin-square-root-transformed before the db-RDA. The community-weighted mean (CWM; [37]) matrix, in which the main values of traits in the community were weighted by the relative abundances of the taxa matrix, was calculated in ‘FD’ and then used in the db-RDA for functional structure. The species scores on the first and second axes in the db-RDA were used to identify species that were influenced by the tested factors the most.
To find the responses of the taxonomic and functional diversity indices, diatom water quality indices, and diatom species and trait categories (with a relative abundance ≥ 1%) to the aquatic regime, river system, and sampling period, we used a three-way ANOVA. In the Völgységi stream system, the response of the environmental parameters and chlorophyll-a measurements to aquatic regime and sampling period was tested using a two-way ANOVA. In addition, a two-way ANOVA was used to test the response of species richness in trait categories that were significantly influenced by aquatic regime and river system. Prior to the ANOVA, the variables were tested for normality and homogeneity of variance. Variables that violated these requirements (as FRic) were log-transformed. Due to the relatively small sample sizes, marginally significant (0.05 ≤ p < 0.10) results were also considered alongside statistically significant results (p < 0.05).
The relationships of the FD indices with species richness were assessed using a linear regression analysis. Prior to the regression analysis, the FD indices were log-transformed to approximate data normality [33].
All of the statistical analyses and graphics were produced in R ver. 4.4.3 [38].
3. Results
3.1. Species Composition
The 10 most abundant diatom taxa were Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot (11.6%), Amphora pediculus (Kützing) Grunow (11.4%), Achnanthidium minutissimum (Kützing) Czarnecki (8.4%), Platonthidium frequentissimum (Lange-Bertalot) Lange-Bertalot (7.4%), Rhoicosphenia abbreviata (C. Agardh) Lange-Bertalot (6.6%), Navicula cryptotenella Lange-Bertalot (3.1%), Cocconeis euglypta Ehrenberg (2.9%), Gomphonema micropus Kützing (2.9%), Amphora indistincta Levkov (2.6%), and Gomphonema pumilum var. rigidum Reichardt & Lange-Bertalot (2.6%).
In the db-RDA for taxonomic structure, all three tested factors—aquatic regime, river system and sampling period—showed significant (p < 0.001) relationships with species composition (Table 3). All three factors explained 21.1% of the total variance in diatom taxonomic composition. Sampling periods and aquatic regimes were clearly separated along the first axis (Figure 2a,b), while river systems were segregated along the second axis (Figure 2c). Amphora indistincta, Cocconeis euglypta, Navicula cryptotenella, N. tripunctata and Rhoicosphenia abbreviata increased significantly (p < 0.05) in their abundance under the conditions of the permanent flow, while Meridion circulare, Planothidium frequentissimum, and P. lanceolatum were higher in abundance under the intermittent flow. Navicula lanceolata and Sellaphora nigri were more abundant in Bükkösdi, whereas Amphora indistincta, Nitzschia inconspicua, N. linearis, Planothidium frequentissimum, and Sellaphora atomoides had a significantly higher abundance in Völgységi. Gomphonema micropus, Meridion circulare, and Planothidium lanceolatum were significantly more abundant in spring, while Amphora indistincta, A. pediculus, Cocconeis euglypta, and Sellaphora nigri were dominant in the summer–autumn period.
3.2. Trait Composition
In the db-RDA for functional structure, only aquatic regime showed a significant effect (p < 0.05) on trait composition, while the differences between sampling seasons and river systems were not significant (Table 3). The aquatic regime explained 13.3% of the total variance in diatom taxonomic composition. The permanent and intermittent sites were clearly separated along the first axis (Figure 3b), whereas different sampling seasons and river systems showed considerable overlaps in trait composition (Figure 3a,c).
Similarly to the results of the db-RDA, when the functional trait categories were tested using an ANOVA, greater differences were found between aquatic regimes, which significantly (p < 0.05) affected eight trait categories (Table 4). In comparison, only four trait categories and one trait category were significantly influenced by the sampling period and river system, respectively (Table 4). Considering the effect of the aquatic regime, the permanent flow was characterized by large-size, occasionally aerophilic, oxybiontic, and β-mesosaprobous taxa (Figure 4a), whereas taxa with a low-profile guild (Figure 5a), aquatic–subaerial taxa, taxa with moderate oxygen requirements, and α-mesosaprobous (Figure 4b) and α-meso-polysaprobous (Figure 4c) taxa were indicative of the intermittent flow (Table 4). Concerning river systems, pioneer taxa were more abundant in Bükkösdi, while micro-sized species, taxa with moderate oxygen requirements, and α-meso-polysaprobous taxa had a higher abundance in Völgységi. With respect to the sampling periods, spring was dominated by meso-sized taxa, while the summer–autumn period was characterized by nano-sized species, taxa with low oxygen requirements, and α-meso-polysaprobous taxa.
3.3. Biodiversity Metrics and Diatom Indices
Taxonomic diversity indices showed a significant response to all three factors tested (Table 5). The aquatic regime resulted in a significant (p < 0.05) decrease in species richness and a marginally significant (p = 0.065) decrease in Shannon’s diversity in the intermittent flow compared to those under the permanent flow (Figure 6a,b; Table 5). River systems differed in their species richness, with significantly (p < 0.01) higher values in Bükkösdi, and Pielou’s evenness, with marginally (p = 0.056) higher values in Völgységi (Figure 6a,c; Table 5). Species richness and Shannon’s diversity showed similar dynamics among seasons: their values significantly (p < 0.05) increased from spring to the summer–autumn period (Figure 6a,b; Table 5).
Among the FD indices, the aquatic regime affected FRic and FDiv, which responded in the opposite manner. FRic marginally (p = 0.063) decreased in the intermittent flow, while FDiv significantly (p < 0.05) increased under these flow conditions (Figure 7a,b; Table 5). Both indices differed significantly (p < 0.05) across seasons: FRic increased, whereas FDiv decreased from the spring to summer–autumn period (Figure 7a,b; Table 5). None of the FD indices showed significant differences between river systems (Table 5).
We found that species richness was significantly positively associated with FRic (p < 0.001; Figure 8a) and FDis (p < 0.01; Figure 8d). No significant relationships were found for FEve and FDiv (p > 0.05; Figure 8b,c).
When testing the response of species richness in trait categories whose relative abundance showed a significant response to the effects of the river system and aquatic regime, we found a similar decrease in species richness under the intermittent flow and in Völgységi in most cases (Table 6).
3.4. Changes in Environmental Parameters and Chlorophyll-a
In the Völgységi stream system, the aquatic regimes varied significantly in most of their water chemical parameters. The intermittent flow was significantly lower compared to the permanent flow in terms of DO, turbidity, NO3−, and TP, but higher in Cond (Figure 10 and Figure 11). Only DO changed across seasons significantly (p < 0.001) with higher values in spring than in the summer–autumn period (Figure 10a). Neither total Chl-a nor diatom Chl-a differed significantly between aquatic regimes (Figure 12). However, both total Chl-a and diatom Chl-a decreased significantly (p < 0.01) from the spring to summer–autumn period (Figure 12). The percentage of diatom Chl-a in the total Chl-a of the phytobenthos varied from 28% to 100%. It showed no significant differences between aquatic regimes (p = 0.150) or seasons (p = 0.178).
4. Discussion
4.1. The Effect of Flow Intermittency on the Structure and Function of Diatom Communities
The results of our study, aiming to improve our understanding of the impact of hydrological intermittency on benthic diatoms, showed that recurrent drying had significant effects on benthic diatom communities. Consistent with our first hypothesis, we found clear differences in taxonomic and functional composition between permanent and intermittent stream sections, confirming previous observations (e.g., [1,9,39,40,41,42]). The relative abundances of Meridion circulare, Planothidium frequentissimum and P. lanceolatum were higher under the conditions of an intermittent flow, reflecting the higher abundance of low-profile diatoms. Falasco et al. [1] also found that low-profile guilds dominated in the intermittent reaches of Mediterranean rivers. While some members of low-profile guilds, such as Amphora indistincta and Cocconeis euglypta, were also observed with high abundance in the permanent sections of our streams, motile (Navicula cryptotenella and N. tripunctata) and high-profile (Rhoicosphenia abbreviata) diatoms represented the characteristic guilds of the permanent-flow conditions. Thus, these differences in guild composition between aquatic regimes mainly indicate differences in periphyton succession stages. Under the intermittent-flow conditions, low-profile diatoms predominated since they tend to be the first colonizers of bare substrates cleared after hydrological disturbance events [22]. In contrast, under the permanent flow, the higher abundance of motile and high-profile diatoms reflected their preference for stable hydrological conditions [22,43], allowing for the development of more mature periphyton communities.
Micro- and large-cell classes of diatoms differed in their response to flow intermittency, indicating their resistance to different flow regimes [44]. Micro-sized taxa exhibited a higher abundance in the Völgységi system, which is characterized by a higher degree of intermittence. This finding is consistent with previous research [40,44,45] and suggests that smaller diatoms, due to their shorter life cycles and fast reproduction, are more resilient to disturbed environments [46]. Conversely, large-sized taxa were more prevalent in stream reaches under a permanent flow, confirming the results of previous studies [40,43,44].
In our streams, diatoms with different moisture preferences demonstrated the expected response to a changing hydrological regime: aquatic–subaerial taxa were indicative of the permanent stream sections, while occasionally aerophilic taxa were characteristic of the intermittent sections. We did not observe a preference for intermittent conditions by the aerophilic taxa (e.g., [9,39,40,47]), probably due to their low relative abundance in the streams studied. Similar to moisture preferences, diatom taxa with different oxygen requirements also showed the predicted ecological responses to a changing hydrological regime [42]. Oxybiontic taxa with fairly high oxygen saturation percentages (>75% sat.) characterized the permanent reaches, while taxa with moderate oxygen requirements (50% sat.) preferred the intermittent reaches. The aquatic regimes also differed in terms of the saprobic preferences of the diatoms: β-mesosaprobous taxa dominated in the permanent flow, whereas α-mesosaprobous and α-meso-polysaprobous taxa had a higher abundance in the intermittent flow, which is consistent with the results obtained by Novais et al. [42]. The observed decrease in the saprobic level of the intermittent sections was likely a result of maintaining isolated water pools surrounded by dry river beds and consequently a reduced self-purification capacity under drought conditions.
Our results indicate that hydrological intermittency negatively affected diatom communities, both in terms of their taxonomic and functional diversity. Remarkably, this decline in diversity was associated with species loss, consistent with Falasco et al. [1], who observed a reduced species richness in the intermittent reaches of Mediterranean streams. Further, we found that functional richness (FRic) was also lower under the intermittent conditions, which agrees with the results obtained by B-Béres et al. [40] in lowland Hungarian streams. So, this statement is much more general; it can be confirmed not only for lowland but also for hilly streams. Besides the decline in FRic, the intermittent reaches in our streams were characterized by high functional divergence (FDiv), indicating the extreme functional characteristics of the dominant taxa [32]. The analysis of the relationships between functional diversity and species richness confirmed that the decline in the FD measures (FRic and FDis) was caused by species loss. The stressful conditions of an intermittent flow were also reflected in a decrease in the species richness of drought- impacted trait categories. Thus, our results clearly indicate that hydrological intermittency acts like an environmental filter, disfavoring species that cannot tolerate drying conditions [48]. Moreover, species loss leads to a decline in functional diversity which can be transferred further to the consumer community with a detrimental effect [49].
Despite the geographical closeness of the two stream systems studied, our study showed that stream identity had a strong effect on diatom species composition. This result is in accordance with the results of other studies conducted in neighboring streams belonging to the same geographic area (e.g., [9,41]). However, contrastingly to these studies, in our river systems, water quality parameters were likely not the main cause of differences in diatom composition, as the diatom indices did not show significant differences between river systems. Thus, we believe that the main driver of the observed species changes between river systems was differences in precipitation levels, while the influence of water chemistry variables was minor. We found that some functional traits (i.e., moderate oxygen requirements and α-meso-polysaprobous) characteristic of the intermittent-flow conditions were also characteristic of the Völgységi stream system. Thus, our second hypothesis that a low precipitation level exacerbates hydrological intermittency was corroborated. Notably, higher water scarcity leads to reduced connectivity, thereby impairing self-purification processes not only in intermittent reaches but also in the entire river system. Furthermore, our findings that the total species richness and species richness of drought-impacted trait categories were significantly lower in the Völgységi system indicate that the species loss under conditions of hydrological intermittency is exacerbated by more intense drought conditions.
Our expectation that the total and diatom chlorophyll-a contents would show a strong negative response to an intermittent flow, as suggested by previous studies [6,50], was not corroborated (the third hypothesis). The most likely reason for this discrepancy is the high turbidity of the water in the permanent reaches of the Völgységi system caused by suspended matter, which prevented the development of periphyton biomass under conditions of a reduced light intensity underwater [51,52,53]. Therefore, the usefulness of chlorophyll-a content (as well as the percentage of diatom chlorophyll-a of the total chlorophyll-a of the phytobenthos) as an indication of hydrological intermittency is highly context-dependent and requires an assessment of the confounding effects of water quality parameters.
4.2. Taxonomic and Functional-Trait-Based Approaches to Assessing the Effect of Flow Intermittency
Our study showed no significant differences in the diatom indices (i.e., IPS, TI, SI) between the permanent and intermittent reaches (the fourth hypothesis), partially confirming previous results obtained by B-Béres et al. [1] in temperate Hungarian streams and Falasco et al. [12] in Mediterranean streams. However, the saprobic preferences of the diatoms showed significant negative (β-mesosaprobous) and positive (α-mesosaprobous and α-meso-polysaprobous) responses to an intermittent flow. This is likely due to differences between the saprobity systems used, with the van Dam et al. [48] saprobity system having priority, at least in the studied streams.
Diatom-based autecological indices designed to assess the response to organic load and nutrient concentrations are poorly adapted to indicating hydrological disturbances [12]. In our study, functional traits, such as diatom guilds, cell size, moisture preference, and oxygen demand, were more reliable than diatom indices in the intermittency impact assessment, as already confirmed in previous studies (e.g., [1,12]). Our study identified specific traits characteristic of stream reaches with an intermittent flow (e.g., a micro-size class, a low profile, moderate oxygen requirements) distinguishable from those under a permanent flow (e.g., a large-size class, occasionally aerophilic and oxybiontic taxa). The db-RDA showed clear differences in the trait composition of the periphytic diatom communities between stream reaches with intermittent- and permanent-flow conditions, regardless of seasonal and interannual changes in meteorological conditions. This indicates the high discriminatory power and strong robustness of the trait indicators. Thus, a functional-trait-based approach offers a promising perspective for tracing the effect of flow intermittency in continental lowland and hilly streams. In particular, a multimetric diatom index based on trait categories and functional diversity measures could be developed to assess hydrological intermittency, as has been conducted to assess the ecological condition of U.S. rivers and streams [41].
5. Conclusions
By analyzing the taxonomic and functional characteristics of benthic diatom communities in two intermittent stream systems, we demonstrated that increasingly severe climatic conditions, particularly water scarcity, can lead to substantial losses in both taxonomic and functional richness. The negative effects of drought were evident at both the local site level and across the entire river system, indicating a decline in the river’s self-purification capacity in response to ongoing climate change. Our findings suggest that the saprobity system holds strong potential for refining and adapting diatom-based indicators to assess water quality in intermittent rivers. Moreover, our study underscored the utility of diatom trait composition and functional diversity metrics in effectively distinguishing between intermittent and perennial stream reaches. Given that hydrological intermittency acts as a strong environmental filter shaping functional community structure, trait-based approaches offer valuable insights into the ecological consequences of drought-induced flow interruptions in stream ecosystems.
Author Contributions
A.G.R.—design of the study, data analysis and interpretation, visualization, and drafting and writing the manuscript; Z.T.—preparation of the diatom samples, species identification, data processing, and writing the manuscript; K.T.K.—species identification and writing the manuscript; J.L.K.—writing the manuscript; M.Y.K.—writing the manuscript; T.B.—writing the manuscript; E.V.—writing the manuscript; É.Á.—conception of the study, species identification, data processing, and drafting and writing the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
The research presented in this article was carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project.
Data Availability Statement
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Acknowledgments
This study was carried out by National University of Public Service within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022 00008 project and as part of the state assignment of the Institute of Limnology RAS (project no. FFZF-2024-0001 for A.G.R.) and the scientific project of Lomonosov Moscow State University (project no. 121032300124-1 for M.Y.K.).
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A
Table A1.
Geographic coordinates, sampling periods, and aquatic regimes of stream sampling sites in the Bükkösdi (B) and Völgységi (V) river systems. Period of sampling: SPR—spring, SUM—summer, AUT—autumn. Aquatic regime: PER—permanent, INT—intermittent.
Table A1.
Geographic coordinates, sampling periods, and aquatic regimes of stream sampling sites in the Bükkösdi (B) and Völgységi (V) river systems. Period of sampling: SPR—spring, SUM—summer, AUT—autumn. Aquatic regime: PER—permanent, INT—intermittent.
| Aquatic Regime | Period of Sampling | Geographic Coordinates (WGS 84) | ## | |
|---|---|---|---|---|
| Bükkösdi | ||||
| PER | SPR, SUM, AUT | 18°02′24.53″ E | 46°07′34.83″ N | B1 |
| PER | SPR, SUM, AUT | 17°59′03.18″ E | 46°05′11.24″ N | B2 |
| INT | SPR, SUM, AUT | 18°01′54.27″ E | 46°07′38.60″ N | B3 |
| PER | SPR, SUM, AUT | 18°03′28.77″ E | 46°09′18.84″ N | B4 |
| INT | SPR, AUT | 18°03′26.57″ E | 46°09′19.36″ N | B5 |
| INT | SPR, SUM | 18°03′25.13″ E | 46°10′05.14″ N | B6 |
| INT | SPR, SUM | 18°03′07.77″ E | 46°10′16.40″ N | B7 |
| PER | SPR, SUM, AUT | 18°02′57.67″ E | 46°11′01.91″ N | B8 |
| PER | SPR, SUM, AUT | 18°06′40.37″ E | 46°08′40.24″ N | B9 |
| PER | SPR, SUM, AUT | 18°05′15.29″ E | 46°08′17.10″ N | B10 |
| Völgységi | ||||
| INT | SPR, SUM | 18°19′18.4″ E | 46°11′21.7″ N | V1 |
| INT | SPR, SUM, AUT | 18°19′18.1″ E | 46°11′22.5″ N | V2 |
| PER | SPR, SUM | 18°20′10.2″ E | 46°13′25.4″ N | V3 |
| PER | SPR, SUM, AUT | 18°20′00.3″ E | 46°13′23.2″ N | V4 |
| PER | SPR, SUM, AUT | 18°19′22.9″ E | 46°13′37.1″ N | V5 |
| INT | SPR | 18°20′39.1″ E | 46°15′03.5″ N | V6 |
| PER | SPR | 18°21′35.5″ E | 46°16′20.8″ N | V7 |
| INT | SPR, SUM | 18°23′28.2″ E | 46°15′15.8″ N | V8 |
| INT | SPR, SUM | 18°23′28.8″ E | 46°15′15.4″ N | V9 |
| PER | SPR, SUM, AUT | 18°23′29.4″ E | 46°15′27.6″ N | V10 |
| INT | SPR, SUM, AUT | 18°25′04.2″ E | 46°14′42.7″ N | V11 |
| INT | SPR, SUM | 18°25′04.4″ E | 46°14′43.4″ N | V12 |
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Figure 1.
A map of the study area in the Mecsek Mountains (southwestern Hungary). (A) Two river systems—Bükkösdi (B) and Völgységi (V) with sampling sites are shown. (B) The location of the study area (black dot) in Hungary, which is marked in blue.
Figure 1.
A map of the study area in the Mecsek Mountains (southwestern Hungary). (A) Two river systems—Bükkösdi (B) and Völgységi (V) with sampling sites are shown. (B) The location of the study area (black dot) in Hungary, which is marked in blue.
Figure 2.
db-RDA biplots of diatom species composition representing sampling sites and centroids of factors: sampling period (a), aquatic regime (b), and river system (c).
Figure 2.
db-RDA biplots of diatom species composition representing sampling sites and centroids of factors: sampling period (a), aquatic regime (b), and river system (c).
Figure 3.
db-RDA biplots of diatom trait composition representing sampling sites and centroids of factors: sampling period (a), aquatic regime (b), and river system (c).
Figure 3.
db-RDA biplots of diatom trait composition representing sampling sites and centroids of factors: sampling period (a), aquatic regime (b), and river system (c).
Figure 4.
Responses of relative abundance of β-mesosaprobous (a), α-mesosaprobous (b) and α-meso-polysaprobous (c) diatom species to three factors (river system, aquatic regime, and sampling period).
Figure 4.
Responses of relative abundance of β-mesosaprobous (a), α-mesosaprobous (b) and α-meso-polysaprobous (c) diatom species to three factors (river system, aquatic regime, and sampling period).
Figure 5.
Responses of relative abundance of low-profile (a), high-profile (b), and motile (c) diatom guilds to three factors (river system, aquatic regime, and sampling period).
Figure 5.
Responses of relative abundance of low-profile (a), high-profile (b), and motile (c) diatom guilds to three factors (river system, aquatic regime, and sampling period).
Figure 6.
The influence of three factors (river system, aquatic regime, and sampling period) on diversity measures (species richness (a), Shannon’s diversity (b), and Pielou’s evenness (c)) of diatom communities.
Figure 6.
The influence of three factors (river system, aquatic regime, and sampling period) on diversity measures (species richness (a), Shannon’s diversity (b), and Pielou’s evenness (c)) of diatom communities.
Figure 7.
The influence of three factors (river system, aquatic regime, and sampling period) on functional richness (FRic) (a) and functional divergence (FDiv) (b) of diatom communities.
Figure 7.
The influence of three factors (river system, aquatic regime, and sampling period) on functional richness (FRic) (a) and functional divergence (FDiv) (b) of diatom communities.
Figure 8.
Relationships between functional diversity indices (functional richness (a), functional evenness (b), functional divergence (c), and functional dispersion (d)) and species richness. Black line represents regression line, gray shadow means 95% confidence interval.
Figure 8.
Relationships between functional diversity indices (functional richness (a), functional evenness (b), functional divergence (c), and functional dispersion (d)) and species richness. Black line represents regression line, gray shadow means 95% confidence interval.
Figure 9.
The response of diatom indices (Specific pollution sensitivity index (a), Rott’s trophic index (b), and Rott’s saprobic index (c) to three factors (river system, aquatic regime, and sampling period).
Figure 9.
The response of diatom indices (Specific pollution sensitivity index (a), Rott’s trophic index (b), and Rott’s saprobic index (c) to three factors (river system, aquatic regime, and sampling period).
Figure 10.
Influence of two factors (aquatic regime and sampling period) on dissolved oxygen (a), turbidity (b) and electrical conductivity (c) in the Völgységi river system.
Figure 10.
Influence of two factors (aquatic regime and sampling period) on dissolved oxygen (a), turbidity (b) and electrical conductivity (c) in the Völgységi river system.
Figure 11.
Influence of two factors (aquatic regime and sampling period) on nitrate (a) and total phosphorus (b) concentrations in Völgységi river system.
Figure 11.
Influence of two factors (aquatic regime and sampling period) on nitrate (a) and total phosphorus (b) concentrations in Völgységi river system.
Figure 12.
The influence of two factors (aquatic regime and sampling period) on the total (a) and diatom (b) chlorophyll-a concentrations in the Völgységi river system.
Figure 12.
The influence of two factors (aquatic regime and sampling period) on the total (a) and diatom (b) chlorophyll-a concentrations in the Völgységi river system.
Table 1.
Precipitation level and air temperature in Bükkösdi (2019) and Völgységi (2021) river systems. Data were obtained from meteorological stations located in Pécs (Bükkösdi) and Váralja (Völgységi).
Table 1.
Precipitation level and air temperature in Bükkösdi (2019) and Völgységi (2021) river systems. Data were obtained from meteorological stations located in Pécs (Bükkösdi) and Váralja (Völgységi).
| Völgységi | Bükkösdi | Precipitation |
|---|---|---|
| 672 ± 77 | 663 ± 56 | Mean (±SD) total annual for 2016–2021 (mm/year) |
| 561 | 703 | Total annual (mm) |
| 352 | 466 | Total for April–September (mm) |
| 19–86 | 15–129 | Range (min–max) for April–September (mm/month) |
| 50 ± 28 | 67 ± 36 | Mean (±SD) for April–September (mm/month) |
| 37 | 61 | Median (mm/month) |
| Völgységi | Bükkösdi | Air Temperature |
| 10.1 ± 4.2 | 12.3 ± 2.3 | Mean (±SD) spring (April) values (°C) |
| 20.4 ± 5.0 | 19.9 ± 5.1 | Mean (±SD) summer (July) values (°C) |
| 21.5 ± 3.0 | 21.1 ± 2.9 | Mean (±SD) autumn (September) values (°C) |
Table 2.
Functional traits, their categories, and the mean relative abundance of trait categories in the diatom communities of the Bükkösdi and Völgységi stream systems.
Table 2.
Functional traits, their categories, and the mean relative abundance of trait categories in the diatom communities of the Bükkösdi and Völgységi stream systems.
| Mean Relative Abundance (%) | Trait Categories | Traits | |
|---|---|---|---|
| 32.6 | 5–99 µm3 | nano | Cell size |
| 19.2 | 100–299 µm3 | micro | |
| 32.4 | 300–599 µm3 | meso | |
| 10.2 | 600–1499 µm3 | macro | |
| 5.6 | ≥1500 µm3 | very large | |
| 49.2 | low-profile | Guilds | |
| 18.9 | high-profile | ||
| 31.3 | motile | ||
| 0.5 | planktic | ||
| 22.7 | pioneer | Spreading | |
| 4.6 | strictly aquatic | Moisture preference | |
| 13.1 | occasional aerophilic | ||
| 53.6 | aquatic-subaerial | ||
| 3.7 | aerophilic | ||
| >0.1 | terrestrial | ||
| 13.6 | 100% saturation | polyoxybiontic | Oxygen demand |
| 37.1 | 75% saturation | oxybiontic | |
| 25.8 | 50% saturation | moderate | |
| 7.4 | 30% saturation | low | |
| 0.4 | 10% saturation | very low | |
| 2.1 | oligosaprobous | Saprobity | |
| 49.9 | β-mesosaprobous | ||
| 20.3 | α-mesosaprobous | ||
| 14.8 | α-meso-polysaprobous | ||
| 1.1 | polysaprobous | ||
| 0.4 | oligotraphentic | Trophic state | |
| 0.5 | oligo-mesotraphentic | ||
| 0.3 | mesotraphentic | ||
| 3.8 | meso-eutraphentic | ||
| 58.2 | eutraphentic | ||
| 2.6 | hypereutraphentic | ||
| 23.4 | indifferent | ||
Table 3.
Significant predictors in the db-RDA models of diatom species and functional composition.
| p | Fmodel | Factors |
|---|---|---|
| Species composition | ||
| <0.001 | 2.478 | Sampling period |
| <0.001 | 4.103 | Aquatic regime |
| <0.001 | 4.114 | River system |
| Functional composition | ||
| 0.143 | 1.504 | Sampling period |
| <0.05 | 3.089 | Aquatic regime |
| 0.225 | 1.389 | River system |
Table 4.
The results of the comparison of the means (±SE) of diatom functional traits through a three-way ANOVA of the effects of river system, aquatic regime and sampling period. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT); sampling period—spring (SPR), summer (SUM), and autumn (AUT). Significant (p ≤ 0.05) differences are marked in bold; marginally significant (0.05 < p ≤ 0.10) differences are marked by an asterisk (*).
Table 4.
The results of the comparison of the means (±SE) of diatom functional traits through a three-way ANOVA of the effects of river system, aquatic regime and sampling period. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT); sampling period—spring (SPR), summer (SUM), and autumn (AUT). Significant (p ≤ 0.05) differences are marked in bold; marginally significant (0.05 < p ≤ 0.10) differences are marked by an asterisk (*).
| Sampling Period | Aquatic Regime | River System | Functional Traits | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| p | AUT | SUM | SPR | p | INT | PER | p | V | B | |
| Cell size (µm3) | ||||||||||
| <0.05 | 44.2 ± 6.0 | 35.9 ± 5.9 | 22.8 ± 4.2 | 0.293 | 29.2 ± 4.8 | 35.3 ± 4.4 | 0.177 | 26.7 ± 4.1 | 38.4 ± 4.9 | Nano (%) |
| 0.489 | 21.6 ± 4.2 | 20.8 ± 4.1 | 16.3 ± 3.2 | 0.150 | 22.3 ± 3.5 | 16.6 ± 2.5 | <0.05 | 23.3 ± 2.9 | 14.9 ± 3.0 | Micro (%) |
| <0.05 | 18.8 ± 2.8 | 27.9 ± 3.7 | 44.2 ± 5.1 | 0.233 | 36.3 ± 4.7 | 29.2 ± 3.6 | 0.525 | 32.6 ± 3.7 | 32.2 ± 4.6 | Meso (%) |
| 0.331 | 10.3 ± 3.2 | 7.3 ± 1.4 | 12.7 ± 2.7 | 0.533 | 9.0 ± 1.8 | 11.2 ± 2.2 | 0.697 | 10.3 ± 2.1 | 10.1 ± 2.1 | Macro (%) |
| 0.117 | 5.1 ± 1.6 | 8.0 ± 2.7 | 3.9 ± 0.8 | <0.05 | 3.1 ± 0.7 | 7.7 ± 1.8 | 0.633 | 6.9 ± 2.0 | 4.3 ± 0.8 | Very large (%) |
| Guilds | ||||||||||
| 0.711 | 45.9 ± 4.2 | 52.5 ± 5.5 | 48.4 ± 5.7 | <0.05 | 56.1 ± 4.2 | 43.7 ± 4.3 | 0.841 | 49.8 ± 4.4 | 48.7 ± 4.6 | Low-profile (%) |
| 0.155 | 14.5 ± 4.1 | 15.8 ± 3.7 | 24.1 ± 4.9 | 0.192 | 16.2 ± 3.4 | 21.0 ± 3.8 | 0.235 | 21.8 ± 3.9 | 16.0 ± 3.5 | High-profile (%) |
| 0.150 | 39.0 ± 5.4 | 31.2 ± 5.6 | 26.9 ± 5.0 | 0.269 | 26.0 ± 4.2 | 35.6 ± 4.5 | 0.717 | 27.9 ± 3.9 | 34.7 ± 4.9 | Motile (%) |
| Spreading | ||||||||||
| 0.176 | 28.9 ± 5.0 | 25.3 ± 5.1 | 16.9 ± 3.6 | 0.349 | 20.0 ± 3.9 | 24.9 ± 3.6 | 0.084 * | 18.1 ± 3.2 | 27.4 ± 4.2 | Pioneer (%) |
| Moisture preference | ||||||||||
| 0.125 | 3.4 ± 0.8 | 3.3 ± 1.0 | 6.5 ± 1.4 | 0.116 | 6.3 ± 1.5 | 3.2 ± 1.6 | 0.165 | 4.0 ± 0.9 | 5.3 ± 1.0 | Strictly aquatic (%) |
| 0.445 | 9.9 ± 2.2 | 15.0 ± 3.8 | 13.4 ± 4.3 | <0.001 | 4.8 ± 1.5 | 19.8 ± 3.5 | 0.404 | 15.2 ± 3.6 | 11.0 ± 2.7 | Occasional aerophilic (%) |
| 0.573 | 55.3 ± 4.8 | 49.8 ± 5.1 | 56.0 ± 4.4 | 0.059 * | 60.1 ± 3.9 | 47.1 ± 3.7 | 0.136 | 48.5 ± 4.4 | 59.7 ± 4.1 | Aquatic-subaerial (%) |
| 0.119 | 2.9 ± 1.1 | 5.7 ± 3.4 | 2.4 ± 1.6 | 0.822 | 3.6 ± 1.5 | 3.8 ± 2.2 | 0.557 | 2.9 ± 1.3 | 4.5 ± 2.5 | Aerophilic (%) |
| Oxygen demand | ||||||||||
| 0.394 | 17.8 ± 4.7 | 9.8 ± 2.7 | 14.4 ± 3.3 | 0.804 | 13.5 ± 2.6 | 13.6 ± 3.0 | 0.897 | 12.5 ± 2.0 | 14.6 ± 3.5 | Polyoxybiontic (%) |
| 0.966 | 32.9 ± 4.4 | 39.2 ± 5.3 | 37.7 ± 4.9 | <0.01 | 27.6 ± 3.9 | 44.7 ± 3.4 | 0.116 | 32.7 ± 4.1 | 41.4 ± 3.9 | Oxybiontic (%) |
| 0.474 | 17.9 ± 3.7 | 24.9 ± 6.1 | 31.1 ± 6.2 | <0.01 | 37.7 ± 5.7 | 16.2 ± 3.3 | 0.062 * | 31.5 ± 5.2 | 19.9 ± 4.5 | Moderate (%) |
| ≤0.01 | 11.5 ± 2.3 | 8.2 ± 2.2 | 4.3 ± 0.9 | 0.499 | 8.3 ± 1.7 | 6.7 ± 1.3 | 0.846 | 6.3 ± 1.3 | 8.5 ± 1.7 | Low (%) |
| Saprobity | ||||||||||
| 0.364 | 3.2 ± 1.0 | 1.7 ± 0.4 | 1.8 ± 0.7 | 0.442 | 1.8 ± 0.5 | 2.4 ± 0.6 | 0.574 | 1.9 ± 0.5 | 2.4 ± 0.6 | Oligosaprobous (%) |
| 0.927 | 48.9 ± 5.3 | 49.0 ± 5.0 | 51.1 ± 5.5 | <0.001 | 38.8 ± 4.7 | 58.7 ± 3.1 | 0.193 | 46.2 ± 4.5 | 53.5 ± 4.1 | β-mesosaprobous (%) |
| 0.248 | 18.3 ± 3.2 | 15.9 ± 3.4 | 25.2 ± 5.0 | <0.001 | 31.2 ± 4.4 | 11.5 ± 1.6 | 0.231 | 21.5 ± 3.2 | 19.1 ± 4.0 | α-mesosaprobous (%) |
| <0.05 | 16.9 ± 3.5 | 17.3 ± 4.1 | 11.4 ± 2.8 | <0.05 | 19.1 ± 3.2 | 11.3 ± 2.4 | 0.090 * | 17.4 ± 2.8 | 12.1 ± 2.9 | α-meso-polysaprobous (%) |
| 0.815 | 0.6 ± 0.3 | 1.5 ± 0.9 | 1.1 ± 0.4 | 0.109 | 0.6 ± 0.2 | 1.6 ± 0.6 | 0.583 | 0.8 ± 0.3 | 1.4 ± 0.6 | Polysaprobous (%) |
| Trophic state | ||||||||||
| 0.421 | 4.5 ± 1.5 | 2.2 ± 0.4 | 4.6 ± 1.4 | 0.180 | 3.4 ± 1.2 | 4.1 ± 0.9 | 0.626 | 4.3 ± 1.2 | 3.2 ± 0.8 | Meso-eutraphentic (%) |
| 0.557 | 62.5 ± 4.7 | 57.5 ± 4.2 | 56.3 ± 4.5 | 0.603 | 59.9 ± 4.0 | 56.8 ± 3.4 | 0.983 | 56.7 ± 3.1 | 59.7 ± 4.2 | Eutraphentic (%) |
| 0. 4 | 0.5 ± 0.4 | 5.1 ± 3.4 | 1.6 ± 0.4 | 0.156 | 1.2 ± 0.2 | 3.7 ± 2.0 | 0.164 | 1.1 ± 0.3 | 4.1 ± 2.4 | Hypereutraphentic (%) |
| 0.189 | 19.8 ± 4.4 | 20.9 ± 3.4 | 27.6 ± 3.7 | 0.296 | 25.9 ± 3.1 | 21.3 ± 3.0 | 0.174 | 25.4 ± 2.4 | 21.4 ± 3.7 | Indifferent (%) |
Table 5.
The results of a comparison of the means (±SE) of various measures of taxonomic and functional diversity through a three-way ANOVA of the effects of river system, aquatic regime and sampling period. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT); sampling period—spring (SPR), summer (SUM), and autumn (AUT). Significant (p ≤ 0.05) differences are marked in bold; marginally significant (0.05 < p ≤ 0.10) differences are marked by an asterisk (*).
Table 5.
The results of a comparison of the means (±SE) of various measures of taxonomic and functional diversity through a three-way ANOVA of the effects of river system, aquatic regime and sampling period. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT); sampling period—spring (SPR), summer (SUM), and autumn (AUT). Significant (p ≤ 0.05) differences are marked in bold; marginally significant (0.05 < p ≤ 0.10) differences are marked by an asterisk (*).
| Sampling Period | Aquatic Regime | River System | Measures | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| p | AUT | SUM | SPR | p | INT | PER | p | V | B | |
| Taxonomic diversity | ||||||||||
| <0.05 | 43.8 ± 3.6 | 41.1 ± 3.0 | 33.2 ± 1.9 | <0.05 | 34.1 ± 2.4 | 42.1 ± 2.2 | <0.01 | 34.1 ± 2.1 | 43.0 ± 2.5 | Species richness |
| <0.05 | 3.8 ± 0.2 | 3.5 ± 0.2 | 3.1 ± 0.2 | 0.065 * | 3.2 ± 0.2 | 3.6 ± 0.1 | 0.409 | 3.5 ± 0.1 | 3.3 ± 0.2 | Shannon’s diversity |
| 0.129 | 0.71 ± 0.02 | 0.65 ± 0.03 | 0.62 ± 0.03 | 0.155 | 0.63 ± 0.03 | 0.68 ± 0.02 | 0.056 * | 0.69 ± 0.02 | 0.62 ± 0.03 | Pielou’s evenness |
| Functional diversity | ||||||||||
| <0.05 | 3.2 ± 0.8 | 3.1 ± 0.6 | 1.4 ± 0.4 | 0.063 * | 1.7 ± 0.5 | 3.0 ± 0.4 | 0.127 | 2.0 ± 0.4 | 2.9 ± 0.5 | Log FRic |
| 0.800 | 0.61 ± 0.02 | 0.60 ± 0.02 | 0.59 ± 0.01 | 0.476 | 0.60 ± 0.01 | 0.59 ± 0.01 | 0.102 | 0.58 ± 0.01 | 0.61 ± 0.01 | FEve |
| <0.05 | 0.61 ± 0.02 | 0.62 ± 0.02 | 0.71 ± 0.03 | <0.05 | 0.69 ± 0.02 | 0.63 ± 0.02 | 0.789 | 0.67 ± 0.03 | 0.65 ± 0.02 | FDiv |
| 0.130 | 0.23 ± 0.01 | 0.21 ± 0.01 | 0.18 ± 0.02 | 0.120 | 0.19 ± 0.01 | 0.21 ± 0.01 | 0.967 | 0.20 ± 0.01 | 0.20 ± 0.01 | FDis |
Table 6.
The results of a comparison of the means (±SE) of species richness in trait categories whose relative abundance showed a significant response to the effects of river system and aquatic regime. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT). Significant (p ≤ 0.05) differences are marked in bold; marginally significant (0.05 < p ≤ 0.10) differences are marked by an asterisk (*).
Table 6.
The results of a comparison of the means (±SE) of species richness in trait categories whose relative abundance showed a significant response to the effects of river system and aquatic regime. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT). Significant (p ≤ 0.05) differences are marked in bold; marginally significant (0.05 < p ≤ 0.10) differences are marked by an asterisk (*).
| Aquatic Regime | River System | Trait Categories | ||||
|---|---|---|---|---|---|---|
| p | INT | PER | p | V | B | |
| 0.223 | 7.8 ± 0.9 | 9.5 ± 0.6 | 0.087 * | 7.8 ± 0.6 | 9.7 ± 0.8 | Micro-sized taxa |
| <0.05 | 3.5 ± 0.5 | 5.5 ± 0.4 | 0.075 * | 4.0 ± 0.5 | 5.2 ± 0.4 | Large taxa |
| <0.01 | 7.7 ± 0.5 | 10.2 ± 0.6 | 0.347 | 8.7 ± 0.4 | 9.4 ± 0.8 | Low-profile guild |
| <0.01 | 3.0 ± 0.3 | 5.4 ± 0.5 | <0.001 | 3.2 ± 0.4 | 5.4 ± 0.5 | Occasional aerophilic |
| 0.610 | 13.2 ± 0.9 | 14.3 ± 0.8 | <0.05 | 12.6 ± 0.7 | 15.0 ± 0.9 | Aquatic-subaerial |
| 0.090 * | 8.5 ± 0.6 | 10.4 ± 0.5 | <0.001 | 8.1 ± 0.6 | 10.9 ± 0.4 | Oxybiontic |
| 0.429 | 5.8 ± 0.4 | 6.6 ± 0.4 | <0.01 | 5.4 ± 0.3 | 7.0 ± 0.4 | Moderate O2 demand |
| <0.05 | 11.3 ± 0.8 | 14.5 ± 0.7 | <0.05 | 11.9 ± 0.7 | 14.3 ± 0.8 | β-mesosaprobous |
| 0.375 | 6.1 ± 0.6 | 7.3 ± 0.6 | <0.05 | 5.7 ± 0.5 | 7.9 ± 0.6 | α-mesosaprobous |
| 0.132 | 5.0 ± 0.4 | 4.6 ± 0.4 | <0.05 | 4.1 ± 0.3 | 5.4 ± 0.4 | α-meso-polysaprobous |
Table 7.
The results of a comparison of the means (±SE) of water quality diatom indices through a three-way ANOVA of the effects of river system, aquatic regime, and sampling period. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT); sampling period—spring (SPR), summer (SUM) and autumn (AUT). Significant (p ≤ 0.05) differences are marked in bold.
Table 7.
The results of a comparison of the means (±SE) of water quality diatom indices through a three-way ANOVA of the effects of river system, aquatic regime, and sampling period. Factor levels: river system—Bükkösdi (B) and Völgységi (V); aquatic regime—permanent (PER) and intermittent (INT); sampling period—spring (SPR), summer (SUM) and autumn (AUT). Significant (p ≤ 0.05) differences are marked in bold.
| Sampling Period | Aquatic Regime | River System | Index | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| p | AUT | SUM | SPR | p | INT | PER | p | V | B | |
| <0.05 | 13.2 ± 0.5 | 13.6 ± 0.6 | 14.9 ± 0.3 | 0.634 | 14.2 ± 0.4 | 13.8 ± 0.4 | 0.501 | 14.2 ± 0.3 | 13.9 ± 0.5 | IPS |
| 0.766 | 6.9 ± 0.3 | 6.5 ± 0.2 | 6.6 ± 0.4 | 0.155 | 6.2 ± 0.4 | 6.9 ± 0.3 | 0.887 | 6.7 ± 0.2 | 6.6 ± 0.3 | TI |
| 0.148 | 12.6 ± 0.2 | 12.3 ± 0.4 | 13.0 ± 0.2 | 0.814 | 12.7 ± 0.2 | 12.6 ± 0.3 | 0.222 | 12.9 ± 0.2 | 12.5 ± 0.3 | SI |
| 0.139 | 10.9 ± 0.3 | 10.8 ± 0.3 | 11.5 ± 0.2 | 0.707 | 11.1 ± 0.2 | 11.2 ± 0.2 | 0.391 | 11.3 ± 0.1 | 11.0 ± 0.3 | ISPITI |
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Rusanov, A.G.; Trábert, Z.; Kiss, K.T.; Korponai, J.L.; Kolobov, M.Y.; Bíró, T.; Vadkerti, E.; Ács, É. Intermittency as an Environmental Filter: Diatom Traits and Water Quality Indicators in a Hydrodynamic Context. Hydrology 2025, 12, 213. https://doi.org/10.3390/hydrology12080213
AMA Style
Rusanov AG, Trábert Z, Kiss KT, Korponai JL, Kolobov MY, Bíró T, Vadkerti E, Ács É. Intermittency as an Environmental Filter: Diatom Traits and Water Quality Indicators in a Hydrodynamic Context. Hydrology. 2025; 12(8):213. https://doi.org/10.3390/hydrology12080213
Chicago/Turabian StyleRusanov, Alexander G., Zsuzsa Trábert, Keve T. Kiss, János L. Korponai, Mikhail Y. Kolobov, Tibor Bíró, Edit Vadkerti, and Éva Ács. 2025. "Intermittency as an Environmental Filter: Diatom Traits and Water Quality Indicators in a Hydrodynamic Context" Hydrology 12, no. 8: 213. https://doi.org/10.3390/hydrology12080213
APA StyleRusanov, A. G., Trábert, Z., Kiss, K. T., Korponai, J. L., Kolobov, M. Y., Bíró, T., Vadkerti, E., & Ács, É. (2025). Intermittency as an Environmental Filter: Diatom Traits and Water Quality Indicators in a Hydrodynamic Context. Hydrology, 12(8), 213. https://doi.org/10.3390/hydrology12080213
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