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Article

Diversity of Benthic Diatoms and Abiotic Patterns in the Headwaters of the Volga River

by
Natalie Ismaiel
1,
Vyacheslav V. Kuzovlev
2,3,
Sergey I. Shaporenko
4,
Andreas Holzinger
1 and
Martin Schletterer
5,*
1
Department of Botany, University of Innsbruck, Sternwartestraße 15, 6020 Innsbruck, Austria
2
Faculty of Environmental Management and Ecology, Tver State Technical University, Naberezhnaya Afanasiya Nikitina 22, Tver 170026, Russia
3
Tver Center for Hydrometeorology and Environmental Monitoring, Russian Federal Service for Hydrometeorology and Environmental Monitoring, Efimova Str. 6, Tver 170006, Russia
4
Institute of Geography, Russian Academy of Sciences, Staromonetnyy Pereulok 29, Moscow 119017, Russia
5
Department of Ecosystem Management, Climate and Biodiversity, Institute of Hydrobiology and Aquatic Ecosystem Management, BOKU University, Gregor-Mendel-Straße 33, 1180 Vienna, Austria
*
Author to whom correspondence should be addressed.
Diversity 2025, 17(12), 842; https://doi.org/10.3390/d17120842
Submission received: 30 September 2025 / Revised: 26 November 2025 / Accepted: 29 November 2025 / Published: 5 December 2025
(This article belongs to the Special Issue Restoring and Conserving Biodiversity: A Global Perspective)
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Abstract

The Volga is the largest river in Europe and its headwaters comprise reference or least disturbed conditions. In the headwaters of the Volga (445 km) upstream of Tver, 27 diatom samples (18 from the Volga and nine from selected tributaries) were collected in shallow water along the banks from different habitats, wherefrom 270 taxa (244 pennate and 26 centric) were identified. Most benthic taxa were found within Naviculaceae (40 taxa), Fragilariaceae (29 taxa), Bacillariaceae (27 taxa), Achnanthaceae (23 taxa), Gomphonemataceae (19 taxa), Cymbellaceae (17 taxa), and 16 taxa belong to the Amphora-complex. Species richness in the Volga and its tributaries was comparable; the mean value was 46 in the Volga and 50 in the tributaries. Regarding the saprobic index, the source region (reach R1) was characterized by a large proportion of xeno- and oligo-saprobic species, with the proportion of oligo-beta and beta-meso-saprobic species increasing along the continuum. This study provides a first comprehensive checklist of benthic diatoms for the Volga headwaters and analyzes longitudinal changes as well as the interplay between abiotic parameters and the diatom community in the headwaters of the Volga.

1. Introduction

Globally, benthic diatoms (Bacillariophyta) have been used for decades for monitoring of running waters. In the beginning, autecological indices were developed in order to evaluate pollution [1], which are based on ecological preferences and tolerances of species [2]. Later on, a community-based approach was taken, also taking in to account the evolving species richness and diversity [3].
Due to short generation times, the diatom coenosis responds quickly to changes in environmental conditions [4]. Their sensitivity to shifts in nutrient loads [5,6], toxic contaminants [7], pH [8,9,10], and conductivity [11] enables a fine-scale assessment of ecological integrity and water quality [12,13]. Analyses of physico-chemical parameters from water samples always represent a snapshot; thus, the integration biological monitoring has great advantages. In Europe, the implementation of the Water Framework Directive (WFD) stipulated the use of the Biological Quality Elements, among the BQE phytobenthos [14].
Biological assessment systems using benthic diatoms, mainly for rivers and streams, were developed more than 100 years ago [15], with ongoing research and optimization [12,16].
In Russia, there is an extensive history of diatomology since the 18th century [17]. This is reflected by contributions to taxonomy (e.g., [18]) as well as the available identification literature [19,20,21]. The composition of benthic diatom community is also used for biomonitoring [22,23,24,25,26].
The headwaters of the Volga River are of special interest, as they represent reference or least disturbed conditions [27] and they are part of a long-term research and monitoring program since 2006, with a focus on macroinvertebrates [28]. However, diatom samples were also continuously collected and stored for subsequent analyses.
Our analyses provide a first comprehensive checklist of benthic diatoms for the Volga river between its source and Tver [29], which comprises baseline data for future comparisons. In this study, we consider three main research questions:
  • Are there longitudinal changes, i.e., according to the hydromorphological reaches, within the diatom community of the headwaters of the Volga?
  • Are there differences in the species richness and composition between the tributaries and the main channel? If so, how is the influence of tributaries on the main channel?
  • How do physico-chemical and hydromorphological parameters affect the diatom community in the headwaters of the Volga?

2. Materials and Methods

2.1. Field Work

Fieldwork was carried out in the context of the Upper Volga Expedition 2005 (UVE 2005) in summer low water period (August 2005), in the headwaters of the Volga (445 km) upstream the city of Tver (rkm 3085). The catchment area covers approximately 31,300 km2 (Figure 1). The upper section is located in a sparsely populated area, the lower section leads past the towns of Rzhev, Staritsa, and Tver (the capital of Tverskaya oblast). The UVE 2005 analyzed the headwaters of the Volga, including the main channel as well as important tributaries. Samples were taken in the main channel above and below large settlements and also, the runoff of selected tributaries was analyzed, in order to evaluate their hydro-chemical influence on the Volga (Table 1). From thirty tributaries (of which 9 were selected for phytobenthos sampling) water samples were taken and compared to samples from the Volga main channel above and downstream the mouth [30].
The parametera used in this study were determined as follows: pH and electrical conductivity were measured directly in the river using portable pH meter and conductometer. Chromaticity, nitrogen, and phosphorus were determined in laboratory conditions. The chromaticity was determined spectrophotometrically, from a water sample filtered through a membrane filter (0.45 microns) and expressed in degrees of a standard chromium-cobalt scale. Total nitrogen and total phosphorus were determined after boiling with potassium persulfate and subsequent determination of nitrates and phosphates by spectrophotometric method.
Overall, 27 diatom samples (18 from the Volga and 9 from selected tributaries) were collected in shallow water along banks from different habitats, i.e., stones (larger stones, pebbles), fine sediment (sand, mud), and macrophytes (according to [31]). At sites where hard substrate (stones or wood) was dominant, at least 15 stones (or other parts of hard substrate) were brushed with a toothbrush in order to detach algae. At locations characterized by fine sediment (psammal or pelal), the uppermost layer (2–3 mm) of the substrate was sampled. In places, parts of macrophytes were sampled using tweezers. In case different habitats were present at one site, the algal suspension from the sampled habitats was mixed to obtain a representative sample for one location. The samples were preserved in 70% ethanol. Shading was classified based on the “River Habitat Survey” [32] and the resulting CEN standard 14614 [33].

2.2. Preparation and Determination

The diatom samples (n = 27; Volga and tributaries), were prepared using the hydrogen peroxide (H2O2) method according to “Kingston 1985” [34]. The boiling samples were enriched with 2 N hydrochloric acid (HCl) to initiate the reaction with the carbonate. They were washed and decanted three times for 15 min at a centrifuge output of 2500× g. Subsequently, 10 mL of hydrogen peroxide (H2O2) was added and the samples boiled for 20 min at a temperature of 100 °C. A spatula tip of potassium bichromate (K2Cr2O7) was added to accelerate consumption of the organic material. Afterwards, the samples were washed three times, the suspension was dripped onto round coverslips (Ø 12 mm), and the dried preparations were embedded in slides in Naphrax™ (Norhtern Biological Supplies Ltd., Bolton, UK, refractive index = 1.74) (per slide 2–3 coverslips per sampling location). A few drops of ethanol (96%) were added to the cleaned samples to maintain them in good condition.
Determination was carried out with common keys [35,36,37,38,39,40,41,42]. Determination and qualitative counts (classification into abundance classes) under the light microscope (1000× magnification, oil immersion) were performed [30]. In order to complete the UVE 2005 dataset and to bring the taxonomy up to date within the present study a quantitative re-count (at least 500 valves per sampling site) was carried out.

2.3. Analyses

Species richness (number of species (R’), alpha diversity), the ratio of planktonic to benthic, as well as raphid to araphid species were determined for each location. The relative abundances (rA, %) were calculated based on the counts of the species. As a measure of diversity within the communities, the Shannon–Weaver index (H’) [43] and the Evenness index (E’, range 0 to 1) [44] were calculated. Relative abundances and biodiversity directly affect these indices. In order to evaluate the differences between the individual sampling locations, a distance matrix was created using Bray–Curtis distance measurement [45]. The dominance ratios are summarized in a Whittaker Plot (rank–abundance diagram, [46]).
There is no national bioindication system in Russia that uses benthic diatoms to assess aquatic ecosystems [47]. The indices were calculated in the program EcoProf 4 [48], which is based on the “Austrian Guidelines for the Collection of Quality Biological Elements—Part A3—Phytobenthos” [49]. The extent of organic pollution is assessed with the Saprobic Index [50] and the nutrient load is calculated based on the Trophic Index [51].
Non-Metric Multidimensional Scaling (NMDS), which is a convenient method for many zero-valued data sets [52], was used in the PC-ORD 5.31 program [53] to determine the number of gradients that should be applied to the distribution of the samples in multivariate space. A final stress value of <20% was classified as “Good Significance/Applicability” and of <10% as “Very Good Significance/Applicability”. Based on these results, a three-dimensional solution was chosen, and in the program, Canoco 5.4 [54,55], a NMDS with rotation in PCA with 999 perturbations was performed. The explained variation in the axes and the distribution of the samples in the ordination were shown in scatter plots (axes 1 and 2, axes 1 and 3). Variables, which explain a larger portion of the variance, are indicated in red.
Cluster analyses were carried out with the software PC-ORD 5.31 for the entire data set (Volga and tributaries), using the Bray–Curtis distance and the linking method Flexy-Beta. The final measure of the linkage (flexy-beta between −1 and 1) was tested until the comparatively lowest “chaining” value (chain formation) was reached. The Indicator Species Analysis tested cluster groupings of sample sites based on their critical indicator species. First, the main groups were tested, then the subgroups, etc., to the respective indicator values of the type (IV%), the mean (mean = comparison of the observed value to the calculated value of a random distribution), the standard deviation (between observed and calculated value of a random distribution), and the significance. The predefined groups (Volga and tributaries, as well as three hydro-morphological sections for the Volga) were also tested. With high indicator value (>30%), concomitant significant p-value (>0.05), and low standard deviation, species were classified as indicator species for the groups tested. The tests were carried out with the raw data as well as with transformed data (Beal’s smoothing, presence/absence transformation, power transformation). Beal’s smoothing is a multivariate transformation designed specifically for zero-valued data. The significance was tested in each case with 4999 Monte Carlo permutations.
Multiresponse permutation procedures (MRPP) were used to test the significance of heterogeneity between the groups [56]. This is a method which tests the significance of the difference between a-priori-defined groups and the data set does not have to meet any requirements regarding distribution (normal distribution).

3. Results

3.1. Species Richness

From 27 locations, 270 taxa (244 pennate and 26 centric) were identified. Regarding benthic diatoms, 243 taxa (222 taxa were determined on species level and 21 on genus level) were identified, of which 130 occurred in the Volga as well as the tributaries. Additionally, 116 species were found only in the Volga and 40 species only in the tributaries. The majority had a raphe (86% Raphales vs. 14% Araphales) and 29 of the taxa are listed in the Red List of Germany [57]. Most taxa were found within Naviculoidae (40 spp.), Fragilarioidae (29 spp.), Nitzschoidae (27 spp.), Achnanthoidae (23 spp.), Gomphonemoidae (19 spp.), Cymbelloidae (17 spp.), and 16 species belong to the Amphora-complex. The 10 most common species were Cocconeis placentula, Achnanthidium minutissimum, Navicula capitatoradiata, Achnanthidium affine, Tabellaria flocculosa, Fragilaria capucina, Nitzschia palea, Cymbopleura naviculiformis, Navicula cryptocephala, and Eolimna minima (nowadays: Navicula minima), with Cocconeis placentula being the most dominant species in the headwaters of the Volga. Also, planktonic taxa were found, among Aulacoseira subarctica, Cyclotella menegheniana (nowadays: Stephanocyclus meneghinianus), and Melosira varians were the most common ones, and overall, their number increased downstream, i.e., no planktonic taxa in R1, 16 species in R2, and 24 species in R3, as well as 14 species in the tributaries.
Species richness in the Volga and its tributaries was comparable; for both, the median was 48, while the mean value was 46 in the Volga and 50 spp. in the tributaries (Figure 2a). Overall, the species richness in the Volga (243 spp.) was higher than in the tributaries (168 spp.); however, this is related to sampling effort. The number of species increased along the river continuum (Figure 2b). Comparing the locations from reach 3 with the tributaries (with n = 9 for both); in the tributaries, 16 more species were found.

3.1.1. Longitudinal Gradient of Species Richness

There was no clear trend of species numbers along the river continuum. Within the 18 sampling locations in the main river, the number of species varied between 29 and 70. In the R1 (two sampling locations), 66 species occurred (mean value = 43), in R2 (seven sampling locations), 151 (mean value = 44), and in R3 (nine sampling locations), 152. The number of species dropped in the first reach (R1) from 46 to 40. In the second reach, the numbers fluctuated at the seven sites along the Upper Volga Lakes (lowest number of species at V06–29 species), and higher species numbers were observed in the tributaries. In R3, the species numbers also fluctuated (maximum species richness at V17–70 species; Figure 3).

3.1.2. Diversity

Shannon diversity (H’) was between 1.46 and 3.61 and Evenness (E’) was between 0.40 (V03) and 0.89 (V08). The lowest E’ values were observed at the uppermost locations (V01 and V03) and the highest ones in reach 2 (V08 and V09).
Comparing the Volga and the tributaries (Table 2), only half the standard deviation of the two diversity indices was observed in the tributaries. Diversity was higher in the feeders, i.e., the mean value of the H ‘value for the Volga sites is approximately equal to the minimum value of the H’ of the tributaries. The maximum values for H’ and E’ of the tributaries were higher than those of the main channel. The range of H’ in the Volga was more than twice as large as in the tributaries.

3.2. Species Dominance

Based on the relative abundances of the species, five dominance classes were defined: eudominant (>25%), dominant (10–25%), abundant (3–10%), occasional (1–3%), and scarce (<1%).
In the main channel, six taxa were eudominant: Achnanthidium minutissimum (72.6%), Cymbopleura naviculiformis (49.5%), Fragilaria capucina var. capucina (47.9%), Cocconeis placentula (44%), Navicula capitatoradiata (32.7%), and Achnanthidium affine (28%). Twelve taxa were dominant, among them, e.g., Tabellaria flocculosa, Nitzschia fonticola, Eolimna minima, Fragilaria vaucheriae, and Fragilaria ulna. Between four and seven of the dominant species occured at each site. Thirty-one species were abundant, 59 species were occasional, and 135 species were scarce. Within the Volga, the sums of the ten species with the highest relative abundances accounted in all sites for more than 20% of the species composition and in 6 out of 18 sample sites, even more than 50% (Figure 4).
The dominance of the species in the tributaries was as follows: eudominant was only Cocconeis placentula (32.8%). Dominant were the five taxa Navicula capitatoradiata (19.7%), Encyonema silesiacum (11.9%), Achnanthidium affine (11.3%), Eolimna minima (10.3%), and Fragilaria capucina var. capucina (10.1%). Between 7 and 10 of the dominant species occurred at each site. Navicula cryptotenelloides, Navicula tripunctata, Amphora pediculus, Achnanthidium minutissimum, and Tabellaria flocculosa were representatives of the class abundant (33 species). Seventy-three species occurred occasional and 89 species were scarce. Within the tributaries, the sum of the ten species with the highest relative abundances accounted in all sites more than 20% of the species composition, and in four out of nine sites, for more than 50% (Figure 4b).
Representatives from the Achnanthidium minutissimum complex were found in most sample sites and had a mass occurrence (72.6%) at the first sampling site (V03) in reach 2; perhaps this is the variety Achnanthidium minutissimum var. jackii. Also, in the tributaries the species was dominant, except in the three tributaries Kud’ (T3), Vazuza (T24), and Iruzha (T26), where no individuals were found.
Cocconeis placentula was the only species found at every site in our dataset. The species had the largest total number of counted individuals. Their relative abundance was initially low (“source region” R1), then rising in the “Upper Volga lakes” (R2), and had the maximum value in the first trial in the third section (R3 “free-flowing section”), e.g., at Rzhev (V13) 44%. This species was also a dominant species in eight out of nine tributaries.
Cymbopleura naviculiformis was found in the uppermost locations (V01 and V02) as well as in one site in the second reach (V10). At V02, this species was eudominant (49.5% relative abundance). In comparison, its occurrence in tributaries (in four of nine) was below 1%.

3.2.1. Longitudinal Characterization of Dominance Relationships

The uppermost reach (R1) was dominated by the araphid species Fragilaria capucina and Cymbopleura naviculiformis. In the second reach (R2), a raphid (mobile) species of the Achnanthidium minutissimum complex was the most abundant, living epiphytically, epilithially, and subaerially. The lowermost reach (R3) was characterized by the raphid species Cocconeis placentula (epiphytic) and Navicula capitatoradiata (epipelic).
Some species within the genera Achnanthes (e.g., Achnanthidium affine), Fragilaria (e.g., Fragilaria ulna, Fragilaria vaucheriae), Navicula (e.g., Eolimna minima, Navicula capitatoradiata), and Nitzschia (e.g., Nitzschia fonticola) were dominant in one or more locations along the main channel.

3.2.2. Characterization of the Dominance Relationships in the Tributaries

Most species occurring in the tributaries had a relative abundance of <10% (common, occasional, or rare), except for Cocconeis placentula, which had eudominant and dominant contributions to the species composition. It characterized the tributary (Runa, T02) and was dominant in five tributaries, common in two, and only in one sample from a small creek running from a spring (Shirkovo, T04), the relative abundance was <1%. The dominance ratios of the tributaries (T03 and T07) were similar: Cocconeis placentula, Fragilaria capucina var. capucina, Eolimna minima, Achnanthidium affine, and Navicula capitatoradiata dominated the community. In the tributary Locha (T22) Achnanthidium affine and Navicula cryptotenella dominated the species composition. In almost all tributaries Achnanthidium affine and A. minutissimum were common.
The species Encyonema minutum, Nitzschia dissipata, and N. palea were found in almost all tributaries. Meridion circulare, Planothidium lanceolatum, and Sellaphora pseudopupula characterized the Shirkovo tributary (T04). Overall, the proportion of dominant species with raphe was higher in the tributaries than in the main river.

3.3. Characterization of the Sampling Locations According to Their Diatom Community

Based on the species composition and relative abundances per species, a distance matrix was created using the Bray–Curtis distance measure. The distance measure is defined as “similarity-1.” The differences between the sampling sites resulted in distances ranging from a minimum of 0.35 to a maximum of 0.97 (Figure 5). This means that, for example, sampling sites T07 and T03 agreed with 65% in their species compositions and relative abundances, whereas sampling sites V36 and V37 only showed 3% similarity with V03. The longitudinal gradient shows a trend from “very dissimilar” or increased variability between the sites in the upper section R1, to increased similarity in the middle section R2, and even greater similarity in the lowest section R3 and the tributaries. Only site V03 stood out in this context within the main river, as it was even more dissimilar to the remaining sites in the second section than the top two sites (R1). Within the distances of the tributaries, a greater dissimilarity of site T04 to the remaining tributaries stood out.

3.3.1. PCA Grouping Based on NMDS

Based on 125 iterations, NMDS revealed a three-dimensionality (k = 3; stress-value = 14.13), i.e., three variables (“composite variables”) affect the distribution of locations based on the diatom community. The first axis explains 41.39%, the second axis 34.88% and the third axis 23.73% of the variability of distances between locations. More than 75% (“cumulative explained variation”) of the variance among locations is explained by the first and second axis. Regarding the longitudinal differentiation, reach 1 (with locations V01 and V02) have the largest distance to all other locations (Figure 6). The third axis reveals an overlap; however, reach 1 is still clearly separated (Figure 6).
Based on these findings, NMDS with simultaneous rotation in PCA was performed with 1000 permutations. The Bray–Curtis distance was used as the distance measure. When comparing inclusion of all species to selection of all species that occurred at least twice, a similar distribution was observed.

3.3.2. Grouping Based on Cluster Analysis

The cluster analyses revealed six groups, with a major cluster including reach 2, reach 3, and most tributaries (Figure 7). Subsequent runs (with flexy-beta= −0.95) were made only for the Volga (chaining = 9.57) and only for the tributaries (chaining = 6.67).

3.3.3. Spatial Distribution of Diatoms in Relation to Environmental Parameters

A detailed description of the physico-chemical conditions is published in [58]; in Table 1, the herein used parameters are summarized. Transparency increased along the river course. No data for the Secchi depth was available for the tributaries, due to their shallow depths. Water temperature increased slightly downstream of the Volga. Due to heavy rainfall, the air temperature decreased during the expedition from 26.8 °C (8 August 2005) to 18.1 °C (22 August 2005) [30]. The chromaticity of water characterizes the presence of humic organic matter in the water. The highest chromaticity in diatom sampling points in the Volga River is observed in its swampy source (V01 with 640°), the lowest in the city of Rzhev. Among the tributaries, the highly paludified Runa River had the highest chromaticity, and the Locha River had the lowest chromaticity. The pH value was higher on average in the tributaries (6.9–8.1) than in the Volga sampling sites (6.0–7.5). The highest value was measured in tributary T10 (8.1), and the lowest in tributary T07 (6.9). It should be noted that pH values can vary significantly throughout the day in summer. Conductivity increased along the Volga and was, on average, higher in the tributaries than in the main river (minimum in tributary T07 (146 µS/cm) and maximum in tributary T22 (540 µS/cm). The conductivity of water is a relative indicator of its mineralization. Among all the diatom sampling sites, the water at the source of the Volga River, which is located in a mesotrophic mire of lacustrine genesis, is characterized by the lowest mineralization. In the section of the Volga River below the Bejshlot, mineralization is continuously increasing. Among the studied tributaries of the Volga, the Selizharovka River had the lowest mineralization at its mouth (it flows from the Lake Seliger); the largest was measured in Locha River.
The highest total nitrogen content was observed in the Lake Sterzh and in the Volga River in Selizharovo (above the confluence of the Selizharovka River). The highest total phosphorus content was observed in the Volga River near Rublevo village and at the mouth of the Solodomlya River (see Table 1).
In the ordination of species with the substrate-specific parameters and the hydromorphological sections (R1, R2, R3 + tributaries (T), which are equivalent to the rkm), 33.1% of the variability was explained (CCA) (Table 3, Figure 8). The parameters R1 and R3 showed significant influence (p = 0.03 for R1; p = 0.001 for R3; without p-value adjustment). In isolation, they each explained 5.3% and 6.3%, respectively, and contributed 16.2% and 18.9%, respectively, to the explanatory variables. The p-value for the remaining parameters (substrate and R2) was outside the significant range. They each explained between 3.2% and 4.0% in isolation, and between 9.7% and 12.0%, respectively, in the sum of the explanation with the remaining parameters.
The ordination was performed with the same parameters for the species traits (Figure 9). The eigenvalues of the axes were half as small, but R1 still had a significant influence (p = 0.0145). In contrast to the ordination with the species, R2 was close to the significant range. In isolation, they each explain 8.1% and 4.8%, respectively, and account for 25.1% and 14.9% of the explanatory variables, respectively. The p-value for the remaining parameters (substrate and R3) is in the non-significant range. They each explain between 2.9% and 4.3% in isolation, and between 7.9% and 11.7% together with the remaining parameters.
In the ordination of species with the physicochemical parameters pH, conductivity, chromaticity, N-NH4, N-NO3, N-NO2, total N, and total P, the variables explained a total of 46.8% in the RDA and 45.5% in the CCA, with no parameter showing significance. All parameters were considered by forward selection. In the ordination of species traits with the same physicochemical parameters, 46.0% of the variability was explained (RDA) (Table 4, Figure 10) with chromaticity (“colour”) showing a significant influence (p = 0.014; without p-value adjustment). Chromaticity alone explains 9.7%. Its contribution to the explanatory variables was 21.1%. The p-value for the remaining parameters is in the non-significant range. They each explain between 4.3 and 6.1% in isolation and 9.3 and 13.3% in the sum of the explanation with the remaining parameters.
Regarding the saprobic index, the source region (reach R1), was characterized by a large proportion of xeno- and oligo-saprobic species, with the proportion of oligo-beta and beta-meso-saprobic species increasing along the continuum (from V01 to V02). The distribution of saprobic valences in the “Upper Volga Lakes” (reach R2), was fluctuating. The ratio between xeno- and oligo-saprobic species is approximately the same at the beginning, then shifted towards oligo-saprobic species (maximum at V11). In the “free flowing section” (reach R3), the proportion of oligo- and oligo-beta saprobic species decreased, while the proportion of beta-meso-saprobic species (max at V36 = 5.19) and beta-alpha-saprobic species (max at V37 = 3.11) species increased (Table 5). Only in this section, alpha-poly and poly-saprobic species were found; however, their shares were very low (<0.05).

4. Discussion

The samples from the UVE 2005 revealed with 270 identified taxa within 64 genera a high diatom diversity in the headwaters of the Volga. The Whittaker plot reveals that the sampling locations were dominated by one or a few species (with high relative abundances). The numbers of species, however, were often high, which reflects a large species richness. However, since the species composition varies seasonally, species numbers are also an indicator of river health (i.e., ecological integrity) as they are often less volatile [3]. Maxima of Shannon–Weaver diversity (H’) and Evenness (E’) were 3.46 and 0.89, respectively; the maximum of species abundance was 70 species (within one sampling location).
Cocconeis placentula was the most dominant species within the whole data set. The pronounced dominance of this widespread epiphyte is common in lowland waters with dense macrophyte populations. The second most common species, Achnanthidium minutissimum, is a pioneer species that often forms mass occurrences. It is possibly the most common diatom in Europe [35] and has a very broad ecological amplitude.
In order to analyze the influence of a possible longitudinal gradient, species numbers and diversity were correlated with river kilometers (distance to source) as well as sections (R1–R3). We did not find a clear trend in species numbers of the Volga (and the tributaries) along the continuum. The number of species increased along the course of the river, but also the number of locations increased. In the “source region (R1)”, which contains only two sampling sites, the number of species was correspondingly lower (66 species in total) than in the “Upper Volga Lakes” (R2; seven sampling sites) (151 species in total) and in the “free flowing section” (R3; nine sampling sites) (151 species in total). On average, however, the species numbers of the sections were similar. The Pearson correlation showed that there is no significant correlation between biodiversity and the distance of the sampling sites to the source of the Volga. Each section has been characterized by one or two “eu-dominant” species that can form mass occurrences. The species with the maximum relative abundances were Fragilaria capucina and Cymbopleura naviculiformis in reach R1, Achnanthidium minutissimum in reach R2, as well as Cocconeis placentula and Navicula capitatoradiata in reach R3.
The distance matrix, based on differences between the species compositions of the samples, showed a longitudinal trend along the river. The diatom communities became more similar further downstream. The variability of species composition decreased from the uppermost (R1) to the lowermost reach (R3) of the Volga.
An attempt was made not to remove any incomplete “samples” from the analysis (only 7 out of 27 sample sites have all data on the environmental parameters available) as the sample size would have been reduced too much. Also, since the validity of individual parameters decreases with increasing number of parameters, different ordinations with parameter groups were performed. One group contained topographical and substrate specific parameters, the parameters longitudinal zoning (sections R1, R2, R3, and feeder, respectively) and substrate. In another ordination, the species data were analyzed based on physical-chemical parameters.
The Volga is the largest river in Europe [59]; in this context, the presented dataset complements the available data about diatoms in this river system. Overall, 135 species out of 270 were scarce; however, also these records of species with relatively low abundance are important for the biodiversity assessment [60]. Also, about 8.4% of the benthic diatom taxa are listed on the German Red List [57]. In this context, it is noteworthy that there is only a single diatom-specific Red List (developed for Germany) available [61].
Overall, this study contributes significantly to the knowledge about the benthic diatom flora in the Volga headwaters, as this research provides the first checklist for the uppermost stretch between the source and Tver. It also constitutes a basis for future research regarding changes related to climate change [62] as well as the spread of invasive species [63].

Author Contributions

Conceptualization, N.I. and M.S.; methodology, N.I., V.V.K., and M.S.; validation, M.S.; formal analysis, N.I. and M.S.; investigation, N.I., V.V.K., S.I.S., A.H., and M.S.; data curation, M.S.; writing—original draft preparation, N.I. and M.S.; writing—review and editing, N.I., V.V.K., S.I.S., A.H., and M.S.; visualization, N.I. and V.V.K.; supervision, A.H. and M.S.; project administration, V.V.K. and M.S. All authors have read and agreed to the published version of the manuscript.

Funding

Sampling took place during an expedition in 2005, which was funded by M.L. Egorov. The analyses of the diatom samples took place years later, this research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The raw data is available at https://doi.org/10.5281/zenodo.17704802.

Acknowledgments

Thanks to M.L. Egorov, who funded the expedition in 2005, and to the whole team of the “Upper Volga Expedition 2005”. We are also thankful to E. Rott for his support and valuable comments to this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study area in the headwaters of the Volga. The diatom sampling points of the UVE 2005 and their location within the different hydromorphological reaches are indicated with different colors: yellow = R1, blue = R2, and green = R3 (points = main channel; squares = tributaries).
Figure 1. Study area in the headwaters of the Volga. The diatom sampling points of the UVE 2005 and their location within the different hydromorphological reaches are indicated with different colors: yellow = R1, blue = R2, and green = R3 (points = main channel; squares = tributaries).
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Figure 2. Species richness: (a) comparison Volga vs. tributaries, (b) species richness as well as (c) Shannon–Weaver diversity, and (d) evenness along the hydromorphological reaches R1, R2, and R3.
Figure 2. Species richness: (a) comparison Volga vs. tributaries, (b) species richness as well as (c) Shannon–Weaver diversity, and (d) evenness along the hydromorphological reaches R1, R2, and R3.
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Figure 3. Changes in benthic diatom species richness with increasing distance (gray line) from the source of the Volga. Sites in the main river are colored blue, while those in the tributaries are colored green. The dashed lines indicate the hydromorphological reaches R1, R2, and R3.
Figure 3. Changes in benthic diatom species richness with increasing distance (gray line) from the source of the Volga. Sites in the main river are colored blue, while those in the tributaries are colored green. The dashed lines indicate the hydromorphological reaches R1, R2, and R3.
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Figure 4. Proportions of the 10 most common species (Coc_pla = Cocconeis placentula, Ach_min = Achnanthidium minutissimum, Nav_cap = Navicula capitatoratiata, Ach_aff = Achnanthidium affine, Tab_floc = Tabellaria flocculosa, Fra_cap = Fragilaria capucina, Nit_pac = Nitzschia palea, Cym_nav = Cymbopleura naviculiformis, Nav_crc = Navicula cryptocephala and Eol_min = Eolimna minima) of the total dataset at the sampling sites in the Volga (a) and the sampling sites in the tributaries (b).
Figure 4. Proportions of the 10 most common species (Coc_pla = Cocconeis placentula, Ach_min = Achnanthidium minutissimum, Nav_cap = Navicula capitatoratiata, Ach_aff = Achnanthidium affine, Tab_floc = Tabellaria flocculosa, Fra_cap = Fragilaria capucina, Nit_pac = Nitzschia palea, Cym_nav = Cymbopleura naviculiformis, Nav_crc = Navicula cryptocephala and Eol_min = Eolimna minima) of the total dataset at the sampling sites in the Volga (a) and the sampling sites in the tributaries (b).
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Figure 5. Distance matrix based on species composition and relative abundances of species at the individual sampling sites (green = low distance; red = high distance). The three hydromorphological sections (R1, R2, R3) are indicated by a frame line, and the tributaries are indicated by a dashed line, and their values are shown in italic.
Figure 5. Distance matrix based on species composition and relative abundances of species at the individual sampling sites (green = low distance; red = high distance). The three hydromorphological sections (R1, R2, R3) are indicated by a frame line, and the tributaries are indicated by a dashed line, and their values are shown in italic.
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Figure 6. Configuration of sampling sites in the ordination field on axes 1 and 2 (left) and on axes 1 and 3 (right). Main river sampling sites are shown as circles, tributary sampling sites as squares (green). The three sections of the Volga’s longitudinal course are color-coded: R1—blue, R2—purple, and R3—orange. The tributaries are indicated with a green dashed cycle.
Figure 6. Configuration of sampling sites in the ordination field on axes 1 and 2 (left) and on axes 1 and 3 (right). Main river sampling sites are shown as circles, tributary sampling sites as squares (green). The three sections of the Volga’s longitudinal course are color-coded: R1—blue, R2—purple, and R3—orange. The tributaries are indicated with a green dashed cycle.
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Figure 7. Cluster analyses (Bray–Curtis distance, flexy-beta −0.5) of all sampling locations (chaining = 1.6).
Figure 7. Cluster analyses (Bray–Curtis distance, flexy-beta −0.5) of all sampling locations (chaining = 1.6).
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Figure 8. Ordination (CCA) based on species composition (abbreviations according to [29]).
Figure 8. Ordination (CCA) based on species composition (abbreviations according to [29]).
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Figure 9. Ordination (RDA) based on community characteristics (left) axes 1 and 2; (right) axes 1 and 3. Substrate specific classes include M = “mud”, OM = “organic matter”, G = “gravel”, S = “sand” and ST =“stones”.
Figure 9. Ordination (RDA) based on community characteristics (left) axes 1 and 2; (right) axes 1 and 3. Substrate specific classes include M = “mud”, OM = “organic matter”, G = “gravel”, S = “sand” and ST =“stones”.
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Figure 10. Ordination (RDA) of the physico-chemical environmental parameters based on community characteristics (left) axes 1 and 2; (right) axes 1 and 3.
Figure 10. Ordination (RDA) of the physico-chemical environmental parameters based on community characteristics (left) axes 1 and 2; (right) axes 1 and 3.
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Table 1. Overview on the 27 sampling locations: 18 were located in the main river (ID “Vxx”-Volga) and 9 in tributaries (ID “Txx”-tributary).
Table 1. Overview on the 27 sampling locations: 18 were located in the main river (ID “Vxx”-Volga) and 9 in tributaries (ID “Txx”-tributary).
IDLocationSampling DateDistance from the Source of Volga River [km]pHEC
[µS/cm]		Color
[°]		Total N
[mg/L]		Total P
[mg/L]
V01Volgoverkhovie7 August 200506.3496403.400.42
V02Upstream Sterzh7 August 20059.37.3892501.700.46
V03Novinka (L1, r.b.)9 August 200510.87.81092204.201.36
V06Lk. Vselug–Lk. Peno8 August 200544.18.01131800.720.24
V07Lk. Peno Pionerlag8 August 200545.8-11398--
V08Lk. Peno (Peno)8 August 200553.98.11301680.590.19
V09Lk. Volgo 1 (Ilinskoe, l.b.)10 August 200566.37.81001810.980.01
V10Lk. Volgo 1 (Zaneprechje, l.b.)10 August 200568.47.41551881.300.26
V11Lk. Volgo 2 (near Bejshlot)11 August 2005103.97.4922201.501.96
V13Bejshlot (L2, r.b.)11 August 2005105.18.01012200.220.07
V17Selisharowo12 August 2005118.5-1001804.641.52
V29Petunovo (L9, r.b.)19 August 2005238.9-185---
V31Rzhev (upst. main bridge)19 August 2005262.78.6191922.900.07
V34Rublevo (L12, r. bank)22 August 2005314.88.0218981.502.88
V35Danilovo Sloboda (l.b.)22 August 2005329.0-221---
V36Borovaja (Bottom Sill 210)22 August 2005336.0-223---
V37Molokovo23 August 2005341.9-2271103.001.70
V38Staritsa (downstr. bridge, r.b.)23 August 2005353.08.42281091.200.25
T02Runa8 August 200527.28.51541841.031.28
T03Kud’9 August 200547.28.31671751.000.76
T04Shirkovo9 August 200516.17.3252520.500.32
T07Selizharovka12 August 2005119.07.9146501.001.60
T10Solodomlya14 August 2005155.08.5300981.802.28
T18Koksha18 August 2005234.07.9452380.780.42
T22Locha19 August 2005269.07.4540413.501.08
T24Vazuza20 August 2005289.08.5273652.800.29
T26Iruzha22 August 2005319.08.3537492.501.16
Table 2. Diversity indices of benthic diatoms in the Volga, the individual sections of the Volga and its tributaries (mean Shannon–Weaver diversity, minimum and maximum Shannon–Weaver diversity, mean evenness, minimum and maximum evenness; standard deviation in each case).
Table 2. Diversity indices of benthic diatoms in the Volga, the individual sections of the Volga and its tributaries (mean Shannon–Weaver diversity, minimum and maximum Shannon–Weaver diversity, mean evenness, minimum and maximum evenness; standard deviation in each case).
ReachH’
Mean		H’
min/max		H’
SD		E’
Mean		E’
min/max		E’
SD
Volga (R1–R3)2.841.46/3.460.560.740.40/0.890.13
>R12.051.97/2.140.120.550.51/0.580.05
>R22.881.46/3.370.680.760.40/0.890.17
>R32.992.42/3.460.370.770.66/0.850.06
tributaries3.222.86/3.610.280.830.72/0.930.06
Table 3. Eigenvalues and explained variance [%] of the four axes in the ordination field (CCA) based on the relative abundances of species in relation to substrate-specific and hydro-morphological environmental parameters.
Table 3. Eigenvalues and explained variance [%] of the four axes in the ordination field (CCA) based on the relative abundances of species in relation to substrate-specific and hydro-morphological environmental parameters.
Species (CCA)Axis 1Axis 2Axis 3Axis 4
Eigenvalues0.200.140.120.10
Explained variation (cumulative) [%]8.1513.7218.6122.85
Pseudo-canonical correlation0.980.970.950.93
Explained fitted variation (cumulative) [%]24.6441.4956.2968.29
Table 4. Eigenvalues and explained variance [%] of the four axes in the ordination field based on species traits in relation to selected physico-chemical environmental parameters.
Table 4. Eigenvalues and explained variance [%] of the four axes in the ordination field based on species traits in relation to selected physico-chemical environmental parameters.
Species (RCA)Axis 1Axis 2Axis 3Axis 4
Eigenvalues0.110.090.060.06
Explained variation (cumulative) [%]10.7619.4925.7131.76
Pseudo-canonical correlation0.970.950.890.95
Explained fitted variation (cumulative) [%]23.3742.3655.8669.01
Table 5. Bioindication at the 27 sampling locations: taxa numbers, saprobic index (SI according to [50]), and trophic index (TI according to [51]).
Table 5. Bioindication at the 27 sampling locations: taxa numbers, saprobic index (SI according to [50]), and trophic index (TI according to [51]).
IDLocationSampling DateBenthic TaxaPlanktonic TaxaSITI
V01Volgoverkhovie7 August 20054201.712.71
V02Upstream Sterzh7 August 20054001.441.93
V03Novinka (L1, r.b.)9 August 20053661.471.39
V06Lk. Vselug–Lk. Peno8 August 20052941.932.82
V07Lk. Peno Pionerlag8 August 200557121.962.62
V08Lk. Peno (Peno)8 August 20054191.972.86
V09Lk. Volgo 1 (Ilinskoe, l.b.)10 August 20054241.742.49
V10Lk. Volgo 1 (Zaneprechje, l.b.)10 August 20055142.192.97
V11Lk. Volgo 2 (near Bejshlot)11 August 200548111.482.38
V13Bejshlot (L2, r.b.)11 August 200539101.722.72
V17Selisharowo12 August 200565161.742.38
V29Petunovo (L9, r.b.)19 August 20055361.882.49
V31Rzhev (upst. main bridge)19 August 20056571.872.86
V34Rublevo (L12, r. bank)22 August 20054532.052.84
V35Danilovo Sloboda (l.b.)22 August 20054752.042.92
V36Borovaja (Bottom Sill 210)22 August 20054282.002.74
V37Molokovo23 August 20053032.243.26
V38Staritsa (downstr. bridge, r.b.)23 August 20054682.113.06
T02Runa8 August 20055461.542.25
T03Kud’9 August 20056691.802.64
T04Shirkovo9 August 20054612.382.89
T07Selizharovka12 August 20055091.692.48
T10Solodomlya14 August 20054621.742.31
T18Koksha18 August 20056462.162.88
T22Locha19 August 20054421.962.67
T24Vazuza20 August 20053972.082.84
T26Iruzha22 August 20054361.982.85
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Ismaiel, N.; Kuzovlev, V.V.; Shaporenko, S.I.; Holzinger, A.; Schletterer, M. Diversity of Benthic Diatoms and Abiotic Patterns in the Headwaters of the Volga River. Diversity 2025, 17, 842. https://doi.org/10.3390/d17120842

AMA Style

Ismaiel N, Kuzovlev VV, Shaporenko SI, Holzinger A, Schletterer M. Diversity of Benthic Diatoms and Abiotic Patterns in the Headwaters of the Volga River. Diversity. 2025; 17(12):842. https://doi.org/10.3390/d17120842

Chicago/Turabian Style

Ismaiel, Natalie, Vyacheslav V. Kuzovlev, Sergey I. Shaporenko, Andreas Holzinger, and Martin Schletterer. 2025. "Diversity of Benthic Diatoms and Abiotic Patterns in the Headwaters of the Volga River" Diversity 17, no. 12: 842. https://doi.org/10.3390/d17120842

APA Style

Ismaiel, N., Kuzovlev, V. V., Shaporenko, S. I., Holzinger, A., & Schletterer, M. (2025). Diversity of Benthic Diatoms and Abiotic Patterns in the Headwaters of the Volga River. Diversity, 17(12), 842. https://doi.org/10.3390/d17120842

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