1. Introduction
Freshwater aquatic macrophytes are among the key habitat-forming components of aquatic ecosystems, shaping the spatial structure and functioning of shallow waterbodies and the littoral zones of large lakes. In ponds, oxbows and slowly flowing river reaches, canals, wetlands, and shallow lake areas (including the littoral), macrophyte stands create most of the structural (three-dimensional) complexity of habitats. By affecting hydrodynamics, the underwater light climate, suspended-matter retention, and the availability of surfaces for colonization, they ultimately determine the distribution and productivity of aquatic biota [
1,
2,
3]. These effects are regarded as one of the central mechanisms maintaining high functional heterogeneity in shallow systems, enhancing resistance to eutrophication, and stabilizing a “clear-water” ecosystem state by competing with phytoplankton for resources. Taken together, this makes macrophyte communities a fundamental element of resilience and the “ecological architecture” of shallow-water habitats [
3,
4,
5].
Alongside morphological habitat engineering, macrophytes also exert biochemical structuring of the water column and the near-bottom layer. Of particular ecological interest are low-molecular-weight organic compounds (LMWOCs), including phenolics, terpenoids, fatty acids, and other metabolites capable of altering the growth, physiology, and community structure of phytoplankton, epiphyton/periphyton, and the associated microbiome. Chemical regulation encompasses the synthesis and release of compounds that may function as defensive metabolites, antimicrobial agents, infochemicals, and allelochemicals affecting competing primary producers and associated biota [
6,
7,
8]. In the literature, this regulation is described as a combination of direct allelopathic effects and indirect pathways (changes in the resource environment, selective pressures on taxa, and modification of trophic and microbial interactions). The contribution of macrophytes to the stability of the “clear-water” state in shallow lakes is commonly interpreted as the outcome of several simultaneous mechanisms, among which allelopathy is considered biogeochemically significant [
7,
9,
10]. At the same time, it was revealed that allelopathy caused stronger inhibition than the shading effect and nutrient competition and dominated the combined mechanisms [
11].
If even a small fraction of the thousands of chemicals produced by different plant species (aquatic and terrestrial) affects their neighbors, then species-specific interactions, natural selection, coevolution, and community functioning may deviate substantially from predictions of conceptual models based solely on resource-competition theory [
12]. For submerged macrophytes, the release of compounds with pronounced algicidal activity has been documented (including hydrolysable polyphenols in
Myriophyllum spicatum), and this has been linked to the suppression of specific phytoplankton groups and/or shifts in competitive outcomes in the water column [
13]. Experimental studies also show that macrophyte chemical effects may target not only phytoplankton [
14] but also epiphytic communities, reducing fouling on leaf and shoot surfaces and thereby influencing light availability and the photosynthetic performance of the plants themselves [
15,
16]. Inputs of LMWOCs may additionally occur via autolysis/leaching from submerged macrophyte tissues [
17], underscoring the role of macrophyte stands as a continuous source of organic “fuel” and chemical signals (including allelopathic impact) for microbial and algal communities.
A special role in these biochemical interactions is played by the diffusive (boundary) layer at the surface of leaves and shoots, where limited exchange with bulk water generates the steepest microgradients of oxygen, pH, and dissolved substances. The existence of diffusive boundary layers—and their dependence on flow velocity, irradiance, and surface roughness—defines the spatial scale of the chemical microenvironment in which direct contacts occur among macrophytes and epiphyton/periphyton, macrophytes and microbiome, macrophytes and phytoplankton. It has been shown that hydrodynamics and the structure of biofouling (periphyton) can alter oxygen profiles and processes at the leaf–biofilm interface, thereby modifying conditions for microorganisms and epiphytic algae, affecting macrophyte growth, and potentially changing the effectiveness of chemical regulation mediated by macrophyte LMWOCs [
8,
18,
19,
20]. Therefore, the ecological “effect” of macrophyte metabolites should be considered not only as a function of their presence in the water but also as the outcome of transport and transformation within the boundary-layer microenvironment of leaves and shoots.
Moreover, recent microbiome research indicates that aquatic plants and their associated microbial communities function as an integrated system in which microbial metabolism can modify the plant’s chemical profile (and thus its metabolites) and, in turn, influence ecological interactions [
21]. Particularly important is the concept of the aquatic-plant exometabolome—the set of LMWOCs that actually enter the external environment, forming an external LMWOCs pool and participating in inter-organism interactions. For submerged plants, diverse exudate components have been described, including organic acids, phenolics, and lipophilic molecules, and both the composition and intensity of exometabolite release have been shown to depend on plant species, growth stage, and environmental factors (light, temperature, trophic status of the waterbody, etc.) [
22]. These compounds form a chemical “interface” between the plant and surrounding organisms: they can serve as substrates for bacteria, modulate periphyton growth and metabolism, and participate in allelopathic effects on phytoplankton and cyanobacteria [
7,
9,
22]. Importantly, the exometabolome is not chemically “static”: its composition and activity are determined not only by plant biosynthesis but also by subsequent transformation in the water and within biofilms.
Accordingly, the ecological effect of metabolites is governed by the dynamics of at least three processes: (i) release/input into the boundary layer and bulk water, (ii) physicochemical partitioning and transformation across microgradients, and (iii) biotic transformation and consumption by the microbiome [
18,
19,
23,
24].
In metabolomics, the metabolome is viewed as the ensemble of small molecules reflecting genetic and environmental regulation, and plant LMWOCs profiles obtained by mass-spectrometric approaches are characterized by broad chemical diversity [
25]. Contemporary metabolomics emphasizes that the metabolome—including the low-molecular-weight metabolome (LMWM)—represents an integrated response of an organism to genotype and environment, while analytical platforms (including gas chromatography–mass spectrometry (GC–MS)) enable the detection of numerous metabolites and the comparison of profiles across organisms and habitats [
25,
26]. Studies in aquatic metabolomics indicate that plant LMWMs comprise tens, hundreds, and even thousands of LMWOCs from different functional chemical classes [
27,
28,
29,
30,
31], and gas chromatographic and mass-spectrometric profiling allows large metabolite sets to be identified and compared, capturing genetic and environmental differences [
32,
33]. For aquatic macrophytes inhabiting highly heterogeneous environments (gradients of light, flow, mineralization, trophic state, and fouling), such chemical multicomponent complexity provides a basis for fine-scale tuning of plant interactions with aquatic communities.
Clearly, it is impossible for a single study to elucidate the ecological and biochemical functions of the entire set of compounds in macrophyte LMWMs in aquatic ecosystems. Nevertheless, from an ecological perspective, the most likely “drivers” of community-level impacts are the major components of the LMWM, because they account for the largest share of the total LMWOCs pool and thus have the greatest chance to reach effective concentrations in the microenvironment at the plant surface as well as in the water. In the present study, “major components” are defined as compounds contributing more than 1% of the total sum of LMWOCs concentrations, calculated from peak areas in the total ion chromatogram (TIC) [
34,
35,
36]. This focus is methodologically justified for two reasons. First, major components are the most likely to generate measurable organic fluxes and to reach concentrations comparable to biological response thresholds within the boundary layer and the water column [
18,
19,
37]. Second, for many allelopathic systems, a key challenge is the “gap” between effective doses observed in laboratory experiments and real concentrations in nature [
12,
38,
39]. Therefore, prioritizing major compounds increases the ecological realism of interpretations and facilitates translation from chemical profiles to community-level effects.
At the same time, when focusing only on major components, it is essential to recognize that minor metabolites can be highly bioactive at low concentrations [
40,
41,
42]. “Majority” increases the likelihood of ecologically relevant concentrations, but it does not guarantee maximal biological activity. Thus, detailed, targeted studies of the ecological role of particular plant species in aquatic communities should also consider highly bioactive minor components of the LMWM.
Given the above, the aims of this work were (i) to identify the major components of the LMWM in widely distributed freshwater macrophytes (Myriophyllum spicatum L., Sparganium emersum Rehm., Sparganium gramineum Georgi, the hybrid Sparganium × foliosum A. A. Bobrov, Volkova, Mochalova et Chemeris, Persicaria amphibia (L.) Delarbre, Potamogeton perfoliatus L., Nuphar lutea (L.) Sibth. & Sm., Potamogeton pectinatus L., Potamogeton natans L., Lobelia dortmanna L., Ceratophyllum demersum L.); and (ii) to analyze their ecological and biochemical roles in aquatic ecosystems, with particular emphasis on potential allelopathic interactions of macrophytes with phytoplankton and periphyton (epiphytes). All of the listed species typically form well-developed plant associations in characteristic habitats and thus provide a representative model for discussing how major macrophyte metabolites may participate in the chemical regulation of community structure and productivity in shallow freshwater ecosystems.
3. Materials and Methods
3.1. Plant Material
In this study, we analyzed the major components of the LMWM of the following widely distributed freshwater macrophytes: Myriophyllum spicatum L., Sparganium emersum Rehm., Sparganium gramineum Georgi, the hybrid Sparganium × foliosum A. A. Bobrov, Volkova, Mochalova et Chemeris, Persicaria amphibia (L.) Delarbre, Potamogeton perfoliatus L., Nuphar lutea (L.) Sibth. & Sm., Potamogeton pectinatus L., Potamogeton natans L., Lobelia dortmanna L., and Ceratophyllum demersum L.
Macrophyte samples were collected from diverse habitats in several water bodies: lakes in the Novgorod, Moscow, Tver, and Yaroslavl regions (Russia) (S. emersum, S. gramineum, S. × foliosum, L. dortmanna); lakes of the Karelian Isthmus, Northwestern Russia (N. lutea, P. natans, M. spicatum); Lake Ladoga (P. perfoliatus, P. pectinatus, P. amphibia, M. spicatum); floodplain lakes of the Volga–Akhtuba floodplain (Astrakhan Region, Russian Federation) (P. pectinatus, C. demersum); and Lake Naroch (Belarus) (M. spicatum).
Plant material was collected at the peak of the growing season (late July–early August). In compliance with [
227], the harvested plants were thoroughly rinsed to remove epiphytes and other attached material. A sufficient number of shoots was collected so that the dry-weight equivalent (at least 50–100 g) was adequate to prepare an integral sample for gas chromatography–mass spectrometry (GC–MS), i.e., a composite sample comprising different shoots of the plant collected from the same habitat.
The plant material was air-dried to constant weight in a shaded, darkened area indoors or under a canopy, protected from direct sunlight, at temperatures not exceeding 35 °C. Such a traditional way of drying in the shade is regarded to be the most suited [
228,
229]. The dried samples were packed in dark bags and stored in the laboratory at room temperature under dry conditions, protected from sunlight. Subsequent GC–MS analysis of the samples was performed no earlier than one month and no later than one year after collection and drying, in accordance with regulatory guidelines for the storage of plant raw materials [
230].
Below, we provide a general ecological and biological characterization of the studied macrophyte species.
3.1.1. Myriophyllum spicatum L.
M. spicatum (Eurasian watermilfoil) is a perennial, fully submerged macrophyte of the family Haloragaceae, producing long stems (up to several meters) and whorled, finely dissected leaves; reproductive shoots form an emergent terminal spike, and the small flowers appear to be predominantly wind-pollinated. The species combines sexual reproduction (by seeds) with a pronounced capacity for vegetative spread: stem fragmentation and subsequent rooting of fragments are regarded as one of the key mechanisms enabling rapid expansion of stands, and its seasonal dynamics and “life strategy” (including overwintering and resumption of growth) have been described in detail for temperate-zone populations [
231,
232,
233,
234]. The native range of
M. spicatum is associated with Eurasia and North Africa; however, during the 20th century the species became widely dispersed and naturalized beyond its original range and is now recorded across the Northern Hemisphere—in Europe, Asia, North America, and North Africa; it has also been reported from eastern Africa (Somalia) and insular areas in the western Pacific (the Philippines) [
234]. For North America, its introduction history and spread across the United States and Canada were summarized in a classic paper [
235]. Ecologically, Eurasian watermilfoil is primarily associated with still and slow-flowing waters (lakes, ponds, reservoirs, and low-energy river reaches), can grow across a range of littoral depths (up to ~10 m where light is sufficient), shows broad tolerance to environmental conditions with respect to temperature, pH and salinity (including persistence in slightly brackish waters), and often performs well in water bodies experiencing anthropogenic impacts and elevated trophic status [
232,
236,
237].
3.1.2. Genus Sparganium L.
The genus
Sparganium (Typhaceae) comprises rhizomatous perennial aquatic macrophytes with pronounced phenotypic plasticity; the flowers are unisexual and arranged in globose heads, and the persistence and expansion of stands are ensured both by seed reproduction and by active clonal spread via creeping rhizomes [
238,
239,
240].
S. emersum is a widely distributed taxon across Eurasia and western North America, typically associated with shallow zones of lakes and with calm/slow-flowing sections of rivers and channels; shoot and leaf morphology varies along depth and hydrodynamic gradients [
238,
239,
241].
S. gramineum is more habitat-restricted: in European Russia it is described as a long-rhizomed polycarpic perennial occurring mainly in the littoral zone of mesotrophic (more rarely oligotrophic) waterbodies; in northern European softwater lakes it is listed among typical components of macrophyte communities associated with low mineral content and high water transparency [
242,
243]. The hybrid
S. × foliosum is regarded as the nothotaxon of the parental pair
S. emersum × S. gramineum, diagnosable by a suite of intermediate characters and occurring predominantly in areas where the parents co-occur [
44,
45].
3.1.3. Genus Potamogeton
Macrophytes of the genus
Potamogeton (Potamogetonaceae) are a cosmopolitan group of aquatic plants, predominantly submerged, rooted hydrophytes with creeping rhizomes, high morphological plasticity, frequent hybridization and polyploidy; the genus is characterized by spike-like inflorescences and diverse overwintering/vegetative renewal strategies (including specialized winter buds/turions), which together confer broad ecological amplitude and a major role in structuring shallow-water communities [
55,
244,
245,
246].
P. perfoliatus is a submerged, rooted macrophyte of the shallow littoral zone and an important component of lake/pond communities; this species often supports substantial epiphyton accumulation on its leaves, which can markedly alter plant photobiological traits [
65,
244,
247]. Consequently, careful cleaning of shoots is required when analyzing its LMWOCs. The native range of the species spans the temperate Northern Hemisphere and extends to Sumatera and eastern/southeastern Australia [
246].
P. pectinatus (in many modern treatments,
Stuckenia pectinata (L.) Börner) is a submerged, narrow-leaved “sago pondweed” that is nearly cosmopolitan [
246] and can tolerate elevated salinity and irradiance; these traits make it a characteristic species of fresh to slightly brackish, often eutrophic habitats [
248].
P. natans (floating-leaved pondweed) is a perennial hydrophyte bearing both floating and submerged leaves, typical of shallow zones of standing and slow-flowing fresh waters (occasionally slightly brackish); it is native to the temperate and subtropical regions of the Northern Hemisphere [
246,
249].
3.1.4. Persicaria amphibia (L.) Delarbre
P. amphibia (Polygonaceae; synonym
Polygonum amphibium L.) is a widely distributed amphibious perennial helophyte, native across subarctic and temperate parts of the Northern Hemisphere and also recorded from parts of Africa (Ethiopia–Kenya and South Africa) [
250,
251]. It is rhizomatous/stoloniferous and highly plastic, producing both an aquatic rooted floating-leaved morph and a terrestrial/emergent shoreline morph; the extent of habitat-driven variation is commonly treated as the “
P. amphibia complex” [
76,
252,
253]. Ecologically, the species is typical of shallow littoral zones of lakes and ponds, river/stream margins, and wet floodplain habitats, and it tolerates strong water-level fluctuations and drawdown, which explains its success in dynamic shoreline environments [
76,
250,
253].
3.1.5. Nuphar lutea (L.) Sm.
N. lutea is a perennial rooted macrophyte with floating leaves and a stout rhizome, widely distributed across the Palearctic [
254,
255]. The species is characterized by marked heterophylly (floating and submerged leaves), clonal growth forming patches/stands, and solitary yellow flowers at the water surface [
256]. It typically occurs at depths of 0.5–1 m in lakes as well as in ponds, reservoirs, backwaters, and slow-flowing rivers, and it is sensitive to water pollution [
254]. Ecologically,
N. lutea is typical of water bodies with soft bottom sediments, most often in shallow littoral zones. Its functional traits and production/biogeochemical parameters vary substantially among water bodies differing in trophic status and habitat conditions [
257,
258]. As a habitat-forming (structuring) species, the yellow water-lily often forms plant associations together with other aquatic macrophytes [
259].
3.1.6. Lobelia dortmanna L.
The species’ range includes Northern, Central, and Eastern Europe as well as North America. It is considered a relict species and is rare throughout its distribution. It grows in the littoral zone of freshwater waterbodies on clean sandy bottoms, typically at depths of about 60–80 cm. Plants occur singly or in small groups and rarely form extensive stands. The species is sensitive to water-level fluctuations. A major limiting factor is waterbody pollution; therefore,
L. dortmanna is regarded as an indicator of water purity [
260]. Ecologically, it is associated with softwater, low-mineralization oligotrophic to weakly mesotrophic lakes with a well-lit shallow zone and mineral (usually sandy), low-organic substrates, and it is sensitive to siltation and organic enrichment followed by sediment deoxygenation [
261,
262]. One of the species’ main physiological adaptations is active root uptake of CO
2 from sediment pore water to support photosynthesis, which is especially important in clear oligotrophic lakes [
82,
263].
3.1.7. Ceratophyllum demersum L.
C. demersum (Ceratophyllaceae) is a widely distributed (cosmopolitan) freshwater submerged macrophyte, either free-floating or loosely anchored to the substrate by thin rhizoid-like shoots arising from the stem base. The plant acquires nutrients directly from the water column [
254,
264]. It develops long, brittle stems and whorled leaves that are deeply dissected into narrow segments (often bearing small teeth/spines), which increases the exchange surface with the surrounding water and promotes efficient gas and ion exchange in the water column [
55,
265]. Ecologically, the species is most typical of still and slow-flowing freshwater habitats (lakes, ponds, canals, oxbow lakes and river backwaters). Plants often form large monospecific stands that may extend down to ~10 m depth under sufficient light. Growth of
C. demersum has been reported at depths where only about 1% of surface irradiance is available. Its high shade tolerance is consistent with a low light-compensation point and the capacity to remain functional beneath ice in temperate lakes. Stands of
C. demersum may have a strong competitive advantage over free-floating competitors, in part by elevating water pH during intense photosynthesis [
55,
254,
264,
266,
267].
3.2. Sample Extraction
Essential oils containing LMWOCs were obtained from dried plant material. A weighed portion of the sample was 10–15 g of dry plant material. Before distillation, the dried plant material was crushed into a powder using a Waring BB-25ES blender. The generally accepted Clevenger method (a method of steam hydrodistillation) was used for extracting LMWOCs from plant material samples by distilling the samples with water vapor for 6 h [
268,
269,
270,
271]. The resultant distillate was extracted with 5 mL hexane. The hexane extract for subsequent chromatography mass spectrometric analysis was kept in hermetically sealed vials in a freezer at -18 °C.
3.3. GC-MS Analysis
GC–MS was used to determine the qualitative and quantitative composition of LMWOCs. Analyses were performed using (i) a SHIMADZU GCMS-QP2010 Ultra GC–MS system equipped with an MTX-1 non-polar capillary column (30 m × 0.25 mm i.d., 0.25 μm film thickness) and (ii) a Thermo Scientific TRACE ISQ GC–MS system equipped with a TRACE TR-5MS capillary column (15 m × 0.25 mm i.d., 0.25 μm film thickness). Helium was used as the carrier gas. Mass spectra were acquired in full-scan mode over the m/z range 30–1090. The oven temperature program was as follows: 35 °C (3 min), ramp at 2 °C/min to 60 °C (hold 3 min), ramp at 2 °C/min to 80 °C (hold 3 min), ramp at 4 °C/min to 120 °C (hold 3 min), ramp at 5 °C/min to 150 °C (hold 3 min), and ramp at 15 °C/min to 240 °C (hold 10 min). Chromatograms were processed step-by-step after data acquisition. Compounds were identified using the NIST 2014 and Wiley mass spectral libraries [
272,
273]. For more accurate identification, linear retention indices were used [
274,
275], calculated using a C7–C30 n-alkane standard mixture. Quantification was performed using benzophenone as an internal standard.
Compound diversity was assessed by qualitative analysis, i.e., by compound identification. Identification reliability was evaluated using the library match factor (Match) and reverse match factor (R.Match); for the compounds reported in this study, these values were typically ≥800–900 (good agreement), and for many of the most abundant compounds (i.e., the major components emphasized in this work) they exceeded 900 (excellent agreement). Quantitative analysis was performed using benzophenone as an internal standard, enabling determination of the concentrations of the identified compounds.
Major components of LMWM were operationally defined as compounds contributing >1% of the total signal (based on peak area relative to the sum of peak areas of all detected LMWOCs). This threshold is commonly used in GC–MS profiling to distinguish dominant constituents from trace compounds and to improve comparability among samples [
36,
276,
277].
When compiling the final lists of LMWOCs for the studied species, including the relative content and concentrations of major components, we used the maximum observed values of relative content and concentration for each component recorded for each species. Thus, the resulting final lists reflect the highest possible level (i.e., the potential) of relative content and the highest possible level (i.e., the potential) of concentration of particular major components in the LMWM of a given macrophyte species. Quantitative comparisons among the studied macrophyte species were performed using these maximum LMWOCs values.
3.4. Similarity Assessment and Statistical Analyses
The similarity of the sets of major components in the studied macrophyte species with respect to the qualitative composition of LMWOCs was assessed using the Jaccard similarity coefficient (J) and the Sørensen–Czekanowski coefficient (Qs) [
278,
279,
280], calculated as:
where
c is the number of LMWOCs common to samples A and B;
a is the number of LMWOCs present in A;
b is the number of LMWOCs present in B.
Similarity estimates between samples based on quantitative data (i.e., the abundances of individual compounds) were obtained using the Morisita (Morisita–Horn) index [
281]:
where an
i is the abundance of the
i-th compound (or compound group) in sample A; bn
i is the same for sample B; (aN) is the total abundance of LMWOCs in sample A; (bN) is the same for sample B; da = ∑(an
i2)/aN
2 , db = ∑( bn
i2)/bN
2.
J and Qs describe overlap in the set of major compounds, whereas the Morisita–Horn index emphasizes dominant molecules and is therefore more sensitive to abundance structure. Moreover, the Morisita–Horn index does not depend on sample size and diversity and thus has a significant advantage [
84].
To estimate the mean content of different chemical groups of major LMWOCs in the LMWM of the studied species, arithmetic means and standard errors of the mean were calculated. The relative variability of the chemical group contents with respect to their mean values was assessed using the coefficient of variation (CV). For the interpretation of the coefficient of variation, a harmonized scale was applied: <10% — very low variability, 10–20% — low, 20–30% — moderate, 30–50% — high, and >50% — very high. The use of this scale was based on publications employing the Pimentel-Gomes classification, while the threshold of CV >50% was adopted from studies assessing climatic and hydrometeorological variability [
282,
283,
284]. Statistical analyses were performed using STATISTICA software, version 10 [
285].
4. Conclusions
The comparative analysis of the major fraction of the LMWM in 11 freshwater macrophyte species revealed pronounced interspecific differentiation while maintaining a shared functional “core” of LMWOCs. In total, 137 major LMWOCs were recorded (four remained unidentified), and their numbers differed markedly among species (from 11 to 71), indicating distinct ecological-biochemical strategies in organizing the principal LMWM pool that constitutes the most abundant and, likely, ecologically relevant component of chemical activity of a given macrophyte in aquatic ecosystems and its adaptation to specific environmental conditions.
Fatty acids represented the most universal dominant module in macrophytes. They were among the top three major components in all species and ranked first or second (or even all three) in 10 of 11 species. This supports the interpretation of the lipid module as a key hub linking (i) tissue structure and surface barrier fractions, (ii) stress signaling (oxylipin cascades), and (iii) potential allelopathic effects on phytoplankton, periphyton, and the microbiome.
The results of a comparison of the similarities/dissimilarities of the studied species based on their major LMWOCs are important. Species similarity depended on what was compared—compound “sets” or “dominance”. Similarity matrices demonstrated a fundamental divergence between similarity based on the presence/absence of compounds and similarity based on dominant molecules (Jaccard/Sørensen–Czekanowski vs. Morisita–Horn indices). Ecologically, this implies that different species may possess distinct lists of major metabolites while exhibiting a similar quantitative metabolomic architecture driven by shared dominant classes/compounds—i.e., the most plausible candidates to reach biologically meaningful concentrations. This, in turn, may enable the implementation of similar adaptive strategies in aquatic ecosystems and the capacity to modify the surrounding water environment in a favorable direction.
Overall, our study provides a basis and a comparable interspecific framework for interpreting the chemical regulation of aquatic communities in macrophyte-dominated habitats, focusing on the major fraction as the most likely driver of ecosystem-level effects, including those expressed in the microenvironment of the diffusive boundary layer. At the same time, we show that the “chemical profile” of a macrophyte should be considered not only as a list of compounds but also as a dominance structure, which may converge across ecologically and taxonomically different plants.
From a theoretical perspective, our findings refine current understanding of how macrophytes shape the chemical component of shallow-water ecosystem functioning and influence other aquatic organisms via dominant metabolic modules that are most likely to exert effects within the plant’s diffusive boundary layer and the water column. From a practical perspective, we compiled a set of priority compound classes and candidate species for targeted tests of anti-cyanobacterial/anti-fouling activity and for monitoring the functional state of macrophyte communities.
Several limitations should be acknowledged. First, our analysis focused on major components (>1% of the total LMWOCs pool), whereas minor metabolites may exhibit high bioactivity even at low concentrations; therefore, the biological significance of macrophyte metabolites is not fully captured by “majority” criteria alone. Second, interspecific comparisons were performed using the maximum observed values of each compound within the LMWM (as an estimate of species “potential”). This approach improves comparability in terms of upper boundaries but does not replace assessments of typical (mean/median) levels of LMWOCs in macrophytes and their actual fluxes to the environment. This should be the subject of future research. Our inferences regarding potential ecological functions of LMWOCs are based on chemical profiles and literature-driven interpretation and require direct verification using bioassays and field measurements of concentrations/gradients in the water and at plant surfaces.
Our results further highlight that the number of potentially relevant metabolites is large; hence, investigating ecological–biochemical functions of macrophyte LMWOCs requires a prioritization strategy when designing and conducting experimental studies. Even the number of major LMWOCs, as shown here, is substantial. To identify the principal regulatory mechanisms in aquatic ecosystems, it may be reasonable to focus primarily on major compounds. However, even in this case, the required research effort remains considerable. Importantly, such work should be embedded within an integrated research framework combining sequential laboratory studies, experiments with mesocosms in natural water bodies, and, subsequently, whole-ecosystem experiments. Only such an approach can resolve the real ecological roles of macrophyte LMWOCs and their place within the complex regulatory matrix of aquatic ecosystems. This workload may be partially reduced by QSAR studies [
101,
199], which can predict biological activities of LMWOCs without extensive “wet-lab” screening across large compound sets. Following QSAR-based identification of the most promising molecules, they can be examined in a more targeted manner, with reduced effort and resources, to confirm and characterize specific chemical–ecological functions.
Future research directions that appear particularly promising include: (i) moving from “within-organism” LMWOC profiles to measurements of the exometabolome and compound concentrations within the diffusive boundary layer at plant surfaces and in the water column; (ii) integrating endo- and exometabolomic chemical profiles with analyses of the microbiome/periphyton/phytoplankton and hydrodynamics (effects on transport and transformation); (iii) targeted bioassay-based experiments (especially at the whole-ecosystem level) for dominant classes, primarily fatty acids and other highly active allelochemicals; and (iv) assessing seasonal and interannual variability in macrophyte LMWOCs and shifting from “potential” (max) to “realized impact”.
Author Contributions
All authors have read and agreed to the published version of the manuscript. Conceptualization, E.A.K. and J.V.K.; Writing—review and editing, E.A.K. and J.V.K.; Methodology, E.A.K. and J.V.K.; Data collection, E.A.K, A.M.Ch., V.V.A., V.A.G., E.Ya.Y.; Research, E.A.K, J.V.K., A.M.Ch., Y.V.B., V.V.A., V.A.G., E.Ya.Y. Formal analysis, E.A.K., J.V.K., A.M.Ch., Y.V.B.; Data curation, E.A.K, J.V.K., Y.V.B.; Supervisor, E.A.K.
Table 1.
Groups of major LMWOCs of the LMWM of S. gramineum and number of major LMWOCs.
Table 1.
Groups of major LMWOCs of the LMWM of S. gramineum and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
5.15 |
1.31 |
0.44 |
5.38 |
0.60 |
0.19 |
1 |
0 |
0.40 |
| Aldehydes |
8.84 |
2.35 |
0.46 |
10.87 |
4.97 |
0.79 |
3 |
1 |
0.29 |
| Hydrocarbons |
39.75 |
3.78 |
0.16 |
46.46 |
11.09 |
0.41 |
5 |
1 |
0.37 |
| Fatty acids |
14.51 |
5.82 |
0.69 |
14.19 |
4.09 |
0.50 |
2 |
1 |
0.67 |
| Sulfur-containing |
4.83 |
2.61 |
0.93 |
6.77 |
4.40 |
1.12 |
1 |
0 |
0.67 |
| TOTAL/N=20 |
73.08 |
1.18 |
0.03 |
83.67 |
17.06 |
0.35 |
13 |
1 |
0.15 |
Table 2.
Groups of major LMWOCs of the LMWM of S. emersum and number of major LMWOCs.
Table 2.
Groups of major LMWOCs of the LMWM of S. emersum and number of major LMWOCs.
| Compounds |
% |
C |
n |
| |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
13.02 |
0.05 |
0.004 |
14.20 |
1.36 |
0.10 |
1 |
0 |
0.00 |
| Aldehydes |
2.68 |
0.19 |
0.071 |
2.93 |
0.50 |
0.17 |
2 |
0 |
0.00 |
| Hydrocarbons |
48.10 |
9.92 |
0.206 |
53.03 |
16.03 |
0.30 |
6 |
1 |
0.13 |
| Fatty acids |
11.70 |
8.80 |
0.752 |
12.30 |
8.33 |
0.68 |
1 |
0 |
0.00 |
| Ketones |
1.97 |
0.91 |
0.463 |
2.10 |
0.78 |
0.37 |
1 |
0 |
0.00 |
| TOTAL/N=13 |
77.47 |
0.36 |
0.005 |
84.56 |
8.77 |
0.10 |
11 |
1 |
0.07 |
Table 3.
Groups of major LMWOCs of the LMWM of S. x foliosum and number of major LMWOCs.
Table 3.
Groups of major LMWOCs of the LMWM of S. x foliosum and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
9.17 |
1.24 |
0.30 |
12.70 |
1.91 |
0.34 |
1 |
0 |
0.61 |
| Aldehydes |
5.19 |
1.24 |
0.53 |
6.68 |
0.91 |
0.31 |
2 |
0 |
0.19 |
| Hydrocarbons |
49.83 |
3.92 |
0.18 |
71.85 |
10.92 |
0.34 |
6 |
1 |
0.21 |
| Fatty acids |
7.67 |
2.78 |
0.81 |
10.68 |
3.62 |
0.76 |
1 |
0 |
0.35 |
| Sulfur-containing |
0.89 |
0.69 |
1.73 |
1.17 |
0.99 |
1.89 |
1 |
0 |
1.67 |
| Ketones |
0.79 |
0.41 |
1.15 |
0.93 |
0.46 |
1.10 |
1 |
0 |
1.10 |
| TOTAL /N=25 |
73.53 |
1.96 |
0.06 |
104.00 |
10.85 |
0.23 |
11 |
1 |
0.15 |
Table 4.
Groups of major LMWOCs of the LMWM of P. pectinatus and number of major LMWOCs.
Table 4.
Groups of major LMWOCs of the LMWM of P. pectinatus and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
15.16 |
0.67 |
0.06 |
19.56 |
8.23 |
0.59 |
4 |
0 |
0.00 |
| Aldehydes |
5.45 |
4.02 |
1.04 |
6.70 |
4.11 |
0.87 |
2 |
1 |
0.89 |
| Hydrocarbons |
9.13 |
3.58 |
0.56 |
9.92 |
2.21 |
0.32 |
3 |
1 |
0.33 |
| Fatty acids |
26.16 |
10.74 |
0.58 |
34.02 |
17.58 |
0.73 |
3 |
0 |
0.22 |
| Esters |
2.98 |
1.00 |
0.48 |
3.30 |
0.63 |
0.27 |
1 |
0 |
0.43 |
| Ketones |
12.31 |
1.89 |
0.22 |
14.97 |
4.53 |
0.43 |
5 |
0 |
0.00 |
| Diverse functional groups |
3.62 |
4.43 |
1.73 |
7.35 |
9.00 |
1.73 |
1 |
1 |
1.73 |
| Phenols |
1.56 |
1.91 |
1.73 |
1.37 |
1.68 |
1.73 |
0 |
0 |
1.73 |
| TOTAL /N=36 |
76.37 |
6.71 |
0.12 |
97.20 |
38.43 |
0.56 |
20 |
2 |
0.12 |
Table 5.
Groups of major LMWOCs of the LMWM of P. natans and number of major LMWOCs.
Table 5.
Groups of major LMWOCs of the LMWM of P. natans and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
23.25 |
6.16 |
0.37 |
124.71 |
13.84 |
0.16 |
4 |
0 |
0.13 |
| Aldehydes |
1.60 |
0.45 |
0.39 |
8.73 |
1.56 |
0.25 |
1 |
0 |
0.00 |
| Hydrocarbons |
1.69 |
1.04 |
0.87 |
12.00 |
9.28 |
1.09 |
1 |
1 |
0.87 |
| Fatty acids |
10.77 |
6.13 |
0.81 |
88.21 |
79.19 |
1.27 |
2 |
1 |
0.50 |
| Esters |
25.50 |
4.64 |
0.26 |
159.23 |
67.05 |
0.60 |
5 |
1 |
0.20 |
| unidentified |
0.47 |
0.57 |
1.73 |
4.96 |
6.07 |
1.73 |
0 |
0 |
1.73 |
| Ketones |
0.49 |
0.61 |
1.73 |
5.26 |
6.45 |
1.73 |
0 |
0 |
1.73 |
| Diverse functional groups |
18.73 |
3.53 |
0.27 |
106.94 |
26.04 |
0.34 |
5 |
1 |
0.29 |
| TOTAL /N=31 |
82.51 |
2.65 |
0.05 |
510.05 |
202.36 |
0.56 |
20 |
1 |
0.11 |
Table 6.
Groups of major LMWOCs of the LMWM of P. perfoliatus and number of major LMWOCs.
Table 6.
Groups of major LMWOCs of the LMWM of P. perfoliatus and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Aromatic Hydrocarbons |
0.19 |
0.20 |
2.45 |
0.22 |
0.24 |
2.45 |
0 |
0 |
2.45 |
| Alcohols |
18.51 |
2.81 |
0.34 |
21.59 |
12.73 |
1.32 |
5 |
0 |
0.22 |
| Aldehydes |
11.59 |
3.90 |
0.75 |
5.48 |
0.66 |
0.27 |
4 |
1 |
0.52 |
| Hydrocarbons |
13.45 |
2.81 |
0.47 |
13.24 |
5.89 |
0.99 |
6 |
1 |
0.34 |
| Fatty acids |
15.69 |
5.88 |
0.84 |
20.73 |
10.85 |
1.17 |
3 |
1 |
0.59 |
| Esters |
1.04 |
0.73 |
1.56 |
0.27 |
0.19 |
1.56 |
1 |
0 |
1.67 |
| Ketones |
12.73 |
3.73 |
0.66 |
11.85 |
7.07 |
1.33 |
4 |
1 |
0.61 |
| Diverse functional groups |
6.59 |
2.67 |
0.91 |
5.05 |
2.86 |
1.27 |
3 |
1 |
0.66 |
| Phenols |
0.33 |
0.36 |
2.45 |
0.07 |
0.08 |
2.45 |
0 |
0 |
2.45 |
| TOTAL /N=71 |
80.11 |
3.31 |
0.09 |
78.50 |
36.65 |
1.04 |
26 |
2 |
0.19 |
Table 7.
Groups of major LMWOCs of the LMWM of M. spicatum and number of major LMWOCs.
Table 7.
Groups of major LMWOCs of the LMWM of M. spicatum and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
12.64 |
5.17 |
0.58 |
33.65 |
7.62 |
0.32 |
2 |
0 |
0.38 |
| Aldehydes |
4.22 |
2.61 |
0.87 |
9.19 |
5.67 |
0.87 |
1 |
1 |
1.20 |
| Hydrocarbons |
23.60 |
4.24 |
0.25 |
86.85 |
46.21 |
0.75 |
5 |
0 |
0.16 |
| Fatty acids |
31.55 |
12.02 |
0.54 |
133.08 |
105.26 |
1.12 |
6 |
0 |
0.10 |
| Esters |
3.97 |
1.11 |
0.40 |
12.89 |
5.30 |
0.58 |
1 |
0 |
0.40 |
| unidentified |
0.44 |
0.53 |
1.73 |
1.11 |
1.36 |
1.73 |
0 |
0 |
2.00 |
| Ketones |
5.60 |
2.82 |
0.71 |
13.64 |
3.66 |
0.38 |
2 |
1 |
0.58 |
| TOTAL /N=25 |
82.01 |
2.48 |
0.04 |
290.41 |
141.10 |
0.69 |
17 |
2 |
0.23 |
Table 8.
Groups of major LMWOCs of the LMWM of P. amphibia and number of major LMWOCs.
Table 8.
Groups of major LMWOCs of the LMWM of P. amphibia and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Aromatic Hydrocarbons |
0.33 |
0.41 |
1.73 |
0.43 |
0.52 |
1.73 |
0 |
0 |
1.73 |
| Alcohols |
2.83 |
0.81 |
0.40 |
2.57 |
0.57 |
0.31 |
1 |
0 |
0.00 |
| Aldehydes |
6.15 |
0.71 |
0.16 |
6.11 |
1.91 |
0.44 |
2 |
0 |
0.00 |
| Hydrocarbons |
3.73 |
1.63 |
0.62 |
3.39 |
1.92 |
0.80 |
2 |
1 |
0.49 |
| Fatty acids |
52.74 |
3.64 |
0.10 |
56.36 |
21.93 |
0.55 |
6 |
1 |
0.20 |
| Esters |
0.34 |
0.42 |
1.73 |
0.14 |
0.17 |
1.73 |
0 |
0 |
1.73 |
| unidentified |
0.39 |
0.47 |
1.73 |
0.49 |
0.60 |
1.73 |
0 |
0 |
1.73 |
| Sulfur-containing |
1.11 |
0.74 |
0.95 |
1.20 |
1.17 |
1.38 |
1 |
0 |
0.87 |
| Ketones |
5.09 |
2.35 |
0.65 |
6.25 |
4.36 |
0.99 |
2 |
1 |
0.65 |
| TOTAL /N=21 |
72.71 |
2.78 |
0.05 |
76.93 |
29.06 |
0.53 |
15 |
1 |
0.07 |
Table 9.
Groups of major LMWOCs of the LMWM of Nuphar lutea and number of major LMWOCs.
Table 9.
Groups of major LMWOCs of the LMWM of Nuphar lutea and number of major LMWOCs.
| Compounds |
% |
C |
n |
| Mean |
SEM |
CV |
Mean |
SEM |
CV |
Mean |
SEM |
CV |
| Alcohols |
3.99 |
2.89 |
0.72 |
239.97 |
294.63 |
1.23 |
1 |
0 |
0.00 |
| Aldehydes |
0.50 |
0.71 |
1.41 |
37.14 |
52.52 |
1.41 |
1 |
1 |
1.41 |
| Hydrocarbons |
2.46 |
3.48 |
1.41 |
182.42 |
257.98 |
1.41 |
1 |
1 |
1.41 |
| Fatty acids |
78.67 |
8.28 |
0.11 |
3388.91 |
2850.72 |
0.84 |
5 |
0 |
0.00 |
| Esters |
1.69 |
0.57 |
0.34 |
64.93 |
43.72 |
0.67 |
2 |
1 |
0.47 |
| TOTAL /N=11 |
87.32 |
1.77 |
0.02 |
3913.37 |
3499.58 |
0.89 |
9 |
1 |
0.16 |
Table 10.
Groups of major LMWOCs of the LMWM of C. demersum and L. dortmanna, and number of major LMWOCs.
Table 10.
Groups of major LMWOCs of the LMWM of C. demersum and L. dortmanna, and number of major LMWOCs.
| |
C. demersum |
L. dortmanna |
| % |
C |
n |
% |
C |
n |
| Alcohols |
5.93 |
3.32 |
3 |
1.34 |
2.66 |
1 |
| Aldehydes |
16.09 |
8.99 |
6 |
1.12 |
2.23 |
1 |
| Hydrocarbons |
6.98 |
3.90 |
4 |
23.96 |
47.63 |
5 |
| Fatty acids |
14.62 |
8.17 |
4 |
47.39 |
94.19 |
5 |
| Esters |
7.57 |
4.23 |
2 |
– |
– |
– |
| Ketones |
19.78 |
11.06 |
7 |
4.75 |
9.45 |
1 |
| TOTAL |
70.97 |
39.67 |
26 |
78.57 |
156.16 |
13 |
Table 11.
Similarity matrix of major components based on presence/absence data: J — Jaccard similarity coefficient (lower left triangle); Qs — Sørensen–Czekanowski coefficient (upper right triangle).
Table 11.
Similarity matrix of major components based on presence/absence data: J — Jaccard similarity coefficient (lower left triangle); Qs — Sørensen–Czekanowski coefficient (upper right triangle).
|
J/Qs
|
M.s.
|
S. f. |
P.a. |
P.per. |
N.l. |
S.g. |
S.e. |
P.pec. |
P.n. |
L.d. |
C.d. |
| M.s. |
|
0.44 |
0.52 |
0.35 |
0.61 |
0.44 |
0.53 |
0.30 |
0.32 |
0.42 |
0.44 |
| S. f. |
0.28 |
|
0.30 |
0.19 |
0.39 |
0.67 |
0.68 |
0.23 |
0.29 |
0.32 |
0.32 |
| P.a. |
0.35 |
0.18 |
|
0.35 |
0.56 |
0.29 |
0.35 |
0.39 |
0.27 |
0.41 |
0.43 |
| P.per. |
0.22 |
0.10 |
0.21 |
|
0.24 |
0.20 |
0.21 |
0.45 |
0.25 |
0.17 |
0.40 |
| N.l. |
0.44 |
0.24 |
0.39 |
0.14 |
|
0.45 |
0.50 |
0.26 |
0.33 |
0.58 |
0.44 |
| S.g. |
0.29 |
0.50 |
0.17 |
0.11 |
0.29 |
|
0.73 |
0.18 |
0.31 |
0.36 |
0.31 |
| S.e. |
0.36 |
0.52 |
0.21 |
0.12 |
0.33 |
0.57 |
|
0.25 |
0.36 |
0.38 |
0.37 |
| P.pec. |
0.18 |
0.13 |
0.24 |
0.29 |
0.15 |
0.10 |
0.14 |
|
0.27 |
0.21 |
0.43 |
| P.n. |
0.19 |
0.17 |
0.16 |
0.15 |
0.20 |
0.19 |
0.22 |
0.16 |
|
0.27 |
0.32 |
| L.d. |
0.27 |
0.19 |
0.26 |
0.09 |
0.41 |
0.22 |
0.24 |
0.12 |
0.16 |
|
0.26 |
| C.d. |
0.28 |
0.19 |
0.28 |
0.25 |
0.29 |
0.18 |
0.23 |
0.28 |
0.19 |
0.15 |
|
Table 12.
Similarity matrix based on concentration data of major components (Morisita–Horn index, Cmh).
Table 12.
Similarity matrix based on concentration data of major components (Morisita–Horn index, Cmh).
| Cmh |
M.s. |
S. f. |
P.a. |
P.per. |
N.l. |
S.g. |
S.e. |
P.pec. |
P.n. |
L.d. |
C.d. |
| M.s. |
|
0.54 |
0.48 |
0.45 |
0.69 |
0.47 |
0.58 |
0.38 |
0.36 |
0.48 |
0.37 |
| S. f. |
0.54 |
|
0.24 |
0.28 |
0.22 |
0.91 |
0.96 |
0.24 |
0.22 |
0.47 |
0.15 |
| P.a. |
0.48 |
0.24 |
|
0.43 |
0.81 |
0.29 |
0.37 |
0.64 |
0.59 |
0.90 |
0.48 |
| P.per. |
0.45 |
0.28 |
0.43 |
|
0.41 |
0.27 |
0.34 |
0.51 |
0.53 |
0.39 |
0.46 |
| N.l. |
0.69 |
0.22 |
0.81 |
0.41 |
|
0.26 |
0.33 |
0.43 |
0.49 |
0.76 |
0.41 |
| S.g. |
0.47 |
0.91 |
0.29 |
0.27 |
0.26 |
|
0.86 |
0.23 |
0.25 |
0.53 |
0.15 |
| S.e. |
0.58 |
0.96 |
0.37 |
0.34 |
0.33 |
0.86 |
|
0.31 |
0.31 |
0.56 |
0.20 |
| P.pec. |
0.38 |
0.24 |
0.64 |
0.51 |
0.43 |
0.23 |
0.31 |
|
0.54 |
0.53 |
0.58 |
| P.n. |
0.36 |
0.22 |
0.59 |
0.53 |
0.49 |
0.25 |
0.31 |
0.54 |
|
0.55 |
0.43 |
| L.d. |
0.48 |
0.47 |
0.90 |
0.39 |
0.76 |
0.53 |
0.56 |
0.53 |
0.55 |
|
0.37 |
| C.d. |
0.37 |
0.15 |
0.48 |
0.46 |
0.41 |
0.15 |
0.20 |
0.58 |
0.43 |
0.37 |
|
Table 13.
Top-3 most abundant major LMWOCs by relative contribution (%), with Cmax values (μg·g−1 DW).
Table 13.
Top-3 most abundant major LMWOCs by relative contribution (%), with Cmax values (μg·g−1 DW).
| Species |
Top1 |
Top2 |
Top3 |
| Myriophyllum spicatum |
Linoleic acid 17.00% (102.45) |
Phytol 16.39% (41.75) |
Tricosane 13.47% (61.14) |
| Sparganium × foliosum |
Pentacosane 39.35% (65.39) |
Heptacosane 17.39% (27.49) |
Palmitic acid 11.03% (16.82) |
| Sparganium gramineum |
Pentacosane 31.42% (51.25) |
Palmitic acid 17.17% (17.60) |
Octadecyl propan-2-yl sulfite 10.37% (17.34) |
| Sparganium emersum |
Pentacosane 28.66% (33.47) |
Palmitic acid 15.05% (15.27) |
Tricosane 13.73% (13.94) |
| Persicaria amphibia |
Palmitic acid 42.53% (54.45) |
α-Linolenic acid 10.43% (8.09) |
Myristic acid 8.33% (12.25) |
| Potamogeton perfoliatus |
α-Linolenic acid 18.41% (21.79) |
Manool 16.44% (44.18) |
Palmitic acid 13.55% (32.14) |
| Potamogeton pectinatus |
Palmitic acid 23.92% (30.88) |
Myristic acid 14.55% (22.37) |
6,10,14-Trimethylpentadecan-2-one 9.09% (8.55) |
| Potamogeton natans |
Manool 19.61% (74.72) |
Palmitic acid 16.57% (176.50) |
Methyl athecate 11.21% (90.48) |
| Nuphar lutea |
α-Linolenic acid 31.31% (807.98) |
Palmitic acid 29.06% (2156.62) |
Linoleic acid 25.03% (1857.81) |
| Lobelia dortmanna |
Palmitic acid 34.40% (68.38) |
Pentacosane 11.92% (23.69) |
Cyclohexadec-8-en-1-one 4.75% (9.45) |
| Ceratophyllum demersum |
Palmitic acid 7.86% (4.39) |
β-Ionone 6.74% (3.77) |
Methyl octadecanoate 6.28% (3.51) |
Table 14.
Maximum relative contributions of the key major n-alkanes in the studied macrophyte species.
Table 14.
Maximum relative contributions of the key major n-alkanes in the studied macrophyte species.
| Species |
Tricosane (C23) |
Pentacosane (C25) |
Heptacosane (C27) |
| Sparganium × foliosum |
10.84 |
39.35 |
17.39 |
| Sparganium emersum |
13.73 |
28.66 |
10.95 |
| Sparganium gramineum |
4.24 |
31.42 |
7.56 |
| Myriophyllum spicatum |
13.47 |
13.44 |
2.79 |
| Potamogeton perfoliatus |
10.79 |
8.73 |
2.16 |
| Lobelia dortmanna |
1.39 |
11.92 |
– |
| Potamogeton pectinatus |
7.83 |
2.26 |
– |
| Potamogeton natans |
1.11 |
1.33 |
– |
| Persicaria amphibia |
2.22 |
– |
– |
| Nuphar lutea |
2.59 |
– |
– |
| Ceratophyllum demersum |
1.04 |
– |
– |