Ecology and Genetics of Cyperus fuscus in Central Europe—A Model for Ephemeral Wetland Plant Research and Conservation

Abstract

The ecology and species diversity of ephemeral wetland vegetation have been fairly well studied, but the biology of its characteristic species has rarely been investigated holistically. Here we combine previous results on the genetic diversity of a suitable model species (the diploid Cyperus fuscus) with new data on its historical and recent occurrence, its ecological and climatic niche, and the associated vegetation. Analysis of phytosociological relevés from Central Europe revealed a broad ecological niche of C. fuscus with an optimum in the Isoëto-Nanojuncetea class, extending to several other vegetation types. Overall species composition in the relevés highlight C. fuscus as a potential indicator of habitat conditions suitable for a range of other threatened taxa. Analysis of historical records of C. fuscus from the Czech Republic showed an increasing trend in the number of localities since the 1990s. It seems that recent climate warming allows the thermophilous C. fuscus to expand its range into colder regions. Isoëto-Nanojuncetea and Bidentetea species are well represented in the soil seed bank in both riverine and anthropogenic habitats of C. fuscus. Vegetation diversity has a weak negative effect and anthropogenic (compared to riverine) habitats have a strong negative effect on genetic diversity in this species.

1. Introduction

Wetlands and their biota currently suffer under multiple threats including global eutrophication, climate change, direct habitat destruction, and land use change [1,2,3,4]. Frequent episodes of droughts, typical of the last two decades, may lead not only to release of nutrients from drying subhydric soils and increase of trophy levels but also to severe water level fluctuations and/or substrate desiccation, and, consecutively, to damage of populations of some plant and animal species with high moisture demands [5,6,7]. Ephemeral wetland plant species, sometimes called mudflat plants and usually classified within the syntaxonomic class Isoëto-Nanojuncetea [8], are a group of organisms with population frequency and/or density strongly fluctuating according to the conditions of the given growing season, particularly temperature and precipitation [9]. On the one hand, mudflat plants possessing persistent soil seed banks may easily balance the loss of a part of their populations in the years with unfavorable conditions. On the other hand, any slight but permanent shift in, e.g., the course of temperatures and precipitations, particularly during such a sensitive development phase like seed germination and/or seedling recruitment, may quickly lead to soil seed bank depletion and a species’ disappearance [9,10]. Many mudflat species are listed in national Red Data Lists and are considered as threatened and worth protecting, some of them even on a continental scale [11,12]. As it is not realistic to study all of these species in detail in a short period of time, we decided to select a model that could be used to explain processes in vegetation and soil seed banks, including genetic aspects, in ecologically similar species. The methodology we adapted to Cyperus fuscus could be used as a standardized protocol in studies of other short-lived wetland species.

Although Cyperus fuscus is rather widespread in some parts of Europe [13], it is considered as rare and threatened in some countries (critically endangered—Denmark [14]; vulnerable—Austria [15], Great Britain [16], Switzerland [17]; threatened and declining—Germany [18], near threatened—Czech Republic [19], Belgium [20], Estonia [21]; extremely rare—Luxembourg [22]). However, our recent investigations suggest that the species might, at least in some regions, profit from global environmental changes, particularly climate change [23]. Frequent availability of suitable exposed muddy bottoms because of summer drought may support more frequent occurrence of the species on already known sites. As high temperatures enhance faster growth and reproduction of this thermophilous species [24], higher soil seed bank and population density of C. fuscus can be expected. For most plant species, the higher their frequency and the propagule pressure in the environment, the higher the probability of their dispersal within the landscape and vice versa [25,26]. Hence, also for C. fuscus we could expect higher probability of its further spread to not yet colonized sites. Therefore, we decided to test the hypothesis that C. fuscus is recently (last ~20 years) spreading in central Europe, compared to the situation in the 20th century, particularly in its first half. Independent of the validity of this hypothesis, habitat preferences of the species could also change, particularly the vegetation types in which the species usually occurs. A similar trend has been observed e.g., in Crassula (Tillaea) aquatica, another ecologically specialized wetland annual herb [10]. We suggest that the vegetation types with recent occurrence of C. fuscus include a higher amount of alien species and ruderals than the analogical plant communities documented in the past.

Böckelmann et al. [27,28] studied phenotypic and genotypic characteristics of populations of Cyperus fuscus in Central Europe. Three habitat types with various intensities of anthropogenic influence inhabited by C. fuscus were in the focus of the studies: the near-natural riverbanks, the fishponds with intermediate levels of human impact, and the fish storage ponds with a strongly anthropogenic disturbance regime. The phenotypes and the genetic structure in the soil seed bank of C. fuscus were also investigated. No phenotypic and only weak genotypic differentiation (in the same order of magnitude as between spatially separated sampling plots within one and the same above-ground population) was found between the soil seed bank and the above-ground population [27,28]. This was equally true for the three habitat types: rivers, fishponds, and fish storage ponds. On the level of the species composition of the plant community, the highly dynamic habitats are usually colonized by annuals, which are also present in the soil seed bank; the perennial vegetation on the more stable sites, which are not deeply flooded, however, differs more from its soil seed bank, which consists of annuals of earlier successional stages [29,30]. We used the similarity in species composition between the soil seed bank and the above-ground vegetation as an indicator of site dynamics in the three habitat types studied [31]. To explain any differences in species composition, we investigated which phytosociological species groups were missing from the soil seed bank or vegetation.

Two different chromosome numbers were so far reported for Cyperus fuscus in the Central European region. Plants with 2n = 36 chromosomes have been reported from the Czech Republic (fishpond Řemínek in the district Náchod in East Bohemia) [32]; plants with 2n = 72 chromosomes have been reported from Slovakia (gravel pit near Lakšárska Nová Ves in the district Senica in West Slovakia) [33]. Further reports are spread randomly across Europe and the Mediterranean. Plants with 2n = 36 chromosomes have been reported from England (Breamore, South Hampshire) [34] and Israel (Hadera river, Sharon plain) [35]; plants of unknown origin cultivated at the Botanical Garden in Uppsala, Sweden, had 2n = 72 chromosomes [36]. As reported for other plant species, ploidy level variation might be related to the geographical origin of populations [37]. Cytotypes may also be differentiated ecologically and higher polyploids may be associated with habitats strongly influenced by anthropogenic activities [38,39]. To assess the distribution and habitat preference of the two cytotypes, we analyzed the genome size and chromosome number in a larger number of populations in Central Europe.

We were also interested whether there is an effect of plant community (vegetation) diversity on within-population genetic diversity. It is suggested that parallel processes, as caused by, for instance, size, area, land-use history, or isolation, on the two levels of diversity may result in a positive relationship between them [40,41]. Böckelmann et al. [28] found significantly reduced values of within-population genetic diversity in anthropogenic habitats (fishponds and fish storage ponds) compared to river habitats. We investigated whether the habitat type has same-directional effects on the two levels of diversity and thus establishes a positive relationship between them. For example, founder effects when anthropogenic habitats were created, restricted connections between anthropogenic and river habitats and/or the selection regime could reduce both levels of diversity. However, plant community diversity may also have a direct effect on within-population genetic diversity, which may vary for species with poor versus good competitive abilities (or rare versus common species [40]). Overall, we aimed to integrate the different levels of information to gain a better understanding of the functioning and current status of ephemeral wetland plants.

2. Materials and Methods

2.1. Sampling of Plant Material and Vegetation Data in the Field, Cultivation of Seeds from Soil

The localities with Cyperus fuscus belonging to the three habitat types (rivers: R1−R11; fishponds: F1−F10; fish storage ponds: S1−S10) are the same as those used for phenotypic and genetic analyses [27,28]. In addition, a fish rearing pond (RP) and an old quarry (Q) were also included for cultivation of seeds from the soil (Table S1). Large populations of C. fuscus were found on all these sites and therefore we selected them for complex study, including the soil seed bank and genetic analyses. Soil samples were taken from 1 m² plots from each of these sites in summer 2012 in the depth of up to 15 cm; the soil surface with seeds matured in 2012 was scraped before the sampling. After six months of storage at 6 °C in the dark, the soil samples were spread out as a 5 mm thin layer on sterile sand (seedling emergence method). The temperature in the glasshouse was set to 28 °C to stimulate the germination of C. fuscus, and the trays were watered daily until August 2013. All species emerging from the soil samples were recorded and C. fuscus plants germinated from the soil seed bank were collected for the phenotypic and genetic analysis [27,28]. Phytosociological relevés were collected using the method of the Zurich-Montpellier school prior to the soil sampling on the same 1 m² plots from which the soil samples were taken. Additionally, on four plots the relevés were collected, but these plots were not included in the soil seed bank and genetic analyses (Table S1). For the evaluation of cover of individual species, the nine-grade modified Braun-Blanquet scale [42] was used.

2.2. Vegetation Data Processing and Analyses

2.2.1. Data Sources

Altogether three basic sources of vegetation data have been used: (1) Our own relevés from plots for complex investigation of Cyperus fuscus (genetics, soil seed bank, vegetation; see Section 2.1). In total, 37 sites in AT, CZ, PL, and SK were sampled (31 of them also served for sampling of plant material for genetic analyses and 32 of them were analyzed for their soil seed bank), with 3 relevés for each of them, i.e., 111 relevés in total (July–October 2012; Table S1); (2) Additional relevés collected by K.G.B., K.B., K.Š., K.T., or P.K. between 2000 and 2019 in AT, CZ, or SK; 37 relevés in total, usually a single relevé per site; (3) Data with the occurrence of C. fuscus from the national phytosociological databases [43] of Austria (Austrian Vegetation Database—AVD [44]; 50 relevés), the Czech Republic (Czech National Vegetation Database—CNPD [45]; 516 relevés), Poland (Polish Vegetation Database —PVD [46]; 337 relevés), and Slovakia (Slovak Vegetation Database, also called Central Database of Phytosociological Samples—CDF [47]; 147 relevés), and from the Gravel Bar Vegetation Database (GBVD [48]; 11 relevés). The initial number of relevés from all sources was 1206.

2.2.2. Compilation of the Vegetation Dataset

All the vegetation data were stored using Turboveg 2.0 database software [49], at the beginning as separated databases, and checked for possible inconsistencies. To concentrate our attention on the vegetation types, where Cyperus fuscus finds its optimum, we removed all relevés where the species occurred with less than 1% cover. These were mainly the mosaics of wet and mesic meadows, forests with small patches of springs, and other more or less terrestrial habitats. Further, we removed all relevés with too small or too large plot sizes. As the plot sizes were very diverse, it was difficult to comply with the rules suggested by Chytrý & Otýpková [50], without substantial loss of the data. Therefore, we accepted relevés with plot sizes between 0.5 to 50 m², as the lower and upper extreme values were still sufficiently frequent, occupying more than 5% of the relevés in some of the national datasets. In the next step, we removed all relevés without sufficiently precise localization, i.e., without coordinates and/or the nearest settlement name, and the relevés from other countries than AT, CZ, PL, and SK. To reduce oversampling of some sites, we randomly selected 3 relevés as maximum for one site defined by coordinates and/or verbal description. Using these selection principles, additional relevés were accepted if they documented different vegetation type(s) of an alliance or higher syntaxonomic rank or if they were related to another period of time, with a minimum interval of 5 years between the samplings (this interval is based on our personal observation of speed of changes in wetland habitats, which may enhance the spread of C. fuscus).

The final Turboveg database included altogether 925 relevés, of which 37 (4%) came from Austria (32 from AVD and the rest from the other databases), 555 (60%) from the Czech Republic (446 from CNPD and the rest from the other databases), 227 (24.5%) from Poland (218 from PVD and the rest from the other databases), and 106 (11.5%) from Slovakia (96 from the CDF and the rest from the other databases). Detailed information about the structure of original databases, as well as the relevés used after the selection procedure, including the most important authors represented in the final dataset, are available in the Appendix A.

The final database in Turboveg was unified under the species list of Czechia_Slovakia_2015 (https://www.sci.muni.cz/botany/juice/KUBAT2015.txt, accessed on 10 December 2020). For further processing and analyses, the data were imported into JUICE software, version 7.0.45 [51]. After importing into the JUICE software, we unified the layers for certain species as follows: for all herbal species and charophytes, including their juveniles, the herb layer was selected. All tree and shrub species were included into the juvenile layer and all bryophytes and algae (except for charophytes) into the moss layer. To simplify the dataset, in the next step we merged some of the taxa into a single species, aggregate, or other higher taxon; for their list see Table S2. However, in the case that the relative or morphologically similar species are ecologically distinct, having an important indicator potential, we made efforts to keep the taxonomic treatment as detailed as possible. During the merging of taxa, we also corrected some highly probable identification errors (see the comments in Table S2). Finally, we unified the nomenclature of taxa according to the Euro+Med PlantBase [52], as this online source reflects the most recent taxonomic treatment. This nomenclature is used throughout the whole paper.

2.2.3. Vegetation Classification and Ordinations

For classification of the final vegetation dataset, we used an automatic expert system (ESY) designed for vegetation classification of large data packages and working under JUICE software. From the expert systems available, we selected the expert system recently developed for Poland [53], which, in contrast to, e.g., ESY for the Czech Republic [54], also includes some additional wetland vegetation types relevant for our study and missing in the Czech Republic. Two rounds of the classification procedure were applied: up to class level for basic orientation in the vegetation types and up to association level for the class represented by the highest amount of the relevés. The first classification round should give us a basic overview of vegetation patterns in the communities with Cyperus fuscus, while the second round was applied to describe the vegetation optimal for the occurrence of the target species in more detail. Syntaxonomic nomenclature of the classes and alliances corresponds to Mucina et al. [8]; the nomenclature of the associations is based on Kącki et al. [53].

As we wanted to determine what factors influence the vegetation composition of the communities with Cyperus fuscus, a canonical correspondence analysis (CCA) was performed. Weighted mean Ellenberg indicator values (EIVs, see Ellenberg et al. [55], i.e., the ordinal estimation scales for moisture, soil reaction, light, nutrients, continentality, temperature) calculated in the JUICE software for each of the relevés, number and cover of archaeophytes and neophytes, cover of C. fuscus, and sampling year were used as the explanatory variables. The cover of C. fuscus was excluded from the EIV calculations and from the response variables in the ordination. The significance of the model as well as the significance of the variables were tested using the Monte Carlo permutation tests (999 permutations). In addition, the correlation of time, expressed as the sampling year, with vegetation composition was tested using generalized additive models (GAM; tested models with 1–6 degrees of freedom; the best model selected based on the AIC) and then projected into the ordination space as contour lines.

To have an alternate view of the relationships of the independent explanatory variables, whose mutual correlations can be easily distorted in ordination diagrams, a set of pairwise correlation plots for all the variables was produced. The significance of the relationships between any two variables was tested using GAM in the mgcv R package [56,57,58,59,60].

Identification of alien species and their classification as either archaeophytes or neophytes was based on two complementary published sources. The checklist of alien species of the Czech Republic [61], suitable also for other “southern” countries (AT, SK), was combined with the alien species checklist for Poland [62]. These checklists overlap by approximately 90–95%; some of the thermophilous species that are considered native or archaeophytes in the southern countries are classified as archaeophytes or neophytes in Poland. In the case of differences in the evaluation of a species between the two checklists, our final classification was based on the country of origin of the majority of relevés with the species in question.

2.3. Species Composition of the Soil Seed Bank

The final dataset based on the cultivation of seeds from the soil and vegetation data collected in the field comprised a species list of the soil seed bank (presence/absence) and the associated above-ground vegetation (relevés) from one sampling plot for each of 32 sites (Tables S1 and S3). To assess the similarity between the soil seed bank and the above-ground vegetation, we used Sørensen’s similarity index [63], defined as S = 2c/(a + b + 2c), where a is the number of species present only in the relevé, b is the number of species present only in the soil seed bank and c is the number of species present in both the relevé and the soil seed bank. Species were assigned to seven groups according to phytosociological classes (Table S3). A linear model was used to estimate the effect of the belonging of a species to one of the seven groups on its proportion of occurrence in the soil (function lm in R [64]).

2.4. Chromosome Counts

Seeds from various localities in Austria, Croatia, the Czech Republic, Hungary, Italy, Poland, and Slovakia (Table S4) were germinated on filter paper in Petri dishes in a Sanyo MLR-352 environmental test chamber (“day”: 35 °C/12 h/light with 15 fluorescent lamps FL40SS-W/37 on; “night”: 15 °C/12 h/dark) and watered with distilled water. After 7−8 days, the radicle was cut from the seedlings and pre-treated with 0.002 M 8-hydroxyquinoline at 12 °C for 4 h or, alternatively, on ice for 4 h and then at 4 °C overnight. After pre-treatment, the radicles were fixed in freshly made absolute ethanol: glacial acetic acid (3:1) and kept at −20 °C until preparation.

Chromosomes were prepared by enzymatic digestion and squashing [65,66]. Fixed root tips were kept in citric acid-trisodium citrate buffer (pH 4.8) for 20 min. Then the citrate buffer was replaced by enzyme mixture (1% (w/v) cellulase Onozuka (Serva, Heidelberg, Germany), 0.4% (w/v) pectolyase (Sigma-Aldrich, Vienna, Austria), 0.4% (w/v) cytohelicase (Sigma-Aldrich), in citrate buffer, pH 4.8, pre-warmed at 37 °C) and the root tips were incubated at 37 °C for 30 min. After removal of the enzyme mixture, the root tips were washed in citrate buffer. For squashing, root tips were transferred to a drop of 60% acetic acid on a slide, dissected using entomological needles and squashed under a cover slip. The coverslips were removed, and preparations were air-dried and stored at 4 °C. The material was then stained with 2 μg/mL DAPI and mounted in antifade Vectashield mounting medium (Vector Laboratories, Burlingame, CA, USA) and analyzed under a Zeiss (Carl Zeiss, Vienna, Austria) Axio Imager.M2 epifluorescence microscope equipped with an AxioCam HRm camera. Images were acquired with the Zeiss AxioVision SE64 software.

2.5. Flow Cytometry

The relative and absolute DNA content was measured from fresh leaves of individual plants (collected in the field or grown from seeds; Table S4) using two different flow cytometric methods: (1) 4’,6-diamidino-2-phenylindole (DAPI) staining for a rough overview of the relative DNA content of a large number of individuals and (2) propidium iodide (PI) staining for determination of the absolute genome size of a limited number of individuals. For both methods, fresh leaves of Solanum pseudocapsicum (1.295 pg/1C [67]) were used as internal size standard.

For the DAPI measurements, the leaves were prepared with the CyStain UV Precise P kit (Partec, Münster, Germany), according to the manufacturer’s instructions. Leaves of the sample and internal size standard were chopped together with a razor blade in 400 μL of extraction buffer. After 1 min of incubation, the suspension with cell walls and cell contents including nuclei was filtered through a CellTrics filter (Partec; mesh size 50 μm). The filtered suspension was incubated with 1.6 mL staining buffer for 1 min or longer. Measurements were done in a Partec Ploidy Analyzer equipped with an HBO 100 long life mercury lamp.

For the PI measurements, we used Otto et al.’s [68] buffer for extraction of nuclei following the chopping method of Galbraith et al. [69]. After chopping, the suspension was filtered through a 30 μm nylon mesh (Sefar, Rüschlikon, Switzerland). Then 50 μL RNase A was added. Digestion of RNA took place at 37 °C for 30 min. After digestion, the suspension was supplied with 4 mL propidium iodide solution (pH ~ 9.5) and incubated in the dark at room temperature for at least 20 min or at 4 °C overnight. Measurements were carried out in a CyFlow ML flow cytometer (Partec) equipped with a Samba 532 nm green laser (Cobolt, Stockholm, Sweden).

For both the DAPI and PI methods, the fluorescence of 5000 particles was recorded and the values for mean and CV of peaks were determined with the software FloMax ver. 2.81 (Partec).

2.6. Relationship between Plant Community (Vegetation) and Genetic Diversity

The Pearson correlation was calculated between the Shannon diversity index (H) and the average expected heterozygosity under Hardy–Weinberg equilibrium (H_S; taken from [28] as a measure of within-population genetic diversity) for the same 31 sites belonging to the three habitat types (rivers: R1−R11; fishponds: F1−F10; fish storage ponds: S1−S10) as those used in Böckelmann et al. [27,28]. A structural equation model was used to test the hypothesis that the habitat type simultaneously influences H (which in turn influences H_S) and H_S in Amos 24.0.0 software (Amos Development Corporation, Wexford, PA, USA).

2.7. Species Distribution in the Czech Republic

The distributional data for Cyperus fuscus for the territory of the Czech Republic were obtained by excerption from all major Czech public herbaria and some Austrian and Slovak herbaria (BRA, BRNM, BRNU, CB, CBFS, CESK, FMM, GM, HOMP, HR, CHEB, CHOM, LIT, MJ, MMI, MP, MZ, NJM, OL, OLM, OP, OSM, PL, PR, PRA, PRC, ROZ, SAV, SLO, SOB, SUM, VM, VYM, W, WU, ZMT; acronyms see Thiers [70]) as well as some private herbaria and from the Czech National Phytosociological Database [45]. In addition, our personal field observations, as well as the observations of a few other field botanists, were also included. All the data on C. fuscus are currently stored in the database PLADIAS (www.pladias.cz, accessed on 21 February 2021), which, among others, summarizes all the digitized records on the species of the Czech flora [71]. Only those records that could be unambiguously georeferenced were retained for further analyses.

Records with the information about the collection year were classified into three groups based on their age reflecting the (in our opinion) most important breakpoints in the management of rivers and water reservoirs in Central Europe. The year 1900 was chosen as the first turning point as the scale of river engineering works in Europe was at its peak and most large European rivers had been channelized by this date [72]. The year 2000 was chosen as the other turning point to test the hypothesis that Cyperus fuscus might benefit from climate change.

2.7.1. Temporal Changes of Species Distribution

To assess the changes of the species’ distribution over time, the numbers of individual records per year were plotted as simple frequency curves. Only dated records could be used; all the records without at least a year of sampling were removed (these were mainly old herbarium records). In the case of duplicates, i.e., two or more records with the same date, locality, and collector, only one record was retained for the analyses and the rest was deleted. The search of the duplicates was done throughout all the sources used, as e.g., some records from the Czech National Phytosociological Database were documented also by herbarium specimens. For the records from different parts of the same fishpond, river etc., at least 0.5 km distance was requested if the site should be considered separately. To account for random fluctuations in the records, the data were smoothed using 11-year moving averages [73]. Importantly, the distributional data were corrected for botanical activity based on a dataset of 13 wetland species (Chenopodium ficifolium, Coleanthus subtilis, Cyperus flavescens, C. michelianus, Gnaphalium uliginosum, Laphangium luteoalbum, Leersia oryzoides, Lythrum hyssopifolia, Oxybasis glauca, O. rubra, Persicaria dubia, Pulicaria dysenterica, P. vulgaris) from 36 Czech public herbaria (BRNL, BRNM, BRNU, CB, CBFS, CESK, FMM, GM, HOMP, HR, CHEB, CHOM, LIM, LIT, MJ, MMI, MP, MZ, NJM, OL, OLM, OMJ, OP, OSM, OVMB, PL, PR, PRA, PRC, ROZ, SOB, SOKO, SUM, VM, VYM, ZMT). The same additional data sources as for C. fuscus were used for these species; all the data are stored in the PLADIAS database. Similar procedure of elimination of duplicate records as in the case of C. fuscus was applied for each of the 13 species. To account for uncertainty in botanical activity during periods with an overall low number of records, 50% jackknifing was performed 10,000 times on the input data tables, and means and 99% percentiles of the corrected number of records were calculated for each year.

2.7.2. Climatic Conditions

The relationship between climatic variables and the species’ distribution in the Czech Republic was analyzed from all georeferenced records. The values of the 19 bioclimatic variables contained in the WorldClim database [74] downloaded in the highest available resolution (30 arc seconds ≈ 1 km²) were extracted for each locality of Cyperus fuscus using the R package raster [75]. The same set of bioclimatic variables was also extracted for the centers of all quadrants of the Central European recording grid [76] located in the Czech Republic and without any records of C. fuscus. These values served as pseudo-absence data to test for climatic variables correlated with the occurrence of C. fuscus. A canonical discriminant analysis (CDA) in Canoco 5 [77] was used to test for the differences in the climatic conditions between locations with and without the presence of C. fuscus.

2.7.3. Climatic Niche Modelling

For predicting the occurrence of Cyperus fuscus in the Czech Republic and identifying any climate-driven limits of its distributional range, we employed the maximum entropy modelling approach implemented in maxent 3.4.1 [78]. The R package wallace was used [79]. We used the same 19 bioclimatic variables previously used in CDA. Duplicate data were removed by spatial thinning at a 1 km distance, and 7000 background points (pseudo-absences) were randomly sampled without replacement from the study area. The occurrences were partitioned into testing and training bins using the checkerboard2 method for fourfold cross-validation (aggregation factor 2). We ran the maxent models with the regularization multiplier (RM) values ranging from 0.5 to 4 (incremented by 0.5) and five alternative settings for feature classes (i.e., L, LQ, H, LQH, LQHP) and used the “area under the receiver operating characteristic curve” (AUC [80]) statistics to select the model with the highest predictive power.

3. Results

3.1. Community Affiliation of Cyperus fuscus and Vegetation Species Composition

Semi-supervised classification of altogether 925 relevés from AT, CZ, PL and SK identified occurrence of C. fuscus in plant communities of altogether ten syntaxonomic classes, with the highest share of the vegetation of the classes Isoëto-Nanojuncetea (622 relevés, i.e., ca 67% of the classified dataset), Bidentetea tripartitae (109 relevés, ca 12%) and Phragmito-Magnocaricetea (73 relevés, ca 8%). The nine other classes, i.e., Molinio-Arrhenatheretea, Scheuchzerio palustris-Caricetea nigrae, Crypsietea aculeatae, Potamogetonetea, Festuco-Puccinellietea, Charetea intermediae, Papaveretea rhoeadis, Littorelletea uniflorae, and Epilobietea angustifolii, were represented by altogether 33 relevés, with 1–9 relevés for each class (

Table 1. Percentage synoptic table of the vegetation with Cyperus fuscus (short version; for full version see Table S5). Classes distinguished: (1) Isoëto-Nanojuncetea; (2) Bidentetea tripartitae; (3) Phragmito-Magnocaricetea; (4) Molinio-Arrhenatheretea; (5) Scheuchzerio-Caricetea nigrae; (6) Crypsietea aculeatae; (7) Potamogetonetea; (8) Festuco-Puccinellietea; (9) Charetea intermediae; (10) Papaveretea rhoeadis; (11) Littorelletea uniflorae; (12) Epilobietea angustifolii. Only the diagnostic species occurring in at least 30 relevés and the other species occurring in at least 50 relevés are displayed. Layers: 6—herb layer, 7—juvenile trees and shrubs, 9—bryophyte and algal layer.

Vegetation Units	Layer	1	2	3	4	5	6	7	8	9	10	11	12
Number of relevés		622	109	73	9	5	5	4	4	2	2	1	1
Isoëto-Nanojuncetea
Cyperus fuscus	6	100	100	100	100	100	100	100	100	100	100	100	100
Plantago major subsp. intermedia	6	49	54	16	11	40	60	25			100
Gnaphalium uliginosum	6	50	38	16							50
Juncus bufonius	6	42	28	12	22						50
Limosella aquatica	6	36	16	12	11			50
Eleocharis acicularis	6	28	3	8				25
Potentilla supina	6	21	25	7		20	60		50		50
Eleocharis ovata	6	23	4	5								100
Carex bohemica	6	19	7	4				50
Lythrum portula	6	21	1	3							50
Riccia cavernosa/crystallina	9	14	1	4
Lindernia procumbens	6	7		3
Pulicaria vulgaris	6	5	6		11				25
Lythrum hyssopifolia	6	4	3	4
Bidentetea tripartitae
Persicaria lapathifolia s. l. (excl. P. lapathifolia subsp. brittingeri)	6	51	61	42	33	40	20	25	25		100	100	100
Rumex maritimus	6	41	67	47	33	60	40	25	50		50		100
Rorippa palustris	6	47	51	29	22	20		50			50		100
Ranunculus sceleratus	6	33	36	22	11	20		50	25			100	100
Persicaria hydropiper	6	26	39	34	22					50	50		100
Bidens tripartitus	6	26	36	23	11				25		50	100	100
Alopecurus aequalis	6	27	21	19	22	60			25		50
Oxybasis rubra	6	20	48	26		20	40		25
Bidens frondosus	6	15	40	23	11	20					50	100
Bidens radiatus	6	13	10	16
Oxybasis glauca	6	11	23	3			40		25
Bidens cernuus	6	10	15	7	22						50
Persicaria maculosa	6	9	14	8			20		25			100
Persicaria minor	6	11	4	5							50
Lipandra polysperma	6	6	24	8					25		50
Atriplex prostrata	6	5	25	5			60	25	25
Persicaria dubia	6	5	5	1		20
Xanthium orientale agg.	6	3	9	5
Chenopodium ficifolium	6	4	7	1			40
Phragmito-Magnocaricetea
Veronica anagallis-aquatica	6	31	32	22	11	40	20	25	25		50	100
Alisma plantago-aquatica	6	27	13	52	22	20		50		50		100	100
Leersia oryzoides	6	26	8	30		20					50
Oenanthe aquatica	6	20	32	27	11	60		50	50			100
Rorippa amphibia	6	14	34	26	22				25
Bolboschoenus maritimus agg.	6	12	12	34	11	40	60		100		50
Phalaroides arundinacea	6	10	31	21	22	20		25					100
Eleocharis palustris agg.	6	15	8	11					25			100
Typha latifolia	6	12	15	19	11	20		25
Phragmites australis	6	9	17	12	22	20	40		25			100
Typha angustifolia	6	7	7	8	11	20			25	50
Poa palustris	6	6	11	5	11	20
Veronica beccabunga	6	5	5	5	11					100		100
Butomus umbellatus	6	2	12	11				25
Molinio-Arrhenatheretea
Lythrum salicaria	6	27	22	25	56		20					100
Taraxacum sect. Ruderalia	6	19	20	8	33	20	20	75	25
Agrostis stolonifera	6	19	17	12	44	20	40		25
Juncus effusus	6	10	11	5	22
Trifolium hybridum	6	12	5	4	11				25
Myosotis palustris agg.	6	10	8	11	11
Trifolium repens	6	9	12	1	33						50
Juncus compressus	6	8	6	7	22	20	40		50
Argentina anserina	6	7	10	7
Rorippa sylvestris	6	7	6	8	22	20			25
Ranunculus repens	6	6	9	4	33	20
Alopecurus geniculatus	6	7	4	5
Poa trivialis	6	2	11	3	33	20		25
Juncus inflexus	6	3	4	1	44	20
Scheuchzerio-Caricetea nigrae
Juncus articulatus	6	34	15	29	56	100			50	50	50
Potamogetonetea
Callitriche palustris agg.	6	18	6	7
Papaveretea rhoeadis
Echinochloa crus-galli	6	41	43	36	22	20	60	25	75		100	100
Tripleurospermum inodorum	6	16	23	10		20	20		25		50
Epilobietea angustifolii
Urtica dioica	6	8	28	5	22	20		25			50
Myosoton aquaticum	6	9	19	5	11	20		25	25		50
Epilobium hirsutum	6	6	6	8									100
Others
Salix sp.	7	34	38	18	22			75	25			100
Lycopus europaeus	6	16	18	18	22	20		25
Nostoc sp.	9	14	4	3		20
Polygonum aviculare agg.	6	9	19	8
Epilobium ciliatum	6	11	5	5	11
Plantago major	6	9	6	10	11				25
Ochlopoa annua	6	8	9	3	22						50
Epilobium sp.	6	8	4	5	22			25			50
Sagina procumbens	6	9	5	3	11						50
Bryum argenteum	9	9	6		11						50

). The rest, 88 relevés, remained unclassified, representing mainly the communities transitional between two or more classes (data not displayed).

When we allowed classification of the relevés belonging to the Isoëto-Nanojuncetea class up to the association level, altogether 462 relevés were assigned to one of the seven detected associations and the rest, 160 relevés, was classified into the class or alliance (Eleocharition soloniensis (=Eleocharition ovatae), Verbenion supinae) level only. Among the associations, Cyperetum micheliani and Polygono-Eleocharitetum ovatae were the most frequent, documented by 329 (ca 36% of the classified dataset) and 103 (ca 11%) relevés, respectively (Table S5). All the other associations, i.e., Cerastio-Ranunculetum sardoi, Veronico anagalloidis-Lythretum hyssopifoliae, Cyperetum flavescentis, Pulicario-Menthetum, and Eleocharito-Schoenoplectetum supini, were represented by only a few relevés each.

Altogether 589 taxa of vascular plants, bryophytes, and algae were identified in the 925 relevés with Cyperus fuscus (Table S5; only the 549 taxa occurring in the classified relevés are presented). Among the taxa often co-occurring with C. fuscus, some diagnostic species of the classes Isoëto-Nanojuncetea (e.g., Plantago uliginosa subsp. intermedia, Gnaphalium uliginosum, Juncus bufonius, and Limosella aquatica) and Bidentetea (e.g., Persicaria lapathifolia s. l., Rumex maritimus, Rorippa palustris, and Ranunculus sceleratus) were the most frequent (frequency >25% in the whole dataset). Very common were also Echinochloa crus-galli (frequency >25%) from the class Papaveretea rhoeadis, Alisma plantago-aquatica, Leersia oryzoides, and Oenanthe aquatica (frequency of each species >20%) from the class Phragmito-Magnocaricetea, Lythrum salicaria from the class Molinio-Arrhenatheretea (frequency >20%), and several other species (Table 1 and Table S5). Most of the species across all the classes had an overall frequency lower than 10%, whereas large parts of them occurred in only one or a few relevés.

Altogether, 91 alien species (i.e., ca 15% of the total number of species) were identified in the vegetation with Cyperus fuscus, with 53 and 38 taxa assigned to archaeophytes and neophytes, respectively. Most of them were rare, occurring in less than 5% of the relevés. Among the aliens with rather high frequency were Echinochloa crus-galli (arch), Bidens frondosus (neo), Xanthium orientale agg. (neo), and Epilobium ciliatum (neo).

3.2. Factors Influencing Species Composition of the Vegetation with Cyperus fuscus

The relation between the selected explanatory variables and the species composition of the plots was highly significant (test on the first axis: F = 1.6, p < 0.001; test on all axes: F = 7.6, p < 0.001). The proportion of variation explained by the explanatory variables was 8.93% (adjusted explained variation). The marginal effects of all the explanatory variables were also highly significant (

Table 2. Explanatory variables used in the canonical correspondence analysis (CCA) and their marginal effects. The p-values were adjusted using the false discovery rate. Environmental variables nutrients, moisture, soil reaction, continentality, temperature, and light correspond to relevant Ellenberg indicator values.

Variable	Explained Variation [%]	F	p (adj.)
Nutrients	1.94	16.0	<0.001
Moisture	1.75	14.5	<0.001
Soil reaction	1.59	13.1	<0.001
Continentality	1.50	12.4	<0.001
Temperature	1.11	9.1	<0.001
Number of archaeophytes	1.08	8.9	<0.001
Number of neophytes	0.92	7.6	<0.001
Light	0.88	7.2	<0.001
Year	0.85	6.9	<0.001
Total cover of archaeophytes	0.63	5.2	<0.001
Total cover of neophytes	0.49	4.0	<0.001
Cyperus fuscus cover	0.27	2.2	<0.001

) although the proportions of explained variation were relatively low. The general additive model (GAM) testing the relation of year and the vegetation composition was significant (F = 8.3, p < 0.001 in the ordination space represented by the 1st and 2nd axes; F = 37.0, p < 0.001 in the ordination space represented by the 1st and 3rd axes). The model (Figure 1) indicates the decline of some rather sensitive wetland species with lower nutrient and temperature demands (Drepanocladus aduncus, Eleocharis acicularis, Juncus bulbosus, Lythrum portula) and the increase of some taller, nutrient demanding species from the Bidentetea and Phragmito-Magnocaricetea classes (Bidens frondosus, Persicaria lapathifolia s. l., Phalaroides arundinacea, Rumex maritimus, Rorippa amphibia) and willow seedlings (Salix sp.) in the newer relevés.

Correlations among all the explanatory variables are displayed in the correlograms (Figure S1). These results show significant relationships between Cyperus fuscus cover and EIVs for temperature, moisture, light, nutrients, and continentality, while the relationships to the other factors including the year, number of species, and cover of archaeophytes and neophytes, and EIVs for soil reaction were not significant (Figure 2 and Figure S1). Optima of C. fuscus, according to EIVs derived from the species co-occurring in the relevés, show C. fuscus to be a highly light demanding species. Its optima for moisture and temperature correspond to 7.5 and 6, respectively, i.e., slightly higher values than the mean of the relevant scale (= 6.5 on the 12-degree scale for moisture and 5 on the 9-degree scale for temperature). In the case of nutrients, the optimum of C. fuscus corresponds to 5, i.e., the mean value, and the value 4 for continentality is slightly lower than the mean (both EIVs have a 9-degree scale). Archaeophytes and neophytes show rather different relationships to the environmental factors and time than C. fuscus (Figure S1). Neophyte species numbers significantly increased since the 1930s, while their cover change was not significant. In contrast, the highest species numbers and covers for archaeophytes were recorded in the historical relevés from the 1940s to the 1960s. Both groups of aliens exhibit substantially higher values for nutrients and lower values for moisture than C. fuscus. EIVs of the aliens for light show the opposite trend than C. fuscus cover. In contrast, similarities between the response curves of aliens and C. fuscus are shown at EIVs for soil reaction, but the relationship is not significant for C. fuscus cover (p = 0.092; Figure S1). Similar positions of optima are also found in the response curves of the EIVs for continentality. Finally, the response curves for EIVs for temperature also exhibit similar trends for number of neophyte species and C. fuscus cover; the optimum EIVs for temperature for archaeophytes is substantially higher (Figure S1).

3.3. Similarity between Soil Seed Bank and Above-Ground Vegetation (Relevés)

There were 16.7 species on average in the relevés across the three habitat types (16.2 in river habitats, 17.6 in fishpond habitats, and 17.0 in fish storage pond habitats, n = 32). In the soil seed bank, there was an average of 12.5 species per m² (14.0 in river habitats, 11.0 in fishpond habitats, and 11.9 in fish storage pond habitats, n = 32; Figure S2). Sørensen’s similarity index (the similarity between the vegetation and the soil seed bank) for the habitat type river was 0.57 ± 0.12 (mean ± SD; median = 0.60, n = 11); for the habitat type fishpond 0.55 ± 0.15 (median = 0.53, n = 10); and for the habitat type fish storage pond 0.51 ± 0.11 (median = 0.49, n = 9; Figure 3a). There was no significant difference in Sørensen’s similarity index among the three habitat types.

Across all habitat types, Sørensen’s similarity index showed a mean similarity between the soil seed bank and the above-ground vegetation of 0.55 (SD = 0.13; n = 32). The belonging of species to groups according to phytosociological classes may be used to explain the remaining dissimilarity, as not all species occurring in mudflat habitats are equally likely to form a soil seed bank there. The proportion of variance explained by the linear model used to estimate the effect of the belonging of a species to one of seven groups according to phytosociological classes on its proportion of occurrence in the soil (multiple R-squared) is 0.25. Isoëto-Nanojuncetea and Crypsietea species (the reference; mean proportion of occurrence in the soil = 0.509, SD = 0.194, n = 17), as well as Potamogetonetea and Lemnetea species (mean proportion = 0.554, SD = 0.422, n = 4), are equally abundant in the soil and in the above-ground vegetation (

Table 3. Linear model of the proportion of occurrence in the soil depending on the belonging of species to one of seven groups according to phytosociological classes. Isoëto-Nanojuncetea and Crypsietea species serve as reference. The estimate of the other groups indicates the deviation from the reference. Significance codes: * <0.050; ** <0.010; *** <0.001.

Coefficient	Estimate	t Value	p Value
Isoëto-Nanojuncetea and Crypsietea (intercept)	0.509	9.53	0.000	***
Bidentetea	−0.086	−1.16	0.251
Phragmito-Magnocaricetea and Scheuchzerio-Caricetea	−0.216	−2.86	0.005	**
Molinio-Arrhenatheretea and other grassland classes	−0.294	−3.77	0.000	***
Potamogetonetea and Lemnetea	0.045	0.36	0.717
Papaveretea and other classes of annual ruderal vegetation	−0.179	−2.10	0.038	*
Epilobietea and other classes of perennial ruderal vegetation	−0.345	−4.05	0.000	***

; Figure 3b). Bidentetea species (mean proportion = 0.423, SD = 0.224, n = 18) are somewhat less frequently represented in the soil seed bank. Phragmito-Magnocaricetea and Scheuchzerio-Caricetea species (mean proportion = 0.293, SD = 0.176, n = 17, p < 0.01), as well as Molinio-Arrhenatheretea and other grassland species (mean proportion = 0.215, SD = 0.213, n = 15, p < 0.001), are significantly less frequent in the soil. Papaveretea and other annual ruderal species (mean proportion = 0.330, SD = 0.228, n = 11, p < 0.05) are less common in the soil than the reference. Lastly, Epilobietea, and other perennial ruderal species are the least abundant in the soil (mean proportion = 0.164, SD = 0.232, n = 11, p < 0.001).

3.4. Chromosome Number, Genome Size, and Ploidy Level

Unequivocal chromosome counts with 2n = 36 chromosomes were obtained from one plant each of seven populations of Cyperus fuscus (one from Austria, three from the Czech Republic, one from Hungary, and two from Slovakia; Figure 4; Table S4). This chromosome number corresponds to a genome size of 0.231 pg/1C (population SK1) or 0.232 pg/1C (population HU2). The mean and standard deviation calculated across 29 additional population 1C-values is 0.233 ± 0.004 pg/1C (range of population 1C-values = 0.227–0.243 pg; Table S4). The flow cytometric measurements (DAPI) of 223 individuals representing 50 populations from Austria, Croatia, the Czech Republic, Hungary, Italy, Poland, and Slovakia also revealed a uniform relative DNA content (Table S4) suggesting that all plants represent the same ploidy level.

3.5. Effect of Plant Community (Vegetation) Diversity on Genetic Diversity in River and Anthropogenic Habitats

There is no significant correlation between Shannon diversity (H) and average expected heterozygosity (for above-ground H_S: r = −0.111, p = 0.554, n = 31; for soil H_S: −0.233, p = 0.207, n = 31). The structural equation model (standardized solution, n = 31) shows the regression coefficient of Shannon diversity on average expected heterozygosity (R-squared of H_S = 0.70) in consideration of the direct and indirect effects of the third variable habitat type (river habitat = reference; Figure 5). There is a moderately significant regression path from Shannon diversity to H_S with a standardized effect size of −0.291 (p = 0.013). The bivariate correlation between the two variables is weaker and not significant, because it is reduced by the effect of the third variable, habitat type, which has a negative effect on both Shannon diversity (weak and not significant effect) and H_S (strong and significant effect). The third variable effect of habitat type, thus, creates a weak positive relationship between Shannon diversity and H_S, which weakens the negative correlation between the two variables.

The relative proportion (species richness and cover) of Isoëto-Nanojuncetea species is somewhat higher in the anthropogenic (fishpond and fish storage pond) habitats in comparison to river habitats (Figure 6 and Figure 7). The mean overall cover of the herbaceous layer does also not differ much among the three habitat types. Plots with Cyperus fuscus in river habitats have a mean cover of 55.2% (SD = 17.9), fishpond habitats of 66.2% (SD = 17.6), and fish storage pond habitats of 55.7% (SD = 18.8).

3.6. Distribution Trends

The oldest dated Cyperus fuscus records are from 1833, which also provides the lower limit of the produced frequency chart (Figure 8). The curve of absolute (uncorrected) values shows important inter-annual fluctuations in the number of records during the whole study period (until 2015). These are, however, most remarkable after 1995 when the number of records strongly increased. Although the botanical activity was the highest in this period, the curve of the corrected species abundance still shows a clear trend in growing abundance values and, at the same time, low uncertainty expressed as 99% confidence intervals (Figure 8). The corrected values in some periods between the 1830s and 1910s are comparable or even higher than in the period after 1995 but uncertainty in the estimation of the corrected species abundance is high due to low numbers of the old records, particularly before the 1850s.

3.7. Climatic Conditions

All 19 bioclim variables differentiated significantly between the map quadrants with and without the records of Cyperus fuscus (

Table 4. Climatic variables and their significance in the canonical discriminant analysis (CDA). Biplot scores of explanatory variables represent the contribution of climatic variables to the first canonical axis separating presences and absences of Cyperus fuscus [77]. Climatic variables with positive biplot score values are positively correlated with C. fuscus occurrence, variables with negative values are positively correlated with C. fuscus absence. The significance was adjusted using the false discovery rate.

Climatic Variable	Description	Explained Variation [%]	p (adj.)	Biplot Score
bio10	Mean temperature of warmest quarter	19.1	<0.001	0.92
bio08	Mean temperature of wettest quarter	18.9	<0.001	0.91
bio05	Maximum temperature of warmest month	18.9	<0.001	0.91
bio01	Annual mean temperature	18.7	<0.001	0.91
bio11	Mean temperature of coldest quarter	15.2	<0.001	0.82
bio04	Temperature seasonality	13.6	<0.001	0.77
bio07	Temperature annual range	12.4	<0.001	0.74
bio06	Minimum temperature of coldest month	9.4	<0.001	0.65
bio02	Mean diurnal range	9.3	<0.001	0.64
bio12	Annual precipitation	6.7	<0.001	−0.54
bio14	Precipitation of driest month	6.6	<0.001	−0.54
bio17	Precipitation of driest quarter	6.4	<0.001	−0.53
bio19	Precipitation of coldest quarter	6.3	<0.001	−0.53
bio16	Precipitation of wettest quarter	5.0	<0.001	−0.47
bio18	Precipitation of warmest quarter	5.0	<0.001	−0.47
bio15	Precipitation seasonality	4.5	<0.001	0.44
bio13	Precipitation of wettest month	4.3	<0.001	−0.44
bio09	Mean temperature of driest quarter	4.2	<0.001	0.43
bio03	Isothermality	3.4	<0.001	0.39

). The differentiation was predominantly unilateral, i.e., the quadrants without C. fuscus mostly differed from quadrants occupied by the species, but not vice versa (Figure S3). Climatic variables related to temperature had larger effects than variables related to precipitation. The occurrences of C. fuscus correlated positively with temperature and negatively with precipitation. Summary charts showed that C. fuscus has the optimum in regions with about 600 mm annual precipitation and 8 °C annual mean temperature (Figure 9).

3.8. Climatic Niche Modelling

The best maxent model (LQH, RM = 1) resulted in high AUC score 0.83 ± 0.0002 (mean ± variance) and low omission rate 0.11 ± 0.0004. The occurrences of Cyperus fuscus in the Czech Republic are concentrated in three regions: river valleys and surrounding lowlands in N and SE parts and fishpond basins in SW parts of the country’s territory (Figure 10). The species clearly prefers regions with higher mean annual temperatures, which are rather poor to moderately rich in precipitation (Table 4, Figure 9). These regions are shown to be important for populations of C. fuscus already in the 19th century, with many further finds during the 20th and 21st century. In contrast, most localities in cold regions (where older occurrences are exceptional) were recorded in the 20th and, most importantly, 21st centuries (Figure 10).

4. Discussion

4.1. Vegetation and Cyperus fuscus Frequency Change over Time

As a large part of the relevés with Cyperus fuscus from the phytosociological databases lacked any environmental data, such as habitat type, type of substrate, or substrate moisture, we could only classify the relevés into the predefined syntaxa, describe the overall species composition of the vegetation, and analyze how it is influenced by the year of sampling and environmental variables expressed as Ellenberg indicator values (EIVs). We also analyzed the correlations between the cover of C. fuscus and the species number and cover of archaeophytes and neophytes.

Our results show that Cyperus fuscus grows in a broad range of non-forest vegetation types, with an optimum in the communities of the Isoëto-Nanojuncetea class. It is also frequent in the vegetation of the Bidentetea tripartitae and Phragmito-Magnocaricetea classes. Although the species of the latter two classes are usually taller and competitively stronger than small wetland annuals of the Isoëto-Nanojuncetea class, it seems that C. fuscus is rather tolerant of these conditions. This is probably related to its morphological plasticity: when soil moisture is high, the species can reach a height of up to several dozen centimeters [81]. Under sub-optimal substrate moisture not only C. fuscus but also potential competitors from the other wetland classes, particularly Bidentetea, decrease their size. Even the stands classified within the class Isoëto-Nanojuncetea were characterized by high frequency (Table 1) and sometimes also cover (data not displayed) of the species of the Bidentetea and Phragmito-Magnocaricetea classes. An important share of these rather nutrient demanding species points out the tolerance of C. fuscus to elevated nutrient amounts (particularly nitrogen, sometimes also phosphorus) in the soil. However, its optimum is in habitats with average amounts of nutrients, as shown by the correlation of C. fuscus cover and EIVs for nutrients (Figure 2 and Figure S1). As in other mudflat species, the optimum of C. fuscus may be modified by high competition pressure of nitrophilous species under the conditions of high nutrient amounts (see e.g., Šumberová et al. [82] for competition by Leersia oryzoides to small wetland annuals). Indeed, during our field data sampling we often encountered numerous populations of C. fuscus on deep sapropelic muddy soils, which are known as an extraordinary nutrient rich substrate. Moreover, sapropelic substrates also store high amounts of water, which have a positive effect on the growth of C. fuscus [24]. These populations usually occurred on sites with limited cover of taller herbs, which is in accordance with very high demands of C. fuscus for light (see the EIVs for light, Figure 2). On the other hand, C. fuscus populations also exist in nitrogen and phosphorus poor, but calcium rich fens or in stands of the rare association Cyperetum flavescentis. Such relevés, mainly historical ones, were very rare in our dataset; most of them came from the Alps [83], some of them from the Carpathians (Hájek, unpublished data). As the occurrence of C. fuscus in these regions is rather sporadic, poorly predictable, and the populations growing in small-scale gaps in perennial vegetation are usually rather small, we did not include these regions into our field trips. This part of the vegetation variability was captured thanks to the data from the phytosociological databases; however, we could miss a relevant part of the genetic variability of C. fuscus.

Cyperus fuscus is considered a thermophilous species, especially due to the high temperatures required for germination [24] and the concentration of its occurrence in warm regions [23]. As its spread related to climate warming is supposed [23], we expected to detect distribution and frequency changes of this species in the Czech Republic (herbarium and other occurrence data) and, at the same time, changes in species composition of the vegetation with C. fuscus towards higher share of thermophilous species. We confirmed an increasing number of localities of C. fuscus in the last two decades, whereby the species is more frequently found in regions where the habitat conditions should not be suitable for its occurrence according to climatic modelling (Figure 10). These occurrences of the species outside of its common range are probably related to the extraordinary hot summers since the 1990s. The populations recorded may be temporary or they could be stored for a couple of years in the soil seed bank, where they are waiting for a similar situation [84,85]. Although the growing number of localities may be partly related to high field research activity in the country, also the corrected values (Figure 8) show the increasing trend and at the same time the high data reliability (the higher peaks in the 19th and the beginning of the 20th centuries have lower reliability, as shown by broad confidence intervals). Therefore, it might be quite surprising that we could not detect any increase of C. fuscus cover in the recent relevés (Figure 2). It is probably due to the sampling of most of the relevés without any focus to record the stands of C. fuscus. Besides our own data from 2012, the relevés were collected randomly to document relevant wetland vegetation types. The relevés with the occurrence of C. fuscus (cover ≥ 1%) were selected subsequently from the databases. Moreover, for the study of species cover changes, permanent plots on selected sites would be an optimal method (see Šumberová et al. [10] for Crassula aquatica). For a thermophilous species, like C. fuscus, we would also expect a higher temperature optimum expressed as EIV (Figure 2). Similarly, the climatic optima derived from the mapping quadrants occupied by C. fuscus in the Czech Republic seem to be quite low for mean annual temperature and quite high for yearly sum of precipitation in comparison to the climate of the warmest parts of the Czech Republic (temperature: 9–10 °C, precipitation: 500–550 mm [86]). We suppose that the recent spread of C. fuscus into the colder regions, which is directly reflected in the number of mapping quadrants, is behind these patterns. Considering the EIVs, some species with rather low temperature demands accompany C. fuscus, particularly in colder regions, while other thermophytes are absent. Precipitation probably plays an important role in the recent distribution of C. fuscus. The warmest parts of the countries studied are also the regions with rather low precipitation. There, C. fuscus is usually concentrated in the large river floodplains with a suitable mesoclimate (particularly high air humidity and thus slower substrate desiccation). It seems that the frequent temperature extremes in colder regions recently allow the species to spread because of more favorable precipitation amounts and/or their distribution throughout the growing season.

Cyperus fuscus is also considered as basiphilous (particularly calciphilous) [87] (pp. 221–226) [88]; this relationship should be particularly remarkable in colder regions [89]. Our results did not show a significant relationship of C. fuscus to soil reaction, but if we considered even the insignificant result (p = 0.092; Figure 2), we could see that there is no sign of higher EIV for soil reaction in this species. In contrast, it seems to be rather generalist in the relationship to soil reaction. Like for temperature, some transitional status of a large part of the relevés, where in one and the same stand species with different habitat requirements (in this case for soil reaction and calcium content) are mixed, probably also plays a role here. These could be for instance the relevés of the Polygono-Eleocharitetum ovatae association, which include some species preferring acidic non-calcareous substrates (e.g., Carex bohemica) but usually lack a higher amount of basiphilous/calciphilous species. It is likely that high summer temperatures in the last two decades not only help Cyperus fuscus to cross the climatic limits in some regions, but also to cope with the conditions of lower calcium availability. However, an opposite explanation is also possible: the continual change of soil chemistry as a consequence of land use and management (e.g., fishpond manuring and liming, wastewater disposal) and climate change synergy [90]. These conditions would support the species with higher requirements for soil reaction and/or nutrients, but the acidophilous species with lower nutrient demands could still thrive as relics of former soil properties.

Although there was a high share of archaeophytes and neophytes compared to the number of native species in the whole dataset of the relevés with Cyperus fuscus, we did not find a significant negative influence of aliens on C. fuscus cover. In most of the relevés occurred at least one alien species, and in many of them, more than 10% of the total species number was formed by archaeophytes and/or neophytes. It is more than given by Chytrý et al. [91] for the littoral vegetation where also the communities of wetland annuals and perennials were included. However, the vegetation in the relevés from fish storage ponds and sandy or gravelly river deposits often exhibits transition to ruderal communities, as shown by the relatively high amount of ruderal species in our plots for complex research of C. fuscus (Figure 6 and Figure 7); many of these species are aliens. On the other hand, the cover of alien species in most of the relevés was lower than 10%. As many of these species were annuals having typically similar or lower height than C. fuscus, their competitive ability is also likely to be similar or lower than that of C. fuscus (see species traits in e.g. Lindernia dubia or Veronica peregrina in the database PLADIAS, www.pladias.cz, accessed on 1 March 2021). Moreover, annual species like Echinochloa crus-galli, which are capable of forming dense and tall stands, often occur in low, prostrate forms in the habitats of C. fuscus; this growth form is probably related to management, such as mowing [82] or to natural disturbances, such as grazing by wild ducks, geese, and swans, as this species may constitute an important part of their diet [92]. These disturbances enable coexistence of species with various habitat requirements and competitive abilities within one stand. Some other aliens, particularly terrestrial ruderal weeds, may mark the margin of the ecological range of C. fuscus, such as sites with substrates that are too dry for C. fuscus. In such cases, the low cover of C. fuscus is not the result of competition by aliens.

Importantly, neophytes show an increase in their species numbers in the recent relevés, but the cover did not change with time. The cover of archaeophytes even decreased. Still, we wanted to know if there is some overlap of ecological demands (expressed as EIVs) of both groups of aliens and Cyperus fuscus at its optimum. We did not detect overlaps for basic factors, such as nutrients, moisture, and light, which would explain why neither the archaeophytes nor the neophytes have any influence on C. fuscus: There is obviously no competition for basic resources in most cases. The overlaps of EIVs for continentality, temperature, and soil reaction may be attributable to similar geographical distribution patterns of the relevés with high C. fuscus cover and with high archaeophyte/neophyte cover (or species number). As each alien species has its specific traits, we compared ecological requirements of C. fuscus, presented here, and of Lindernia dubia, an alien analyzed in an earlier study [93]. Optima expressed as EIVs of C. fuscus are much more like those of the native L. procumbens than those of L. dubia, which is less moisture and light and more temperature and nutrient demanding.

In fact, Cyperus fuscus thrives under high substrate moisture, i.e., on sites with waterlogged or, in the time after seedlings’ establishment, even shallowly flooded substrate [24,81]. However, many relevés in our dataset are from sites, where the substrate desiccates rather early (e.g., fish storage pond bottoms or sandy river deposits); the moisture is still sufficient (although not optimal) for C. fuscus growth [27], but, at the same time, it also enables germination of terrestrial species. The presence of large numbers of terrestrial species in the relevés obviously pushed down the EIV value for moisture of C. fuscus in our analyses (compared to the corrected values in www.pladias.cz (accessed on 21 February 2021), where C. fuscus has the EIV 9 for moisture). Still, it is difficult to evaluate both the species’ moisture range and optimum, as the populations of different habitat types seem to differ in their moisture requirements and flooding tolerance [27].

Although we have shown that there is a high number of alien as well as native ruderal species in the vegetation with Cyperus fuscus, the same applies for rare and threatened taxa. We did not analyze these species in more detail, because there are large differences among the national species lists of Austria [15], the Czech Republic [19], Poland [94], and Slovakia [95], not only in the particular species assessments, but also in the classification systems. However, there are several dozen species in the vegetation with C. fuscus (Table S5), which are on the Red Data List of at least one of the target countries. Most of them are characteristic species of the Isoëto-Nanojuncetea class. Among the species, which are under high threat pressures in most of the target countries, are for instance Cyperus flavescens, C. michelianus, Elatine hydropiper, Lindernia procumbens (protected by Bern Convention on the Conservation of European Wildlife and Natural Habitats and also by the Habitats Directive of the European Union), and Pulicaria vulgaris. Even species like Eleocharis acicularis, E. ovata, and Limosella aquatica, having high frequencies in our dataset (Table 1 and Table S5), are highly threatened in Austria [15]. These facts highlight C. fuscus as a potential indicator of habitat conditions suitable for a range of species, which are much more threatened than C. fuscus itself.

4.2. Genetics and Soil Seed Bank

In contrast to our expectation derived from previous publication records (2n = 36 for the Czech Republic [32], 2n = 72 for Slovakia [33]), we found no variation of chromosome numbers and no substantial variation in genome sizes. The sampling of populations for flow cytometry was rather dense in the Czech Republic, eastern Austria, western Slovakia, and western Hungary and it included various habitat and vegetation types. The genome size obtained related to 2n = 36 chromosomes. The number of 2n = 72 chromosomes reported from a gravel pit near Lakšárska Nová Ves, Slovakia [33], could not be found in the samples used in the current study. We searched for Cyperus fuscus in this area but could not find it again there. The closest sampled population with similar ecological conditions (acidic sand) is from the dam reservoir Vodná nádrž Horná Studená voda (constructed on the site of a former large gravel pit) NW of Tomky, Slovakia (P. Kúr & K. Tremetsberger, 20.9.2013) and has 2n = 36 chromosomes. Plants from other gravel pits in Slovakia (NW of Dubnica nad Váhom and SE of Lednické Rovne) did not significantly deviate in genome size, so that our data give no evidence of the occurrence of polyploids in C. fuscus. One might hypothesize that the appearance of the cytotype with 2n = 72 chromosomes was only temporary, possibly due to a lower viability. The incidence of spontaneous autopolyploids may often not be detected. Cyperus fuscus with 2n = 36 chromosomes behaves genetically as a diploid with no more than two alleles per microsatellite locus per individual and allele dosage corresponding to a diploid [28,96]. Roalson [97] noted that peaks in haploid chromosome numbers in the genus Cyperus at 18, 36, and 54 could be interpreted as 1X, 2X, 3X pattern. Another possible interpretation is genetic/cytological diploidization. Uniform genome sizes and genetic indication of diploid-like behavior recommend C. fuscus as an ecological-genetic model plant.

Previously, no greater genetic differentiation than that between sampling plots within a given site was found between plants of Cyperus fuscus derived from seeds stored in the soil and plants derived from above-ground individuals [28]. Böckelmann et al. [28] also showed that C. fuscus immigrants have similar probabilities of germinating or entering the soil seed bank after arrival in river or anthropogenic sites. Here, we used Sørensen’s similarity index as an indicator of species turnover between the soil and the yearly above-ground vegetation. The index did not differ significantly among the three studied habitat types (rivers, fishponds, and fish storage ponds), although there is a slight tendency for higher similarity in species composition at river sites. In contrast, in Cardamine amara, which is also found in habitats influenced by water movements, there was a slight tendency for lower similarity in species composition at riverbanks compared to retention basins and meadows [31]. We conclude that more natural sites along rivers and anthropogenic habitats disconnected from the river with high density of Cyperus fuscus do not seem to differ much in their dynamics between the soil seed bank and the above-ground population/vegetation, neither with respect to individual species (genetic diversity) nor with respect to the vegetation (species diversity).

The structural equation model revealed a negative effect (standardized regression weight = −0.291, p = 0.013) of plant community (vegetation) diversity (measured by the Shannon index) on within-population genetic diversity (H_S). A negative effect can be expected, because Cyperus fuscus is a small and short-lived pioneer species (intermediate between the r- and s-strategy types) with high demand for light [85,98]; it is specialized to the conditions encountered in mudflat habitats, which are not suitable for many species. Under conditions of high competition from many other species, fewer genotypes of C. fuscus may be able to survive, because a diverse community of competitors may limit the ability of the individual species to use different parts of the environment (i.e., the niche breadth is reduced) [41]. The effect of the habitat type on H_S, however, is not mediated by plant community diversity (indirect effect of the fishpond habitat mediated by Shannon diversity = 0.041; indirect effect of the fish storage pond habitat mediated by Shannon diversity = 0.036), because the direct effect of the habitat type on Shannon diversity is weak and not significant (Figure 5). The strong and significant effect of the habitat type on H_S must therefore be mediated by other mechanisms than plant community diversity, composition, or cover (Figure 6 and Figure 7), such as differences in the strength of selection pressures, founder effects when anthropogenic habitats were created through initiation of fish farming activities, or different levels and patterns of immigration [28]. Despite that the vegetation of anthropogenic habitats harbors a great diversity of Isoëto-Nanojuncetea species (similar to that of riverine stands of C. fuscus), C. fuscus plants from riverbanks exceed those from anthropogenic habitats in terms of genetic diversity, adaptation to flooding (lower cost of low-oxygen escape strategy), and fitness [27,28]. This has important implications for conservation: It is necessary to preserve the dynamic riverine habitats if one wants to maintain all the adaptive potential of the species.