Formalized reproduction of an expert‐based phytosociological classification: A case study of subalpine tall‐forb vegetation

Abstract. Delimitation of vegetation units in phytosociology is traditionally based on expert knowledge. Applications of expert‐based classifications are often inconsistent because criteria for assigning relevés to vegetation units are seldom given explicitly. Still, there is, e.g. in nature conservation, an increasing need for a consistent application of vegetation classification using computer expert systems for unit identification. We propose a procedure for formalized reproduction of an expert‐based vegetation classification, which is applicable to large phytosociological data sets. This procedure combines Bruelheide's Cocktail method with a similarity‐based assignment of relevés to constancy columns of a vegetation table. As a test of this method we attempt to reproduce the expert‐based phytosociological classification of subalpine tall‐forb vegetation of the Czech Republic which has been made by combination of expert judgement and stepwise numerical classification of 718 relevés by TWINSPAN. Applying the Cocktail method to a geographically stratified data set of 21794 relevés of all Czech vegetation types, we defined groups of species with the statistical tendency of joint occurrences in vegetation. Combinations of 12 of these species groups by logical operators AND, OR and AND NOT yielded formal definitions of 14 of 16 associations which had been accepted in the expert‐based classification. Application of these formal definitions to the original data set of 718 relevés resulted in an assignment of 376 relevés to the associations. This assignment agreed well with the original expert‐based classification. Relevés that remained un‐assigned because they had not met the requirements of any of the formal definitions, were subsequently assigned to the associations by calculating similarity to relevé groups that had already been assigned to the associations. A new index, based on frequency and fidelity, was proposed for calculating similarity. The agreement with the expert‐based classification achieved by the formal definitions was still improved after applying the similarity‐based assignment. Results indicate that the expert‐based classification can be successfully formalized and converted into a computer expert system.     

Towards unification of national vegetation classifications: A comparison of two methods for analysis of large data sets

Abstract. In European phytosociology, national classifications of corresponding vegetation types show considerable differences even between neighbouring countries. Therefore, the European Vegetation Survey project urgently needs numerical classification methods for large data sets that are able to produce compatible classifications using data sets from different countries. We tested the ability of two methods, TWINSPAN and COCKTAIL, to produce similar classifications of wet meadows (Calthion, incl. Filipendulenion) for Germany (7909 relevés) and the Czech Republic (1287 relevés) in this respect. In TWINSPAN, the indicator ordination option was used for classification of two national data sets, and the extracted assignment criteria (indicator species) were applied crosswise from one to the other national data set. Although the data sets presumably contained similar community types, TWINSPAN revealed almost no correspondence between the groups derived from the proper classification of the national data set and the groups defined by the assignment criteria taken from the other national data set. The reason is probably the difference in structure between the national data sets, which is a typical, but hardly avoidable, feature of any pair of phytosociological data sets. As a result, the first axis of the correspondence analysis, and consequently the first TWINSPAN division, are associated with different environmental gradients; the difference in the first division is transferred and multiplied further down the hierarchy. COCKTAIL is a method which produces relevé groups on the basis of statistically formed species groups. The user determines the starting points for the formation of species groups, and groups already found in one data set can be tested for existence in the other data set. The correspondence between the national classifications produced by COCKTAIL was fairly good. For some relevé groups, the lack of correspondence to groups in the other national data set could be explained by the absence of the corresponding vegetation types in one of the countries, rather than by methodological problems.     

Numerical reproduction of traditional classifications and automatic vegetation identification

Questions: Is it possible to develop an expert system to provide reliable automatic identifications of plant communities at the precision level of phytosociological associations? How can unreliable expert‐based knowledge be discarded before applying supervised classification methods? Material: We used 3677 relevés from Catalonia (Spain), belonging to eight orders of terrestrial vegetation. These relevés were classified by experts into 222 low‐level units (associations or sub‐associations). Methods: We reproduced low‐level, expert‐defined vegetation units as independent fuzzy clusters using the Possibilistic C‐means algorithm. Those relevés detected as transitional between vegetation types were excluded in order to maximize the number of units numerically reproduced. Cluster centroids were then considered static and used to perform supervised classifications of vegetation data. Finally, we evaluated the classifier's ability to correctly identify the unit of both typical (i.e. training) and transitional relevés. Results: Only 166 out of 222 (75%) of the original units could be numerically reproduced. Almost all the unrecognized units were sub‐associations. Among the original relevés, 61% were deemed transitional or untypical. Typical relevés were correctly identified 95% of the time, while the efficiency of the classifier for transitional data was only 64%. However, if the second classifier's choice was also considered, the rate of correct classification for transitional relevés was 80%. Conclusions: Our approach stresses the transitional nature of relevé data obtained from vegetation databases. Relevé selection is justified in order to adequately represent the vegetation concepts associated with expert‐defined units.     

The management of vegetation classifications with fuzzy clustering

Questions: Does fuzzy clustering provide an appropriate numerical framework to manage vegetation classifications? What is the best fuzzy clustering method to achieve this? Material: We used 531 relevés from Catalonia (Spain), belonging to two syntaxonomic alliances of mesophytic and xerophytic montane pastures, and originally classified by experts into nine and 13 associations, respectively. Methods: We compared the performance of fuzzy C‐means (FCM), noise clustering (NC) and possibilistic C‐means (PCM) on four different management tasks: (1) assigning new relevé data to existing types; (2) updating types incorporating new data; (3) defining new types with unclassified relevés; and (4) reviewing traditional vegetation classifications. Results: As fuzzy classifiers, FCM fails to indicate when a given relevé does not belong to any of the existing types; NC might leave too many relevés unclassified; and PCM membership values cannot be compared. As unsupervised clustering methods, FCM is more sensitive than NC to transitional relevés and therefore produces fuzzier classifications. PCM looks for dense regions in the space of species composition, but these are scarce when vegetation data contain many transitional relevés. Conclusions: All three models have advantages and disadvantages, although the NC model may be a good compromise between the restricted FCM model and the robust but impractical PCM model. In our opinion, fuzzy clustering might provide a suitable framework to manage vegetation classifications using a consistent operational definition of vegetation type. Regardless of the framework chosen, national/regional vegetation classification panels should promote methodological standards for classification practices with numerical tools.     

Synanthropic vegetation of the <Emphasis Type="Italic">Eragrostion cilianensi-minoris</Emphasis> alliance in the Czech Republic

A synthesis of the alliance Eragrostion cilianensi-minoris in the Czech Republic is presented on the basis of 82 relevés including new unpublished data. A TWINSPAN classification and detrended correspondence analysis were used to identify the main vegetation types included in the alliance Eragrostion cilianensi-minoris. A syntaxonomic revision of the data set revealed five associations of the alliance: Digitario sanguinalis-Eragrostietum minoris, Portulacetum oleraceae, Eragrostio poaeoidis-Panicetum capillaris, Cynodontetum dactyli, and Hibisco trioni-Eragrostietum poaeoidis. The latter was recently found in several arable fields in Southern Moravia (Czech Republic) and was newly characterized.     

Plot sizes used for phytosociological sampling of European vegetation

Abstract. In European phytosociology, variable plot sizes are traditionally used for sampling different vegetation types. This practice may generate problems in current vegetation or habitat survey projects based on large data sets, which include relevés made by many authors at different times. In order to determine the extent of variation in plot sizes used in European phytosociology, we collected a data set of 41 174 relevés with an indication of plot size, published in six major European journals focusing on phytosociology from 1970 to 2000. As an additional data set, we took 27 365 relevés from the Czech National Phytosociological Database. From each data set, we calculated basic statistical figures for plot sizes used to sample vegetation of various phytosociological classes. The results show that in Europe the traditionally used size of vegetation plots is roughly proportional to vegetation height; however, there is a large variation in plot size, both within and among vegetation classes. The effect of variable plot sizes on vegetation analysis and classification is not sufficiently known, but use of standardized plot sizes would be desirable in future projects of vegetation or habitat survey. Based on our analysis, we suggest four plot sizes as possible standards. They are 4 m² for sampling aquatic vegetation and low‐grown herbaceous vegetation, 16 m² for most grassland, heathland and other herbaceous or low‐scrub vegetation types, 50 m² for scrub, and 200 m² for woodlands. It has been pointed out that in some situations, sampling in either small or large plots may result in assignment of relevés to different phytosociological classes or habitat types. Therefore defining vegetation and habitat types as scale‐dependent concepts is needed.     

Phytosociological data give biased estimates of species richness

Abstract. Large phytosociological data sets of three types of grassland and three types of forest vegetation from the Czech Republic were analysed with a focus on plot size used in phytosociological sampling and on the species‐area relationship. The data sets included 12975 relevés, sampled by different authors in different parts of the country between 1922 and 1999. It was shown that in the grassland data sets, the relevés sampled before the 1960s tended to have a larger plot size than the relevés made later on. No temporal variation in plot sizes used was detected in forest relevés. Species‐area curves fitted to the data showed unnatural shapes, with levelling‐off or even decrease in plot sizes higher than average. This distortion is explained by the subjective, preferential method of field sampling used in phytosociology. When making relevés in species‐poor vegetation, researchers probably tend to use larger plots in order to include more species. The reason for this may be that a higher number of species gives a higher probability of including presumed diagnostic species, so that the relevé can be more easily classified in the Braun‐Blanquet classification system. This attitude of phytosociologists has at least two consequences: (1) in phytosociological data bases species‐poor vegetation types are underrepresented or relevés are artificially biased towards higher species richness; (2) the suitability of phytosociological data for species richness estimation is severely limited.     

Local ranges of phytosociological associations: are they reflected in numerical classification?

In the tradition of European phytosociology, delimitations of vegetation units such as associations are mostly based on data from small areas where more detailed vegetation sampling has been carried out. Such locally delimited vegetation units are often accepted in large-scale synthetic classifications, e.g. national vegetation monographs, and tentatively assigned to a small geographical range, forming groups of similar (vicarious) vegetation units in different small areas. These vicarious units, however, often overlap in species composition and are difficult to recognize from each other. We demonstrate this issue using an example of the classification of dry grasslands (Festuco-Brometea) in the Czech Republic. The standard vegetation classification of the Czech Republic supposes that the majority of accepted associations (66 out of 68) have a restricted distribution in one of the two major regions, Bohemia or Moravia. We compared the classification into traditional associations with the numerical classification of 1440 phytosociological relevés from the Czech Republic, in order to test whether the traditionally recognized associations with small geographical ranges are reflected in numerical classification. In various comparisons, the groups of relevés identified by numerical analysis occupied larger areas than the traditional associations. This suggests that with consistent use of total species composition as the vegetation classification criterion, the resulting classification will usually include more vegetation units with larger geographical ranges, while many of the traditional local associations will disappear.     

A phytosociological classification of Swiss mire vegetation

The mapping and monitoring of Swiss mires has so far relied on a classification system based on expert judgement, which was not supported by a quantitative vegetation analysis and which did not include all wetland vegetation types described in the country. Based on a spatially representative sample of 17,608 relevés from 112 Swiss mires, we address the following questions: (1) How abundant are wetland vegetation types (phytosociological alliances) in Swiss mires? (2) How are they distributed across the country––is there a regional pattern? (3) How clearly are they separated from each other? (4) How clear and reliable is their ecological interpretation? Using published wetland vegetation relevés and lists of diagnostic species for phytosociological units (associations and alliances) established by experts, we developed a numerical method for assigning relevés to units through the calculation of similarity indices. We applied this method to our sample of 17,608 relevés and estimated the total area covered by each vegetation type in Switzerland. We found that vegetation types not included in previous mapping were either rare in Switzerland (partly due to mire drainage) or poorly distinguished from other vegetation units. In an ordination, the Swiss mire vegetation formed a triangular gradient system with the Sphagnion medii, the Caricion davallianae and the Phragmition australis as extreme types. Phytosociological alliances were clearly separated in a subset of 2,265 relevés, which had a strong similarity to one particular association, but poorly separated across all relevés, of which many could not be unequivocally assigned to one association. However, ecological gradients were reflected equally well by the vegetation types in either case. Overall, phytosociological alliances distinguished until now proved suitable schemes to describe and interpret vegetation gradients. Nevertheless, we see the urgent need to establish a data base of Swiss wetland relevés for a more reliable definition of some vegetation units.     

Bayesian classification of vegetation types with Gaussian mixture density fitting to indicator values

Question: Is it possible to mathematically classify relevés into vegetation types on the basis of their average indicator values, including the uncertainty of the classification? Location: The Netherlands. Method: A large relevé database was used to develop a method for predicting vegetation types based on indicator values. First, each relevé was classified into a phytosociological association on the basis of its species composition. Additionally, mean indicator values for moisture, nutrients and acidity were computed for each relevé. Thus, the position of each classified relevé was obtained in a three‐dimensional space of indicator values. Fitting the data to so called Gaussian Mixture Models yielded densities of associations as a function of indicator values. Finally, these density functions were used to predict the Bayesian occurrence probabilities of associations for known indicator values. Validation of predictions was performed by using a randomly chosen half of the database for the calibration of densities and the other half for the validation of predicted associations. Results and Conclusions: With indicator values, most reléves were classified correctly into vegetation types at the association level. This was shown using confusion matrices that relate (1) the number of relevés classified into associations based on species composition to (2) those based on indicator values. Misclassified relevés belonged to ecologically similar associations. The method seems very suitable for predictive vegetation models.     

Syntaxonomical revision of the Triseto flavescentis-Polygonion bistortae alliance in the Carpathians

Abstract

This phytosociological study of the Carpathian species-rich mesophilous mountain hay meadows (Triseto flavescentis-Polygonion bistortae alliance, Molinio-Arrhenatheretea class) presents the first unified large-scale classification system in four countries: Slovakia, Poland, Romania and Ukraine. The starting dataset contained relevés of the Molinio-Arrhenatheretea, Mulgedio-Aconitetea and Nardetea strictae classes. Numerical classification and semi-supervised classification by K-means method were used for the analyses. An electronic expert system and diagnostic species for grassland vegetation served for identification of a priori groups in K-means method. The final dataset contained 612 relevés. Altitude, climatic data and Ellenberg indicator values were used for ecological differentiation of syntaxa. The main gradients in floristic composition were analysed by Detrended Correspondence Analysis. Finally, the eight well-differentiated associations and one newly described association were determined: Campanulo glomeratae-Geranietum sylvatici, Geranio sylvatici-Trisetetum flavescentis, Crepido mollis-Agrostietum capillaris, Geranio-Alchemilletum crinitae, Alchemillo-Deschampsietum caespitosae, Phyteumo (orbicularis)-Trifolietum pratensis, Astrantio-Trisetetum flavescentis, Trollio altissimi-Knautietum dipsacifoliae and Violo declinatae-Agrostietum capillaris ass. nova. The differences in vegetation diversity of mountain hay meadows between particular countries were confirmed: Alchemillo-Deschampsietum caespitosae occurs in all studied territories, Campanulo glomeratae-Geranietum sylvatici occurs predominantly in Slovakia and the newly described association Violo declinatae-Agrostietum capillaris ass. nova could be found only in Ukraine.     

Formalized classification of the vegetation of <Emphasis Type="Italic">Abies alba</Emphasis>-dominated forests in the Czech Republic

A phytosociological classification of silver fir (Abies alba) forests in the Czech Republic was carried out using the Braun-Blanquet approach. It is based on the formalized and supervised Cocktail classification method. The definitions of associations were created by combinations of sociological species groups using logical operators. Dominance of single species was included in the definitions of associations. All relevés with at least 50% cover of silver fir in tree layer available from the Czech Republic were used for analysis. Three associations within two classes were distinguished. Vaccinio vitis-idaeae-Abietetum albae (Vaccinio-Piceetea, Piceion excelsae) is an oligotrophic, species-poor spruce-pine-fir forest dominated by Vaccinium myrtillus in the herb layer occurring mostly on podzols. Luzulo-Abietetum albae (Querco-Fagetea, Luzulo-Fagion) is an oligo-mesotrophic spruce-fir forest characterized by the dominance of graminoids (Luzula luzuloides, Calamagrostis arundinacea) in the herb layer. It occurs especially on cambisols. Nutrient-demanding species are typical of the stands of herb-rich mesotrophic Galio rotundifolii-Abietetum albae (Querco-Fagetea, Fagion sylvaticae, Galio rotundifolii-Abietenion) that occurs also mostly on cambisols. Soil nutrients and soil reaction (represented by Ellenberg indicator values) were determined as the most important ecological gradients affecting the variation of the vegetation in these communities.     

Formal definitions of Slovakian mire plant associations and their application in regional research

We applied the Cocktail method to a large data set of 4 117 relevés of all Slovak vegetation types with the aim to create formalised definitions of all Slovakian mire plant associations. We defined 21 groups of species with the statistical tendency of joint occurrences in vegetation. These groups differed substantially in their position along the pH/calcium gradient. We further defined 24 plant associations according to presence and/or absence of certain groups and/or strong dominance of some species. Only six traditional plant associations were not possible to be reproduced this way. We applied our formalised definitions to the regional data set of mires from the surrounding of the Vysoké Tatry Mts. Combined with frequency-positive fidelity index this method has led to the classification of the majority of vegetation plots into ten associations. When the vegetation types obtained from Cocktail-based classification and from cluster analysis were compared with respect to measured pH and conductivity in the study region, 82% of pairs differed significantly either in pH or in water conductivity in the former classification and 69% in the latter one.     

Trends in species diversity and composition of urban vegetation over three decades

Question: What was the change in diversity of urban synantropic vegetation in a medium‐sized Central European city during the period of increasing urbanization (1960s‐1990s)? Location: The city of Plzeň, an industrial centre of the western part of the Czech Republic. Methods: Sampling of various types of synanthropic vegetation, conducted in the 1960s, was repeated by using the same methods in the 1990s. This yielded 959 relevés, of which 623 were made in the 1960s and 336 in the 1990s. The relevés were assigned to the following phytosociological classes: Chenopodietea, Artemisietea vulgaris, Galio‐Urticetea, Agropyretea repentis and Plantaginetea majoris. Total number of vascular plant species, evenness index J, number of alien species (classified into archaeophytes and neophytes), and mean Ellenberg indicator values for light, temperature, continentality, moisture, soil reaction, and nutrients were obtained for each relevé. Results: From 1960s to 1990s, there was a significant decrease of species richness and diversity in synanthropic vegetation. The proportion of archaeophytes decreased in most vegetation types, indicating the contribution of this group of species, often confined to specific rural‐like habitats, to the observed impoverishment of ruderal vegetation. The proportion of neophytes did not change between the two periods. Comparison between 1960s and 1990s indicated a decrease in light, temperature, moisture, soil reaction and nutrient indicator values in some vegetation types. In both periods, Artemisieta, Galio‐Urticetea and Chenopodietea formed a distinct group harbouring more species than Agropyretea and Plantaginetea. Neophytes, i.e. recently introduced species, were most represented in the early successional annual vegetation of Chenopodietea, rather than in perennial vegetation of the other classes. Conclusions: Synanthropic vegetation of Plzeň exhibited a general trend of decrease in species diversity.     

Variability of the <Emphasis Type="Italic">Molinion</Emphasis> meadows in Slovakia

Nine vegetation types were distinguished using cluster analysis within Molinion meadows in Slovakia. Vegetation of cluster 1 occurs on most acidic soils and is characterized by the occurrence of species of the Caricion fuscae alliance and of the Nardus grasslands. Vegetation of cluster 2 is also found on rather acidic soils but in contrast to cluster 1 vegetation it contains species of base-rich sites, such as Betonica officinalis, Galium boreale or Serratula tinctoria. Vegetation of cluster 3 occurs in wet base-rich habitats and often contains species of the Caricion davallianae alliance. Species of dry and Nardus grasslands are typical for vegetation of cluster 4, which is found at the driest sites and is confined to oligotrophic sandy soils. Vegetation of clusters 5 and 6 occurs on moist mesotrophic soils. Their species composition is quite similar, the main difference being that the former includes species-poor relevés and the latter includes species-rich relevés. Relevés of cluster 7 include species of dry grasslands and some ruderal species and represent degraded types of inundated floodplain meadows of the Deschampsion alliance. Vegetation of clusters 8 is characterized by species of the Phragmito-Magnocaricetea class and of the Deschampsion alliance, and occurs in wet nutrient-rich habitats. Vegetation of cluster 9, which usually develops from vegetation of cluster 8 due to decrease in the ground-water table, often contains species of dry grasslands and mesic meadows. Except for relevés of clusters 1 and 7, all others can be assigned to the Molinietum caeruleae Koch 1926 association. Cluster 1 corresponds to the Junco effusi-Molinietum caeruleae Tüxen 1954 association. Average Ellenberg indicator values for relevés, which were passively projected on the ordination biplot of detrended correspondence analysis, showed that the first ordination axis correlates with nutrients, soil base status and temperature, and second axis with moisture.     

Contribuzione alla flora algologica del mare Adriatico

The specific species-rich high-altitude vegetation of the class Carici rupestris-Kobresietea bellardii Ohba 1974 (CK), with the occurrence of many arctic-alpine and endemic species, was chosen for a case study. The analyses were based on a dataset of 37,204 phytosociological relevés from the Slovak Vegetation Database. The traditional classification of the class CK, based on cluster analyses, was reproduced satisfactorily by means of formalised classification, based on the formal definitions created by the Cocktail method together with the frequency-positive fidelity index affiliation. Unequivocal assignment criteria for all eight associations of both alliances [Oxytropido-Elynion Br.-Bl. (1948) 1949 and Festucion versicoloris Krajina 1933] of the class CK were formulated. The formal delimitations followed the traditional ones very well. It was demonstrated that the results of applying the formal definitions created on the basis of a large, geographically stratified dataset capturing the occurrence of all vegetation types in Slovakia were highly similar in comparison with the traditional classification based on the results of cluster analysis. The reliability and the pros and cons of the expert system are also discussed.     

Plant communities structure and composition in three coastal wetlands in southern Apulia (Italy)

In this paper the results of a study on the composition and the distribution of the plant communities in three coastal areas of southern Apulia are presented. A total of about 180 vegetation relevés were performed following the Braun-Blanquet phytosociological method. Vegetation data were analysed using both classification (UPGMA, similarity ratio) and ordination methods (including Non-metric Multidimensional Scaling (NMS) and Detrended Correspondence Analysis (DCA). The relevés are distributed in the following classes: Molinio-Arrhenateretea, Phragmito-Magnocaricetea, Juncetea maritimi, Sarcocornietea fruticosae, Saginetea maritimae, Thero-Salicornietea, Helianthemetea guttati. Detailed information about structure and zoning of the detected plant communities are here provided. Two new associations, belonging to the Alkanno-Maresion nanae alliance (microphytic ephemeral plant communities growing on sandy soils, Helianthemetea guttati class) have been described here, both in the “Torre Guaceto” site. The area of “Le Cesine” showed the highest total number of plant communities, while the “Saline di Punta della Contessa” site revealed the largest number of Sarcocornietea fruticosae plant communities.     

How reliable are our vegetation analyses?

Abstract. Two sets of 40 relevés, made independently by two observers on the same 5m x 5m sample plots, were compared to estimate the sampling error and to assess the effect of this sampling error on (1) estimates of species richness and diversity (2) results of multivariate analyses, and (3) estimation of species turnover in repeated sampling. The relevés were made according to the standard Braun-Blanquet method. The sampling error was estimated for (1) recording of species in sample plots and (2) visual estimation of the degree of cover (or of the general population size). Despite the fact that the sample plots were searched thoroughly for 30 - 40 min, the number of overlooked species was high with a discrepancy of 13% between corresponding relevés. Regarding multivariate analysis, the error caused by missing species was at least as important as the error in visual estimation of species cover. The estimates of degree of cover using the Braun-Blanquet scale are sufficiently reliable for use in multivariate analysis when they are subjected to ordinal transformation. When average cover values are used, the patterns detected are based solely on dominants. Species richness and species diversity could be reliably estimated from the relevés, but the estimates of equitability are very unreliable. The classical relevé method remains one of the most efficient survey methods for recognition of vegetation types on the macro-community and landscape scales.     

Classification of weed vegetation of arable land in the Czech Republic and Slovakia

Numerical classification of 2653 geographically stratified relevés of weed vegetation from the Czech and Slovak Republics was performed with cluster analysis. Diagnostic species were determined for each of the seven main clusters using statistical measures of fidelity. The classification reflected clear distinctions between lowland (mostly calcicole) and highland (mostly calcifuge) sites, spring and summer phenological stages, and cereals and root crops. The results of the cluster analysis were compared with traditional phytosociological units. Two clusters corresponded to calcifuge weed vegetation of theScleranthion annui alliance; one cluster represented the vegetation of root crops on moist soils of theOxalidion europaeae alliance; one cluster contained thermophilous weed vegetation of theCaucalidion lappulae alliance; two clusters included weed vegetation of root crops and of stubble fields, which can be assigned to theCaucalidion, Panico-Setarion,Veronico-Euphorbion andEragrostion alliances; one cluster included vernal weed vegetation in little disturbed habitats of theCaucalidion lappulae andScleranthion annui alliances. Our analysis did not support the concept of theSherardion andVeronico-Taraxacion alliances, which were included in earlier overviews of the vegetation units of the Czech Republic and Slovakia.