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.     

Arranging phytosociological tables by species-relevé groups

Abstract. A newmethod of arranging phytosociological tables by species-relevé groups (blocks) on the basis of the density of rows and columns (relative species frequency and relative species number) is presented. Each block fulfils a given minimum criterion regarding its density. With a density threshold of e.g. 50 %, blocks are formed with only those species that are present in at least 50 % of the block's relevés, while at the same time the block's relevés comprise at least 50 % of the block's species. The procedure starts with the complete table and iteratively masks species and relevés with the smallest densities. This is performed step by step with species and relevés and continues until the given density threshold for all species and relevés is exceeded. Without any further parameters other than the minimum density, species-relevé groups of gradually decreasing size are formed. Data processing is performed with a computer program (ESPRESSO). The main application of the method is found in an effective pre-sorting of relevé data. The blocks formed can be arranged in the final table as desired.     

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.     

Neophyte Invasion in Moldavia (Eastern Romania) in Different Habitat Types

The actual state of neophyte invasion in Moldavia (Eastern Romania) is described in this paper on the basis of 11,055 phytosociological relevés. We analyzed the i) proportion of relevés with neophytes, ii) mean proportion of neophytes per relevés, and iii) mean coverage of neophytes per relevé for 36 EUNIS habitat types to identify general plant invasion patterns. The level of invasion differed considerably between habitats. The invasion of neophytes especially affected habitats strongly determined or influenced by man, such as anthropogenic woodlands, ruderal habitats, arable lands or trampled areas. Most natural habitats are either slightly invaded or entirely free of neophytes. Only riverine willow stands and wet tall-herb stands are relatively highly invaded. However, the absence of neophytes in some natural habitats less represented in the phytosociological dataset could be of artifactual nature. No significant relationship between the number of neophytes and non-neophytes was found in the analysis across different habitats. When the analyses were made within-habitats, both negative and positive relationships were found, which confirm that the relationship between alien and native species richness depends on the habitats. A total number of 105 neophyte species were recorded in the phytosociological relevés used in this study. Among these, 13 species that are currently considered invasive in Moldavia occur in at least 10 types of habitats.     

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.     

TURBOVEG,a comprehensive data base management system for vegetation data

Abstract. The computer software package TURBOVEG (for Microsoft® Windows®) was developed in The Netherlands for the processing of phytosociological data. This package comprises an easy‐to‐use data base management system. The data bank to be managed can be divided into several data bases which may consist of up to 100 000 relevés each. The program provides methods for input, import, selection, and export of relevés. In 1994, TURBOVEG was accepted as the standard computer package for the European Vegetation Survey. Currently it has been installed in more than 25 countries throughout Europe and overseas.     

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.     

Some notes on estimation of the basic homoteneity-coefficient of sets of phytosociological relevés

The formula for calculation of the basic homotoneity-coefficient of sets of phytosociological relevés does not give adequate values for sets of 4 or 3 relevés. Therefore an empirical correction procedure is proposed for the calculation of this coefficient for such small sets of relevés. For sets of 2 relevés the calculation of the basic homotoneity-coefficient gives values equal toSørensen’s coefficient of floristic similarity. A simplification of calculation of the basic homotoneity-coefficient for sets of more than 20 relevés is proposed.     

A simple method for estimating homotoneity of sets of phytosociological relevés

The homogeneity of sets of phytosociological relevés or syntaxa—the homotoneity—is tested by means of a homotoneity-coefficient. This coefficient consists of the basic homotoneity-coefficient expressing the proportion of highly constant species (61–100%) in the species composition of the average relevé and the correcting factor which is proportional to the difference of species number between the richest and poorest relevé. Successive analysis of heterotoneity of sets of relevés for detecting sources of heterotoneity is proposed.     

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.     

Assignment of relevés to pre‐defined classes by supervised clustering of plant communities using a new composite index

Question: How does a newly designed method of supervised clustering perform in the assignment of relevé (species composition) data to a previously established classification. How do the results compare to the assignment by experts and to the assignment using a completely different numerical method? Material: Relevés analysed represent 4186 Czech grassland plots and 4990 plots from a wide variety of vegetation types (359 different associations or basal communities) in The Netherlands. For both data sets we had at our disposal an expert classification, and for the Czech data we also had available a numerical classification as well as a classification based on a neural network method (multi‐layer perceptron). Methods: Two distance indices, one qualitative and one quantitative, are combined into a single index by weighted multiplication. The composite index is a distance index for the dissimilarity between relevés and vegetation types. For both data sets the classifications by the new method were compared with the existing classifications. Results: For the Czech grasslands we correctly classified 81% of the plots to the classes of an expert classification at the alliance level and 71% to the classes of the numerical classification. Correct classification rates for the Dutch relevés were 64, 78 and 83 % for the lowest (subassociation or association), association, and alliance level, respectively. Conclusion: Our method performs well in assigning community composition records to previously established classes. Its performance is comparable to the performance of other methods of supervised clustering. Compared with a multi‐layer perceptron (a type of artificial neural network), fewer parameters have to be estimated. Our method does not need the original relevé data for the types, but uses synoptic tables. Another practical advantage is the provision of directly interpretable information on the contributions of separate species to the result.     

Patterns of plant species composition on Amazonian sandstone outcrops in Colombia

Vascular plant species compositional patterns of the low forest, scrub, and herbaceous vegetation on white sand soils and sandstone substrates were studied at six sandstone plateaus in Colombian Amazonia, by means of a field survey according to the Braun‐Blanquet relevé method. Canonical Correspondence Analysis (CCA) was applied to separate effects of habitat and spatial configurations of the plateaus on species patterns. Also, information on dispersal ability and phytogeographic affinity of species was used to test explanations for between plateau differences. Low trees, shrubs and herbs were the main species recorded in 212 relevés. The main gradients in the species patterns were linked to the spatial configuration of the plateaus. Spatially controlled species patterns were mainly related to soil depth and soil organic matter. The association between phytogeographic affinity and the habitat controlled spatial link of species pointed at insufficient sampling at one plateau. Dispersal ability did not explain the habitat controlled spatially distributed occurrences of plant species. This might indicate a low frequency of local extinctions at the sandstone plateaus, especially of the poorly dispersed species, possibly because plant populations survive fire or drought disturbances in local sheltered places. Space and habitat controlled species patterns at one plateau were quite distinct from patterns at the other plateaus. This might be due to unmeasured habitat factors (e.g. unrecorded soil variation or human disturbance history) or the preferential, surveyor biased sampling procedure.     

Diversity change of mountain hay meadows in the Swiss Alps

We investigated changes in plant diversity in the traditionally fertilised and species-rich Golden Oat meadows by repeating historic grassland relevés from the 1940s in two agricultural areas in the Swiss Alps. The effects of time on alpha and beta diversity at plot level were analysed within the study areas. The specificity of the two study areas was investigated by comparing the variability of species composition within and between study areas.In both regions, species richness at plot level (alpha diversity) was found to be lower in the recent relevés than in the historic ones. However, the variability of species composition within the study areas (beta diversity) was higher between the recent relevés than between the historic relevés. There was a significant floristic differentiation between the two study areas sixty years ago but not today.Plant diversity in Golden Oat meadows has changed significantly during the last sixty years. The decrease in species richness at plot level was anticipated, but not the increase in beta diversity between plots, which may indicate individualised management regimes of modern farmers. The loss of specificity between the study areas revealed an important and as yet hardly considered further dimension of biodiversity change, which leads to a homogenisation of plant diversity at a regional level.     

Computer assisted floristic similarity analysis

A program for polythetic numerical evaluation of phytosociological material is described. Using Sörensen's coefficient of floristic similarity it computes the homogeneity of subjectively chosen sets of relevés, the affinity of each constituent relevé to the set as well as the similarity between any pair of sets. It is also able to plot a dendrogram of the hierarchic system obtained by agglomerating individual relevés into complex groupings. The program is suitable for processing phytosociological data arranged in any conventional table.     

Current knowledge and phytosociological data on the high-altitude vegetation in the Western Carpathians — a review

Presented survey summarizes the results of the studies published predominantly after 2000, dealing with the plant communities around and above the timberline in (montane) subalpine to alpine (subnival) belt of the Western Carpathians. All of these communities underwent a critical syntaxonomical and nomenclatorical revision, hence the demonstrated overview of high-mountain vegetation of Western Carpathians (mostly from Slovakia, less from Poland border areas) represent the current state of knowledge. The high-altitude vegetation database, which is the part of Slovak National Vegetation Database, SNVD (), incorporated 8,160 published relevés on 15 May 2007 (of the total of 30,469 published relevés in the SNVD). Concerning the unpublished relevés, the individual authors have provided more than 18,400 of them to be stored in SNVD; 2,301 of all unpublished relevés could be assigned to high-altitude vegetation. Mountain and alpine vegetation is in SNVD presented by 15 classes; the most frequent class is Mulgedio-Aconitetea. With its quantity and also the quality of relevés, the high-altitude database, as well as the whole SNVD, represents the unique database within Slovakia, which provides information not only about the locality, floristic composition and variability of individual vegetation types, but also about several environmental variables such as inclination, aspect, geology or soil type, characteristic for individual relevés. Together with other Central European databases, SNVD takes up the leading position in Europe.     

Sul grado di accestimento delle piante di grano colpite dalla “Carie„

Abstract

We numerically analysed 154 relevés of Potentillo chrysocraspedae–Festucetum airoidis in order to review the compositional variability of these grasslands, the main eco-floristic gradients and the representativeness of the lectotype. Apart from 30 small-sized clusters composed of singular or transitional relevés (outliers), three distinctive groups of 77, 19 and 12 communities were finally retained and denominated as typical (TP), closed (CL) and open (OP) facies, as they were significantly different in terms of total species cover. The three facies are well separated but do not form distinctive clusters in the non-metric multidimensional scaling (NMDS) ordination space. Juncus trifidus and Agrostis rupestris are the best differential species of OP and TP, respectively, whereas the best discriminator of CL is the higher cover of F. airoides. There are no significant differences between the three facies regarding altitude. The floristic structure of CL indicates poorer but moister soils compared with the other facies. CL may represent either a post-disturbance, recovery phase following sheep overgrazing and intensive trampling, or a late seral stage. OP gathers communities that are little disturbed and mainly occur on ridges and upper, sunny slopes. Although well distinguished floristically, TP is weakly defined in terms of homotoneity and complexity of the core species assemblage. The most representative relevé of TP is poorer in character species than the relevé lectotype (5 versus 12), the latter being classified as an outlier in terms of normal specific assemblage. Such patterns may reflect the spatio-temporal heterogeneity in alpine grasslands due to uncontrolled, intensive grazing and stochastic natural disturbances.     

Classification and gradient analysis of the beech forest vegetation of the southern Rodopi (northeast Greece)

Pure and mixed beech forest vegetation of the southern Rodopi range (northeast Greece) was studied using 614 relevés and multivariate analyses (TWINSPAN and DCA). Classification of the relevés resulted in 12 vegetation units, 8 of which were ranked as associations or communities and the rest as subcommunities and variants. DCA diagrams of relevés and taxa indicated that floristic differentiation was attributed mainly to factors such as altitude (affecting temperature and humidity), soil nutrient content and substrate type (affecting physical and chemical soil properties). Differential taxa of vegetation units were chosen based on their phi coefficient values, which were calculated from three different percentage synoptic tables that corresponded to three ranks (ecological groups, associations and communities, and subcommunities and variants) of floristic differentiation. The calculation of phi coefficient on the basis of relative constancy of taxa helps to overcome the problem of the dependence of fidelity values on the number of relevés per vegetation unit and to facilitate the better investigation of the floristic differentiation even of rare vegetation units represented by a small number of relevés. Furthermore, the calculation of fidelity values for different hierarchical levels enables a more detailed and thorough investigation of the floristic differentiation of the vegetation units.     

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.     

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.     

Malcolmia littorea: The isolated Italian population in the European context

We compared the coenological information of the only Italian population of Malcolmia littorea (L.) R. Br. with published phytosociological relevés, including ones of this species, throughout its European range. With the aim of highlighting the main climatic features influencing the distribution patterns of M. littorea, we integrated coenological data with some climatic variables and considered major drivers for plant distribution at the European scale. Finally, we analysed the population extent of M. littorea in Italy, in order to assess its conservation status at regional level. The DCA analysis, performed on a matrix 139 relevés × 183 species, separated the relevés according to their floristic composition, showing a geographic gradient from Portugal to Mediterranean coasts, until Italy; with Mediterranean relevés clearly separated from Atlantic ones as well. Along the beach-inland gradient, the analysis highlights that the species is typical of fixed dunes habitats (more inland, mainly stabilised dunes), although in the Atlantic it can also be found in mobile dunes. The analysis of climatic variables in relation to M. littorea distribution, suggested that the species is sensitive to low winter temperature and to summer drought. The only Italian population of M. littorea is subjected to many threats, due to its small dimensions (<1 ha), isolation from the rest of its distribution area, that ranges from Portugal to France (until the Camargue region) and intensive human disturbances. Using both field and remote sensing information, we showed a considerable decrease of the occupied surface in Italy, leading us to suggest that the IUCN threat category of M. littorea in Italy should be reassessed from endangered to critically endangered.