JUICE,software for vegetation classification

Abstract. The program JUICE was designed as a Microsoft® WINDOWS® application for editing, classification and analysis of large phytosociological tables and databases. This software, with a current maximum capacity of 30 000 relevés in one table, includes many functions for easy manipulation of table and header data. Various options include classification using COCKTAIL and TWINSPAN methods, calculation of interspecific associations, fidelity measures, average Ellenberg indicator values, preparation of synoptic tables, automatic sorting of relevé tables, and export of table data into other applications (word processors, spreadsheet programs or mapping packages). JUICE is optimized for use in association with TURBOVEG which is the most widespread database program for storing phytosociological data in Europe.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Geographical and ecological differentiation in Greek Fagus forest vegetation

Question: Which are the gradients of floristic differentiation in Greek beech (Fagus sylvatica) forests? Which is the role of geographical and ecological factors in this differentiation? Location: Beech forests of the plant geographical regions Northeast, North Central and East Central Greece. Methods: A total of 1404 published and unpublished phytoso‐ciological relevés were used in the analyses. TWINSPAN and DCA were applied to classify and ordinate the relevés. Altitude, Indicator Values of relevés and their X and Y coordinates were used in a posteriori interpretation of the ordination axes. Kendall's correlation coefficients were calculated between DCA relevé scores and explanatory variables. Multiple linear regression was used to partition the variation explained by the first two DCA axes, between the geographical and the ecological variables. Results: Classification resulted in 14 vegetation units defined by species composition. Two types of gradients, ecological and geographical, were revealed by the DCA of all releves. The partition of the variation accounted for by the first and second DCA axis was attributed mainly to ecological and geographical variables, respectively. Conclusions: Beech forests of northeast and Central Greece show phytogeographical differences, while ecologically similar vegetation units occur in both regions. A west‐east gradient is revealed in Greek beech forest vegetation. The extent of the study area, its position along regional gradients and the comprehensiveness of the data set that is analysed determine the types of the gradients which can be revealed in a vegetation study.     

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.     

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.     

Common data standards for recording relevés in field survey for vegetation classification

Abstract. In the framework of the European Vegetation Survey common data standards are proposed for recording phytosociological relevés for syntaxonomical classification. The authors wish to establish the notion that common data standards for recording phytosociological data can only be advantageous for advancing the credibility and application of vegetation science, and may stimulate other projects.     

Effects of soil erosion on the floristic composition of plant communities on marl in northeast Spain

Abstract. This study explored the validity of three responses of vegetation to increased soil erosion: reduction of vegetation cover, number of species and reduced substitution of species. 201 relevés, including edaphic and geomorphological data, were surveyed in the intensely eroded Eocene marls of the Prepyrenees (NE Spain). Changes in plant species’ presence in relevés from different degradation stages were compared. The level of vegetation degradation was defined as the total phanerogam cover which, in the studied area, was correlated to the degree of soil erosion. The considered trends were validated. Reduction of phanerogam cover and species number were gradual from low to high‐eroded areas. Vegetation degradation explained 48% of the species number variance. In the later stages of degradation a significant substitution of species was not observed, only a lower frequency of occurrence of several species that appeared in the whole set of relevés. Through the process of degradation, 47% of species displayed significantly reduced frequencies as degradation increased, none showed a significant increase in frequency. It is concluded that there are no characteristic species in these plant communities that survive in the severely eroded marls. Among the few species that had increased in frequency, most only colonised favourable micro‐environments.     

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 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.     

Use of Phytosociological Databases for Species Distribution Models

Species Distribution Models are key in modern ecological studies. They employ information about species locations and environmental factors to generate statistical functions that predict the potential distribution of species on the basis of landscape suitability. Although these models are powerful and useful tools, often the required information about species distribution is lacking, and the only resources are pre-collected museum data. Phytosociological databases contain a myriad of relevés with precious information, but are often considered to be the exclusive ownership of vegetation scientists. Our study tested the efficiency of a phytosociological database in the building of Species Distribution Models, including spatial autocorrelation (SAC) as a predictor to evaluate its effects on model performance. Spatial autocorrelation (SAC) is a natural characteristic of species distribution that depends on exogenous and endogenous processes. The latter??s effects could be overestimated by a subjective sample choice. We chose Festuca riccerii, an Italian endemic species. We split the whole dataset (671 relevés) into a calibration (443 relevés) and testing set (228 relevés) and performed a GLM on these data to identify the main ecological factors that lead distribution in order to build a Species Distribution Model. The dataset??s efficiency was assessed by testing the predicting power of the calibrated model on the testing subset. The phytosociological database proved to be good for building model (AUC?=?0.821), providing a useful basis for fast and low cost ecological analysis, and could be used subsequently for more detailed analyses.     

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.     

Vegetation and environmental factors during primary succession on glacier forelands: Some outlines from the Italian Alps

ABSTRACT

Relationships between plant communities and the physical environment during primary succession on recently deglaciated glacier forelands were studied in 3 areas of the Italian Alps. The aim of the research was to relate traditional phytosociological data with environmental variables. Twenty-eight phytosociological relevés were performed, each associated with twenty-six environmental variables; quantitative parameters of richness and diversity were also calculated. Species/relevés, environmental variables/relevés and species/environmental variables matrices were analyzed by cluster analysis, PCA and Spearman correlation coefficient. Three main stages of succession were identified by floristic composition and confirmed by environmental parameter evaluation. A complex of environmental variables seems to be closely correlated with terrain age and richness/diversity parameters, even though diversity decreases in late successional stages. The phytosociological significance of species is in accordance with their position in the context of succession.     

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.