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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Validity of Ellenberg indicator values judged from physico‐chemical field measurements

Abstract. The relationship between mean Ellenberg indicator values (IV) per vegetation relevé and environmental parameters measured in the field usually shows a large variation. We tested the hypothesis that this variation is caused by bias dependent on the phytosociological class. For this purpose we collected data containing vegetation relevés and measured soil pH (3631 records) or mean spring groundwater level (MSL, 1600 records). The relevés were assigned to vegetation types by an automated procedure. Regression of the mean indicator values for acidity on soil pH and the mean indicator values for moisture on MSL gave percentages explained variance similar to values that were reported earlier in literature. When the phytosociological class was added as an explanatory factor the explained variance increased considerably. Regression lines per vegetation type were estimated, many of which were significantly different from each other. In most cases the intercepts were different, but in some cases their slopes differed as well. The results show that Ellenberg indicator values for acidity and moisture appear to be biased towards the values that experts expect for the various phytosociological classes. On the basis of the results, we advise to use Ellenberg IVs only for comparison within the same vegetation type.     

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.     

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.     

Semi‐dry grasslands along a climatic gradient across Central Europe: Vegetation classification with validation

Question: What is the variation in species composition of Central European semi‐dry grasslands? Can we apply a training‐and‐test validation approach for identifying phytosociological associations which are floristically well defined in a broad geographic comparison; can we separate them from earlier described associations with only a local validity? Location: A 1200 km long transect running along a gradient of increasing continentality from central Germany via Czech Republic, Slovakia, NE Austria, Hungary to NW Romania. Methods: Relevés with > 25% cover of Brachypodium pin‐natum and/or Bromus erectus were geographically selected from a larger database. They were randomly split into two data sets, TRAINING and TEST, each with 422 relevés. Cluster analysis was performed for each data set on scores from significant principal coordinates. Different partitions of the TRAINING data set were validated on the TEST data set, using a new method based on the comparison of % frequencies of species occurrence in clusters. Clusters were characterized by statistically defined groups of diagnostic species and values of climatic variables. Results: Species composition changed along the NW‐SE gradient and valid clusters were geographically well separated. Optimal partition level was at 11 clusters, six being valid: two clusters Germany and the Czech Republic corresponded to the Bromion erecti; two clusters from the Czech Republic and Hungary to the Cirsio‐Brachypodion, and two clusters were transitional between these two alliances. Conclusion: The training‐and‐test validation method used in this paper proved to be efficient for discriminating between robust clusters, which are appropriate candidates for inclusion in the national or regional syntaxonomic overviews, and weak clusters, which are specific to the particular classification of the given data set.     

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.     

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.     

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.     

Bias in Ellenberg indicator values — problems with detection of the effect of vegetation type

A recent analysis published in this journal found different relationships between mean Ellenberg indicator values and environmental measurements in different vegetation types. The cause was stated as bias in mean Ellenberg values between relevés which in turn suggested to reflect a bias in individual Ellenberg values. We discuss two phenomena that could explain these results without the need to invoke bias in either individual or mean Ellenberg values. Firstly, slopes of linear regression lines underestimate true relationships when analyses involve explanatory variables measured with error. Secondly, syntaxon‐specific distributions of Ellenberg values follow from the floristic definition of phytosociological units. Mean Ellenberg values per relevé therefore carry the stamp of their associated syntaxon even though associated abiotic conditions may vary between relevés. This will lead to variation in slopes and intercepts between vegetation types not because of bias in individual Ellenberg values but because of prescribed bias in the distribution of Ellenberg values between syntaxa. The residual variation in calibrations carried out across vegetation types is undoubtedly reduced by introducing vegetation type as a factor. However users should note that this is unlikely to reflect bias in individual Ellenberg values but is more likely to reflect error in environmental measurements as well the constraint imposed by phytosociological classification.     

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.     

Determination of diagnostic species with statistical fidelity measures

Abstract. Statistical measures of fidelity, i.e. the concentration of species occurrences in vegetation units, are reviewed and compared. The focus is on measures suitable for categorical data which are based on observed species frequencies within a vegetation unit compared with the frequencies expected under random distribution. Particular attention is paid to Bruelheide's u value. It is shown that its original form, based on binomial distribution, is an asymmetric measure of fidelity of a species to a vegetation unit which tends to assign comparatively high fidelity values to rare species. Here, a hypergeometric form of u is introduced which is a symmetric measure of the joint fidelity of species to a vegetation unit and vice versa. It is also shown that another form of the binomial u value may be defined which measures the asymmetric fidelity of a vegetation unit to a species. These u values are compared with phi coefficient, chi‐square, G statistic and Fisher's exact test. Contrary to the other measures, phi coefficient is independent of the number of relevés in the data set, and like the hypergeometric form of u and the chi‐square it is little affected by the relative size of the vegetation unit. It is therefore particularly useful when comparing species fidelity values among differently sized data sets and vegetation units. However, unlike the other measures it does not measure any statistical significance and may produce unreliable results for small vegetation units and small data sets. The above measures, all based on the comparison of observed/expected frequencies, are compared with the categorical form of the Dufrêne‐Legendre Indicator Value Index, an index strongly underweighting the fidelity of rare species. These fidelity measures are applied to a data set of 15 989 relevés of Czech herbaceous vegetation. In a small subset of this data set which simulates a phytosociological table, we demonstrate that traditional table analysis fails to determine diagnostic species of general validity in different habitats and large areas. On the other hand, we show that fidelity calculations used in conjunction with large data sets can replace expert knowledge in the determination of generally valid diagnostic species. Averaging positive fidelity values for all species within a vegetation unit is a useful approach to measure quality of delimination of the vegetation unit. We propose a new way of ordering species in synoptic species‐by‐relevé tables, using fidelity calculations.     

The terrestrial ruderal and segetal vegetation of North Korea: A synthesis

267 published and 32 unpublished phytosociological relevés from North Korea were synthesized. As a result, a revision of the units of the ruderal and segetal terrestrial vegetation known so far, and a discussion of their relationship to the analogous Japanese and European vegetation are presented. 17 associations and 4 communities at association level have been distinguished. They are assigned to the classesBidentetea (Bidentetalia, Panico-Bidention), Stellarietea mediae (Commelinetalia, Cassio-Phyllanthion, Cosmo-Humulion), Plantaginetea majoris (Plantaginetalia asiaticae, Plantaginion asiaticae) andMiscanthetea sinensis (Caricetalia nervatae; Zoysion japonicae).