A new measure of fidelity and its application to defining species groups

Abstract. The first objective of this paper is to define a new measure of fidelity of a species to a vegetation unit, called u. The value of u is derived from the approximation of the binomial or the hypergeometric distribution by the normal distribution. It is shown that the properties of u meet the requirements for a fidelity measure in vegetation science, i.e. (1) to reflect differences of a species’relative frequency inside a certain vegetation unit and its relative frequency in the remainder of the data set; (2) to increase with increasing size of the data set. Additionally (3), u has the property to be dependent on the proportion of the vegetation unit's size to the size of the whole data set. The second objective is to present a method of how to use the value of u for finding species groups in large data bases and for defining vegetation units. A species group is defined by possession of species that show the highest value of u among all species in the data set with regard to the vegetation unit defined by this species group. The vegetation unit is defined as comprising all relevés that include a minimum number of the species in the species group. This minimum number is derived statistically in such a way that fewer relevés always belong to a species group than would be expected if the differential species were distributed randomly among the relevés. An iterative algorithm is described for detecting species groups in data bases. Starting with an initial species group, species composition of this group and the vegetation unit defined by this group are mutually optimized. With this algorithm species groups are formed in a data set independently of each other. Subsequently, these species groups can be combined in such a way that they are suited to define commonly known syntaxa a posteriori.     

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.     

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.     

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.     

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.     

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.     

Using species‐environmental amplitudes to predict pH values from vegetation

Question: Species optima or indicator values are frequently used to predict environmental variables from species composition. The present study focuses on the question whether predictions can be improved by using species environmental amplitudes instead of single values representing species optima. Location: Semi‐natural, deciduous hardwood forests of northwestern Germany. Methods: Based on a data set of 558 relevés, species responses (presence/absence) to pH were modelled with Huisman‐Olff‐Fresco (HOF) regression models. Species amplitudes were derived from response curves using three different methods. To predict the pH from vegetation, a maximum amplitude overlap method was applied. For comparison, predictions resulting from several established methods, i. e. maximum likelihood/present and absent species, maximum likelihood/present species only, mean weighted averages and mean Ellenberg indicator values were calculated. The predictive success (squared Pearson's r and root mean square error of prediction) was evaluated using an independent data set of 151 relevés. Results: Predictions based upon amplitudes defined by maximum Cohen's x probability threshold yield the best results of all amplitude definitions (R²= 0.75, RMSEP = 0.52). Provided there is an even distribution of the environmental variable, amplitudes defined by predicted probability exceeding prevalence are also suitable (R²= 0.76, RMSEP = 0.55). The prediction success is comparable to maximum likelihood (present species only) and – after rescaling – to mean weighted averages. Predicted values show a good linearity to observed pH values as opposed to a curvilinear relationship of mean Ellenberg indicator values. Transformation or rescaling of the predicted values is not required. Conclusions: Species amplitudes given by a minimum and maximum boundary for each species can be used to efficiently predict environmental variables from species composition. The predictive success is superior to mean Ellenberg indicator values and comparable to mean indicator values based on species weighted averages.     

Application of association coefficients for estimating the mean similarity between sets of vegetational relevés

General rules for the use of all kinds of association coefficients for the direct computation of mean similarity between sets of vegetational relevés are given in the present paper. In the table the main kinds of association coefficients used in plant sociology are listed according toSokal andSneath (1963) and the corresponding formulas for direct computation of the mean similarity between and within sets of relevés are given.     

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.     

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.     

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.     

Vegetation of beech forests in the Rychlebské Mountains,Czech Republic,re-inspected after 60 years with assessment of environmental changes

From 1941–;1944 nearly 30 phytosociological relevés were completed by F. K. Hartmann in the Rychlebské Mountains, a typical mountainous area in northeastern Czech Republic. Of the original plots still covered with adult grown beech (Fagus sylvatica) forest, 22 were resampled in 1998 and 1999. In order to describe the recent vegetation variability of the sites 57 relevés were recorded. Changes in vegetation were estimated using relative changes in species density and ordinations (PCA, RDA). Environmental changes were assessed using Ellenberg indicator values when no direct measurements were available. A decline in species diversity has been documented, particularly, many species occurring frequently in deciduous forests with nutrient and moisture well-supplied soils around neutral have decreased. In contrast, several light-demanding, acid- and soil desiccation-tolerant species have increased. Natural succession, quantified as forest age, contributed slightly to these changes. In Ellenberg indicator values, a decline in F (soil moisture), R (soil calcium) and N (ecosystem productivity), and an increase in L (understorey light) were shown. This is interpreted as the influence of modified forestry management and of airborne pollutants. Intensified logging caused the canopy to open and soil conditions to worsen. The latter is most likely also due to acid leaching of soil cations (Ca, K, Na). This caused a decline in soil productivity, thus the effect of nitrification could not be detected. The original relevés may have differed in size influencing the results. This revised version was published online in August 2006 with corrections to the Cover Date.     

Iteratio: calculating environmental indicator values for species and relevés

Question: Is it possible to translate vegetation maps into reliable thematic maps of site conditions? Method: This paper presents a new method, called Iteratio, by which a coherent spatial overview of specific environmental conditions can be obtained from a comprehensive vegetation survey of a specific area. Iteratio is a database application which calculates environmental indicator values for vegetation samples (relevés) on the basis of known indicator values of a limited number of plant species. The outcome is then linked to a digitalized vegetation map (map of plant communities) which results in a spatial overview of site conditions. Iteratio requires the indicator values of a minimum of 10–20% of the species occurring. The species are given a relative weight according to their amplitudes: species with a narrow range are weighted stronger, species with a broad range are weighted weaker. Conclusion: The method presented here enables a coherent assessment of site conditions on the basis of a vegetation survey and the indicator values of a limited number of plant species.     

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.     

Zur Syntaxonomie desDeschampsio flexuosae-Abietetum Husová 1968

Based on new relevés from the area of the Czech Socialist Republic, the associationDeschampsio flexuosae-Abietetum Husová 1968 is divided into two subassociations:D.f.-A. deschampsietosum flexuosae andD.f.-A. calamagrostietosum. The species composition and variability of the association and both subassociations is given in a synoptic table. The soil properties are also added.     

Do alien and native tree species from Central Argentina differ in their water transport strategy?

In this study we assessed the water transport strategies and the abundance of alien and native tree species at a regional scale in Córdoba Mountains, Central Argentina. The aims of this study were: (i) to analyse whether alien and native tree species show divergent water transport strategies; and (ii) to explore whether species abundances of alien and natives are associated with specific trait attributes. Eight alien species and 12 native species were recorded in 50 complete vascular plant vegetation relevés. Water transport strategies were assessed through the following functional traits: minimum leaf water potential, potential water content of wood, effective leaf area, leaf area per sapwood area and wood density. Also, resource use strategies were assessed throughout the measurement of specific leaf area. We found that alien species had a higher efficiency in water transport (i.e. higher minimum leaf water potential and lower wood density values) and faster resource acquisition and use (higher specific leaf area values) than native species. We did not find evidence suggesting that the relative abundance of species was associated to water transport strategies and faster resource acquisition and use. Alien species seem to differ from natives in specific functional attributes that are absent in the resident community and might allow aliens to use more resources and at a higher rate than native species. Finally, our results show the potential of a trait‐based predictive framework for alien species, and the possible effects on ecosystem functions.     

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

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