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.     

The influence of sample plot size on evaluations with Ellenberg indicator values

The effect of plot size was tested on heterogeneous and homogeneous data sets that were obtained by sampling grassland and forest vegetation on plots differing in size. Mean EIV for relevés revealed no differences among data sets from various plot sizes or between homogeneous and heterogeneous data sets. This is probably due to a similar indicator value for species newly occurring in plots with increasing plot size. Using EIV is thus a robust method even for data sets associated with wide range of plot sizes.     

Randomvs non-random sampling: Effects on patterns of species abundance, species richness and vegetation-environment relationships

From a strictly statistical perspective, most of the commonly used statistical tests cannot be performed on vegetation data obtained using a non-random sampling design. Despite this, non-randomly sampled plots such as phytosociological relevés still make sense: because they may focus on objectives not appropriately addressed by random sampling, such as the study of rare plant communities or species; and because random sampling is often more time-demanding and expensive. Considering the huge body of phytosociological data available, an interesting question arises: if we compare randomly and non-randomly sampled data sets, to what extent do the results of our analyses differ with respect to various species and vegetation parameters? We present an attempt to tackle this question by comparing two data sets collected in a 25 km² area close to the city of Bremen, northwestern Germany: the first data set consisted of 30 subjectively (non-randomly) placed, homogeneous plots across different plant communities, each of which was laid out in a nested design including 9 sizes from 0.5 m² to 1,000 m². The second data set consisted of 30 (again nested) plots randomly selected and located with a GPS device; plots were rejected only if they for some reason were inaccessible. The data collection was the same for both data sets: presence-absence of all vascular plants was recorded for the different plot sizes, and soil samples were collected for the determination of the values of some important environmental variables. For the comparison of the two data sets, we used either the complete data sets or sub-sets of those plots located in woodlands. The main results included the following: (1) Species abundance patterns: Random sampling resulted in a larger number of common and a smaller number of rare species than non-random sampling. (2) Species richness at different spatial scales: For the small plot sizes, the number of species in the non-randomly placed plots was higher than in the randomly placed plots, while the differences were less pronounced at larger spatial scales. As a consequence, also the parameters of species-area curves differed between the data sets, especially in the sub-set including woodland plots. (3) Vegetation differentiation: In random sampling, there was considerable redundancy, i.e., there were several plots with high floristic similarity. (4) Vegetation-environment relationships: The ordination scores of the non-randomly placed plots showed a larger number of significant correlations to soil parameters than the scores of randomly placed plots. The results suggest that conclusions drawn from the analysis of non-randomly placed plots such as phytosociological relevés may be biased, especially regarding estimates of species abundance and species richness patterns.     

Sampling design in large-scale vegetation studies: Do not sacrifice ecological thinking to statistical purism!

Most of the historical phytosociological data on vegetation composition have been sampled preferentially and thus belong to those ecological data that do not fulfill the statistical assumption of independence of observations, necessary for valid statistical testing and inference. Nevertheless, phytosociological data have been recently used for various ecological meta-analyses, especially in studies of large-scale vegetation patterns. For this reason, we focus on the comparison of preferential sampling with other sampling designs that have been recommended as more convenient alternatives from the point of view of statistical theory. We discuss that while simple random sampling, systematic sampling and stratified random sampling better meet some of the statistical assumptions, preferential sampling yields data sets that cover a broader range of vegetation variability. Moreover, today’s large phytosociological databases provide huge amounts of vegetation data with unrivalled geographic extent and density. We conclude that in the near future ecologists will not be able to replace the preferentially sampled phytosociological data in large-scale studies. At the same time, phytosociological databases have to be complemented with relevés of vegetation composed mostly of common and generalist species, which are under-represented in historical data. Stratified random sampling seems to be a suitable tool for doing this. Nevertheless, a methodology and input data for stratification have to be developed to make stratified random sampling an ecologically more relevant and practical method.     

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.     

Exploring large vegetation databases to detect temporal trends in species occurrences

Question: Can vegetation relevé databases be used to analyse species losses and gains in specific vegetation types in Germany over time? Does the type of response (increase or decline in relative frequency) conform to observed large‐scale environmental trends in the last decades? Location: Germany. Exploring the German Vegetation Reference Database Halle (GVRD) that was established for forest and grassland vegetation within the framework of German Biodiversity Exploratories. Methods: Use of generalized linear models (GLMs) for testing changes in temporal frequency of plant taxa in a semi‐dry grassland data set (Mesobromion) and a beech forest data set (Fagion). Data were either aggregated by year, decade or by a balanced re‐sampling approach. Interpretation of the observed changes was based on species traits. Results: In both data sets significant temporal changes were observed, although the frequency of the majority of species remained unchanged. In both data sets, species with a temporal increase in frequency had higher Ellenberg N and F indicator values, compared to species that decreased, thus indicating effects of widespread atmospheric nitrogen deposition. In the forest data set, the observed increase in recruitment of deciduous trees pointed to a change in management, while trends in the grassland data set suggested use abandonment, as seen in an increased frequency of woody species. Conclusion: We demonstrate that vegetation databases represent very valuable resources for analysis of temporal changes in species frequencies. GLMs proved their value in detecting these trends, as also shown by the interpretability of model results with species traits. In contrast, the method of aggregation or re‐sampling had little influence on the general outcome of analyses.     

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.     

Vegetation structure along the altitudinal gradient at the treeline of Mount Paektu,North Korea

Vegetation structure of the treeline was studied on the southeastern slope of Mount Paektu (North Korea). Fifteen temporary plots (20m×20m) were situated along the altitudinal transect. Seven square samples (phytosociological relevés 5 m×5 m) were analyzed in each plot. Although the character of the vegetation was rather continuous altitudinally, five similar groups of vegetation samples were distinguished by the TWINSPAN procedure. The distribution of samples in the classification showed not only the effect of altitude but also the effect of competition between the tree and the shrub layers and other factors. In the canonical correspondence analysis (CCA) ordination several environmental variables were used (such as altitude of each plot, distance of each plot from the forest edge and the cover percentage of tree, shrub, herb and moss/lichen layers). The variable ‘cover of tree layer’ had the strongest relation to the species data. Continuous changes of species richness along the altitude were confirmed. Species richness decreased significantly with altitude.     

Bias in vegetation databases? A comparison of stratified‐random and preferential sampling

Aim: Vegetation plots collected since the early 20th century and stored in large vegetation databases are an important source of ecological information. These databases are used for analyses of vegetation diversity and estimation of vegetation parameters, however such analyses can be biased due to preferential sampling of the original data. In contrast, modern vegetation survey increasingly uses stratified‐random instead of preferential sampling. To explore how these two sampling schemes affect vegetation analyses, we compare parameters of vegetation diversity based on preferentially sampled plots from a large vegetation database with those based on stratified‐random sampling. Location: Moravian Karst and Silesia, Czech Republic. Methods: We compared two parallel analyses of forest vegetation, one based on preferentially sampled plots taken from a national vegetation database and the other on plots sampled in the field according to a stratified‐random design. We repeated this comparison for two different regions in the Czech Republic. We focussed on vegetation properties commonly analysed using data from large vegetation databases, including alpha (within‐plot) diversity, cover and participation of different species groups, such as endangered and alien species within plots, total species richness of data sets, beta diversity and ordination patterns. Results: The preferentially sampled data sets obtained from the database contained more endangered species and had higher beta diversity, whereas estimates of alpha diversity and representation of alien species were not consistently different between preferentially and stratified‐randomly sampled data sets. In ordinations, plots from the preferential samples tended to be more common at margins of plot scatters. Conclusions: Vegetation data stored in large databases are influenced by researcher subjectivity in plot positioning, but we demonstrated that not all of their properties necessarily differ from data sets obtained by stratified‐random sampling. This indicates the value of vegetation databases for use in biodiversity studies; however, some analyses based on these databases are clearly biased and their results must be interpreted with caution.     

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.     

The influence of <Emphasis Type="Italic">Ceratophyllum demersum</Emphasis> L. and <Emphasis Type="Italic">Stratiotes aloides</Emphasis> L. on richness and diversity of aquatic vegetation in the lakes of mid-eastern Poland

The aim of this study was to estimate the influence of Ceratophyllum demersum L. and Stratiotes aloides L. on the species richness and phytocoenotic diversity of aquatic vegetation in lakes. The study was based on field investigations in the Łęczna-Włodawa Lake District located in mid-eastern Poland. The studied lakes (32) included both polymictic and dimictic reservoirs. Both in the polymictic and dimictic lakes, statistically significant correlation coefficients were obtained between the parameters that characterize Stratiotes aloides (the frequency in the phytosociological relevés, the percent share of Stratiotetum aloidis association in the phytolittoral) and those characteristic for species richness (the total number of hydromacrophytes, the number of charophytes, elodeids, nymphaeids and lemnids), phytocoenotic richness (the mean number of species in the phytosociological relevés) and phytocoenotic diversity (the Shannon–Wiener Index). The communities with a share of S. aloides are characterized by higher species richness. However, not a single case of statistically significant dependency was reported between the parameters that describe C. demersum (the frequency in the phytosociological relevés, the percent share Ceratophylletum demersi association in the phytolittoral) and the vegetation traits in both lake groups. Common occurrence of Stratiotes aloides might be considered to be evidence for good status of an aquatic ecosystem and a very good indicator of species richness and diversity of aquatic vegetation.     

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.     

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.     

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.     

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.     

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.     

Diversity patterns in sandy forest-steppes: a comparative study from the western and central Palaearctic

The Palearctic forest-steppe biome is a narrow vegetation zone between the temperate forest and steppe biomes, which provides important habitats for many endangered species and represents an important hotspot of biodiversity. Although the number of studies on forest–grassland mosaics is increasing, information currently available about the general compositional and structural patterns of Eurasian forest-steppes is scarce. Our study aimed to compare the habitat structure, species composition and diversity patterns of two distant sandy forest-steppes of Eurasia. We compared 72 relevés made in the main habitat components (forest, forest edge and grassland) of sandy forest-steppes in three Hungarian and three Kazakh sites. The size of the plots was 25 m². Species number, Shannon diversity and species evenness values were calculated for each plot. Fidelity calculations and linear mixed effects models were used for the analyses. We found that the vegetation and diversity patterns of the two forest-steppes are similar and their components play important roles in maintaining landscape-scale diversity. Despite the higher species richness in Hungary, Shannon diversity was higher in Kazakhstan. The deciduous forest edges of both areas had significantly higher species richness than the neighbouring habitats (forests and grasslands); therefore they can be considered local biodiversity hotspots. Due to the special characteristics of this vegetation complex, we emphasize the high conservation value of all landscape components as a coherent system throughout the entire range of the Eurasian forest-steppe biome.     

Recent changes in mountain grasslands: a vegetation resampling study

Understanding how land‐use changes affect different facets of plant biodiversity in seminatural European grasslands is of particular importance for biodiversity conservation. As conclusions of previous experimental or synchronic observational studies did not converge toward a general agreement, assessing the recent trends in vegetation change in various grassland systems using a diachronic approach is needed. In this resurvey study, we investigated the recent changes in grassland vegetation of the French Jura Mountains, a region with a long tradition of pastoralism. We compared the floristic composition of 150 grassland plots recorded between 1990 and 2000 with new relevés made in 2012 on the same plots. We considered taxonomic, phylogenetic and functional diversity as well as ecological characteristics of the plant communities derived from ecological indicator values and life strategies of the species. PCA of the floristic composition revealed a significant general trend linked to the sampling year. Wilcoxon paired tests showed that contemporary communities were generally more dominated by grass species and presented a higher tolerance to defoliation, a higher pastoral value, and a higher nutrient indicator value. Comparisons revealed a decrease in phylogenetic and functional diversity. By contrast, local species richness has slightly increased. The intensity of change in species composition, measured by Hellinger distance between pairs of relevés, was dependent on neither the time lag between the two surveys, the author of the first relevé nor its location or elevation. The most important changes were observed in grasslands that previously presented low pastoral value, low grass cover, low tolerance to defoliation, and high proportion of stress‐tolerant species. This trend was likely linked to the intensification of grassland management reported in the region, with a parallel increase in mowing frequency, grazing pressure, and fertilization level. More restrictive specifications should be applied to agricultural practices to avoid overexploitation of mountain species‐rich grasslands and its negative consequences on their biodiversity and resilience.     

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.     

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.