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.     

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.     

Towards objectivity in vegetation classification: the example of the Austrian forests

We present a numerical classification of 2145 objectively sampled relevés from the entire forest area of Austria (Central Europe). The sample sites were selected by a combined method involving a systematic matrix and stratified random sampling. A TWINSPAN classification led to 32 clusters which are described in detail. Three main groups can be distinguished: (1) Alpine-dinaric coniferous forests on carbonate soils, (2) Coniferous forests on acid soils and (3) Deciduous forests. These groups correspond with accuracy to the classes Erico-Pinetea, Vaccinio-Piceetea and Querco-Fagetea in the traditional Braun-Blanquet system. Thus, the value of the Braun-Blanquet approach is supported by more or less objective sampling and numerical classification methods. The assumption of the objective existence of ecological species groups is strongly supported, too. Moreover, our results may help to solve some controverse points discussed in the European forest classification regarding the delimination between the three mentioned classes. This revised version was published online in August 2006 with corrections to the Cover Date.     

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.     

SaudiVeg ecoinformatics: Aims,current status and perspectives

During the last decade many electronic databases of vegetation plots were established in many countries around the world. These databases contain valuable phytosociological information assisting both governmental and NGO (Non-governmental organizations) agencies to formulate strategies and on-ground plans to manage and protect nature resources. This paper provides an account on aims, current status and perspectives of building of a vegetation database for the Central Region (Najd) of Saudi Arabia – the founding element of the Saudi Vegetation Database (SVD). The data stored by the database are sample plots (vegetation relevés) collected according to the field techniques of the Braun-Blanquet approach (lists of taxa accompanied by semi-quantitative cover assessment), and are accompanied by general vegetation characteristics such as vegetation layering and cover, information on life-form of the recorded species, geographical coordinates, altitude, soil typology, topography and many more. More than 2900 vegetation-plot records (relevés) have so far been collected in the Najd region; of these more than 2000 have already been stored using the Turboveg database platform. These field records cover many habitats such as depressions, wadis (dry river beds), agricultural lands, sand dunes, sabkhas, and ruderal habitats. The ecological information collected in the database is currently the largest set of vegetation data collated into a database in the Middle East. These data are of great importance for biodiversity studies in Saudi Arabia, since the region is recording a loss of biodiversity at a fast rate due to environmental problems such as global warming and land-use changes. We envisage that this database would catalyze further data collection on vegetation of the entire Arabian Peninsula, and shall serve as one of the most important datasets for classification and mapping of the vegetation of the Kingdom of Saudi Arabia.     

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.     

Multi-scaled pattern analysis: An example with savanna vegetation and a proposal for a sampling design

A detailed pattern analysis has been undertaken in a savanna vegetation, at several scales, using statistical and other data analytical methods. Monospecific patterns were studied at 11 different scales: five scales within the relevés and six starting with the relevé scale. The examination of the connection between the monospecific patterns and the results of multivariate analyses reveals the phytosociological properties of these latter methods. Conclusions about a future design are drawn.     

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.     

Use of Phytosociological Databases for Species Distribution Models

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

Syntaxonomy of vegetation of Svjatoj Nos Peninsula,Lake Baikal 1. Non forest communities

Natural and semi-natural plant communities of Svjatoj Nos Peninsula on the East coast of Lake Baikal, Eastern Siberia, Russia, are classified and described using the methods of Braun-Blanquet phytosociology. A total of 48 associations and communities were recognized, comprising alpine tundra, subalpine forb vegetation, aquatic macrophyte vegetation, tall-herb and poor fens, mires, bogs, meadows, sand-dune and steppe vegetation. Twenty six syntaxa of ranks ranging from subassociation to class are described or validated for the first time. All communities are documented by phytosociological relevés.     

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 salt marsh vegetation on the East Adriatic coast

Phytosociological characteristics and a rate of endangerment of the salt marsh vegetation in central and southern parts of the east Adriatic coast were studied. A total of 73 vegetation relevés were made and elaborated according to the standard procedures of the Braun-Blanquet method. Numerical analysis of the relevés and life forms was performed. Two associations of the class Arthrocnemetea-Puccinellio festuciformis-Arthrocnemetum fruticosi and Limonio-Artemisietum coerulescentis were recorded, together with the association Juncetum maritimo-acuti of the class Juncetea maritimi. These associations show no significant differentiation with regard to their floristic composition, but only in terms of particular species cover and frequency rates, as well as by life forms and microecological habitat conditions. These are specific habitats, rarely found in the studied area, and highly threatened by human activity (tourism, agriculture).     

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.     

Plant communities structure and composition in three coastal wetlands in southern Apulia (Italy)

In this paper the results of a study on the composition and the distribution of the plant communities in three coastal areas of southern Apulia are presented. A total of about 180 vegetation relevés were performed following the Braun-Blanquet phytosociological method. Vegetation data were analysed using both classification (UPGMA, similarity ratio) and ordination methods (including Non-metric Multidimensional Scaling (NMS) and Detrended Correspondence Analysis (DCA). The relevés are distributed in the following classes: Molinio-Arrhenateretea, Phragmito-Magnocaricetea, Juncetea maritimi, Sarcocornietea fruticosae, Saginetea maritimae, Thero-Salicornietea, Helianthemetea guttati. Detailed information about structure and zoning of the detected plant communities are here provided. Two new associations, belonging to the Alkanno-Maresion nanae alliance (microphytic ephemeral plant communities growing on sandy soils, Helianthemetea guttati class) have been described here, both in the “Torre Guaceto” site. The area of “Le Cesine” showed the highest total number of plant communities, while the “Saline di Punta della Contessa” site revealed the largest number of Sarcocornietea fruticosae plant 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.     

The vegetation of alpine belt karst-tectonic basins in the central Apennines (Italy)

Abstract

The vegetation communities of the karst-tectonic basins of the Majella massif alpine belt were studied using the phytosociological methods, and analysed from coenological, synchorological and syntaxonomical viewpoints. During the field-work, 115 relevés were performed using the phytosociological approach of Braun-Blanquet, and these relevés were further subjected to multivariate analyses. Eight clusters of relevés resulted from the numerical classification. The plant communities identified in the study area were ascribed to the following five associations, two sub-associations and one community type: Leontopodio – Seslerietum juncifoliae (ass. nova); Helianthemo – Festucetum italicae (ass. nova); Gnaphalio – Plantaginetum atratae; Taraxaco – Trifolietum thalii gnaphalietosum magellensis (subass. nova); Luzulo italicae – Nardetum, Carici – Salicetum retusae; Saxifrago – Papaveretum julici, Saxifrago – Papaveretum androsacetosum (subass. nova), Plantago atrata and Leontodon montanus community. The distribution of these communities within the karst basins was found to be related to variations in topographic and geomorphological parameters, such as altitude, slope, soil availability and stoniness. All the new associations proposed in this paper belong to the suballiance Leontopodio – Elynenion and to the alliance Seslerion apenninae, both of which are endemic to the central Apennines. In order to compare the plant community types identified within the Majella massif to similar associations found in the rest of the Apennine chain, synoptic tables were constructed. Finally, a comparative phytogeographical analysis of the alpine belt vegetation of the Apennines, Dinarides, southern Balkans and eastern Alps is presented.     

Plant indicator values of a high-phytodiversity country (Italy) and their evidence,exemplified for model areas with climatic gradients in the southern inner Alps

We tested the new Ellenberg–Pignatti indicator values in Festucetalia valesiacae communities of three valley regions (southern inner Alps: Valle d’Aosta, Valtellina, Valle Venosta/Vinschgau). In these landscape types gradients of all value types exist: light (L), temperature (T), moisture (F/M), nitrogen (N), continentality (C) and soil reaction (R). L- and T-values were extended from 9 to 12 in the database of Pignatti due to the higher intensity of these factors in the area in question; in our dataset this is especially relevant for the L-values.In a spatial approach, we compared DCA results with indicator value results (presence–absence) and with climatic data for eight different plant communities. We found comprehensible results in all cases, also for the extension of the L-factor.In a temporal approach, we compared relevés and their indicator values from two time windows: 1930–1950 (Braun-Blanquet) and 1990–1995 (Schwabe and Kratochwil) for six of the eight different plant communities. Both relevé types were made in the same or in similar localities, but no permanent plots existed. Mostly we found in these communities, which are said to have high “stability”, no significant changes on average for any of the indicator values. In the case of N- and R-values there was a trend of increase in the different datasets, and in some cases this trend is significant.In general, the new database has shown the “robustness” of the Ellenberg indicator value model including the extended L-values, and established its usefulness for a synthetic approach in the studied valley systems. In our systems L-, T-, F/M- and C-gradients can be characterised well by means of indicator values and are an excellent tool for explaining DCA results. Caution is necessary especially when correlations of different factors are intermingled in temporal approaches.     

Black alder swamps on forested peatlands in Latvia

The black alder (Alnus glutinosa (L.)Gaertn.) stands occupy 2.5% of the forest area in Latvia. The majority of its communities lie on peatlands; they have been studied in the whole of latvia using the Braun-Blanquet approach. One hundred and fifty alder dominated relevés selected from 334 forest areas have been analysed. Three associations (Carici elongatae-Alnetum, Sphagno squarrosi-Alnetum, andCircaeo-Alnetum), one with four subassociations have been recognized; these belong to the Eurosiberian alder swamps (cl.Alnetea glutinosae) and the European broad-leaved forests (cl.Querco-Fagetea). The phytosociological structure, distribution in Latvia and floristic features of these communities are reported. Results are compared with similar communities in the Baltic Sea states and neighbouring countries.     

Syntaxonomic analysis of theAndropogon-rich grasslands (Hyparrhenietalia hirtae) in the western Mediterranean region

Using the Braun-Blanquet approach, a syntaxonomical revision of the orderHyparrhenietalia hirtae in the western Mediterranean region was made. Various syntaxa were studied with relevés from the Iberian Peninsula, southern France, Sardinia, Sicily and adjacent islands, Balearic Islands, Canary Islands and Morocco. One alliance (Hyparrhenion hirtae), 8 associations (one of them new:Lotononido lupinifoliae-Hyparrhenietum sinaicae) and several subassociations and variants were distinguished. A complete classification of theHyparrhenietalia hirtae in the studied area with ecological and biogeographical diagnoses is given.