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.     

Current knowledge and phytosociological data on the high-altitude vegetation in the Western Carpathians — a review

Presented survey summarizes the results of the studies published predominantly after 2000, dealing with the plant communities around and above the timberline in (montane) subalpine to alpine (subnival) belt of the Western Carpathians. All of these communities underwent a critical syntaxonomical and nomenclatorical revision, hence the demonstrated overview of high-mountain vegetation of Western Carpathians (mostly from Slovakia, less from Poland border areas) represent the current state of knowledge. The high-altitude vegetation database, which is the part of Slovak National Vegetation Database, SNVD (), incorporated 8,160 published relevés on 15 May 2007 (of the total of 30,469 published relevés in the SNVD). Concerning the unpublished relevés, the individual authors have provided more than 18,400 of them to be stored in SNVD; 2,301 of all unpublished relevés could be assigned to high-altitude vegetation. Mountain and alpine vegetation is in SNVD presented by 15 classes; the most frequent class is Mulgedio-Aconitetea. With its quantity and also the quality of relevés, the high-altitude database, as well as the whole SNVD, represents the unique database within Slovakia, which provides information not only about the locality, floristic composition and variability of individual vegetation types, but also about several environmental variables such as inclination, aspect, geology or soil type, characteristic for individual relevés. Together with other Central European databases, SNVD takes up the leading position in Europe.     

Ecology of inland sand dunes “nafuds” as a hyper-arid habitat,Saudi Arabia: Floristic and plant associations diversity

Sand seas of Saudi Arabia cover about one-third of the Arabian Peninsula and are still poorly explored in scientific literature. This study aimed to address the floristic structure and association diversity of the inland sand seas in central Saudi Arabia after 20 years of protection. Twenty-three relevés were selected in Nafud Al-Urayq reserve to cover different sandy dune variations. These relevés are subjected to floristic and multivariate analysis of classification with TWINSPAN and ordination with DECORANA & CANOCO techniques. One hundred thirty-five species belonging to 108 genera in 37 families have been recorded. Annual and perennial species are equally represented. Four vegetation groups (i.e., plant associations) are identified as the following: VG I (Haloxylon salicornicum-Lycium shawii-Acacia raddiana), VG II (Calligonum comosum-Tetraena propinqua), VG III (Haloxylon persicum-Haloxylon salicornicum-Stipagrostis drarii), and VG IV (Pulicaria undulata-Citrullus colocynthis). The association of VG I inhabited in the wadi and non-dune or shallow sand habitat had the high species diversity indices (i.e., total species, species richness, species evenness and Shannon index). In contrast, the association of VG II inhabited hyper-arid and salinized habitat and had low species diversity indices. These associations are discussed and illustrated in accordance with competition and adaptation. The advantages of inland sand dune vegetation therefore apply specifically to habitat management and the conservation of plants. These studies extend the advantages of succession of sand dunes and show that rising vegetative diversity is consistent with the combat of desertification.     

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

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

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.     

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.     

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.     

Assignment of relevés to pre‐defined classes by supervised clustering of plant communities using a new composite index

Question: How does a newly designed method of supervised clustering perform in the assignment of relevé (species composition) data to a previously established classification. How do the results compare to the assignment by experts and to the assignment using a completely different numerical method? Material: Relevés analysed represent 4186 Czech grassland plots and 4990 plots from a wide variety of vegetation types (359 different associations or basal communities) in The Netherlands. For both data sets we had at our disposal an expert classification, and for the Czech data we also had available a numerical classification as well as a classification based on a neural network method (multi‐layer perceptron). Methods: Two distance indices, one qualitative and one quantitative, are combined into a single index by weighted multiplication. The composite index is a distance index for the dissimilarity between relevés and vegetation types. For both data sets the classifications by the new method were compared with the existing classifications. Results: For the Czech grasslands we correctly classified 81% of the plots to the classes of an expert classification at the alliance level and 71% to the classes of the numerical classification. Correct classification rates for the Dutch relevés were 64, 78 and 83 % for the lowest (subassociation or association), association, and alliance level, respectively. Conclusion: Our method performs well in assigning community composition records to previously established classes. Its performance is comparable to the performance of other methods of supervised clustering. Compared with a multi‐layer perceptron (a type of artificial neural network), fewer parameters have to be estimated. Our method does not need the original relevé data for the types, but uses synoptic tables. Another practical advantage is the provision of directly interpretable information on the contributions of separate species to the result.     

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.     

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.     

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.     

Life-history traits and habitat preferences of colonizing plant species in long-term spontaneous succession in abandoned gravel–sand pits

The following question was asked: Species of what traits and ecological demands are the best and the least successful colonizers in the course of succession in disused gravel–sand pits?Abandoned gravel–sand pits (36) were studied in the Czech Republic. Together 224 phytosociological relevés were recorded in 5 m×5 m plots in all available seral stages ranging in age from 1 to 75 years. Complete lists of species occurring in (semi-)natural habitats were surveyed up to a distance of 100 m from each relevé. The colonization success of each species was expressed by an index between 0 and 1 which was obtained as the ratio of the number of relevés with species present in a pit/the number of relevés with the species occurrence in their surroundings. Species characteristics were taken from available databases. Data were elaborated by ordination analysis and regression tree analysis. Generally, the best colonizers of gravel–sand pits were hydrophytes with the ability to vegetatively reproduce. In particular, at the beginning of succession, anemochorous species played the most important role. Stress tolerant species, possessing light diaspores, were typical of nitrogen poor and acidic habitats. Later, sciophilous and nitrophilous species of mesic habitats increased in importance. They have heavier diaspores, and are mostly phanerophytes or geophytes, often with the ability to vegetatively reproduce as well as exhibiting higher demand for pH. Plant functional traits were recognized as powerful tools to predict the colonization success of plants available in the local species pool. They may help predict vegetation succession in various human-disturbed sites and thus be used in various restoration programmes.     

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.     

Marshland vegetation of the class <Emphasis Type="Italic">Phragmito-Magnocaricetea</Emphasis> in northwest Croatia (Krapina river valley)

Marshland vegetation of the class Phragmito-Magnocaricetea in the Krapina river valley was investigated during 2006 and 2007, and some sporadic investigations were made earlier. Phytosociological studies were carried out in accordance with the standard Braun-Blanquet methodology. As a result of the field work, and a small amount of data from the literature, 120 relevés were collected and 18 communities were established. For the purposes of comparison, the relevés were also classified using numerical methods. The clusters obtained mostly correspond to specific associations, but do not confirm the division into traditional vegetation alliances and orders. In the analysis of the ecological factors it is established that separation of the relevés is influenced by nutrient content, soil reaction, soil moisture, depth of water, and type of management. Analysis of the plant life forms shows, in all marshland communities, a prevalence of hemicryptophytes, geophytes and hydrophytes. The most widespread marshland communities of the investigated area are: Phalaridetum arundinaceae, Phragmitetum australis and Galio palustris-Caricetum ripariae. Furthermore, Carex randalpina community is recorded for the first time in Croatia. The most threatened marshland communities could be considered to be: Carex randalpina community, Caricetum vesicariae, Leersietum oryzoidis and Oenantho-Rorippetum. They are selected because of their very small surfaces in the investigated area and the small number of known localities within the territory of Croatia. The most invasive alien plant species in the Krapina river valley is Solidago gigantea. It spreads in potential habitats of marshland vegetation, and it is recorded in the species composition of many marshland communities. For the preservation of marshland vegetation, and especially threatened types, it is necessary to maintain the water regime of the habitats, to not remove natural plant cover due to spreading of neophytes, and to provide occasional mowing and burning.     

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.     

Main vegetation types and plant species diversity along an altitudinal gradient of Al Baha region,Saudi Arabia

Plant species composition patterns and vegetation types were investigated along Elevational Gradients in Al Baha region, Saudi Arabia. Sandy plain, wadis, drainage lines, rocky outcrops, hills and fallow lands occur over a wide geographic range encompassing variation in plant species and communities among these different ecological sites. To provide a quantitatively based classification of the vegetation we used Multi Variant Statistical Package (MVSP) software, followed by the re-arrangement of a matrix of the similar plant species in rows and similar sample sites in columns. Plant density and environmental variables were measured and recorded in each quadrat. Two-way indicator species analysis and Canonical Correspondence Analysis (CCA) were used to analyze the relationships between vegetation and environmental variables, while Arc Map was used to analyze the pattern of plant species density. A total of 59 sample plots (25 × 25 m), stratified, randomly-placed relevés were collected in Al Baha region, along a cross section running from south-west to north-west. About 190 plant species belonging to 59 families were recognized. This study showed that these plant species formed 15 vegetation types that primarily correspond mainly to different combinations of elevation, and topography. The study concluded that this research has provided the first quantitative and systematic survey of the vegetation in Al Baha region.     

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.     

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).     

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

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