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Aim: Assessing the performances of different sampling approaches for documenting community diversity may help to identify optimal sampling efforts and strategies, and to enhance conservation and monitoring planning. Here, we used two data sets based on probabilistic and preferential sampling schemes of Italian forest vegetation to analyze the multifaceted performances of the two approaches across three major forest types at a large scale. Location: Italy. Methods: We pooled 804 probabilistic and 16,259 preferential forest plots as samples of vascular plant diversity across the country. We balanced the two data sets in terms of sizes, plot size, geographical position, and vegetation types. For each of the two data sets, 1000 subsets of 201 random plots were compared by calculating the shared and exclusive indicator species, their overlap in the multivariate space, and the areas encompassed by spatially‐constrained rarefaction curves. We then calculated an index of performance using the ratio between the additional and total information collected by each sampling approach. The performances were tested and evaluated across the three major forest types. Results: The probabilistic approach performed better in estimating species richness and diversity of species assemblages, but did not detect other components of the regional diversity, such as azonal forests. The preferential approach outperformed the probabilistic approach in detecting forest‐specialist species and plant diversity hotspots. Conclusions: Using a novel workflow based on vegetation‐plot exclusivities and commonalities, our study suggests probabilistic and preferential sampling approaches are to be used in combination for better conservation and monitor planning purposes to detect multiple aspects of plant community diversity. Our findings can assist the implementation of national conservation planning and large‐scale monitoring of biodiversity. [ABSTRACT FROM AUTHOR]

High mountain ecosystems are hotspots of biodiversity that are highly vulnerable to climate warming and land use change. In Europe, high mountain habitats are included in the EC Directive 92/43/EEC (Habitats Directive) and the identification of practices facilitating effective monitoring is crucial for meeting HD goals. We analyzed the temporal changes in species composition and diversity on high mountain EU habitats and explored if the subgroup of diagnostic species was able to summarize the comprehensive information on plant community variations. We performed a re-visitation study, using a set of 30 georeferenced historical plots newly collected after 20 years on two EU habitats (Galium magellense community growing on screes (8120 EU) and Trifolium thalii community of snowbeds (6170 EU)) in the Maiella National Park (MNP), which is one of the most threatened Mediterranean mountains in Europe. The presence of several endangered species and the availability of a botanical garden, a seed bank, and a nursery, make the MNP an excellent training ground to explore in situ and ex situ conservation strategies. We compared overall and diagnostic species richness patterns over time by rarefaction curves and described the singular aspects of species diversity (e.g., richness, Shannon index, Simpson index, and Berger–Parker index), by Rènyi’s diversity profiles. Diversity values consistently varied over time and across EU habitat types, with increasing values on scree communities and decreasing values on snowbeds. These changes could be associated with both land use change, through the increase of grazing pressure of Apennine chamois (Rupicapra pyrenaica ornata), which determined a rise of nitrophilous species in the scree community, and an increase of grasses at the expense of forbs in snowbeds, and to climate change, which promoted a general expansion of thermophilous species. Despite the two opposite, ongoing processes on the two plant communities studied, our results evidenced that diagnostic species and overall species followed the same trend of variation, demonstrating the potential of diagnostics for EU habitat monitoring. Our observations suggested that the re-visitation of historical plots and the implementation of frequent monitoring campaigns on diagnostic species can provide important data on species abundance and distribution patterns in these vulnerable ecosystems, supporting optimized in situ and ex situ conservation actions.

Aims: Although Sinai is a global hotspot for desert vegetation, there is no well‐documented overview of the Sinai vegetation. We aim to provide a phytosociological overview of Sinai desert vegetation based on an extensive database and formal classification. We further aim to describe the vegetation communities and provide information on their distribution. Location: Sinai, Egypt. Methods: We built a comprehensive database utilizing all available vegetation plot data of the study area from published literature and our field surveys. We determined the database clustering tendency (Hopkins' test analysis) and estimated its optimal number of clusters (Elbow method). We performed a cluster analysis (modified TWINSPAN) and improved the validity of the resulting groups by approximating natural clustering using the Silhouette algorithm. We visualized the results by calculating Non‐metric Multidimensional Scaling and drawing distribution maps for the observed vegetation communities. Results: We distinguished nine classes representing Sinai desert vegetation: Salicornietea fruticosae, Retametea raetam, Haloxylonetea salicornici, Retamo‐Tamaricetea fluviatilis, Acacietea tortilis, Artemisietea herbae‐albae, Anabasietea articulatae, Chiliadenetea iphionoidis, and Stellarietea mediae. We distinguished 25 vegetation groups, of which seven are new findings, representing four main vegetation groups: salt desert, lowland desert, mountain desert, and ruderal desert. We observed a high diversity in life forms, chorotypes, and alpha‐diversity of the vegetation among the main groups. Therophytes, chamaephytes, hemicryptophytes, and phanerophytes are the dominant life forms. Prevailing chorotypes are Saharo‐Arabian, Mediterranean, Mediterranean‐Irano‐Turanian and Irano‐Turanian‐Saharo‐Arabian. The salt desert and lowland desert vegetation are species‐poor, whereas the mountain desert vegetation is relatively species‐rich. The ruderal desert vegetation is the most species‐rich. Conclusion: We present a common classification of Sinai desert vegetation based on cutting‐edge methods and provide an updated description of the desert vegetation groups of Sinai. Our study forms an important basis for decision‐making in nature conservation, global change issues, and further in‐depth studies on Sinai vegetation. [ABSTRACT FROM AUTHOR]

High mountain ecosystems are hotspots of biodiversity that are highly vulnerable to climate warming and land use change. In Europe, high mountain habitats are included in the EC Directive 92/43/EEC (Habitats Directive) and the identification of practices facilitating effective monitoring is crucial for meeting HD goals. We analyzed the temporal changes in species composition and diversity on high mountain EU habitats and explored if the subgroup of diagnostic species was able to summarize the comprehensive information on plant community variations. We performed a re-visitation study, using a set of 30 georeferenced historical plots newly collected after 20 years on two EU habitats (Galium magellense community growing on screes (8120 EU) and Trifolium thalii community of snowbeds (6170 EU)) in the Maiella National Park (MNP), which is one of the most threatened Mediterranean mountains in Europe. The presence of several endangered species and the availability of a botanical garden, a seed bank, and a nursery, make the MNP an excellent training ground to explore in situ and ex situ conservation strategies. We compared overall and diagnostic species richness patterns over time by rarefaction curves and described the singular aspects of species diversity (e.g., richness, Shannon index, Simpson index, and Berger-Parker index), by Rènyi's diversity profiles. Diversity values consistently varied over time and across EU habitat types, with increasing values on scree communities and decreasing values on snowbeds. These changes could be associated with both land use change, through the increase of grazing pressure of Apennine chamois (Rupicapra pyrenaica ornata), which determined a rise of nitrophilous species in the scree community, and an increase of grasses at the expense of forbs in snowbeds, and to climate change, which promoted a general expansion of thermophilous species. Despite the two opposite, ongoing processes on the two plant communities studied, our results evidenced that diagnostic species and overall species followed the same trend of variation, demonstrating the potential of diagnostics for EU habitat monitoring. Our observations suggested that the re-visitation of historical plots and the implementation of frequent monitoring campaigns on diagnostic species can provide important data on species abundance and distribution patterns in these vulnerable ecosystems, supporting optimized in situ and ex situ conservation actions. [ABSTRACT FROM AUTHOR]

Aims: The machine‐readable formal language of classification expert systems has become a standard for applying plot assignment rules in vegetation classification. Here we present an efficient algorithm implementing the vegetation classification expert system in the statistical programming language R. Methods: The principal idea of the R implementation is to solve the assignments to vegetation types not sequentially plot by plot but to parse the assignment rules into (nested) components that each can be evaluated by simultaneous vector‐based processing of all plots in a database. Results and conclusions: We demonstrate the algorithm taking the EUNIS classification expert system of European habitat types (EUNIS‐ESy) as an example. The R code version of the vegetation classification expert system is particularly useful in large vegetation‐plot databases because it solves all logical operations vector‐wise across all plots, allowing for efficient evaluation of membership expressions and formulas. Another advantage of the R implementation is that membership formulas are not only readable but can also be produced as a machine‐written result, for example as the output of classification algorithms run in R. [ABSTRACT FROM AUTHOR]

Aims: River gravel bars are endangered habitats in Europe. However, classification schemes of their vegetation and habitat types differ among European countries, and they are even ignored in some national schemes. This causes problems in conservation planning, monitoring and management. Hence we aimed at building the first unified vegetation classification for river gravel‐bar habitats across European mountain systems. Location: Europe. Methods: In total 4,769 vegetation plot records of river gravel‐bar plant communities were collected from national, regional or private databases, digitized from the literature and newly collected in the field. A hierarchical classification expert system with formal definitions of vegetation types was created. The definitions combined the criteria of presence or cover of groups of species with similar ecology or single species narrowly specialized to a particular gravel‐bar habitat. The TWINSPAN classification was applied to early‐successional vegetation types to check whether the classification based on formal definitions was supported by the results of unsupervised classification. Similarity patterns among vegetation types were visualized using the detrended correspondence analysis (DCA) ordination. Results: Early‐successional and scrub gravel‐bar vegetation types were respectively classified into two classes: Thlaspietea rotundifolii and Salicetea purpureae. Eleven associations and four alliances (Calamagrostion pseudophragmitae, Epilobion fleischeri, Salicion cantabricae and Salicion eleagno‐daphnoidis) were defined formally. Based on a critical revision, some associations or alliances defined in the previous literature were merged or discarded. The main gradient in variability within the gravel‐bar vegetation is connected with the altitudinal gradient, biogeographical variation, local hydromorphological processes and various successional changes. Conclusions: The first unified and formalized classification system of the European mountain river gravel‐bar vegetation was created, and species composition, ecology and distribution of these types were characterized. The syntaxonomical nomenclature of these types was checked and revised. This study provides a base for conservation planning of these threatened and rapidly disappearing habitats. [ABSTRACT FROM AUTHOR]

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment. [ABSTRACT FROM AUTHOR]

Semi-natural grasslands have an important conservation value in Europe but have been in continuous decline since the early twentieth century. Valuable and well-preserved semi-natural grasslands must be identified in order to plan conservation and restoration strategies. The main aim of this paper is to develop an expert system based on diagnostic species for the identification and assessment of EU semi-natural grasslands using a dataset of 3238 vegetation plots from the Iberian Peninsula (Portugal and Spain, including the French Pyrenees). The dataset was obtained by stratified resampling of a larger dataset of 12,204 vegetation plots containing other related grasslands and herbaceous vegetation types. We applied a k-means classification on the resampled dataset and selected the diagnostic species for each group of EU semi-natural grasslands in order to develop an expert classification system with definitions based on their species composition and biogeographic distribution. The expert-based classification was applied to 14 vegetation subtypes belonging to semi-natural grasslands in the Habitats Directive, corresponding to semi-dry calcareous grasslands (Habitat 6210), Nardus grasslands (6230), hay meadows (6510, 6520) and Molinia meadows on peaty soils (6410). We provide a practical and easy tool for the identification, monitoring and assessment of EU semi-natural grasslands on the Iberian Peninsula. [ABSTRACT FROM AUTHOR]

Aims: To create a comprehensive, consistent and unequivocal phytosociological classification of European marsh vegetation of the class Phragmito‐Magnocaricetea. Location: Europe. Methods: We applied the Cocktail method to a European data set of 249,800 vegetation plots. We identified the main purposes and attributes on which to base the classification, defined assignment rules for vegetation plots, and prepared formal definitions for all the associations, alliances and orders of the class Phragmito‐Magnocaricetea using formal logic. Each formula consists of the combination of "functional species groups", cover values of individual species, and in the case of high‐rank syntaxa also of "discriminating species groups" created using the Group Improvement (GRIMP) method. Results: The European Phragmito‐Magnocaricetea vegetation was classified into 92 associations grouped in 11 alliances and six orders. New syntaxa (previously invalidly published according to the International Code of Phytosociological Nomenclature) were introduced: Bolboschoeno maritimi‐Schoenoplection tabernaemontani, Glycerio maximae‐Sietum latifolii, Glycerio notatae‐Veronicetum beccabungae, Schoenoplectetum corymbosi and Thelypterido palustris‐Caricetum elongatae. Based on a critical revision, some other syntaxa were rejected or excluded from the class Phragmito‐Magnocaricetea. Conclusions: This work provides the first consistent classification of the class Phragmito‐Magnocaricetea at the European scale, which is an important tool for nature conservation. Our classification largely respects previously existing concepts of syntaxa, but it also proposes modifications to the recently published EuroVegChecklist. This work also provides a protocol that can be used for extending the current classification to new syntaxa and geographical regions. [ABSTRACT FROM AUTHOR]

Aims: To develop forest vegetation classification at the level of alliances and associations across the Hyrcanian ecoregion, Northern Iran, and to explore the effects of main environmental and geographic gradients on their distribution. Location: Hyrcanian ecoregion, Northern Iran. Methods: A database of 1,597 vegetation plots of mostly 400 m2 in size with a total of 802 vascular plant taxa was established, covering the whole geographic range of the Hyrcanian forests at altitudes ranging from −22 to 2,850 m a. s. l. An expert system was developed for automatic classification of vegetation plots into alliances and associations. Detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to determine the most important environmental and geographic gradients affecting species composition. Results: Twenty‐one associations and seven alliances of these forests, belonging to five orders and four classes, were defined. Among them, eleven associations and five alliances were described as new syntaxa. Alnion glutinosae and Smilaco excelsae‐Alnion barbatae, both distributed in the lowland belt, include swamp and wet forests, respectively. Parrotio persicae‐Carpinion betuli and Alnion subcordatae are respectively mesic and wet forests of the submontane belt. Solano kieseritzkii‐Fagion orientalis is a mesic beech forest in the montane belt, and finally, Quercion macrantherae, an open oak forest, and Centaureo hyrcanicae‐Carpinion orientalis, a dry hornbeam forest, occur in the upper‐montane belt. DCA and CCA analyses showed that the distribution of these alliances and associations is mainly related to altitude and mean annual temperature. Conclusions: Based on our results and comparison between the Hyrcanian and European forests, we propose a new, comprehensive syntaxonomic scheme for the Hyrcanian forests, supported by a classification expert system. Unlike previous studies, we linked the classification system to that of EuroVegChecklist because, though this area is outside of Europe, its vegetation is very similar to that of the European temperate forest vegetation. [ABSTRACT FROM AUTHOR]

The relationship between species' niche breadth (i.e. the range of environmental conditions under which a species can persist) and range size (i.e. the extent of its spatial distribution) has mostly been tested within geographically restricted areas but rarely at the global extent. Here, we not only tested the relationship between range size (derived from species' distribution data) and niche breadth (derived from species' distribution and co‐occurrence data) of 1255 plant species at the regional extent of the European Alps, but also at the global extent and across both spatial scales for a subset of 180 species. Using correlation analyses, linear models and variation partitioning, we found that species' realized niche breadth estimated at the regional level is a weak predictor of species' global niche breadth and range size. Against our expectations, distribution‐derived niche breadth was a better predictor for species' range size than the co‐occurrence‐based estimate, which should, theoretically, account for more than the climatically determined niche dimensions. Our findings highlight that studies focusing on the niche breadth vs range size relationship must explicitly consider spatial mismatches that might have confounded and diminished previously reported relationships. [ABSTRACT FROM AUTHOR]

This study intends to assess the application of Cocktail method in the classification of large vegetation databases. For this purpose, Buxus hyrcana dataset consisted of 442 relevés with 89 species were used and by the modified TWINSPAN. For running the Cocktail method, first primarily classification was done by modified TWINSPAN, and by performing phi analysis in the groups resulted five species were selected which had the highest fidelity value. Then sociological species groups were formed by examining co-occurrence of these 5 species with other species in the database. 21 plant communities belongs to 6 variant, 17 sub associations, 11 associations, 4 alliance, 1 order and 1 class were recognized by assigning 379 releves to the sociological species groups by using logical formulas. Also, 63 releves by the logical formula were not assigned to any sociological species groups, by FPFI index were assigned to the sociological species groups which had the most index value. According to 91% classification agreement with Brown-Blanquet classification and Cocktail classification, we suggest Cocktail method to vegetation scientists as an efficient alternative of Braun-Blanquet method to classify large vegetation databases.

Multi-year temporal studies are invaluable tools for monitoring changes in biodiversity through time. However, their applications in coastal ecosystems are still scarce. We investigated temporal trends in coastal dunes analyzing a set of 858 randomly-sampled georeferenced relevés performed between 2002 and 2015 along Central Italy’s sandy coastlines. Specifically, we explored changes in species richness and cover of targeted sandy habitats, we investigated trends in the cover of selected psammophilous native species and we assessed patterns of invasion by means of regression techniques. We observed a significant decrease in species richness and cover of the dune grasslands habitat. The species-level analysis confirmed a negative trend for two characteristic species of dune grasslands, Cutandia maritima and Medicago littoralis, while revealing a similar decline for Crucianella maritima and for Ammophila arenaria subsp. australis, key species of mobile dunes. The most striking trends emerged analyzing patterns in the cover of an invasive alien species, Carpobrotus sp., which showed a concerning increase in shifting dunes. In conclusion, our analyses reveal concerning changes involving dune grasslands, and at the same time hint at “early warnings” of degradation processes traceable in shifting dunes. [ABSTRACT FROM AUTHOR]

Questions Which are the main vegetation types of lowland hay meadows and pastures in Western and Central Europe? What are the main environmental gradients that drive patterns of species composition? Is it possible to classify these grasslands to phytosociological alliances that reflect management practices? Location Western and Central Europe (excluding the Alps and Carpathians). Methods A database of 21 400 vegetation plots of mesic grasslands across Western and Central Europe was compiled. After geographically stratified resampling, semi-supervised classification based on the K-means algorithm was applied to assign a subset of plots into 32 a priori association-level vegetation types and to search for new types within the subset of non-assigned plots. The vegetation plots assigned into the final vegetation types were submitted to another K-means classification to show the grouping into higher-level vegetation types. Results A total of 36 associations were distinguished in the resampled subset of 8277 vegetation plots and were grouped into four large groups: (1) eutrophic and intensively managed hay meadows and permanent pastures; (2) nutrient-rich grasslands developed from recently abandoned fields or managed under irregular practices of mowing and manuring; (3) non-eutrophic lowland and submontane hay meadows; (4) extensively managed pastures and Atlantic grazed hay meadows. A PCoA of the associations of these four groups showed that extensively managed pastures were floristically more similar to non-eutrophic hay meadows than to permanent intensively managed pastures, which was more obvious in the Atlantic region than in Central Europe. Species composition of the lowland hay meadows was clearly differentiated according to biogeographic sectors. Other floristic differences were related to climate, altitude, soil base status and topography. Conclusions This analysis challenges the traditional concept of mesic grassland alliances separating hay meadows from pastures. New classification should be based mainly on the differences in management intensity rather than in management practice. Consequently, nutrient-poor extensive pastures, which currently are not considered in the European Habitats Directive, should receive the same conservation attention as low-intensive hay meadows, because both types of vegetation can be equally species-rich and do not differ substantially in floristic composition from each other. [ABSTRACT FROM AUTHOR]

Plant seeds exhibit many species-specific traits, thus potentially being especially helpful for forensic investigations. Seeds of a broad range of plant species occur in soil seed banks of various habitats and may become attached in large quantities to moving objects. Although plant seeds are now routinely used as trace evidence in forensic practice, only scant information has been published on this topic in the scientific literature. Thus, the standard methods remain unknown to specialists in such botanical subjects as plant ecology and plant geography. These specialists, if made aware of the forensic uses of seeds, could help in development of new, more sophisticated approaches. We aim to bridge the gap between forensic analysts and botanists. Therefore, we explore the available literature and compare it with our own experiences to reveal both the potential and limits of soil seed bank and seed dispersal analysis in forensic investigations. We demonstrate that habitat-specific and thus relatively rare species are of the greatest forensic value. Overall species composition, in terms of species presence/absence and relative abundance can also provide important information. In particular, the ecological profiles of seeds found on any moving object can help us identify the types of environments through which the object had travelled. We discuss the applicability of this approach to various European environments, with the ability to compare seed samples with georeferenced vegetation databases being particularly promising for forensic investigations. We also explore the forensic limitations of soil seed bank and seed dispersal vector analyses. [ABSTRACT FROM AUTHOR]

Correct spelling of taxon names in vegetation databases is a fundamental prerequisite for many data processing steps. However, manual detection and correction of spelling mistakes is inefficient, prone to errors and non-reproducible, especially when scanning large databases. Here, I review six software tools that spell-check taxon names in vegetation databases: (1) the Global Names Resolver, (2) the Interim Register of Marine and Nonmarine Genera, (3) the Taxonomic Name Resolution Service and R packages (4) Plantminer, (5) Taxonstand and (6) tpl. In particular, I test their capacity to spell-check names across the taxonomic ranks and organism groups frequently encountered in vegetation data and challenge their ability to screen names from different geographic regions. Performance by software tools differed widely in these tests. Backed up by multiple reference lists, the Global Names Resolver emerged as the most versatile software tool. All software solutions currently suffer from some minor limitations, including an inability to spell-check names of hybrid taxa. Furthermore, some spelling mistakes, by their nature, cannot be resolved unambiguously. Given these limitations, taxon names should be spell-checked with software tools in a semi-automatic rather than an automatic way. [ABSTRACT FROM AUTHOR]

This study intends to assess the application of Cocktail method in the classification of large vegetation databases. For this purpose, Buxus hyrcana dataset consisted of 442 relevés with 89 species were used and by the modified TWINSPAN. For running the Cocktail method, first primarily classification was done by modified TWINSPAN, and by performing phi analysis in the groups resulted five species were selected which had the highest fidelity value. Then sociological species groups were formed by examining co-occurrence of these 5 species with other species in the database. 21 plant communities belongs to 6 variant, 17 sub associations, 11 associations, 4 alliance, 1 order and 1 class were recognized by assigning 379 releves to the sociological species groups by using logical formulas. Also, 63 releves by the logical formula were not assigned to any sociological species groups, by FPFI index were assigned to the sociological species groups which had the most index value. According to 91% classification agreement with Brown-Blanquet classification and Cocktail classification, we suggest Cocktail method to vegetation scientists as an efficient alternative of Braun-Blanquet method to classify large vegetation databases. [ABSTRACT FROM AUTHOR]

This study is aimed at collection of all available phytosociological data on vegetation of Sinai Peninsula, a region that is still poorly explored. An overview of the plant communities of Sinai is compiled based on additional field work and inventories. The database for Sinai vegetation will serve as a nucleus for the National Vegetation Databank of Egypt--'VegEgypt'. Aspects like species richness, species turnover, conservation categories, and endemism were given special attention. The database was set up and analysed using the Turboveg and Juice programs. A matrix of 816 relevés and 496 species belonging to 69 families and 281 genera formed the basis for further analysis. Asteraceae, Poaceae and Fabaceae were the most represented families. The lists contain 52 threatened, 16 endemic and 20 sub-endemic species. The percentage of endemic species is highest in insular floras, peninsulas and mountain chains. The vegetation analysis resulted in 21 associations. The plant associations on sand habitats have the lowest species richness and species turnover because of water scarcity. On the other hand, plant communities or associations inhabiting rocky habitats have the highest species richness and species turnover. [ABSTRACT FROM AUTHOR]

Aims To produce a formalized classification of floodplain forests in the Iberian Peninsula and to assess their main bioclimatic gradients. Location Iberian Peninsula. Methods A data set with more than 3000 vegetation plots of floodplain forests was compiled from vegetation-plot databases, while climatic data were derived from a digital climatic atlas. After filtering of plots according to their area and geographic stratification, 1892 plots were used to build a typology from association to order level using multivariate classification methods (Fuzzy C-means, agglomerative hierarchical clustering). The phi fidelity index was used to determine the diagnostic species of the syntaxa in the proposed classification. Main climatic gradients were explored using non-metric multidimensional gradient analysis, and ANOVA was carried out in order to define the bioclimatic features of Iberian floodplain forests. Results A total of 41 floodplain forest associations were distinguished for the Iberian Peninsula, grouped in nine suballiances, four alliances and two orders. Mediterraneity (summer aridity) was the main climatic driver, as it separates the temperate floodplain forests of the order Alno-Fraxinetalia from the Mediterranean forests of the Populetalia albae. Continentality and precipitation were mainly relevant at alliance level, as they separated both the temperate alliances Alnion and Hyperico-Alnion, the latter more oceanic, and the Mediterranean alliances Populion and Osmundo- Alnion, the latter from more rainy areas. Temperature was an important driver at association level, as the associations included in the same suballiance or alliance differed regarding their thermicity index. Conclusions Our study develops the first formalized classification of Iberian floodplain forests and provides their bioclimatic diagnosis. One new alliance, Hyperico-Alnion, is proposed for floodplain forests of the Cantabrian watershed. Mediterraneity, continentality and precipitation drive floodplain forest diversity at broad scale, while temperature is the main bioclimatic driver at fine scale. The proposed classification provides the scientific basis for the conservation of this habitat type, with high conservation priority, in southern Europe. [ABSTRACT FROM AUTHOR]

The European Vegetation Archive (EVA) is a centralized database of European vegetation plots developed by the IAVS Working Group European Vegetation Survey. It has been in development since 2012 and first made available for use in research projects in 2014. It stores copies of national and regional vegetationplot databases on a single software platform. Data storage in EVA does not affect on-going independent development of the contributing databases, which remain the property of the data contributors. EVA uses a prototype of the database management software TURBOVEG 3 developed for joint management of multiple databases that use different species lists. This is facilitated by the Syn-BioSys Taxon Database, a system of taxon names and concepts used in the individual European databases and their corresponding names on a unified list of European flora. TURBOVEG 3 also includes procedures for handling data requests, selections and provisions according to the approved EVA Data Property and Governance Rules. By 30 June 2015, 61 databases from all European regions have joined EVA, contributing in total 1 027 376 vegetation plots, 82% of them with geographic coordinates, from 57 countries. EVA provides a unique data source for large-scale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/eva-database. [ABSTRACT FROM AUTHOR]

Rendiconti Lincei has dedicated a Special Issue to present a number of case studies highlighting the role played by the European Vegetation Survey Working Group established by Sandro Pignatti and his colleagues in support to the implementation of the Habitats Directive. Studies include theoretical analyses as well as researches conducted at different spatial and temporal scales focused on the assessment and monitoring of the conservation status of habitats and target plant species, identification of new habitats and subtypes, and their diagnostic species. [ABSTRACT FROM AUTHOR]

Aims Most vegetation classification systems developed for large areas include various inconsistencies. Therefore, we (1) propose a new consistent Cocktail-based approach to redefine the traditional phytosociological classification of species-poor vegetation; (2) apply it to create a classification protocol for aquatic vegetation; (3) implement this protocol in a computer expert system; and (4) test it with a data set previously classified using an older version of the Cocktail method. Methods The new approach uses formal logic to provide formal definitions of vegetation units. In the classification protocol for aquatic vegetation we defined consistent criteria for delimitation of associations according to the concepts that are predominantly used in phytosociology, based on species cover, dominance patterns and functional species groups. We applied these criteria in a computer expert system running in the JUICE 7.0 program, and applied them to a test data set of 12 171 vegetation plots from the Czech Republic containing at least one aquatic species. The new classification was compared with (1) the previous national Cocktail classification based on species cover values and in few cases on sociological species groups, and (2) a non-formalized expert-based classification. Results Thirteen functional species groups were created to build logical formulas of 64 aquatic associations and 5297 (44% of the total data set) vegetation plots were assigned to these associations, i.e. by 4% and 12% more than in the previous Cocktail and expert-based classifications, respectively. There was 94% and 83% classification agreement with the previous Cocktail and expert-based classification. Conclusions The new approach produces a formal, consistent and unequivocal classification of species-poor vegetation with several advantages over similar approaches. It provides not only a set of formal definitions of vegetation units, but also a set of rules for building such definitions. All associations with common characteristics are defined by structurally identical formulas, ensuring consistency of the classification. While similar approaches for species-rich vegetation use sociological species groups, which are not applicable to species-poor vegetation, the new approach introduces the use of functional species groups, which reflect vegetation physiognomy and spatial structure and, in combination with species dominance, enable the classification of species-poor vegetation in a similar manner as in traditional phytosociology. [ABSTRACT FROM AUTHOR]

For the first time, an overview of plant communities in Slovenia is presented according to the Braun-Blanquet approach. In total 588 associations (and some communities classified into higher syntaxa) belonging to 51 classes have been registered in Slovenia. Additionally 149 syntaxa are mentioned as registered in the field or in, the literature, but not documented with relevé material. Syntaxonomical classification is based on the "EuroChecklist" and includes also the Slovenian written definition of the high-rank syntaxa. [ABSTRACT FROM AUTHOR]

Question: Diagnostic species are useful tools for the identification and ecological interpretation of community types. Vegetation data- bases facilitate the computation of diagnostic values of regional validity, but it is essential to understand the behaviour of fidelity measures in large data sets. Methods: We focused our study on the phi-coefficient (P) of association and its limit value, the Ochiai index. The northeast Spanish relevé database was stratified using an arbitrary distance threshold in species composition. Diagnostic species analysis was undertaken using three methods of context selection: 1. within a syntaxon of higher rank; II. including relevés with similar composition to that of the target unit; III. using the entire stratified database. Species diagnostic values were computed as well as bootstrap percentile confidence intervals. Results: Many species deemed as diagnostic by method I have their optima in vegetation types neighbouring the unit chosen as context. In contrast, method LI excluded many of these species. Φ-values and confidence intervals were similar to those obtained by the Ochiai indexwhen using a large dataset (method HI) but this similarity was greater for low level syntaxa. Conclusions: The diagnostic value of species in a given region is best assessed using the Ochiai index, since it can be split into two interpretable asymmetrical components. We recommend the determination of context-dependent differential species using the Φ-coefficient, and the assessment of species regional diagnostic value by means of a stratification procedure in combination with the Ochiai index. [ABSTRACT FROM AUTHOR]

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

The rapid developments in computer techniques and the availability of large datasets open new perspectives for vegetation analysis aiming at better understanding of the ecology and functioning of ecosystems and underlying mechanisms. Information systems prove to be helpful tools in this new field. Such information systems may integrate different biological levels, viz. species, community and landscape. They incorporate a GIS platform for the visualization of the various layers of information, enabling the analysis of patterns and processes which relate the individual levels. An example of a newly developed information system is SynBioSys Europe, an initiative of the European Vegetation Survey (EVS). For the individual levels of the system, specific sources are available, notably national and regional Turboveg databases for the community level and data from the recently published European Map of Natural Vegetation for the landscape level. The structure of the system and its underlying databases allow user-defined queries. With regard to its application, such information systems may play a vital role in European nature planning, such as the implementation the EU-program Natura 2000. To illustrate the scope and perspectives of the program, some examples from The Netherlands are presented. They are dealing with long-term changes in grassland ecosystems, including shifts in distribution, floristic composition, and ecological indicator values. [ABSTRACT FROM AUTHOR]

LÁJER (2007) reviewed the use of statistical methods for the analysis of vegetation data and concluded that their assumptions are often violated. Most importantly, the vegetation data are usually not a random sample of vegetation, and consequently the statistical tests should not be used at all. Although we appreciate many concerns raised in Lájer's paper, we find his conclusions far-fetched and inappropriate for practical use. In large-scale observational studies, it is practically impossible to define the sampled statistical population in the way that would allow for truly random sampling. As we are unable to ensure that any part of the population can appear in our sample with the same probability, we must try to avoid interaction between any bias imposed by the sampling procedure with the hypotheses we test. The same stance can also be taken in the case of datasets extracted from the databases of phytosociological relevés, where a substantial bias was introduced by phytosociologists' prejudice in selection of sampling locations. We can hardly use this kind of data when testing hypotheses concerning absolute values of species richness or discontinuities in community variation, but there are also many important research hypotheses that can be tested even with the help of this data source. In fact, such voluminous databases are the only available source of data for exploring research questions referring to large spatial or temporal scales. We must also reject Lájer's suggestion that application of descriptive, exploratory statistical methods is less harmful for datasets with sampling bias than application of tests of statistical hypotheses. Finally, we stress the difference between observational and experimental studies, because the rigor of sampling design should be respected much more in the case of latter ones. [ABSTRACT FROM AUTHOR]

Aim: Concentration of species occurrences in groups of classified sites can be quantified with statistical measures of fidelity, which can be used for the determination of diagnostic species. However, for most available measures fidelity depends on the number of sites within individual groups. As the classified data sets typically contain site groups of unequal size, such measures do not enable a comparison of numerical fidelity values of species between different site groups. We therefore propose a new method of measuring fidelity with presence/absence data after equalization of the size of the site groups. We compare the properties of this new method with other measures of statistical fidelity, in particular with the Dufrêne-Legendre Indicator Value (IndVal) index. Methods: The size of site groups in the data set is equalized, while relative frequencies of species occurrence within and outside of these groups are kept constant. Then fidelity is calculated using the phi coefficient of association. Results: Fidelity values after equalization are independent of site group size, but their numerical values vary independently of the statistical significance of fidelity. By changing the size of the target site group relative to the size of the entire data set, the fidelity measure can be made more sensitive to either common or are species. We show that there are two modifications f the IndVal index for presence/absence data, one of which is also independent of the size of site groups. Conclusion: The phi coefficient applied to site groups of equalized size has advantages over other statistical measures of fidelity based on presence/absence data. Its properties are close to an intuitive understanding of fidelity and diagnostic species in vegetation science. Statistical significance can be checked by calculation of another fidelity measure that is a function of statistical significance, or by direct calculation of the probability of observed species concentrations by Fisher's exact test. An advantage of the new method over IndVal is its ability to distinguish between positive and negative fidelity. One can also weight the relative importance of common and rare species by changing the equalized size of the site groups. [ABSTRACT FROM AUTHOR]

Small-scale landscape elements, such as ditch banks are an important remaining source of biodiversity in many agricultural landscapes, including the Western Peat District in the Netherlands. Unfortunately, plant species richness is declining even in these habitats. To understand the factors threatening biodiversity, we studied demographic traits (occupancy, trend, colonisation and extinction) for a large number of plant species, in a 25-year long data set. We developed a method to investigate the relative importance of colonisation and extinction for species increase and decrease in multi-species assemblages. We show that colonisation has been more important for determining species trends than extinction. Decreasing species were small and characterised by low nutrient tolerance and high light requirements, indicating that competitive ability influences species trends. The mechanism by which high nutrient levels reduce plant diversity appears to be closely related to colonisation (germination and seedling establishment). Local management should therefore continue to focus on nutrient reduction and the creation of regeneration sites. Yet, these measures will be insufficient for restoring species richness since isolation also hampers species increase. Therefore, to maximise the effects of local management, additional regional management solutions are required to improve seed dispersal for example, from nature reserves. [Copyright &y& Elsevier]

• • We provided a forest development stage assessment method for the plot-based vegetation surveys. • • For this we used data from forest management plans and traditional vegetation surveys. • • The method gave a very realistic division and characteristics of the developmental stages. • • However, quantification of the proportion of the development stages in the forest was unsatisfactory. • • Distinguished stages were characterised by a separate herb layer species composition. The possibility to distinguish changes in vegetation related to the dynamics of the forest stand and / or the regimes of forest management from directional or random changes would allow for more precise recognition, and counteracting the effects of global threats. However, in most cases, records for particular periods of vegetation surveys do not contain data allowing assessment of the forest stand dynamic. In this work, we provided the forest developmental stages assessment method using variables recorded on the sampling plots designed for vegetation surveys, supplemented by variables from forest inventories conducted in managed European beech forests from the Carpathian Mountains. Three distinct forest stages were distinguished. Based upon distribution of variables, specific for individual stages, we classified them as growing (G), optimum (O), and terminal (T) stage. The characteristics of these stages were similar to those for old-growth forests European beech forests. Our results demonstrated a simple, clear and repeatable method of using forest inventories and data from traditional vegetation surveys, useful in the assessment of managed forest stands for long term study purposes. It was possible based on 10 variables, among which the most decisive seems to be stocking, tree regeneration and mean tree DBH and height. As each of the distinguished stages were characterised by a separate herb layer species composition, the method allows for better identification of the impact of cyclical changes in the structure of the stand from the directional causes of long-term changes in forest herbaceous vegetation. Although our method gave a very realistic division and characterisation of the developmental stages, due to the bias of vegetation researchers (who more often conducted research in the optimum stage of the forest), does not allow for the correct quantification of the proportion of developmental stages in the forest. [ABSTRACT FROM AUTHOR]