Aims Vegetation classification consistent with the Braun‐Blanquet approach is widely used in Europe for applied vegetation science, conservation planning and land management. During the long history of syntaxonomy, many concepts and names of vegetation units have been proposed, but there has been no single classification system integrating these units. Here we (1) present a comprehensive, hierarchical, syntaxonomic system of alliances, orders and classes of Braun‐Blanquet syntaxonomy for vascular plant, bryophyte and lichen, and algal communities of Europe; (2) briefly characterize in ecological and geographic terms accepted syntaxonomic concepts; (3) link available synonyms to these accepted concepts; and (4) provide a list of diagnostic species for all classes. Location European mainland, Greenland, Arctic archipelagos (including Iceland, Svalbard, Novaya Zemlya), Canary Islands, Madeira, Azores, Caucasus, Cyprus. Methods We evaluated approximately 10 000 bibliographic sources to create a comprehensive list of previously proposed syntaxonomic units. These units were evaluated by experts for their floristic and ecological distinctness, clarity of geographic distribution and compliance with the nomenclature code. Accepted units were compiled into three systems of classes, orders and alliances (EuroVegChecklist, EVC) for communities dominated by vascular plants (EVC1), bryophytes and lichens (EVC2) and algae (EVC3). Results EVC1 includes 109 classes, 300 orders and 1108 alliances; EVC2 includes 27 classes, 53 orders and 137 alliances, and EVC3 includes 13 classes, 24 orders and 53 alliances. In total 13 448 taxa were assigned as indicator species to classes of EVC1, 2087 to classes of EVC2 and 368 to classes of EVC3. Accepted syntaxonomic concepts are summarized in a series of appendices, and detailed information on each is accessible through the software tool EuroVegBrowser. Conclusions This paper features the first comprehensive and critical account of European syntaxa and synthesizes more than 100 yr of classification effort by European phytosociologists. It aims to document and stabilize the concepts and nomenclature of syntaxa for practical uses, such as calibration of habitat classification used by the European Union, standardization of terminology for environmental assessment, management and conservation of nature areas, landscape planning and education. The presented classification systems provide a baseline for future development and revision of European syntaxonomy.
Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects.We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives. Geosphere-Biosphere Program (IGBP) and DIVERSITAS, the TRY database (TRY-not an acronym, rather a statement of sentiment; https ://www.try-db.org; Kattge et al., 2011) was proposed with the explicit assignment to improve the availability and accessibility of plant trait data for ecology and earth system sciences. The Max Planck Institute for Biogeochemistry (MPI-BGC) offered to host the database and the different groups joined forces for this community-driven program. Two factors were key to the success of TRY: the support and trust of leaders in the field of functional plant ecology submitting large databases and the long-term funding by the Max Planck Society, the MPI-BGC and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, which has enabled the continuous development of the TRY database.
Abstract. Statistical measures of fidelity, i.e. the concentration of species occurrences in vegetation units, are reviewed and compared. The focus is on measures suitable for categorical data which are based on observed species frequencies within a vegetation unit compared with the frequencies expected under random distribution. Particular attention is paid to Bruelheide's u value. It is shown that its original form, based on binomial distribution, is an asymmetric measure of fidelity of a species to a vegetation unit which tends to assign comparatively high fidelity values to rare species. Here, a hypergeometric form of u is introduced which is a symmetric measure of the joint fidelity of species to a vegetation unit and vice versa. It is also shown that another form of the binomial u value may be defined which measures the asymmetric fidelity of a vegetation unit to a species. These u values are compared with phi coefficient, chi‐square, G statistic and Fisher's exact test. Contrary to the other measures, phi coefficient is independent of the number of relevés in the data set, and like the hypergeometric form of u and the chi‐square it is little affected by the relative size of the vegetation unit. It is therefore particularly useful when comparing species fidelity values among differently sized data sets and vegetation units. However, unlike the other measures it does not measure any statistical significance and may produce unreliable results for small vegetation units and small data sets. The above measures, all based on the comparison of observed/expected frequencies, are compared with the categorical form of the Dufrêne‐Legendre Indicator Value Index, an index strongly underweighting the fidelity of rare species. These fidelity measures are applied to a data set of 15 989 relevés of Czech herbaceous vegetation. In a small subset of this data set which simulates a phytosociological table, we demonstrate that traditional table analysis fails to determine diagnostic species of general validity in different habitats and large areas. On the other hand, we show that fidelity calculations used in conjunction with large data sets can replace expert knowledge in the determination of generally valid diagnostic species. Averaging positive fidelity values for all species within a vegetation unit is a useful approach to measure quality of delimination of the vegetation unit. We propose a new way of ordering species in synoptic species‐by‐relevé tables, using fidelity calculations.
Habitats vary considerably in the level of invasion (number or proportion of alien plant species they contain), which depends on local habitat properties, propagule pressure, and climate. To determine the invasibility (susceptibility to invasions) of different habitats, it is necessary to factor out the effects of any confounding variables such as propagule pressure and climate on the level of invasion. We used 20 468 vegetation plots from 32 habitats in the Czech Republic to compare the invasibility of different habitats. Using regression trees, the proportion of alien plants, including archaeophytes (prehistoric to medieval invaders) and neophytes (recent invaders), was related to variables representing habitat properties, propagule pressure, and climate. The propagule pressure was expressed as the proportion of surrounding urban and industrial or agricultural land, human population density, distance from a river, and history of human colonization in the region. Urban and industrial land use had a positive effect on the proportion of both archaeophytes and neophytes. Agricultural land use, higher population density, and longer history of human impact positively affected the proportion of archaeophytes. Disturbed human-made habitats with herbaceous vegetation were most invaded by both groups of aliens. Neophytes were also relatively common in disturbed woody vegetation, such as broad-leaved plantations, forest clearings, and riverine scrub. These habitats also had the highest proportion of aliens after removing the effect of propagule pressure and climate, indicating that they are not only the most invaded, but also most invasible. These habitats experience recurrent disturbances and are rich, at least temporarily, in available nutrients, which supports the hypothesis that fluctuating resources are the major cause of habitat invasibility. The least invaded habitats were mires and alpine-subalpine grasslands and scrub. After removing the effect of propagule pressure and climate, some habitats actually invaded at an intermediate level had very low proportions of aliens. This indicates that these habitats (e.g., dry, wet, and saline grasslands, base-rich fens, and broad-leaved deciduous woodlands) are resistant to invasion.
Summary 1.Although invasions by alien plants are major threats to the biodiversity of natural habitats, individual habitats vary considerably in their susceptibility to invasion. Therefore the risk assessment procedures, which are used increasingly by environmental managers to inform effective planning of invasive plant control, require reliable quantitative information on the extent to which different habitats are susceptible to invasion. It is also important to know whether the levels of invasion in different habitats are locally specific or consistent among regions with contrasting climate, flora and history of human impact. 2. We compiled a database of 52 480 vegetation plots from three regions of Europe: Catalonia (Mediterranean-submediterranean region), Czech Republic (subcontinental) and Great Britain (oceanic). We classified plant species into neophytes, archaeophytes and natives, and calculated the proportion of each group in 33 habitats described by the European Nature Information System (EUNIS) classification. 3. Of 545 alien species found in the plots, only eight occurred in all three regions. Despite this large difference in species composition, patterns of habitat invasions were highly consistent between regions. None or few aliens were found in environmentally extreme and nutrient-poor habitats, e.g. mires, heathlands and high-mountain grasslands. Many aliens were found in frequently disturbed habitats with fluctuating nutrient availability, e.g. in man-made habitats. Neophytes were also often found in coastal, littoral and riverine habitats. 4. Neophytes were found commonly in habitats also occupied by archaeophytes. Thus, the number of archaeophytes can be considered as a good predictor of the neophyte invasion risk. However, neophytes had stronger affinity to wet habitats and disturbed woody vegetation while archaeophytes tended to be more common in dry to mesic open habitats. 5. Synthesis and applications. The considerable inter-regional consistency of the habitat invasion patterns suggests that habitats can be used as a good predictor for the invasion risk assessment. This finding opens promising perspectives for the use of spatially explicit information on habitats, including scenarios of future land-use change, to identify the areas of highest risk of invasion.
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 SynBioSys 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 largescale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/evadatabase.
Question: How many vegetation plot observations (relevés) are available in electronic databases, how are they geographically distributed, what are their properties and how might they be discovered and located for research and application?Location: Global. Methods:We compiled the Global Index of Vegetation-Plot Databases (GIVD; http://www.givd.info), an Internet resource aimed at registering metadata on existing vegetation databases. For inclusion, databases need to (i) contain temporally and spatially explicit species co-occurrence data and (ii) be accessible to the scientific public. This paper summarizes structure and data quality of databases registered in GIVD as of 30 December 2010.Results: On the given date, 132 databases containing more than 2.4 million non-overlapping plots had been registered in GIVD. The majority of these data were in European databases (83 databases, 1.6 million plots), whereas other continents were represented by substantially less (North America 15, Asia 13, Africa nine, South America seven, Australasia two, multi-continental three). The oldest plot observation was 1864, but most plots were recorded after 1970. Most plots reported vegetation on areas of 1 to 1000 m 2 ; some also stored timeseries and nested-plot data. Apart from geographic reference (required for inclusion), most frequent information was on altitude (71%), slope aspect and inclination (58%) and land use (38%), but rarely soil properties ( o 7%). Conclusions:The vegetation plot data in GIVD constitute a major resource for biodiversity research, both through the large number of species occurrence records and storage of species co-occurrence information at a small scale, combined with structural and plot-based environmental data. We identify shortcomings in available data that need to be addressed through sampling under-represented geographic regions, providing better incentives for data collection and sharing, developing user-friendly database exchange standards, as well as tools to analyse and remove confounding effects of sampling biases. The increased availability of data sets conferred by registration in GIVD offers significant opportunities for largescale studies in community ecology, macroecology and global change research.Dengler, J.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
334 Leonard St
Brooklyn, NY 11211
Copyright © 2023 scite Inc. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.