6 research outputs found

    Disturbance indicator values for European plants

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    Motivation Indicator values are numerical values used to characterize the ecological niches of species and to estimate their occurrence along gradients. Indicator values on climatic and edaphic niches of plant species have received considerable attention in ecological research, whereas data on the optimal positioning of species along disturbance gradients are less developed. Here, we present a new data set of disturbance indicator values identifying optima along gradients of natural and anthropogenic disturbance for 6382 vascular plant species based on the analysis of 736,366 European vegetation plots and using expert-based characterization of disturbance regimes in 236 habitat types. The indicator values presented here are crucial for integrating disturbance niche optima into large-scale vegetation analyses and macroecological studies. Main types of variables contained We set up five main continuous indicator values for European vascular plants: disturbance severity, disturbance frequency, mowing frequency, grazing pressure and soil disturbance. The first two indicators are provided separately for the whole community and for the herb layer. We calculated the values as the average of expert-based estimates of disturbance values in all habitat types where a species occurs, weighted by the number of plots in which the species occurs within a given habitat type. Spatial location and grain Europe. Vegetation plots ranging in size from 1 to 1000 m(2). Time period and grain Vegetation plots mostly sampled between 1956 and 2013 (= 5th and 95th quantiles of the sampling year, respectively). Major taxa and level of measurement Species-level indicator values for vascular plants. Software format csv file

    Ecological Indicator Values for Europe (EIVE) 1.0

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    Aims: To develop a consistent ecological indicator value system for Europe for five of the main plant niche dimensions: soil moisture (M), soil nitrogen (N), soil reaction (R), light (L) and temperature (T). Study area: Europe (and closely adjacent regions). Methods: We identified 31 indicator value systems for vascular plants in Europe that contained assessments on at least one of the five aforementioned niche dimensions. We rescaled the indicator values of each dimension to a continuous scale, in which 0 represents the minimum and 10 the maximum value present in Europe. Taxon names were harmonised to the Euro+Med Plantbase. For each of the five dimensions, we calculated European values for niche position and niche width by combining the values from the individual EIV systems. Using T values as an example, we externally validated our European indicator values against the median of bioclimatic conditions for global occurrence data of the taxa. Results: In total, we derived European indicator values of niche position and niche width for 14,835 taxa (14,714 for M, 13,748 for N, 14,254 for R, 14,054 for L, 14,496 for T). Relating the obtained values for temperature niche position to the bioclimatic data of species yielded a higher correlation than any of the original EIV systems (r = 0.859). The database: The newly developed Ecological Indicator Values for Europe (EIVE) 1.0, together with all source systems, is available in a flexible, harmonised open access database. Conclusions: EIVE is the most comprehensive ecological indicator value system for European vascular plants to date. The uniform interval scales for niche position and niche width provide new possibilities for ecological and macroecological analyses of vegetation patterns. The developed workflow and documentation will facilitate the future release of updated and expanded versions of EIVE, which may for example include the addition of further taxonomic groups, additional niche dimensions, external validation or regionalisation

    Ellenberg-type indicator values for European vascular plant species

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    Aims: Ellenberg-type indicator values are expert-based rankings of plant species according to their ecological optima on main environmental gradients. Here we extend the indicator-value system proposed by Heinz Ellenberg and co-authors for Central Europe by incorporating other systems of Ellenberg-type indicator values (i.e., those using scales compatible with Ellenberg values) developed for other European regions. Our aim is to create a harmonized data set of Ellenberg-type indicator values applicable at the European scale. Methods: We collected European data sets of indicator values for vascular plants and selected 13 data sets that used the nine-, ten- or twelve-degree scales defined by Ellenberg for light, temperature, moisture, reaction, nutrients and salinity. We compared these values with the original Ellenberg values and used those that showed consistent trends in regression slope and coefficient of determination. We calculated the average value for each combination of species and indicator values from these data sets. Based on species’ co-occurrences in European vegetation plots, we also calculated new values for species that were not assigned an indicator value. Results: We provide a new data set of Ellenberg-type indicator values for 8908 European vascular plant species (8168 for light, 7400 for temperature, 8030 for moisture, 7282 for reaction, 7193 for nutrients, and 7507 for salinity), of which 398 species have been newly assigned to at least one indicator value. Conclusions: The newly introduced indicator values are compatible with the original Ellenberg values. They can be used for large-scale studies of the European flora and vegetation or for gap-filling in regional data sets. The European indicator values and the original and taxonomically harmonized regional data sets of Ellenberg-type indicator values are available in the Supporting Information and the Zenodo repository

    Mapping species richness of plant families in European vegetation

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    none40siAims: Biodiversity is traditionally studied mostly at the species level, but biogeographical and macroecological studies at higher taxonomic levels can provide valuable insights into the evolutionary processes at large spatial scales. Our aim was to assess the representation of vascular plant families within different vegetation formations across Europe. Location: Europe. Methods: We used a data set of 816,005 vegetation plots from the European Vegetation Archive (EVA). For each plot, we calculated the relative species richness of each plant family as the number of species belonging to that family divided by the total number of species. We mapped the relative species richness, averaged across all plots in 50 km Ă— 50 km grid cells, for each family and broad habitat groups: forests, grasslands, scrub and wetlands. We also calculated the absolute species richness and the Shannon diversity index for each family. Results: We produced 522 maps of mean relative species richness for a total of 152 vascular plant families occurring in forests, grasslands, scrub and wetlands. We found distinct spatial patterns for many combinations of families and habitat groups. The resulting series of 522 maps is freely available, both as images and GIS layers. Conclusions: The distinct spatial patterns revealed in the maps suggest that the relative species richness of plant families at the community level reflects the evolutionary history of individual families. We believe that the maps and associated data can inspire further biogeographical and macroecological studies and strengthen the ongoing integration of phylogenetic, functional and taxonomic diversity concepts.noneVecera M.; Axmanova I.; Padulles Cubino J.; Lososova Z.; Divisek J.; Knollova I.; Acic S.; Biurrun I.; Boch S.; Bonari G.; Campos J.A.; Carni A.; Carranza M.L.; Casella L.; Chiarucci A.; Custerevska R.; Delbosc P.; Dengler J.; Fernandez-Gonzalez F.; Gegout J.-C.; Jandt U.; Jansen F.; Jaskova A.; Jimenez-Alfaro B.; Kuzemko A.; Lebedeva M.; Lenoir J.; Lysenko T.; Moeslund J.E.; Pielech R.; Ruprecht E.; Sibik J.; Silc U.; Skvorc Z.; Swacha G.; Tatarenko I.; Vassilev K.; Wohlgemuth T.; Yamalov S.; Chytry M.Vecera M.; Axmanova I.; Padulles Cubino J.; Lososova Z.; Divisek J.; Knollova I.; Acic S.; Biurrun I.; Boch S.; Bonari G.; Campos J.A.; Carni A.; Carranza M.L.; Casella L.; Chiarucci A.; Custerevska R.; Delbosc P.; Dengler J.; Fernandez-Gonzalez F.; Gegout J.-C.; Jandt U.; Jansen F.; Jaskova A.; Jimenez-Alfaro B.; Kuzemko A.; Lebedeva M.; Lenoir J.; Lysenko T.; Moeslund J.E.; Pielech R.; Ruprecht E.; Sibik J.; Silc U.; Skvorc Z.; Swacha G.; Tatarenko I.; Vassilev K.; Wohlgemuth T.; Yamalov S.; Chytry M

    Benchmarking plant diversity of Palaearctic grasslands and other open habitats

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    Abstract Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 mÂČ and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology
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