Testing macroecological abundance patterns: The relationship between local abundance and range size, range position and climatic suitability among European vascular plants

Aim: A fundamental question in macroecology centres around understanding the relationship between species' local abundance and their distribution in geographical and climatic space (i.e. the multi‐dimensional climatic space or climatic niche). Here, we tested three macroecological hypotheses that link local abundance to the following range properties: (a) the abundance-range size relationship, (b) the abundance-range centre relationship and (c) the abundance-suitability relationship. Location: Europe. Taxon: Vascular plants. Methods: Distribution range maps were extracted from the Chorological Database Halle to derive information on the range and niche sizes of 517 European vascular plant species. To estimate local abundance, we assessed samples from 744,513 vegetation plots in the European Vegetation Archive, where local species' abundance is available as plant cover per plot. We then calculated the 'centrality', that is, the distance between the location of the abundance observation and each species' range centre in geographical and climatic space. The climatic suitability of plot locations was estimated using coarse‐grain species distribution models (SDMs). The relationships between centrality or climatic suitability with abundance was tested using linear models and quantile regression. We summarized the overall trend across species' regression slopes from linear models and quantile regression using a meta‐analytical approach. Results: We did not detect any positive relationships between a species' mean local abundance and the size of its geographical range or climatic niche. Contrasting yet significant correlations were detected between abundance and centrality or climatic suitability among species. Main conclusions: Our results do not provide unequivocal support for any of the relationships tested, demonstrating that determining properties of species' distributions at large grains and extents might be of limited use for predicting local abundance, including current SDM approaches. We conclude that environmental factors influencing individual performance and local abundance are likely to differ from those factors driving plant species' distribution at coarse resolution and broad geographical extents

Distribution maps of vegetation alliances in Europe

Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

Distribution maps of vegetation alliances in Europe

Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

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

European Vegetation Archive (EVA): An integrated database of European vegetation plots

© 2016 International Association for Vegetation Science. 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 vegetation- plot 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 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

Different sets of traits explain abundance and distribution patterns of European plants at different spatial scales

Plant functional traits summarize the main variability in plant form and function across taxa and biomes. We assess whether geographic range size, climatic niche size, and local abundance of plants can be predicted by sets of traits (trait syndromes) or are driven by single traits. Location: Eurasia. Methods: Species distribution maps were extracted from the Chorological Database Halle to derive information on the geographic range size and climatic niche size for 456 herbaceous, dwarf shrub and shrub species. We estimated local species abundances based on 740,113 vegetation plots from the European Vegetation Archive, where abundances were available as plant species cover per plot. We compiled a complete species-by-trait matrix of 20 plant functional traits from trait databases (TRY, BiolFlor and CLO-PLA). The relationships of species’ geographic range size, climatic niche size and local abundance with single traits and trait syndromes were tested with multiple linear regression models. Results: Generally, traits were more strongly related to local abundances than to broad-scale species distribution patterns in geographic and climatic space (range and niche size), but both were better predicted by trait combinations than by single traits. Local abundance increased with leaf area and specific leaf area (SLA). Geographic range size and climatic niche size both increased with SLA. While range size increased with plant height, niche size decreased with leaf carbon content. Conclusion: Functional traits matter for species’ abundance and distribution at both local and broad geographic scale. Local abundances are associated with different combinations of traits as compared to broad-scale distributions, pointing to filtering by different environmental and ecological factors acting at distinct spatial scales. However, traits related to the leaf economics spectrum were important for species’ abundance and occurrence at both spatial scales. This finding emphasizes the general importance of resource acquisition strategies for the abundance and distribution of herbaceous, dwarf shrub and shrub species

Ellenberg‐type indicator values for European vascular plant species

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 repositor

sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring

Rooting depth and xylem vulnerability are independent woody plant traits jointly selected by aridity, seasonality, and water table depth

Evolutionary radiations of woody taxa within arid environments were made possible by multiple trait innovations including deep roots and embolism-resistant xylem, but little is known about how these traits have coevolved across the phylogeny of woody plants or how they jointly influence the distribution of species. We synthesized global trait and vegetation plot datasets to examine how rooting depth and xylem vulnerability across 188 woody plant species interact with aridity, precipitation seasonality, and water table depth to influence species occurrence probabilities across all biomes. Xylem resistance to embolism and rooting depth are independent woody plant traits that do not exhibit an interspecific trade-off. Resistant xylem and deep roots increase occurrence probabilities in arid, seasonal climates over deep water tables. Resistant xylem and shallow roots increase occurrence probabilities in arid, nonseasonal climates over deep water tables. Vulnerable xylem and deep roots increase occurrence probabilities in arid, nonseasonal climates over shallow water tables. Lastly, vulnerable xylem and shallow roots increase occurrence probabilities in humid climates. Each combination of trait values optimizes occurrence probabilities in unique environmental conditions. Responses of deeply rooted vegetation may be buffered if evaporative demand changes faster than water table depth under climate change.Plant sciencesNaturali