Lysenko 91,92 | Armin Macanović 93 | Parastoo Mahdavi 94 | Peter Manning 35 | Corrado Marcenò 13 | Vassiliy Martynenko 95 | Maurizio Mencuccini 96 | Vanessa Minden 97 | Jesper Erenskjold Moeslund 54 | Marco Moretti 98 | Jonas V. Müller 99 | Abstract Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level.Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale. K E Y W O R D S biodiversity, community ecology, ecoinformatics, functional diversity, global scale, macroecology, phylogenetic diversity, plot database, sPlot, taxonomic diversity, vascular plant, vegetation relevé 166 |

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 m2 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.

Question: How can we determine differential taxa in a vegetation data set? Methods: The new algorithm presented here uses an intuitive fidelity threshold based on relative constancy differences. It is tested on a simulated and a real data set. The results of the proposed algorithm are discussed in comparison with other methods used for the determination of differential taxa. Results: The new algorithm defines each taxon in each group of relevés as: (1) positively differentiating, (2) positively‐negatively differentiating, (3) negatively differentiating, or (4) non‐differentiating. Each taxon in a data set may be: (1) positively, positively‐negatively or negatively differentiating for each group in the data set, (2) differentiating for some groups and non‐differentiating for the remaining groups, or (3) non‐differentiating for all groups in the data set. Conclusions: The new algorithm finds the relevé groups that are positively differentiated against other groups that are negatively differentiated. It reveals differentiating structures in the data set and thus makes quantification of the relations among and between different syntaxonomic ranks conceivable. As it distinguishes between different types of differential taxa, it might improve standards of typification in vegetation classification.

The aim of this study is to investigate the flood management and mitigation measures in ungauged NATURA protected watersheds. The examined watersheds are located in one the most European significant NATURA areas (Prespa Natural Park North Greece). SCS-CN model was applied to perform the hydrological modeling for extreme rainfalls of 50, 100 and 1000 return periods. Extensive field research was conducted to record all the hydrotechnical works of the study area, to evaluate their current condition and measure the respective hydraulic characteristics. The results of the hydrological modeling showed that the flood danger in the study area is generally low. However, almost the half of the hydrotechnical works could not discharge the high and medium probability (50 and 100 years) peak flows. The main causes are the extremely dense riparian vegetation that has been developed on the banks and the thalweg of the riverbeds and in some cases the inappropriate dimensioning of the technical works. The intense development of the riparian vegetation, has increased the roughness coefficient and reduced the dimensions and discharge capability of the technical works, while NATURA restrictions and regulations may be limiting any logging and trimming activities within the streams, especially in priority habitat types. Special Ecological Evaluation studies and educating the public about the necessity of the flood control measures and impact, could provide a framework for a thorough discussion about the flood management in NATURA areas.

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