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

GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

Investigation on Zinc Selenide and Copper Selenide Thin Films Produced by Chemical Bath Deposition

The zinc selenide and copper selenide thin films were deposited by chemical deposition technique on glass substrates. For both films, sodium selenosulphate was used as a selenide ion source in an alkaline solution. The X-ray diffraction patterns show that the ZnSe has a cubic structure and $Cu_3Se_2$ film has a tetragonal structure. The relative intensity $K_β / K_α$ of zinc and copper selenide thin films has been measured by using a $\text{}^{241}Am$ radioisotope source (75 mCi). The obtained results were compared with the theoretical values

Germination sensitivity to water stress in four shrubby species across the Mediterranean Basin

Mediterranean shrublands are generally water-limited and fire-driven ecosystems. Seed-based post-fire regeneration may be affected by varying rainfall patterns, depending on species sensitivity to germinate under water stress. In our study, we considered the germination response to water stress in four species from several sites across the Mediterranean Basin. Seeds of species with a hard coat (Cistus monspeliensis, C. salviifolius, Cistaceae, Calicotome villosa, Fabaceae) or soft coat (Erica arborea, Ericaceae), which were exposed or not to a heat shock and smoke (fire cues), were made to germinate under water stress. Final germination percentage, germination speed and viability of seeds were recorded. Germination was modelled using hydrotime analysis and correlated to the water balance characteristics of seed provenance. Water stress was found to decrease final germination in the three hard-seeded species, as well as reduce germination speed. Moreover, an interaction between fire cues and water stress was found, whereby fire cues increased sensitivity to water stress. Seed viability after germination under water stress also declined in two hard-seeded species. Conversely, E. arborea showed little sensitivity to water stress, independent of fire cues. Germination responses varied among populations of all species, and hydrotime parameters were not correlated to site water balance, except in E. arborea when not exposed to fire cues. In conclusion, the species studied differed in germination sensitivity to water stress; furthermore, fire cues increased this sensitivity in the three hard-seeded species, but not in E. arborea. Moreover, populations within species consistently differed among themselves, but these differences could only be related to the provenance locality in E. arborea in seeds not exposed to fire cues. © 2016 German Botanical Society and The Royal Botanical Society of the Netherland

Numerical classification and ordination of Esenli (Giresun) forest vegetation

KARAKOSE, MUSTAFA/0000-0003-0534-3996WOS: 000503432200003The forest vegetation of Esenli Forest Planning Unit was investigated between 2015 and 2018 from the phytosociological point of view. The study area is situated in the Euxine province of Euro-Siberian Region. Phytosociological studies were carried out in accordance with the classical Braun-Blanquet methodology, and 131 releves were collected during the field survey. The releves were classified using the Modified TWINSPAN classification, and general distribution patterns of vegetation were analysed using indirect ordination analysis (Principal Component Analysis) with the R-Project available in the JUICE program. In addition to topographic factors, ecological factors were assessed using the mean Ellenberg Indicator Values to observe the ecological relationships among communities. Four new plant associations (Cirsio trachylepidis-Pinetum sylvestris, Angelico sylvestri-Alnetum barbatae, Circaeo lutetianae-Fagetum orientalis, and Veronico chamaedryo-Piceetum orientalis) were described as belonging to humid montane coniferous and thermophilous deciduous forests within four classes. Distribution pattern of plant communities was strictly influenced by altitude, inclination, moisture, nutrient content, and light

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

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

Motivation 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. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked