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. Abbreviations: EIV = Ecological indicator value; EIVE = Ecological Indicator Values for Europe; EVA = European Vegetation Archive; GBIF = Global Biodiversity Information Facility; i = index for taxa; j = index for EIV systems; L = ecological indicator for light; M = ecological indicator for moisture; N = ecological indicator for nitrogen availability; R = ecological indicator for reaction; T = ecological indicator for temperature.
The advantages and disadvantages of some most common methods of quantitative analysis used in processing of synphytoindication data were analyzed. These methods enabled reflection of important ecological characteristics of plant communities and assessment of the nature of their topological and regional differentiation characterizing α-, β-, γ-diversity. We also examined current debatable issues regarding the use of scales of ecological indicator values and methods of their correct comparison based on bringing to a single "denominator". The visual aspects of the gradient analysis used in assessment of topological differentiation of habitats based on the establishment of various types (vector, combinative and complex) of ecological and coenotic profiles are considered. We focused our attention on the application of optimal models of ordination methods (detrended correspondence analysis – DCA, non-metric multidimensional scaling – NMDS). The use of cluster analysis reflected in various methods of dendrogram constructing was evaluated. The analysis of the above methods allows us to evaluate the efficiency of their use in various aspects of synphytoindication techniques. This allows us to use such data for forecasting and modeling biocoenoses changes and development, for assessment and classification of biotopes, landscape structure (ecomer), zoning (ecochor), as well as for evaluation of the resistance of vegetation to the influence of external factors. The methods and approaches of mathematics and cybernetics are expected to be more widely used in geobotany in the future, since many pressing ecological issues related to non-linear development, emergent changes in the ecosystems properties and search for critical thresholds cannot be solved in a traditional way.
Based on the analysis of more than 17,000 vegetation plots (relevés), the participation of 261 protected species (254 vascular plants, six lichens, and one bryophyte) in 30 EUNIS grassland habitat types was revealed. Vegetation plots were assigned to the habitat types using the EUNIS-ESy expert system with further verification. We consider as protected species those listed in the current edition of the Red Data Book of Ukraine, Resolution 6 of the Bern Convention, Annexes II and IV of the Habitat Directive, and the IUCN Red List (only categories VU, EN, CR). The participation of protected species was studied according to the following three criteria: (1) the total number of protected species in the plots assigned to a certain habitat type, (2) the number of plots in which at least one protected species is present, and (3) the mean number of protected species per plots within each habitat type. True steppes (R1B) and meadow steppes (R1A) differed with a significant predominance of the total number of protected species. Arctic alpine calcareous grassland (R44) and Continental dry rocky steppic grassland and dwarf scrub on chalk outcrops (R15) had the largest proportion of plots with protected species and the highest mean numbers of protected species per relevé. Saline habitats, in particular Temperate inland salt marsh (R63) and Semi desert salt pan (R64), were characterized by the smallest number of plots with protected species. Among all species, Gymnadenia conopsea, Stipa capillata, Colchicum autumnale and Gladiolus imbricatus occurred in the largest number of studied habitat types. Based on the results of the analysis, appropriate ways of optimizing the protection of grassland habitats and protected species are proposed.
Польові дослідження проводились у веснянолітній період 2013-2017 рр. і передбачали виконання геоботанічних описів із прив'язкою до географічних координат кожного опису за допомогою GPS-навігатора Magellan Triton 400. На основі зібраних матеріалів була створена база даних у програмі ТURBOVEG 2.79 (Hennekens, Schaminée, 2001). Подальшу обробку зібраного матеріалу пров одили в програмі Juice (Tichý, 2002), що передбачало побудову кластерів та оцінку їхньої
Наведено класифікаційну схему біотопів ПЗ «Крейдова флора» (Донецька обл.), яка найбільш детально описує рослинний покрив заповідника. Для визначення біотопів досліджуваної територі ї під час експедицій у різні етапи вегетаційного періоду (з квітня по серпень упродовж 2016-2019 рр.) було проведено геоботанічні описи в усіх частинах заповідника. За результатами власних досліджень, а також аналізу літературних і картографічних джерел [4-7] було сформовано класифікаційну схему біотопів, основою для якої стали класифікації UkrBiotop, розроблені для різних регіонів України.
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