The Balkan Vegetation Database (BVD; GIVD ID: EU-00-019) is a regional database, which was established in 2014. It comprises phytosociological relevés covering various vegetation types from nine ...countries of the Balkan Peninsula (Albania – 153 relevés, Bosnia and Herzegovina – 1715, Bulgaria – 12,282, Greece – 465, Croatia – 69, Kosovo – 493, Montenegro – 440, North Macedonia – 13 and Serbia – 2677). Currently, it contains 18,306 relevés (compared to 9.580 in 2016), and most of them (82.8%) are geo-referenced. The database includes both digitized relevés from the literature (65.6%) and unpublished data (34.5%). Plot size is available for 84.7% of all relevés. During the last four years some “header data information” was improved e.g. elevation (now available for 83.4% of all relevés), aspect (67.7%), slope (66%), total cover of vegetation (54.3%), cover of tree, shrub, herb, bryophyte and lichen layers (27.1%, 20.1%, 40.2%, 11.5% and 2.1%), respectively. Data access is either semi-restricted (65.6%) or restricted (34.4%). Most relevés (84.6%) are classified to syntaxa of different levels. The database has been used for numerous studies with various objectives from floristic, vegetation and habitat-related topics, to macroecological studies at the local, regional, national, continental and global levels. During the last four years, BVD data were requested from 111 different projects via the EVA and sPlot databases.
A total of 546 releves collected in western Bulgaria and referred to Festuco-Brometea were classified into the alliances Festucion valesiacae, Saturejion montanae, Cirsio-Brachypodion pinnati and ...Chrysopogono-Danthonion calycinae. All releves assigned to alliance Cirsio-Brachypodion pinnati were further classified towards lower level which resulted in the description of a new association - Hieracio pilosellae-Festucetum dalmaticae and two new subassociations added to ass. Galio lovcense-Artemisietum chamaemelifoliae. Both associations were ecologically well differentiated on the basis of soil parameters (pH and humus content) as well as some additional factors (exposition, land use, etc.).
V zahodni Bolgariji smo naredili 546 vegetacijskih popisov, ki jih uvrščamo v razred Festuco-Brometea in dalje v zveze Festucion valesiacae, Saturejion montanae, Cirsio-Brachypodion pinnati in Chrysopogono-Danthonion calycinae. Vse popise, ki smo jih uvrstili v zvezo Cirsio-Brachypodion pinnati smo členili na nižje sintaksonomske enote. Opisali smo novo asociacijo - Hieracio pilosellae-Festucetum dalmaticae in dodali dve novi subasociaciji k asociaciji Galio lovcense-Artemisietum chamaemelifoliae. Obe asociaciji sta ekološko jasno ločeni na podlagi talnih parametrov (pH in vsebnost humusa) in nekaterih dodatnih dejavnikov (ekspozicija, raba tal, itd.).
Questions: Studying dry grasslands in a previously unexplored region, we asked: (a) which environmental factors drive the diversity patterns in vegetation; (b) are taxonomic groups (vascular plants, ...bryophytes, lichens) and functional vascular plant groups differently affected; and (c) how is fine‐grain beta diversity affected by environmental drivers?
Location: Northwestern and Central Bulgaria.
Methods: We sampled environmental data and vascular plant, terricolous bryophyte and lichen species in 97 10‐m2 plots and 15 nested‐plot series with seven grain sizes (0.0001–100 m2) of ten grassland sites within the two regions. We used species richness as measure of alpha‐diversity and the z‐value of the power‐law species–area relationship as measure of beta‐diversity. We analysed effects of landscape, topographic, soil and land‐use variables on the species richness of the different taxonomic and functional groups. We applied generalised linear models (GLMs) or, in the presence of spatial autocorrelation, generalised linear mixed‐effect models (GLMMs) in a multi‐model inference framework.
Results: The main factors affecting total and vascular plant species richness in 10‐m2 plots were soil pH (unimodal) and inclination (negative). Species richness of bryophytes was positively affected by rock cover, sand proportion and negatively by inclination. Inclination and litter cover were also negative predictors of lichen species richness. Elevation negatively affected phanerophyte and therophyte richness, but positively that of cryptophytes. A major part of unexplained variance in species richness was associated with the grassland site. The z‐values for total richness showed a positive relationship with elevation and inclination.
Conclusions: Environmental factors shaping richness patterns strongly differed among taxonomic groups, functional vascular plant groups and spatial scales. The disparities between our and previous findings suggest that many drivers of biodiversity cannot be generalised but rather depend on the regional context. The large unexplained variance at the site level calls for considering more site‐related factors such as land‐use history.
We analysed drivers of species richness of vascular plants, bryophytes, lichens and functional groups of vascular plants in Bulgarian dry grasslands across seven spatial scales (0.0001–100 m2) with multi‐model inference. We found strong differences in environmental factors shaping richness among these groups and across scales. The high explanatory power of grassland site highlights the importance of the regional context.
Aims
Developing a hierarchical classification system for classes, orders and alliances of the diverse dry grasslands of the Central and Eastern Balkan Peninsula and translating this into an ...electronic expert system (ES) for the automatic assignment of plots.
Location
Serbia, Kosovo, North Macedonia, Bulgaria and northern Greece.
Methods
We extracted 5734 plots from the Balkan Dry Grassland Database corresponding to eight classes of dry grasslands reported from the region, using the EuroVegChecklist ES. This data set and later the plots within each derived subunit were subjected to a new numerical approach: starting with an initial partitioning (expert‐interpreted TWINSPAN classification), diagnostic species were determined based on their phi‐values for the target vegetation type and the differences in phi‐values to the next similar types. These diagnostic species were fed into an ES to create a new partitioning, a procedure which was iterated until diagnostic species and species of the ES converged. Then the same approach was applied within each of the derived units to define the units of the next‐lower level.
Results
The iterative cluster optimisation (ICO) converged in all cases. The resulting hierarchical expert system (HES) classified 95% of all plots to alliances. We distinguished four classes with eight orders and 12 alliances: (1) Tuberarietea guttatae (Romuleion); (2) Stipo‐Brachypodietea distachyi (Clinopodio alpini‐Thymion striati); (3) Festuco‐Brometea with Brachypodietalia pinnati (Chrysopogono‐Danthonion calycinae and Cirsio‐Brachypodion pinnati), Festucetalia valesiacae (Festucion valesiacae), an unnamed order of rocky steppes (with Pimpinello‐Thymion zygioidis) and Koelerietalia splendentis (Centaureo‐Bromion fibrosi, Saturejion montanae and Diantho haematocalycis‐Festucion hirtovaginatae); (four) Koelerio‐Corynephoretea with Sedo acris‐Festucetalia (Festucion vaginatae) and Trifolio arvensis‐Festucetalia ovinae (Armerio rumelicae‐Potentillion and Minuartio montanae‐Poion molinerii all. nov.).
Conclusions
We created a unified hierarchical classification with an electronic ES using diagnostic species defined by phi‐values. Our new approach (ICO‐HES: iterative cluster optimisation for hierarchical expert systems) allows dividing large data sets into meaningful units at several hierarchical levels, and thus has high potential for complex classifications. Importantly, it overcomes the divide between ES species and diagnostic species and re‐unites them into one concept.
We classified the dry grasslands of the Central and Eastern Balkan Peninsula with a large dataset and a new classification approach, called iterative cluster optimisation for hierarchical expert systems (ICO‐HES). We distinguish and describe 12 alliances, placed in eight orders and four classes, with one alliance and one order new to science. ICO‐HES has great potential also for other classifications as it is hierarchical, leaves very few plots unclassified and unites expert system species and diagnostic species into one concept.
This study deals with the diversity of forest vegetation in the Slivenska Mountain (Eastern Stara planina) and presents a contemporary classification scheme for the identified syntaxa. A total of 137 ...relevés were collected and analyzed using specialized software (JUICE 7.0 and PC-ORD Version 4). As a result, forest vegetation is classified into 10 associations, 3 subassociations, 4 variants and 5 communities They belong to 7 alliances, 5 orders and 3 classes:
e,
and
. The recorded 18 distinguished vegetation groups show a relatively high diversity of forest plant communities of the study area.
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