Diversity of Mulgedio-Aconitetea communities in the Sudetes Mts. (SW Poland) in the Central European context

Abstract

Aims: To describe the compositional and ecological diversity of Mulgedio-Aconitetea communities in the Sudetes Mts. and their foothills. Study area: The Sudetes Mts. (Southwestern Poland). Methods: A total of 399 vegetation relevés from own field studies and the literature were sorted into groups that match the higher syntaxa of the EuroVegChecklist and associations described in the literature. Diagnostic species of the so delimited associations were determined with the phi-coefficient of association, and maps of the associations produced. Direct ordination methods were applied to identify the main environmental gradients shaping the plant communities. Results: We distinguished nine associations, belonging to four alliances: submontane and colline communities (Petasition officinalis: Geranio phaei-Urticetum dioicae, Petasitetum hybridi, Chaerophyllo hirsuti-Petasitetum albi, Prenanthetum purpureae), upper montane nitrophilous communities (Rumicion alpini: Rumicetum alpini); subalpine communities with a dominance of graminoids and ferns (Calamagrostion villosae: Poo chaixii-Deschampsietum cespitosae, Crepido conyzifoliae-Calamagrostietum villosae, Athyrietum filicis-feminae) and subalpine tall-herb communities (Adenostylion alliariae: Cicerbitetum alpinae). Altitude, light availability, and bedrock type, which determines nutrient availability and soil reaction, played an important role in differentiating the studied communities. Conclusions: For convenience, we placed the four alliances in four separate orders as in the EuroVegChecklist. The fact that our ordination diagram separated only two main groups suggests the need of further research in this matter. Taxonomic reference: Euro+Med (2006-) for vascular plants. Syntaxonomic reference: Higher syntaxa follow Mucina et al. (2016). Abbreviations: db-RDA = distance-based redundancy analysis; EIV = Ellenberg indicator value; pANOVA = permutational analysis of variance; PCoA = principal coordinates analysis.