Gradient analysis (DCA) of the dataset. Environmental variables and EIVs are projected over the ordination. The vectors shown correlate with at least |r| = 0.80 with one of the two axes. Above – vegetation types; below – the 20 most common species in the relevés, as well as the diagnostic species of the numerical classification, are shown: “Arabsubc” – Arabis subcoriacea; “Agrogiga” – Agrostis gigantea; “Aneuping” – Aneura pinguis; “Astebell” – Aster bellidiastrum; “Bracglar” – Brachythecium glareosum; “Bracrivu” – Brachythecium rivulare; “Bryupseu” – Bryum pseudotriquetrum aggr.; “Caredava” – Carex davalliana; “Careflac” – Carex flacca; “Chaehirs” – Chaerophyllum hirsutum; “Cratdeci” – Cratoneuron decipiens; “Desccesp” – Deschampsia cespitosa; “Epilalsi” – Epilobium alsinifolium; “Equivari” – Equisetum variegatum: “Gerasylv” – Geranium sylvaticum; “Knauaggr” – Knautia dipsacifolia; “Palufalc” – Palustriella falcata; “Palucomm” – Palustriella commutata; “Plagaspl” – Plagiochila asplenioides; “Plagmedi” – Plagiomnium medium; “Polyvivi” – Polygonum viviparum; “Poteerec” – Potentilla erecta; “Rhizmagn” – Rhizomnium magnifolium; “Salifoet” – Salix foetida; “Saxiaizo” – Saxifraga aizoides; “Seslcaer” – Sesleria caerulea; “Toficaly”– Tofieldia calyculata.