An expert-based classification of high-altitude arctic-alpine vegetation of the class Carici rupestris-Kobresietea Ohba 1974: Achievements and obstacles

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An expert-based classification of high-altitudearctic-alpine vegetation of the class Carici rupestris-Kobresietea Ohba 1974: Achievements and obstaclesI. Svitková a & J. Šibík aa Institute of Botany, Slovak Academy of Sciences, Dúbravská cesta 9, SK-845 23, Bratislava,Slovakia

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An expert-based classification of high-altitude arctic-alpine vegetationof the class Carici rupestris-Kobresietea Ohba 1974: Achievements andobstacles

I. SVITKOVA & J. SIBIK

Institute of Botany, Slovak Academy of Sciences, Dubravska cesta 9, SK-845 23 Bratislava, Slovakia

AbstractThe specific species-rich high-altitude vegetation of the class Carici rupestris-Kobresietea bellardii Ohba 1974 (CK), with theoccurrence of many arctic-alpine and endemic species, was chosen for a case study. The analyses were based on a dataset of37,204 phytosociological releves from the Slovak Vegetation Database. The traditional classification of the class CK, basedon cluster analyses, was reproduced satisfactorily by means of formalised classification, based on the formal definitionscreated by the Cocktail method together with the frequency-positive fidelity index affiliation. Unequivocal assignmentcriteria for all eight associations of both alliances [Oxytropido-Elynion Br.-Bl. (1948) 1949 and Festucion versicoloris Krajina1933] of the class CK were formulated. The formal delimitations followed the traditional ones very well. It was demonstratedthat the results of applying the formal definitions created on the basis of a large, geographically stratified dataset capturing theoccurrence of all vegetation types in Slovakia were highly similar in comparison with the traditional classification based onthe results of cluster analysis. The reliability and the pros and cons of the expert system are also discussed.

Keywords: Alpine communities, Cocktail method, frequency-positive fidelity index, syntaxonomy, Western Carpathians

Introduction

Phytosociological research has a long history in

Europe (cf. Schaminee et al. 2011), and hence in

Slovakia as well, where it goes back to the beginning

of the 20th century. Although the description of the

vegetation (including its characteristics, structure,

dynamics and variability, and its consequent classi-

fication in a particular region – e.g. country,

mountain range, continent) is quite often not among

the main goals of scientific research, it serves as an

irreplaceable tool for the generation of a conceptual

basis for phytosociology and habitat mapping (Chy-

try 2000). Phytosociological studies produced local

and regional overviews of vegetation types based on

the classification of the sampled releves (Schaminee

et al. 2009). Local studies were progressively

supplanted by vegetation surveys of larger regions.

The initial methods of manual and intuitive evalua-

tion and comparison of vegetation were later

replaced with the development of more powerful

computers and software for vegetation data analysis,

by more unbiased statistical analyses and methods

(Mucina & van der Maarel 1989; Chytry & Tichy

2003; Podani 2005, 2006; Jarolımek & Sibık 2008;

Carni et al. 2011).

During the last decade, several studies summarised

the vegetation overviews in individual countries

(Rodwell 1990, 1991, 1992; Grabherr & Mucina

1993; Valachovi�c et al. 1995; Jarolımek et al. 1997;

Valachovi�c 2002; Kliment & Valachovi�c 2007) and

were followed by supra-regional syntheses (Dubravko-

va et al. 2010; Michl et al. 2010; Sibık et al. 2010).

Simultaneous with these studies, there was an

effort to create methods that do not have the

disadvantages of traditional numerical classifications,

which in some cases do not take into account the

general diagnostic value of the species or the fact that

it is based on the current structure of the analysed

datasets only and hence it is valid only in the used

partial datasets. These new methods are usually

referred to as formalised approaches and should aim

at precise definitions of classification criteria and

algorithms (Chytry 2000). The Cocktail method

Correspondence: I. Svitkova, Institute of Botany, Slovak Academy of Sciences, Dubravska cesta 9, SK-845 23 Bratislava, Slovakia. Email:

[email protected]

Plant Biosystems, 2012; 1–18, iFirst article

ISSN 1126-3504 print/ISSN 1724-5575 online ª 2012 Societa Botanica Italiana

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(Bruelheide 1995, 2000) has become one of the most

used methods in classification of large datasets to

determine the major vegetation types by providing

unequivocal criteria for assignment of releves to the

plant associations (Bruelheide & Chytry 2000). The

first complex national vegetation overview based on

the formalised criteria was the series Vegetation of the

Czech Republic (Chytry 2007, 2009), which followed

numerous studies dealing with defining formalised

criteria for particular vegetation types in different

regions (Ko�cı et al. 2003; Boublık et al. 2007; Dıte

et al. 2007, Role�cek 2007, Silc & Carni 2007,

Hrivnak et al. 2008, Boublık 2010, Rozbrojova et al.

2010).

The high-altitude vegetation of Slovakia (the

Western Carpathians) was analysed only recently

(Kliment & Valachovi�c 2007), using traditional

methods based on cluster analyses. The specifics of

high-altitude vegetation, its patchiness and abrupt

changes in individual ecological gradients causing

great variability were all taken into account when

performing the cluster analyses, which were often

achieved in several steps by experts specialising in

individual vegetation types (cf. Kliment et al. 2010).

Recently, alongside the vegetation surveys of

Slovakia, the preparation of an expert system for

the identification of individual vegetation units in

Slovakia has started, using external a priori defined

criteria created by the Cocktail method. The first

publication to use this system is a survey of meadow

and pasture vegetation (Janisova et al. 2007). Since

the time when the formal definitions were created for

individual vegetation units of meadows and pastures

(Janisova et al. 2007), a number of releves, primarily

of high-altitude vegetation, have increased signifi-

cantly in the Slovak Vegetation Database (SVD, cf.

Sibıkova et al. 2009). Moreover, the quality of data

already stored in the database increased dramatically

as a result of the more accurate post-hoc identification

of the geographical coordinates of older releves, more

precise control of data input, and other changes.

Hence, it was necessary to take this fact into account in

this study and to critically evaluate the constituents of

some previously defined species groups.

The class Carici rupestris-Kobresietea bellardii Ohba

1974 (CK) represents a specific species-rich high-

altitude vegetation, which includes many arctic-alpine

and endemic species (Sibıkova et al. 2010). It was

chosen as a case study due to several facts. It is a

natural type of vegetation, only minimally influenced

by human activities and individual associations are

well determined. The basic question of our analyses

was if the application of formal definitions created on

the basis of an extensive dataset capturing the

occurrence of all vegetation types in Slovakia will yield

similar results in comparison with the traditional

classification based on the results of cluster analysis.

The main goals of this study can be summarised as

follows: (i) to create unequivocal definitions of the

traditional associations using the combinations of

created species groups and to characterise the

successfully delimited associations; (ii) to test the

applicability of the definitions and compare the results

with the traditional classifications taking into account

the reliability of the expert system.

Material and methods

The analyses were based on a dataset of 37,204

phytosociological releves from the SVD (Jarolımek &

Sibık 2008, www.ibot.sav.sk/cdf; Sibıkova et al.

2009; Sibık 2012) and from the private databases

of the authors. The releves were exported and further

analysed in the JUICE software (Tichy 2002). Due

to uneven distribution of releves across the country,

geographically stratified resampling of the dataset

was performed in JUICE software (Tichy 2002)

using a 1.25 longitudinal6 0.75 latitudinal minute

geographical grid (cf. Knollova et al. 2005). The

resulting dataset of 21,142 releves, including mosses

and lichens, was used for all analyses.

Species found in several layers (especially woody

species) were merged into one layer in each releve.

Taxa determined only to the genus level were

excluded from the analysis. Taxa determined to the

subspecies and variety level were merged to the

species level or within broadly conceived taxa. The

nomenclature of the vascular plants generally follows

the checklist by Marhold and Hindak (1998). The

detailed methods of preparing the dataset follow the

one used by Jarolımek and Sibık (2008).

The species groups (Table I) were created in the

geographically stratified dataset of 21,142 releves by

the Cocktail method (Bruelheide 1995, 2000), using

the phi coefficient (Chytry et al. 2002). The species

groups defined by Janisova et al. (2007) were tested

in our dataset and critically evaluated due to

substantial expansion of releves from high altitudes

in our dataset in comparison with dataset of Janisova

et al. (2007). The phi coefficient was used to

measure species’ tendencies to occur together in

the releves included in the dataset. The aim was to

define such species groups, where individual species

have the highest fidelity values. The defined species

groups had at least three members and were

considered present when at least half of the members

were present. The formal definitions (Table II) of the

associations were created by combining the species

groups using the logical operators AND, OR and

AND NOT (Bruelheide 1997) and the cover value of

diagnostically important taxa. Detailed descriptions

of the individual steps involved in creating the

species groups and definitions can be found in the

study by Ko�cı et al. (2003).

2 I. Svitkova and J. Sibık

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https://www.researchgate.net/publication/227663186_Formalized_reproduction_of_an_expert-based_phytosociological_classification_A_case_study_of_subalpine_tall-forb_vegetation?el=1_x_8&enrichId=rgreq-7bf2abfa-c96a-4ae3-b8f8-7ca23ee0ce13&enrichSource=Y292ZXJQYWdlOzI1NjkxMjMxMztBUzoxMDE2OTMwMjY5OTYyMjhAMTQwMTI1NjkxNTgwMg==

The resulting formal definitions were then tested

and applied to the large dataset of 37,204 phytoso-

ciological releves. To assign the releves that were

assigned to more than one association after applying

the formal definition, as well as the releves that did

not suit any of the definitions and were previously

assigned to the class CK (by the original author or by

Petrık et al. 2006), the frequency-positive fidelity

index (FPFI), which compares the similarity of the

species composition of a selected releve to a group of

releves (Tichy 2005), was used. Only those releves

with a FPFI value of more than 5 were finally

assigned to the association.

A synoptic table (see Supplementary material) was

created and the diagnostic species of the formally

defined associations were determined using the

Table I. Species groups used for the Cocktail classification of the high-altitude arctic-alpine vegetation of the class Carici rupestris-Kobresietea

Ohba 1974 from the Western Carpathians.

Species group No. of releves Species (F6 100)

Androsace chamaejasme 41 Androsace chamaejasme (112.95), Hedysarum hedysaroides (104.27), Oxytropis halleri (90.78)

Carex firma 93 Carex firma (107.13), Dryas octopetala (103.45), Ranunculus alpestris (100.04)

Cerastium eriophorum 69 Cerastium eriophorum (114.52), Carex fuliginosa (109.84), Luzula spicata (102.05)

Doronicum stiriacum 138 Salix retusa agg. (101.90), Doronicum stiriacum (95.74), Pulsatilla scherfelii (90.06)

Draba siliquosa 12 Draba siliquosa (139.30), Plagiobryum demissum (98.89), Agrostis alpina (73.94)

Elyna myosuroides 10 Elyna myosuroides (117.79), Physconia muscigena (112.77), Dactylina madreporiformis (99.50)

Oreochloa disticha 451 Oreochloa disticha (126.08), Campanula alpina (120.97), Juncus trifidus (118.90), Festuca supina

(113.89)

Oxyria digyna 51 Oxyria digyna (113.70), Cardaminopsis neglecta (101.36), Saxifraga androsacea (98.13)

Oxytropis carpatica 24 Oxytropis carpatica (100.09), Helianthemum alpestre (85.29), Arenaria tenella (72.82)

Primula auricula 152 Primula auricula (111.24), Gentiana clusii (102.93), Trisetum alpestre (101.66)

Saxifraga wahlenbergii 26 Saxifraga wahlenbergii (116.29), Pritzelago alpina (76.86), Salix reticulata (75.23)

Silene acaulis 118 Lloydia serotina (123.22), Ligusticum mutellinoides (117.27), Minuartia sedoides (117.22), Silene

acaulis (111.75), Pedicularis oederi (101.21)

Vaccinium myrtillus 1611 Vaccinium myrtillus (119.89), Avenella flexuosa (99.35), Homogyne alpina (98.81), Vaccinium

vitis-idaea (90.29),

Species of each group are ranked by decreasing fidelity to the group, calculated as the phi coefficient in a stratified data set of 21,142 releves

of all vegetation types of Western Carpathians. The F values (multiplied by 100) of the species are given. The number of releves, in which the

group occurs, is the number of releves containing at least half of the group’s species.

Table II. Cocktail definitions of the associations from the class Carici rupestris-Kobresietea Ohba 1974.

Association Cocktail definition

Oxytropido-Elynion

1. Oxytropido carpaticae-

Elynetum

myosuroides

{5### Elyna myosuroides4AND(5### Silene acaulis4OR5### Androsace

chamaejasme4)}AND5Elyna myosuroidesUP054

2. Drabo siliquosae-Festucetum

versicoloris

(5Festuca versicolorUP254AND5### Draba siliquosa4)NOT5Silene acaulisUP124

3. Pyrolo carpaticae-Salicetum

reticulatae

{(5Salix reticulataUP054AND5### Saxifraga wahlenbergii4)AND5### Cerastium

eriophorum4}NOT(5### Oxyria digyna4OR5Carex rupestrisUP054)

4. Festucetum versicoloris {(5### Silene acaulis4AND5Festuca versicolorUP054)AND5### Androsace

chamaejasme4}NOT[{(5Dryas octopetalaUP054OR5Elyna myosuroidesUP054)OR(5Salix

reticulataUP124OR5Oreochloa distichaUP054)}OR(5Carex firmaUP054OR5### Draba

siliquosa4)]

5. Festuco versicoloris-

Oreochloetum distichae

[{(5Festuca supinaUP124OR5Oreochloa distichaUP204)AND5### Oreochloa

disticha4}AND5### Androsace chamaejasme4]NOT5Salix reticulataUP25>

Festucion versicoloris

6. Silenetum acaulis (5### Silene acaulis4AND5Silene acaulisUP054)NOT{((5Festuca

versicolorUP054OR5Oxyria digynaUP124)OR(5### Vaccinium myrtillus4OR5###

Androsace chamaejasme4))OR(5### Oxytropis carpatica4OR5### Saxifraga wahlenbergii4)}

7. Agrosti alpinae-Festucetum

versicoloris

(5### Oreochloa disticha4AND5Festuca versicolorUP054)NOT[((5### Androsace

chamaejasme4OR5Vaccinium vitis-idaeaUP054)OR(5### Saxifraga wahlenbergii4OR5###

Primula auricula4))OR(5Salix alpinaUP254OR5### Draba siliquosa4)]

8. Salicetum kitaibelianae [5Salix retusa agg.UP254OR{(5### Doronicum styriacum4AND5### Oreochloa

disticha4)AND5Salix retusa agg.UP054}]NOT{(5### Carex firma4OR5Festuca

versicolorUP12>)OR(5Juncus trifidusUP05>OR5### Androsace chamaejasme4)}

Classification of high-altitude arctic-alpine vegetation 3

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fidelity calculations in the JUICE software (Tichy

2002), using the final dataset of 422 releves assigned

to the association level by the created formal

definitions and FPFI calculations. Species with phi

values higher than 0.3 and Fisher’s exact test

significance higher than 0.001 (p5 0.001) were

designated as diagnostic. The similarity of synoptic

tables was also calculated by the JUICE software

(Tichy 2002). In the synoptic table, the diagnostic

and most frequent species of all the eight associations

of the class CK are shown.

The main gradients in floristic composition were

analysed by non-metric dimensional scaling (NMDS)

in the R program (R Development Core Team 2007)

via JUICE 7.0. Non-metric dimensional scaling was

used to analyse the matrix of dissimilarities between

samples and was performed on a matrix of Bray–

Curtis dissimilarities between releves. The NMDS was

visualised using the function ‘‘Ordispider’’ in the R

program ‘‘Vegan’’ package (Oksanen et al. 2009),

which draws spider diagrams with each point (releve)

connected to the cluster centroid by a line. A three-

dimensional ordination diagram with sites was drawn.

Statistica 8.0 (StatSoft Inc. 2006, http://www.stat

soft.com/) was used for the construction of box and

whisker plots comparing the individual groups

(vegetation units) using Ellenberg’s indicator values

(Ellenberg et al. 1992). Because the original Ellen-

berg’s indicator values do not list many species

occurring in Slovakia (especially Carpathian and

West Carpathian endemics and subendemics), the

indicator values for such species were added into the

dataset was following the study by Sibıkova et al.

(2010). The Tukey post-hoc test was used for

multiple comparisons following one-way analysis of

variance (ANOVA). Box and whisker plots were also

constructed for the frequency of arctic-alpine ele-

ments and endemics in relation to a particular

vegetation type and for the Shannon–Wiener index

of diversity and the number of vascular plants in

releve. Geographical elements were defined accord-

ing to Sibıkova et al. (2010). Spearman’s correlation

coefficient (non-parametric measure of correlation),

which assesses how well an arbitrary monotonic

function describes the relationship between two

variables, was used (Table III).

The nomenclature of higher syntaxa follows

Jarolımek and Sibık (2008) and Kliment et al.

(2010). The subspecies are marked by an asterisk.

Results

Thirteen species groups were defined in the stratified

dataset by means of the Cocktail method and,

together with the dominance criteria, used in formal

definitions of the associations of the class CK

(Table I). All eight associations from both alliances

of the class CK were satisfactorily reproduced by the

Cocktail definitions.

Some of the species groups are typical for individual

associations (e.g. Elyna myosuroides group for the

association Oxytropido carpaticae-Elynetum myosur-

oides or Draba siliquosa group for the association

Drabo siliquosae-Festucetum versicoloris), for individual

alliances (e.g. Androsace chamaejasme group for the

alliance Oxytropido-Elynion) or for the class Carici

rupestris-Kobresietea bellardii (e.g. Silene acaulis

group). Some species groups were typical for other

classes (e.g. Oreochloa disticha or Vaccinium myrtil-

lus groups) and were used in the definitions to

differentiate marginally overlapping habitats.

The created definitions were applied to a dataset

with 490 releves assigned by Petrık et al. (2006) or

the original authors to the class CK (at the

association, alliance or class level). Of them, based

on the criteria, 380 (77.6%) releves were assigned to

individual associations. Seven releves were assigned

to more than one vegetation unit. After the calcula-

tion of FPFI, six of them were assigned to only one

association. The definitions were also applied to the

unstratified dataset to see whether there are any

releves which would meet the conditions of the

definitions and which were previously classified

within some other higher vegetation units. In this

step, 18 releves from other higher vegetation units

fitted the created definitions and were assigned to

one of the eight associations of CK.

The results, however, matched the traditional

classification based on the cluster analyses. For the

remaining 104 unassigned releves, the FPFI index

was calculated following Ko�cı et al. (2003); accord-

ing to the results, 18 releves were assigned to

individual associations and 86 releves remained

unassigned according to our criteria.

The comparison of synoptic tables generated by

the application of the traditional, expert-based

classification and the classification based on the

Cocktail definitions indicated that their results

agreed at the level of 83.85%.

Table III. Correlations of individual variables in selected vegetation types. The non-parametric Spearman’s correlation test was used.

Significance level: p5 0.001.

Variable Arctic-Alpine Endemics Light Temperature Continentality Moisture Soil reaction Nutrients

Arctic-Alpine – 0.631885 0.633533 70.200291 0.704428 70.277126 0.752559 n.s.

Endemics 0.631885 – 0.386910 n.s. 0.532203 n.s 0.605137 0.264859


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https://www.researchgate.net/publication/227663186_Formalized_reproduction_of_an_expert-based_phytosociological_classification_A_case_study_of_subalpine_tall-forb_vegetation?el=1_x_8&enrichId=rgreq-7bf2abfa-c96a-4ae3-b8f8-7ca23ee0ce13&enrichSource=Y292ZXJQYWdlOzI1NjkxMjMxMztBUzoxMDE2OTMwMjY5OTYyMjhAMTQwMTI1NjkxNTgwMg==

Dissimilarities between vegetation types are de-

picted in Figure 1, which combines the results of our

analysis and NMDS ordination. The main differ-

ences are shown along the first axis, where the releves

from the association Salicetum kitaibelianae are the

most remote in comparison with other communities

from the class CK. The Salicetum kitaibelianae seems

to be the most aberrant syntaxon of the studied

group. This community shows transitional charac-

teristics (floristic and ecological) of several high-rank

syntaxa, including the alliances Festucion versicoloris

and Loiseleurio-Vaccinion. It occupies scree habitats

below the steep rocky cliffs on mylonite or acidic

granite bedrock. The dominant species Salix kitai-

beliana represents microspecies from the broadly

defined group Salix retusa agg. (Dubravcova & Sibık

2006; Petrık et al. 2006; Sibık et al. 2006). According

to the positions of individual centroids (representing

the plant communities) within the first axes, we can

assume a correlation with the gradient of soil reaction

related to the characteristics of the substratum in the

habitats of individual associations, such as the

calcium and magnesium availability in the soil (cf.

Petrık et al. 2006).

Box plot diagrams (Figure 2) show the distribu-

tions of the occurrence of arctic-alpine and endemic

species as well as the richness of vascular plants and

the Shannon–Wiener index of biodiversity in relation

to individual vegetation types from the class CK. A

comparison of groups according to Ellenberg’s

indicator values is shown in box plot diagrams, too

(Figure 3). The significant differences between the

associations are depicted by the letters a–d.

To interpret the correlations between arctic-

alpine and endemic species with Ellenberg’s in-

dicator values, as an indirect assessment of environ-

mental factors in selected vegetation types, the non-

parametric Spearman’s correlation test was used

(Table III). The results show that the occurrence of

both the arctic-alpine and the endemic species

increased significantly with increasing light require-

ments, continentality and soil reaction; the occur-

rence of endemic species also correlates positively

with the amount of nutrients. There were significant

negative correlations between the occurrence of the

arctic-alpine species and both moisture and tem-

perature as a result of their occurrence in colder

habitats.

Oxytropido-Elynion Br.-Bl. (1948) 1949

Alpine xero-cryophilous wind-exposed swards and

carpets on calcium-rich soils. Contact vegetation:

Figure 1. Non-metric multi-dimensional scaling (NMDS) ordination diagram of vegetation plots from the class Carici rupestris-Kobresietea

(CK, see legend below). Each spider connects individual plots (releves) to the cluster centroid by a line. Note: Oxytropido-Elynion: 1

Oxytropido carpaticae-Elynetum myosuroides, 2 Drabo siliquosae-Festucetum versicoloris, 3 Pyrolo carpaticae-Salicetum reticulatae, 4 Festucetum

versicoloris, 5 Festuco versicoloris-Oreochloetum distichae; Festucion versicoloris: 6 Silenetum acaulis, 7 Agrosti alpinae-Festucetum versicoloris, 8

Salicetum kitaibelianae.


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Potentillion caulescentis, Caricion firmae, Seslerion

tatrae. Distributional area: Belianske Tatry Mts, rare

Zapadne Tatry Mts.

1. Oxytropido carpaticae-Elynetum myosur-

oides (Puscaru et al. 1956) Coldea 1991

Formal definition: Table II.

Diagnostic species: see Supplementary material, col-

umn 1.

Brief characteristics: Open, species-rich plant com-

munity dominated by Elyna myosuroides and with

high frequencies of Festuca *versicolor and Silene

acaulis with relation to the phytocoenoses of the

rocky fissures of the alliance Potentillion caulescentis. It

occupies extremely windswept rocky ridges and

edges on quartzite, horn-stones and marls in the

alpine belt of the Belianske Tatry Mts.

Comparison: The releves traditionally assigned to this

association met the formal definition.

2. Drabo siliquosae-Festucetum versicoloris

Petrık in Petrık et al. 2006



umn 2.

Brief characteristics: Dense, species-rich, mat-forming

plant community occurring on the terraces on

convex parts of the steep slopes on calcium-rich

shale and horn-stones in the alpine belt of the

Belianske Tatry Mts with a close relation to some

phytocoenoses of the alliance Seslerion tatrae.


association met the formal definition.

3. Pyrolo carpaticae-Salicetum reticulatae Pet-

rık in Petrık et al. 2006



umn 3.

Figure 2. Box plot diagrams of the distribution of arctic-alpine and endemic species, number of vascular plants and Shannon-Wiener

diversity index in relation to individual associations. Significant differences between the associations are depicted by the letters a–d, and these

differences were tested by Tukey’s post-hoc test (p50.05). The box length is the interquartile range. The square inside the boxes indicates

the median. For legend for associations see Figure 1.


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Brief characteristics: Dense, species-rich plant com-

munity with the typical character of arctic-alpine

tundra seen in the low carpets of Salix reticulata and

Dryas octopetala. The stands occur on windward

marly (or less often calcareous) slopes with relatively

long snow cover in the ridge parts of the Belianske

Tatry Mts. The stands have close relations to the

association Arenario tenellae-Caricetum firmae (alli-

ance Caricion firmae).

Comparison: The formal definition did not include a

small group of releves with high frequency or

dominancy of Carex firma. These releves might have

closer relations to the stands from the alliance

Caricion firmae.

Figure 3. Box and whisker plots of the Ellenberg’s indicator values in relation to individual associations. Letters a–d indicate homogenous

groups according to post-hoc comparisons using ANOVA (Tukey test, p50.05). The box length is the interquartile range. The square

inside the boxes indicates the median. For legend for associations see Figure 1.


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4. Festucetum versicoloris Domin 1929



umn 4.

Brief characteristics: Species-rich, cushion- and mat-

forming plant community dominated by Festuca

*versicolor and Silene acaulis. At lower altitudes and

on more leeward slopes, it is closely related to the

phytocoenoses of the alliance Seslerion tatrae (Seslerio

tatrae-Festucetum versicoloris). It occupies the rocky

slopes on calciphilous slates, horn-stones and marls

in the alpine belt of the Belianske Tatry Mts.


small group of releves of dense phytocoenoses with

the occurrence of acidophilous species, such as

Luzula alpinopilosa or Doronicum stiriacum, or the

high frequency of Cetraria islandica previously as-

signed to subass. caricetosum atratae Petrık et al. 2006.

These releves have relatively close relations to the

association Festuco versicoloris-Oreochloetum distichae

(cf. Petrık et al. 2006; Sibık et al. 2007), but they do

not meet the definition of this association either.

5. Festuco versicoloris-Oreochloetum distichae

Pawłowski et Stecki 1927 corr. Petrık et al.

2006 nom. invers. propos.



umn 5.

Brief characteristics: Species-rich, cushion- and mat-

forming plant community dominated by Festuca

supina and Silene acaulis, with a high frequency of

Oreochloa disticha and the occurrence of acidophilous

species. It has close relations to the plant commu-

nities of the alliance Juncion trifidi. The stands occur

on windward flat ridges on marls in the alpine belt of

the Belianske Tatry Mts and Zapadne Tatry –

Cervene vrchy Mts and represent typical arctic-

alpine tundra (Petrık & Sibık 2010).


association met the formal definition except for very

few releves lacking plant species from the Androsace

chamaejasme group.

Festucion versicoloris Krajina 1933

Alpine xero-cryophilous tussocky, cushion-like and

dwarf-shrub vegetation on siliceous-neutral soils on

mylonites or other type of metamorphic bedrock.

Contact vegetation: Androsacion alpinae, Juncion trifi-

di. Distributional area: Mylonite zones of the Tatra

Mts.

6. Silenetum acaulis Krajina 1933



umn 6.

Brief characteristics: Cushion-forming plant commu-

nity dominated by Silene acaulis and Saxifraga species

with a relation to scree phytocoenoses from the

alliance Androsacion alpinae. The stands of this

community occur on extreme south-facing mylonite

screes in the subnivale belt of the Vysoke and

Zapadne Tatry Mts or on north-facing mylonite

screes in the alpine belt.


group of releves from stable soil substrates with

occurrence of species such as Agrostis alpina, Agrostis

rupestris or Carex *silicicola, which were previously

assigned to the subass. agrostietum alpinae (Krajina

1933) Dubravcova et Sibık 2006. These releves have

relatively close relations to the association Agrosti

alpinae-Festucetum versicoloris (cf. Dubravcova and

Sibık 2006, Sibık et al. 2007), but they do not meet

the definition of this association either.

7. Agrosti alpinae-Festucetum versicoloris

Pawłowski in Pawłowski et al. 1928 nom.

invers. propos.



umn 7.

Brief characteristics: Tussocks forming open plant

community dominated by Festuca *versicolor of very

steep rocky slopes and ridges on mylonite screes in

the alpine belt of the Vysoke and less often Zapadne

Tatry Mts.

Comparison: The formal definition corresponds well

with the traditional classification.

8. Salicetum kitaibelianae Krajina 1933



umn 8.

Brief characteristics: Relatively heterogeneous scree

plant community dominated by Salix kitaibeliana (S.

retusa agg.) of the alpine belt of the Vysoke and

Zapadne Tatry Mts. The stands occur on mylonite

and granite screes below the steep rocky slopes.

Comparison: The formal definition corresponds well

with the traditional classification.

Discussion

Comparison of two classifications

Ko�cı et al. (2003) and Role�cek (2007) tested the

created definitions in smaller datasets, which in-

cluded only the releves assigned by the original

authors to the studied vegetation unit (class).


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However, there are many overlapping biotopes where

phytocoenoses from different classes are in contact.

It may be that the stands on one side of a gradient

being classified, e.g. to the alliance Oxytropido-

Elynion (CK), are on the other side of the gradient

similar to the plant communities of the alliance

Caricion firmae (Elyno-Seslerietea – ES). Sometimes

the releve assigned to an alliance as a marginal releve

or as a successional stage of the community of the

first alliance meets the definitional criteria of the

plant community from the second alliance (and

class) and vice versa. Hence, we did not test the

created definitions in a smaller dataset of the class

CK but in the large, unstratified dataset comprised of

releves from all vegetation units. The calculation of

FPFI coefficients for the releves assigned to more

than one vegetation unit, and for unassigned releves

previously (i.e. by prior authors) classified within the

class CK, was on the other hand performed in the

smaller dataset.

Several authors have tried to test whether they can

successfully use the Cocktail method to either create

formal definitions to classify or revise studied

vegetation units (Lososova 2004; Hajkova et al.

2006; Havlova 2006) or apply the created formal

definitions in an attempt to reproduce the traditional

classifications (Ko�cı et al. 2003; Dıte et al. 2007;

Role�cek 2007). The null hypothesis of our analyses

was that the results of applying the formal definitions

created on the basis of a large, geographically

stratified dataset including the occurrence of all

vegetation types of Slovakia would not differ from the

results of the traditional classification. As a case

study, the specific species-rich high-altitude vegeta-

tion with the occurrence of many arctic-alpine and

endemic species (Figure 2), was chosen. The

distinctiveness (and the presence) of the class CK

in the Western Carpathians was rejected by some

authors from other regions, especially from Oro-

Mediterranean (cf. Oriolo 2001; Peyre & Font

2011). The fact is that for the class CK, it is very

difficult to distinguish the characteristic species s. str.

They are usually circumpolar distributed arctic-

alpine species which naturally occur also in contact

phytocoenoses. The difference is that their distribu-

tional optimum covers extreme habitats, which

served as refugia for these species during the

postglacial periods. Therefore, we evaluate the

characteristic taxa in broader context, not only from

regional point of view (which often means marginal),

but taking into account the overall distributional

range of the plant communities of the class CK,

where these species have their natural optimum (cf.

Ohba 1974). On the other hand, like some other

studies (Coldea 1997; Sibık et al. 2007; Sibıkova

et al. 2010; Lancioni et al. 2011), this study supports

its delimitation.

It was possible to satisfactorily reproduce the

traditional classification of the class CK by means

of formal classification based on the formal defini-

tions created by the Cocktail method together with

the FPFI affiliation of the unclassified releves. We

were able to formulate the unequivocal assignment

criteria for all eight associations of both alliances of

the class CK. The formal delimitations agree very

well with the traditional ones. The positive criteria

species groups used in the formal definition contain

many species previously used as diagnostic (char-

acteristic, differential or constant) for individual

associations (Table I; see also Supplementary mate-

rial). Of the species used in the positive criteria

species groups, 32% were arctic-alpine taxa and 8%

were endemic, demonstrating the relic character of

the stands.

The statistical comparison of both synoptic tables

of associations – the first created from the dataset of

464 releves with the original assignment based on the

traditional expert classification using the cluster

analyses (Petrık et al. 2006, Kliment et al. 2010)

and the second (see Supplementary material) based

on formal classification – shows that we can accept

the null hypotheses.

Formalised classification – how reliable is the expert

system?

Several projects have recently been undertaken in

Slovakia to study meadows and pastures. One of

these studies yielded an expert system for grassland

vegetation (Janisova et al. 2007). Hence, we aimed to

continue creating new species groups and definitions

based on the existing expert system and to develop

the existing database. But the dataset has been

improved, up to the present, mainly with the

addition of new high-altitude releves. Therefore,

even after the geographical stratification, the new

dataset was considerably larger (21,142 releves vs.

the former 16,640). As we realised, the creation of

the species groups is strongly database dependent,

and after improving the dataset and adding a large

number of new releves, it is not possible to apply the

results from previous studies or from an expert

system based on a different dataset. Whereas the

results of the cluster or divisive classifications are

more dependent on the analysed dataset and there

are possible changes in the results after adding even a

small number of releves, the differences in the

process of creating the species groups used to define

the associations by the Cocktail method are evident

only after substantial modification of the dataset. In

our case, an increase in releves of 20% in the

stratified dataset, mainly as a result of adding the

high-altitude vegetation, affected the structures of

previously defined species groups. It is clear that due


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to the increase in the number of releves of various

vegetation types, which were insufficiently included

in the former dataset; the representativeness of the

new dataset and hence the results obtained might be

considered as more objective. Based on these results,

we propose the occasional testing of the defined

species groups and formal definitions in improved,

more representative datasets, assuming that, e.g.

more data on the scarce vegetation types will be

included or the amount of data from sparsely

covered areas will increase. No classification of the

vegetation should be considered as definitive if all of

the vegetation types and the whole studied region are

not covered sufficiently and representatively.

Role�cek (2007) also pointed out some limitations

caused by the rules of using the species groups – in

particular, it might be difficult to define a vegetation

unit because suitable diagnostic species are already

included in other species groups used for different

vegetation types. This issue makes it more difficult to

continue creating the expert system (even using the

same dataset) after one part of the system for one

vegetation group has been finished. We suggest that

the strict ‘‘rule of priority’’ of previously used species

in particular species groups should be replaced by a

‘‘rule of consensus’’ and that the inclusion of

particular species into a species group should be

considered by experts on related (from the syneco-

logical or syndynamical point of view) vegetation

types.

When creating the species groups, several other

problems were encountered. They can be divided

into four main cases. In the first case, species that

belonged to previously defined species groups for

grassland vegetation (Janisova et al. 2007) were not

coherent in our dataset, i.e. particular species groups

were not observed and new groups were needed. In

the second case, after adding new species, the

broader species group was divided into two new

species groups, which had higher positive fidelity

values in the dataset than the former group did. In

the third case, almost identical species groups arose

with a difference in one species; the new group again

had higher positive fidelity values than the previous

one. The last case covers such species, which we did

not involve in any of the species groups due to its

weak diagnostic affinity, but these species were

previously used to form a species group – e.g. Sesleria

albicans. Janisova et al. (2007) used this species to

create a xero-thermophilous species group (Sesleria

albicans group: S. albicans, Genista pilosa, Leontodon

incanus) to define the xero-thermophilous grasslands.

S. albicans, however, has a wide vertical distributional

area and is typical also of high-altitude calcareous

grasslands. In subalpine belt, it often occurs with L.

incanus as a diagnostic species of several high-altitude

vegetation units (Kliment et al. 2007).

The question is to what extent we can rely on the

expert system (or use this method as a classification

tool) in cases when we expect that a large number of

releves will be added to the database in the near

future (i.e. with a horizon of 5 years), making the

dataset significantly larger and different. After every

significant extension of the database (especially from

few vegetation types), there is a significant chance

that it will not be possible to use the previously

generated species groups created from a smaller

dataset, and hence, the Cocktail definitions will no

longer be applicable. The authors are aware that this

new method and the formal definitions of vegetation

types do not have to be considered as final because

the ecological and geographical representativeness

will probably improve over time (Role�cek 2007), but

this method is, together with other classification

methods, a highly useful and complementary tool to

obtain objective results.

According to Mucina, even objective methods

need not yield objective results (Mucina, in verb., 3

May 2008, 17th International Workshop ‘‘European

Vegetation Survey’’, Brno). It would be interesting to

compare the results of several scientists, working

independently, with comparable knowledge back-

grounds in terms of how different the results would

be after processing the same dataset. The team of

experts that is behind the formation of species groups

and the fact that they are the experts on every

vegetation type are important to prevent the possi-

bility of ‘‘stealing’’ a species for a particular species

group or of incorrect inclusion of any species in a

suboptimal species group. However, there might not

have been full agreement even when using the

methods of numerical classification. Experts on

individual vegetation types could obtain similar (or

identical) results by means of numerical classification

(e.g. cluster analysis) when performing subsequent

partial and subjectively chosen analyses; hence, they

could create a specific ‘‘expert system’’, but this

system would be more difficult to replicate or define

by another person without specific (expert) knowl-

edge.

The expert system is also dependent on the quality

of the entries in the dataset. Sibıkova et al. (2009)

indicated that the SVD should be improved in terms

of the completeness and quality of its data. The

missing entries in particular fields, such as the

coordinates, are most significant. Both missing

coordinates and inaccurately or incompletely deter-

mined post-hoc coordinates have strong impacts on

the state (quality) of a geographically stratified

dataset and on its subsequent processing. The

releves from the regions where many vegetation

types co-occur on relatively small areas with rugged

relief that causes substantial changes in the ecological

conditions of the habitats are especially sensitive to


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the accuracy of post-hoc determination of the

coordinates. The high-altitude mountain regions

are a good example of such habitats. If the

coordinates were determined inaccurately (e.g. as a

hypothetical centre of a valley in a mountain range),

they are useful only for a rough draft of the

distribution of individual vegetation units on, e.g.

the national level, but they are not suitable for

objective geographical stratification of the dataset.

The stratification of the releves from one vegetation

unit and one area (e.g. mountain valley) with such

inaccurately determined post-hoc coordinates leads

to the loss of information about variability of that

vegetation unit; hence, the created species groups

were not generally valid and were strongly dependent

on the quality of the database. Currently, Senko and

Sibık (in prep.) are addressing the precise post-hoc

determination of old phytosociological releves.

Another issue concerns the objective way to create

the definitions. By means of logical operators

together with the dominance threshold criteria, it is

possible to create a more or less complicated formal

definition for almost every vegetation unit or

assembly of releves. The questions are to what extent

the definitions would be applicable in praxis and to

what extent they would be database specific. Role�cek

(2007) believes that there is more to lose than to gain

from complicated definitions because they are

difficult to comprehend and usually strongly data-

base specific. But when the aim is to cover not only

the narrowly comprehended (basic) core of the

vegetation unit but also its whole content, i.e. to

cover the whole ecological scale of the unit including

the subunits and not only the releves of nominative

subassociation, it is often difficult to create a simple

definition, such as A AND B or A NOT B. This is

the case of vegetation units that cover more diverse

habitats and ecological conditions, including the

mountain ecosystems. As Dıte et al. (2007) indi-

cated, it is possible to simplify the formal definitions

by omitting the negative members of the definition.

This is also applicable to cases when the definitions

are created or tested in the unstratified dataset

containing only the releves from the specific well

determined vegetation units or in cases when only

the releves from one class (that does not include

transitional vegetation units) are analysed.

Role�cek (2007) raised two important issues – if the

large dataset of a large spatial and temporal scale is

really representative and if it is suitable for specific

purposes (classification) in a particular time and

area. In our opinion, the application of any classifica-

tion method, even the most objective one, no matter

how large the dataset may be, reflects to a large

extent the current state (i.e. the quality) of the

dataset (database) and the professionalism (i.e. the

level of expertise) of the botanist processing the data.

As Chytry (2000) pointed out in his crucial article

about formalised approaches to classification, the

imperfectly formalised approaches (e.g. cluster ana-

lysis) are essential in fine-scale classifications at the

regional and landscape levels, whereas the formalised

approach is superior for large-scale vegetation

surveys. The two methods are hence complementary

and, in general, it is not viable to put one above the

other. On the contrary, it is important to consider the

presumptive benefits of each of the approaches. The

feasibility of the formal classification is strongly

dependent on the quality and representativeness of

the database created for the area where the formal

definitions are to be valid. Hence, these methods are

widely used only in a few countries, but their rapid

spread is expected in the near future, along with the

development of high-quality national and supra-

national databases.

Acknowledgements

We are indebted to American Journal Experts

(www.journalexperts.com) for English proofreading.

This work was supported by the grant agency VEGA,

grant no. 2/0121/09 and 2/0090/12.

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Supplementary material. Shortened synoptic table of the high-altitude arctic-alpine vegetation of the

class Carici rupestris-Kobresietea Ohba 1974 in the Western Carpathians.

Diagnostic taxa (F4 0.30) with the percentage values of their frequency are sorted according to their fidelity to

the vegetation type (phi koeficient6 100, upper index). The species with probability of random distribution in

the vegetation type higher than 0.001 yelded by Fisher’s exact test were excluded from the list of diagnostic

species. Explanations: dg¼Taxa characterized by Sibık et al. (2007) as diagnostic (differential, characteristic or

transgressive) for any syntaxa of the class Carici rupestris-Kobresietea; aa¼ arctic-alpine taxon according to

Sibıkova et al. (2010). Species printed in bold are characteristic species s.str. of the class Carici rupestris-

Kobresietea according to Kliment & Valachovi�c (2007).

Group No. 1 2 3 4 5 6 7 8

No. of releves 10 11 31 24 19 86 100 141

Oxytropido carpaticae-Elynetum myosuroides

aa Elyna myosuroides dg 10088.7 .— .— 8— 11— .— 4— .—

Physconia muscigena (E0) dg 8073.9 .— .— 2512.9 .— 1— 1— .—

Primula auricula dg 5065.0 .— .— 4— .— .— .— .—

Fulgensia bracteata (E0) dg 4060.7 .— .— .— .— .— .— .—

Leontopodium alpinum 4060.7 .— .— .— .— .— .— .—

Trisetum alpestre 7056.5 18— .— 3318.4 .— 2— .— 1—

Ochrolechia upsaliensis (E0) 4056.2 .— .— .— 5— .— .— .—

Psora decipiens (E0) 5054.7 .— .— 2115.9 .— .— .— .—

Squamarina gypsacea (E0) 4052.2 .— .— 8— .— 2— .— .—

Hypnum vaucheri (E0) 4049.7 .— .— 8— .— 2— 4— .—

Caloplaca ammiospila (E0) 4049.0 .— .— 12— .— 2— 1— .—

Mycobilimbia lobulata (E0) dg 5048.2 9— .— 2517.6 .— 1— .— .—

Cladonia pyxidata agg. (E0) dg 9047.6 27— 16— 12— 26— 38— 22— 19—

Distichium inclinatum (E0) 3046.1 .— 6— .— .— .— .— .—

Cetraria muricata (E0) 3044.6 .— 3— 4— .— .— 1— .—

Anaptychia bryorum (E0) 2042.4 .— .— .— .— .— .— .—

Campanula cochleariifolia 3040.1 .— .— 12— .— 2— .— .—

Lecanora epibryon (E0) 3039.4 .— .— 8— 5— 2— .— .—

Phaeorrhiza nimbosa (E0) 3036.6 .— .— 2122.4 .— .— .— .—

Oxytropis carpatica dg 5035.7 9— 19— 4227.0 5— .— .— .—

Myurella julacea (E0) 6034.2 5529.2 10— 5025.1 .— 3— 1— .—

Drabo siliquosae-Festucetum versicoloris

Draba siliquosa dg 20— 10088.2 .— 4— .— .— .— .—

Plagiothecium laetum (E0) dg .— 7383.2 .— .— .— .— .— 1—

Helianthemum grandiflorum dg .— 9178.3 .— 21— 11— .— 3— .—

Linum extraaxillare dg .— 7377.3 .— .— 5— .— 5— .—

Plagiobryum demissum (E0) dg 10— 8276.3 10— 4— .— .— .— 1—

Parnassia palustris dg .— 10063.5 16— 4213.3 37— 3— 7— 4—

Astragalus australis dg 30— 8263.3 10— 21— .— .— .— .—

(continued)


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Appendix 1. (Continued)

Group No. 1 2 3 4 5 6 7 8

No. of releves 10 11 31 24 19 86 100 141

Tephroseris capitata dg 10— 7363.1 3— 12— 16— .— .— .—

Campylopus schimperi (E0) dg .— 5561.1 .— 8— 5— 1— 1— .—

Poa nemoralis dg 10— 6459.7 .— 17— 5— .— .— 1—

Anthoxanthum alpinum dg .— 9159.0 3— 17— 16— 3— 19— 4417.5

aa Astragalus norvegicus dg .— 4552.0 6— 12— .— .— .— .—

Erigeron hungaricus dg 10— 6448.8 .— 3317.7 21— 1— .— .—

Alchemilla spec. div. .— 7347.6 10— 17— 26— 13— 24— 8—

Sesleria tatrae dg .— 9145.4 6524.3 5416.1 5819.0 .— 4— 1—

aa Saussurea alpina dg .— 7343.6 29— 4619.7 3711.7 1— 3— 1—

Plagiopus oederiana (E0) dg .— 3643.3 6— 12— .— .— 1— .—

Desmatodon latifolius (E0) .— 2741.7 .— 4— .— 2— 2— .—

Saxifraga adscendens dg .— 1840.3 .— .— .— .— .— .—

Carduus glaucinus dg .— 1840.3 .— .— .— .— .— .—

Primula halleri .— 1840.3 .— .— .— .— .— .—

Trichostomum crispulum (E0) .— 2739.2 .— 8— .— 3— .— .—

Carex sempervirens s.l. dg 10— 10038.6 48— 38— 58— 28— 7418.9 36—

Scabiosa lucida .— 3638.1 3— 17— 5— .— 5— 1—

Phyteuma orbiculare dg 20— 9137.7 52— 5812.7 58— 10— 30— 15—

Myosotis alpestris dg 20— 10037.3 9030.0 6712.1 8929.3 21— 9— 9—

aa Rhodiola rosea 70— 10033.1 6— 79— 53— 53— 37— 55—

Encalypta alpina (E0) 5028.7 5533.0 6— 3312.9 .— 12— 2— .—

aa Astragalus frigidus dg 10— 4531.2 19— 12— 3722.3 .— .— .—

Pyrolo carpaticae-Salicetum reticulatae

Saxifraga wahlenbergii dg 10— .— 9060.6 4216.9 32— 5— 5— .—

aa Dryas octopetala dg 20— .— 9052.8 25— 5825.4 8— 21— .—

Ranunculus alpestris dg 10— .— 8452.1 42— 21— 19— 20— 1—

Selaginella selaginoides dg 10— .— 7450.9 8— 37— 7— 17— 8—

Swertia *alpestris dg .— 45— 8749.0 21— 21— 9— 387.9 6—

Dicranum spadiceum (E0) dg .— .— 4248.3 .— 16— 2— 2— .—

Blepharostoma trichophyllum (E0) dg .— .— 4847.8 4— .— 13— 6— 10—

Hylocomium splendens (E0) .— .— 9445.3 12— 74— 34— 39— 35—

Philonotis tomentella (E0) .— .— 2944.2 .— 5— 2— .— .—

Isopterygiopsis pulchella (E0) dg .— .— 2643.6 .— .— 3— 1— .—

Polytrichum formosum (E0) dg .— .— 3943.5 .— 21— .— .— 3—

Meesia uliginosa (E0) dg .— .— 3242.7 4— .— 8— 2— .—

Pritzelago alpina .— .— 2940.6 12— .— .— .— .—

Soldanella carpatica .— .— 9740.3 12— 79— 45— 63— 55—

Timmia austriaca (E0) .— 9— 4540.0 12— 5— 17— .— 2—

Orthothecium rufescens (E0) .— .— 2639.5 8— .— .— 1— .—

Mnium thomsonii (E0) dg 20— 55— 7438.8 4614.9 5— 12— 9— 4—

Thuidium philibertii (E0) .— .— 2638.7 4— 5— .— 1— .—

Ranunculus thora dg .— .— 2338.5 .— 5— .— 1— .—

Scapania cuspiduligera (E0) .— .— 2336.7 8— .— .— .— .—

aa Pinguicula alpina dg .— .— 3235.6 4— 11— 6— 7— .—

Biscutella laevigata dg .— .— 1935.6 .— 5— .— .— .—

Distichium capillaceum (E0) .— 18— 5533.3 42— .— 3111.0 10— 2—

Carex firma dg 30— 9— 5833.0 4218.0 26— 3— 7— .—

aa Carex fuliginosa dg 50— 45— 9732.7 7919.3 7415.2 34— 45— 6—

Sanionia uncinata (E0) dg .— 9— 7432.5 29— 26— 48— 35— 48—

Campylium chrysophyllum (E0) .— .— 1631.5 4— .— 1— .— .—

Festucetum versicoloris

Didymodon asperifolius (E0) dg .— .— .— 2951.5 .— .— .— .—

Draba aizoides dg 30— .— 10— 5445.4 11— 1— 1— .—

Ditrichium flexicaule (E0) dg 40— 27— 6528.0 8343.5 11— 10— 7— .—

Vulpicida tubulosus (E0) dg 50— 9— 4213.5 7542.0 21— 10— 2— .—

Delphinium oxysepalum dg .— 9— 6— 4238.4 21— 1— 4— 1—

Hypnum bambergeri (E0) dg 10— .— 13— 3337.9 .— .— 2— .—

Entodon concinnus (E0) 30— 9— 4828.1 5837.6 5— 1— 1— .—

Ctenidium procerrimum (E0) 30— .— 3— 3837.4 .— .— 2— .—

Caloplaca stillicidiorum (Vahl) Lynge (E0) .— .— .— 1737.0 .— 1— .— .—

Artemisia eriantha 40— .— 3— 4633.5 .— 14— 13— 1—

(continued)


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Group No. 1 2 3 4 5 6 7 8

No. of releves 10 11 31 24 19 86 100 141

aa Saxifraga oppositifolia dg 30— .— 13— 5832.3 .— 5226.8 21— 6—

Crepis jacquinii dg .— 18— 10— 2931.4 .— 2— .— .—

Poa alpina dg 50— 45— 7723.4 8831.0 6816.6 27— 14— 3—

Festuco versicoloris-Oreochloetum distichae

Senecio *carpathicus dg .— .— .— .— 4254.6 1— 3— 6—

Trollius altissimus .— .— 3— .— 3250.4 .— .— .—

Dianthus glacialis dg .— .— 26— 21— 6849.7 17— 9— 2—

aa Saxifraga hieraciifolia .— .— 4521.4 8— 7447.5 339.8 9— 6—

Ptilidium ciliare (E0) .— .— 4225.8 8— 6347.4 1— 8— 10—

Bistorta major dg .— 55— 19— 4— 7945.4 5— 25— 23—

Dicranum fuscescens (E0) .— .— 19— .— 4244.2 5— 4— 1—

aa Carex atrata agg. dg 10— 45— 5814.8 29— 9543.2 27— 34— 13—

aa Potentilla crantzii dg .— 45— 3— 12— 6341.6 14— 15— 3—

Luzula sudetica dg .— 45— 5225.4 17— 6840.4 .— 3— 1—

Hedysarum hedysaroides dg 30— 6418.0 7426.1 5813.9 8937.9 2— 1— 4—

Lophozia obtusa (E0) .— .— .— .— 1637.5 .— .— .—

Rhodax alpestris dg 50— 18— 6120.9 7128.5 7934.9 .— .— .—

Salix hastata dg .— .— .— .— 1634.8 .— 2— .—

Dicranum bonjeanii (E0) .— .— 3— .— 1633.3 .— .— .—

Botrychium lunaria .— .— .— 4— 1632.2 .— .— .—

Silenetum acaulis

Gentiana frigida dg .— .— 16— 12— .— 7151.3 36— 11—

Novosieversia reptans dg .— .— .— .— .— 3650.3 7— 1—

Saxifraga bryoides dg 10— .— 6— 8— 5— 5348.9 8— 3—

Cardaminopsis neglecta dg .— .— .— .— .— 4748.5 25— 3—

Leucanthemopsis alpina dg .— .— .— .— .— 3742.6 10— 13—

aa Oxyria digyna dg .— .— 3— 4— .— 3439.1 13— 3—

Pogonatum urnigerum (E0) dg .— .— 6— 12— 11— 4936.2 21— 19—

Saxifraga androsacea dg .— .— 32— .— 5— 4034.7 8— 2—

Solorina crocea (E0) .— .— .— .— .— 2334.4 6— 6—

Cetraria nivalis (E0) dg 10— .— 3— 21— 32— 5533.7 23— 12—

aa Erigeron uniflorus dg .— .— .— .— .— 3333.3 21— 13—

Poa laxa dg 10— .— .— .— .— 3031.1 20— 4—

aa Salix herbacea dg .— .— .— .— .— 2630.5 18— 6—

Agrosti alpinae-Festucetum versicoloris

Callianthemum coriandrifolium dg .— .— .— .— .— 7— 2436.1 4—

Anemone narcissiflora dg .— 36— 3— 4— 5— 6— 4330.5 18—

Salicetum kitaibelianae

Salix retusa agg. (incl. S. kitaibelliana) dg 10— .— 35— 8— 21— 31— 68— 10052.3

Vaccinium myrtillus dg .— .— 3— .— 5— .— 14— 3944.4

Pulsatilla scherfelii dg .— 9— .— .— 32— 9— 50— 6843.7

Gentiana punctata dg .— .— .— .— .— .— 4— 2340.7

Avenella flexuosa dg .— 9— .— .— .— .— 6— 2838.2

Doronicum stiriacum .— 9— 13— 12— 32— 59— 35— 7437.4

Valeriana tripteris dg .— .— .— .— .— .— .— 1637.3

Solidago *minuta dg .— 18— 3— .— .— .— 5— 3337.2

Oreogeum montanum dg .— .— .— .— .— 5— 2— 2135.8

Cladonia arbuscula s.l. (E0) .— .— .— .— 11— 16— 17— 3935.6

Ligusticum mutellina .— .— .— .— 5— 6— 28— 3534.0

Senecio *carniolicus .— .— .— .— .— 3— 1— 1733.5

Homogyne alpina .— .— 6— 4— .— 6— 12— 3033.5

Ranunculus pseudomontanus .— .— .— .— 5— 9— 23— 3332.5

Diagnostic taxa for more syntaxa

Dactylina madreporiformis (E0) dg 8055.1 9— 10— 6238.8 5— .— .— .—

Arenaria tenella dg 7046.8 18— 10— 5431.9 5— 5— .— .—

Oxytropis halleri dg 7033.9 27— 26— 7941.5 32— .— .— .—

aa Aster alpinus dg 5033.4 7356.3 .— 12— .— .— .— .—

Agrostis alpina dg 6032.0 8251.3 3— 21— .— 5— 20— 1—

Ranunculus breyninus dg 10031.0 10031.0 52— 9627.7 8922.8 12— 26— 4—

Bupleurum ranunculoides dg 5030.6 8261.5 .— 17— .— .— .— .—

Thymus pulcherrimus dg 10— 5538.6 3— 5438.2 11— .— .— .—

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Group No. 1 2 3 4 5 6 7 8

No. of releves 10 11 31 24 19 86 100 141

Rhytidiadelphus triquetrus (E0) dg .— .— 9460.7 .— 6334.0 2— 15— 22—

Pyrola carpatica dg .— .— 7156.8 .— 5337.8 .— 2— 2—

aa Salix reticulata dg .— .— 10053.6 42— 9549.3 9— 16— 4—

Saxifraga aizoides dg 10— 18— 7445.8 6235.3 5— 3— 10— 1—

Minuartia pauciflora (Kit. ex Kanitz) Dvor. dg 30— 45— 10038.7 9232.4 63— 34— 20— 6—

Cardaminopsis halleri dg .— 27— 4831.2 8— 5335.5 .— 1— .—

aa Androsace chamaejasme dg 10031.4 9124.4 7714.0 10031.4 10031.4 2— 3— .—

Other taxa with higher fidelity or frequency

aa Cerastium eriophorum dg 9017.6 10025.7 9420.5 9622.3 9521.4 34— 35— 4—

Minuartia sedoides dg 80— 45— 9722.0 9621.2 10024.6 9117.0 37— 16—

Festuca versicolor dg 100— 100— 9716.7 10019.7 9514.8 29— 9918.7 10—

Galium anisophyllon dg 80— 10028.5 8718.4 9222.0 10028.5 9— 29— 13—

aa Pedicularis oederi dg 40— 100— 10023.7 9216.7 84— 60— 752.7 23—

Campanula tatrae 80— 100— 65— 9620.2 74— 41— 731.0 47—

aa Silene acaulis dg 90— 55— 10017.2 96— 95— 10017.2 896.1 39—

Oreochloa disticha dg 20— 45— 23— 25— 79— 77— 78— 72—

Primula minima 70— 18— 58— 58— 68— 8619.9 7914.5 44—

Viola biflora 20— 36— 10— 4— 26— 12— 3513.8 19—

aa Bistorta vivipara dg 100— 100— 100— 100— 95— 65— 78— 82—

Festuca supina dg 50— 45— 52— 58— 79— 9220.3 76— 80—

Saxifraga paniculata 80— 91— 8411.9 10025.1 63— 50— 51— 36—

Tortella tortuosa 80— 9125.0 719.7 9225.6 21— 53— 50— 9—

aa Bartsia alpina 20— 64— 74— 21— 21— 34— 56— 6717.3

aa Juncus trifidus .— 82— 23— 38— 84— 35— 7216.2 7215.9

aa Astragalus alpinus 10— 27— 3— 8— 11— .— .— .—

Bellidiastrum michelii .— 9— 16— 4— 11— 2— 6— 1—

Cerastium *glandulosum .— 18— 19— 8— 37— 13— 6— 6—

Saxifraga moschata dg 20— 100— 71— 79— 9523.2 8616.3 49— 25—

aa Luzula spicata dg 30— 73— 42— 58— 53— 7117.6 40— 15—

Saxifraga carpathica .— .— .— 4— .— 1019.6 5— .—

aa Gentiana nivalis dg 30— 3626.3 6— 2513.5 5— .— .— 1—

Coeloglossum viride dg .— .— 3229.6 .— 16— .— 11— 16—

Draba dubia 20— .— .— 8— .— 1— 3— .—

Gentianella lutescens 40— 18— .— 12— .— 6— 8— 5—

Geranium sylvaticum .— 18— .— .— .— .— 1— 5—

Aconitum firmum .— 18— 6— 4— 16— 1— 2— 6—

aa Pedicularis verticillata .— 73— 45— 29— 21— 57— 46— 51—

Hypnum cupressiforme 30— .— 10— 17— 11— 8— 12— 3—

Androsace lactea 20— .— .— 12— .— 1— .— .—

Euphrasia salisburgensis dg 5025.5 5529.7 6— 5429.3 5— 2— 2— 1—

Achillea *sudetica .— 18— 3— .— 5— .— 4— 1—

aa Carex atrofusca dg .— .— 1029.3 .— .— .— .— .—

Huperzia selago dg .— .— 23— 12— .— 53— 48— 46—

Thymus alpestris 50— 64— 13— 42— 21— 8— 29— 16—

Saussurea pygmaea dg 10— 9— .— 12— .— 17— 2821.4 8—

Campanula alpina 10— .— 48— 38— 84— 53— 8226.7 58—

Saxifraga retusa dg .— .— 3— .— .— 1923.3 1822.3 1—

Leontodon pseudotaraxaci dg 10— 27— 26— 29— 16— 6— 268.0 4—

Luzula luzuloides .— 27— .— .— 5— .— 4— 9—

Plantago atrata .— .— .— .— 5— .— .— .—

Sedum alpestre .— .— .— .— .— 13— 4— 12—

aa Chamorchis alpina 10— 9— 2320.0 8— 11— 2— 2— .—

Euphrasia tatrae .— 27— 3— .— 5— 2— 3— 3129.2

Hieracium alpinum .— .— 3— .— 32— 8— 27— 4029.2

Polytrichum alpinum .— .— .— .— .— 37— 39— 4128.3

Pyrola minor .— .— .— .— .— .— .— 927.4

Vaccinium gaultherioides .— .— 6— 4— .— 3— 12— 2326.2

Agrostis rupestris .— 9— .— .— 16— 5— 27— 3124.5

Salix silesiaca .— .— .— .— .— .— .— 623.7

Festuca picturata .— 45— .— 4— 5— .— 4— 2921.8

Luzula alpinopilosa .— 9— 23— 8— 68— 55— 36— 5821.0

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Group No. 1 2 3 4 5 6 7 8

No. of releves 10 11 31 24 19 86 100 141

Veratrum *lobelianum .— .— .— .— .— .— 1— 620.1

Avenula versicolor dg 10— 9— 10— 17— 32— 6— 40— 4219.9

Vaccinium vitis-idaea dg .— .— 42— 4— 32— 12— 4822.8 4519.8

Potentilla aurea .— 9— 3— .— 32— .— 16— 2416.8

aa Lloydia serotina dg 90— 91— 878.9 9616.8 89— 78— 71— 16—

aa Ranunculus glacialis .— .— .— .— .— 1529.7 5— 1—

aa Ligusticum mutellinoides dg 70— 27— 8418.0 71— 9526.4 7410.7 48— 16—

aa Draba fladnizensis 10— 9— .— 2127.5 .— .— .— .—

Cardaminopsis arenosa agg. .— 36— 2311.6 3323.9 5— 1— 1— .—

Schistidium apocarpum agg. 40— .— 10— 3829.8 .— 3— 2— 3—

Cortusa matthioli .— 18— 3— .— 5— .— .— 1—

aa Antennaria carpatica dg 50— 9— 32— 46— 21— 15— 23— 21—

aa Carex capillaris dg 5024.0 5528.1 13— 4216.6 26— .— .— .—

aa Comastoma tenellum dg 6029.8 5525.1 19— 5424.7 16— .— 1— .—

aa Tofieldia pusilla dg .— .— 1029.3 .— .— .— .— .—

aa Carex rupestris dg .— .— 3— .— .— 2— 1529.7 .—

Other arctic-alpine taxa or rare taxa of West Carpathians’ flora

aa Kobresia simpliciuscula 20— .— .— 4— 5— 1— .— .—

Bellardiochloa variegata .— 9— .— .— .— .— .— .—

aa Arctous alpina dg .— .— 6— .— .— .— .— .—

Draba tomentosa .— .— .— 4— .— .— 1— .—

Pilosella alpicola .— .— .— .— .— .— 3— 4—

aa Arabis alpina .— .— .— .— .— .— 3— 1—

aa Dichodon cerastoides .— .— .— .— .— .— 1— 1—

Pulsatilla vernalis dg .— .— .— .— .— .— 2— .—

aa Veronica alpina .— .— .— .— .— 8— 1— 2—

Armeria alpina .— .— .— .— .— 1— 1— .—

Cerastium uniflorum .— .— .— .— .— 1— 1— 1—

aa Omalotheca supina .— .— .— .— .— 2— .— .—

Woodsia alpina .— .— .— .— .— 1— .— .—

Bryophytes and Lichens (E0)

Cetraria islandica 10— 27— 9025.4 50— 95— 65— 54— 65—

Thamnolia vermicularis 90— 9— 52— 8827.8 58— 6611.7 31— 13—

Rhytidium rugosum 30— 45— 52— 46— 58— 22— 36— 10—

Campylium stellatum 20— .— 5529.6 33— 5— 4419.9 15— 6—

Alectoria ochroleuca 30— .— 10— 8— 11— 34— 23— 26—

Ctenidium molluscum 20— 9— 19— 17— .— .— 7— .—

Plagiochila porelloides 20— 4525.7 4525.4 29— 5— .— 6— .—

Polytrichum alpinum 20— 18— 3514.3 3816.2 4220.5 1— 8— .—

Cladonia rangiferina .— .— 3— .— 53— 14— 21— 3822.8

Lecidoma demissum 10— 9— .— 2121.7 11— 1— 1— .—

Cratoneuron commutatum .— .— .— .— .— 622.6 .— .—

Pohlia cruda .— 36— 5229.4 .— .— 4220.2 20— 13—

Blindia acuta .— .— .— .— .— 1226.4 4— .—

Dicranum majus .— .— .— .— .— 724.8 .— .—

Alectoria nigricans .— .— .— .— .— 824.9 1— .—

Polytrichum piliferum 10— .— .— .— .— 3129.2 14— 18—

Hypnum hamulosum .— 36— 19— 2920.6 .— 3— 5— .—

Stegonia latifolia 20— .— .— 1721.8 .— .— .— .—

Anthelia juratzkana .— .— .— 4— .— 1323.4 2— 3—

Cetraria cucullata 20— .— 3— 21— 53— 4823.4 15— 17—

Bryum elegans .— .— .— .— .— 622.6 .— .—

Amphidium lapponicum .— .— .— .— .— 724.8 .— .—

Hypogymnia physodes 20— .— .— 4— .— .— 2— .—

Hypnum revolutum 20— .— 6— 8— .— .— .— .—

Gymnomitrion concinnatum .— .— .— .— .— 1226.4 4— .—

Pohlia drummondii .— .— .— .— .— 826.8 .— .—

Solorina bispora 10— 9— 3— 2529.1 .— 1— 2— .—

Geheebia gigantea 10— .— 16— 2122.7 .— 2— 1— .—

Encalypta ciliata 20— 2729.8 .— 8— .— .— 1— .—

Tritomaria quinquedentata .— .— 3528.9 17— 11— 14— 5— 9—

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Group No. 1 2 3 4 5 6 7 8

No. of releves 10 11 31 24 19 86 100 141

Cirriphyllum cirrosum .— .— 23— 17— 5— 1913.2 4— 3—

Ptychodium plicatum .— .— 1929.0 8— 5— .— .— .—

Racomitrium lanuginosum .— .— 19— 4— 5— 28— 3022.2 4—

Paraleucobryum enerve .— .— .— .— .— 14— 5— 6—

Tayloria lingulata .— .— 1029.3 .— .— .— .— .—

Bartramia ithyphylla .— .— 3— .— .— 16— 6— 7—

Cynodontium polycarpon .— 9— .— 21— .— 5— 5— 4—

Cladonia uncialis .— .— .— .— 37— 20— 22— 10—

Cetraria ericetorum .— .— 3— .— 16— 1— 2— 1—

Cladonia coccifera 20— 9— 3— 12— 11— 26— 20— 11—

Encalypta streptocarpa 10— 18— .— .— .— .— .— .—

Encalypta rhaptocarpa 20— 9— .— 12— .— 3— 1— .—

Dicranum scoparium .— .— 29— .— 26— 10— 20— 18—

Hylocomium pyrenaicum .— .— 16— .— 11— .— 4— 3—

Pseudoleskea catenulata 20— 9— 10— 8— .— .— .— .—

Myurella tenerrima 10— 18— 10— .— .— 6— .— .—

Polytrichum strictum .— .— 6— 12— 26— 5— 4— 4—

Pleurozium schreberi .— .— 26— .— 42— 14— 19— 26—

Megaspora verrucosa 20— .— 3— 8— .— 2— .— .—

Pseudevernia furfuracea 20— .— .— 12— .— 2— 4— .—

Racomitrium canescens 10— .— 19— 8— 5— 1— 1— 5—

Cladonia gracilis s.l. .— 18— 6— 17— 42— 27— 26— 31—

Aulacomnium palustre .— .— 3— 4— 16— 1— 2— .—

Rhytidiadelphus squarrosus .— .— 13— .— 11— .— 1— 2—


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Documents

An expert-based classification of high-altitude arctic-alpine vegetation of the class Carici rupestris-Kobresietea Ohba 1974: Achievements and obstacles