ORIGINAL PAPER

The Balkan wet grassland vegetation: a prerequisite tobetter understanding of European habitat diversity

Michal Hajek Æ Petra Hajkova ÆDesislava Sopotlieva Æ Iva Apostolova ÆNikolay Velev

Received: 5 February 2007 / Accepted: 20 May 2007

� Springer Science+Business Media B.V. 2007

Abstract The knowledge of broad-scale floristic

variation in wet grasslands, which are endangered

throughout Europe, is still limited and some regions

have remained unexplored so far. In addition, hitherto

published phytosociological studies were concen-

trated at the national level and therefore national

vegetation classifications are not consistent with each

other. In order to overcome these shortcomings of

traditional phytosociology, we gathered original data

from Bulgaria and analysed them together with the

data from Central Europe. We further analysed major

compositional gradients within Bulgarian wet grass-

lands and changes in species richness along them. We

sampled 164 wet grassland vegetation plots through-

out Bulgaria. We further prepared a restricted data set

of wet grasslands from Central-European phytoso-

ciological databases. Both data sets were merged and

classified by modified TWINSPAN. Four distinct

vegetation types were differentiated. Even if they

correspond with traditional alliances, which are

primarily drawn as geographically defined units in

Western and Central Europe (sub-Mediterranean

Trifolion resupinati, sub-continental Deschampsion

cespitosae and Molinion caeruleae and sub-oceanic

Calthion palustris), they all occur in Bulgaria. When

more precise classification was applied, two types of

sub-Mediterranean wet grasslands and one high-

altitude type of Calthion grasslands were detected

solely in Bulgaria. DCA analysis showed that altitude

is a dominant gradient controlling variation in Balkan

wet grasslands. The second DCA axis was interpreted

as the gradient of nutrient availability. Species

richness shows skewed-unimodal trends along both

major gradients, with the highest species richness in

intermittently wet nutrient-limited grasslands. Tukey

post-hoc test of altitudinal differences amongst

vegetation types is significant for all pairs of clusters,

suggesting that altitudinal differentiation is responsi-

ble for co-occurrence of nearly all European types of

wet grasslands in Bulgaria. Our results suggest that

(1) climate is an important factor for the diversity of

wet grasslands; (2) Balkan vegetation of middle

altitudes matches with that of Central Europe,

whereas that of the lowest altitudes corresponds

rather to the sub-Mediterranean region and high

mountains are specific; (3) upward shift of Central-

European vegetation types in southern Europe, so

often described in forest vegetation is also evident for

grassland vegetation and (4) the high diversity of

M. Hajek � P. Hajkova

Institute of Botany, Czech Academy of Sciences, 3b

Porıcı, 60300 Brno, Czech Republic

M. Hajek (&) � P. Hajkova

Institute of Botany and Zoology, Faculty of Science,

Masaryk University, Kotlarska 2, 61137 Brno, Czech

Republic

e-mail: hajek@sci.muni.cz

D. Sopotlieva � I. Apostolova � N. Velev

Institute of Botany, Bulgarian Academy of Sciences,

Acad. Georgi Bonchev St., bl.23, 1113 Sofia, Bulgaria

123

Plant Ecol

DOI 10.1007/s11258-007-9315-8

Balkan vegetation is determined by a diverse relief

enabling confluence of habitats possessing different

climatic conditions.

Keywords Altitude � Climate � Compositional data

analysis � Molinietalia � Wet meadows � Wetlands

Introduction

Wet grasslands are strongly endangered habitats

throughout Europe as they suffer from both the

ongoing changes in agricultural practices and eutro-

phication (Prach 1993; Schrautzer et al. 1996; Jensen

and Schrautzer 1999; van der Hoek and Sykora

2006). Both species richness and the presence of

endangered plant species decreases especially due to

enhanced aboveground biomass and increasing

amount of litter (e.g. Jensen and Meyer 2001;

Peintinger and Bergamini 2006). Many contemporary

studies are therefore attempting to find relationships

between nutrient availability, water regime, biomass

and species richness (Dwire et al. 2004; Grootjans

et al. 2005; Hardtle et al. 2006) or to test the effect of

various factors on seedling recruitments (e.g. Holzel

2005; Petru 2005). Nevertheless, all these studies are

conducted mostly within a single or few habitats and

they reveal only little of the wet grassland diversity

on a broader spatial scale.

Our knowledge of broad-scale variation in wet

grassland vegetation is limited. We know that on a

landscape scale, the major gradients in floristic

variation within wet grasslands are regulated by pH

predominantly, and to a lesser extent by nutrients and

water regime (Blackstock et al. 1998; Hajek and

Hajkova 2004; Havlova 2006), i.e. by the same

factors that determine variation in many other

habitats (e.g. Wohlgemuth et al. 1999; Ejrnaes and

Bruun 2000; Nekola 2004; Hajek et al. 2006;

Virtanen et al. 2006). Concerning other knowledge,

we are limited mostly to phytosociological data. It

could seem that the large boom in phytosociological

studies that took place in Central, Western and SW

Europe during the 20th century provides a sufficient

source of broad-scale knowledge of wet grassland

habitat diversity. Phytosociology was, however, tra-

ditionally based on the local studies on relatively

small areas (Ewald 2003a), which have made the

drawing of broad-scale comparisons complicated.

Since syntheses, more often uncritical than critical,

have mainly remained at the national level (Mucina

et al. 1993), national vegetation classifications are not

consistent with each other. Bruelheide and Chytry

(2000) found almost no correspondence between the

wet-meadow vegetation types derived from the two

national data sets of neighbouring countries, even

when the same method of numerical classification

was applied. All these pitfalls may occur in the

interpretation of broad-scale patterns in wet meadow

diversity solely from hitherto published phytosocio-

logical studies and syntheses.

Rodwell et al. (2002) propose several broad

vegetation types (alliances) of wet meadows occur-

ring at the European scale, but they are mostly

described as geographically defined units. However,

there is no evidence that these alliances are really

vicariant. There is also a general lack of studies

exploring relation between wet meadow diversity and

climate, as opposed to a large set of studies that were

focussed on edaphic factors and productivity. The

first attempt to overcome this shortcoming of tradi-

tional phytosociology was the multi-national synthe-

sis of wet-meadow vegetation made by Botta-Dukat

et al. (2005). This analysis identified continentality to

be the most important control of wet meadow

diversity, and also merged several alliances tradition-

ally recognised in particular countries into one

alliance.

Another gap in phytosociological data that im-

pedes broad-scale syntheses in wet-meadow vegeta-

tion diversity is the lack of data for some European

regions. One of the most apparent gaps concerns

Bulgaria: a country with a high floristic as well as

landscape diversity, and with a high number of

refugial, endemic and range-margin occurrences of

wetland plants (e.g. Hajek et al. 2005; Hajkova and

Hajek 2007). In this article, we aim to compare our

original data set of Bulgarian wet grasslands with an

analogous data set from Central Europe. Three major

questions are asked: (i) whether the species compo-

sition of wet grasslands changes along the marked

geographical gradient from Central- to SE Europe;

(ii) whether major vegetation types are really region-

specific, as suggested by syntaxonomical systems;

(iii) whether edaphic, or rather climatic factors

correlate with the major compositional gradient in

wet meadows in the Balkans.

Plant Ecol

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Material and methods

Definition of wet grasslands

In our study, we defined wet grasslands as recently or

formerly mowed treeless habitats influenced by water

oversupply at least during part of the year, and

therefore characterised by occurrence of wetland

species such as tall sedges, small fen sedges and

alluvial species avoiding permanently dry habitats.

Fen vegetation dominated by bryophytes and Cyper-

aceae, lacking nutrient-demanding grasses and herbs

was not included in this study, regardless whether it is

managed or not (see Hajek et al. 2006). Ruderal,

strongly disturbed and halophytic vegetation were

also disregarded. This characteristic of wet grasslands

corresponds to the syntaxonomic orders Molinietalia

and Trifolio-Hordeetalia from the Molinio-Arrhena-

theretea class (Horvat et al. 1974).

Field sampling in Bulgaria

We tried to cover all known localities of wet

grassland in Bulgaria. The large wet grasslands

complexes have been known from the National

Grassland Inventory of Bulgaria (Meshinev et al.

2005), the small localities of wet grasslands have

been described during extensive research on wetland

diversity (Hajkova et al. 2006) or with the help of

floristic data. Vegetation plots were randomly placed

in the vegetation segments that meet the above-

mentioned criteria. Pseudo-replications were avoided.

Vegetation was sampled on the plots of 16 m2 (see

Chytry and Otypkova 2003). The total number of

originally collected samples was 164. Altitude and

co-ordinates were measured by GPS Garmin Etrex

Summit (WGS 84 system) with altimeter calibrated

by current atmospheric pressure. The nomenclature

of vascular plants follows Andreev et al. (1992) and

the bryophytes nomenclature follows Natcheva and

Ganeva (2005). The nomenclature of syntaxa is

according to Rodwell et al. (2002).

Comparative Central-European data set

We have compiled data set of wet grasslands from

Czech (Chytry and Rafajova 2003), Slovak and

Hungarian (data from Botta-Dukat et al. 2005)

phytosociological databases. The initial data set was

stratified by geographical stratification, which di-

vided all countries into quadrats of a geographical

grid of 2.5 longitudinal and 1.5 latitudinal minutes,

i.e. ca. 3 km · 2.8 km. Each of these quadrats

contained only one releve originally assigned to one

association (for details of stratified resampling

method see Knollova et al. 2005). Only vegetation

originally assigned to the Molinietalia order was

considered. This step led to the selection of 3,932

releves—2,725 releves were from the Czech Repub-

lic, 857 from Slovakia and 350 from Hungary. In

order to obtain more representative data set, we

randomly restricted national subsets to equal number

of 250 releves. Resulting data set of 750 releves was

then subjected to Twinspan classification (Hill 1979,

for details see below). The clusters obtained were

interpreted with terms of traditional phytosociologi-

cal alliances Calthion palustris, Molinion caeruleae

and Deschampsion cespitosae, as in Botta-Dukat

et al. (2005). Within these alliances, random restric-

tion was applied in order to obtain data set with the

same number of releves as what was collected in

Bulgaria (n = 164).

Data processing

Both the Central-European data set and the Bulgarian

data set were merged. The classified vegetation is

determined by few dominant ecological factors,

therefore we preferred to use divisive TWINSPAN

classification instead of any cluster analysis. The

main disadvantage of this method is that it basically

produces partitions with cluster numbers equal to 2,

4, 8, 16 etc., while partitions with other number of

clusters are skipped even though they may be

ecologically relevant. In order to control the resulting

cluster number we used a slightly modified TWIN-

SPAN version, which is available in the JUICE

program (Tichy 2002). After each division we

calculated mean Sørensen dissimilarity in species

composition between all pairs of plots within each

terminal cluster (100 � S, where S is Sørensen

similarity; Koleff et al. 2003, for the next application

of the method see Havlova et al. 2004). Then, only

the cluster with the highest mean internal dissimilar-

ity was divided using the usual TWINSPAN divisive

algorithm. We repeated this procedure until newly

appearing clusters were no longer easily interpret-

able. This method does not modify TWINSPAN

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123

classification tree, only the importance of each

division is weighted. TWINSPAN was applied with

three pseudospecies cut levels of 0, 5 and 25% of

species cover and minimum group size for further

division was set at 10 releves.

Central-European releves were deleted from the

table and the following analyses concerned only the

Bulgarian data. Frequency-positive fidelity index

(Tichy 2005) was calculated in order to find whether

each releve really displays the highest similarity to

the vegetation type to which it was assigned by the

Twinspan classification of the total data set. In

several cases, Frequency-positive fidelity index

revealed higher similarity of some releve to another

cluster. Such releves were manually transferred to the

respective group. In the synoptic tables, species were

ranked according to their fidelity value for individual

clusters. Fidelity was calculated by the / (phi)

coefficient of association, applied to the classified

data set with equalised sizes of clusters according to

Tichy and Chytry (2006). The species of insignificant

occurrence concentration in the plots of particular

cluster (Fischer exact test, P < 0.001) were excluded.

Bulgarian releves were subjected to DCA analysis.

Data about altitude, slope angle and species richness

were a posteriori placed onto the DCA scatter. The

Kendall s (tau) correlation coefficient between DCA

site scores and these variables was calculated.

Further, attribute plot showing changes in species

richness along the first two DCA axes was con-

structed as based on Generalised Additive Model

(GAM), using Poisson distribution. The fitted model

was compared to the null model. Nonlinearity test

was applied. Smooth term complexity was selected

using the Akaike information criterion (AIC).

Differences amongst particular vegetation types

were tested by Tukey post-hoc test following one-

way ANOVA. Altitude was log-transformed before

this analysis to approximate normal distribution.

Results

Vegetation classification

TWINSPAN classification of the entire data set

(Bulgaria and Central Europe) resulted in the differ-

entiation of four distinct vegetation types. Even if

they corresponded with traditional phytosociological

alliances Trifolion resupinati (sub-Mediterranean

type, see Micevski 1964), Deschampsion cespitosae

(sub-continental type, including Alopecurion praten-

sis, Cnidion venosi and Agrostion albae, see Botta-

Dukat et al. 2005), Molinion caeruleae (see Koch

1926) and Calthion palustris (sub-oceanic and moun-

tain type, see Tuxen 1937), which are rather drawn as

geographically defined units, they all occur in

Bulgaria (Fig. 1, App. 1–2). When a more precise

classification at the level of seven clusters was

applied, two types of sub-Mediterranean wet grass-

lands and one high-altitude type of sub-oceanic

Calthion grasslands with Balkan (sub)endemics (Jun-

cus thomasii, Dactylorhiza cordigera, Silene asterias)

were detected solely in Bulgaria (Fig. 1, Appendix 1–

2). On the other hand, one vegetation type represent-

ing waterlogged Cirsium meadows with Cirsium

palustre, C. rivulare, Angelica sylvestris, Myosotis

palustris agg., Dactylorhiza majalis and Chaerophyl-

lum hirsutum was detected only in the Central-

European data set. Other vegetation types (Des-

champsion cespitosae, Molinion and low-altitude

base-rich Calthion) were distributed in both regions

under study.

Major gradient in species composition

Altitude is a dominant gradient controlling variation

in Balkan wet grasslands (Fig. 2a). Eigenvalue of the

first axis (0.628; 8.4% of total inertia) is more than

two times higher than eigenvalue of the second DCA

axis (0.278; 3.7%). Moreover, Kendall s correlation

coefficient between the first DCA axis and altitude is

high (0.780, P < 0.001). Vegetation types are clearly

differentiated according to the first DCA axis, with

the exception of Molinion grasslands, which are

clearly separated along the second axis (Fig. 2a).

However, Tukey post-hoc test of altitudinal differ-

ences amongst vegetation types is significant for all

pairs of clusters (P < 0.05), suggesting that altitudinal

differentiation is responsible for co-occurrence of

nearly all European types of wet grasslands in

Bulgaria (Fig. 3).

Species richness

Trends in species richness along the major floristic

gradients are not linear. GAM model shows skewed-

unimodal trends along both major gradients, with the

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123

highest species richness in intermittently wet nutri-

ent-limited grasslands of the Deschampsion cespito-

sae and, especially, Molinion caeruleae alliances

(Fig. 2b). Here, species richness varies from 20 to 70

species per 16 m2 and very often it exceeds 40

species.

Discussion

Climate as an important determinant of wet

grassland diversity

The major broad-scale vegetation types of wet

grasslands in Bulgaria are differentiated by altitude

and occur here in a close spatial contact. Altitude is a

factor that expresses two basic climatic variables, the

mean annual temperature and the precipitation sum.

In Bulgaria, the temperature decreases and precipi-

tation increases along the altitudinal gradient (Mate-

eva 2002). In our case, direct climatic data are not

available for the majority of localities and therefore

altitude is a suitable substitution of them. However,

the correlation between the altitude and the major

compositional gradient (first DCA axis) is weaker in

the zone around 1,400 m of elevation. Despite it,

altitude significantly differs between all pairs of

major vegetation types in our study (Fig. 3).

The importance of climate as a crucial factor

determining plant species distribution and vegetation

zonation was demonstrated many times in habitats

where precipitation is a major source of moisture and

where drought is an important stressing factor in

some vegetation types (e.g. Archibold 1995; Kovacs-

Lang et al. 2000; Duarte et al. 2005; Chytry et al.

2007). Our study shows that the diversity of wet

grasslands, which are saturated by groundwater or

surface water, is substantially influenced by climate

as well. Not only nutrient availability, pH or flooding

intensity, predominantly studied so far (e.g. Olde

Venterink et al. 2001; Schaffers 2002; Hajek and

Hajkova 2004; Hardtle et al. 2006), but also local

climate accounts for variation in the wet grassland

species composition.

Many studies have proven that ongoing climate

change has the potential to dramatically alter the

geographic distribution of vegetation types such as

dry grasslands, tundra, alpine vegetation or forests

(Melillo 1999; Meshinev et al. 2000; Bachelet et al.

2001; Calef et al. 2005). Our results suggest possible

changes also in geographic distribution of particular

types of wet grasslands. In regions of diverse relief

Fig. 1 Classification tree of wet grasslands in the merged data

set containing vegetation samples from both Central Europe

and Bulgaria. Classification is based on slightly modified

Twinspan alghoritm: after calculation, in each division, of the

mean Sørensen dissimilarity in species composition between

all pairs of plots within each terminal cluster, only the cluster

with the highest mean internal dissimilarity being divided

using the usual TWINSPAN divisive algorithm. Syntaxonom-

ical interpretation of obtained clusters is outlined. Geograph-

ical distribution of particular vegetation types is presented by

the abbreviations BG (Bulgaria) and CE (Central Europe)

Plant Ecol

123

such as the Balkans, where major types of wet

grasslands are differentiated by altitude, climate

change (i.e. increasing temperatures, or drought)

could cause deterioration of high-altitude wet grass-

lands, rich in local endemics.

Habitat differentiation of wet grasslands in

Bulgaria

In Bulgaria, the lowest altitudes are occupied by the

sub-Mediterranean type of wet grasslands, which is

described as the Trifolion resupinati alliance. The

analogous vegetation is known from low altitudes of

the Former Yugoslav Republic of Macedonia (Micev-

ski 1964) and from sub-Mediterranean regions of

Greece (Raus 1983). Two major vegetation types of

sub-Mediterranean wet grasslands have been identi-

fied which are differentiated not only by altitude, but

also by soil mineral richness. Conductivity of soil

solution is significantly higher in the first cluster

(Sopotlieva, unpublished data), which is noteworthy

Fig. 2 Detrended correspondence analysis of vegetation plots

from Bulgarian wet meadows. (A) Position of samples along

the first two axes. Altitudes, degree of inclination and total

species richness are plotted passively onto the scatter. The

correlation coefficients (Kendall tau) and significance levels

(*** P 0.001; ** P 0.01) are presented for the first axis. All

these factors are not correlated significantly with the second

axis. Different symbols correspond to particular Twinspan

clusters (1, 2, 3, 4, 5, 7; from the left to the right), which are

presented in Appendix 2 and in Fig. 1. (B) Changes in species

richness along the first two DCA axes expressed as an attribute

plot based on the GAM model. Ecological interpretation of the

axes is presented

Fig. 3 Differences in altitude between major vegetation types

of wet grasslands in Bulgaria obtained from Twinspan

classification. Significant pairwise differences (Tukey post-

hoc test) are indicated by different letters

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due to the occurrence of salt-tolerating species

Hordeum secalinum, Carex divisa, Scorzonera lacin-

iata and Juncus gerardii (App. 2).

An interesting insight into biogeography and

ecology of wet grasslands is drawn by the comparison

of the distribution pattern of Deschampsion grass-

lands in the Central Europe and on the Balkans. In

Central Europe, this vegetation type is limited to

flooded lowland meadows of large river alluvia with a

continental affinity, up to 350 m of altitude (Botta-

Dukat et al. 2005). On the contrary, the Bulgarian

localities of this vegetation type are found only at

altitudes of about 700 m, especially in the inter-

mountain basin around the City of Sofia. This

comparison underlines the fact that upward shift of

Central-European vegetation types in southern Eur-

ope, so often described in forest vegetation (e.g.

Horvat et al. 1974), is also evident for grassland

vegetation. In Bulgaria, intermittently wet Molinion

grasslands were found in higher altitudes than do

Deschampsion grasslands. However, there is a great

altitudinal overlap between them in Bulgaria and

these two vegetation types often occur together in one

locality. DCA analysis suggests that nutrient avail-

ability is partially responsible for their habitat

differentiation. Molinion grasslands often occur in

soils with unfavourable nutrient supply as opposed to

Deschampsion grasslands (Botta-Dukat et al. 2005).

Molinion grasslands are probably strongly limited by

phosphorus, as suggested by (i) their common

occurrence in the complexes of calcareous fens,

which are known as strongly P-limited habitats

(Boyer and Wheeler 1989; Boeye et al. 1997;

Bedford et al. 1999), and their exclusive occurrence

on calcareous organic soils in lowlands (Botta-Dukat

et al. 2005), (ii) high representation of herbs as

compared to graminoids (compare Hardtle et al.

2006) and (iii) their absence in alluvia regularly

inundated by phosphorus-rich river water (compare

Hardtle et al. 2006).

Wet grasslands of the highest altitudes are occu-

pied by Calthion grasslands in Bulgaria. As com-

pared to intermittently wet Molinion and

Deschampison grasslands, permanently waterlogged

Calthion grasslands display higher beta diversity in

both, Central Europe and the Balkans. It accords well

with the finding of Havlova et al. (2004), who have

also found that grassland vegetation in waterlogged

habitats exhibits a higher degree of change in species

composition amongst different sites. In Bulgaria, the

major difference was found between waterlogged

grasslands of middle altitudes of ca 900–1,300 m

a.s.l. and waterlogged grasslands of high altitudes of

ca 1,400–1,700 m a.s.l. Altitudinal range of the

Calthion grasslands partially overlaps with that of the

Molinion grasslands. When Calthion and Molinion

grasslands occur together at the same site, Calthion

habitats occupy the wettest patches. Floristic exclu-

sivity of the high-mountain Calthion, is deepened by

both the mineral-poor crystalline bedrock and the

high representation of Balkan endemics and sub-

endemics. The analogous pattern has been found in

high-mountains fens where representation of Balkan

elements also increased with altitude (Hajkova et al.

2006).

The marked altitudinal differentiation of otherwise

broad-scale vegetation types suggests that distribu-

tions of wet-grassland vegetation types in Bulgaria

are influenced by the individual micro-climatic and

moisture requirements of species rather than by

chance and dispersal limitation as would be indicated

by the neutral theory (Hubbell 2005). Complete

species turnover from sub-Mediterranean type of wet

grasslands through Molinion and sub-continental

Deschampsion grasslands towards sub-oceanic Cal-

thion grasslands was described along the southern

slopes of Stara Planina Mt., which measures only

several kilometres.

Species richness

Interestingly, relation between the first DCA axis

(climatic gradient) and species richness in Bulgarian

wet grasslands is left-skewed, with a low number of

species in sub-Mediterranean wet grasslands. Medi-

terranean grasslands are generally known to be rich in

species but their high species richness is mostly due

to annual plant species (Archibold 1995; Tallis 1991).

Annuals are rare in Bulgarian wet sub-Mediterranean

grasslands and some of these habitats are, in addition,

stressed by high concentration of salts. On the other

hand, a decrease in species richness towards moun-

tain waterlogged Calthion grasslands can be ex-

plained by increasing aboveground biomass that limit

local species richness (Al-Mufti et al. 1977; Wheeler

and Shaw 1991; Dwire et al. 2004). The second factor

that reduces the species richness in Bulgarian high-

altitude wet grasslands is acidity, the effect of which

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123

increases upwards along the altitudinal gradient in

Bulgaria (Hajkova and Hajek 2007). In the Northern

Hemisphere, acid soils are markedly poorer in species

than alkaline soils (Partel 2002).

It is generally accepted that high species richness

in Deschampsion and Molinion grasslands is caused,

amongst other reasons, by extremely variable mois-

ture regime that allows a unique co-existence of

flood- and drought-tolerant plant species. We hy-

pothesise that the species richness pattern in Bulgar-

ian wet grasslands is further deepened by the species

pool effect. More common habitats tend to be richer

in species since they offered more opportunities for

speciation (Aarssen and Schamp 2002; Partel 2002;

Pither and Aarssen 2005) and showed a low extinc-

tion of specialised species (Ewald 2003b). High

species richness of intermittently wet Deschampsion

grasslands can therefore be caused by the fact that

this vegetation occupies more ample territory in

Bulgaria than both the sub-Mediterranean wet grass-

lands and the mountain Calthion grasslands (Mesh-

inev et al. 2005).

Relationship between the second DCA axis, inter-

preted as an axis of increasing nutrient availability,

and plant species richness is right-skewed. Herb-rich

Molinion meadows, occupying nutrient-poor part of

this gradient, are species-richest due to small repre-

sentation of nutrient-requiring graminoids that utilise

an improved nutrient supply to increase their com-

petitive power (Hardtle et al. 2006).

High habitat diversity in the Balkans

Hitherto vegetation typologies suppose rather locally

distributed, mutually vicariant vegetation types in the

Balkans. On the contrary, our study found that nearly

all Central-European types of wet grasslands occur in

Bulgaria, with the exception of one type of sub-

montane but acidic waterlogged grasslands with

Cirsium palustre (the Angelico sylvestris–Cirsietum

palustris association, see Hajek and Hajkova 2004).

Altitudinal differentiation of nearly all major ‘‘Euro-

pean’’ broad-scale types of wet grasslands on the

rather small territory of Bulgaria has certain analo-

gies in other habitats. Generally, it seems that the

Balkan vegetation of middle altitudes matches that of

Central Europe, whereas lowest altitudes one corre-

sponds rather to sub-Mediterranean region and high-

est altitudes are specific due to a high endemism,

severe climatic conditions and prevailing crystalline

bedrock. This pattern was also revealed by a detailed

analysis of Bulgarian beech forests (Tzonev et al.

2006) and it is also indicated by the data from mires

(Hajkova et al. 2006). Diverse relief, which is

characterised by steep altitudinal gradients from

warm and dry lowlands to alpine grasslands, enables

confluence of habitats possessing different climatic

conditions at a local scale and represents the key for

understanding extraordinary vegetation diversity in

the Balkans. Our data suggest that this phenomenon

holds true not only for moisture-limited habitats, but

also for the diversity of wet grasslands.

Acknowledgements We thank Hristo Pedashenko and

Marcela Havlova for providing us unpublished releves from

Bulgaria. We thank Boryana Mihova for the English revision

of the manuscript. Thanks are extended to Erwin Bergmeier

and two anonymous reviewers, whose comments improved the

manuscript. The research was performed within the long-term

research plans of Masaryk University, Brno (No.

MSM0021622416) and of Botanical Institute of Czech

Academy of Sciences (No. AVZ0Z60050516). Field

investigation was partly carried out within the exchange

project of the Czech and Bulgarian Academies of Sciences

(Vegetation diversity of the lowland wet meadows in Bulgaria,

2005–2007).

Appendix 1

Shortened synoptic table of species percentage

occurrence in seven major vegetation types of wet

grasslands resulting from the Twinspan classification

of the merged data set. Diagnostic species of

individual vegetation types were determined using

the phi-coefficient of association (* U > 0.35, **

U > 0.45). Species, the occurrence concentration

probability of which, in the given vegetation type,

does not differ from random at P < 0.05 are excluded

from the list of diagnostic species. Only species with

U > 0.35 or with percentage constancy >50% at least

in one column are presented. Abbreviation ‘‘dif.’’

indicates the species having clear optimum outside

wet grassland vegetation. The diagnostic (i.e. differ-

entiate) value of such a species is valid only within

our data set. Classified data sets contained 164

vegetation plots from Bulgaria and 164 vegetation

plots from Central Europe.

Plant Ecol

123

No of cluster 1 2 3 4 5 6 7

No of releves 21 22 70 81 46 29 59

Trifolion resupinati (cluster 1: salt-rich, lowest altitudes)

Hordeum secalinum 81** 14 . . . . .

Carex divisa 38** . 3 . . . .

Cichorium intybus 52** 27 . 1 . . .

Bromus secalinus 43** 23 . . . . .

Elymus repens 48** . 23 1 2 7 .

Alopecurus myosuroides 33* 14 . . . . .

Lolium perenne 52* 45 6 1 . . .

Scorzonera laciniata 19* . . . . . .

Centaurea calcitrapa 19* . . . . . .

Trifolium resupinatum 19* . . . . . .

Geranium dissectum 19* . . . . . .

Trifolium michelianum 14* . . . . . .

Hordeum bulbosum 14* . . . . . .

Trifolion resupinati (cluster 2)

Ranunculus sardous 38 95** 1 . . . .

Orchis laxiflora agg. 5 59** 10 5 . 3 3

Trifolium patens 5 59** 7 4 . 7 5

Galium debile . 32** . . . . .

Carex distans 29 59** 9 15 . 3 .

Gratiola officinalis . 41** 14 5 . 3 .

Alopecurus rendlei 5 27* . . . . .

Moenchia mantica 10 32* . 1 . . .

Plantago lanceolata 43 86* 43 46 9 17 7

Rhinanthus angustifolius . 18* . . . . .

Euphrasia stricta . 18* . . . . .

Chrysopogon gryllus (dif.) . 23* . 6 . . .

Amblystegium riparium . 18* . . . . 2

Rhinanthus rumelicus . 36* 9 7 . 10 3

Ononis arvensis 14 41* 9 17 . . 2

Cynosurus cristatus 5 59* 11 15 4 31 31

Mentha spicata 10 23* . . . . .

Deschampsion (cluster 3)

Alopecurus pratensis 14 . 84** 12 54 24 5

Taraxacum sect Ruderalia 24 9 69** 17 2 24 8

Carex praecox 5 . 29* 1 . . .

Glechoma hederacea s. lat. . . 33* 4 . 14 .

Poa pratensis agg. 14 14 70* 42 39 31 3

Molinion (cluster 4)

Molinia caerulea s. lat. . . . 80** 13 7 14

Serratula tinctoria . . 16 49** 2 . 3

Betonica officinalis . 5 6 42** 2 3 3

Linum catharticum . . . 31** 2 3 2

Plant Ecol

123

No of cluster 1 2 3 4 5 6 7

No of releves 21 22 70 81 46 29 59

Centaurea jacea agg. . . 29 48** 4 . 3

Leontodon hispidus . 5 10 36* . . 2

Succisa pratensis . . 6 49* 15 . 22

Carex flacca . . 1 28* 2 . 3

Filipendula vulgaris . 18 9 41* 2 . 3

Sanguisorba officinalis . . 44 63* 30 10 7

Galium boreale . . 19 35* 7 . .

Trifolium montanum . . . 15* . . .

Carex panicea . 5 21 67* 41 38 24

Calthion (cluster 5: Central-European waterlogged Cirsium palustre grasslands)

Cirsium palustre . . 1 4 46** 3 .

Angelica sylvestris . . 6 5 48** 3 .

Myosotis palustris s. lat. . . 9 10 74** 21 51

Cardamine pratensis agg. . . 29 4 43* 3 .

Rhytidiadelphus squarrosus . . . 2 24* 3 .

Cirsium rivulare . . 3 12 37* 10 2

Dactylorhiza majalis s. lat. . . . 2 20* . .

Chaerophyllum hirsutum . . . . 26* 3 8

Calthion (cluster 6: sub-montane waterlogged grasslands on alkaline soils)

Mentha longifolia . . 3 . 11 55** 22

Hypericum tetrapterum . . 1 . 2 34** 7

Lythrum salicaria . . 19 25 11 55* 10

Juncus inflexus . 9 6 15 4 41* 7

Ranunculus repens 5 9 61 20 43 79* 41

Plagiomnium undulatum . . . 1 7 24* 3

Calthion (cluster 7: Balkan high-mountain waterlogged grasslands)

Geum coccineum . . . . . 3 61**

Luzula sudetica . . . . . . 49**

Epilobium palustre . . . . 20 10 53**

Juncus thomasii . . 1 . 2 10 41**

Trifolium spadiceum . . . . . . 25**

Veratrum album s. lat. . . . 5 11 . 39**

Parnassia palustris . . . 4 4 . 32**

Dactylorhiza cordigera . . . . 2 10 36**

Carex echinata . . . 2 11 24 49**

Hieracium caespitosum . . . 2 . 21 41*

Galium palustre s. lat. 10 . 19 11 35 62 78*

Agrostis canina . 9 . 9 22 24 53*

Potentilla erecta . 5 . 47 41 41 73*

Oenanthe fistulosa 5 5 1 1 . 17 37*

Aulacomnium palustre . . . 1 4 . 22*

Nardus stricta . . . 15 17 . 37*

Alchemilla vulgaris agg. . . 10 4 46 28 58*

Appendix 1 continued

Plant Ecol

123

Appendix 2

Shortened synoptic table of species percentage

occurrence in six major Bulgarian vegetation types

of wet grasslands resulting from the Twinspan

classification of the merged data set from Bulgaria

and Central Europe. Diagnostic species of individual

vegetation types were determined using the phi-

coefficient of association (* U > 0.35, ** U > 0.45).

Species, the occurrence concentration probability of

which, in the given vegetation type, does not differ

from random at P < 0.001 are excluded from the list

of diagnostic species. Only species with U > 0.35 or

with percentage constancy >50% at least in one

column are presented. Cluster numbers are the same

as in Appendix 1 and Fig. 1. Abbreviation ‘‘dif.’’

indicates the species having clear optimum outside

wet grassland vegetation. The diagnostic (i.e. differ-

entiate) value of such a species is valid only within

our data set.

No of cluster 1 2 3 4 5 6 7

No of releves 21 22 70 81 46 29 59

Carex nigra agg. . . 3 10 52 14 54*

Myosotis sicula . 5 . . . 14 29*

Eriophorum latifolium . 5 . 5 4 . 25*

Carex canescens . . . . 7 . 20*

Species diagnostic for two clusters

Poa sylvicola 95** 73* 11 . . 28 14

Scirpus sylvaticus . . 4 5 80* 86* 63

Other frequent species

Ranunculus acris 5 . 66 72 72 62 69

Deschampsia caespitosa 5 9 46 65 46 34 83

Festuca pratensis agg. 33 82 63 36 41 62 19

Holcus lanatus . 86 39 49 33 69 37

Festuca rubra agg. . 5 29 52 57 38 71

Rumex acetosa . 23 51 35 59 59 37

Anthoxanthum odoratum s. l. . 73 34 36 37 45 39

Lathyrus pratensis . . 43 41 48 41 42

Lychnis flos-cuculi . . 61 23 57 62 17

Lysimachia nummularia . 41 57 25 22 66 19

Prunella vulgaris . 50 27 44 17 45 34

Achillea millefolium agg. 14 23 50 49 24 28 7

Poa trivialis 10 5 50 7 46 52 39

Cirsium canum 14 9 53 48 11 31 5

Trifolium pratense 38 73 37 22 13 38 19

Juncus effusus . 23 11 6 43 55 68

Calliergonella cuspidata . 32 11 16 22 59 63

Filipendula ulmaria . . 16 19 61 45 31

Caltha palustris . . 6 10 57 38 54

Plagiomnium affine agg. . . 1 11 39 52 54

Equisetum arvense . 9 17 19 20 52 31

Appendix 1 continued

Plant Ecol

123

No. of cluster 1 2 3 4 6 7

No. of releves 22 18 22 22 29 51

Trifolion resupinati (cluster 1: salt-rich, lowest altitudes)

Bromus secalinus 64** . . . . .

Hordeum secalinum 77** 6 9 . . .

Cichorium intybus 68** 11 . 5 . .

Lolium perenne 68** 28 18 5 . .

Crepis setosa 50** 22 . . . .

Carex divisa 36** . 9 . . .

Plantago major 45** 6 9 . 7 2

Poa sylvicola 95* 61 55 5 31 12

Centaurea calcitrapa 18* . . . . .

Geranium dissectum 18* . . . . .

Scorzonera laciniata 18* . . . . .

Alopecurus myosuroides 32* 17 . . . .

Elymus repens 36* 6 14 . 7 .

Juncus gerardii 36* 28 . . . .

Trifolion resupinati (cluster 2)

Ranunculus sardous 55 94** . . . .

Cirsium arvense (dif.) 5 39** 5 . . .

Orchis laxiflora s.l. 5 67** 32 14 14 .

Euphrasia stricta . 22* . . . .

Sanguisorba minor . 22* . . . .

Rhinanthus angustifolius . 22* . . . .

Amblystegium riparium . 22* . . . 2

Galium debile 9 28* . . . .

Trifolium patens 18 56* 23 5 10 4

Gratiola officinalis 5 44* 14 9 10 .

Ononis arvensis 14 56* 14 32 3 .

Chrysopogon gryllus(dif.)

. 33* . 18 . .

Ophioglossum vulgatum . 22* . 5 . .

Festuca nigrescens . 22* . 5 . .

Deschampsion (cluster 3)

Taraxacum sectRuderalia

. 6 73** 14 10 8

Alopecurus pratensis . . 68** 9 21 6

Carex otrubae 18 11 59** . . .

Carex spicata . . 36** . 3 .

Cirsium canum . 6 86** 64 38 .

Bromus commutatus . . 36** . 7 2

Juncus compressus . 11 36** . . .

Carex melanostachya . . 18* . . .

Potentilla reptans 41 33 73* 5 31 2

Poa trivialis . . 68* 9 48 41

Molinion (cluster 4)

Appendix 2 continued

No. of cluster 1 2 3 4 6 7

No. of releves 22 18 22 22 29 51

Serratula tinctoria . . 5 73** . .

Filipendula vulgaris . 28 14 86** 3 .

Stachys officinalis . 6 9 68** 3 .

Sanguisorba officinalis . . 18 73** 3 4

Molinia caerulea s.l. . . . 68** 14 8

Carex caryophyllea . . . 32** . .

Iris sibirica . . . 27** . .

Luzula multiflora . . . 27** . 2

Luzula campestris . . 5 32* . 4

Danthonia alpina . . 9 32* . .

Viola jordanii . . . 18* . .

Gentiana pneumonanthe . . . 18* . .

Rhinanthus wagneri . . . 18* . .

Potentilla erecta . 6 . 77* 45 71

Bistorta major . . . 41* 7 22

Carex panicea . . 50 73* 41 22

Festuca rubra . 6 32 82* 48 71

Centaurea jacea . . 9 27* . 4

Juncus conglomeratus . . 23 45* 10 16

Calthion (cluster 6: sub-montane waterlogged grasslands on

alkaline soils)

Hypericum tetrapterum . . . . 48** 2

Lythrum salicaria . . 23 9 69** 6

Mentha longifolia . . 5 . 59** 20

Ranunculus repens . 6 55 5 90** 37

Lycopus europaeus . . . . 31** 4

Epilobium parviflorum . . . . 24** .

Lysimachia vulgaris . . 9 14 45* 10

Plagiomnium affine agg. . . . 14 59* 53

Calthion (cluster 7: Balkan high-mountain waterlogged

grasslands)

Luzula sudetica . . . . . 57**

Geum coccineum . . . . 14 65**

Carex nigra . . . . 14 59**

Epilobium palustre . . . . 17 57**

Myosotis nemorosa s.l. . . . . 21 57**

Caltha palustris . . . . 34 59**

Alchemilla vulgaris agg. . . . 14 28 59**

Parnassia palustrs . . . . 7 33**

Crepis paludosa . . . . 7 33**

Carex rostrata . . . . 3 29**

Carex curta . . . . . 24**

Trifolium spadiceum . . . . 3 27**

Plant Ecol

123

Appendix 3

Species scores along the first DCA axis. Only species

with the weight >5 in the analysis are presented.

Appendix 2 continued

No. of cluster 1 2 3 4 6 7

No. of releves 22 18 22 22 29 51

Juncus tomasii . . 5 9 14 43*

Carex echinata . . . 5 38 51*

Veratrum lobelianum . . . 18 7 41*

Eriophorum angustifolium . . . . . 20*

Dactylorhiza cordigera . . . . 21 37*

Agrostis canina 5 6 . 18 28 55*

Climacium dendroides . . . 9 38 47*

Cardamine rivularis . . . . . 16*

Aulacomnium palustre . . . 9 . 24*

Species diagnostic for two clusters (Calthion)

Scirpus sylvaticus . . 9 5 72** 69*

Galium palustre . . 27 14 76* 80*

Other frequent species

Deschampsia caespitosa . 6 59 82 48 82

Holcus lanatus 18 78 55 82 72 31

Ranunculus acris . . 64 77 66 67

Anthoxanthum odoratum 14 78 59 68 45 35

Festuca pratensis 41 78 64 41 59 16

Calliergonella cuspidata . 39 27 41 55 59

Juncus effusus . 28 23 14 59 67

Trifolium pratense 50 67 45 41 38 16

Rumex acetosa 9 22 36 55 59 33

Plantago lanceolata 55 78 73 41 17 6

Cynosurus cristatus 14 56 45 55 34 27

Lysimachia nummularia 5 39 59 36 55 14

Carex hirta 14 44 59 32 34 18

Stellaria graminea . . 36 64 31 37

Equisetum arvense . 11 27 23 59 25

Lychnis flos-cuculi . . 59 23 59 14

Carex pallescens . . 23 55 21 33

Agrostis stolonifera . . 55 45 38 6

Bromus secalinus �0.8955

Hordeum secalinum �0.5779

Crepis setosa �0.3426

Carex divisa �0.1794

Appendix 3 continued

Bromus secalinus �0.8955

Cichorium intybus �0.1595

Alopecurus myosuroides �0.1431

Vicia grandiflora 0.1025

Elymus repens 0.1780

Juncus gerardii 0.2227

Oenanthe silaifolia 0.2253

Lolium perenne 0.2733

Alopecurus rendlei 0.6686

Mentha spicata 0.7316

Convolvulus arvensis 0.8175

Poa sylvicola 0.8214

Moenchia mantica 0.8330

Ranunculus sardous 0.9300

Plantago major 0.9430

Daucus carota 0.9980

Cirsium arvense 1.2299

Rumex crispus 1.2796

Medicago lupulina 1.4163

Carex distans 1.5629

Lotus corniculatus 1.5642

Trifolium patens 1.5970

Trifolium repens 1.6102

Potentilla reptans 1.6704

Ononis arvensis 1.7301

Chrysopogon gryllus 1.7438

Plantago lanceolata 1.7890

Carex otrubae 1.7894

Trifolium pratense 1.9264

Festuca pratensis 1.9311

Galium verum 2.0918

Orchis laxiflora 2.0929

Dactylis glomerata 2.0938

Rhinanthus rumelicus 2.2552

Gratiola officinalis 2.2618

Juncus compressus 2.3433

Trifolium campestre 2.3920

Achillea millefolium 2.4135

Carex spicata 2.4149

Carex tomentosa 2.4543

Eleocharis palustris 2.4850

Festuca valesiaca 2.5343

Festuca arundinacea 2.5627

Leucanthemum vulgare 2.6597

Alopecurus pratensis 2.7119

Plant Ecol

123

Appendix 3 continued

Bromus secalinus �0.8955

Filipendula vulgaris 2.7377

Anthoxanthum odoratum 2.7386

Juncus articulatus 2.7387

Bromus commutatus 2.7697

Cynosurus cristatus 2.7786

Carex hirta 2.7921

Holcus lanatus 2.8180

Ranunculus polyanthemus 2.8408

Poa pratensis 2.8414

Eleocharis uniglumis 2.8532

Taraxacum sect. Ruderalia 2.8603

Cirsium canum 2.8776

Rhinanthus minor 2.8804

Leontodon hispidus 2.8877

Phleum pratense 2.9338

Sieglingia decumbens 3.0523

Agrostis stolonifera 3.0563

Stachys officinalis 3.0649

Lysimachia nummularia 3.0769

Drepanocladus aduncus 3.1030

Centaurea jacea 3.1626

Trifolium hybridum 3.1779

Leontodon autumnalis 3.2043

Juncus atratus 3.2093

Prunella vulgaris 3.2340

Serratula tinctoria 3.2415

Cerastium holosteoides 3.2438

Bromus racemosus 3.2758

Carex acuta 3.3125

Danthonia alpina 3.4155

Centaurea phrygia 3.4169

Rumex acetosa 3.4844

Sanguisorba officinalis 3.5560

Juncus inflexus 3.5592

Agrostis capillaris 3.6201

Lychnis flos-cuculi 3.6825

Carex panicea 3.7254

Briza media 3.8039

Luzula campestris 3.8283

Myosotis caespitosa 3.8519

Molinia caerulea 3.9568

Ranunculus repens 3.9577

Stellaria graminea 3.9830

Poa trivialis 3.9941

Appendix 3 continued

Bromus secalinus �0.8955

Calliergonella cuspidata 4.0122

Lythrum salicaria 4.0160

Carex ovalis 4.0278

Equisetum arvense 4.0354

Oenanthe banatica 4.0582

Cardamine matthioli 4.0720

Ranunculus acris 4.0936

Juncus conglomeratus 4.1269

Brachythecium rutabulum 4.1680

Deschampsia caespitosa 4.2354

Juncus effusus 4.2399

Vicia cracca 4.2577

Mentha arvensis 4.2923

Festuca rubra 4.2995

Equisetum palustre 4.3071

Carex pallescens 4.3205

Bryum pseudotriquetrum 4.3495

Lathyrus pratensis 4.3806

Blysmus compressus 4.3984

Oenanthe fistulosa 4.4194

Lysimachia vulgaris 4.4683

Hypericum tetrapterum 4.5527

Brachythecium rivulare 4.6075

Agrostis canina 4.6378

Lycopus europaeus 4.6380

Succisa pratensis 4.6526

Mentha longifolia 4.6639

Hieracium caespitosum 4.7176

Ajuga reptans 4.7360

Equisetum fluviatile 4.7896

Galium palustre 4.8112

Scirpus sylvaticus 4.8379

Ranunculus auricomus 4.8594

Potentilla erecta 4.9011

Climacium dendroides 4.9182

Nardus stricta 4.9254

Bistorta major 4.9378

Philonotis fontana 4.9383

Myosotis sicula 4.9498

Plagiomnium affine 4.9534

Ranunculus flammula 4.9727

Campylium stellatum 4.9995

Carex flava 5.0675

Veronica scutellata 5.0982

Plant Ecol

123

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Appendix 3 continued

Bromus secalinus �0.8955

Trifolium spadiceum 5.1833

Cruciata glabra 5.2041

Carex echinata 5.2574

Juncus tomasii 5.3017

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Caltha palustris 5.8021

Ranunculus nemorosus 5.8457

Carex rostrata 5.8802

Geum rivulare 5.9116

Crepis paludosa 5.9376

Dactylorhiza cordigera 5.9480

Veratrum lobelianum 5.9483

Carex curta 5.9882

Parnassia palustris 6.0211

Epilobium palustre 6.0849

Luzula sudetica 6.2168

Myosotis nemorosa 6.2762

Carex paniculata 6.3033

Geum coccineum 6.4584

Cardamine rivularis 6.5399

Carex nigra 6.5802

Silene asterias 6.7124

Chaerophyllum hirsutum 6.7303

Eriophorum angustifolium 6.8843

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