Impact of management on biodiversity-biomass relationsin Estonian flooded meadows

Lena Neuenkamp • Jaak-Albert Metsoja •

Martin Zobel • Norbert Holzel

Received: 13 February 2013 / Accepted: 8 May 2013

� Springer Science+Business Media Dordrecht 2013

Abstract A negative species richness–productivity

relationship is often described in grasslands at smaller

scales. We aimed to study the effect of management on

this relationship. In particular, we addressed the

relative importance of biomass cutting, hay removal

and nutrient impoverishment on species richness and

growth form structure. We conducted fieldwork in

flooded meadows in Alam-Pedja Nature Reserve,

central Estonia. We sampled vegetation in managed

and abandoned stands of two types of alluvial

meadows, sedge and tall forb meadow. Aboveground

biomass and litter were harvested, weighed and

analysed for major plant nutrients by near infrared

reflectance spectroscopy. Three groups of general

additive models were developed and compared,

addressing the impact of (i) productivity, (ii) nutrients

and (iii) management regime on species richness.

Management—mowing and hay removal—reduced

the amount of litter but not aboveground biomass.

Management led to a decrease in nitrogen in the

biomass and enhanced species richness, particularly in

the tall forb meadow. The strongest determinant of

species richness was the amount of litter, exhibiting a

hump-shaped relationship with richness. The effect of

nitrogen supply was significant, but explained less

variation. Management increased the proportion of

sedges in the sedge meadow and of small herbs in the

tall forb meadow. We conclude that litter removal is

the most important management means to support

biodiversity. On highly productive sites, reducing

nutrients via hay removal is of secondary importance

within a timeframe of 10 years.

Keywords Grassland � Mowing � Species richness �Growth form � Litter � Nitrogen

Introduction

Successful management of biodiversity has to account

for all interactions between biodiversity, productivity

and nutrient status (Robson et al. 2010; Tilman et al.

2012). Particularly in grasslands, mowing and hay

removal can influence directly both productivity and

nutrient content by removing biomass and hence

reducing nutrient levels in the ecosystem. At the same

time, local species richness is affected by productivity,

which in turn is dependent on nutrient pools in the soil

(Berendse et al. 1992; Wahlman and Milberg 2002).

Electronic supplementary material The online version ofthis article (doi:10.1007/s11258-013-0213-y) containssupplementary material, which is available to authorized users.

L. Neuenkamp (&) � J.-A. Metsoja � M. Zobel

Institute of Ecology and Earth Science, University of

Tartu, Lai 40, 51005 Tartu, Estonia

e-mail: lena@ut.ee

L. Neuenkamp � N. Holzel

Institute of Landscape Ecology, University of Muenster,

Robert-Koch-Str. 28, 48149 Muenster, Germany

123

Plant Ecol

DOI 10.1007/s11258-013-0213-y

Therefore, it is crucial to examine management in

terms of its impact on all three components—species

richness, productivity and nutrient statusof the

ecosystem.

Hay removal is known to remove nutrients from the

ecosystem and thus reduce long-term biomass pro-

duction (e.g. Bakker 1989; Jansen 2000; Olde Vent-

erink et al. 2001). Many studies have shown that

nitrogen (N) and phosphorus (P) are the most frequent

growth-limiting nutrients in European herbaceous

grass-and wetland vegetation (Verhoeven et al.

1996; Olde Venterink et al. 2003). The relative

importance of soil N and P in explaining patterns of

plant species richness has not been completely disen-

tangled yet. N is frequently considered as the key

nutrient limiting terrestrial production (Bobbink et al.

1998; Stevens et al. 2004), but recent studies found N

and P co-limitation to be equally important (Elser et al.

2007) or P limitation being even more important

(Wassen et al. 2005; Klaus et al. 2011a; Ceulemans

et al.2013).

Productivity affects species richness in grasslands

via increased aboveground biomass, height and com-

petition for light (Hautier et al. 2009). Compared with

competition for soil resources, competition for light is

more asymmetric and thus more likely to drive inferior

species to extinction (Grime 1979). Similarly, seed-

ling recruitment is strongly hampered by raised

biomass levels (Tilman 1997; Foster and Gross

1998; Leps 1999; Foster et al. 2004). Under high

productive conditions, as in the floodplain meadows,

regular extensive management—mowing and hay

removal—is mandatory in order to enable short

growing species, otherwise suffering from asymmetric

light competition, to persist (Leps 1999; Hautier et al.

2009). However, as shown by Socher et al. (2012),

management can modulate biodiversity productivity

relations in various directions depending on regional

environmental settings.

Together with the amount of living biomass, litter is

an important factor influencing plant community

structure and processes (Xiong et al. 2003; Lamb

2008; Patrick et al. 2008; Loydi et al. 2013). Plant litter

can alter germination cues (Facelli and Pickett 1991;

Weltzin et al. 2005), may cause direct physical

interference (Facelli 1994), provides a cover for seeds

and seed predators (Crawley and Long 1995; Donath

and Eckstein 2012), and encourage pathogens (Xiong

and Nilsson 1999). In particular, a thick litter layer

may inhibit seed germination and seedling establish-

ment, and thus reduce local richness (Jensen and

Gutekunst 2003; Eckstein and Donath 2005; Lamb

2008).

Changes in the management regime and their

effects on the intensity and asymmetry of light

competition often induce changes in the growth form

composition of plant communities as well. Mowing

and grazing remove disproportionally more tall plants,

thus reducing the asymmetry in competition (Grime

et al. 1987; Leps 1999). When management ceases,

tall-growing species can exhibit their competitive

potential and outcompete shorter species (Jensen and

Schrautzer 1999). Consequently, mowing favours

shorter species that are weaker competitors for light;

the persistence of many typical grassland species often

depends strongly on mowing (Poptcheva et al. 2009).

Management of semi-natural grasslands requires a

coherent understanding of likely interactions in order

to maintain species richness and diversity. We

analysed how plant species richness in flooded mead-

ows in Estonia is influenced concurrently by the

amount of aboveground biomass and litter, as well as

by the nutrient status of the ecosystem, and how these

relationships relate to management.

In particular, we addressed the following questions:

i. What is the relative importance of aboveground

biomass and litter in determining species

richness?

ii. To what extent does management reduce nutrients

in aboveground biomass in highly productive

floodplain meadows, and does the rate of reduc-

tion differ among community types? Does nutri-

ent reduction affect productivity?

iii. Which growth forms profit from management

and does management suppress dominant

competitors?

Materials and methods

Study area

The study was conducted in the Alam-Pedja Nature

Reserve (NR) in central Estonia (26� 14090 E; 58� 280

N; 342 km2)) (Fig. 1). Situated 32–47 m a.s.l., the

Plant Ecol

123

mean annual temperature is ?4.5 �C and the mean

annual precipitation is 629 mm (Metsoja et al. 2012).

Alam-Pedja NR was established in 1994 to protect

forests and wetlands, of which 260 km2 were declared

a Ramsar Site in 1997. The entire NR, including ca.

3,000 ha of Northern boreal alluvial meadows (habitat

type 6450) along the banks of the Emajogi, Poltsamaa

and Pedja rivers, was designated a Natura 2000 site in

2004. Until the 1980s the flooded-meadow areas were

mown annually for hay-making. Management then

ceased almost completely until 2000, when restoration

management started. Since then, the managed area has

increased up to about 1,100 ha in 2011. Mowing now

extends from ca. 10th of july until the end of

september, matching the historical timing of manage-

ment. However, due to weather conditions (e.g. floods)

the regularity of management in situ varies

considerably.

We studied flooded meadows near Kirna village

located on the banks of the Pedja river at two sites with

well-documented management history. Two major

meadow vegetation types can be distinguished at both

sites according to the typology of Estonian grasslands

(Krall et al. 1980). Sedge meadows (Caricetum acutae

community) are present in old riverbeds with high and

persistent inundation. Tall forb meadows (Filipendu-

lo-Geranietum palustris community) are located at

higher elevations of the floodplain and are less prone

to flooding. Flooding in the sedge meadow occurs

typically from the end of march to the beginning of

may (5–6 weeks). The tall forb community is flooded

for approximately 3 weeks (data from the Estonian

meteorological and hydrological institute from

2000–2011; unpublished material by JA Metsoja).

The water level rises by up to one meter in the tall forb

meadow and by more than 2 m in the sedge meadow.

Sampling design

Sampling was conducted in the tall forb and sedge

meadow communities at two sites during summer

2011. Both community types were represented either

by abandoned stands, where mowing ceased perma-

nently in mid-1980s, or by stands where regular

mowing restarted in 2000. Each available combination

of site, community and management regime (alto-

gether six combinations) was sampled in six repli-

cates, leading to a total of 48 samples. A map of the

sampling area is provided in the online resource

(Fig. 1).

Vegetation sampling

The occurrence of all vascular plants was recorded on

randomly located 1 9 1 m plots within each target

stand (a uniform area of approximately 30 9 30 m).

Fig. 1 Study area

Plant Ecol

123

Species cover was estimated using increments of 1 %

up to a cover of 10 %, and increments of 5 % for cover

[10 %. The plant species nomenclature follows Kukk

(1999).

Growth form composition was characterized by

classifying each species into one of the following

growth form categories: tall forbs ([1 m), small herbs,

sedges (Carex, Juncus and Luzula families), grasses,

legumes and shrubs (online resource, Table 1). The

cover data from corresponding species were then

added up to generate integrative cover values for each

growth form type. Because shrubs and legumes were

sparsely distributed and exhibited very low cover, they

were excluded from further analysis.

Biomass sampling

Aboveground biomass and litter—lying and standing

dead biomass—were cut with scissors 2–3 cm above

the soil surface within an area of 0.1 m2 in late July

2011. To leave vegetation sampling plots intact,

cutting was done 1 m east of each plot. Samples were

dried immediately after harvesting for 24 h at 75 �C

and weighed.

Recording NIR-spectra and chemical analysis

Nutrient concentrations in aboveground plant biomass

integrate spatial and temporal variation in soil

resources and weather conditions during the growing

season. As such, they serve as a good indicator of plant

nutrition and productivity (Marschner 2005; Klaus

et al. 2011a; Kleinebecker et al. 2011). All dried

samples were ground to pass a 0.5 mm screen. We

measured the concentrations of the main plant nutri-

ents: Carbon (C), Nitrogen (N), Phosphorus (P),

Potassium (K), Magnesium (Mg) and Calcium (Ca)

with near infrared reflectance spectroscopy (NIRS)

(Foley et al. 1998; Klaus et al. 2011a; Kleinebecker

et al. 2011) using a spectra star 2,400 (Unity Scientific,

Columbia, MD, USA). For each sample we recorded

the reflectance at intervals of 1 nm from 1,250 to

2,350 nm. The full reflectance spectrum was derived

from 24 measurements of each sample scan, which

were averaged to generate a single spectrum. Calibra-

tion models for the measurement of nutrient concen-

trations by Klaus et al. 2011a and Kleinebecker et al.

(2011) based on broad spectrum of temperate Euro-

pean grassland vegetation were validated and further

improved with samples from our study. Parameters of

model quality are given in the online resource,

Table 2. Klaus et al. (2012) and references therein

provide further details concerning NIRS measure-

ments and calibration.

Statistical analysis

We calculated species richness as species number/m2.

The relationship between species richness as depen-

dent variable and habitat characteristics as indepen-

dent variables were analysed using general additive

models (GAM). Since such relations are often non-

linear, GAM appeared to be appropriate since it

provides the possibility to add local smooth factors

including smoothing splines to the explanatory vari-

ables in order to gain a better model fit (Venables and

Dichmont 2004).

The error distributions of response variables were

negative binomial for species richness with a log-link

function. A negative binomial model was applied

because over-dispersion was apparent in a Poisson

model fit to the species richness data—a common

approach for analysis of count data (Gotelli and

Ellison 2004).

Univariate models were first built for all predictors

and dependent variables. GAMs with cubic spline

smoother values of k = 3 and k = 4 were specified,

whereby k describes the upper limit of degrees of

freedom for the cubic splines (Wood 2004). For

further modelling the smoother value with the lower

associated Akaike information criterion (AIC) cor-

rected for small sample size (AICc) was selected for

further modelling. If AICc did not differ among

smoother values, the lower value (3) was selected to

prevent over-fitting. For categorical predictors, a

smoother value of 1 was chosen. Specification of

actually needed degrees of freedom and estimation of

smoothing parameters was done using generalized

cross validation (Wood 2004). Smoother values of the

explanatory variables are given in Table 3, online

resource. Univariate models were checked visually by

plotting the univariate relationships with confidence

intervals. Those variables that were significant pre-

dictors of species richness (p \ 0.05) were included in

the multivariate GAMs of the respective dependent

variable.

Three groups of multivariate candidate models

were built to investigate (1) management and

Plant Ecol

123

community effects as well as their interaction; (2)

productivity, characterised by the amount of biomass

and litter; and (3) nutrient concentrations as well as

nutrient ratios in aboveground biomass.

As there was little prior information to build

meaningful candidate models for nutrients, multivar-

iate GAMs were built containing all possible combi-

nations of nutrients. Highly correlated variables

(Spearman’s r C 0.7) were tested in separate models.

Because the study sites were expected to differ slightly

in their local conditions, site was included as a fixed

factor in every model.

The informative quality of candidate models of the

same dependent variable (model set) was compared by

ranking according to their AICc, following an infor-

mation theoretical approach to model selection (Bur-

ham and Anderson 2002). The differences (DAICc)

among models were calculated to determine model

quality relative to the model with the lowest AICc

(best model). Evaluation of model quality and plau-

sibility with respect to the best model was conducted

following the DAICc-categorization of Burham and

Anderson (2002): candidate models have substantial

support (evidence) if DAIC \ 0–2, those in which

DAIC \ 4–7 have considerably less support, and

models having DAIC [ 10 have almost no support,

thus being very unlikely. The relative likelihood of the

models was calculated using Akaike weights (wi) in

order to compare each model to the best model in the

set. Differences among managed and unmanaged plots

were assessed using Mann–Whitney tests (two-sided).

Management effects were tested for the following

parameters: species richness, aboveground biomass

and litter mass, nutrient concentration in aboveground

biomass and growth form composition.

Statistical analyses were carried out using R

2.14.11 (R Development Core Team, 2011). The

Package hmgcvi and hMuMIni were used to perform

the general additive modelling and comparisons based

on calculation of AICc, DAICc and Akaike weights.

Results

Management effects on aboveground biomass,

litter and nutrients

In both communities the amount of litter was signif-

icantly lower in managed plots (p \ 0.001) (Table 1).

Overall mean litter reduction was 218 ± 52 g/m2 with

community means in the sedge meadow decreasing

from 358 to 121 g/m2 and in the tall forb meadow from

541 to 343 g/m2 (Fig. 2; Table 1). Management

resulted in no significant change in standing above-

ground biomass.

The amount of nutrients stored in aboveground

biomass declined due to meadow management, which

was more pronounced in the tall forb than in the sedge

meadow. In the latter, only Mg in biomass exhibited a

significant difference between the unmown and mown

plots (Table 1). In the tall forb meadow, all nutrient

contents were lower in the managed plots, but only the

differences in N and Mg were significant. In addition,

the C:N-ratio was significantly larger in managed plots

of the tall forb community with values of 25 and 30,

respectively (Fig. 2; Table 1).

Relations between management, productivity,

nutrients and biodiversity measures

The interaction between management and community

type exhibited significant effects on species richness

(GAM; p \ 0.05) (Table 2); management resulted in

higher richness in tall forb, but not in sedge meadow

(Fig. 2; Table 1). According to the post hoc Mann–

Whitney test, only the tall forb meadow community

responded significantly to management with greater

species richness; the managed forb meadow commu-

nities contained an average of 11 ± 2 species per m2,

whereas unmanaged communities averaged 3 ± 0.4

species per m2 (Table 1).

Litter was a highly significant predictor of species

richness (p \ 0.01) (Table 2). The species richness–

litter relationship was somewhat hump backed—

richness peaked between 200 and 300 g litter per m2

and decreased with increasing litter values (Fig. 3).

According to GAM, aboveground biomass was not a

significant predictor of species richness.

N concentration and C:N-ratio in aboveground

biomass were highly significant predictors of species

richness in two separate models (N concentration

p \ 0.001; C:N-ratio p \ 0.01) (Table 2). The two

models can be considered equal in informative quality

since the DAICc was in both cases\0.5. An increase

in N was associated with a decrease in species richness

(Fig. 3), whereas species richness and C:N-ratio

exhibited a positive relationship (Fig. 3). Other nutri-

ents were excluded from the set of candidate models

Plant Ecol

123

beforehand since they exhibited no significant effects

in univariate models.

Relative importance of management, productivity

and nutrients on species richness

Comparison of models across all groups of predictor

variables (management, productivity, nutrients)

revealed a single best model group (DAICc \ 2) for

species richness, that including management and

community type (Table 2). The model including

biomass and litter per m2 (Table 2) indicated some

but considerably less support than the best model

(DAICc 4–7). With a DAICc of about 8, models

relating nutrients to species richness generated weak

support. Productivity measures (biomass and litter per

m2) explained species richness better than nutrient

content; Akaike weights were about twice as high for

the productivity model (Table 2). The ratio of the

weight of the best to the second best model was about

25, suggesting that, compared to the effect of manage-

ment, productivity and nutrients could explain only a

limited proportion of the variation in species richness.

Management effects on growth form composition

The effect of management on growth form composi-

tion differed among the two community types;

unmanaged sedge meadows were dominated by

sedges and grasses, covering on average 57 and

30 %, respectively. Management affected both groups

significantly, with grasses being strongly reduced,

occupying only 10 %, and sedges increasing to 75 %

(Fig. 4; Table 1). Tall forbs and small herbs covered

less than 3 % each and showed significant difference

under management (Table 1). More detailed inspec-

tion of species changes showed that despite the overall

increase in sedge cover, management resulted in

partial replacement of Carex acuta and Carex elata—

the most common species in unmown plots—by Carex

disticha and Carex cespitosa.

In the tall forb meadows, unmanaged plots were

dominated by tall forbs with their cover achieving

more than 75 %. The canopy consisted mainly of

Filipendula ulmaria, which had a minimum coverage

of 65 %. The only other tall forb recorded was Urtica

dioica, which occurred in only two managed plots,

with coverage not exceeding 6 %. Other growth forms

exhibited low coverage, led by small herbs covering

on average 2.9 % (Fig. 4; Table 1). Management did

not significantly suppress the dominance of F. ulma-

ria, but nonetheless resulted in a significant fivefold

increase in small herbs and sedges up to 10 and 4 % of

cover, respectively. Grasses were also facilitated by

management, with 12 % of cover recorded on average

in mown compared to only 3 % in unmown plots,

Table 1 Summary of results describing the effects of management at community level (means with standard error (SE))

Factor Sedge meadow Tall forb meadow

Unmown SE (±) Mown SE (±) p value Unmown SE (±) Mown SE (±) p value

Litter (g/m2) 358.38 49.76 121.13 22.28 0.001 540.86 35.40 343.10 56.47 0.010

Biomass (g/m2) 1,121.70 84.85 940.02 91.16 0.198 1,278.15 151.93 1,034.07 81.48 0.160

Species richness (1/m2) 4.33 0.62 5.50 0.80 0.280 3.42 0.38 10.67 2.31 0.002

Nitrogen (%) 1.55 0.08 1.47 0.08 0.643 1.90 0.10 1.59 0.07 0.017

Phosphorus (%) 0.20 0.01 0.20 0.01 0.859 0.25 0.01 0.24 0.01 0.930

Potassium (%) 1.01 0.04 1.09 0.09 0.583 1.31 0.21 1.25 0.11 0.623

Magnesium (%) 0.24 0.01 0.27 0.01 0.042 0.35 0.01 0.32 0.01 0.017

Calcium (%) 0.61 0.09 0.65 0.06 0.099 1.24 0.04 1.09 0.08 0.156

C:N ratio 29.43 1.53 31.68 1.84 0.590 25.11 1.26 29.54 1.29 0.017

N:P ratio 7.69 0.45 7.30 0.48 0.340 7.75 0.50 6.68 0.38 0.101

Tall forbs (%) 1.67 0.91 1.50 1.23 0.948 78.33 7.99 77.38 6.32 0.816

Small herbs (%) 2.83 1.32 1.88 1.11 0.400 2.08 0.68 9.71 2.48 0.006

Sedges (%) 54.63 7.69 75.75 5.11 0.043 0.88 0.83 4.00 1.94 0.036

Grasses (%) 30.04 7.10 9.42 3.85 0.009 2.88 2.47 12.46 4.84 0.095

p values are from Mann–Whitney tests. Bold numbers significance (p \ 0.05)

Plant Ecol

123

although this difference was not statistically signifi-

cant (Table 1).

Discussion

Management effects on nutrients and productivity

Management resulted in a general decrease in biomass.

The mean decrease was fairly small and not

statistically significant (Fig. 2), suggesting that overall

nutrient depletion over 12 years was too weak to

reduce productivity severely (Marrs 1993). Manage-

ment specifically reduced N and Mg in the above-

ground biomass of the tall forb community (Fig. 2).

Successful N-removal through mowing and hay

removal has been recorded in several studies concern-

ing nutrient impoverishment in different grassland

ecosystems (Bakker et al. 2002; Smits et al. 2008;

Oelmann et al. 2009). Management has been shown to

Fig. 2 The effect of management on aboveground biomass and

litter mass (g/m2), concentrations of N and C:N ratio in

aboveground biomass and species richness per m2 tested using

Mann–Whitney tests separately for the sedge and tall forb

meadow (white fill unmown, grey fill mown). Stars indicate

significant differences among management regimes (* p \ 0.05;

** p \ 0.01)

Plant Ecol

123

reduce Mg as well (Oelmann et al. 2009). Other

nutrients did not differ among managed and abandoned

communities (Table 1). Due to the relatively low land

use intensity, abiotic conditions in these Estonian

floodplain meadows remain largely unchanged by

management (Sammul et al. 2000; Metsoja et al. 2012).

Nutrient contents in the soil of flooded meadows are

persistently rather high, a consequence of nutrient

input via regular inundation (Klaus et al. 2011b). This

effect can likewise explain the lack of nutrient

reduction in aboveground biomass in the managed

sedge meadow. This community type is situated in old

riverbeds that are more frequently and longer inun-

dated than the tall forb meadow resulting in higher

rates of nutrient input and favourable mineralisation

conditions in periods of dry weather. Limited nutrient

Fig. 3 Plots of significant

univariate GAMs relating

concentration of N (%;

p \ 0.001), C:N ratio

(p \ 0.01) and litter (g/m2;

p \ 0.01) in aboveground

biomass to species richness

per m2. Smoother values

(k) = 3 for N (%) and

(k) = 4 for C:N-ratio and

litter (g/m2) were used.

Dashed lines represent 95 %

confidence intervals

Table 2 Best multivariate GAMs modelling species richness per m2 separately in relation to the following thematic groups of

independent variables: (i) productivity, (ii) management and (iii) nutrients

Model group Intercept Independent variables (%) Variance explained AICc DAICc Akaike weight

Biomass Litter

Productivity 0.620 - 2 43.70 248.31 6.46 0.037

Management Man:com

Management 0.403 -0.320 0.624 57.70 241.85 0.00 0.927

N C:N

Nutrients 0.939 2 35.60 249.64 8.33 0.019

0.925 1 35.30 249.77 8.46 0.018

For variables to which a smoother value was applied, the direction of the relationship is coded as follows:? positive;- negative; 0hump backed. Numeric parameter estimates are given for variables to which no smooth factor was necessary. Estimates/signs in bold

type significant effects. man:com = interaction of management regime and community type

Plant Ecol

123

reduction under inundation regimes has also been

observed in other studies (Bakker 1989; Hardtle et al.

2006, Klaus et al. 2011a), but removal of biomass still

remains useful by preventing further nutrient accumu-

lation (Olde Venterink et al. 2001).

Link between species richness and productivity

As expected, management resulted in a decrease in the

amount of litter, with hay removal presumably the

primary cause. Although absolute reduction of litter

was similar to that of biomass, the relative reduction of

litter was considerably higher (Fig. 2).The overall

effect of mowing and hay removal on species richness

was positive in the tall forb meadow (Fig. 2). Such an

effect is in accordance with many published studies

(e.g. Collins et al. 1998; Leps 1999; van Diggelen et al.

2006; Poptcheva et al. 2009). The tall forb meadow is

highly productive, with more than 1,100 g/m biomass.

In such highly productive communities, competition

for light and seedling recruitment have been found to

be the most important factor determining species

richness (e.g. Leps 1999; Eek and Zobel 2001; Hautier

et al. 2009). Mowing has a balancing effect on

competition for light (Kull and Zobel 1991), increas-

ing the amount of light reaching shorter plants and the

soil surface (Jutila and Grace 2002), thus promoting

seedling germination (Leps 1999).

Our analysis demonstrates that litter mass is a

relatively more important determinant for species

richness than aboveground biomass (Table 2), which

is consistent with the strong management effects on litter

reduction mentioned above. The amount of litter usually

increases with increasing productivity (Foster and Gross

1998). Vegetation in fertile habitats is rich in rapidly-

growing herbs and grasses that shed a large amount of

their aboveground biomass every autumn (Eskelinen

et al. 2009). Live biomass turnover is promoted by high

nutrient availability, which results in accelerated litter

rather than biomass accumulation (Eskelinen et al.

2012). Finally, excessive amounts of litter lead to

suppression of seedling emergence (Twolan-Strutt and

Keddy 1996; Clark and Tilman 2010). For communities

suffering from drought, litter may exert a positive

impact on seedlings (Holmgren et al. 1997; Eckstein and

Donath 2005; Loydi et al. 2013). In the present study a

threshold value for litter beyond which negative effects

on species richness outweigh those of facilitation

seemed to be about 300 g/m2 (Fig. 3). This pattern is

concordant with recent results from a mesocosm

experiment conducted by Donath and Eckstein (2010).

The value of 300 g/m2 represents a moderate amount of

litter at the studied sites. That management reduced the

amount of litter in almost all plots to \400 g/m2

suggests that hay removal following mowing is crucial

for maintaining suitable microsites for seed germination

in these floodplain meadows.

Soil nutrient availability is another factor driving

productivity and species composition as increased

productivity is closely linked to competitive exclusion

and decreasing niche availability for shade intolerant

species which in turn leads ultimately to lower species

richness (Leps 1999; Hautier et al. 2009). The N

content in the aboveground biomass, a proxy of overall

nutrient conditions, and C:N ratio were important

determinants of species richness (Table 2). These

Fig. 4 The effect of management on the cover of different

growth forms in the sedge and tall forb meadow. Boxplot-fill

signifies management regime (white fill unmown, grey fill

mown). Stars indicate significant differences among manage-

ment regimes separately within the sedge and tall forb

community (Mann–Whitney Test; * p \ 0.05; ** p \ 0.01)

Plant Ecol

123

findings agree with the overview by Olde Venterink

et al. (2001). The explanatory power of N content was,

however, less than that of aboveground biomass and of

litter mass (Table 2).

Management effects on growth form composition

Restoration projects in flooded meadows aim to

establish vital communities that maintain typical

grassland species, including short plants (Bissels

et al. 2004). Mowing or grazing is a prerequisite for

maintaining such species as it reduces the asymmetric

light competition and thus prevents their competitive

exclusion (Grime et al. 1987). Analysis of the growth

form composition of floodplain meadow communities

supported this concept. Management resulted in

significantly higher cover of small herbs (Fig. 4).

Consequently, management leads to a shift not only in

species composition, but also in growth form compo-

sition. Analogous changes due to management are

evident in both community types, although the differ-

ences in growth form composition were more pro-

nounced in tall forb communities (Fig. 4). This

coincides with the results of a previous study by

Metsoja et al. (2012), who suggested that the weaker

management effects in the sedge meadow may reflect

a lower intensity of management, since wet summers

inhibit mowing in sedge communities.

Conclusion

Management by mowing and hay removal was a

successful means to enhance light availability, result-

ing in an increase in overall species richness and a

change in growth form composition to a greater

abundance of short growing forbs. Litter mass was the

strongest determinant of species richness and almost

all management effects were connected to litter

reduction. Therefore, regular hay removal should be

included in conservation practise.

Aboveground biomass and nutrient status—mainly

N—are less affected by management within a time-

frame of 10 years and consequently of secondary

importance for the short-term enhancement of species-

richness. Overall, our results clearly show that plant

species richness in highly productive communities,

such as flooded meadows, is determined primarily by

light and litter rather than nutrient availability.

Acknowledgments This study was supported by grants

SF0180098s08, ESF 9157 and by the European Union through

the European Regional Development Fund (Center of

Excellence FIBIR). Further this work was supported by travel

grants for Lena Neuenkamp provided by the German Academic

Exchange Service and the University of Munster. Robert Szava-

Kovats kindly commented on the first draft of the manuscript.

References

Bakker JP (1989) Nature management by grazing and cutting.

Kluwer, Dordrecht

Bakker JP, Elzinga JA, de Vries Y (2002) Effects of a long-term

cutting in a grassland system: perspectives for restoration

of plant communities on nutrient-poor soils. Appl Veg Sci

5:107–120

Berendse F, Oomes MJM, Altena HJ, Elberse WT (1992)

Experiments on the restoration of species-rich meadows in

the Netherlands. Biol Conserv 62:59–65

Bissels S, Holzel N, Donath TW, Otte A (2004) Evaluation of

restoration success in alluvial grasslands under contrasting

flooding regimes. Biol Conserv 18:641–650

Bobbink R, Hornung M, Roelofs JGM (1998) The effects of air-

borne nitrogen pollutants on species diversity in natural

and semi-natural European vegetation. J Ecol 86:717–738

Burham KP, Anderson D (2002) Model Selection and Multi-

model Inference. A Practical Information Theoretical

Approach, 2nd edn. Springer Science?Business Media,

Inc., New York

Ceulemans T, Mercks R, Hens M, Honnay O (2013) Plant

species loss from European semi-natural grasslands fol-

lowing nutrient enrichment—is it nitrogen or is it phos-

phorus? Glob Ecol Biogeogr 22:73–82

Clark CM, Tilman D (2010) Recovery of plant diversity fol-

lowing N cessation: effects of recruitment, litter and ele-

vated N cycling. Ecology 91:3620–3630

Collins SL, Knapp AK, Briggs JM, Blair JM, Steinauer EM

(1998) Modulation of diversity by grazing and mowing in

native tallgrass prairie. Science 280:745–747

Crawley MJ, Long CR (1995) Alternate bearing, predator sati-

ation and seedling recruitment in Quercus robur L. J Ecol

83:683–696

Donath TW, Eckstein RL (2010) Effects of bryophytes and grass

litter on seedling emergence vary by vertical seed position

and seed size. Plant Ecol 207:257–268

Donath TW, Eckstein RL (2012) Litter effects on seedling

establishment interact with seed position and earthworm

activity. Plant Biol 14:163–170

Eckstein RL, Donath TW (2005) Interactions between litter and

water availability affect seedling emergence in four

familial pairs of floodplain species. J Ecol 93:807–816

Eek LK, Zobel M (2001) Structure and diversity of a species-

rich grassland community, treated with additional illumi-

nation, fertilization and mowing. Ecogr 24:157–164

Elser JJ, Bracken MES, Cleland EE, Gruner DS, Harpole WS,

Hillebrand H, Ngai JT, Seabloom EW, Shurin JB, Smith JE

(2007) Global analysis on nitrogen and phosphorus limi-

tation of primary producers in freshwater, marine and ter-

restrial ecosystems. Ecol Lett 10:1135–1142

Plant Ecol

123

Eskelinen A, Stark S, Mannisto M (2009) Links between plant

community composition, soil organic matter quality and

microbial communities in contrasting tundra habitats. Oe-

cology 161:113–123

Eskelinen A, Harrison S, Tuomi M (2012) Plant traits mediate

consumer and nutrient control on plant community pro-

ductivity and diversity. Ecology 93:2705–2718

Facelli JM, Pickett STA (1991) Plant litter: light interception

and effects on an old field plant community. Ecology

72:1024–1031

Facelli JM (1994) Multiple indirect effects of plant litter affect

the establishment of woody seedlings in old fields. Ecology

75:1727–1735

Foley WJ, McIlwee A, Lawler I, Aragones L, Woolnough AP,

Berding N (1998) Ecological applications of near infrared

reflectance spectroscopy—a tool for rapid, cost-effective

prediction of the composition of plant and animal tissues and

aspects of animal performance. Oecology 116:293–305

Foster BL, Gross KL (1998) Species richness in a successional

grassland: effects of nitrogen enrichment and plant litter.

Ecology 79:2593–2602

Foster BL, Dickson TL, Murphy CA, Karel IL, Smith VH (2004)

Propagule pools mediate community assembly and diver-

sity—ecosystem regulation along a grassland productivity

gradient. J Ecol 92:435–449

Gotelli NJ, Ellison AM (2004) A primer of ecological statistics.

Sinauer Associates, Inc., Massachusetts

Grime JP (1979) Plant strategies and vegetation process. Wiley,

Chichester

Grime JP, Mackey JML, Hillier SH, Read DJ (1987) Floristic

diversity in model system using experimental microcosms.

Nature 328:420–422

Hardtle W, Redecker B, Assmann T, Meyer H (2006) Vegeta-

tion responses to environmental conditions in floodplain

grasslands: prerequisites for preserving plant species

diversity. Basic Appl Ecol 7:280–288

Hautier Y, Niklaus PA, Hector A (2009) Competition for light

causes plant biodiversity loss after eutrophication. Science

324:636–638

Holmgren M, Scheffer M, Huston MA (1997) The interplay of

facilitation and competition in plant communities. Ecology

78:1966–1975

Jansen A (2000) Hydrology and restoration of wet heathland and

fen meadow communities. PhD Thesis, University of

Groningen

Jensen K, Schrautzer J (1999) Consequences of abandonment

for a regional fen flora and mechanisms of successional

change. Appl Veg Sci 2:79–88

Jensen K, Gutekunst K (2003) Effects of litter on establishment

of grassland species: the role of seed size and successional

status. Basic Appl Ecol 4:579–587

Jutila HM, Grace JB (2002) Effects of disturbance on germi-

nation and seedling establishment in coastal prairie grass-

land: a test of the competitive release hypothesis. J Ecol

90:291–302

Klaus V, Kleinebecker T, Holzel N, Bluthgen N, Boch S, Muller

J, Socher SA, Prati D, Fischer M (2011a) Nutrient con-

centrations and fibre contents of plant community biomass

reflect species richness patterns along a broad range of

land-use intensities among agricultural grasslands. Per-

spect Plant Ecol Evol Syst 13(4):287–295

Klaus V, Sintermann J, Kleinebecker T, Holzel N (2011b)

Sedimentation-induced eutrophication in large river

floodplains—an obstacle to restoration? Biol Conserv

144:451–458

Klaus V, Kleinebecker T, Boch S, Muller J, Socher SA, Prati D,

Fischer M, Holzel N (2012) NIRS meets Ellenberg’s

indicator values: prediction of moisture and nitrogen val-

ues of agricultural grassland vegetation by means of near-

infrared spectral characteristics. Ecol Indic 14:82–86

Kleinebecker T, Weber H, Holzel N (2011) Effects of grazing on

seasonal variation of aboveground biomass quality in cal-

careous grasslands. Plant Ecol 212:1563–1576

Krall HK, Pork K, Aug H, Puss O, Rooma I, Teras T (1980) Eesti

NSV looduslike rohumaade tuubid ja tahtsamad taimek-

ooslused. Eesti NSV Pollumajandusministeriumi Infor-

matiooni ja Juurutamise Valitsus, Tallinn

Kukk T (1999) Eesti taimestik. Teaduste Akadeemia kirjastus,

Tallinn

Kull K, Zobel M (1991) High species richness in an Estonian

wooded meadow. J Veg Sci 2:715–719

Lamb EG (2008) Direct and indirect control of grassland com-

munity structure by litter, resources, and biomass. Ecology

89:216–225

Leps J (1999) Nutrients status, disturbance and competition: an

experimental test of relationships in a wet meadow. J Veg

Sci 10:219–230

Loydi A, Eckstein RL, Otte A, Donath TW (2013) Effect of litter

on seedling establishment in natural and semi-natural

grasslands: a meta-analysis. J Ecol 101:454–464

Marschner H (2005) Mineral nutrition of higher plants. Aca-

demic Press, Amsterdam

Marrs RH (1993) Soil fertility and nature conservation in Eur-

ope: theoretical considerations and practical management

solutions. Adv Ecol Res 24:241–300

Metsoja JA, Neuenkamp L, Pihu S, Vellak K, Kalwij JM, Zobel

M (2012) Restoration of flooded meadows in Estonia:

vegetation changes and indicators. Appl Veg Sci 15(2):

231–244

Oelmann Y, Broll G, Holzel N, Kleinebecker T, Vogel A,

Schwartze P (2009) Nutrient impoverishment and limita-

tion of productivity after 20 years of conservation man-

agement in wet grasslands of north-west Germany. Biol

Conserv 142:2941–2948

Olde Venterink H, Van der Vliet RE, Wassen MJ (2001)

Nutrient limitation along a productivity gradient in wet

meadows. Plant Soil 234:171–179

Olde Venterink H, Wassen MJ, Verkroost AWM, De Ruiter PC

(2003) Species richness-productivity patterns differ

between N, P and K limited wetlands. Ecology 84:

2191–2199

Patrick LB, Fraser LH, Kershner MW (2008) Large-scale

manipulation of plant litter and fertilizer in a managed

successional temperate grassland. Plant Ecol 197:183–195

Poptcheva K, Schwartze P, Vogel A, Kleinebecker T, Holzel N

(2009) Changes in wet meadow vegetation after 20 years

of different management in a field experiment (North-West

Germany). Agr Ecosyst Environ 134:108–114

Robson TM, Baptist F, Clement JC, Lavorel S (2010) Land use

in subalpine grasslands affects nitrogen cycling via chan-

ges in plant community and soil microbial uptake dynam-

ics. J Ecol 98:62–73

Plant Ecol

123

Sammul M, Kull K, Oksanen L (2000) Competition intensity

and its importance: results of field experiments with An-thoxanthum odoratum. Oecology 125(1):18–25

Socher S, Prati D, Muller J, Klaus VH, Holzel N, Fischer M

(2012) Direct and productivity-mediated indirect effects of

fertilization, mowing and grazing intensities on grassland

plant species richness. J Ecol 100:1391–1399

Smits NAC, Willems JH, Bobbink R (2008) Long-term after-

effects of fertilisation on the restoration of calcarous

grasslands. Appl Veg Sci 11:279–292

Stevens CJ, Dise NB, Mountford JO, Gowing DJ (2004) Impact

of nitrogen deposition on the species richness of grass-

lands. Science 303:1876–1879

Tilman D (1997) Community invasibility, recruitment limita-

tion and grassland biodiversity. Ecology 78:81–92

Tilman D, Reich PB, Isbell F (2012) Biodiversity impacts

ecosystem productivity as much as resources, disturbance,

or herbivory. Proc Natl Acad Sci USA 109:10394–10397

Twolan-Strutt L, Keddy PA (1996) Above-and belowground

competition intensity in two contrasting wetland plant

communities. Ecology 77:259–270

van Diggelen R, Middelton B, Bakker JP, Grootjans AP, Wassen

M (2006) Fens and floodplains of the temperate zone:

present status, threats, conservation and restoration. Appl

Veg Sci 9:157–162

Venables WN, Dichmont CM (2004) GLMs, GAMs and

GLMMs: an overview of theory for applications in fisheries

research. Fish Res 70(2–3):319–337

Verhoeven JTA, Koerselman W, Meuleman AFM (1996)

Nitrogen- or phosphorus-limited growth in herbaceous, wet

vegetation: relations with atmospheric inputs and man-

agement regimes. Trends Ecol Evol 11:494–497

Wahlman H, Milberg P (2002) Management of semi-natural

grassland vegetation: evaluation of a long-term experiment

in Southern Sweden. Ann Bot Fenn 39:159–166

Wassen MJ, Venterink HO, Lapshina ED, Tanneberger F (2005)

Endagered plant species persist munder phosphorus limi-

tation. Nature 437:547–550

Weltzin JF, Keller JK, Bridgham SD, Pastor J, Allen PB, Chen J

(2005) Litter controls plant community composition in a

northern fen. Oikos 110:537–546

Wood SN (2004) Stable and efficient multiple smoothing

parameter estimation for generalized additive models.

J Am Stat Assoc 99(467):673–686

Xiong S, Nilsson C (1999) The effects of plant litter: a meta-

analysis. J Ecol 87(6):984–994

Xiong S, Johansson ME, Hughes FMR, Hayes A, Richards KS,

Nilsson C (2003) Interactive effects of soil moisture, veg-

etation canopy and seed addition on plant diversity in a

wetland community. J Ecol 91(6):976–986

Plant Ecol

123