Biodiversity, vegetation gradients and key biogeochemical processes in the heathland landscape

Biological Conservation 142 (2009) 2191–2201

Contents lists available at ScienceDirect

Biological Conservation journal homepage: www.elsevier.com/locate/biocon

Biodiversity, vegetation gradients and key biogeochemical processes in the heathland landscape Maaike C.C. De Graaf a,*, Roland Bobbink b,c, Nina A.C. Smits c,d, Rudy Van Diggelen e,f, Jan. G.M. Roelofs a a

Department of Aquatic Ecology and Environmental Biology, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, NL-6525 ED, The Netherlands B-ware Research Centre, Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands c Landscape Ecology, Institute of Environmental Biology, Utrecht University, P.O. Box 800.84, Utrecht, NL-3508 TB, The Netherlands d Centre for Ecosystem Studies, Alterra, P.O. Box 47, 6700AA, Wageningen, The Netherlands e Ecosystem Management Research Group, Department of Biology, University of Antwerp, Universiteitsplein 1c, B2610 Antwerpen, Belgium f Faculty of Spatial Sciences, University of Groningen, P.O. Box 800, 9700AV Groningen, The Netherlands b

a r t i c l e

i n f o

Article history: Received 5 November 2008 Received in revised form 8 April 2009 Accepted 22 April 2009 Available online 26 May 2009 Keywords: Acidification Eutrophication Reduced nitrogen Restoration EUNIS habitat type Data analysis

a b s t r a c t The northwest European heathland landscape with its characteristic communities of nutrient-poor and acidic soils has a high nature value, because of its locally high biodiversity and the distinct site conditions. In order to conserve and restore the heathlands, numerous rehabilitation projects have been performed, although with varying success. This is partly due to the fact that the key biogeochemical processes distinguishing the various vegetation types within the heathlands are not known in detail. Therefore, we performed a statistical survey on the main communities and their soil characteristics. In addition, we analyzed the data for key factors determining biodiversity in the heathland landscape. Data from previous studies and surveys was used to compile a dataset of 267 vegetation relevés (classified as EUNIS habitat types) with extensive soil measurements (22 parameters). A canonical discriminant analysis revealed that soil acidity explained most of the differences between the habitat types, while soil moisture content and soil fertility were less important. Acidity-related factors as Al3+, Al/Caratio and pH were also strongly correlated to plant diversity in the majority of the habitat types, respectively, the species-rich Nardus grasslands, the Rhynchosporion communities and the species-rich Molinia meadows. In the dry heaths and over the total heathland landscape, plant diversity was negatively correlated with soil NHþ 4 -concentrations. Only in wet heath, nutrient availability, in this case P, was the primary factor in explaining plant diversity. This study presents ranges for all major soil parameters for the studied well-developed heathland habitat types, thereby providing clear guidelines for conservation and restoration. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction The north-western European heathland landscape consists of wet and dry heaths, acidic grasslands, fen meadows and inland sand dunes. Although the dwarf shrub-dominated heaths comprise the majority of the landscape, plant diversity is especially high in the acidic Nardus grasslands and fen meadows and in the transitions between these communities and both heath types. In this paper, we use ‘heathland’ to refer to the total heathland landscape. The dwarf shrub-dominated vegetations are referred to as ‘wet heath’ or ‘dry heath’. The heathlands develop on (extremely) nutrient poor, sandy or loamy soils, which are acid (pH < 4.5) to weakly acidic (pH be-

* Corresponding author. Tel.: +31 243652401; fax: +31 243652409. E-mail addresses: [email protected] (M.C.C. De Graaf), r.bobbink@ b-ware.eu (R. Bobbink), [email protected] (N.A.C. Smits), [email protected] (R. Van Diggelen), [email protected] (Jan. G.M. Roelofs). 0006-3207/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2009.04.020

tween 4.5 and 6). Various hydrological regimes (infiltration, inundation and upward seepage) result in a wide range of soil moisture conditions, varying from extremely dry heaths and inland dunes to wet heaths and meadows. In places where decomposition and mineralization are hampered by acidic or anaerobic conditions, the topsoil can be peaty. The inland northwest European heathland landscape has developed under former agricultural use (Webb, 1998; Karg, 2008) and can only be maintained by some kind of management, e.g. mowing, extensive grazing, burning or sod cutting. However, land use has been changed tremendously during the past century, resulting in a drastic decline in heathland area. Moreover, a large part of the remainder of the heathlands is affected by changes in hydrology, increased atmospheric deposition of nitrogen (N) and sulphur (S) and habitat fragmentation. This has caused also a qualitative degradation of the remaining heaths and grasslands, often leading to a loss in biodiversity (Roelofs et al., 1996; Bobbink et al., 1998; Webb, 1998; Piessens et al., 2004).

2192

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

The importance of conservation is recognised in the European Union Habitat Directive (Directive 92/43/EEC), which lists many of the heathland ecosystems amongst the protected habitat types. The protection of species-rich acidic grasslands is even given priority. The quantitative degradation of the heathlands can be stopped by designating areas as nature reserves and by the reclamation of former agricultural fields, but in order to stop its qualitative degradation, additional management is often required. Despite the major efforts that are put into the restoration, success is often limited and not all species re-establish, resulting in partial recovery of communities (De Graaf et al., 1998a; Verhagen et al., 2001). Two major causes have been identified for the limited success: (1) the inability of species to access the restored sites and (2) the fact that even after restoration soil conditions and hydrology do not meet the requirements of the characteristic species of the heathland communities. Re-establishment of target species often fails, as many species of the landscape have a transient soil seed bank (Thompson et al., 1997; Bekker et al., 1998; Matus et al., 2003; Piessens et al., 2004). Hence, re-establishment depends on dispersal, but this process is hampered by habitat fragmentation and the restricted dispersal capacity of many species (Piessens et al., 2004; Soons et al., 2005). Success rates increase when restoration creates the appropriate soil conditions (Roelofs et al., 1996; De Graaf et al., 1998a; Lamers et al., 2002). And so, in order to set clear targets for restoration, it is important to have a clear picture of the key biogeochemical conditions under which the various heathland vegetation types may develop and persist. However, information on the exact abiotic conditions that determine the development and maintenance of heathland communities is scattered and unequivocal. Some information is obtained from studies on habitat characteristics of rare species (Houdijk et al., 1993; Kleijn et al., 2008), some from gradient studies on a specific site (Balme, 1953; Blackstock et al., 1998; Roem and Berendse, 2000; Roem et al., 2002), from studies on peaty soils (Hayati and Proctor, 1990; Wheeler and Proctor, 2000) or focus on a single aspect (generally nutrient availability; Schaffers, 2002) or only one part of a gradient (Roelofs et al., 1996; Janssens et al., 1998; De Graaf, 2000). Additional information from ecological and ecophysiological experiments has added to the understanding of deterioration processes in the heathlands (Van Dobben, 1991; De Graaf et al., 1997, 1998b; Dorland et al., 2003; Van den Berg et al., 2005, 2008). However, these experiments are performed under standardized conditions with a limited number of species, and it is therefore difficult to generalize the results. Moreover, the relative importance of key processes in various parts of the heathland landscape is not evident. We therefore performed a statistical survey on the distribution of the plant communities across the whole heathland landscape, both wet and dry, ranging from pioneer communities on inland dunes and on sod cut areas or moorland pool banks, via dry and wet heath, including acidic grasslands both on dry and moist soils. We did so by analysing original vegetation relevés (vegetation plots) and top soil chemical data from a range of studies and surveys from Pleistocene, sandy areas. In this paper, we address the following topics:  First we provide an overview of the abiotic conditions prevailing in different heathland communities on sandy soils and determine the key factors in distinguishing between habitat types.  Secondly, we explore the relationship between edaphic factors and the number of species, both common and endangered, per habitat type in order to get a better understanding of drivers of biodiversity.  Thirdly, we determine processes that are responsible for the decline of wet and dry dwarf shrub-dominated communities, by comparing degraded and well-developed heaths.

In order to ensure the usefulness of the study for restoration purposes, we have chosen to cluster the original vegetation data into EUNIS habitat types of the European Union Habitat Directive, as we expect that many restoration projects in the near future will aim to restore on this level. By giving a clear insight in both key processes in the heathland landscape and the ranges of a number of top soil parameters under which the habitat types occur, the abiotic targets for restoration will become clear and success rates are likely to increase.

2. Materials and methods 2.1. The dataset We compiled a dataset from previous studies (Houdijk et al., 1993; De Graaf et al., 1998a and several unpublished studies) of more than 1300 vegetation relevés with measurements on top soil (0–10 cm) chemistry. Data were collected in the period 1980–2006. Most samples originate from The Netherlands; some are taken from lowland heathlands in Belgium or Germany, close to the Dutch border. Average minimum temperature in the regions of the sample sites varied from 4.8 to 6 °C, maximum from 13 to 14 °C and mean annual precipitation of 740–775 mm (Royal Netherlands Meteorological Institute). The top soil layer consists of sand or peat, apart from some of the Nardus grasslands which occurred on a loess top soil. Detailed information on the plots is provided in Appendix B. From these relevés, we selected the data relevant for the heathland landscape. Therefore, we started with the selection of eight relevant habitat types for the northwest European heathland landscape (Table 1). In order to characterize the relevés as habitat types, the relevés were first classified according to Dutch vegetation types using ASSOCIA program (Van Tongeren et al., 2008), which has been developed to identify vegetation relevés and is performed within TURBOVEG for Windows 2.68 (Hennekens and Schaminée, 2001). All identified relevés were checked manually and reidentified when necessary, as ASSOCIA classifies only about 80% of the relevés correctly, e.g. to the same class as an expert (Van Tongeren et al., 2008). The classified relevés were compared with those in the database underlying the Dutch classification system. Miss-classifications occurred especially in degraded heaths. Degraded heaths are identified as wet or dry heath vegetations in which the original dwarf shrub-dominated vegetation had changed into grass heath and/or of which a large proportion of the characteristic species had disappeared. Relevés that could not be classified were excluded from further analyses. Next, the identified relevés were classified according to habitat types (conform the detailed Dutch interpretation of the EUNIS habitat types by Janssen and Schaminée, 2003). As the ‘Dry sand heaths with Calluna and Genista’ (2310) and the ‘Dry sand heaths with Calluna and Empetrum nigrum’ (2320) make up part of the ‘European dry heaths’ (4030) and it is not always possible to separate the different dry heath vegetation types based on floristic composition, we combined the habitat types 2310, 2320 and 4030 into one category: dry heath. A synthetic table showing the species composition of the distinguished habitat types is given in Appendix A. Only data of well-developed plant communities were used in order to determine key processes in the heathland landscape. In addition, we used the selected degraded stands to assess the causes for their deterioration of the wet and dry heaths. In order to avoid pseudo replication, we did not incorporate more than two relevés classified as the same vegetation type and occurring on the same soil type of one specific site. The relevés were chosen at random. At the end of the selection procedure, the dataset for further analysis consisted of 267 relevés (Table 1).

2193

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201 Table 1 Selected Natura 2000 habitat types: number of samples and number of sites included in this analysis. NATURA 2000 habitat name

Alliancea

NATURA 2000 habitat type code

Referred to as

Number of samples

Number of areas

Dry sand heaths with Calluna and Genista

Calluno-Genistion pilosae RG Cytisus scoparius-[CallunoUlicetea/Nardetea]

2310

Dry heath

51

28

Dry sand heaths with Calluna and Empetrum nigrum

Vaccinio-Callunetum Genisto anglicae-Callunetum lophozietosum ventricosae

2320

Dry heath

European dry heaths

Calluno-Genistion pilosae RG Cytisus scoparius-[CallunoUlicetea/Nardetea]

4030

Dry heath

Degraded dry heath

12

7

Wet heath

26

18

Degraded wet heath

15

9

Northern Atlantic wet heaths with Erica tetralix

Ericetum tetralicis Sphagno palustris-Ericetum RG Myrica gale-[OxycoccoSphagnetea]

4010

Inland dunes with open Corynephorus and Agrostis grasslands

Corynephorion-canescentis Dunes without vegetation

2330

Inland dunes

9

6

Depressions on peat substrates of the Rhynchosporion

Rhynchosporion albae Lycopodio-Rhynchosporetum

7150

Rhynchosporion

34

24

Species-rich Nardus grasslands, on silicious substrates in mountain areas (and submountain areas in continental Europe)*

Nardo-Galion saxatilis

6230

Species-rich Nardus grasslands

94

60

Molinia meadows on calcareous, peaty or clayey-silt-laden soils (Molinion caeruleae)

Cirsio dissecti-Mollinietum

6410

Species-rich Molinia meadows

26

11

a *

Nomenclature of syntaxa follows Schaminée et al. (1995, 1996). Priority habitat type.

The final dataset was checked for unintended biases in plant diversity due to the extended sampling period, but we did not find any strong correlation between the year of sampling and the number of species per m2 (R2 < 0.12 within the habitat types and over the heathland landscape).

Concentrations of all elements were expressed in lmol kg1 dry soil. The soil moisture content was determined by oven drying the fresh soils (105 °C, 24 h), soil organic matter (OM) was determined by weight loss after ignition (550 °C, 4 h).

2.2. Soil sampling and analysis

2.3. Missing data

In each vegetation relevé the upper 10 cm of the soil was sampled using a 3 cm diameter auger. Eight to twelve sub-samples were pooled, mixed and stored in polyethylene bags at 4 °C until analysis. Fresh soil (70 g) was mixed with 200 ml bidistilled water (for determination of water-extractable elements) or 200 ml 0.2 M NaCl solution (exchangeable elements). In 28 samples which were characterized as species-rich Nardus grasslands, 0.1 M KCl was used as extractant. Within this habitat type, there were no significant differences in the chemical concentrations of macro-ions NaCl- and KCl-extracts. The mixtures were shaken for 1 h (120 movements per minute) after which the pH of the solution was measured (Radiometer type PHM 82 pH-meter). Subsequently, the solution was centrifuged (12,000 rpm, 20 min) and the supernatant was stored in polyethylene bottles at 28 °C. 2+ 2+ and K+ were determined in water- and salpH, NHþ 4 Ca , Mg 3þ  textracts, Al ; Fe3þ ; Cl ; NO 3 and P were only determined in waterextracts. Al3+, Ca2+, Mg2+, P and Fe3+-concentrations were determined using an ICP optical emission spectrometer (Jarrell Ash Plasma-200). K+ was analyzed with flame photometry (Techni  con Flame Photometer IV). NHþ 4 ; NO3 and Cl concentrations were determined colourimetrically with a continuous-flow autoanalyser (Technicon AAII system). Phosphate was not measured as such, but the P-fraction in the waterextracts mainly consists of PO3 4 . Therefore, we refer to P as phosphate or PO3 4 .

As the dataset was compiled from several surveys and experiments, missing values occurred for almost all soil variables except pH. The causes for the missing data are restricted analyses of soil variables, non-comparable soil analyses techniques and equipment failure. The number of missing values varied per soil parameter but was generally less than 20%, with the exception of missing values for Fe3+ (31%), organic matter (33%) and PO3 4 (55%). As missing data may have a distinct effect on the outcome of statistical analyses, we chose to create an inference dataset by multiple imputation of missing values (Rubin, 1987; Schafer, 1997). With multiple imputations (Rubin, 1987), each missing value is replaced by a set of plausible values that represent the uncertainty about the right value to impute. Then, the multiple imputed data sets are analyzed by using standard procedures for complete data and combining the results from these analyses. Prior to imputation, soil variables were log transformed for a better fit to a normal distribution. A multiple imputation procedure was performed for each habitat type using a Markov Chain Monte Carlo (MCMC) method with a multiple chain to create five imputations. The starting value for the chain is calculated from the EM algorithm, with the median value from the observations in the original dataset for each parameter as the input value for l0. The maximum number of iterations needed for convergence was set at 5000. The five datasets with imputed values were then combined into one dataset by taking the mean of the five values for each param-

2194

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

eter. The relative efficiency (RE) of imputation states whether enough imputations have been used in order to get a reliable output. The relative efficiency (RE) is calculated as RE = (1 + k/m)1, in which k is the proportion of missing data and m is the number of imputations (Rubin, 1987). In general, the relative efficiency was higher than 95%, with the lowest efficiency being 86%. The variance for a certain variable within the datasets was always lower than the variance for that variable between the imputed datasets. The estimated mean and its standard error were computed for each variable. The difference between the population mean of the initial dataset (without imputation) and the combined dataset were tested for each variable with a T-test. We did not find any significant differences between these means, except for Cl, soil moisture and OM in one habitat type only, the species-rich Nardus grasslands. We therefore concluded that it is permitted to use the inference dataset for further statistical analysis. Some indicative soil parameters as the base cation content (BC; summation of Ca2+, Mg2+ and K+ in ueq/kg) and total mineral nitro gen content (Nmintot; NHþ 4 þ NO3 ) and ratios between elements or nutrients (e.g. Al/Ca ratio, or NH4/NO3 ratio) were calculated after the inference dataset was completed. 2.4. Differentiation of the habitat types In order to select the soil variables that explain most variation between the habitat types, a canonical discriminant analysis (CDA) was performed. As a prelude to the CDA, we selected a subset of potential discriminator soil variables between the habitat types by performing a stepwise discriminant analysis. In this analysis, variables are chosen to enter or leave the model according to one of two criteria:  the significance level of an F-test from an analysis of covariance, in which the previously selected variables act as covariates and the variable under consideration is the dependent variable and  the squared partial correlation for predicting the variable under consideration from the dependent variables, controlling for the effects of the variables already selected for the model. Based on the stepwise selection analysis, pH (water-extracts), base cation concentration, aluminium and exchangeable ammonium were excluded from the canonical discriminant analysis. To address the question whether the habitat types do differ in soil characteristics, the squared Mahalanobis distances between the group means were calculated. An ANOVA was used to test

whether the squared Mahalanobis distances varied between the group means. We then performed a canonical discriminant analysis on the inference dataset. This is a dimension-reduction technique related to principal component analysis (PCA) and canonical correlation, but differs from PCA in that predefined groups are used. The canonical discriminant analysis also indicates the most important factors that differentiate between the habitat types. Following the canonical discriminant analysis, a GLM-procedure was performed on the variables with high correlations on the first three canonical axes. In order to establish significant differences in soil variables between the habitat types, we used the Tukey–Kramer test on all main effect means. 2.5. Plant diversity and soil biogeochemistry In order to determine explanatory factors in the species number and number of endangered species within each habitat type, degraded and well-developed vegetation types of wet and dry heaths were analyzed together. We started by establishing differences in the number of total and endangered higher plant species between the habitat types, by performing a GLM procedure followed by a Tukey–Kramer test. Next, the relationships between the soil variables and species numbers were tested In order to avoid multicollinearity and to perform the regression on the most important soil parameters, we performed a standardized principle component analysis (PCA) prior to the stepwise regression. Since PCA-axes are orthogonal and independent of each other by definition, the procedure not only selects the most important soil factors, but also avoids the problem of multicollinearity. In the PCA, the heathland landscape and each habitat type were analyzed separately. Only axes that explained more than 10% of the variance were selected (3 or 4 axes per habitat type or heathland landscape). The variables with the highest eigenvectors with these axes were used for further analysis, with the restriction that from these group, strongly correlated variables (R2 > 50%) were omitted, leaving the variables that had the highest eigenvector on the axis for further analyses. With this data we performed a stepwise regression, with total species number and the number of endangered species as dependent variables and the log transformed soil parameters as independent variables. In the stepwise regression, we also included the plot size as an independent variable, since plot size is often correlated with the number of species (Auestad et al., 2008). The significance levels for entering and leaving the model were set at 0.05.

Table 2 Summary of the canonical discriminant analysis. The correlation coefficients between the correlated soil variables and the canonical axes are given between brackets in the last column. Suffices: ‘-ex’: exchangeable soil fraction, ‘-aq’: extraction by water. Canonical axis

Canonical correlation

Squared canonical correlation

Eigenvaluea

Proportion of variance

Cumulative variance

F Value

Pr > F

Highest correlated soil variables in the canonical structure

1

0.82

0.67

2.04

0.48

0.48

6.94

<0.0001

2 3

0.70 0.55

0.50 0.30

0.99 0.43

0.23 0.10

0.71 0.81

4.91 3.66

<0.0001 <0.0001

4

0.51

0.26

0.35

0.08

0.89

3.19

<0.0001

Caex (0.78) Caaq (0.69) Mgex (0.64) Mgaq (0.64) Organic matter (0.61) Al/Ca (0.60) pHex (0.52) Soil moisture (0.50) Soil moisture (0.56) P (0.52) NH4-aq (0.44) Nmintot (0.37) NO3 (0.35) Kex (0.51) Kaq (0.36)

a

Eigenvalues of lnv(E) * H.

2195

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

SAS 9.1.3 was used for statistical analyses. Mean data were back-transformed for presentation purposes, resembling the geometrical means.

2 Inland dunes

CDA Axis 2

3. Results

Degraded dry heath Degraded wet heath

0

Dry heath

Molinia meadows

-1 Wet heath Rhynchosporion

-2 -2

-1

0

1

2

3

4

5

CDA Axis 1 3

Degraded wet heath

CDA Axis 3

2

Degraded dry heath

1 Inland

Rhynchosporion

0 dunes

Molinia meadows

Nardus grasslands Dry heath

-1 -2

Wet heath

-1

0

1 2 CDA Axis 1

3

4

5

Fig. 1. Biplots of the canonical variables of the class means of each habitat type in the canonical discriminant analysis.

60

Soil moisture (%)

50 Molinia meadows

40 Wet heath

30

Degraded wet heath

Rhynchosporion

20 10

Nardus grasslands Degraded dry heath

Dry heath Inland dunes

0 100

1000

10000

100000

Ca-ex ( mol kg-1 DW) 600 500

Nmintot ( mol kg-1 DW)

Based on their soil characteristics, all habitat types differed significantly from each other (analysis of squared Mahalanobis distances; p < 0.05), with exception of the two degraded heath communities (squared Mahalanobis distance between the degraded wet and dry heath: 1.51950, p = 0.0837). The first two axes from the canonical discriminant analysis explained 71% of the total variance (Table 2). The results showed a strong correlation between acidity-related soil factors and the first canonical axis. This axis also correlated with the organic matter content of the soil. The second axis is correlated with soil moisture content. The third axis can be characterized as a nutrient axis, as the highest correlation of this axis is with phosphorus and various mineral nitrogen forms. The fourth axis, explaining 8% of the variance, is strongly correlated with potassium. In general, the grasslands were less acidic than the heaths, having higher pH and base cation concentrations (Figs. 1 and 2, Table 3). Though the aluminium concentrations in the grasslands were similar or even higher than in the heaths, the Al/Ca-ratio was significantly lower in the grasslands. Molinia meadows are the least acidic grasslands, species-rich Nardus grasslands have intermediate values. Within the heath communities, no differences in acidity-related factors were observed between Rhynchosporion and wet heaths vegetations, and hardly any variation with the dry sand heaths. Well-developed heaths had significantly higher pH values than degraded heaths, but no other acidity-related factors differed significantly between the heaths. The inland dunes combined rather high pH values with rather low base cation concentrations, caused by the relatively young, unweathered sandy soils with a low cation exchange capacity. A distinct gradient in mineral nitrogen concentration is observed, with the inland dunes and dry sand heaths having the lowest concentrations and the species-rich Molinia meadows showing the highest values. No significant differences in phosphate concentrations were found between the well-developed habitat types. However, the degraded wet heaths showed significantly higher phosphate concentrations compared to the well-developed habitat types, and both the degraded wet and dry heaths had increased  mineral N values (both NHþ 4 and NO3 ) compared to the well-developed heath communities. The grasslands had generally higher species numbers (vascular plants), both common and endangered, than the other habitat types (Table 3). The lowest species numbers were recorded in the heathlands and the extremely dry inland dunes. The degraded heath vegetations had significantly less species than the other habitat types. In most habitat types, the size of the plots did not have any significant effects on the species numbers. Only in the inland dunes, a positive relation between plot size and the number of species is found (Table 4). In the wet heaths, plot size contributed significantly to the model (endangered species), but the regression coefficient was very low (0.002). The number of plant species per plot is, over the whole heathland landscape, best explained by the ammonium concentration, where soils with higher ammonium concentrations have a lower plant diversity (Table 4, Fig. 3). Similar results are obtained within the dry heaths. In the other habitat types, acidity-related factors as pHex, Al3+ and Al/Ca-ratio were the most important factors for species richness, with lower species numbers occurring on more acid soils. In the wet heaths, a negative correlation between soil phosphate and plant diversity was found.

Nardus grasslands

1

400

Degraded dry heath

Degraded wet heath

300

Nardus Molinia grasslands meadows

200 100 0 100

Wet heath Rhynchosporion Dry heath

1000

Inland dunes

10000

100000

Ca-ex ( mol kg-1 DW) Fig. 2. Mean values (±SEM) per habitat type of the exchangeable calcium, soil moisture content and total mineral nitrogen concentrations (Nmintot).

The model fit for the regression on the number of endangered species over the soil edaphic factors was low, due to the fact that there were only few endangered plant species per relevé (Table

2196

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

Table 3 Median values and 10–90 percentiles (between brackets) for numbers of total and endangered species per plot and soil parameters. Concentrations in lmol kg1 dry soil, base cation concentration (BC) in leq kg1 dry soil. Soil moisture and organic matter (OM) content are given as% of dry soil. Nmintot: total mineral nitrogen (exchangeable  NHþ 4 þ NO3 ). Different letters indicate significant differences between habitat types at p < 0.05.

Number of species All species Endangered species Water-extractable pH Al Ca Al/Ca Mg K Fe

NO 3 NHþ 4  NHþ 4 =NO3

P Cl Exchangeable Ca

Mg

K BC

NHþ 4  NHþ 4ðexÞ =NO3

Nmintot soil moisture OM

Dry sand heaths

Inland dunes

Wet heaths

Species-rich Nardus grasslands

Molinia meadows

Rhynchosporion

Degraded dry heaths

Degraded wet heaths

9 (3–19) a 1 (0–3)

6 (1–9) ac 1 (0–2)

6.5 (4–14) a 1 (0–4)

18.5 (9–38) b 3 (1–9)

14 (9–25) b 3 (1–4)

8 (4–15) a 3 (2–5)

6 (3–14) ac 0 (0–1)

4 (2–6) c 0 (0–1)

a

ac

ad

be

de

be

c

c

4.4 (3.8–4.9) ac 58 (19–259) ab 9 (0–93) a 7.1 (1.0–13.6) ab 0 (0–16) ae 36 (1–118) a 45 (4–250)

5.1 (4.4–5.8) ab 24 (6–92) b 9 (0–103) a 3.6 (0.4–24.3) abd 0 (0–12) abe 25 (0–487) ab 17 (3–36)

5.1 (4.3–5.9) b 68 (17–360) ab 85 (0–368) b 1.7 (0.1–7.8) d 15 (0–59) bc 75 (10–488) b 29 (5–137)

5.6 (4.7–6.4) b 146 (27–488) b 674 (171–2000) c 0.2 (0.1–0.7) c 70 (24–275) d 35 (6–285) ab 258 (10–2162)

4.6 (4.1–5.3) ac 77 (29–281) ab 39 (5–86) ab 2.9 (0.8–8.1) ad 16 (0–36) bce 119 (23–304) b 51 (2–84)

4.2 (4.1–4.4) c 119 (55–197) ab 9 (0–76) ab 10.6 (1.6–20.8) ab 0 (0–19) ae 81 (81–107) ab 51 (30–88)

4.2 (3.9–4.8) c 139 (29–240) ab 6 (0–52) a 9.6 (1.1–22.9) b 0 (0–35) e 105 (63–195) ab 36 (10–98)

abd 2 (0–33) a 7 (0–112) a 5.3 (0.7–10.3) acd 0.3 (0.0–3.6) a 118 (4–945) ab

abd 27 (0–150) abc 25 (1–80) abc 2.3 (0.0–7.5) abd 0.6 (0.0–3.2) ab 15 (0–306) a

4.4 (3.9–5.4) ac 131 (15–861) a 44 (0–317) ab 5.0 (0.6–14.5) ab 37 (0–137) c 151 (0–505) ab 96 (9– 2773576) c 12 (0–99) abc 53 (1–814) bc 8.1 (1.5–14.0) c 0.5 (0.0–2.6) a 368 (215–766) bc

ad 14 (0–247) bc 30 (1–212) b 2.8 (0.1–6.6) b 0.4 (0.0–2.9) a 361 (0–25109) c

bc 17 (4–129) bc 53 (19–258) bc 5.0 (0.4–13.0) abc 0.0 (0.0–9.1) a 489 (159–3939) c

d 8 (0–31) ac 53 (3–253) bc 7.2 (2.4–17.2) c 0.4 (0.0–2.4) a 321 (151–579) bc

abd 97 (7–227) b 77 (33–561) bc 1.3 (0.2–9.0) bd 0.1 (0.0–7.2) ab 270 (110–476) abc

abd 45 (0–203) bc 109 (44–313) c 3.8 (1.1–5.8) abc 3.7 (0.0–41.5) b 236 (21–456) abc

426 (75– 3433) a 208 (56–427)

855 (66–3687)

3457 (396– 11482) b 432 (129–1884)

654 (280–1011)

761 (277–2982)

a 180 (34–1048)

a 170 (31–389)

a 159 (71–814)

ad 137 (26–481) a 1527 (485– 7690) a 26 (0–173) a 8.7 (1.7–19.5) a 33 (1–221) a 17 (8–34) a 4.8 (1.6–11.9) a

abd 136 (48–522) ab 2531 (245– 9947) a 35 (7–99) abc 2.3(0.3–13.0) a 44 (16–204) ab 5 (1–13) c 1.3 (0.8–1.5) b

26721 (12501– 64262) c 2855 (548– 6269) c 258 (41–781) ab 62750 (25765– 134322) c 236 (25–757) c 10.4 (2.1–37.5) a 300 (28–1079) b 49 (24–82) b 18.1 (8.2–64.5) c

617 (79–3331)

ab 327 (21–1194)

892 (174– 8401) a 450 (122– 1641) ab 262 (90–852) b 3851 (740– 18788) ab 73 (0–509) abc 8.3 (2.6–20.3) a 98 (0–531) ab 29 (16–64) bd 5.9 (0.4–21.7) a

ad 202 (54–976) ab 2067 (447– 9683) a 53 (2–279) ab 8.4 (3.3–27.0) a 63 (3–310) ac 27 (18–41) de 5.5 (1.6–9.9) a

d 153 (88–380) ab 1754 (898– 3180) a 135 (32–698) bc 2.4 (0.3–4.6) a 275 (40–851) bc 15 (10–28) ade 5.5 (5.2–6.4) a

ad 230 (175–501) ab 2167 (1271–7842)

b 283 (110–872) b 8937 (1367– 26615) b 96 (13–510) bc 6.2 (0.5–16.7) a 140 (19–672) bc 16 (5–38) a 5.0 (2.0–11.5) a

a 209 (25–991) bc 2.8 (1.8–14.8) a 226 (31–991) b 15 (8–39) ade 7.4 (5.7–8.6) a

Table 4 Summarizing table of the stepwise regression on total species number and the number of endangered species. Exchangeable fractions are indicated by the suffix ‘ex’. Number of total species

Heathland landscape (all habitat types) Inland dunes Species-rich Nardus grasslands Species-rich Molinia meadows Rhynchosporion Dry sand heath Wet heath

Number of endangered species

Model R2

Highest partial R2

Regression coefficient

Partial R2

Partial R2 > 0.05 and significant at p < 0.05

Model R2

Highest partial R2

0.52

NHþ 4

3.46

0.21

BC, Nmintot

0.23

BC

0.62 0.38 0.41 0.24 0.46 0.22

Mg2þ ex 0.41 – – 0.07 0.28

NH4/NO3 – – NHþ 4 Soil moisture

0.84 0.57 0.57 0.49 0.53 0.22

Plot size Al3+ pH-ex Al/Ca NHþ 4 P

0.68 4.77 4.71 1.66 2.24 1.65

Ca-ex, NH4-/NO3 Kþ ex BC, plot size BC

Partial R2

R2 > 0.05 and significant at p < 0.05

0.08

0.43

Nmintot, þ NO 3 ; NH4

0.60

0.21 – – 0.07 0.15

Ca2+, Al3+ – –

Regression coefficient

0.14 0.18

Plot size

2197

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

Heathland landscape 50

Number of species

45 40 35 30 25 20 15 10 5 0 0,01

0,1

1

10

100

1000

10000

NH4 in µmol/kg DW Wet heath

Dry sand heaths

16

30 25

Number of species

Number of species

14 12 10 8 6 4 2 0 0,01

20 15 10 5 0

0,1

1

10

100

0,1

1

P in µmol/kg DW

100

1000

NH4 in µmol/kg DW

Nardus grasslands

Molinia meadows 30

50 45

25

40

Number of species

Number of species

10

35 30 25 20 15 10

20 15 10 5

5 0

0 1

10

100

1000

3

4

5

Al 3+ in µmol/kg DW

6

7

pH -ex

Inland dunes

Rhynchosporion 25

10 8

Number of species

Number of species

9 7 6 5 4 3 2

20 15

10 5

1 0

0 0

500

Mg

2+ -ex

1000

in µmol/kg DW

1500

0

2

4

6

8

10

12

P in µmol/kg DW

Fig. 3. Relation between species number and the most explaining factors for the total heathland landscape and its habitat types. For regression statistics see Table 4.

2198

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

4). Plant diversity in the heathland gradient correlated positively with the base cation concentration. The number of endangered  þ plant species correlated with NHþ 4 and NH4ex =NO3 in, respectively, the dry heaths and Nardus grasslands, whereas a positive correlation between soil moisture content and the species number is found in the wet heath communities. We did not find any soil parameters that correlated with the number of endangered species in the Molinia meadows and the Rhynchosporion communities.

4. Discussion This paper focuses on the interaction between soil chemistry and vegetation. The data underlying the analysis is collected over a 26 year time span. During this period, conditions for plant growth may have been altered due to e.g. changes in atmospheric deposition, aerial ozone concentrations and climate. This may have led to unintended biases in the database and hence affect the outcome of the study. However, as we selected well-developed communities for the study, in which species number was correlated very weakly with the sample year (R2 < 0.12 for each community), we assume that management of the sites was adequate and counteracted potentially effects of the ascribed processes. 4.1. Biogeochemical characterisation of habitats 4.1.1. Acidity In the heathland landscape, gradients exist in acidity, soil moisture content and nutrient availability, which are reflected in the occurrence of different habitat types in different parts of the gradients. In well-developed communities, soil acidity is the most important factor and distinguishes stronger between habitat types than soil fertility. This is consistent with gradient analyses in wet heaths and fen meadows (Wheeler and Proctor, 2000), with observations on dry heath and Nardo-Galion communities (Roelofs et al., 1996) and with surveys on the distribution of characteristic species of these habitats along these gradients (Balme, 1953; Hayati and Proctor, 1990; Houdijk et al., 1993; De Graaf, 2000; Kleijn et al., 2008). Soil acidity is expressed in a variety of soil parameters, with pH being only one of them. The strong correlation of the first CDA axis with calcium and magnesium indicates a separation in main buffering processes: soils with high calcium and magnesium concentrations (species-rich Nardus grasslands, species-rich Molinia grasslands and inland dunes) are mainly buffered by cation exchange processes, whereas soils with low values of these cations (dry sand heaths, degraded wet and dry heaths) are buffered by dissolution of aluminium hydroxides (Scheffer and Schachtschabel, 1979). Wet heaths and Rhynchosporion are buffered by both processes, with the main buffering process varying per site. In cation exchange buffering, hydrogen ions, originating from soil processes or atmospheric input, are exchanged for base cations at negatively charged soil particles (e.g. clay minerals, organic matter). As almost all vegetation stands occurred on sandy or loamy soils with a low clay fraction, the cation exchange capacity is strongly determined by the organic matter content of the soil. This explains the strong correlation between the first CDA-axis and the organic matter content (Table 2). The transition from cation exchange to aluminium buffering takes place around pH = 4.5. Below this value, plant availability of important resources as calcium, magnesium, potassium and sodium is lowered. Moreover, an increase in potential phytotoxic Al3+, H+, Mn2+ is observed, as well as a reduction in the nitrification rate (Marschner, 1991). The latter causes a shift in the dominant mineral þ N form from oxidized nitrogen ðNO 3 Þ to reduced N ðNH4 Þ. Though H+ itself may be toxic to plants (Marschner, 1995), many species of these habitats can resist the low pH values (Van Dobben, 1991). In hydroponic culture, Al3+ has been shown to be

toxic to seedlings of Arnica montana and Cirsium dissectum, characteristic species of species-rich Nardus and Molinia grasslands (De Graaf et al., 1997). This contrasts with the tolerance of Calluna vulgaris to aluminum, the dominant dwarf shrub in dry sand heaths. Moreover, germination on heath soils (pH = 4.3–4.6) of several species (e.g. Succisa pratensis, Parnassia palustris, Euphrasia stricta, A. montana and Gentiana pneumonanthe) was reduced by the addition of aluminium (Roem et al., 2002; Van den Berg et al., 2003). Field surveys by Houdijk et al. (1993) and Kleijn and coworkers (2008) showed that not the aluminium concentration itself but the Al/ Ca-ratio in the soil determined the distribution of the heathland species. This can be explained by the ameliorating effect of calcium on aluminium toxicity (Rengel, 1992; De Graaf et al., 1997). In the present survey, the canonical correlation of Al3+ with the first CDAaxis was weaker (R2 = 0.21) than that with the Al/Ca ratio (R2 = 0.60), supporting the findings of Houdijk et al. (1993), Kleijn et al. (2008) and De Graaf et al. (1997) and indicating the greater importance of Al/Ca ratios in explaining the distribution of species rather than the Al3+-concentration itself. 4.1.2. Nutrients Though less important than acidity and soil moisture content, the importance of differences in nutrient availability as distinguishing factor is evident even in this nutrient-poor heathland landscape (this study, Wheeler and Shaw, 1995; Bobbink et al., 1998; Wheeler and Proctor, 2000; Roem and Berendse, 2000). The fact that soil fertility is found to be less important might be due to the method of estimating nutrient availability. Nutrient availability in soils is hard to establish, unequivocally because of different methodological drawbacks (Marschner, 1995). Mineral fractions, as used in this analysis, are extracted by different solvents. For nitrogen, our extraction methods give a plausible insight into mineral N available to plants, but the plant available phosphorus amount is likely to be underestimated as water is not a powerful extractant (Marschner, 1995). Moreover, mineral concentrations are very variable in soil as they are the outcome of several input processes, e.g. mineralization, nitrification, input by ground water or atmospheric deposition and removal processes such as uptake by plants and microorganisms, and leaching. Nevertheless, the measured mineral N and P fractions follow the pattern for fertility generally found in these gradients, with low nutrient concentrations in the soils of pioneer vegetations and heathlands and higher in fen meadows and species-rich Nardus grasslands (Wheeler and Proctor, 2000; De Graaf, 2000). Nitrogen availability is, apart from input by atmospheric deposition, strongly determined by the rates of mineralization and nitrification, which in turn are affected by acidity, substrate availability (both quantity and quality), and soil moisture content (anoxia). In this survey we did not measure mineralization rates, but our results show a distinct positive correlation between the mineral N-concentrations (especially NHþ 4 ) and soil acidity (expressed as pH or Caex (Fig. 1)), referring to the reduced mineralization at higher acidity. Effects of substrate availability on N-mineralization are shown by the higher N-concentrations in the Nardus grasslands when compared to the inland dunes, which have comparable pH values but differ in organic matter contents and mineral N-concentrations (Table 3). This correlation was even stronger in degraded heaths, which showed significantly increased N and organic matter concentrations compared to their well-developed counterparts. The accumulation of organic matter and N during succession of heaths and in degraded grass dominated heaths has been shown to correlate with an increase in mineralization rates (Berendse, 1990; Van Vuuren et al., 1992). 4.2. Biodiversity and heathland decline Plant diversity is analyzed both on the landscape level (‘heathland landscape’) and for the habitat types separately. Soil ammo-

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

nium is the most important factor in explaining plant diversity in the heathlands. Both on the landscape level and in the dry heath communities a negative correlation is found between ammonium concentration of the soil and the number of plant species (Table 4, Fig. 3). Increased ammonium concentrations are the result of increased N-deposition, from hampered nitrification in soils with low pH and/or from impaired plant or microbial uptake/immobilization as a result of other stresses (Dorland et al., 2004). The negative response of wet and dry heaths to increased nitrogen availability as a result of atmospheric deposition has received much attention and it is evident that in such conditions grasses as Molinia caerulea and Deschampsia flexuosa can outcompete the original dwarf shrub vegetation (Roelofs, 1986; Aerts and Heil, 1993; Bobbink et al., 1998). It has also been shown, though less emphasized, that these grasses can withstand increased ammonium concentrations and though ammonium is toxic to many heathland species, experiments showed that neither high NHþ 4 nor high NH4/NO3 had any negative effects on growth of these grasses (Houdijk et al., 1993; Van den Berg et al., 2005, 2008). This in contrast to species from weakly buffered habitats, which are very sensitive to NHþ 4 as is consistently shown by surveys (Houdijk et al., 1993; Roelofs et al., 1996; Vergeer et al., 2003; Kleijn et al., 2008), mesocosm studies (Van den Berg et al., 2008) and experiments on hydroponic cultures (De Graaf et al., 1998a,b; Van den Berg et al., 2005). Even Calluna vulgaris, a characteristic species of the dry sand heaths occurring on acid soils, is sensitive to very high ammonium concentrations. Moreover, ammonium toxicity is more pronounced at lower pH in many species (Gigon and Rorison, 1972; Dijk and Eck, 1995; Lucassen et al., 2003; Britto and Kronzucker, 2002; Van den Berg et al., 2005) and some typical species, like C. dissectum, only suffer from ammonium toxicity at low pH (Lucassen et al., 2003). Though ammonium toxicity itself is not evident from the present study, it is demonstrated that a combination of low pH and high ammonium concentrations does not occur in the well-developed Molinia meadows and Nardus grasslands. However, when these grasslands acidify, as a result of atmospheric deposition or reduced influx of base-rich ground water, such conditions may occur, resulting in the decline of these ecosystems. Our results have shown that for these grasslands, as for the Rhynchosporion communities, the primary explaining factor for plant diversity is directly related to the acidity of the soil and hence that soil acidification is a serious threat to these ecosystems. Nutrient availability (N, P and/or K) is generally assumed to have a negative impact on biodiversity. The results of the present study support this, as negative correlations between plant diversity and nutrient availability have been found for the heathland landscape and dry heaths (N), wet heath (P) and the species-rich Molinia meadows (K). Recently, it has been shown that in some wet and dry heaths N is no longer limiting due to increased aerial input (Kirkham, 2001; Roem et al., 2002) and it has been suggested that species as M. caerulea might benefit from this (Kirkham, 2001). The importance of P-limitation for the conservation of endangered species in wet ecosystems has been stressed (Wassen et al., 2005). In wet heaths at weakly buffered soils, species like Dactylorhiza maculata, C. dissectum, Pedicularis sylvatica and S. pratensis are sensitive to increased P-levels. They probably become outcompeted by M. caerulea, the major competitor in the heath ecosystems (Aerts and Berendse, 1988). Nutrient availability is in our analysis less important than soil acidity in explaining biodiversity in most habitat types including grasslands. At first sight, this is in contrast with the findings of Janssens et al. (1998) in grasslands who found that nutrient availability, especially of P and K, was more important than pH. They

2199

state that the relationship between soil acidity and plant diversity is more complex than the correlation between nutrient availability and species numbers. However, they surveyed a much wider range of grassland types that included different habitats, such as intensively fertilized grasslands and the acid grasslands (pH < 4.5) are lacking. Hence, high and toxic concentrations of Al3+, NHþ 4 , etc. are absent. In such a gradient, other mechanisms, especially competitive interaction, become more prominent in explaining plant diversity, than in the heathland gradient. The latter can be characterized by a shift in buffering processes; when crossing the line, plant adaptations to the changed edaphic circumstances, including toxicity to Al3+, NHþ 4 , etc., becomes important. When remaining in the same buffering range, either in the aluminium bufferrange or the cation exchange buffering, nutrient availability becomes more important. 4.3. Implications for nature management Our study stresses the importance of soil acidity as the major factor for biodiversity in the heathland landscape. Biodiversity is higher on soils with cation exchange buffering, but unfortunately, these soils are very sensitive to acidification. Such knowledge is important for conservation and restoration, as nature management should aim at the well functioning of these key processes. However, conservation and restoration projects in the heathland landscape traditionally aim at reducing nutrient availability and pay, especially in the dry communities, little attention to ameliorating effects of soil acidification. Thus, more then until now, restoration of extensive heathlands should focus on re-establishing the original soil acidity gradient and buffer capacity. In wet acidified soils, hydrological measures are often taken to counteract acidification (e.g. Roelofs et al., 1996; Jansen et al., 2004; Dorland et al., 2005b; Klimkovska et al., 2007), whereas in dry soils liming is an appropriate measure (De Graaf et al., 1998a,b). Increasing base cation and (bi-) carbonate concentrations not only counteracts soil acidification, it also reduces ammonium toxicity by (1) lowering soil ammonium concentrations by increasing nitrification rates at higher pH (Dorland et al., 2004) and (2) by the fact that ammonium is less or non-toxic at higher soil pH (Lucassen et al., 2003; Van den Berg et al., 2005). However, heathlands rarely suffer from soil acidification solely. Atmospheric deposition of N and changes in hydrological regimes increase plant available N and sometimes P. A combined approach by both counteracting acidification and nutrient enrichment is preferred in the heathland communities that are originally buffered by cation exchange buffering. Such an approach has been proven to increase the success rate of heathland restoration projects (De Graaf et al., 1998a; Dorland et al., 2005a,b; Klimkovska et al., 2007). In heathlands on originally very acid soils (pH < 4.5), as most of the wet and dry heath communities, species are adapted to acid conditions. Usually these heathlands are rather poor in vascular plant species. In these communities, increasing the base cation concentration and soil pH is not likely to improve plant performance or survival of the characteristic species (De Graaf et al., 1998a) and does therefore not add to the conservation or restoration of the original plant communities. In these communities, reverting to the original low nutrient soil properties is the major target. Many studies have shown the success of such management measures, especially after sod cutting (e.g. De Graaf et al., 1998a; Dorland et al., 2005a; Van den Berg et al., 2003; Härdtle et al., 2006, 2009). We conclude that knowledge of the key biogeochemical processes and of the causes for decline in a certain community is a major prerequisite for conservation and restoration. The given ranges in soil variables in this paper (Table 3) provide clear targets for the successful restoration of degraded heathland ecosystems.

2200

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201

Acknowledgements This project was funded by The Netherlands Organization for Scientific Research (NOW; Project No. 014.22.061). The authors thank B-WARE Research Centre for making parts of their vegetation-soil database available for this project. We thank Prof. Dr. J. van Groenendael and the anonymous referents for their helpful comments on this paper. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.biocon.2009.04.020. References Aerts, R., Berendse, F., 1988. The effect of increased nutrient availability on vegetation dynamics in wet heathlands. Vegetatio 76, 63–69. Aerts, R., Heil, G.W., 1993. Heathlands: Patterns and Processes in a Changing Environment. Kluwer Academic Publishers, Dordrecht. Auestad, I., Knut, R., kland, R.H., 2008. Scale-dependence of vegetation– environmental relationships in semi-natural grasslands. Journal of Vegetation Science 19, 139–148. Balme, O.E., 1953. Edaphic and vegetational zoning on the carboniferous limestone of the Derbyshire Dales. Journal of Ecology 41, 331–344. Bekker, R.M., Schaminée, J.H.J., Bakker, J.P., Thompson, K., 1998. Seed bank characteristics of Dutch plant communities. Acta Botanica Neerlandica 47, 15–26. Berendse, F., 1990. Organic matter accumulation and nitrogen mineralization during secondary succession in heathland ecosystems. Journal of Ecology 78, 413–427. Blackstock, T.H., Stevens, D.P., Stevens, P.A., Mockridge, C.P., Yeo, M.J.M., 1998. Edaphic relationships among Cirsio-Molinietum and related wet grassland communities in lowland Wales. Journal of Vegetation Science 9, 431–444. Bobbink, R., Hornung, M., Roelofs, J.G.M., 1998. The effects of air-borne nitrogen pollutants on species diversity in natural and semi-natural European vegetation. Journal of Ecology 86, 717–738. Britto, D.T., Kronzucker, H.J., 2002. NHþ 4 toxicity in higher plants: a critical review. Journal of Plant Physiology 159, 567–584. De Graaf, M.C.C., Bobbink, R., Verbeek, P.J.M., Roelofs, J.G.M., 1997. Aluminium toxicity and tolerance in three heathland species. Water Air and Soil Pollution 98, 229–239. De Graaf, M.C.C., Verbeek, P.J.M., Bobbink, R., Roelofs, J.G.M., 1998a. Restoration of species-rich dry heaths: the importance of appropriate soil conditions. Acta Botanica Neerlandica 47, 89–111. De Graaf, M.C.C., Bobbink, R., Roelofs, J.G.M., Verbeek, P.J.M., 1998b. Differential effects of ammonium and nitrate on three heathland species. Plant Ecology 135, 185–196. De Graaf, M.C.C., 2000. Exploring the Calcicole – Califuge Gradient in Heathlands. PhD Thesis, Radboud University Nijmegen. Dijk, E., Eck, N., 1995. Ammonium toxicity and nitrate response of axenically grown Dactylorhiza incarnata seedlings. New Phytologist 131, 361–367. Dorland, E., Bobbink, R., Messelink, J.H., Verhoeven, J.T.A., 2003. Soil ammonium accumulation after sod cutting hampers the restoration of degraded wet heathlands. Journal of Applied Ecology 40, 804–814. Dorland, E., van den Berg, L.J.L., van de Berg, A.J., Vermeer, M.L., Roelofs, J.G.M., Bobbink, R., 2004. The effects of sod cutting and additional liming on potential net nitrification in heathland soils. Plant and Soil 265, 267–277. Dorland, E., Hart, M.A.C., Vermeer, M.L., Bobbink, R., 2005a. Assessing the success of wet heath restoration by combined sod cutting and liming. Applied Vegetation Science 8, 209–218. Dorland, E., van den Berg, L.J.L., Brouwer, E., Roelofs, J.G.M., Bobbink, R., 2005b. Catchment liming to restore degraded, acidified heathlands and moorland pools. Restoration Ecology 13, 302–311. Gigon, A., Rorison, I.H., 1972. Response of some ecologically distinct plant species to nitrate–nitrogen and to ammonium–nitrogen. Journal of Ecology 60, 93– 102. Härdtle, W., Niemeyer, M., Niemeyer, T., Assmann, T., Fottner, S., 2006. Can management compensate for atmospheric deposition in heathland ecosystems? Journal of Applied Ecology 43, 759–769. Härdtle, W., Von Oheimb, G., Gerke, A.-K., Niemeyer, M., Niemeyer, T., Assmann, T., Drees, C., Matern, A., Meyer, H., 2009. Shifts in N and P budgets of heathland ecosystems: effects of management and atmospheric inputs. Ecosystems 12, 298–310. Hayati, A.A., Proctor, M.C.F., 1990. Plant distribution in relation to mineral nutrient availability and uptake on a wet-heath site in South-west England. Journal of Ecology 78, 134–151. Hennekens, S.M., Schaminée, J.H.J., 2001. TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science 12, 589– 591.

Houdijk, A.L.F.M., Verbeek, P.J.M., Van Dijk, H.F.G., Roelofs, J.G.M., 1993. Distribution and decline of endangered herbaceous heathland species in relation to the chemical composition of the soil. Plant and Soil 148, 137– 143. Jansen, A.J.M., Fresco, L.F.M., Grootjans, A.P., Janlink, M.H., 2004. Effects of restoration measures on plant communities of wet heathland ecosystems. Applied Vegetation Science 7, 243–252. Janssen, J.A.M., Schaminée, J.H.J., 2003. Europese Natuur in Nederland. Habitattypen. KNNV Uitgeverij, Utrecht. Janssens, F., Peeters, A., Tallowin, J.R.B., Bakker, J.P., Bekker, R.M., Fillat, F., Oomes, M.J.M., 1998. Relationship between soil chemical factors and grassland diversity. Plant and Soil 202, 69–78. Karg, S., 2008. Direct evidence of heathland management in the early Bronze age (14th century BC) from the grave-mound Skelhoj in western Denmark. Vegetation History and Archaeobotany 17, 41–49. Kirkham, F.W., 2001. Nitrogen uptake and nutrient limitation in six hill moorland species in relation to atmospheric nitrogen deposition in England and Wales. Journal of Ecology 89, 1041–1053. Kleijn, D., Bekker, R.M., Bobbink, R., De Graaf, M.C.C., Roelofs, J.G.M., 2008. In search for key biogeochemical factors affecting plant species persistence in heathland and acidic grasslands: a comparison of common and rare species. Journal of Applied Ecology 45, 680–687. Klimkovska, A., Van Diggelen, R., Bakker, J.P., Grootjans, A.P., 2007. Wet meadow restoration in Western Europe: a quantitative assessment of the effectiveness of several techniques. Biological Conservation 140, 318– 328. Lamers, L.P.M., Smolders, A.J.P., Roelofs, J.G.M., 2002. The restoration of fens in The Netherlands. Hydrobiologia 478, 107–130. Lucassen, E.C.H.E., Bobbink, R., Smolders, A.J.P., van der Ven, P.J.M., Lamers, L.P.M., Roelofs, J.G.M., 2003. Interactive effects of low pH and high ammonium levels responsible for the decline of Cirsium dissectum (L.) Hill. Plant Ecology 165, 45– 52. Marschner, H., 1991. Mechanisms of adaptations of plants to acid soils. Plant and Soil 134, 1–20. Marschner, H., 1995. Mineral Nutrition of Higher Plants, 2nd ed. Academic Press Ltd., London. Matus, G., Verhagen, R., Bekker, R.M., Grootjans, A.P., 2003. Restoration of the Cirsio dissecti-Molinietum in The Netherlands: Can we rely on soil seed banks? Applied Vegetation Science 6, 73–84. Piessens, K., Honnay, O., Martin, H., 2004. The role of fragment area and isolation in the conservation of heathland species. Biological Conservation 211, 61– 69. Rengel, Z., 1992. Role of calcium in aluminium toxicity. New Phytologist 121, 499– 513. Roelofs, J.G.M., 1986. The effect of airborne sulfur and nitrogen deposition on aquatic and terrestrial heathland vegetation. Experientia 42, 372– 377. Roelofs, J.G.M., Bobbink, R., Brouwer, E., De Graaf, M.C.C., 1996. Restoration ecology of aquatic and terrestrial vegetation on non-calcareous sandy soils in The Netherlands. Acta Botanica Neerlandica 45, 517–541. Roem, W.J., Berendse, F., 2000. Soil acidity and nutrient supply ratio as possible factors determining changes in plant species diversity in grassland and heathland communities. Biological Conservation 92, 151–161. Roem, W.J., Klees, H., Berendse, F., 2002. Effects of nutrient addition and acidification on plant species diversity and seed germination in heathland. Journal of Applied Ecology 39, 937–948. Rubin, D.B., 1987. Multiple Imputation for Nonresponse in Surveys. J. Wiley and Sons, New York. Schafer, J.L., 1997. Analysis of Incomplete Multivariate Data. Chapman and Hall, London. Schaffers, A.P., 2002. Soil, biomass, and management of semi-natural vegetation – Part I. Interrelationships. Plant Ecology 158, 229–246. Schaminée, J.H.J., Weeda, E.J., Westhoff, V., 1995. De vegetatie van Nederland. Deel 2. Plantengemeenschappen van wateren, moerassen en natte heiden. Opulus Press. Upsala, Leiden. Schaminée, J.H.J., Stortelder, A.H.F., Weeda, E.J., 1996. De vegetatie van Nederland. Deel 3. Plantengemeenschappen van graslanden, zomen en droge heiden. Opulus Press. Upsala, Leiden. Scheffer, F., Schachtschabel, P., 1979. Lehrbuch der Bodenkunde. Ferdinand Enke Verlag, Stuttgart. Soons, M.B., Messelink, J.H., Jongejans, E., Heil, G.W., 2005. Habitat fragmentation reduces grassland connectivity for both short-distance and long-distance winddispersed forbs. Journal of Ecology 93, 1214–1225. Thompson, K., Bakker, J., Bekker, R.M., 1997. The Soil Seed Banks of North West Europe: Methodology, Density and Longevity. Cambridge University Press, Cambridge. Van den Berg, L.J.L., Vergeer, P., Roelofs, J.G.M., 2003. Heathland restoration in The Netherlands: effects of turf cutting depth on germination of Arnica montana. Applied Vegetation Science 6, 117–124. Van den Berg, L.J.L., Dorland, E., Vergeer, P., Hart, M.A.C., Bobbink, R., Roelofs, J.G.M., 2005. Decline of acid-sensitive plant species in heathland can be attributed to ammonium toxicity in combination with low pH. New Phytologist 166, 551– 564. Van den Berg, L.J.L., Peters, C.J.H., Ashmore, M.R., Roelofs, J.G.M., 2008. Reduced nitrogen has a greater effect than oxidised nitrogen on dry heathland vegetation. Environmental Pollution 154, 359–369.

M.C.C. De Graaf et al. / Biological Conservation 142 (2009) 2191–2201 Van Dobben, H.F., 1991. Integrated effects (low vegetation). Acidification research in The Netherlands. In: Heij, G.J., Schneider, T. (Eds.), Final Report of the Dutch Priority Programme on Acidification, Elsevier, Amsterdam. Van Tongeren, O., Gremmen, N., Henneskens, S., 2008. Assignment of relevés to predefined classes by supervised clustering of plant communities using a new composite index. Journal of Vegetation Science 19, 525–536. Van Vuuren, M., Aerts, R., Berendse, F., De Visser, W., 1992. Nitrogen mineralization in heathland ecosystems dominated by different plant species. Biogeochemistry 16, 151–166. Vergeer, P., Rengelink, R., Ouborg, N.J., Roelofs, J.G.M., 2003. Effects of population size and genetic variation on the response of Succisa pratensis to eutrophication and acidification. Journal of Ecology 91, 600–609.

2201

Verhagen, R., Klooker, J., Bakker, J.P., Van Diggelen, R., 2001. Restoration success of low-production plant communities on former agricultural soils after top-soil removal. Applied Vegetation Science 4, 75–82. Wassen, M.J., Olde Venterink, H., Lapshina, E.D., Tanneberger, F., 2005. Endangered plants persist under phosphorus limitation. Nature 437, 547–550. Webb, N.R., 1998. The traditional management of European heathlands. Journal of Applied Ecology 35, 987–990. Wheeler, B.D., Proctor, M.C.F., 2000. Ecological gradients, subdivisions and terminology of north-west European mires. Journal of Ecology 88, 187–203. Wheeler, B.D., Shaw, S.C., 1995. A focus on fens – controls on the composition of fen vegetation in relation to restoration. In: Wheeler, B.D., Shaw, S.C., Fojt, W.J., Robertson, R.A. (Eds.), Restoration of Temperate Wetlands. Wiley, Chichester, UK, pp. 49–72.