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Keywords:

  • Eutrophication;
  • Litter raking;
  • Canopy closure;
  • Cryptogams;
  • Species diversity

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Question

Does eutrophication drive vegetation change in pine forests on nutrient deficient sites and thus lead to the homogenization of understorey species composition?

Location

Forest area (1600 ha) in the Lower Spreewald, Brandenburg, Germany.

Methods

Resurvey of 77 semi-permanent plots after 45 yr, including vascular plants, bryophytes and ground lichens. We applied multidimensional ordination of species composition, dissimilarity indices, mean Ellenberg indicator values and the concept of winner/loser species to identify vegetation change between years. Differential responses along a gradient of nutrient availability were analysed on the basis of initial vegetation type, reflecting topsoil N availability of plots.

Results

Species composition changed strongly and overall shifted towards higher N and slightly lower light availability. Differences in vegetation change were related to initial vegetation type, with strongest compositional changes in the oligotrophic forest type, but strongest increase of nitrophilous species in the mesotrophic forest type. Despite an overall increase in species number, species composition was homogenized between study years due to the loss of species (mainly ground lichens) on the most oligotrophic sites.

Conclusions

The response to N enrichment is confounded by canopy closure on the N-richest sites and probably by water limitation on N-poorest sites. The relative importance of atmospheric N deposition in the eutrophication effect is difficult to disentangle from natural humus accumulation after historical litter raking. However, the profound differences in species composition between study years across all forest types suggest that atmospheric N deposition contributes to the eutrophication, which drives understorey vegetation change and biotic homogenization in Central European Scots pine forests on nutrient deficient sites.


Nomenclature
Jansen & Dengler (2008)

vascular plants

Koperski et al. (2000)

bryophytes

Scholz (2000)

lichens

Abbreviations
N

nitrogen

I

invader species

W

winner species

L

loser species

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Eutrophication due to nitrogen (N) deposition has altered ecosystems and changed plant species compositions in various ecosystems (e.g. Lameire et al. 2000; Smart et al. 2005; Stevens et al. 2011). In temperate forests, this is accompanied by a high risk of a decrease in species richness in the herb layer (Bobbink et al. 2010). The critical load for temperate forest understorey vegetation of 10–15 kg·N·ha−1·yr−1 (Bobbink et al. 2010) is still exceeded in large parts of Central Europe (Fischer et al. 2010). However, a recent meta-analysis on vegetation change in the understorey of deciduous forests in Europe (Verheyen et al. 2012) revealed inconsistencies in the consequences of nutrient enrichment across forest communities. Canopy closure apparently obscured the effects of eutrophication on the ground vegetation, as a gradient of N deposition across all study sites did not serve to explain the observed eutrophication effect. Therefore, the authors suggested further research on the topic in different forest ecosystems.

Given the increasingly ubiquitous nature of human-induced N deposition, the N homogeneity hypothesis predicts that N saturation ultimately will decrease forest biodiversity (Gilliam 2006). Many studies address vegetation change in the forest understorey due to N enrichment, but few explicitly address changes in compositional similarity (but see van Calster et al. 2007; Keith et al. 2009). Keith et al. (2009) showed that eutrophication and increased shading during recent decades have gradually led to taxonomic impoverishment of woodland plant communities in the UK. Van van Calster et al. (2007)found an increase in nitrophilous species, but abiotic and biotic homogenization was mainly ascribed to changes in management.

Pine forests on nutrient deficient sites are under-represented in comparative studies on vegetation change, even though such forests account for the majority of forest sites in large parts of the northern Central European lowlands, from the Netherlands to Poland (e.g. Heinken 2008). These forest ecosystems could prove suitable for detecting confounding factors in the interpretation of eutrophication effects in broadleaved forests. First, oligotrophic pine forests are adapted to nutrient deficiency and should therefore respond strongly to eutrophication, and the relative increase of available N may be larger on N-poor soils (Diekmann & Dupré 1997; Nordin et al. 2005). Second, pine forests, by their nature, have less dense canopies (Heinken 1995), so the effect of canopy closure on vegetation change through enhanced productivity due to atmospheric N deposition (Verheyen et al. 2012) and autogenic succession after abandonment of grazing or coppice (Schmidt 1999; Verheyen et al. 2012) should be low. Resurvey studies on nutrient limited pine forests are mostly from Scandinavia (e.g. van Dobben et al. 1999; Nordin et al. 2005; Köchy & Bråkenhielm 2008). These studies are not directly transferable to Central European pine forests, since the nutrient deficiency of boreal forests is due to slow N cycling under low temperatures (Mäkipää 1994), and current loads of N deposition in Northern Europe are relatively low (Bobbink et al. 2010). In contrast, nutrient deficiency of temperate pine forests is often influenced by human top soil degradation through litter raking, but in some areas these forests also form the natural vegetation on sites with very low initial N availability (Rodenkirchen 1992; Heinken 2008).

Due to the inherent nutrient limitation of temperate pine forests, the spread of common nitrophilous species, along with a decline of rare specialist species adapted to nutrient deficiency has been observed as a result of eutrophication in these forests (e.g. Rodenkirchen 1992). According to McKinney & Lockwood (1999), such replacement of specialists by widespread generalist species may lead to increasingly similar species compositions and thus to biotic homogenization. Amarell (2000) and Jenssen & Hofmann (2005) suggest the homogenization of pine forest vegetation in northeast Germany is due to N deposition, but this has not yet been demonstrated by means of comparative vegetation surveys.

For an exact quantification of vegetation change in forest ecosystems, a time interval of more than 20 yr is recommended to account for the long life span of many forest species (Verheyen et al. 2012), and reliable historical data are usually scarce. Furthermore, comparative studies in nutrient deficient pine forests often face problems with bioindication through Ellenberg indicator values (see Ellenberg et al. 2001). These are qualitative values that reflect the realized optima of species, and thus allow interpretation of changes in environmental conditions, when direct measurements are not possible, for example in regard to historical data (see Diekmann 2003). However, reliable bioindication is often impossible in these forest types, because the number of vascular plants is low, and bryophyte and lichen species were often not included in the original survey data (e.g. Schmidt 1993). Our study uses semi-permanent plots of a well-documented and extensive historical data set (Klemm 1969). It is, to our knowledge, the first concerned with nutrient-poor temperate pine forests covering a considerable environmental and temporal gradient that also includes ground-dwelling bryophyte and lichen species.

Due to the low attention given to nutrient deficient pine forests despite their expected sensitivity towards eutrophication, we wanted to test the following hypotheses: (1) eutrophication drives vegetation change in the understorey of pine forests on nutrient deficient sites; (2) eutrophication-related vegetation changes lead to homogenization of the vegetation; and (3) the strongest vegetation change and homogenization of species composition is found on the most oligotrophic sites along the N availability gradient.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Study area

The study area comprises ca. 1600 ha in two large adjacent forest patches within the Lower Spreewald region, Brandenburg, Germany (52°03′50″–52°07′05″ N, 13°54′00″–13°59′32″ E). The climate is relatively continental, characterized by warm summers (mean July: 18.3 °C), cold winters (Jan: mean −0.6 °C) and low precipitation (557 mm) (Gauer & Aldinger 2005). The study area is characterized by nutrient-poor glacifluvial sands from the Weichsel glacial, and riverine sediments with drift sand dunes (Gauer & Aldinger 2005). Oligotrophic gley-podzols and gley-brown soils prevail on alluvial sand sites, and sand dunes comprise mostly podzols (Gauer & Aldinger 2005). Birch–oak (Betula pendula, Quercus robur) forests, partly with beech (Fagus sylvatica), are assumed to grow naturally on alluvial sands, mixed with Scots pine (Pinus sylvestris) on poorer and drier sites (Gauer & Aldinger 2005; Hofmann & Pommer 2005). Today almost all sites are covered with Scots pine forest stands of differing management intensity, from near-natural lichen–pine forest to pine or birch–pine substitute stands.

Historical data set and re-sampling

The original data set was extracted from 195 20 m × 20 m plots of pine forest vegetation on poor acidic soils (Dicrano-Pinion alliance according to Heinken 2008) surveyed by Klemm (1969) during the years 1964–1966 (further denoted as 1965). For the re-survey, we selected all plots with a minimum stand age of 15 yr at first survey that had not been harvested since, which resulted in 77 plots with relatively even distribution throughout the study area. Plots were not permanently marked, but re-location was possible from detailed sketches on survey maps at a scale of 1:5000. Minor re-location errors (a few meters) are therefore possible, but this does not preclude the detection of actual historic change, even if the vegetation of a stand is slightly heterogeneous (Ross et al. 2010).

We re-surveyed the plots from June to August 2010 using the same plot size as in the original survey. Bryophytes and lichens were collected for exact identification in the laboratory. In order to lower bias of misidentification between study years, very similar species were combined in the following analysis. Species cover was estimated according to the method of Braun-Blanquet (1964) to ensure compatibility between surveyors and converted to a nominal scale from 1–7 for the following analysis (with r = 1, + = 2, 1 = 3, etc.). We estimated the percentage cover of the total tree layer, comprising an upper (>10 m) and at some sites also a lower tree layer (3–10 m).

Data collection and analysis

For the following analysis, species abundances of the forest understorey (shrub and field layer, including tree saplings) from 77 plots and from both study years were used. We applied a three-dimensional, non-metric multidimensional scaling (NMDS, function: metaMDS, maximum iterations: 500, dimensions: 3, dissimilarity index: Bray & Curtis 1957), using the ‘vegan’ package in the software program R (R Foundation for Statistical Computing, Vienna, AT). We tested for the significance of compositional change with a non-parametric multivariate analysis of variance (MANOVA; function: adonis, 999 permutations, dissimilarity index: Bray–Curtis), which performs a permutational test using distance matrices of the species composition of plots to find significant differences between years (Anderson 2001).

We determined alpha-diversity (DivAlpha) as total species number per plot and also separately analysed the number of species of vascular plants (SpecVP), lichens (SpecLich) and bryophytes (SpecBry). Beta-diversity (DivBeta), defined as the floristic distinctiveness of each plot with regard to all other plots within each study year, was calculated using the Morisita–Horn index (Horn 1966) as implemented in function vegdist, because this index is not influenced by differences in species richness among plots, unlike the Bray–Curtis index (see Naaf & Wulf 2010). We used the concept of winner (W) and loser (L) species, defined as species with a significant increase/decrease in abundance or in frequency across plots. Increasing species that were completely new to the plots in 2010 were treated separately as invaders (I). These are not necessarily neophytes, but can also be ‘native invaders’ (Naaf & Wulf 2010) from the regional species pool. We tested the significance of distribution changes in I, W and L species using Fisher's exact test for frequency data and Wilcoxon signed-rank test for abundance data (package ‘stats’ in R). These tests were restricted to species with a minimum number of five occurrences in either study year. We characterized I, W and L species through mean Ellenberg indicator values for light availability (mL), soil N availability (mN), soil reaction (mR) and soil moisture (mM). We tested the significance of differences between these I, W and L species using one-way KruskalWallis test (package stats in R). We also calculated unweighted arithmetic means of Ellenberg indicator values mL, mN, mR and mM for each plot to describe the changes in environmental conditions per plot. We included canopy cover (Canopy Cover), given as percentages, as a more direct measure of light availability. We tested for differences in diversity measures, I/W/L species and environmental variables between study years using paired samples t-tests or Wilcoxon signed-rank tests, depending on the results of a Shapiro–Wilk normality test (all in package ‘stats’ in R).

Due to the strong influence of the top soil on plant nutrient availability, but the lack of detailed information on its previous degradation state, plots were also characterized through their initial forest vegetation type at first survey in 1965 (VEGTYPE). Vegetation classification was done with the program JUICE 7.0. Differentiating species for each type are those with a minimal frequency of 25%, and with at least twice as high a frequency in this type as compared to the other two. The understorey vegetation of the most oligotrophic and dry pine forests (further denoted as ‘oligotrophic’; 31 plots) was characterized mainly by ground lichens of the genus Cladonia and various bryophytes and can be assigned to the Cladonio-Pinetum association sensu Heinken (2008). Molinia caerulea, Pteridium aquilinum and Vaccinium myrtillus were indicative and often dominant species of the richer sites. The more mesotrophic forest type (Leucobryo-Pinetum; further denoted as ‘mesotrophic’; 31 plots) lacked its own set of characteristic species. More nutrient-demanding vascular plant species and bryophytes like Calamagrostis epigejos and Scleropodium purum characterized the most eutrophic and moister forest type (Deschampsia-Pinus community, further denoted as ‘eutrophic’; 15 plots). The three forest types were rather evenly distributed across the study area. We calculated the pair-wise differences in diversity measures, I/W/L species and environmental variables between study years for each plot and tested for differences in these changes between vegetation types using the Kruskal–Wallis test and a post-hoc test from the R package ‘asbio’.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Multiple iterations of the three-dimensional NMDS converge towards a stress value of 12.69 with a non-metric goodness of fit of R2 = 0.984. The only marginal overlap of plots from 1965 and 2010 in the ordination diagram (Fig. 1) indicates a non-analogous species composition between vegetation surveys, which is supported by the ANOVA (adonis: R2 = 0.09; < 0.01; df = 1). While the ground lichens disappeared from most plots in favour of bryophytes by 2010, the change in vegetation between study years was not as obvious on the initially lichen-poor sites. Beta-diversity overall decreased from 0.60 to 0.49 between study years (< 0.001), despite a slight but significant increase of alpha-diversity in the whole study area (DivAlpha; < 0.001; Fig. 2). The loss of beta-diversity (DivBeta) is most pronounced in the oligotrophic and least pronounced in the mesotrophic forest type (< 0.001; Fig. 2). The slight decrease of alpha-diversity (DivAlpha) in the oligotrophic forest type is significantly distinct from the increase of DivAlpha in the mesotrophic and in the eutrophic forest type (< 0.001).

image

Figure 1. Ordination diagram of non-metric multi-dimensional scaling (NMDS) with 77 pine forest plots from both study years (n = 154), using three dimensions; the third dimension has been left out in the diagram for reasons of better perceptibility; stress value: 12.69. Mean Ellenberg indicator values for light availability (mL), soil nutrient content (mN), soil reaction (mR) and soil moisture (mM) were fitted; all vector fits with < 0.001.

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image

Figure 2. Mean Ellenberg indicator values for soil nutrient content (mN), soil reaction (mR) and light availability (mL), CanopyCover, alpha- (DivAlpha) and beta-diversity (DivBeta), number of vascular plant/bryophyte/lichen species (SpecVP/SpecBry/SpecLich) and invader (I), winner (W) and loser species (L) for each study year (1 = 1965; 2 = 2010) and vegetation type (o = oligotrophic; m = mesotrophic; e = eutrophic); median values (black line), upper and lower quartiles (box) and 95% confidence intervals (whiskers) are given. Significant differences in changes of variables between vegetation types are marked with the letters A and B. SpecVP, SpecBry and W changes between study years are given for completeness, but have not been tested for differences between vegetation types, as overall changes between study years were not significant for these three variables.

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All Ellenberg indicator values fit significantly into ordination space, showing an increase of mN and mR opposed to a decrease in mL, directed roughly along the direction of compositional change. Accordingly, the mean value for mN increased significantly between 1965 and 2010 (< 0.001; Fig. 2), as did the mean value for mR (mR (1965): 2.71; mR (2010): 3.13; < 0.001). These increases are stronger in the mesotrophic than in the oligotrophic forest type (< 0.05). At the same time, mL decreased (< 0.001; Fig. 2), especially in the oligotrophic forest type (< 0.001). In contrast, Canopy Cover only increased significantly in the eutrophic forest type (< 0.01), but not overall (Canopy Cover (1965): 34.40; Canopy Cover (2010): 42.42; = 0.06). The large decrease in Ellenberg indicator values for light availability can thus mainly be attributed to the massive eutrophication-driven (see below) loss of lichens in poor pine forests, which contribute comparatively high light indicator values to the mean. The fact that mL is correlated with Canopy Cover in the survey from 2010, but not 1965, when lichens were much more abundant, is also in favour to this hypothesis (1965: rho = 0.06, = −0.41, < 0.001). The mean values for mM also fit significantly into the ordination, but seem to indicate a gradient among plots, rather than a change from 1965 to 2010, as mM did not change significantly between study years (mM (1965): 6.23; mM (2010): 5.92; = 0.12).

These results are also reflected in the 12 I, 19 W and 21 L species (Appendix S1). Loser species are characterized by significantly lower mN and mR and a higher mL in comparison with invader species (Table 1). The three groups do not differ significantly in regard to mM (Table 1). Most of the L species are lichens (12 Cladonia spp., Cetraria aculeata) and bryophytes like Dicranum spurium and Leucobryum glaucum. Both the highest number of L and the highest decrease in lichens is therefore found in the oligotrophic forest type (< 0.001). There are neophytes among invader species, e.g. Prunus serotina and Quercus rubra, but most I and W are from the native species pool of the region. Among these are nitrophilous species such as Rubus fruticosus agg. and R. idaeus, species from broad-leaved forests, e.g. Fagus sylvatica and Quercus robur, as well as pleurocarpous bryophytes, e.g. Hypnum cupressiforme and Pleurozium schreberi. The number of I is significantly lower in the oligotrophic forest (< 0.001), while the increase of W did not differ significantly between forest types (> 0.05), and neither did the numbers of vascular plants or bryophytes (> 0.05).

Table 1. Characterization of invader, winner and loser species through mean Ellenberg indicator values for light availability (mL), soil nutrient content (mN), soil reaction (mR) and soil moisture (mM) per group
Vegetation variableInvaderWinnerLoser P
  1. Significance of differences in mean values between groups is given as P-values from Kruskal–Wallis test with *< 0.05; **< 0.01; ***< 0.001; ***> 0.05 n.s.

mN 4.13.31.9 ***
mR 4.63.42.4 *
mL 5.65.56.7 *
mM 4.75.04.9n.s.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Vegetation change in pine forests on nutrient deficient sites

Species composition of nutrient deficient pine forests shifted strongly within the 45 yr between studies, and vegetation changed towards both N-rich and shadier conditions, while apparently no relevant vegetation shift related to changes in groundwater table took place. The increase in mean indicator values for soil reaction is probably only due to a co-increase along with N, because of the strong correlation between these indicator values among species. On acid soils such a correlation has also been found in previous studies (Seidling & Fischer 2008; Verheyen et al. 2012). The response of vascular plants to acidification is most pronounced on mesic sites and seems to be less important on initially acidic sites (Schmidt 1999; van Calster et al. 2007) such as pine forests on sandy substrates.

When studying eutrophication effects in deciduous forests, canopy closure is often identified as a major confounding factor (Verheyen et al. 2012). In temperate pine forests, in contrast, the reduction of light availability seems to have no influence on vegetation change (Rodenkirchen 1992; Zerbe et al. 2000), while the eutrophication effect is obvious across all previous studies (Rodenkirchen 1992; Amarell 2000; Zerbe et al. 2000; Dzwonko & Gawronski 2002). Our study is in line with the latter results and, indeed, shows that canopy closure is only important in the eutrophic forest type, where pine forests are largely forestry stands on natural deciduous forest sites. These tend to develop into acidic oak or beech forests due to humus accumulation (Heinken 1995; Zerbe et al. 2000), while they are assumed to be the natural climax community only on very dry and poor sites where humus accumulation is limited (Heinken 2008; Ellenberg & Leuschner 2010). The latter are represented by the oligo- and mesotrophic forest types in this study and seem to be unaffected by canopy closure. The most pressing changes in vegetation composition, nonetheless, seem to be attributable to N enrichment. Our expectations were that richer pine forests would display weaker responses to eutrophication than poorer types, because they are initially less nutrient limited. Even though the oligotrophic forest type indeed experienced the strongest changes in species composition, it was the mesotrophic forest type that displayed the strongest increases in mean Ellenberg indicator value for N. It is likely that this is because the oligotrophic pine forest type is not only on the N-poorest sites, but also on the driest part of a moisture gradient. While many N-demanding species may have replaced more N deficiency adapted species at rather moist sites, few were successful at dry but enriched sites (see also Lameire et al. 2000 for a deciduous forest system).

Unfortunately, we cannot clearly distinguish the magnitude of influence of different sources of N enrichment. The effect of atmospheric N deposition is undeniable, given the critical loads for temperate forests (10–15 kg·N·ha−1·yr−1; Bobbink et al. 2010) and actual deposition rates of N in the study region (19.78 kg·N·ha−1·yr−1; Builtjes et al. 2011). However, we also observed an increased relative contribution of deciduous tree species on the richest and most moist sites. Plant species from nutrient-rich ecosystems produce easily degradable litter and, thus, enhance nutrient cycling (e.g. Hobbie 1992). Moreover, oligotrophic lichen-rich pine forests in Central Europe are mostly humus-poor degradation phases after litter raking, recovering from former nutrient depletion (Heinken 2008; Ellenberg & Leuschner 2010). With increasing litter accumulation most of these can develop into ground lichen-poor communities of the mesotrophic forest type. As cessation of litter use coincided with the start of increasing air pollution (Dzwonko & Gawronski 2002), we have no indications from which to discern the higher importance of either (autogenic) recovery processes or (allogenic) N deposition.

Jenssen & Hofmann (2005) claim that as a consequence of N deposition the same pine forest ecosystems would be found in northeast Germany, although in different localities and in different proportions than before. Vegetation types would usually develop into the next richest community type along the natural nutrient-determined gradient (Jenssen & Hofmann 2005). Such a transition from the Cladonio-Pinetum to the Leucobryo-Pinetum, and further to either the Deschampsia-Pinus community or to acidic mixed deciduous forests has indeed been described in the context of recovery processes from degradation (Heinken 1995, 2008). However, our ordination diagram clearly shows that the species composition of most plots today is by no means identical to the species composition of any old plots. The observed changes in species composition thus cannot be easily attributed to mere autogenic successional processes. We therefore strongly suggest that the observed change in species composition is actually influenced by atmospheric N deposition.

Homogenization due to the loss of cryptogams

The loss of species adapted to nutrient-poor conditions has overall led to a loss of beta-diversity across the study area. Epigeic lichens are known for their adaptation to nutrient-poor acidic soils and their low competitive ability (Nash 1996), and the detrimental effect of eutrophication on lichens is found world- and vegetation-wide (Bobbink et al. 2010). Bryophytes may decline through nutrient enrichment, if suffering from increased litter production or shading (e.g. Malkönen 1990) or competitive exclusion (Heinken & Zippel 2004). As cryptogams often grow on sites that are too extreme in environmental conditions for vascular plants, their loss should also be seen in light of functional homogenization sensu Olden et al. (2004). Overall, species composition was homogenized despite an increase of species number due to the invasion of mixed forest vascular plants at the more eutrophic sites. The increase of species number at some sites could have compensated for the loss of species at other sites in regard to beta-diversity, and could have contributed to the differentiation between habitats, but this was not the case. Studies from broad-leaved forests reported no change in species richness (Keith et al. 2009) or increasing species number (van Calster et al. 2007; Naaf & Wulf 2010) with decreasing beta-diversity. Our results are in line with the latter studies and support the opinion that alpha-diversity alone is not a sufficient indicator for changes in species diversity, and that the inclusion of beta-diversity measures is needed to thoroughly understand the impact of environmental drivers (Olden & Rooney 2006; Jurasinski & Kreyling 2007) such as eutrophication.

Olden & Rooney (2006) emphasize the need to explore the spatial dependencies of biotic homogenization. Studies in other ecosystems have detected small-scale homogenization between habitats and found that the magnitude of similarity depends on the particular habitat types studied (Britton et al. 2009; Ross et al. 2012). The differential responses of the forest types to eutrophication in our study imply that the habitat type and its inherent N availability status influence the overall changes in beta-diversity. According to the N homogeneity hypothesis, this could be based on the decrease in spatial heterogeneity of N availability that is typically high in forests under N limited conditions (Gilliam 2006). Removal of N, as seen through the historic land-use practice of litter raking, could therefore contribute to differentiation of the abiotic conditions in order to mitigate biotic homogenization in eutrophicated pine forests on naturally nutrient deficient sites.

Conclusions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Our study provides the first reliable quantification of vegetation responses of temperate pine forests on nutrient-deficient sites to eutrophication over an environmental gradient. Canopy closure, identified as a major confounding factor in studying eutrophication in deciduous forests, was only important on more N-rich sites, while the eutrophication effect was strong and consistent across the study area. Even though the magnitude of influence of natural humus accumulation and atmospheric N deposition on this effect could not be clearly separated, the profound changes in species composition suggest that N deposition is important in changing the species composition of pine forests on nutrient deficient sites. Despite an overall increase in species number through the invasion of more N demanding species on richer sites, the loss of species adapted to N deficiency on oligotrophic sites resulted in a decrease of beta-diversity at the landscape level. We could demonstrate that besides vascular plants also bryophytes and lichens should be included when measuring homogenization, and that eutrophication-driven homogenization of species composition is not only proceeding in deciduous forests but also in pine forests, which cover the majority of poor acidic sands in the lowlands of Central Europe.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

We thank Monika Wulf and Tobias Naaf (Leibniz Centre for Agricultural Landscape Research (ZALF) e.V.), and Martin Diekmann (University of Bremen) who provided valuable support in the statistical analysis and valuable contributions to the manuscript. We also thank Jörg Müller (University of Potsdam) for helping with the determination of bryophytes and Ewald Weber (University of Potsdam) for reviewing the manuscript.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information
  • Amarell, U. 2000. Kiefernforste der Dübener Heide. Ursachen und Verlauf der Entstehung und Veränderung von Forstgesellschaften. Dissertationes Botanicae 325: 1246.
  • Anderson, M.J. 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology 26: 3246.
  • Bobbink, R., Hicks, K., Galloway, J., Spranger, T., Alkemade, R., Ashmore, M., Bustamante, M., Cinderby, S., Davidson, E., Dentener, F., Emmett, B., Erisman, J.-W., Fenn, M., Gilliam, F., Nordin, A., Pardo, L. & de Vries, W. 2010. Global assessment of nitrogen deposition effects on terrestrial plant diversity: a synthesis. Ecological Applications 20: 3059.
  • Braun-Blanquet, J. 1964. Pflanzensoziologie. Grundzüge der Vegetationskunde. 3rd edn. Springer, Wien, AT.
  • Bray, J.R. & Curtis, J.T. 1957. An ordination of upland forest communities of southern Wisconsin. Ecological Monographs 27: 325349.
  • Britton, A.J., Beale, C.M., Towers, W. & Hewison, R.L. 2009. Biodiversity gains and losses: evidence of Scottish alpine vegetation. Biological Conservation 142: 17281739.
  • Builtjes, P., Hendriks, E., Koenen, M., Schaap, M., Banzhaf, S., Kerschbaumer, A., Gauger, T., Nagel, H.D., Scheuschner, T. & Schlutow, A. 2011: Erfassung, Prognose und Bewertung von Stoffeinträgen und ihren Wirkungen in Deutschland – Zusammenfassender Abschlussbericht. Umweltbundesamt. Appendix 11: Texte Nr. 42 [http://www.uba.de/uba-info-medien/4141.html; accessed 09.11.2011].
  • van Calster, H., Baeten, L., De Schrijver, A., De Keersmaeker, L., Rogister, J., Verheyen, K. & Hermy, M. 2007. Management driven changes (1967–2005) in soil acidity and the understorey plant community following conversion of a coppice-with-standards forest. Forest Ecology and Management 241: 258271.
  • Diekmann, M. 2003. Species indicator values as an important tool in applied plant ecology – a review. Basic and Applied Ecology 4: 493506.
  • Diekmann, M. & Dupré, C. 1997. Acidification and eutrophication of deciduous forests in northwestern Germany demonstrated by indicator species analysis. Journal of Vegetation Science 8: 855864.
  • van Dobben, H., ter Braak, C. & Dirkse, M. 1999. Undergrowth as a biomonitor for deposition of nitrogen and acidity in pine forests. Forest Ecology and Management 114: 8395.
  • Dzwonko, Z. & Gawronski, S. 2002. Effect of litter removal on species richness and acidification of a mixed oak–pine woodland. Biological Conservation 106: 389398.
  • Ellenberg, H. & Leuschner, C. 2010. Vegetation Mitteleuropas mit den Alpen: in ökologischer, dynamischer und historischer Sicht, 6th edn. Ulmer, Stuttgart, DE.
  • Ellenberg, H., Weber, H.E., Düll, R., Wirth, V. & Werner, W. 2001. Zeigerwerte von Pflanzen in Mitteleuropa, 3rd edn. Scripta Geobotanica, Goltze, Göttingen, DE.
  • Fischer, R., Lorenz, M., Köhl, M., Mues, V., Granke, O., Iost, S., van Dobben, H., Reinds, G. J. & de Vries, W. 2010: The Condition of Forests in Europe: 2010 Executive Report. ICP Forests and European Commission, Hamburg and Brussels, 21 pp [http://www.icpforests.org/RepEx.htm].
  • Gauer, J. & Aldinger, G. 2005. Waldökologische Naturräume Deutschlands. Forstliche Wuchsgebiete und Wuchsbezirke mit Karte 1: 1.000.000. Mitteilungen des Vereins für Forstliche Standortskunde und Forstpflanzenzüchtung 43: 1324.
  • Gilliam, F. 2006. Response of the herbaceous layer of forest ecosystems to excess nitrogen deposition. Journal of Ecology 94: 11761191.
  • Heinken, T. 1995. Naturnahe Laub- und Nadelwälder grundwasserferner Standorte im niedersächsischen Tiefland. Gliederung, Standortsbedingungen, Dynamik. Dissertationes Botanicae 239: 1311.
  • Heinken, T. 2008. Vaccinio-Piceetea (H7) – Beerstrauch-Nadelwälder, Teil 1: Dicrano-Pinion – Sand- und Silikat-Kiefernwälder. In: Dierschke, H. (ed.) Synopsis der Pflanzengesellschaften Deutschlands, pp. 188. Die Arbeitsgemeinschaft, Göttingen, DE.
  • Heinken, T. & Zippel, E. 2004. Natural re-colonisation of experimental gaps by terricolous bryophytes in Central European pine forests. Nova Hedwigia 79: 329351.
  • Hobbie, S. 1992. Effects of Plant Species on Nutrient Cycling. Trends in Ecology and Evolution 7: 336339.
  • Hofmann, G. & Pommer, U. 2005. Die Potentielle Natürliche Vegetation von Brandenburg und Berlin, mit Karte M 1:200 000. Eberswalder Forstliche Schriftenreihe 14: 1315.
  • Horn, H.S. 1966. Measurement of “Overlap” in comparative ecological studies. The American Naturalist 100: 419424.
  • Jansen, F. & Dengler, J. 2008. GermanSL – Eine universelle taxonomische Referenzliste für Vegetationsdatenbanken in Deutschland. Tuexenia 28: 239253.
  • Jenssen, M. & Hofmann, G. 2005. Einfluss atmogener Stickstoffeinträge auf die Vielfalt der Vegetation in Wäldern Nordostdeutschlands. Beiträge für Forstwirtschaft und Landschaftsökologie 39: 132141.
  • Jurasinski, G. & Kreyling, J. 2007. Upward shift of alpine plants increases floristic similarity of mountain summits. Journal of Vegetation Science 18: 711718.
  • Keith, S., Newton, A., Morecroft, M., Bealey, C. & Bullock, J. 2009. Taxonomic homogenization of woodland plant communities over 70 years. Proceedings of the Royal Society B: Biological Sciences 276: 35393544.
  • Klemm, G. 1969. Die Pflanzengesellschaften des nordöstlichen Unterspreewald-Randgebietes. 1. Teil. Verhandlungen des Botanischen Vereins der Provinz Brandenburg 106: 2462.
  • Köchy, M. & Bråkenhielm, S. 2008. Separation of effects of moderate N deposition from natural change in ground vegetation of forests and bogs. Forest Ecology and Management 255: 16541663.
  • Koperski, M., Sauer, M., Braun, W. & Gradstein, S.R. 2000. Referenzliste der Moose Deutschlands. Schriftenreihe für Vegetationskunde 34: 1519.
  • Lameire, S., Hermy, M. & Honnay, O. 2000. Two decades of change in the ground vegetation of a mixed deciduous forest in an agricultural landscape. Journal of Vegetation Science 11: 695704.
  • Mäkipää, R. 1994. Effects of nitrogen fertilization on the humus layer and ground vegetation under closed canopy in boreal coniferous stands. Silva Fennica 28: 8194.
  • Malkönen, E. 1990. Estimation of nitrogen saturation on the basis of long-term fertilization experiments. Plant and Soil 128: 7582.
  • McKinney, M. & Lockwood, J. 1999. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends in Ecology and Evolution 14: 450453.
  • Naaf, T. & Wulf, M. 2010. Habitat specialists and generalists drive homogenization and differentiation of temperate forest plant communities at the regional scale. Biological Conservation 143: 848855.
  • Nash, T.H. III. 1996. Photosynthesis, respiration, productivity and growth. In: Nash, T.H. III (ed). Lichen Biology, pp. 88120. Cambridge University Press, Cambridge, UK.
  • Nordin, A., Strengbom, J., Witzell, J., Näsholm, T. & Ericson, L. 2005. Nitrogen deposition and the biodiversity of boreal forests: implications for the nitrogen critical load. Ambio 34: 2024.
  • Olden, J. & Rooney, T. 2006. On defining and quantifying biotic homogenization. Global Ecology and Biogeography 15: 113120.
  • Olden, J., LeRoy Poff, N., Douglas, M.R., Douglas, M.E. & Fausch, K. 2004. Ecological and evolutionary consequences of biotic homogenization. Trends in Ecology and Evolution 19: 1824.
  • Rodenkirchen, H. 1992. Effects of acid precipitation, fertilization and liming on the ground vegetation in coniferous forests of southern Germany. Water, Air, and Soil Pollution 61: 279294.
  • Ross, L.C., Woodin, S.J., Hester, A., Tompson, D.B.A. & Birks, H.J.B. 2010. How important is plot relocation accuracy when interpreting re-visitation studies of vegetation change? Plant Ecology & Diversity 3: 18.
  • Ross, L.C., Woodin, S.J., Hester, A., Tompson, D.B.A. & Birks, H.J.B. 2012. Biotic homogenization of upland vegetation: patterns and drivers at multiple spatial scales over five decades. Journal of Vegetation Science 23: 755770.
  • Schmidt, P. 1993. Veränderung der Flora und Vegetation von Wäldern unter Immissionseinfluß. Forstwissenschaftliches Centralblatt 112: 213224.
  • Schmidt, W. 1999. Bioindikation und Monitoring von Pflanzengesellschaften – Konzepte, Ergebnisse, Anwendungen, dargestellt an Beispielen aus Wäldern. Berichte der Reinhold-Tüxen-Gesellschaft 11: 133155.
  • Scholz, P. 2000. Katalog der Flechten und flechtenbewohnenden Pilze Deutschlands. Schriftenreihe für Vegetationskunde 31: 1298.
  • Seidling, W. & Fischer, R. 2008. Deviances from expected Ellenberg indicator values for nitrogen are related to N throughfall deposition in forests. Ecological Indicators 8: 639646.
  • Smart, S., Bunce, R., Marrs, R., LeDuc, M., Firbank, L., Maskell, L., Scott, W.A., Thompson, K. & Walker, K.J. 2005. Large-scale changes in the abundance of common higher plant species across Britain between 1978, 1990 and 1998 as a consequence of human activity: tests of hypothesised changes in trait representation. Biological Conservation 124: 355371.
  • Stevens, C., Duprè, C., Gaudnik, C., Dorland, E., Dise, N., Gowing, D., Bleeker, A., Alard, D., Bobbink, R., Fowler, D., Vandvik, V., Corcket, E., Mountford, J.O., Aarrestad, P.A., Muller, S. & Diekmann, M. 2011. Changes in species composition of European acid grasslands observed along a gradient of nitrogen deposition. Journal of Vegetation Science 22: 207215.
  • Verheyen, K., Baeten, L., De Frenne, P., Bernhardt-Römermann, M., Brunet, J., Cornelis, J., Decocqu, G., Dierschke, H., Eriksson, O., Hédl, R., Heinken, T., Hermy, M., Hommel, P., Kirby, K., Naaf, T., Peterken, G., Petřík, P., Pfadenhauer, J., van Calster, H., Walther, G.-R., Wulf, M. & Verstraeten, G. 2012. Driving factors behind the eutrophication signal in understorey plant communities of deciduous temperate forests. Journal of Ecology 100: 352365.
  • Zerbe, S., Brande, A. & Gladitz, F. 2000. Kiefer, Eiche und Buche in der Menzer Heide (N-Brandenburg). Verhandlungen des Botanischen Vereins von Berlin Brandenburg 133: 4586.

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information
FilenameFormatSizeDescription
jvs12069-sup-0001-AppendixS1.pdfapplication/PDF73KAppendix S1. List of winner, invader and loser species in 2010.

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