Multiple environmental changes drive forest floor vegetation in a temperate mountain forest

Human‐induced changes of the environment and their possible impacts on temperate forest understory plant communities have been examined in many studies. However, the relative contribution of individual environmental factors to these changes in the herb layer is still unclear. In this study, we used vegetation survey data covering a time period of 21 years and collected from 143 permanent plots in the Northern Limestone Alps, Austria. Data on soil chemistry (49 plots), light condition (51 plots), soil temperature and moisture (four and six plots), disturbance (all plots), climate (one station in a clearing area), and airborne sulfur (S) and nitrogen (N) deposition (two forest stands) were available for analyses. We used these data together with plot mean Ellenberg indicator values in a path analysis to attribute their relative contributions to observed vegetation changes. Our analysis reveals a strong directional shift of the forest understory plant community. We found strong evidence for a recovery of the ground‐layer vegetation from acidification as response to decreased S deposition. We did not observe a community response to atmospheric N deposition, but we found a response to altered climatic conditions (thermophilization and drying). The path analysis revealed that changes in the light regime, which were related to small‐scale disturbances, had most influence on herb layer community shifts. Thermophilization and drying were identified as drivers of understory community changes independent of disturbance events.     

Short-term and long-term variation in seed bank/vegetation relations along an environmental and successional gradient

The seed bank along a successional and environmental gradient was analysed. Soil was collected in 3-cm thick horizons from permanent plots along two transects across a land uplift seashore, spanning several centuries of succession from shoreline to mature forest. Vegetation in the plots was recorded when the soil was sampled and also 9 and 15 yr before that. Within- and between-plot effects on seed bank./vegetation relationships were analysed using estimates of seed longevity. Sorensen's similarity index and mean Ellenberg indicator values.
A seed bank longevity index was constructed by using the database by Thompson et al, (1997 The soil seed banks of north west Europe. Methodology, density and longevity, Cambridge Univ Press), for all species with more than one entry in the database. For species with one or no entry, an internal Index was constructed. The two indices were correlated and it was suggested that the internal index should be used where the Thompson database is insufficient.
There were small differences between the upper three soil horizons in seed density, in similarity with the vegetation and in mean Ellenberg values. The highest seed densities and seed bank/vegetation similarities were found at the shoreline, after that the density and the similarity decreased with increasing successional age, with the mature forest having very low seed density and similarity values. Weighted mean Ellenberg indicator values for light, nitrogen, salt and moisture differed between vegetation and seed bank. For the seed bank, the mean Ellenberg values for light, moisture and nitrogen and weighted mean of seed bank longevity indices showed a trend along one of the transects.     

Are Plant Censuses Carried Out on Small Quadrats More Reliable than on Larger Ones?

Plant censuses are known to be significantly affected by observers’ biases. In this study, we checked whether the magnitude of observer effects (defined as the % of total variance) varied with quadrat size: we expected the census repeatability (% of the total variance that is not due to measurement errors) to be higher for small quadrats than for larger ones. Variations according to quadrat size of the repeatability of species richness, Simpson equitability and reciprocal diversity indices, Ellenberg indicator values, plant cover and plant frequency were assessed using 359 censuses of vascular plants. These were carried out independently by four professional botanists during spring 2002 on the same 18 forest plots, each comprising one 400-m² quadrat, four 4-m² and four 2-m² quadrats. Time expenditure was controlled for. General Linear Models using random effects only were applied to the ecological indices to estimate variance components and magnitude of the following effects (if possible): plot, quadrat, observer, plant species and two-way interactions. High repeatability was obtained for species richness and Ellenberg indicator values. Species richness and Ellenberg indicator values were generally more accurate but also more biased in large quadrats. Simpson reciprocal diversity and equitability indices were poorly repeatable (especially equitability) probably because plant cover estimates varied widely among observers, irrespective of quadrat size. Grouping small quadrats usually increased the repeatability of the variable considered (e.g. species richness, Simpson diversity, plant cover) but the number of plant species found on those pooled 16 m² was much lower than if large plots were sampled. We therefore recommend to use large, single quadrats for forest vegetation monitoring.     

Effects of plot size on the ordination of vegetation samples

Questions: Do ordination patterns differ when based on vegetation samples recorded in plots of different size? If so, how large is the effect of plot size relative to the effects of data set heterogeneity and of using presence/absence or cover‐abundance data? Can we combine plots of different size in a single ordination? Methods: Two homogeneous and two heterogeneous data sets were sampled in Czech forests and grasslands. Cover‐abundances of plant species were recorded in series of five or six nested quadrats of increasing size (forest 49‐961 m2; grassland 1‐49 m²). Separate ordinations were computed for plots of each size for each data set, using either species presences/absences or cover‐abundances recorded on an ordinal scale. Ordination patterns were compared with Procrustean analysis. Also, ordinations of data sets jointly containing plots of different size were calculated; effects of plot size were evaluated using a Monte Carlo test in constrained ordination. Results: The results were consistent between forest and grassland data sets. In homogeneous data sets, the effect of presence/absence vs. cover‐abundance was similar to, or larger than, the effect of plot size; for presence/absence data the differences between ordinations of differently sized plots were smaller than for cover‐abundance data. In heterogeneous data sets, the effect of plot size was larger than the effect of presence‐absence vs. cover‐abundance. The plots of smaller size (= 100 m2 in forests, = 4 m² in grasslands) yielded the most deviating ordination patterns. Joint ordinations of differently sized plots mostly did not yield patterns that would be artifacts of different plot size, except for plots from the homogeneous data sets that differed in size by a factor of four or higher. Conclusions: Variation in plot size does influence ordination patterns. Smaller plots tend to produce less stable ordination patterns, especially in data sets with low ß‐diversity and species cover‐abundances. Data sets containing samples from plots of different sizes can be used for ordination if they represent vegetation with large ß‐diversity. However, if data sets are homogeneous, i.e. with low ß‐diversity, the differences in plot sizes should not be very large, in order to avoid the danger of plot size differences distorting the real vegetation differentiation in ordination patterns.     

Vegetation monitoring in a 100-year-old calcareous grassland reserve in Germany

Calcareous grasslands harbor specialized species and are cultural relics. Therefore, they are prime habitates for conservation and restoration, but negative effects of inappropriate management, eutrophication and fragmentation continue to exist. These effects also influence grasslands which serve as target for restoration. Unfortunately, monitoring of long-term vegetation dynamics in calcareous grassland is rare. Here, we studied such changes over 35 years in the nature reserve ‘Garchinger Heide’, which is well known for its high abundance of rare species. Furthermore, it has been managed for conservation for more than 100 years. Therefore, species composition, total species richness, numbers of habitat specialists, red-list species and the proportion of graminoids were examined in 42 plots with frequency recording (1984–2018), and in 40 plots based on vegetation relevés (2003–2018). Ellenberg indicator values, specific leaf area, seed mass, and canopy height were analysed to detect patterns in trait response to environmental change. Within 35 years there were considerable vegetation dynamics. Specialist plants of calcareous grassland and red list species decreased, and insect-pollinated species declined in contrast to wind-pollinated species. Ellenberg N as well as graminoid abundance, canopy height, seed mass, and multi-trait functional dispersion increased, while specific leaf area showed no such change. Our results suggest that environmental change like deposition of atmospheric nitrogen, management regime, pollinator decline or isolation could be correlated with vegetation dynamics, while these correlations would need experimental confirmation. The grassland management certainly helped achieving several conservation goals, although it was not able to stop a decrease of rare species. The results show that also in nature reserves with long-term conservation management monitoring is essential to detect vegetation dynamics and to adjust the management to these changes.     

Plant diversity,species turnover and shifts in functional traits in coastal dune vegetation: Results from permanent plots over a 52‐year period

Question: What is the relationship between plant diversity and species turnover in coastal dune vegetation plots? How is the long‐term change in species composition of vegetation plots related to shifts in functional traits, and what does it tell us about the dominant processes? Location: Coastal dunes, the Netherlands. Methods: Our data set comprised 52 years of vegetation data from 35 permanent plots in grassland/scrub/woodland vegetation. Vegetation dynamics were described in terms of changes in species composition and abundance, and shifts in 13 functional traits related to resources capture and forage quality, regeneration and dispersal. Results: Species turnover in the plots was high, because of local extinction and colonization. Species‐rich plots were more stable in terms of species abundance and composition compared with species‐poor plots. Over time, the plots converged with respect to their abiotic conditions, as reflected by Ellenberg indicator values – indicating that the prevailing process was succession. The high species turnover reflected high invasibility: accordingly, the relative importance of annuals increased. Most newcomer annuals, however, were competitive generalists of little conservation value. The functional trait analysis allowed us to unravel the complexity of effects of disturbances and succession, and yielded information on the processes driving the observed vegetation dynamics. Conclusions: In this study, small‐scale species turnover was negatively related to species diversity, indicating more stability in species‐rich communities. Regarding shifts in trait diversity, unifying filters appeared to be more dominant than diversifying filters. Counteracting this homogenization process poses a challenge for nature management.     

Recovery of pristine boreal forest floor community after selective removal of understorey, ground and humus layers

In boreal spruce forests that rarely experience extensive disturbances, fine-scale vegetation gaps are important for succession dynamics and species diversity. We examined the community implications of fine-scale gap disturbances by selective removal of vegetation layers in a pristine boreal spruce forest in Northern Finland. The aim was to investigate how the speed of recovery depends on the type of disturbance and the species growth form. We also wanted to know if there appeared changes in species composition after disturbance. Five different treatments were applied in the study: Control, removal of the ground layer (bryophytes and lichens), removal of the understorey layer (dwarf shrubs, herbs and graminoids), removal of both the ground and understorey layers, and complete removal of the vegetation and humus layers above the mineral soil. The vegetation recovery was monitored in terms of cover and species numbers over a 5-year period. Understorey layer cover, composed mainly of clonal dwarf shrubs, recovered completely in 4 years in treatments where the humus layer remained intact, whereas ground layer cover did not reach the control level in plots from where bryophytes and lichens were removed. Recovery was faster in terms of species number than species cover. Bryophytes, graminoids and dominant dwarf shrubs appeared in all disturbed plots quickly after disturbance. Seedlings of trees appeared exclusively in disturbed plots. Graminoids dominated after the removal of humus layer. The results indicate that the regeneration of forest floor after small gap disturbance occurs mainly by re-establishment of the dominant species. Although destruction of the humus layer leaves a long-lasting scar to the forest floor, exposing of mineral soil may enhance the sexual reproduction of dominant species and the colonization of weaker competitors.     

The contribution of nitrogen deposition to the eutrophication signal in understorey plant communities of European forests

We evaluated effects of atmospheric deposition of nitrogen on the composition of forest understorey vegetation both in space and time, using repeated data from the European wide monitoring program ICP‐Forests, which focuses on normally managed forest. Our aim was to assess whether both spatial and temporal effects of deposition can be detected by a multiple regression approach using data from managed forests over a relatively short time interval, in which changes in the tree layer are limited. To characterize the vegetation, we used indicators derived from cover percentages per species using multivariate statistics and indicators derived from the presence/absence, that is, species numbers and Ellenberg's indicator values. As explanatory variables, we used climate, altitude, tree species, stand age, and soil chemistry, besides deposition of nitrate, ammonia and sulfate. We analyzed the effects of abiotic conditions at a single point in time by canonical correspondence analysis and multiple regression. The relation between the change in vegetation and abiotic conditions was analyzed using redundancy analysis and multiple regression, for a subset of the plots that had both abiotic data and enough species to compute a mean Ellenberg N value per plot using a minimum of three species. Results showed that the spatial variation in the vegetation is mainly due to “traditional” factors such as soil type and climate, but a statistically significant part of the variation could be ascribed to atmospheric deposition of nitrate. The change in the vegetation over the past c. 10 years was also significantly correlated to nitrate deposition. Although the effect of deposition on the individual species could not be clearly defined, the effect on the vegetation as a whole was a shift toward nitrophytic species as witnessed by an increase in mean Ellenberg's indicator value.     

Airborne hyperspectral data predict Ellenberg indicator values for nutrient and moisture availability in dry grazed grasslands within a local agricultural landscape

Species-based ecological indices, such as Ellenberg indicators, reflect plant habitat preferences and can be used to describe local environment conditions. One disadvantage of using vegetation data as a substitute for environmental data is the fact that extensive floristic sampling can usually only be carried out at a plot scale within limited geographical areas. Remotely sensed data have the potential to provide information on fine-scale vegetation properties over large areas. In the present study, we examine whether airborne hyperspectral remote sensing can be used to predict Ellenberg nutrient (N) and moisture (M) values in plots in dry grazed grasslands within a local agricultural landscape in southern Sweden. We compare the prediction accuracy of three categories of model: (I) models based on predefined vegetation indices (VIs), (II) models based on waveband-selected VIs, and (III) models based on the full set of hyperspectral wavebands. We also identify the optimal combination of wavebands for the prediction of Ellenberg values. The floristic composition of 104 (4 m × 4 m grassland) plots on the Baltic island of Öland was surveyed in the field, and the vascular plant species recorded in the plots were assigned Ellenberg indicator values for N and M. A community-weighted mean value was calculated for N (mN) and M (mM) within each plot. Hyperspectral data were extracted from an 8 m × 8 m pixel window centred on each plot. The relationship between field-observed and predicted mean Ellenberg values was significant for all three categories of prediction models. The performance of the category II and III models was comparable, and they gave lower prediction errors and higher R² values than the category I models for both mN and mM. Visible and near-infrared wavebands were important for the prediction of both mN and mM, and shortwave infrared wavebands were also important for the prediction of mM. We conclude that airborne hyperspectral remote sensing can detect spectral differences in vegetation between grassland plots characterised by different mean Ellenberg N and M values, and that remote sensing technology can potentially be used to survey fine-scale variation in environmental conditions within a local agricultural landscape.     

Epigeic bryophytes do not improve bioindication by Ellenberg values in mountain forests

Based on a stratified random sample of 93 vegetation plots and coincident measurements of ecological conditions in mountain forests of the Bavarian Alps, the degree to which species composition and Ellenberg indicator values derived thereof were related to measured environmental variables was assessed for vascular understorey plants and epigeic bryophytes. According to Mantel tests vascular composition contained ca. 30% more ecological information than bryophyte composition. When expressed as average Ellenberg or Düll values, vascular plant-based values reflected 60% more of measured variables than bryophyte-based values. The differences remained after rarefaction of the vascular matrix to the gamma diversity of bryophytes, showing that indication is not a function of indicator richness. Analysing vascular plants and bryophytes combined yielded very similar, or even slightly less stringent relationships with the environment than using vascular plants only.Bivariate relationships of indicator values with corresponding ecological measurements confirmed the specific potential of the values to estimate ecological factors from both plant groups, but vascular plants performed better for all factors. Bryophyte indication was particularly poor for light, temperature and base saturation. Bryophyte-based indicator values did not significantly predict the residuals of measured ecological variables against vascular plant-based Ellenberg values.For the study region, it is concluded that indicator values of vascular forest understorey should be used without consideration of Düll's indicator values for epigeic bryopyhtes. There appears to be potential to improve bioindication by recalibrating indicator values of epigeic bryophytes based on ecological measurements and vascular plant indicator values.     

Reliability of Ellenberg indicator values for moisture,nitrogen and soil reaction: a comparison with field measurements

Abstract. Ellenberg indicator values for moisture, nitrogen and soil reaction were correlated with measured soil and vegetation parameters. Relationships were studied through between‐species and between‐site comparisons, using data from 74 roadside plots in 14 different plant communities in The Netherlands forming a wide range. Ellenberg moisture values correlated best with the average lowest moisture contents in summer. Correlations with the annual average groundwater level and the average spring level were also good. Ellenberg N‐values appeared to be only weakly correlated with soil parameters, including N‐mineralization and available mineral N. Instead, there was a strong relation with biomass production. We therefore endorse Hill & Carey's (1997) suggestion that the term N‐values be replaced by ‘productivity values'. For soil reaction, many species values appeared to need regional adjustment. The relationship with soil pH was unsatisfactory; mean indicator values were similar for all sites at pH > 4.75 because of wide species tolerances for intermediate pH levels. Site mean reaction values correlated best (r up to 0.92) with the total amount of calcium (exchangeable Ca²⁺ plus Ca from carbonates). It is therefore suggested that reaction values are better referred to as ‘calcium values'. Using abundance values as weights when calculating mean indicator values generally improved the results, but, over the wide range of conditions studied, differences were small. Indicator values for bryophytes appeared well in line with those for vascular plants. It was noted that the frequency distributions of indicator values are quite uneven. This creates a tendency for site mean values to converge to the value most common in the regional species pool. Although the effect on overall correlations is small, relationships tended to be less linear. Uneven distributions also cause the site mean indicator values at which species have their optimum to deviate from the actual Ellenberg values of these species. Suggestions for improvements are made. It is concluded that the Ellenberg indicator system provides a very valuable tool for habitat calibration, provided the appropriate parameters are considered.     

Classification of the Sieversio montanae-Nardetum strictae in a cross-section of the Eastern Alps

The Sieversio montanae-Nardetum strictae is one of the most widespread plant communities in (sub-) alpine regions of the Alps. Our study examines the composition, ecology and distribution of this plant community in the Eastern Alps and addresses the issue of how the community is to be classified in the phytosociological system of Nardus-rich grasslands. Therefore, 357 vegetation relevés were taken from the literature and 115 from our own inventories were recorded from 2005 to 2007 in Western Austria (mostly Tyrol) and Northern Italy (mostly South Tyrol). Additionally, indicator values of Ellenberg and land-use information were used to help better interpret the ecological site conditions of the subgroups. The HCA revealed there the existence of four groups of the Sieversio montanae-Nardetum strictae, which were classified to subassociations: (1) typicum, (2) vaccinietosum, (3) trifolietosum pratensis, and (4) seslerietosum albicantis. Besides the specific plant composition, altitude specifies the first, land-use intensity the second and third, and the pH of the topsoil the fourth subassociation. For the Eastern Alps, the plant community of the Sieversio montanae-Nardetum strictae should now be reclassified in the order of Nardetalia and the class of Calluno-Ulicetea. Finally, this plant community can be further classified by using the four above-mentioned subassociations.     

Prediction of herbage yield in grassland: How well do Ellenberg N‐values perform?

Question: How useful are Ellenberg N‐values for predicting the herbage yield of Central European grasslands in comparison to approaches based on ordination scores of plant species composition or on soil parameters? Location: Central Germany (11°00′‐11°37’E, 50°21‐50°34’N, 500–840 m a.s.l.). Methods: Based on data from a field survey in 2001, the following models were constructed for predicting herbage yield in montane Central European grasslands: (1) Linear regression of mean Ellenberg N‐, R‐ and F‐values; (2) Linear regression of ordination scores derived from Non‐metric Multidimensional Scaling (NMDS) of vegetation data; and (3) Multiple linear regression (MLR) of soil variables. Models were evaluated by cross‐validation and validation with additional data collected in 2002. Results: Best predictions were obtained with models based on species composition. Ellenberg N‐values and NMDS scores performed equally well and better than models based on Ellenberg R‐ or F‐values. Predictions based on soil variables were least accurate. When tested with data from 2002, models based on Ellenberg N‐values or on NMDS scores accurately predicted productivity rank order of sites, but not the actual herbage yield of particular sites. Conclusions: Mean Ellenberg N‐values, which are easy to calculate, are as accurate as ordination scores in predicting herbage yield from plant species composition. In contrast, models based on soil variables may be useful for generating hypotheses about the factors limiting herbage yield, but not for prediction. We support the view that Ellenberg N‐values should be called productivity values rather than nitrogen values.     

Correlation between stand structure and ground vegetation: an analytical approach

The effect of stand structure on the diversity of the forest's ground vegetation was examined based on data on permanent sample plots collected in the northern parts of North-Carelia, eastern Finland. Different ordination methods (DCA, GNMDS, LNMDS, and HMDS) were used together with the TWINSPAN classification method. The aim was to construct a basis for classifying forests with respect to the biodiversity of the forest vegetation. Fertility and stand age showed the strongest correlation with the variation in ground vegetation. Other important factors were basal area, tree species composition, and crown cover. These variables were important in the division of the sample plots into different classes. According to the diversity indices, species diversity was at its highest in young stands on fertile forest sites. As a result, twenty-one different classes were formed based on the relative abundance of understorey species. The variables with the highest correlation were used to describe the stand structure in these classes.     

NIRS meets Ellenberg's indicator values: Prediction of moisture and nitrogen values of agricultural grassland vegetation by means of near-infrared spectral characteristics

Ellenberg indicator values are widely used ecological tools to elucidate relationships between vegetation and environment in ecological research and environmental planning. However, they are mainly deduced from expert knowledge on plant species and are thus subject of ongoing discussion. We researched if Ellenberg indicator values can be directly extracted from the vegetation biomass itself. Mean Ellenberg “moisture” (mF) and “nitrogen” (mN) values of 141 grassland plots were related to nutrient concentrations, fibre fractions and spectral information of the aboveground biomass. We developed calibration models for the prediction of mF and mN using spectral characteristics of biomass samples with near-infrared reflectance spectroscopy (NIRS). Prediction goodness was evaluated with internal cross-validations and with an external validation data set. NIRS could accurately predict Ellenberg mN, and with less accuracy Ellenberg mF. Predictions were not more precise for cover-weighted Ellenberg values compared with un-weighted values. Both Ellenberg mN and mF showed significant and strong correlations with some of the nutrient and fibre concentrations in the biomass. Against expectations, Ellenberg mN was more closely related to phosphorus than to nitrogen concentrations, suggesting that this value rather indicates productivity than solely nitrogen. To our knowledge we showed for the first time that mean Ellenberg indicator values could be directly predicted from the aboveground biomass, which underlines the usefulness of the NIRS technology for ecological studies, especially in grasslands ecosystems.     

Cover‐weighted averaging of indicator values in vegetation analyses

Question: How should species cover be weighted when calculating average indicator values of vegetation relevés? Location: The Netherlands. Method: Various weighting methods were statistically investigated with 188 relevés from The Netherlands for which accurate groundwater levels were available. For each method the correlation between average Ellenberg indicator value for moisture and mean spring groundwater level was calculated. A permutation test on correlation coefficients revealed whether differences between methods were significant or not. Results: Optimization of a general weighting function did not produce a significantly higher correlation than disregarding cover and calculating the average as the arithmetical mean of indicator values. Giving a higher weight to species at both ends of the indicator scale and using indifferent species as indicators of mediocre conditions did improve the correlation significantly. Weighting species proportionate to their cover yielded a significantly lower correlation than the correlation obtained with the method that disregards cover. A significantly lower correlation was also established when taking into account the fact that cover is related to the growth strategy of species.     

Factors influencing vegetation gradients across ancient‐recent woodland borderlines in southern Sweden

Abstract. We studied gradients in field layer vegetation across ecotone‐type borderlines between 12 ancient woodlands and adjacent secondary deciduous woodlands on former arable land. The aim of the study was to determine how distance from the borderline influences species distributions as compared with soil factors and degree of canopy closure. Correspondence Analysis showed that distance from the borderline is closely related to the first ordination axis at all study sites. Canonical Correspondence Analysis with variation partitioning revealed that distance from the borderline was the single most important factor in explaining vegetation variation. In general, the results suggest the following order of decreasing importance: Distance from the borderline < Soil reaction < Soil nitrogen < Soil moisture < Canopy cover. However, the sum of soil variables, as estimated by weighted averages of Ellenberg indicator values for moisture, reaction and nitrogen, accounted for as much as ca. 50–70% of the total variation explained by environmental variables. Important gradients in field layer vegetation are due to a decrease in typical woodland species and an increase in other species with increasing distance from the ancient woodland. The results suggest dispersal limitation of woodland species as an important determinant of secondary forest succession. However, the importance of distance to species distributions decreases with increasing stand age as most woodland species gradually colonize the recent woodlands. After 70 yr, ca. 50 % of the woodland species present at a site showed complete colonization within 50 m from the ancient woodland border.     

Picea abies andAbies alba forests of the austrian alps: Numerical classification and ordination

A TWINSPAN classification of a representative set of 3026 relevés of spruce and fir forests from the Eastern Alps (Austria) is presented. Ecological features of relevé clusters and species groups are described by means of Ellenberg indicator values, site factors and stand characteristics. The most important floristic discontinuity in the data set separates acidophilous communities on mostly silicate substrates from basiphilous communities on mostly carbonate substrates. Further divisions reflect a combined gradient of temperature, nutrient regime and shading. This is supported by the correlation of average Ellenberg values of sample plots with DCA axes. A qualitative comparison between TWINSPAN clusters and a syntaxonomic system widely used in the Austrian Alps is drawn. The two ordersPiceetalia excelsae andAthyrio-Piceetalia largely coincide with the clusters of the first level of divisions. Alliances are partly reproduced by TWINSPAN. Clusters on the fifth and fourth level of division mostly correspond to associations. However, a considerable portion of the lower level clusters is of a transitional type. Out of thirteen fir and spruce associations described for the Austrian Alps, five associations are not reproduced by TWINSPAN, i.e.Bazzanio-Piceetum, Veronico-Piceetum, Adenostylo alliariae-Abietetum, Asplenio-Piceetum andCarici-Piceetum. Three associations are split on the second level of division, i.e.Larici-Piceetum, Luzulo nemorosae-Piceetum andCalamagrostio variae-Piceetum.     

Facilitation between woody and herbaceous plants that associate with arbuscular mycorrhizal fungi in temperate European forests

In late‐successional environments, low in available nutrient such as the forest understory, herbaceous plant individuals depend strongly on their mycorrhizal associates for survival. We tested whether in temperate European forests arbuscular mycorrhizal (AM) woody plants might facilitate the establishment of AM herbaceous plants in agreement with the mycorrhizal mediation hypothesis. We used a dataset spanning over 400 vegetation plots in the Weser‐Elbe region (northwest Germany). Mycorrhizal status information was obtained from published resources, and Ellenberg indicator values were used to infer environmental data. We carried out tests for both relative richness and relative abundance of herbaceous plants. We found that the subset of herbaceous individuals that associated with AM profited when there was a high cover of AM woody plants. These relationships were retained when we accounted for environmental filtering effects using path analysis. Our findings build on the existing literature highlighting the prominent role of mycorrhiza as a coexistence mechanism in plant communities. From a nature conservation point of view, it may be possible to promote functional diversity in the forest understory through introducing AM woody trees in stands when absent.