Validity of Ellenberg indicator values judged from physico‐chemical field measurements

Abstract. The relationship between mean Ellenberg indicator values (IV) per vegetation relevé and environmental parameters measured in the field usually shows a large variation. We tested the hypothesis that this variation is caused by bias dependent on the phytosociological class. For this purpose we collected data containing vegetation relevés and measured soil pH (3631 records) or mean spring groundwater level (MSL, 1600 records). The relevés were assigned to vegetation types by an automated procedure. Regression of the mean indicator values for acidity on soil pH and the mean indicator values for moisture on MSL gave percentages explained variance similar to values that were reported earlier in literature. When the phytosociological class was added as an explanatory factor the explained variance increased considerably. Regression lines per vegetation type were estimated, many of which were significantly different from each other. In most cases the intercepts were different, but in some cases their slopes differed as well. The results show that Ellenberg indicator values for acidity and moisture appear to be biased towards the values that experts expect for the various phytosociological classes. On the basis of the results, we advise to use Ellenberg IVs only for comparison within the same vegetation type.     

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.     

Apparently we do need phytosociological classes to calibrate Ellenberg indicator values!

Abstract. We stated (Wamelink et al. 2002) that mean Ellenberg indicator values are biased towards expectations of phytosociologists. Witte & von Asmuth (2003; this volume) have two major points of criticism: (1) the data we used would be systematically biased; (2) in calibrating Ellenberg indicator values for moisture availability against mean spring groundwater level we should have assumed a sigmoid response instead of a linear one. As to (1), a bias in the data would require that wet vegetation types were visited in wet years and dry vegetation types in dry years. We do not see any evidence for this. As to (2), our data do not provide strong evidence for a sigmoid relation instead of a linear one. Neither is there any indication that the bias in the Ellenberg indicator values would disappear when a sigmoid function would be fitted. We do agree with Witte & von Asmuth that it is preferable to characterize the species’ response by those variables to which they most directly respond.     

A site classification for Scottish native woodlands

Summary

The proposed site classification should assist in choice when creating or rehabilitating native woodlands on site types of different quality. Eight climatic zones are defined by warmth and wetness factors. Eight soil moisture regimes are defined by water table depth and the amount of available water in summer. Six soil nutrient regimes are defined by soil acidity and nitrogen availability. Woodland and scrub sub-communities of the National Vegetation Classification are ordinated by their preferences for soil moisture and soil nutrients, using Ellenberg ecological indicator values. After stratification by climatic zone, the communities are then located on the grid of soil moisture and nutrient regimes. The actual and relative positions of the communities and sub-communities are discussed in relation to existing knowledge of their distribution in relation to climate and soil types.     

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.     

Do we really need phytosociological classes to calibrate Ellenberg indicator values?

Abstract. Wamelink et al. (2002) calibrated Ellenberg indicator values for acidity and water availability against measured soil pH and measured mean spring groundwater level (MSL), respectively. Linear regression between indicator value and measured value of all the observations gave a poor fit. Regression lines per phytosociological vegetation class, on the other hand, generally described the observations well. In this article we demonstrate that this result is, at least partly, an artefact. First, because the data utilized are likely to contain systematic errors, and second, because a wrong regression model was applied. A sigmoid function for the relation between the indicator value for water availability and MSL gives a far better fit than a linear function does.‘Vegetation class’ is not an obvious choice as an extra explanatory variable for the regression, as it is only a convenient label for vegetation and should not be used as if it were a real independent environmental variable. In general, indicator values of plant species should be calibrated against environmental variables with great care. This implies that researchers should have knowledge about the ecological demands plants make on their environment, as well as about the spatial and temporal variability of this environment.     

The TRM Model of Potential Natural Vegetation in Mountain Forests

Due to advances in spatial modeling and improved availability of digital geodata, traditional mapping of potential natural vegetation (PNV) can be replaced by ecological modeling approaches. We developed a new model to map forest types representing the potential natural forest vegetation in the Bavarian Alps. The TRM model is founded on a three-dimensional system of the ecological gradients temperature (T), soil reaction (R), and soil moisture (M). Within such a “site cube” forest types are defined as homogenous site units that give rise to forest communities with comparable species composition, structure, production and protective functions. The three gradients were modeled using regression algorithms with area-wide, high resolution geodata on climate, relief and soil as predictors and average Ellenberg indicator values for temperature, acidity and moisture of vegetation plots as dependent variables summarizing plant responses to ecological gradients. The resulting predictor-response relationships allowed us to predict gradient positions of each raster cell in the region from geodata layers. The three-dimensional system of gradients was partitioned into 26 forest types, which can be mapped for the whole region. TRM-based units are supplemented by 22 forest types of special sites defined by other ecological factors such as geomorphology, for which individual GIS rules were developed. The application of our model results in an intermediate-scale map of potential natural forest vegetation, which is based on an explicit function of temperature, reaction and moisture and is therefore consistent and repeatable in contrast to traditional PNV maps.     

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.     

Prediction of yield in the Rothamsted Park Grass Experiment by Ellenberg indicator values

Abstract. The Rothamsted Park Grass Experiment was established in 1856, with experimental plots subjected to annual applications of fertilizer and twice-yearly cutting of hay. There were two major responses to fertilizer, one reflecting high ammonium-nitrogen and increased acidity and the other reflecting high herbage yield without increased acidity. We calculated mean Ellenberg indicator values for N (nitrogen) and R (soil reaction) for the hay harvested between 1948 and 1975, using both unweighted and abundance-weighted means. Plot Ellenberg values were compared with herbage yield and with fertilizer application rates and published soil data. Annual yield of hay varied from 1.5 to 7.4 t/ha and was well predicted by the unweighted mean Ellenberg N-values (r = 0.91). Relatively large negative residuals from the relationship were found in plots whose soil combined low K and low pH. Soil pH was poorly predicted by the unweighted mean R-value, but showed a moderately good relation with weighted mean R (r = 0.73). The fact that Ellenberg N-values correlated better with yield than with applied nitrogen suggests that they might rather be called productivity values.     

Dynamics of species-rich upland hay meadows over 15 years and their relation with agricultural management practices

Questions: Has the species-rich vegetation of upland hay meadows been maintained under low intensity management imposed by an agri-environment scheme? Is the target plant community re-establishing where it has been modified previously by intensive agricultural practices? What combinations of management practices and soil properties are associated with changes towards or away from the target community? Location: The Pennines, northern England, UK. Methods: A survey of 116 hay meadows in 1987 was repeated in 2002 by recording plant species in permanent quadrats. Changes in community variables (species richness, Ellenberg values, upland hay meadow community coefficients) were analysed in species-rich, modified species-rich and degraded grassland types. Redundancy Analysis and Generalised Linear Models were used to show the relationship between management practices and soil properties and change in species composition and community variables. Results: Few sites contained the species-rich grassland type, and here forb richness declined. In the modified species-rich type, total and grass species richness increased but Ellenberg N-values also increased. Total and grass species richness increased in the degraded type and the community coefficient increased. Management was weakly related to change in species composition but showed clear relationships with the community variables. Re-establishment of the target species-rich community was more likely with late cutting, in the absence of cattle or prolonged spring grazing, and at lower soil nutrient status. Conclusion: The species-rich community was not maintained but some reversion occurred in degraded grassland. Inorganic fertiliser application and intensive spring grazing should be avoided and cutting delayed until late July.     

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.     

Empirical realised niche models for British higher and lower plants – development and preliminary testing

Question: Can useful realised niche models be constructed for British plant species using climate, canopy height and mean Ellenberg indices as explanatory variables? Location: Great Britain. Methods: Generalised linear models were constructed using occurrence data covering all major natural and semi‐natural vegetation types (n=40 683 quadrat samples). Paired species and soil records were only available for 4% of the training data (n=1033) so modelling was carried out in two stages. First, multiple regression was used to express mean Ellenberg values for moisture, pH and fertility, in terms of direct soil measurements. Next, species presence/absence was modelled using mean indicator scores, cover‐weighted canopy height, three climate variables and interactions between these factors, but correcting for the presence of each target species in training plots to avoid circularity. Results: Eight hundred and three higher plants and 327 bryophytes were modelled. Thirteen per cent of the niche models for higher plants were tested against an independent survey dataset not used to build the models. Models performed better when predictions were based only on indices derived from the species composition of each plot rather than measured soil variables. This reflects the high variation in vegetation indices that was not explained by the measured soil variables. Conclusions: The models should be used to estimate expected habitat suitability rather than to predict species presence. Least uncertainty also attaches to their use as risk assessment and monitoring tools on nature reserves because they can be solved using mean environmental indicators calculated from the existing species composition, with or without climate data.     

An application case of ecological indicator values (Zeigerwerte) calculated with a simple algorithmic approach

Abstract

The vegetation of the study site near Rome (Castelporziano Estate), where different woodland types occur, was analysed on the basis of ecological indicator values (Zeigerwerte) for light, temperature, continentality of climate, soil moisture, soil pH and nitrogen. Indicator values were estimated with Hill's reprediction algorithm for the flora of Central-Southern Italy relying on a database of 4,207 original relevés representing a balanced survey of the vegetation of this and surrounding areas. It was possible to obtain indicator values for an important fraction of the Italian Mediterranean flora. Results are ecologically reasonable, and it was possible to find strong correlation between the recalculated values and a few environmental variables. These correlations were not significant in an analogous test with subjectively derived scores of Ellenberg indicator values.     

Plant interspecific differences in arbuscular mycorrhizal colonization as a result of soil carbon addition

Soil nutrient availability and colonization by arbuscular mycorrhizal fungi are important and potentially interacting factors shaping vegetation composition and succession. We investigated the effect of carbon (C) addition, aimed at reducing soil nutrient availability, on arbuscular mycorrhizal colonization. Seedlings of 27 plant species with different sets of life-history traits (functional group affiliation, life history strategy and nitrophilic status) were grown in pots filled with soil from a nutrient-rich set-aside field and amended with different amounts of C. Mycorrhizal colonization was progressively reduced along the gradient of increasing C addition in 17 out of 27 species, but not in the remaining species. Grasses had lower colonization levels than forbs and legumes and the decline in AM fungal colonization was more pronounced in legumes than in other forbs and grasses. Mycorrhizal colonization did not differ between annual and perennial species, but decreased more rapidly along the gradient of increasing C addition in plants with high Ellenberg N values than in plants with low Ellenberg N values. Soil C addition not only limits plant growth through a reduction in available nutrients, but also reduces mycorrhizal colonization of plant roots. The effect of C addition on mycorrhizal colonization varies among plant functional groups, with legumes experiencing an overproportional reduction in AM fungal colonization along the gradient of increasing C addition. We therefore propose that for a better understanding of vegetation succession on set-aside fields one may consider the interrelationship between plant growth, soil nutrient availability and mycorrhizal colonization of plant roots.     

Long‐term impacts of nitrogen and sulphur deposition on forest floor vegetation in the Northern limestone Alps,Austria

Question: Are there effects of long‐term deposition of airborne nitrogen and sulphur on the forest floor vegetation from permanent plots collected in 1993 compared to 2005. Location: Northern limestone Alps in Austria. Methods: Single species responses were analysed by correlating trends in cover‐abundance values, as derived from marginal models, with Ellenberg indicator values. Changes in the species composition of plots were analysed by correlating changes in mean Ellenberg indicator values with the displacement of plots within a multidimensional scaling ordination. Results: Trends in single species abundance were positively correlated with indicator values of soil pH but were independent of nutrient availability. A general trend towards the homogenisation of vegetation, due to convergent time vectors of the relevés, became obvious. Oligotrophic sites previously situated at the distal ends of ordination axes shifted towards the centre since they were enriched by species preferring mesotrophic conditions. The bulk of plots with intermediate site conditions hardly showed any trends. A concomitant analysis demonstrated that temporal changes in species composition exceed the variation in cover abundance estimates among different field botanists. Conclusions: N deposition can lead to a homogenisation of forest floor vegetation. Larger limestone areas with diverse soil conditions, such as the Northern limestone Alps in Austria, as a whole are thus negatively affected by airborne N deposition. Nevertheless, the vegetation was at least as strongly affected by an increase of basiphilous species as a result of decreasing S deposition.     

Calibration of Ellenberg indicator values for the Faroe Islands

Abstract. Elenberg's bio‐indication system for soil moisture (F), soil nitrogen (N) and soil reaction (R) was examined, based on 559 vegetation samples and environmental characteristics (vegetation cover, soil depth, soil moisture, chemical soil properties) from four Faroe islands. The original indicator values from central Europe were used for the calculation of weighted community indicator values of F, N and R. These were regressed with respect to environmental data, applying standard curvilinear regression and generalized linear modelling (GLM) and new predicted values of community indicator values were obtained from the best model. Faroe species optima values of 162 taxa for one or more of the three EUenberg scales were derived from fitting Huisman‐Olff‐Fresco (HOF) models of species abundance with respect to predicted community indicator values and are proposed as new EUenberg species indicator values to be used in the Faroe Islands. F was best correlated with a GLM model containing soil moisture, organic soil fraction, soil depth and total vegetation cover, R with a GLM model containing pH and calcium in % organic soil fraction, N with total phosphorus in % organic soil fraction. The calibrated species indicator scales are much truncated, as compared with the original values, resulting in significantly different overall distributions of the original and new species indicator values. The recalculated community indicator values are much better correlated to environmental measurements. Several species do not have clear optima, but linear or monotone relationships to the examined indicator scales. This probably indicates that the occurrence of some species in the Faroe Islands are either determined by factors other than moisture, pH or soil nutrient status or, given the young age and environmental instability of the islands, are governed by stochastic mechanisms. Extension of Ellenberg indicator values outside central Europe should always be carefully calibrated by means of adequate environmental data and adequate statistical models, such as HOF models, should be applied.     

Bias in Ellenberg indicator values — problems with detection of the effect of vegetation type

A recent analysis published in this journal found different relationships between mean Ellenberg indicator values and environmental measurements in different vegetation types. The cause was stated as bias in mean Ellenberg values between relevés which in turn suggested to reflect a bias in individual Ellenberg values. We discuss two phenomena that could explain these results without the need to invoke bias in either individual or mean Ellenberg values. Firstly, slopes of linear regression lines underestimate true relationships when analyses involve explanatory variables measured with error. Secondly, syntaxon‐specific distributions of Ellenberg values follow from the floristic definition of phytosociological units. Mean Ellenberg values per relevé therefore carry the stamp of their associated syntaxon even though associated abiotic conditions may vary between relevés. This will lead to variation in slopes and intercepts between vegetation types not because of bias in individual Ellenberg values but because of prescribed bias in the distribution of Ellenberg values between syntaxa. The residual variation in calibrations carried out across vegetation types is undoubtedly reduced by introducing vegetation type as a factor. However users should note that this is unlikely to reflect bias in individual Ellenberg values but is more likely to reflect error in environmental measurements as well the constraint imposed by phytosociological classification.     

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.     

Impact of tree species on nutrient and light availability: evidence from a permanent plot study of old-field succession

This paper compares vegetation composition, light availability, carbon and nutrient pools and Ellenberg indicator values among four old-field successional permanent plots that have received an initial treatment (ploughing, herbicide or sterilisation) prior to being left undisturbed in 1969, a second set of six plots received additional treatments (continued ploughing or mulching until 1982). On all plots species rich pioneer forests developed. Vegetation still varies among plots with different initial treatments: Sterilised plots can be distinguished from the others by dominance of Betula pendula, ploughed plots by Fraxinus excelsior, whereas herbicide-treated plots are intermediate with proportions of both species. By affecting light availability at the ground, tree species in turn influences ground vegetation and soil properties. Light availability turned out to be the dominant factor determining the composition of the vegetation in old-field succession.     

Relative Roles of Soil Moisture,Nutrient Supply,Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies

Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis’ continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ¹³C of C₃ plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ¹³C increased with CI toward “drier” sites, and decreased with soil depth and % silt content. Variation in δ¹³C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500–1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward “wetter” sites. CI accounted for 54% of compositional variance but δ¹³C accounted for only 6.2%, despite the strong relationships of δ¹³C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This study is the first to quantify the effects of soil mechanical impedance on community ecology.