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.     

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.     

Changes in the distribution area of vascular plants in Flanders (northern Belgium): eutrophication as a major driving force

In large parts of Western Europe agricultural intensification after World War II has led to an increased use of fertilisers. The resulting nutrient enrichment (=eutrophication) has a huge impact on the occurrence and distribution of plant species and is one of the main pressures on native plant communities. We used the distribution maps (grid size: 16 km2) of individual plant species, obtained through two consecutive survey projects (1939–1971 and 1972–2004) in Flanders (northern Belgium), to estimate the relative change in their distribution area. The comparison of changes in range size among groups of taxa classified according to habitat preference and Ellenberg indicator values, demonstrated a marked decline in distribution area in species that are characteristic for nutrient-poor habitats. To assess geographic patterns in the change of species assemblages, we calculated the mean Ellenberg N- and R-values for every grid cell during each of both survey periods. Differences between these values were analysed in relation to soil type and estimates of atmospheric nitrogen deposition. The largest shifts in Ellenberg N-values, reflecting a decline of species from nutrient-poor conditions and/or an increase of nitrophilous plants, were observed in areas with nutrient-poor, acid sandy soils and high nitrogen deposition rates. Hence, shifts in species composition were modulated by geographic variation in soil type and levels of nitrogen deposition. As the levels of atmospheric nitrogen deposition are still very high in Flanders, it is likely that species from nutrient-poor habitats such as heathlands, will further decline in the near future. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Nomenclature—Lambinon et al. (2004) for vascular plants.     

Investigations into nitrogen sources and supply in reclaimed colliery spoil

Summary Two trials were established to investigate the supply of nitrogen from ammonium and nitrate fertilizers, slow release nitrogen fertilizers, an organic nitrogen fertilizer and a legume, at two phosphate levels, to eight grass cultivars on colliery spoil. Spoil nitrogen supply and chemical characteristics and herbage dry matter and nitrogen yields were monitored for up to seven years. pH and conductivity fell at both sites. pH trends appeared to be independent of nitrogen treatment. Nitrogen in the ammonium form gave better yields than in the nitrate form when 125 kg N ha^–1 was supplied in a season but there was no difference when 62.5 kg N ha^–1 was applied. Slow release forms of nitrogen gave better yields more evenly distributed over the season than one application of ammonium sulphate per season. Once established white clover (Trifolium repens) plots had a more consistent nitrogen supply, more evenly distributed yield and better quality herbage than nitrogen fertilizer plots.Lolium perenne yielded poorly at low fertility.Festuca rubra andAgrostis castellana, although establishing slowly, yielded well under high and low fertility.     

Using species‐environmental amplitudes to predict pH values from vegetation

Question: Species optima or indicator values are frequently used to predict environmental variables from species composition. The present study focuses on the question whether predictions can be improved by using species environmental amplitudes instead of single values representing species optima. Location: Semi‐natural, deciduous hardwood forests of northwestern Germany. Methods: Based on a data set of 558 relevés, species responses (presence/absence) to pH were modelled with Huisman‐Olff‐Fresco (HOF) regression models. Species amplitudes were derived from response curves using three different methods. To predict the pH from vegetation, a maximum amplitude overlap method was applied. For comparison, predictions resulting from several established methods, i. e. maximum likelihood/present and absent species, maximum likelihood/present species only, mean weighted averages and mean Ellenberg indicator values were calculated. The predictive success (squared Pearson's r and root mean square error of prediction) was evaluated using an independent data set of 151 relevés. Results: Predictions based upon amplitudes defined by maximum Cohen's x probability threshold yield the best results of all amplitude definitions (R²= 0.75, RMSEP = 0.52). Provided there is an even distribution of the environmental variable, amplitudes defined by predicted probability exceeding prevalence are also suitable (R²= 0.76, RMSEP = 0.55). The prediction success is comparable to maximum likelihood (present species only) and – after rescaling – to mean weighted averages. Predicted values show a good linearity to observed pH values as opposed to a curvilinear relationship of mean Ellenberg indicator values. Transformation or rescaling of the predicted values is not required. Conclusions: Species amplitudes given by a minimum and maximum boundary for each species can be used to efficiently predict environmental variables from species composition. The predictive success is superior to mean Ellenberg indicator values and comparable to mean indicator values based on species weighted averages.     

Regionalizing Nutrient Values of Vegetation to Assess Site Fertility of Mountain Forests in the Bavarian Alps

Height growth and productivity of forests depend on temperature, water and nutrients. Ellenberg indicator values that summarize vegetation response to growth factors are suited to predict site fertility. Macronutrients (NPK), as represented by N-values, are a crucial component of site fertility and susceptibility towards biomass extraction. Based on 1,500 vegetation plots from an inventory stratified over all important forest types of the Bavarian Alps we regionalized Ellenberg N-values against area-wide soil, climate and relief predictors including a spatial effect at a scale of 1 : 25,000, resulting in a general additive model (GAM) with eight predictors and an explained deviance of 53 % on test data. The N-value layer was combined with other regionalized indicator values (temperature, reaction, moisture) to predict height of Norway spruce at reference age (site index) of an independent forest inventory data set, resulting in a GAM with an explained deviance of 35 %. After temperature the nutrient value was the second most important predictor of site index and clearly superior to soil reaction. It can be concluded that forest growth is sensitive to reductions of NPK-availability through whole tree harvesting and that maps of N-values deliver important information for planning sustainable harvesting.     

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.     

Prediction of occurrence of vascular plants in deciduous forests of South Sweden by means of Ellenberg indicator values

Abstract. In this study we present a new method for predicting the occurrences of species using data from deciduous forests in South Sweden. Complete species lists of vascular plants were compiled from 101 stands and from representative sample plots inside the stands. Soil samples from each stand were collected for determination of pH and nitrogen mineralization. Presence-absence data for species were fitted to the values of four environmental variables - soil moisture, soil reaction (pH), soil nitrogen and light - by means of Linear (Multiple) Logistic Regression (LLR), and Gaussian (Multiple) Logistic Regression (GLR). First, these values were estimated by calculating the weighted averages of Ellenberg indicator values. Second, the estimates for reaction and nitrogen were substituted by the real measurements of pH and mineralized NH₄⁺, keeping the Ellenberg estimates for light and moisture. The models were validated by an independent test data set. In general, the models had high predictive abilities. GLR fitted the species occurrences better to the environmental variables than LLR, but had a lower accuracy of prediction of species occurrence in the stands. The use of soil measurements instead of Ellenberg indicator values did not improve the predictive abilities of the models. The environmental conditions in the stand test set were successfully estimated by using species data from the plots. When using the species lists of the stands instead of plot data, a slightly better predictive ability was obtained. The collection of plot data, however, is easier and less time-consuming. The accuracy of prediction differed considerably between species.     

Calibrating Ellenberg indicator values for moisture,acidity, nutrient availability and salinity in the Netherlands

A general calibration of Ellenberg indicator values for moisture, acidity, nutrient availability and salinity was carried out on a large database of relevées and environmental variables from a variety of ecosystems in the Netherlands.Satisfying relationships with Ellenberg indicator values for moisture, acidity and salinity were found for mean groundwater level in spring time, soil pH and chloride concentration in groundwater. For mean groundwater level in spring and chloride concentration in groundwater subdivision of the database led to clearer relationships with indicator values. For the Ellenberg indicator value for nutrient availability satisfying calibration results were only achieved with data on standing crops and N stock in standing crop. The relationship with soil chemical variables was less clear.Although the correlation between indicator and measured values is obvious, the variation around the regression lines is considerable. However, because of the size and composition of the database, it is unlikely that our calibration results can be much improved by adding more (Dutch) data.The calibration results will be applied in the multi-stress model SMART-MOVE, developed to predict changes in species composition due to acidification, eutrophication and the effects of lowering groundwater.     

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.     

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.     

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.     

Effects of Nitrogen Deposition: Results of a Temporal-Spatial Analysis of Deciduous Forests in South Sweden

Abstract: We studied permanent plots in deciduous forests in two provinces of South Sweden, Skåne (127 plots) and Småland (116 plots). Vegetation data were sampled in 1983 and 1993 and used to calculate weighted averages of Ellenberg indicator values for light, reaction (pH) and nitrogen. Soil samples were collected from all plots in 1993 for determination of pH, organic matter content and potential net nitrogen mineralization (minN). Data on minN were also available for 66 plots in Skåne from 1983. Nitrogen deposition is considerably higher in Skåne than in Småland. The same holds true for total minN, minNH₄⁺, minNO₃^-_-, and the proportion of total minN due to nitrate (nitrification ratio). According to the comparison of average Ellenberg indicator values between 1983 and 1993, the stands had become darker (not in the heavily managed plots), more acid and nitrogen rich, except at the most acid sites where only minor changes could be observed. The nitrification ratio was significantly higher in 1993 than in 1983. Mean soil nitrification ratios were determined for the most common species in both regions. The means were higher in Skåne than in Småland. It is likely that nitrogen deposition causes an increase in nitrification rate and nitrification ratio. This ratio is a significant determinant of the species composition in deciduous forests.     

Reversal of adverse effects of heavy ammonium sulphate application on growth and nutrient status of a kikuyu pasture

Summary Adverse effects resulting from fertilization with high rates of ammonium sulphate were determined on a kikuyu grass (Pennisetum clandestinum) pasture grown on a krasnozem in a sub-tropical environment. Corrective fertilizer practices using lime and phosphorus were evaluated.Ammonium sulphate application (336 kg N/ha/annum for 4 years followed by 672 kg N/ha/annum for 2 years) decreased soil pH from 5.0 to 4.0. Under these conditions, soluble Al in the soil increased, while exchangeable Ca, Mg, and K decreased. Concentrations of Ca, Mo, and P in the kikuyu tops were lowered, while concentrations of Mn were raised. Liming to pH 5.5 promoted growth more at 672 kg N/ha/annum than at 134 kg N/ha/annum, while generally little further yield response occurred as soil pH was raised to about 6.0. Liming increased the concentrations of P, Ca, N, and Mo but decreased Mn in kikuyu tops.Phosphorus application decreased soluble aluminium in the soil in all nitrogen treatments, but only increased kikuyu yield where 672 kg N/ha/annum was applied. It did not alter plant chemical composition, except for an increase in P concentration.Yield increases to liming and P were attributed to the alleviation of Al toxicity in the high N treatments. Lime responses in low N treatments were due to improved N nutrition resulting from mineralization of organic N.Lime application reduced the amount of N fertilizer required for maximum growth of kikuyu from 672 kg N/ha/annum on the unlimed soil to 134 kg N/ha/annum, while maintaining an adequate level of nutrients in the herbage and avoiding the problems of excess soil acidity. re]19760622     

Bryophyte biomass and species richness on the Park Grass Experiment,Rothamsted, UK

The relationships between bryophyte biomass and species richness and soil pH, nutrient applications and vascular plant biomass and species richness were analyzed for the Park Grass Experiment (Rothamsted, UK). The study examined the abundance of bryophytes in relation to long-term fertilizer and lime application and to fertilizer treatments recently being ceased on some plots. The probability of bryophytes being present on a plot increased with increasing soil pH, and on plots at soil pH 3.3–4.5, the lowest values in this experiment, there were virtually no mosses present. Total bryophyte biomass decreased with increasing vascular plant biomass and vascular plant richness. Both bryophyte biomass and species richness showed a curvilinear response to soil pH. Bryophyte biomass was markedly increased on plots where nitrogen (N) fertilization had recently been ceased. The abundance of the common bryophyte species showed individualistic responses to treatments. N had a negative effect on the abundance of Brachythecium rutabulum. Increasing soil pH, and the application of phosphorus (P) and potassium (K) fertilizer together, had a positive effect on Eurhynchium praelongum. This species was also negatively affected by N, but tolerated larger amounts of it (100–150 kg ha^–1 N) than B. rutabulum. An ephemeral moss, Bryum subapiculatum, had a unimodal response to soil pH but showed no response to N, P, K or other explanatory variables.     

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.     

Imputation of environmental variables for vegetation plots based on compositional similarity

Question: Large databases contain many plots, but few subsets with measured environmental data. To obtain broader datasets, researchers use expert‐based indicator values as surrogates; alternatively, these can be estimated by imputation. Does imputation provide more exact approximations than indicator values? Location: West Carpathians (Slovakia, Poland, Czech Republic) and Bulgaria. Methods: We developed a simple imputation method based on plot similarity that estimates missing environmental variables for plots –MOSS (mean of similar samples). This was tested for pH and conductivity, important environmental factors influencing vegetation composition and structure within wetlands, on two datasets of 485 (West Carpathians) and 118 (Bulgaria) plots for which directly measured values were available. The West Carpathian dataset was used for calibration. Imputation was based on calculating mean of the measured factor from a group of most similar plots. Using pre‐defined similarity criteria, we selected subsets of both datasets and compared estimated and measured values. Using root mean‐squared error of prediction, we compared predictive power of MOSS with Ellenberg indicator values and other recent methods. Results: Within one study region, MOSS predicts sample pH and conductivity more precisely than Ellenberg and similar calibration methods. Predictive power slightly decreased when MOSS was transferred to a distant region. Conclusions: Imputation using MOSS appears to accurately predict pH and conductivity from existing composition data within a single geographical region, and thus increases number of replicates. MOSS does not require expert‐based indicator values, which may be imprecise. We provide examples where MOSS can be utilised without risk of circular reasoning or introducing pseudo‐replications.     

On the statistical analysis of vegetation change: a wetland affected by water extraction and soil acidification

Abstract. A case study is presented on the statistical analysis and interpretation of vegetation change in a wetland subjected to water extraction and acidification, without precise information on the environmental changes. The vegetation is a Junco-Molinion grassland and the changes in vegetation are evaluated on the basis of relevés in 1977 and 1988 of 20 plots in a small nature reserve on moist oligotrophic, Pleistocene sands in the Netherlands. The changes are attributed to water extraction (since 1972) and soil acidification and the effect of the environmental changes on the vegetation is inferred from data on water depth and acidity collected in 1988. Many species typical of wetlands decreased in abundance, including rare species such as Parnassia palustris, Selinum carvifolia and Ophioglossum vulgatum. Some species increased, notably Anthoxanthum odoratum, Holcus lanatus and Plantago lanceolata. A significant decrease was found in the mean Ellenberg indicator values for moisture and acidity. The mean indicator value for nutrients did not change significantly. Multivariate analysis of the species data by Redundancy Analysis demonstrated the overall significance of the change in species composition between 1977 and 1988 (P < 0.01, Monte Carlo permutation). The spatial and temporal variation in the species data was displayed in ordination diagrams and interpreted in terms of water depth and pH. A simple model is developed to infer the change in water depth and pH from the relevé data and recent data on water depth and pH. Because the correlation between water depth and pH made a joint estimation of the changes useless, the change in pH was estimated for a series of likely changes in water depth. For the most likely change in water depth, significant acidification was inferred from the change in vegetation. The model is more generally applicable as a constrained calibration method.     

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.     

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.