Mean Ellenberg Values Research Articles

And the winner is …. ! A test of simple predictors of plant species richness in agricultural grasslands

Land-use intensification, nutrient enrichment and enhanced productivity levels are major drivers of the current biodiversity loss in agricultural grasslands. Although these drivers are potentially strongly causally linked, their potential to explain changes in biodiversity can enhance each other and often varies over time. Here, we explored the explanatory power of different abiotic drivers and the Ellenberg indicator value for nutrient availability to predict plant species richness using data of 150 grassland plots over seven years. The approach also allows to assess the temporal robustness of many of these drivers. Our results revealed the Ellenberg indicator value for nutrients to be the best and temporally most consistent predictor of plant species richness. Unweighted mean Ellenberg values showed an even stronger negative relationship to plant species richness than abundance weighted mean values. Direct measurements of soil and plant biomass nutrients, aboveground biomass and land-use intensity predicted plant species richness less well and showed considerable temporal variability in the respective association. In case of biomass nitrogen and phosphorus concentrations, current year weather conditions are assumed to strongly affect the strength of the relationship by shifting the phenological development considerable among sampling years. Although mainly driven by aboveground biomass, a combination of biomass nutrient concentrations with productivity, i.e. the nutrient stock in the aboveground biomass, turned out to better predict plant species richness than its single components and inter-annual variability in the relationship was markedly lower. Especially for aboveground biomass and the intensity of land-use, long-term mean values significantly improved the explanatory power compared to single year measurements. We conclude that studies explaining biodiversity changes should carefully take into account temporal variability in the drivers under study before judging the strength of a particular mechanistic relationship.

Pollution and climate change drive long-term change in Scottish wetland vegetation composition

Wetlands are key components of upland landscapes and support a diverse and specialised biota. These habitats are subject to multiple drivers of change including pollutant deposition, climate change and grazing, which have varied over the last four decades. We used a resurvey approach to investigate vegetation change in Carex swamps and spring communities in the Scottish uplands between the 1970s and 2000s. We assessed changes in species group richness and cover and cover-weighted mean Ellenberg values between surveys, and related this to change in nitrogen and sulphur deposition, climate and grazing by sheep and deer.Species richness, particularly of graminoids and forbs, but also bryophytes in springs, increased between surveys. Graminoid cover in springs increased while forbs and bryophytes declined. Changes in Ellenberg values, suggested slight eutrophication in swamp habitats, but acidification and reduction in nutrient availability in springs. This apparent acidification occurred despite large reductions in sulphur deposition over the survey period and was associated with both cumulative sulphur and oxidised nitrogen deposition. Impacts of climate change were detected in spring habitats, where increases in growing degree days were associated with increased graminoid cover and a decline in forb cover. Grazing impacts were detected only in springs, where sheep grazing appeared to counteract the deleterious effects of warming by reducing graminoid cover. Our study highlights the multiple threats facing wetland communities in the uplands. The results show the need for ongoing pollution reductions to prevent further degradation of sensitive wetland habitats which are further impacted by climate change.

Resurvey of historical vegetation plots: a tool for understanding long‐term dynamics of plant communities

Resurvey of historical vegetation plots: a tool for understanding long‐term dynamics of plant communities

Climate, pollution and grazing drive long‐term change in moorland habitats

AbstractQuestionDwarf shrub moorland dominated by ericaceous plants is a distinctive, internationally important feature of northwest Europe, with its stronghold in Scotland. There have been major declines in its condition and extent. How has moorland composition changed within Scotland over the past ca. 35 yr and what is the role of climate change, pollution and grazing in driving these changes?LocationFive hundred and forty locations across Scotland, UK.MethodsWe used a long‐term resurvey approach to assess change across Scottish moorlands. We relocated plots sampled ca. 35 yr previously in alpine heath, dry heath, wet heath and bog, and recorded vegetation species composition. We assessed change in species group richness and cover and mean Ellenberg values between surveys, using paired t‐tests. We used CCA with variation partitioning and regression analysis to analyse the vegetation data with spatial data sets on climate, pollution and grazing, to assess the role of each driver in driving vegetation changes.ResultsSignificant diversity and compositional changes between surveys were found for all habitat types, particularly alpine heath. Significant associations were found with climate (many variables), pollution (N and S) and herbivore number (primarily deer). Species richness generally increased, but several specialist species declined in cover, especially those associated with higher altitude habitats (e.g. Arctostaphylos uva‐ursi, Salix herbacea and alpine lichens). Many of the most successful species are ubiquitous, e.g. the widespread grazing‐ and pollution‐tolerant graminoids Anthoxanthum odoratum, Juncus squarrosus, Festuca rubra and Nardus stricta and the generalist mosses Rhytidiadelphus squarrosus and Hylocomium splendens.ConclusionsDiversity and composition of moorlands in Scotland have changed significantly over the ca. 35‐yr period studied; the drivers of these changes are complex, with climate, pollution and grazing playing variable roles across habitats. The reduction in specialist species, homogenization of alpine heaths and declines in forb and lichen cover all represent negative changes in the biodiversity value of Scottish moorlands.

Measuring size and composition of species pools: a comparison of dark diversity estimates.

Ecological theory and biodiversity conservation have traditionally relied on the number of species recorded at a site, but it is agreed that site richness represents only a portion of the species that can inhabit particular ecological conditions, that is, the habitat‐specific species pool. Knowledge of the species pool at different sites enables meaningful comparisons of biodiversity and provides insights into processes of biodiversity formation. Empirical studies, however, are limited due to conceptual and methodological difficulties in determining both the size and composition of the absent part of species pools, the so‐called dark diversity. We used >50,000 vegetation plots from 18 types of habitats throughout the Czech Republic, most of which served as a training dataset and 1083 as a subset of test sites. These data were used to compare predicted results from three quantitative methods with those of previously published expert estimates based on species habitat preferences: (1) species co‐occurrence based on Beals' smoothing approach; (2) species ecological requirements, with envelopes around community mean Ellenberg values; and (3) species distribution models, using species environmental niches modeled by Biomod software. Dark diversity estimates were compared at both plot and habitat levels, and each method was applied in different configurations. While there were some differences in the results obtained by different methods, particularly at the plot level, there was a clear convergence, especially at the habitat level. The better convergence at the habitat level reflects less variation in local environmental conditions, whereas variation at the plot level is an effect of each particular method. The co‐occurrence agreed closest the expert estimate, followed by the method based on species ecological requirements. We conclude that several analytical methods can estimate species pools of given habitats. However, the strengths and weaknesses of different methods need attention, especially when dark diversity is estimated at the plot level.

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 (4m×4m 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 8m×8m 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.

Invasion of Calluna heath by native and non-native conifers: the role of succession, disturbance and allelopathy

The coastal heathlands of North-western Europe are treeless anthropogenic landscape of high conservation value, now threatened by encroachment by both native (Pinus sylvestris L.) and non-native (Picea sitchensis (Bong) Carr.) conifers. This study wants to gain insight into the different external drivers which interact with the natural successional processes to determine the future development of the heathland landscape. We tested how seedling emergence and establishment is related to competitive effects from the standing vegetation. Heathlands are nutrient-stressed habitats and we tested the seedling emergence and establishment along a nutrient gradient using mean Ellenberg values. In addition we tested if phytotoxic substances are affecting the seedling emergence and establishment related to different successional stages. Study species differed in seed size and we expected different colonization rates and competitive effects from the heathland vegetation. A factorial experiment was carried out in three different successional stages to isolate the effects of competition versus phytotoxins on seedling emergence and establishment by combining vegetation cutting and charcoal addition treatments. Both conifers were able to invade all successional stages, but invasibility decreased during succession. This was largely attributable to competitive effects from the standing vegetation, although phytotoxic effects were also detected, especially in late-successional stages. Seedling emergence and establishment was higher in the larger-seeded P. sylvestris than in P. sitchensis. These results present a management challenge as fire is an important component of the traditional management of the coastal heathlands, while at the same time increasing invasibility. Managers at sites susceptible to invasion should ensure that resources for tree seedling control are available before fire or other management-related disturbances are applied.

Phytosociology and dynamics of calcareous grasslands in Ķemeri National Park, Latvia

Ecology, phytosociology, and regional characteristics of and management effects on calcareous grasslands in Kemeri National Park (Latvia) were studied. The data set included 181 phytosociological releves. According to TWINSPAN division and mean Ellenberg values the releves were classified into four major groups at association level and classified as Sesleria caerulea-Primula veris community (alliance Bromion), Sesleria caerulea-Inula salicina community, Molinietum caeruleae community, and Carex hostiana community (alliance Molinion). Environmental factors were analysed by DCA using the mean Ellenberg values. The variances in species composition were mainly influenced by moisture, the only factor significantly differing among the phytosociological groups. The recent management has not directly affected the present species richness and vegetation structure at community level. Some aspects of grassland dynamics and conservation are discussed.

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.

Changes in species richness and composition in European acidic grasslands over the past 70 years: the contribution of cumulative atmospheric nitrogen deposition

AbstractOur study investigates the negative impact of nitrogen (N) deposition on species richness in acidic grasslands, based on a temporal comparison of vegetation data spanning a period of almost 70 years. We compiled a large data base of plots assigned to the Violion caninae grassland type, composed of managed, but unfertilized semi‐natural grasslands on nutrient‐poor, acidic soils. In total 1114 plots, mainly from Great Britain, the Netherlands and Germany, were compiled, dating back to 1939. Environmental site information included geographical and soil (mean Ellenberg values) variables as well as estimates of cumulative N and sulphur (S) deposition since 1939. Statistical analyses were carried out separately for the data subsets from the three regions. In all regions, the vegetation differentiation was mainly related to soil acidity and nutrient availability, as well as to the year of sampling and the cumulative amounts of N and S deposition. Plot‐species richness of vascular plants and bryophytes (analysed for Great Britain only) decreased with time and analyses suggest these are affected by various factors, notably soil pH, but also latitude and cumulative N deposition. The latter explained more of the variation in species number than the year of sampling and cumulative S deposition, which supports the interpretation that the decline in species richness is mainly caused by increasing N availability and less by altered management and soil acidification. For Great Britain and Germany, cumulative N deposition showed a strong negative relationship with several biodiversity measures, especially the proportion of dicots, whereas it was positively related to the proportion of grass species. In general, our results give temporal evidence for the negative effect of N deposition on species richness in semi‐natural vegetation.

Predicting patterns of invasion by black cherry (Prunus serotina Ehrh.) in Flanders (Belgium) and its impact on the forest understorey community

ABSTRACTThe design of cost‐efficient control strategies for invasive species that are too widespread and abundant for complete eradication, at least in the short term, will benefit from a rigorous analysis of invasion patterns and associated effects on native biodiversity. In this paper, the case of the invasive North American tree Prunus serotina in Flanders (Belgium) is presented. Our main objectives were to determine the susceptibility of forest stands to invasion by P. serotina and the subsequent effects of invasion on the understorey community. We used the large database of the first Flemish Forest Inventory. Multiple logistic regressions indicated that P. serotina occurred more frequently in privately owned, younger forest on coarse‐textured, dry soils (podzols), and the combination of these factors allowed us to correctly predict presence/absence of P. serotina in 70% of the validation plots. However, locational variables proved to be important as well, indicating that the invasion process is still ongoing. Prediction of P. serotina densities by means of multiple linear regressions was less successful. Effects on the understorey richness were analysed by comparing the number of species and the mean Ellenberg values between pairs of plots, only differing by the presence of P. serotina in the shrub layer. A reduction of the understorey richness following invasion was only pronounced on the more moist soils, while compositional changes mainly occurred on drier soils. It is concluded that priority for control should be given to landscapes with a low fraction of invaded stands and to forest stands located on more moist soils. However, using its potential to threaten native biodiversity as an argument for control should be done with care as further research is needed whether the observed negative effects are due to a species (i.e. native vs. non‐native) or a density effect (high vs. low).

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

AbstractA 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.

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 releves 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 releve therefore carry the stamp of their associated syntaxon even though associated abiotic conditions may vary between releves. 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.

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.

The use of ground vegetation and humus type as indicators of soil nutrient regime for an ecological site classification of British forests

In many countries ground vegetation and humus type are used as indicators of forest soil quality, especially nutrient regime. This paper reports the development of such methods for use in British forests, within a new Ecological Site Classification combining climate, soil moisture regime and soil nutrient regime. To develop a field assessment method for soil nutrient regime, a study was made of soil chemistry, humus type and ground vegetation in British forests. Sites were selected in both mature plantations and semi-natural woodlands. Soil and humus profiles were described and the soil was sampled volumetrically for later chemical analysis. Vascular ground vegetation was recorded in quadrats by species cover fraction, and classified according to the existing British National Vegetation Classification. Soils were analyzed for a number of chemical variables. Vegetation data were treated by application of the species indicator values for soil reaction ( R) and soil nitrogen ( N), as proposed by Ellenberg [Vegetation Ecology of Central Europe, 4th Edition. Cambridge University Press, Cambridge]. Site mean indicator values mR and mN (weighted by species cover fraction) were then calculated. Multivariate statistical analysis techniques were applied to both the soil chemical and the vegetation sample data. Soil nutrient regime was shown to be a composite gradient of several soil chemical variables, of which the pH value and the availability of mineral (especially nitrate) nitrogen, and of calcium, were of particular importance. The species composition of the ground vegetation was related to position on this soil nutrient gradient. The vegetation: soil nutrient correlation using the site mean Ellenberg values was satisfactory ( r=0.89), but was improved by using indicator values generated from within the present data. The occurrence of the major humus types (mor, moder and mull) is broadly related to soil nutrient regime defined in this way. Both ground vegetation and humus type can therefore be used as soil nutrient indicators in British forests. A division of the soil nutrient gradient into five classes (Very Poor, Poor, Medium, Rich and Very Rich) is proposed. Future sampling work may lead to the definition of an additional class of soils with carbonate nutrient regimes. The Ecological Site Classification will provide forest managers in Great Britain with an improved basis for the selection of tree species for planting, and the adoption of silvicultural methods best suited to the site.