Average Ellenberg Indicator Values Research Articles

Diversity and ecology of forest communities in Küre Mountains National Park of Turkey

This study aimed at analyzing the diversity and ecological characteristics of forest associations (121 releves classified under eight associations) in Kure Mountains National Park. Ordination analyses (DCA and CCA) and response curves were used to reveal ecological characteristics of vegetation using soil parameters (pH, electrical conductivity, sand, clay and dust content, soil moisture) and topographical variables (altitude, slope, potential direct incident radiation and heat load). Ecological conditions of communities were also tested using average Ellenberg indicator values (EIVs). Among forest associations, the highest species diversity was found in Phillyreo latifoliae-Pinetum brutiae and the lowest diversity in Hedero-Castanetum sativae, which had a dense Rhododendron ponticum shrub layer. However, Salicio-Platanetum orientale and Buxo sempervirens-Carpinetum betuli had the highest beta diversity since they harbored unique species composition. Conditional effects of altitude, slope, pH and electrical conductivity, soil dust and sand content, sandy-loam and loam soil types presented significant contributions in species composition. While Carpino-Quercetum petraeae was found on soil with high dust content having high pH and electrical conductivity values, Quercetum roburi-Aceretum campestri and Salicio-Platanetum orientale were related to soil with loam. Species responses to soil and topographical variables varied for most tree species. Light EIVs, which has a high positive correlation with potential direct incident radiation and heat load, related to Phillyreo latifoliae-Pinetum brutiae and Salicio-Platanetum orientale. Riverside forest communities differed from other communities in nutrient and humidity EIVs. However, EIVs did not show a good correlation with associated soil parameters such as soil moisture-humidity EIVs and soil pH-acidity EIVs.

Understanding the importance of spatial scale in the patterns of grassland invasions

The invasion of alien plant species is a serious problem for conservation and the maintenance of biodiversity in grasslands. Therefore, it is important to find environmental factors correlated with the distribution of invasive species in such areas. In this study, we examined the impacts of environmental factors operating at different spatial scales on the distribution of invasive species. The study area were located in the Sudetes Mountains, Poland (3800 km2). We sampled field data from 163 random plots located in grassland, among which there were 94 plots with invasive species and 69 plots without invasive species. For each plot, we collected data on resident vegetation (species richness, community structure), geodiversity (topography, soil type), environmental heterogeneity (landscape structure) and climate (temperature and precipitation). Since the factors examined are likely to operate at different spatial scales, we calculated values of environmental variables with different spatial scopes (10m2 plot and buffers with 50, 250 and 1250 m radii). The probability of invasive plant presence was modeled using boosted regression trees (BRT). The results of our study showed that the distribution of invasive species is explained by factors operated at different spatial scale: in the finer scale the presence of invasive species was driven predominantly by the average Ellenberg's Indicator Values for soil moisture, in medium-scale by the average topographic wetness index and sum of edges, while at coarse-scale by temperature. It was also presented that the effect of drivers operating at fine-spatial scale is overwhelming by effect of drivers operating at coarse scale. From a practical point of view, the results demonstrate that effective grassland management should be planned on a larger spatial context, because focussing on the management of a single site cannot be successful.

Long-term effects of liming on the species composition of the herb layer in temperate Central-European forests

Upon the occurrence of acidic deposition-driven damage to forests at the beginning of the 1980s, large-scale liming has been applied to acidic forest sites in Germany. Due to possible negative consequences on soil chemistry and on (soil) fauna and flora, this measure was discussed highly controversially right from the beginning and is disputed until today. In investigations of liming effects on the forest understory vegetation, very few studies covered a time period of more than two decades with intermittent relevés. We analyzed relevés of the herbal understory on limed and control plots in one pine (Pinus sylvestris), one oak (Quercus robur), two European beech (Fagus sylvatica) and five Norway spruce (Picea abies) stands at permanent observation sites in south-western Germany. These relevés had been repeatedly conducted during approximately 25 years.The number of herbal plant species was generally low. An increase in the herb layer's plant cover with time was found at six out of the nine study sites and was mainly due to spreading of two grass species (Milium effusum, Deschampsia flexuosa) and of the subshrub Vaccinium myrtillus, which might have benefitted from continuous nitrogen deposition. Only two species (Agrostis stolonifera, Stellaria media) with a main distribution in open landscapes were found in the years of investigation and their occurrence was restricted to only four sites and some few years.Across all sites, the average Ellenberg indicator values of nutrient (nitrogen) supply (N-values) were significantly increased on the limed plots ten years after liming, and at Year 10, the N-values of the limed plots were significantly higher than that of the control, presumably due to increased decomposition rates after liming. At the spruce sites, the average Ellenberg indicator values of soil reaction (R-values) of the limed plots 10 years after liming were significantly higher than at the beginning (Year 0) and at the end of the investigation (2013). We found no significant differences among the Ellenberg indicator values of light condition (L-values).In conclusion, liming had a significant, but only transient effect on the composition of the understory species. Therefore, our results do not support arguments against liming of acidic forests that are based on long-term changes in the herbal flora. In managed forests for wood production on acidic soils, liming can continue contributing to buffer the soils against ongoing acidification and accompanying cation leaching caused by anthropogenic deposition of nitrogen.

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.

Airborne laser scanner (LiDAR) proxies for understory light conditions

Canopy cover and canopy closure are two closely related measures of vegetation structure. They are used for estimating understory light conditions and their influence on a broad range of biological components in forest ecosystems, from the demography and population dynamics of individual species to community structure. Angular canopy closure is more closely related to the direct and indirect light experienced by a plant or an animal than vertical canopy cover, but more challenging to estimate. We used airborne laser scanner (ALS) data to estimate canopy cover for 210 5-m radius vegetation plots in semi-open habitats and forests in protected nature areas in Denmark. The method was based on the area of Thiessen (Voronoi) polygons generated from the ALS points. We also estimated angular canopy closure by transforming ALS points from Cartesian to spherical coordinates, and calculating the percentage of azimuth and zenith angle intervals which contained points. We compared these estimates with field-based estimates using densiometer for 60 vegetation plots in forest. Finally, we compared ALS-based estimates of canopy cover and canopy closure to field-based estimates of understory light, based on the average Ellenberg indicator values for light for the plant species present in a given plot. The correlations of Ellenberg values with ALS-based canopy closure were higher (r2: 0.47) than those with ALS-based canopy cover (r2: 0.26) and densiometer readings (r2: 0.41) for the forest sites. ALS-based canopy closure is thus a reasonable indicator of understory light availability and has the advantage over field-based methods that it can be rapidly estimated for extensive areas.

Application of the Ancient Forest Concept to Potential Natural Vegetation Mapping in Flanders, A Strongly Altered Landscape in Northern Belgium

Construction of potential natural vegetation (PNV) poses particular challenges in landscapes heavily altered by human activity and must be based on transparent, repeatable methods. We integrated the concept of ancient forest (AF) and ancient forest species (AFS) into a four-step procedure of PNV mapping: 1) classification of forest vegetation releves; 2) selection of those vegetation types that can serve as PNV units, based on AF and AFS; 3) merging of selected vegetation types into five PNV units that can be predicted from a digital morphogenetic soil map; 4) mapping of three additional PNV units based on additional environmental data. The second step, concerning the selection of reference forest vegetation, is of particular interest for PNV construction in Flanders (northern Belgium), where forest cover has been subject to temporal disruption and spatial fragmentation. Among the variety of extant forest recovery states, we chose as PNV units those vegetation types for which a high proportion of releves had been located in AF and that contained many AFS. As the frequency of AFS depends on site conditions, we only compared and selected vegetation types that are found on similar sites according to average Ellenberg indicator values. While succession is irrelevant for the definition of PNV, colonization rates of AFS can be used to estimate the time required for PNV to be restored in a site.

Spontaneous restoration of target vegetation in old‐fields in a central European landscape: a repeated analysis after three decades

AbstractQuestions(a) What are directions of spontaneous succession; in particular, do target stages (identified as shrubby grassland and semi‐natural deciduous woodland) develop, and if so, which species are involved? (b) Are the target stages predictable? (c) How do species richness and environmental characteristics change during succession? (d) What are the consequences for restoration and landscape management?LocationThe Bohemian Karst Protected Landscape Area, SW of Prague, Czech Republic (49° 52′–50° 00′ N, 14° 03′–14° 21′ E, 251–488 m a.s.l.).MethodsIn a repeated analysis, phytosociological relevés recorded in 4 m × 4 m plots in 58 old‐fields initially surveyed in 1975 were compared to those from 28 still existing fields in 2008–2009. Average Ellenberg indicator values were calculated for each relevé. Aspect and slope were measured and potential radiation calculated. pH was measured from soil samples. Species were grouped according to their affiliation to the phytosociological classes Querco‐Fagetea, Festuco‐Brometea, Trifolio‐Geranietea, Molinio‐Arrhenatheretea, and weedy and ruderal vegetation. Those belonging to the first three classes were considered target species. The data were analysed using multivariate (ordination methods) and univariate statistics.ResultsThe spontaneous succession in old‐fields proceeded towards target stages, either deciduous woodlands or shrubby grasslands. Their establishment can be tentatively predicted by soil pH and early occurrence of grassland species. Except pH, all Ellenberg indicator values changed during succession. pH values (Ellenberg and measured) were higher in shrubby grasslands than in woodlands. The total number of species decreased during succession, the number of target woodland species increased, and target grassland species remained the same in the shrubby grassland stages but decreased in the woodland stages during the past 33 yr of succession.ConclusionsTarget shrubby grasslands, resembling natural steppe‐like communities typical of the region and valuable from a conservation point of view, can be restored by spontaneous succession within a few decades in about one‐third of the studied old‐fields. Other fields developed into deciduous woodland. Restoration of well‐developed target woodland will take longer, but the trend is already obvious, although less desirable nitrophilous woodland might also alternatively develop. Repeating earlier chronosequence studies may provide valuable information useful in restoration ecology and landscape management.

Modelling effective thermal climate for mountain forests in the Bavarian Alps: Which is the best model?

AbstractQuestion: Which thermal climate model performs best in predicting the combined effects of temperature and radiation on forest vegetation in the Bavarian Alps?Location: Bavarian Alps, Germany.Methods: In order to find the best model for effective thermal climate for the Bavarian Alps, we analysed models using the following predictors derived from climate data and/or a digital elevation model: (a) temperature variables only, (b) temperature plus slope aspect and inclination, and (c) temperature plus potential global solar radiation. Models were tested by linear regression against four response variables based on average Ellenberg indicator values for temperature (cover weighted/unweighted, with/without bryophytes), which were computed for 2280 georeferenced relevés from the vegetation database BERGWALD. We optimized (b) by empirically searching for thermally most favourable slope aspect and inclination.Results: Closest model fit was achieved for unweighted temperature values based on vascular plants without bryophytes. Model fit (adj. R2) increased from using temperature alone to temperature–radiation, to temperature–aspect–inclination as predictors. The best spatially explicit model for predicting temperature values (adj. R2=0.57) was based on the variable combination mean temperature in the growing season (May to September), slope aspect (optimal aspect 195°) and inclination (optimal slope 30°).Conclusion: Combining mean temperatures and relief variables in GIS allows creation of predictive maps of mountain forest response to thermal climate. Applied to climate change scenarios, our model can forecast potential vegetation distribution in the future. The superiority of simple empirical relief factors over a widely used model of potential radiation casts doubt on the meaningfulness of the latter for vegetation studies.

Ecological preferences of alien plant species in North-Eastern Germany

The large, comprehensive vegetation database of Mecklenburg-Vorpommern/NE Germany with 51,328 releves allowed us to study an entire regional flora of 133 non-native plants (NNP, immigration after 1492 AD) with regard to their preferences to all kinds of habitats and along different ecological gradients. For each releve, we computed average Ellenberg indicator values (EIV) for temperature, light, moisture, reaction, nutrients and salt as well as plant strategy type weights. We partitioned the dataset into releves with and without occurrences of NNP and compared them with respect to the relative frequencies of EIVs and strategy type weights. We identified deviations from random differences by testing against permuted indicator values. To account for bias in EIV between community types, NNP preferences were differentiated for 34 phytosociological classes. We tested significance of preferences for the group of NNP as a whole, as well as for single NNP species within the entire dataset, as well as differentiated by phytosociological classes and formations. NNP as a group prefer communities with high EIVs for temperature and nutrients and low EIVs for moisture. They avoid communities with low EIV for reaction and high EIV for salt. NNP prefer communities with high proportions of ruderal and low proportion of stress strategists. The differentiation by phytosociological classes reinforces the general trends for temperature, nutrients, moisture, R and S strategy types. Nevertheless, preferences of single species reveal that NNP are not a congruent group but show individualistic ecological preferences.

Syntaxonomy and ecology of forest vegetation in the Štiavnické vrchy Mts (Central Slovakia)

Vegetation of deciduous forests in the Štiavnické vrchy Mts (Central Slovakia) was studied using the standard Zürich-Montpellier approach. The numerical classification and ordination technique were applied to determine the main forest vegetation types and to find the responsible environmental drivers related to their distribution patterns, respectively. The data set including 198 relevés collected by authors in 1997-2009 and 185 relevés excerpted from literature was used to analysis. Numerical classification resulted in delimitation of fourteen vegetation types representing eleven associations with two variants and two communities within the Quercetea robori-petraeae and Querco-Fagetea classes. The major environmental gradients in variation of forest species composition were associated with moisture and nutrient content following the average Ellenberg indicator values. Along the moisture gradient, vegetation types were ordered from subxerophilous oak forests turn mesophilous mixed oak-hornbeam, beech and ravine forests to hygrophilous riparian alder forest. The results confirmed important role of soil nutrients and moisture by determination of forest vegetation in subcontinental part of Central Europe. Special attention was given to the discussion of floristical characteristics, site conditions and syntaxonomy.

Using topographic wetness index in vegetation ecology: does the algorithm matter?

AbstractQuestions: How important is the choice of flow routing algorithm with respect to application of topographic wetness index (TWI) in vegetation ecology? Which flow routing algorithms are preferable for application in vegetation ecology?Location: Forests in three different regions of the Czech Republic.Methods: We used vegetation data from 521 georeferenced plots, recently sampled in a wide range of forest communities. From a digital elevation model, we calculated 11 variations of TWI for each plot with 11 different flow routing algorithms. We evaluated the performance of differently calculated TWI by (1) Spearman rank correlation with average Ellenberg indicator values for soil moisture, (2) Mantel correlation coefficient between dissimilarities of species composition and dissimilarities of TWI and (3) the amount of variation in species composition explained by canonical correspondence analysis.Results: The choice of flow routing algorithm had a considerable effect on the performance of TWI. Correlation with Ellenberg indicator values for soil moisture, Mantel correlation coefficient and explained variation doubled when the appropriate algorithm was used. In all regions, multiple flow routing algorithms performed best, while single flow routing algorithms performed worst.Conclusions: We recommend the multiple flow routing algorithms of Quinn et al. and Freeman for application in vegetation ecology.

Variability of the Molinion meadows in Slovakia

Nine vegetation types were distinguished using cluster analysis within Molinion meadows in Slovakia. Vegetation of cluster 1 occurs on most acidic soils and is characterized by the occurrence of species of the Caricion fuscae alliance and of the Nardus grasslands. Vegetation of cluster 2 is also found on rather acidic soils but in contrast to cluster 1 vegetation it contains species of base-rich sites, such as Betonica officinalis, Galium boreale or Serratula tinctoria. Vegetation of cluster 3 occurs in wet base-rich habitats and often contains species of the Caricion davallianae alliance. Species of dry and Nardus grasslands are typical for vegetation of cluster 4, which is found at the driest sites and is confined to oligotrophic sandy soils. Vegetation of clusters 5 and 6 occurs on moist mesotrophic soils. Their species composition is quite similar, the main difference being that the former includes species-poor releves and the latter includes species-rich releves. Releves of cluster 7 include species of dry grasslands and some ruderal species and represent degraded types of inundated floodplain meadows of the Deschampsion alliance. Vegetation of clusters 8 is characterized by species of the Phragmito-Magnocaricetea class and of the Deschampsion alliance, and occurs in wet nutrient-rich habitats. Vegetation of cluster 9, which usually develops from vegetation of cluster 8 due to decrease in the ground-water table, often contains species of dry grasslands and mesic meadows. Except for releves of clusters 1 and 7, all others can be assigned to the Molinietum caeruleae Koch 1926 association. Cluster 1 corresponds to the Junco effusi-Molinietum caeruleae Tuxen 1954 association. Average Ellenberg indicator values for releves, which were passively projected on the ordination biplot of detrended correspondence analysis, showed that the first ordination axis correlates with nutrients, soil base status and temperature, and second axis with moisture.

Measurement errors and regression to the mean cannot explain bias in average Ellenberg indicator values

AbstractSmart & Scott (2004, this is sue) criticized our paper (Wamelink et al. 2002) about the bias in average Ellenberg indicator values. Their main criticism concerns the method we used, regression analysis. They state the bias can be mimicked by the construction of an artificial data set and that regression analysis is not a suited tool to investigate underlying phenomena. Moreover they claim that the present bias is caused by the distribution of Ellenberg indicator values between syntaxa, instead of a bias in average Ellenberg indicator values per species. We show that their criticism of the use of regression analysis does not hold. We selected average Ellenberg values per vegetation group for several pH classes and applied an F‐test to determine whether or not the vegetation groups within each pH class differed significantly from each other. This was the case for all tested classes (P < 0.001). Moreover we simulated an artificial data set, of which the F‐test for varying measurement error could not explain the magnitude of the F‐value we found earlier. This indicates that the bias we found in average Ellenberg indicator values cannot be explained by measurement errors or by regression to the mean. In the end, Smart & Scott, as we did, come to the conclusion that there is a bias present and that separate regression lines per vegetation type are necessary, but the debate remains open on whether or not this is caused by the bias in Ellenberg indicator values per species.

Measurement errors and regression to the mean cannot explain bias in average Ellenberg indicator values

Measurement errors and regression to the mean cannot explain bias in average Ellenberg indicator values

JUICE, software for vegetation classification

Abstract. The program JUICE was designed as a Microsoft® WINDOWS® application for editing, classification and analysis of large phytosociological tables and databases. This software, with a current maximum capacity of 30 000 relevés in one table, includes many functions for easy manipulation of table and header data. Various options include classification using COCKTAIL and TWINSPAN methods, calculation of interspecific associations, fidelity measures, average Ellenberg indicator values, preparation of synoptic tables, automatic sorting of relevé tables, and export of table data into other applications (word processors, spreadsheet programs or mapping packages). JUICE is optimized for use in association with TURBOVEG which is the most widespread database program for storing phytosociological data in Europe.

JUICE, software for vegetation classification

Abstract The program JUICE was designed as a Microsoft® WINDOWS® application for editing, classification and analysis of large phytosociological tables and databases. This software, with a current maximum capacity of 30 000 releves in one table, includes many functions for easy manipulation of table and header data. Various options include classification using COCKTAIL and TWINSPAN methods, calculation of interspecific associations, fidelity measures, average Ellenberg indicator values, preparation of synoptic tables, automatic sorting of releve tables, and export of table data into other applications (word processors, spreadsheet programs or mapping packages). JUICE is optimized for use in association with TURBOVEG which is the most widespread database program for storing phytosociological data in Europe.

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.