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We compared results derived using three different approaches to assess the suitability of common tree species on the Franconian Plateau in southern Germany under projected warmer and drier climate conditions in the period 2061-2080. The study area is currently a relatively warm and dry region of Germany. We calculated species distribution models (SDMs) using information on species’ climate envelopes to predict regional species spectra under 63 different climate change scenarios. We complemented this with fine-scale ecological niche analysis using data from 51 vegetation surveys in seven forest reserves in the study area, and tree-ring analysis (TRA) from local populations of five tree species to quantify their sensitivity to climatic extreme years. The SDMs showed that predicted future climate change in the region remains within the climate envelope of certain species (e.g. Quercus petraea), whilst for e.g. Fagus sylvatica, future climate conditions in one third of the scenarios are too warm and dry. This was confirmed by the TRA: sensitivity to drought periods is lower for Q. petraea than for F. sylvatica. The niche analysis shows that the local ecological niches of Quercus robur and Fraxinus excelsior are mainly characterized by soils providing favorable water supply than by climate, and Pinus sylvestris (planted) is strongly influenced by light availability. The best adapted species for a warmer and potentially drier climate in the study region are Acer campestre, Sorbus torminalis, S. aria, Ulmus minor, and Tilia platyphyllos, which should therefore play a more prominent role in future climate-resilient mixed forest ecosystems.

Aims The community‐weighted mean (CWM) approach is used to analyse the relationship between species attributes (traits, Ellenberg‐type indicator values) and sample attributes (environmental variables, richness) via the community matrix. It has recently been shown to suffer from inflated Type I error rate if tested by a standard test and the results of many published studies are probably affected. I review the current knowledge about this problem, and clarify which studies are likely affected and by how much. Methods I suggest classifying hypotheses commonly tested by CWM approach into three categories, which differ in the formulation of the null hypothesis. I use simulated and real data to show how the Type I error rate of the standard test is affected by data characteristics. Results The CWM approach with the standard test returns a correct Type I error rate for hypotheses assuming a link between species attributes and composition (Category A). However, for hypotheses assuming a link between composition and sample attributes (Category B) or not assuming any link (Category C), the standard test is inflated, and alternative tests are needed to control for this. The inflation of standard tests for Category C is negatively related to the compositional β‐diversity, and positively to the strength of the composition–sample attributes relationship and data set sample size. These results apply to CWM analyses with extrinsic sample attributes (not derived from the compositional matrix). CWM analysis with intrinsic sample attributes (derived from the composition, such as species richness) is a case of spurious correlation and can be tested using a column‐based (modified) permutation test. Conclusions The concept of three hypothesis categories offers a simple tool to evaluate which hypothesis has been tested and whether the results have correct or inflated Type I error rate. In the case of inflated results, the level of inflation can be estimated from the data characteristics. Community weighted mean approach tests the relationship of species attributes (traits, indicator values) to sample attributes (environmental variables, richness) and the test is known to have inflated Type I error rate. I argue that whether test results are inflated depends on the type of tested hypothesis and that the level of inflation depends on dataset parameters (e.g. beta diversity).

With the phytocenological research of riparian mixed forests and pannonic woods in the Podunajská nížina in 2018 and 2019, we obtained 113 phytocenological relevés of invaded and non-invaded stands. Using the Modified Permutation Test, we derived modified Ellenberg indication values (EIVs) in order to determine statistically significant differences and correlation relationships between diversity indices and EIVs. We recorded 15 invasive species in the stands, for example, and . We also confirmed the occurrence of species important for conservation: agg., and the like. We tested the statistical significance of EIVs as explanatory variables by redundancy analysis and Monte Carlo permutation test (stepwise selection, number of permutations 499, < 0.05). In addition to the EIV continentality, the contribution of light, moisture, nutrients, soil reaction and temperature was higher than random. The model explains 20.21% of the variability pursuant to the coefficient of determination ( ), with its adjusted (more accurate) variant ( ) capturing 15.70% of the variability of the model. Using the Kruskal–Wallis test, we confirmed the statistically significant differences ( *) in mean values between count of species, Shannon–Wiener index, Simpson dominance index and taxonomic diversity of invaded and non-invaded vegetation. For EIVs, we found significant differences in the mean values for moisture and soil reaction factors. In our model, count of species, Shannon–Wiener index, Simpson dominance index and taxonomic diversity index were positively correlated with . Non-invaded stands showed statistically significant negative correlation with the EIVs moisture, soil reaction and nutrients. Biotic indices are appropriate and sensitive metrics for assessing the rate of community invasion. Lowland riparian forests are dynamic ecosystems through the structure of their stands and the dynamics of the nutrient and energy cycle of the river landscape. After disturbance (fire, wind, logging), the high degree of invasibility makes them vulnerable to the infiltration and spread of non-native species, which is a problem, especially in protected areas.

Abandoned croplands can be considered a new category of »scattered elements« of mountain landscapes. To gain a deeper understanding of the conservation status (sensu EEC Directive 92/43) of abandoned cropland in the northern Apennines, we used the concept of the social behavior type (SBT) of plant communities. SBTs refer to the behaviour and ecological attributes of species at a given observation level and allow the understanding of the plant community conservation status. We found that topographic and soil conditions drive species assemblage in pastures after crop abandonment, but that long-term abandonment does not lead to the recovery of the semi-natural grassland communities deemed worthy of conservation in the EEC Directive. It was mainly the lack of appropriate disturbance regimes that allowed the spread of dominant tall herbs, which, in turn, reduced site suitability for subordinate plants. Moreover, their spread fostered the presence of elements such as ruderals and fringe species. We concluded that these abandoned croplands had a good potential to develop into a Habitat as defined in the EU Directive but without appropriate management plans they would remain of low representativeness.

In salt marshes, species richness changes along environmental, disturbance and productivity gradients forming a complex network of abiotic and biotic factors. On 2,691 plots along 121 transects, we sampled vegetation along the German mainland North Sea coast (13 regions) during 1987-1989. Applying regression tree analysis (RTA), we now used this large data set to analyse variance in species richness (SRich) in relation to 13 explanatory variables varying on different scales. SRich (mean, 4.9 per m²) was significantly correlated to most variables. Only six variables were included in our final model, together explaining 68.5 % of variance in SRich, in hierarchical order: moisture, salinity, evenness, nitrogen, region and elevation. Predominantly, SRich was limited by environmental heterogeneity (moisture, salinity and nitrogen, each explained approx. 50 % variance). SRich tended to be high on plots exhibiting a combination of low moisture, salinity and nitrogen values, with high evenness—and especially high in some regions when plots were lying high in relation to mean high tide. Grazing regimes did not affect SRich significantly. In conclusion, our model showed that SRich in the study area was predominantly explained on a small scale and less along large-scale gradients. RTA proved suitable to identify the set of variables that mainly explained variance in SRich. Our tree model improves the understanding of richness patterns in salt marshes and can be used to predict species richness for the study area. Furthermore, our data provide a reference to detect richness changes due to, for example, management changes or sea level rise.

Recent analyses of plant traits across large sets of species have revolutionized our understanding of plant functional differentiation. However, understanding of ecological relevance of this differentiation is contingent upon knowledge of environmental preferences of species, namely along gradients of disturbance and productivity for which no quantitative data were available until recently. We examined the relationships of key functional traits (life‐history categories, leaf‐height‐seed (LHS) traits, clonal growth and bud bank traits) in the herb‐dominated flora of Central Europe to species niche positions along the gradients of disturbance frequency, disturbance severity and productivity. Life‐history categories and bud bank size showed the strongest response to disturbance and productivity, whereas relationship of LHS traits was much weaker. A number of traits, including clonal growth form and bud bank size, showed a significantly unimodal response to disturbance frequency. Responses of many traits to disturbance frequency were different from their responses to disturbance severity. Our findings support the notions that disturbance and productivity are key gradients of species functional differentiation and that disturbance severity and frequency select for different trait suites. Furthermore, the data indicate that in a predominantly herbaceous flora, the traits of life span, clonal growth and resprouting show stronger relationship with the environment than the LHS traits, which are more important in floras with high proportions of woody species. Since most previous trait analyses are based on woody‐plant‐dominated floras, patterns revealed in a herb‐dominated flora deepen our understanding of the full range of variation within the plant kingdom. A plain language summary is available for this article. Plain Language Summary

Fungi are known to exert a significant influence over soil organic matter (SOM) turnover, however understanding of the effects of fungal community structure on SOM dynamics and its consequences for ecosystem fertility is fragmentary. Here we studied soil fungal guilds and SOM decomposition processes along a fertility gradient in a temperate mountain beech forest. High-throughput sequencing was used to investigate fungal communities. Carbon and nitrogen stocks, enzymatic activity and microbial respiration were measured. While ectomycorrhizal fungal abundance was not related to fertility, saprotrophic ascomycetes showed higher relative abundances under more fertile conditions. The activity of oxidising enzymes and respiration rates in mineral soil were related positively to fertility and saprotrophic fungi. In addition, organic layer carbon and nitrogen stocks were lower on the more fertile plots, although tree biomass and litter input were higher. Together, the results indicated a faster SOM turnover at the fertile end of the gradient. We suggest that there is a positive feedback mechanism between SOM turnover and fertility that is mediated by soil fungi to a significant extent. By underlining the importance of fungi for soil fertility and plant growth, these findings furthermore emphasise the dependency of carbon cycling on fungal communities below ground.

Arthropods respond to vegetation in multiple ways since plants provide habitat and food resources and indicate local abiotic conditions. However, the relative importance of these factors for arthropod assemblages is less well understood. We aimed to disentangle the effects of plant species composition and environmental drivers on arthropod taxonomic composition and to assess which aspects of vegetation contribute to the relationships between plant and arthropod assemblages. In a multi-scale field study in Southern Germany, we sampled vascular plants and terrestrial arthropods in typical habitats of temperate landscapes. We compared independent and shared effects of vegetation and abiotic predictors on arthropod composition distinguishing between four large orders (Lepidoptera, Coleoptera, Hymenoptera, Diptera), and five functional groups (herbivores, pollinators, predators, parasitoids, detritivores). Across all investigated groups, plant species composition explained the major fraction of variation in arthropod composition, while land-cover composition was another important predictor. Moreover, the local habitat conditions depicted by the indicator values of the plant communities were more important for arthropod composition than trophic relationships between certain plant and arthropod species. Among trophic groups, predators showed the strongest response to plant species composition, while responses of herbivores and pollinators were stronger than those of parasitoids and detritivores. Our results highlight the relevance of plant community composition for terrestrial arthropod assemblages across multiple taxa and trophic levels and emphasize the value of plants as a proxy for characterizing habitat conditions that are hardly accessible to direct environmental measurements.

Summary Ellenberg indicator values (EIVs) can be used as a numerical system to classify species’ habitat niches and their peak occurrence along gradients. By finding correlations of EIVs with morphological or ecophysiological properties, it is possible to identify determinants of species distributions with respect to environmental factors. We surveyed existing literature containing species comparisons from controlled experiments and combined them with EIVs. The picture emerging is that multiple determinants can be identified for nutrient numbers (N), soil reaction numbers (R) and also soil moisture numbers (M), while only few can be found for light numbers (L) and especially for continentality (C) and temperature numbers (T). Functional characterizations of the different EIV can thus be deduced which help to understand the mechanisms and processes driving the ecological niche of a plant. The described approach is a powerful tool to analyse the ecological significance of different plant properties. Species screenings specifically designed to allow for correlations with EIV have large potential for high explanatory power. Lay Summary