Aims Classification of vegetation is an essential tool to describe, understand, predict and manage biodiversity. Given the multiplicity of approaches to classify vegetation, it is important to develop international consensus around a set of general guidelines and purpose‐specific standard protocols. Before these goals can be achieved, however, it is necessary to identify and understand the different choices that are made during the process of classifying vegetation. This paper presents a framework to facilitate comparisons between broad‐scale plot‐based classification approaches. Results Our framework is based on the distinction of four structural elements (plot record, vegetation type, consistent classification section and classification system) and two procedural elements (classification protocol and classification approach). For each element we describe essential properties that can be used for comparisons. We also review alternative choices regarding critical decisions of classification approaches; with a special focus on the procedures used to define vegetation types from plot records. We illustrate our comparative framework by applying it to different broad‐scale classification approaches. Conclusions Our framework will be useful for understanding and comparing plot‐based vegetation classification approaches, as well as for integrating classification systems and their sections.

Running headline: Assembly rules along a long stress gradient Summary 1. A central issue of community ecology is finding rules that explain the composition and abundance of co-existing species. Nowadays two main processes, environmental filtering and limiting similarity are thought to play the main roles in structuring communities. Their relative importance under different environmental conditions, however, is still not properly clarified. 2. We studied the strength and the effect of environmental filtering (causing convergence) and limiting similarity (causing divergence) in 137 sample plots along an extremely long environmental gradient ranging from open sand grasslands to highly productive marshes, using a trait based approach. The main environmental gradient (i.e. productivity) was characterised by the Normalized Difference Vegetation Index, an indicator of aboveground live biomass. Cover of the plant species was estimated visually. Values of 11 plant traits were collected from field measurements and databases. Mean and dispersion of the trait values of the plots were quantified by community-weighted means and Rao's quadratic entropy. Trait convergence and divergence were tested by randomization tests, followed by the study of changes in effect size along the productivity gradient by fitting generalized additive mixed models (GAMM). 3. For vegetative traits we found mainly convergence, indicating the filtering effect of environmental constraints, while traits related to regeneration showed divergence. 4. The strength of convergence in vegetative traits generally decreased as productivity grew, indicating that while under harsh conditions environmental constraints strongly limit the possible trait values; under more benign conditions various water and nutrient-use strategies are adaptable. At high productivity, the strength of divergence in regenerative traits decreased. Since the larger diversity of vegetative traits found here reduces competition, the importance of diverse reproductive strategy is probably lower. 5. Synthesis: Our results partly support the stress-dominance hypothesis, but reveal that assembly rules are more complex. The relative importance of environmental filtering and limiting similarity depends on the trait and on the environmental conditions of the habitat. Traits related to resource use are generally limited by environmental filtering, and this restriction is weakening as conditions become more favourable, while traits related to regeneration are constrained by limiting similarity and are more diverse under harsh conditions.

Questions Which environmental and management factors are the most important determinants of arable weed species composition in intensively farmed areas across an area of 93 000 km2? Does the relative importance of environmental and management factors depend on plot location within fields (centre or edge)? Location Hungary. Methods The abundance of late‐summer weed flora and 25 environmental, management and site context factors were measured in 243 maize, sunflower and stubble fields representing the entire country. Data were analysed by redundancy analysis (RDA) after backward variable selection. The gross and net effect on weed species composition were calculated for each variable. Variation partitioning based on RDA was used to assess the relative effects of the three groups of explanatory variables. Results The net effects of 24 variables on species composition were significant, explaining 25% of the total variation in species data. Most variation in species composition was explained by plot location, which was followed by temperature, crop type, precipitation, soil texture, neighbouring habitat, altitude, soil pH, sodium and potassium content of the soil. Variation partitioning revealed that environmental variables accounted for twice more variance than management variables, but the relative impact of management variables was larger in field cores than in field edges. Conclusions Our results suggest that even for intensified agriculture the effects of environmental factors are of greater importance than management factors on summer arable weed composition in a country‐wide context. The effects of intensive crop management decrease towards the field periphery.

No abstract

S. (2019) Formalized classification of semi-dry grasslands in central and eastern Europe.-Preslia 91: 25-49 European semi-dry grasslands are among the most species-rich vegetation types in the northern hemisphere and form an important part of the habitat mosaics in the forest-steppe zone. However, there is no comprehensive evaluation of the variation in their composition and the phytosociological classification of these grasslands. For the syntaxonomic revision, we used a dataset of 34,173 vegetation plot records (relevés) from central and eastern Europe, which were assigned to the class Festuco-Brometea using the diagnostic species listed in the EuroVegChecklist. To determine the diagnostic species of the orders, we used a TWINSPAN classification of the whole dataset. Of the total dataset, 15,449 relevés were assigned to the order Brachypodietalia pinnati, which corresponds to semi-dry grasslands. This subset was again classified using TWINSPAN. Formal definitions of the following alliances were established: Mesobromion erecti, Cirsio-Brachypodion pinnati (incl. Fragario-Trifolion montani, Agrostio-Avenulion schellianae, Scabioso ochroleucae-Poion angustifoliae and Adonido vernalis-Stipion tirsae), Scorzonerion villosae and Chrysopogono-Danthonion. Another alliance, Armerion elongatae (= Koelerio-Phleion phleoidis p.p.), is transitional towards the class Koelerio-Corynephoretea and its status needs further evaluation. We also established formal definitions of all of the associations of Mesobromion and Cirsio-Brachypodion within the area studied. Associations were identified using (i) a TWINSPAN classification of the whole order, (ii) TWINSPAN classifications of regionally restricted data sets (usually all Brachypodietalia plots in one country) and (iii) existing national classification schemes. All formal definitions were written in the expert system language of the JUICE program. To obtain a more complete picture of the floristic similarities and gradients, we performed a DCA ordination of the associations. Our results revealed that meadow steppes in the forest-steppe zone in eastern Europe are very similar to semi-dry grasslands in central Europe.

Aim: Phytosociological databases often contain unbalanced samples of real vegetation, which should be carefully resampled before any analyses. We propose a new resampling method based on species composition, called heterogeneityconstrained random (HCR) resampling.Method: Many subsets of the source vegetation database are selected randomly. These subsets are sorted by decreasing mean dissimilarity between pairs of the vegetation plots, and then sorted again by increasing variance of these dissimilarities. Ranks from both sortings are summed for each subset, and the subset with the lowest summed rank is considered as the most representative. The performance of this method was tested using simulated point patterns that represented different levels of aggregation of vegetation plots within a database. The distributions of points in the subsets resulting from different resampling methods, both with and without database stratification, were compared using Ripley's K function. The mean of random selections from an unbiased sample was used as a reference in these comparisons. The efficiency of the method was also demonstrated with real phytosociological data.Results: Both stratified and HCR resampling yielded selection patterns more similar to the reference than resampling without these tools. Outcomes from the resampling that combined these two methods were the most similar to the reference. The efficiency of the HCR resampling method varied with different levels of aggregation in the database. Conclusions:This new method is efficient for resampling phytosociological databases. As it only uses information on species occurrences/abundances, it does not require the definition of strata, thereby avoiding the effect of subjective decisions on the selection outcome. Nevertheless, this method can also be applied to stratified databases.

Cluster analysis plays vital role in pattern recognition in several fields of science. Silhouette width is a widely used index for assessing the fit of individual objects in the classification, as well as the quality of clusters and the entire classification. Silhouette combines two clustering criteria, compactness and separation, which imply that spherical cluster shapes are preferred over others—a property that can be seen as a disadvantage in the presence of complex, nonspherical clusters, which is common in real situations. We suggest a generalization of the silhouette width using the generalized mean. By changing the p parameter of the generalized mean between −∞ and +∞, several specific summary statistics, including the minimum, maximum, the arithmetic, harmonic, and geometric means, can be reproduced. Implementing the generalized mean in the calculation of silhouette width allows for changing the sensitivity of the index to compactness versus connectedness. With higher sensitivity to connectedness, the preference of silhouette width toward spherical clusters should reduce. We test the performance of the generalized silhouette width on artificial data sets and on the Iris data set. We examine how classifications with different numbers of clusters prepared by different algorithms are evaluated, if p is set to different values. When p was negative, well‐separated clusters achieved high silhouette widths despite their elongated or circular shapes. Positive values of p increased the importance of compactness; hence, the preference toward spherical clusters became even more detectable. With low p, single linkage clustering was deemed the most efficient clustering method, while with higher parameter values the performance of group average, complete linkage, and beta flexible with beta = −0.25 seemed better. The generalized silhouette allows for adjusting the contribution of compactness and connectedness criteria, thus avoiding underestimation of clustering efficiency in the presence of clusters with high internal heterogeneity.

Perceptual animacy is the tendency for observers to represent inanimate objects as animate, based on simple motion cues. Several features of the chasing pattern can elicit animacy perception and, similarly to adult humans, dogs perceive dots showing this pattern as animate. Here, we used moving objects with a heading alignment (isosceles triangles) to investigate whether human and dog behavior continues to show similarities following such slight but important change in the pattern. We hypothesized that a heading alignment would facilitate animacy perception in both species in a similar manner. We displayed chasing and nonchasing (independent) motions side-by-side on a screen in two subsequent trials (Trial 1 and 2). Looking duration at each pattern as well as frequency of gaze shifting between the patterns was measured. Humans looked at the independent motion for longer already during Trial 1; however, dogs looked at this pattern longer only during Trial 2, whereas during Trial 1, their looking time increased toward the chasing pattern. Gaze shifting was observed in humans more often in both trials than in dogs. Although ultimate preference for the independent motion suggests rapid perception of the chasing pattern directing gaze in both species toward the “unrecognized” pattern, there was an initial interspecies difference. We suggest that different behavior across humans and dogs could be explained by ecological differences, although the role of differences in visual strategies, irrespective of perception of animacy, cannot be excluded.