The Fitness Check of the Birds and Habitats Directives: A discourse analysis of stakeholders’ perspectives

In 2015, the European Union’s Birds and Habitats Directives underwent an evaluation in which selected national stakeholders provided their perspectives on the directives’ implementation. Analyzing the views of different stakeholder groups from eight European member states, this study found that these views could be synthesized into three more general perspectives. The first perspective focuses on problems, indicating that these are caused by legislative drawbacks in the directives. The second perspective holds that problems are generated by improper implementation by member states. The third perspective commends the benefits of the directives in face of the existing implementation problems. Interest groups and to a minor extent governmental bodies espoused the first perspective, and environmental non-governmental organizations especially favored the third. The struggle between these three perspectives reflects ongoing debates regarding positive and negative aspects of the directives and possibilities for improving their implementation. We conclude that the relevance and impact of conservation policies should never be seen as self-evident. In order to reach the conservation goals envisaged, continuous efforts are needed to enforce and maintain environmental legislation.     

Using regression trees to predict alpha diversity based upon geographical and habitat characteristics

Different environmental factors act as driving forces of diversity at different scales of analysis; and also the effect of one environmental factor changes as the scale of analysis changes. Most studies rely on multiple regression models, and such models tend to mix-up the effect of all factors and assume that factors effects are additive. We believe that the effect of environment on diversity should be characterized by a hierarchical structure with coarse scale factors, like geographical tropics to poles gradients, defining the envelope of possible diversity conditions, and other more local factors, like habitat structure, being responsible for the fine tuning of diversity. This structure is most efficiently modeled with regression trees. We show that for six habitat types in Greek protected areas regression tree models were able to describe plant species richness based upon environmental factors considerably more efficiently than multiple regression models. More importantly when the models were extrapolated to other sites in Greece, outside their domain, the differences between the predictive ability of the two approaches was magnified. The tree models picked up important ecological characteristics, and a hierarchical structure that used coarse scale factors, like latitude and longitude, for the coarse scale estimate of alpha diversity, and finer scale factors like fragmentation, for the fine-tuning of the estimation. Therefore, we advocate that the regression tree methodology is most appropriate for modeling the relationship between diversity and environmental factors, and the use of the classical regression approaches might be misleading.     

Fine-scale vertical position as an indicator of vegetation in alkali grasslands – Case study based on remotely sensed data

Vertical position is an important driver of vegetation zonation at multiple scales, via determining abiotic environmental parameters, such as climate, soil properties and water balance. In inland alkali landscapes, elevation is a key factor for understanding patterns of salt accumulation and water table which is therefore considered a good indicator of alkali vegetation types. Remote sensing techniques offer viable solutions for linking elevation data to vegetation patterns by providing an elevation model of extended areas. Our goal was to test the relationships between fine-scale differences in vertical position and vegetation patterns in inland alkali landscapes by vegetation data collected in the field and elevation data generated using airborne laser scanning (ALS). We studied whether vertical position influences vegetation patterns at the level of main vegetation groups (based on alliances) or even at the level of associations. Our study sites were situated in a lowland alkali landscape in Hortobágy National Park (East-Hungary). We grouped the associations into four main vegetation groups: loess grasslands, alkali steppes, open alkali swards and alkali meadows. Even though we detected a very limited range (121 cm) in the vertical position of the main vegetation groups, they were well separated by their vertical positions. At the level of associations, a more detailed elevation-based distinction was also possible in many cases. The revealed elevation–vegetation correlations show that high-resolution mapping based on ALS remote sensing techniques is an ideal solution in complex lowland areas, such as alkali landscapes. Our findings suggest that in other types of lowland landscapes, characterised by elevation differences, the applied method might hold a great potential as a supporting tool for vegetation mapping.     

Heterogeneity‐constrained random resampling of phytosociological databases

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 heterogeneity‐constrained 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.     

Objective classification and analysis of vegetation data

A program package is described in which vegetation data can be objectively classified and analysed. Classification is based on minimum entropy. Results show that in a comparison with TWINSPAN, improvements to the relevé sequence, in terms of community variation, can be obtained. Furthermore, TWINSPAN classifications are shown to be dependent on a particular relevé input sequence.     

Mediterranean hay meadow communities: diversity and dynamics in mountain areas throughout the Iberian Central Range (Spain)

This paper reports a phytosociological study on managed hay meadow communities in the main mountains of the Spanish Central Range. Multivariate techniques (Cluster analysis and CA-ordination) were applied in the classification of the relevés and ordination of vegetation units and species. Clusters were related to the following associations: Agrostio castellanae–Arrhenatheretum bulbosi, Festuco amplae–Cynosuretum cristati, and F. amplae–Agrostietum castellanae. The scattergram suggested that the dynamic patterns between communities are associated with soil nutrient content and moisture. We propose a new subassociation: F. amplae–A. castellanae gaudinietosum fragilis that includes Salmantincensean Agrostis castellana communities growing in regions with lower supramediterranean thermotype.