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(1) Background: Forestry will have to react to climate change because many tree species suffer. Mitigation can be realized either by planting non-native trees from regions with high climatic stress or by utilizing native tree provenances already adapted to stressful environments. Non-native trees have often generated problems in the past due to uncontrolled invasiveness. The use of native trees pre-adapted to the prospective climatic conditions is far less risky for the respective ecosystems. We offer a tool for selecting ecotypes of native trees as provenances for future forestry. (2) Methods: We propose the selection of tree species native to Middle Europe from a database of vegetation relevés of ± natural forest stands. By calculating the mean ecological indicator values of stands from their vegetation, cover sites can be elected that can provide seeds of provenances well adapted to future climatic conditions. (3) Results: By selecting the 10% partition of the most extreme stands of European tree species, seeds can be sampled and propagated for re-cultivating forests fit for future climate. (4) Conclusions: One can expect ecotypes of tree species that grow well on dry sites, since generations have faced evolutionary selection, for survival under stressful environments. This approach helps to avoid ecological risks of non-native trees. [ABSTRACT FROM AUTHOR]

We assessed the relationships between site size, habitat quality, landscape factors (fragmentation, landscape diversity) and species richness in communities of Collembola in 50 small dry grassland habitat patches in an agricultural landscape of eastern Austria. Grasslands in that region were once widespread and extensive, but have become increasingly fragmented and isolated. We hypothesized that dry grassland springtails species richness is significantly correlated with site variables (soil properties, habitat quality) and that the size of grassland sites is positively correlated with species richness. We used pitfall traps in 50 dry grasslands in differently structured agricultural landscapes and tested total abundance and three species richness measures: (1) the number of dry grassland specialist species; (2) total number of dry grassland species and (3) overall species richness. In the multivariate correlation models, we found that all species richness measures were significantly related to the plant species richness, a shape parameter of the sites, soil properties such as humus, temperature, sand and gravel content and the landscape variable reflecting isolation (distance to the nearest large dry grassland area). This landscape variable indicates that neighbouring grasslands are influencing the species richness of the sites. This may be a result of passive wind dispersal across the landscape or historic connection of the small sites with much larger dry grasslands. The size of the site did not show any significant correlation with total, dry grassland specialist, dry grassland generalist or generalist species richness. The small size of Collembola might explain these findings, because they have high population densities even in small patches. [ABSTRACT FROM AUTHOR]