Within branched root systems, a distinct heterogeneity of traits exists. Knowledge about the ecophysiology of different root types is critical to understand root system functioning. Classification schemes have to match functional root types as closely as possible to be used for sampling and modeling. Among ecophysiological root traits, respiration is of particular importance, consuming a great amount of carbon allocated. Root architecture differs between the four deciduous tree seedlings. However, two types of terminal root segments (i.e. first and second orders), white colored and brown colored, can be distinguished in all four species but vary in frequency, their morphology differing widely from each other and higher coarse root orders. Root respiration is related to diameter and tissue density. The use of extended root ordering (i.e. order and color) explains the variance of respiration two times as well as root diameter or root order classes alone. White terminal roots respire significantly more than brown ones; both possess respiration rates that are greater than those of higher orders in regard to dry weight and lower in regard to surface area. The correlation of root tissue density to respiration will allow us to use this continuous parameter (or easier to determine dry matter content) to model the respiration within woody root systems without having to determine nitrogen contents. In addition, this study evidenced that extended root orders are better suited than root diameter classes to picture the differences between root functional types. Together with information on root order class frequencies, these data allow us to calculate realistic, species-specific respiration rates of root branches.

The understanding of spatial distribution patterns of native riparian tree species in Europe lacks accurate species distribution models (SDMs), since riparian forest habitats have a limited spatial extent and are strongly related to the associated watercourses, which needs to be represented in the environmental predictors. However, SDMs are urgently needed for adapting forest management to climate change, as well as for conservation and restoration of riparian forest ecosystems. For such an operative use, standard large-scale bioclimatic models alone are too coarse and frequently exclude relevant predictors. In this study, we compare a bioclimatic continent-wide model and a regional model based on climate, soil, and river data for central to south-eastern Europe, targeting seven riparian foundation species—Alnus glutinosa, Fraxinus angustifolia, F. excelsior, Populus nigra, Quercus robur, Ulmus laevis, and U. minor. The results emphasize the high importance of precise occurrence data and environmental predictors. Soil predictors were more important than bioclimatic variables, and river variables were partly of the same importance. In both models, five of the seven species were found to decrease in terms of future occurrence probability within the study area, whereas the results for two species were ambiguous. Nevertheless, both models predicted a dangerous loss of occurrence probability for economically and ecologically important tree species, likely leading to significant effects on forest composition and structure, as well as on provided ecosystem services.