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Aim: Our knowledge of Pleistocene refugia and post-glacial recolonization routes of forest understorey plants is still very limited. The geographical ranges of these species are often rather narrow and show highly idiosyncratic, often fragmented patterns indicating either narrow and species-specific ecological tolerances or strong dispersal limitations. However, the relative roles of these factors are inherently difficult to disentangle., Location: Central and south-eastern Europe., Time Period: 17,100 BP - present., Major Taxa Studied: Five understorey herbs of European beech forests: Aposeris foetida , Cardamine trifolia , Euphorbia carniolica , Hacquetia epipactis and Helleborus niger ., Methods: We used spatio-temporally explicit modelling to reconstruct the post-glacial range dynamics of the five forest understorey herbs. We varied niche requirements, demographic rates and dispersal abilities across plausible ranges and simulated the spread of species from potential Pleistocene refugia identified by phylogeographical analyses. Then we identified the parameter settings allowing for the most accurate reconstruction of their current geographical ranges., Results: We found a largely homogenous pattern of optimal parameter settings among species. Broad ecological niches had to be combined with very low but non-zero rates of long-distance dispersal via chance events and low rates of seed dispersal over moderate distances by standard dispersal vectors. However, long-distance dispersal events, although rare, led to high variation among replicated simulation runs., Main Conclusions: Small and fragmented ranges of many forest understorey species are best explained by a combination of broad ecological niches and rare medium- and long-distance dispersal events. Stochasticity is thus an important determinant of current species ranges, explaining the idiosyncratic distribution patterns of the study species despite strong similarities in refugia, ecological tolerances and dispersal abilities., Competing Interests: The authors declare that they have no conflict of interest., (© 2023 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd.)

Aim: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales., Location: European Alps., Methods: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses., Results: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients., Main Conclusions: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.