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The analysis of diversity across multiple scales is hampered by methodological difficulties resulting from the use of different sampling methods at different scales and by the application of different definitions of the communities to be sampled at different scales. It is our aim to analyse diversity in a nested hierarchy of scales by applying a formalized sampling concept used in population ecology when analysing population structure. This concept involved a precise definition of the sampled vegetation type by the presence of a target species, in our case Hornungia petraea. We compared separate indices of inventory diversity (i.e. number of species) and differentiation diversity (i.e. extent of change in species composition or dissimilarity) with indices derived from species accumulation curves and related diversity patterns to topographical plot characteristics such as area and distance. Ten plots were established systematically over a distance of 100 km each in the distribution centre of H. petraea in Italy (i.e. Marche and Umbria) and in a peripheral exclave in Germany (i.e. Thuringia and Saxony-Anhalt). We used a nested sampling design of 10 random subplots within plots and 10 systematically placed plots within regions. Internal α-diversity (species richness) and internal β-diversity (dissimilarity) were calculated on the basis of subplots, α-, β- and γ-diversity on the basis of plots in Italy and Germany. In addition, indices of inventory diversity and differentiation diversity were derived by fitting species accumulation curves to the Michaelis–Menten equation. There was no significant difference in the internal α-diversity between German and Italian plots but the α- and γ-diversity were higher in Italy than in Germany. In Germany, the internal β-diversity and β-diversity were lower than in Italy. The differentiation diversity increased with increasing scale from subplots over plots to regions. The same results were obtained by calculating species accumulation curves. Significant positive correlations were encountered between the internal α-diversity and α-diversity in both countries, while the internal β-diversity and internal α-diversity showed a correlation only for the Italian plots. Similarity decay was found for German plots with respect to inter-plot distance and for Italian plots with respect to altitudinal difference and to a smaller degree to distance between plots. The design chosen and the consistent analysis of species accumulation curves by the Michaelis–Menten equation yielded consistent results over different scales. The specific therophyte vegetation type in this study reflected diversity patterns also observed in other studies, e.g. a greater differentiation diversity in central than in peripheral habitats and a trend of increasing species richness towards lower altitudes. No asymptotic saturation of species richness between different scales was observed. Indications were found that the absolute level of inventory diversity at a particular scale and the completeness of the sampling procedure are the main clues for explaining the relationship between inventory and differentiation diversity at this particular scale. [ABSTRACT FROM AUTHOR]

The central-marginal model assumes unfavourable and more variable environmental conditions at the periphery of a species' distribution range to negatively affect demographic transition rates, finally resulting in reduced population sizes and densities. Previous studies on density-dependence as a crucial factor regulating plant population growth have mainly focussed on fecundity and survival. Our objective is to analyse density-dependence in combination with the effect of inter-annual variation and range position on all life stages of an annual plant species, Hornungia petraea, including germination and seed incorporation into the seed bank. As previous studies on H. petraea had revealed a pattern opposite to existing theory with lower population densities at the distribution centre in Italy than at the periphery in Germany, we hypothesised that (1) demographic transition rates are lower, (2) the inter-annual variation in demographic transition rates is higher and (3) the intensity of density-dependence is weaker in Italy than in Germany. To analyse demographic transition rates, we used an autoregressive covariance strategy for repeated measures including density and inter-annual variation. All the three hypotheses were confirmed, but the impact of range position, density-dependence and inter-annual variation differed among the transition steps. All transition rates except fecundity were higher in the German populations than in the Italian populations. Germination rate and incorporation rate into the seed bank were strongly density-dependent. Central populations showed a larger inter-annual variation in fecundity and winter survival rate. Winter survival rate was the only transition step with a stronger density-dependence in peripheral populations. In most cases, these differences between distribution centre and periphery would not have emerged without taking density-dependence and inter-annual variation into account. We conclude that including range position, inter-annual variation and density-dependence in one single statistical model is an important tool for the interpretation of demographic patterns regarding the central-marginal model.