Abstract

AbstractQuestionsWhich environmental factors influence fine‐grain beta diversity of vegetation and do they vary among taxonomic groups?LocationPalaearctic biogeographic realm.MethodsWe extracted 4,654 nested‐plot series with at least four different grain sizes between 0.0001 m² and 1,024 m² from the GrassPlot database, covering a wide range of different grassland and other open habitat types. We derived extensive environmental and structural information for these series. For each series and four taxonomic groups (vascular plants, bryophytes, lichens, all), we calculated the slope parameter (z‐value) of the power law species–area relationship (SAR), as a beta diversity measure. We tested whether z‐values differed among taxonomic groups and with respect to biogeographic gradients (latitude, elevation, macroclimate), ecological (site) characteristics (several stress–productivity, disturbance and heterogeneity measures, including land use) and alpha diversity (c‐value of the power law SAR).ResultsMean z‐values were highest for lichens, intermediate for vascular plants and lowest for bryophytes. Bivariate regressions of z‐values against environmental variables had rather low predictive power (mean R² = 0.07 for vascular plants, less for other taxa). For vascular plants, the strongest predictors of z‐values were herb layer cover (negative), elevation (positive), rock and stone cover (positive) and the c‐value (U‐shaped). All tested metrics related to land use (fertilization, livestock grazing, mowing, burning, decrease in naturalness) led to a decrease in z‐values. Other predictors had little or no impact on z‐values. The patterns for bryophytes, lichens and all taxa combined were similar but weaker than those for vascular plants.ConclusionsWe conclude that productivity has negative and heterogeneity positive effects on z‐values, while the effect of disturbance varies depending on type and intensity. These patterns and the differences among taxonomic groups can be explained via the effects of these drivers on the mean occupancy of species, which is mathematically linked to beta diversity.

Highlights

  • One of the central aims of ecology and evolutionary biology is to understand the drivers of biological diversity at different spatial and temporal scales (Allan et al, 2011; Isbell et al, 2011)

  • We found an increase in fine-­grain β-­diversity of vascular plants and bryophytes with elevation, which contrasts with Moradi et al (2020) for grasslands in Iran (2,000–­4,500 m a.s.l.), Kraft et al (2011) for forests in Ecuador (400–­2300 m a.s.l.; only trees) and Qiao et al (2012) for forests in China (300–­3,150 m a.s.l.), who found decreasing z-­values

  • Before our study, there was only scattered and inconclusive knowledge and hardly any theory about drivers of fine-­grain z-­values, our comprehensive study has enabled us to propose a theory consisting of a set of hypotheses that are in agreement with our findings (Figure 6, Appendix S7)

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Summary

| INTRODUCTION

One of the central aims of ecology and evolutionary biology is to understand the drivers of biological diversity at different spatial and temporal scales (Allan et al, 2011; Isbell et al, 2011). The vegetation of Palaearctic grasslands is suitable for studying fine-­grain β-­diversity as it regularly contains three taxonomic groups with contrasting ecological properties (vascular plants, bryophytes, lichens). Such grasslands occur under very diverse site conditions (e.g. from sea level to more than 5,000 m a.s.l., from very wet to very dry sites) and management regimes (e.g. natural, semi-­natural, intensified; Dengler et al, 2020b). We use the extensive GrassPlot database (Dengler et al, 2018), which provides multi-­scale species richness data of grasslands and other non-­forested habitats across the whole Palaearctic biogeographic realm, to test how fine-­grain β-­diversity (measured as z-­values of nested-­plots SARs) is related to multiple potential drivers. How are z-­values related to small-­scale ecological characteristics, related to stress–­productivity, disturbance and heterogeneity?

| METHODS
| DISCUSSION
Findings
| Conclusions and outlook
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