Post-glacial determinants of regional species pools in alpine grasslands

[Aim] Alpine habitats support unique biodiversity confined to high-elevation areas in the current interglacial. Plant diversity in these habitats may respond to area, environment, connectivity and isolation, yet these factors have been rarely evaluated in concert. Here we investigate major determinants of regional species pools in alpine grasslands, and the responses of their constituent species groups.[Location] European mountains below 50° N.[Time period] Between 1928 and 2019.[Major taxa studied] Vascular plants.[Methods] We compiled species pools from alpine grasslands in 23 regions, including 794 alpine species and 2,094 non-alpines. We used species–area relationships to test the influence of the extent of alpine areas on regional richness, and mixed-effects models to compare the effects of 12 spatial and environmental predictors. Variation in species composition was addressed by generalized dissimilarity models and by a coefficient of dispersal direction to assess historical links among regions.[Results] Pool sizes were partially explained by current alpine areas, but the other predictors largely contributed to regional differences. The number of alpine species was influenced by area, calcareous bedrock, topographic heterogeneity and regional isolation, while non-alpines responded better to connectivity and climate. Regional dissimilarity of alpine species was explained by isolation and precipitation, but non-alpines only responded to isolation. Past dispersal routes were correlated with latitude, with alpine species showing stronger connections among regions.[Main conclusions] Besides area effects, edaphic, topographic and spatio-temporal determinants are important to understand the organization of regional species pools in alpine habitats. The number of alpine species is especially linked to refugia and isolation, but their composition is explained by past dispersal and post-glacial environmental filtering, while non-alpines are generally influenced by regional floras. New research on the dynamics of alpine biodiversity should contextualize the determinants of regional species pools and the responses of species with different ecological profiles.The authors thank Daniela Gaspar for support in GIS analyses. B.J.-A. thanks the Marie Curie Clarín-COFUND program of the Principality of Asturias-EU (ACB17-26), the regional grant IDI/2018/000151, and the Spanish Research Agency grant AEI/ 10.13039/501100011033. J.V.R.-D. was supported by the ACA17-02FP7 Marie Curie COFUND-Clarín grant. G.P.M. was funded by US National Science Foundation award 1853665. C.M. was funded by grant no. 19-28491 of the Czech Science Foundation.Peer reviewe

Fine-grain beta diversity of Palaearctic grassland vegetation

Questions: Which environmental factors influence fine-grain beta diversity of vegetation and do they vary among taxonomic groups? Location: Palaearctic biogeographic realm. Methods: We 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). Results: Mean 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. Conclusions: We 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

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Aims Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location Palaearctic biogeographic realm. Methods We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology