Abstract
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.
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.
| Original language | English |
|---|---|
| Article number | e13045 |
| Number of pages | 15 |
| Journal | Journal of Vegetation Science |
| Volume | 32 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 22 May 2021 |
Bibliographical note
Funding Information:The Bavarian Research Alliance (via the BayIntAn scheme) and the Bayreuth Center of Ecology and Environmental Research (BayCEER) funded the initial GrassPlot workshop during which the database was established and the current paper was initiated (grants to JDe). WU acknowledges support from the Polish National Science Centre (grant 2017/27/B/NZ8/00316). IB, JAC and IG‐M were funded by the Basque Government (IT936‐16). GF carried out the research in the frame of the MIUR initiative “Department of excellence” (Law 232/2016). SBa was supported by the GINOP‐2.3.2‐15‐2016‐00019 project. CM was supported by the Czech Science Foundation (grant no. 19‐28491X) and the Basque Government (IT936‐16). ID was supported by the Polish National Science Centre (grant DEC‐2013/09/N/NZ8/03234) and by a Swiss Government Excellence Scholarship for Postdocs (ESKAS No. 2019.0491). MJ was supported by the Slovak Academy of Sciences (grant VEGA 02/0095/19). AN was supported by a “Master Plan Project” in the University of Mazandaran, Iran. DS was supported by the Czech Science Foundation (grant no. 20‐29554X). AK, IV and DV were supported by the National Research Foundation of Ukraine (project no. 2020.01/0140). JDo was supported by the Czech Science Foundation (GA17‐19376S) and LTAUSA18007
Funding Information:
The Bavarian Research Alliance (via the BayIntAn scheme) and the Bayreuth Center of Ecology and Environmental Research (BayCEER) funded the initial GrassPlot workshop during which the database was established and the current paper was initiated (grants to JDe). WU acknowledges support from the Polish National Science Centre (grant 2017/27/B/NZ8/00316). IB, JAC and IG-M were funded by the Basque Government (IT936-16). GF carried out the research in the frame of the MIUR initiative ?Department of excellence? (Law 232/2016). SBa was supported by the GINOP-2.3.2-15-2016-00019 project. CM was supported by the Czech Science Foundation (grant no. 19-28491X) and the Basque Government (IT936-16). ID was supported by the Polish National Science Centre (grant DEC-2013/09/N/NZ8/03234) and by a Swiss Government Excellence Scholarship for Postdocs (ESKAS No. 2019.0491). MJ was supported by the Slovak Academy of Sciences (grant VEGA 02/0095/19). AN was supported by a ?Master Plan Project? in the University of Mazandaran, Iran. DS was supported by the Czech Science Foundation (grant no. 20-29554X). AK, IV and DV were supported by the National Research Foundation of Ukraine (project no. 2020.01/0140). JDo was supported by the Czech Science Foundation (GA17-19376S) and LTAUSA18007 We thank all vegetation scientists who carefully collected the multi-scale plant diversity data from Palaearctic grasslands available in GrassPlot. The Eurasian Dry Grassland Group (EDGG) and the International Association for Vegetation Science (IAVS) supported the EDGG Field Workshops, which generated a core part of the GrassPlot data.
Publisher Copyright:
© 2021 The Authors. Journal of Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science
Keywords
- disturbance
- elevation
- fine-grain beta diversity
- heterogeneity
- land use
- macroecology
- mean occupancy
- Palaearctic grassland
- productivity
- scale dependence
- species–area relationship (SAR)
- z-value
