Data from: Biotic pressures and environmental heterogeneity shape beta-diversity of seedling communities in tropical montane forests
Barczyk, Maciej et al. (2023), Data from: Biotic pressures and environmental heterogeneity shape beta-diversity of seedling communities in tropical montane forests, Dryad, Dataset, https://doi.org/10.5061/dryad.3r2280gmh
Many theories have been proposed to explain the high diversity of plants in the tropics. However, we lack an understanding of the processes that drive plant diversity and community assembly at different spatial scales. Here, we applied beta-diversity partitioning to test how biotic and abiotic factors are associated with seedling beta-diversity in a tropical montane forest in Southern Ecuador. We recorded seedling communities on 81 subplots at nine plots located at three elevations along a 2000-m elevational gradient. We measured biotic pressures (i.e. herbivory and fungal pathogen attacks) and environmental conditions (i.e. soil moisture and canopy closure) at all subplots and related them to species turnover and richness differences in seedling communities within and between elevations. We found that species turnover increased with differences in biotic dissimilarity within elevations, while differences in species richness within elevations increased with increasing environmental dissimilarity. Between elevations, species turnover increased with increasing environmental dissimilarity. Our findings show that species turnover and changes in species richness are related differently to abiotic and biotic factors, and that the importance of these factors for shaping seedling diversity is scale-dependent. Our study contributes to better understand the processes driving seedling beta-diversity and the assembly of plant communities in highly diverse tropical montane forests.
Seedling recruitment along the elevational gradient (1000, 2000 and 3000 m a.s.l.) in primary forest of Podocarpus National Park and San Francisco Reserve. The data was collected on 81 study subplots in the years 2019 and 2020.
Deutsche Forschungsgemeinschaft, Award: FOR2730