Data from: Untangling the contributions of species and site to beta diversity in a temperate forest region
Cite this dataset
Hao, Minhui et al. (2024). Data from: Untangling the contributions of species and site to beta diversity in a temperate forest region [Dataset]. Dryad. https://doi.org/10.5061/dryad.pg4f4qrxc
Abstract
Aims: The variation of species composition among communities, commonly known as beta diversity, is central to ecology because of its role in explaining community assembly processes. However, traditional species-centered beta diversity predominantly focuses on the variation in species abundance while neglecting functional and phylogenetic characteristics. This study presents a new approach that integrates functional and phylogenetic characteristics into the traditional beta diversity framework.
Location: Northeastern China.
Methods: We extend the traditional beta diversity framework by introducing the concept of community-weighted mean pairwise distance (CWMPD) that incorporates species’ functional and phylogenetic information. Using observations from a large forest observational network, we estimate beta diversity based on a) species, b) functional traits, and c) phylogenetic information. Then, total beta diversity is partitioned into species (SCBD) and local contributions to beta diversity (LCBD) to estimate the ecological uniqueness of species and locations, respectively. We used regression analysis and variation partitioning to determine the underlying processes that drive specific patterns of SCBD and LCBD.
Results: We found that the patterns of beta diversity, SCBD and LCBD differed among species, functional and phylogenetic information. Species-based metrics help to identify species with specific distributions, and locations with unique species compositions. Functional- and phylogenetic-based metrics aid in identifying species and locations with distinctive ecological and evolutionary attributes. Deterministic as well as stochastic processes contribute to specific diversity patterns. However, after integrating functional and evolutionary information, the relative effect of environmental filtering and dispersal limitation became more apparent.
Main conclusions: Tested on an extensive set of observations, our research provides a new opportunity to characterize the ecological uniqueness of species and locations. Functional- and phylogeny-based metrics offer distinct perspectives beyond species-based metrics. This study thus provides a new basis for a deeper understanding of community assembly processes that may be helpful in guiding biodiversity conservation and vegetation management.
README: Untangling the contributions of species and site to beta diversity in a temperate forest region
https://doi.org/10.5061/dryad.pg4f4qrxc
The data package contains six files (csv format) that were used in the analyses of the study: Minhui Hao, Klaus von Gadow, Qingmin Yue, Chunyu Zhang, Xiuhai Zhao. Untangling the contributions of species and site to beta diversity in a temperate forest region.
Description of the data and file structure
File List:
1. Bioclim.csv: Bioclimatic variables table
2. comm.csv: Community composition table
3. Geo.csv: Geographic coordinates table
4. splist.csv: Species list
5. Topo.csv: Topographic variables table
6. traits.csv: Plant functional traits table
Specific information for: Bioclim.csv
1. Number of variables/columns: 42
2. Number of plots/rows: 412
3. Variable list:
- MAT: Mean annual temperature (℃)
- MAP: Mean annual precipitation (mm)
- ISO: Isothermality (/)
- TS: Temperature seasonality (/)
- PS: Precipitation seasonality (/)
- MDR: Mean diurnal range (℃)
- TAR: Temperature annual range (℃)
- MTWM: Max temperature of warmest month (℃)
- MTCM: Min temperature of coldest month (℃)
- MTWQ: Mean temperature of warmest quarter (℃)
- MTCQ: Mean temperature of coldest quarter (℃)
- MTWeQ: Mean temperature of wettest quarter (℃)
- MTDQ: Mean temperature of driest quarter (℃)
- PWM: Precipitation of wettest month (mm)
- PDM: Precipitation of driest month (mm)
- PWQ: Precipitation of wettest quarter (mm)
- PDQ: Precipitation of driest quarter (mm)
- PWaQ: Precipitation of warmest quarter (mm)
- PCQ: Precipitation of coldest quarter (mm)
- PET: Potential evapotranspiration (mm)
- BLA: Water balance (mm)
4. Specialized format or other abbreviation used: _2 represents the binomial transformation of a variable
Specific information for: comm.csv
1. Number of species/columns: 68
2. Number of plots/rows: 412
Specific information for: Geo.csv
1. Number of variables/columns: 2
2. Number of plots/rows: 412
3. Variable list:
- LNG: Longitude
- LAT: Latitude
Specific information for: splist.csv
1. Number of columns: 3
2. Number of species/rows: 68
Specific information for: Topo.csv
1. Number of variables/columns: 8
2. Number of plots/rows: 412
3. Variable list:
- ELE: Elevation (m)
- SLO: Slope (°)
- DEP: Soil depth (cm)
- ASP_WE: Aspect (west-east)
- ASP_NS: Aspect (north-south)
4. Specialized format or other abbreviation used: _2 represents the binomial transformation of a variable
Specific information for: traits.csv
1. Number of variables/columns: 8
2. Number of species/rows: 68
3. Variable list:
- SLA: Specific leaf area (mm2/g)
- LDMC: Leaf dry matter content (%)
- LN: Leaf nitrogen content (%)
- CN: Leaf carbon-nitrogen ratio (/)
- WD: Wood density (mg/mm3)
- Hmax: Maximum height (m)
- FT: Fruit type (/)
- LT: Leaf type (/)
Code/Software
n/a
Funding
National Natural Science Foundation of China, Award: 32201555