DOI: 10.5061/dryad.pg4f4qrxc
title: Data from: Untangling the contributions of species and site to beta diversity in a temperate forest region

description: 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.
description: # Untangling the contributions of species and site to beta diversity in a
 temperate forest region
 [https://doi.org/10.5061/dryad.pg4f4qrxc](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