DOI: 10.5061/dryad.n8pk0p35r
title: The proportion of low abundance species is a key predictor of plant β-diversity across the latitudinal gradient

description: The diversity of life displays very strong patterns of disparity across
 the Earth. Beta (β)-diversity (species compositional differences among
 sites) of woody plants, for instance, has usually been documented to
 decline with increasing latitude. Understanding these patterns, however,
 remains a grand challenge in ecology and evolution. We develop a
 mathematical model to explain patterns of β-diversity across multiple
 landscapes. The model effectively predicts β-diversity in simulated and
 natural communities, regardless of the types of species abundance
 distributions. Our model provides the novel insight that the proportion of
 species in the lowest abundance category (PL), which represents the share
 of relatively rare species in the regional species pool, is the key
 predictor of plant β-diversity. By applying the model to global forest
 inventories sampled from 40.7° S to 60.7° N, we find that PL explains
 nearly 85% of the variation in plant β-diversity along the global
 latitudinal gradient. Through a series of numerical simulations, we
 further show that the predictive power of PL on plant β-diversity on a
 global scale is largely determined by the variation of intraspecific
 aggregation among different communities. Synthesis: We develop a new
 sampling model to predict patterns of β-diversity and find that the
 proportion of species in the lowest abundance category explains the
 majority of the variation in plant β-diversity along the latitudinal
 gradient. Our work provides a new tool in analyzing β-diversity and
 advances the theoretical understanding of large-scale β-diversity patterns
 across environmental gradients.
description: # The proportion of low abundance species is a key predictor of plant
 β-diversity across the latitudinal gradient
 [https://doi.org/10.5061/dryad.n8pk0p35r](https://doi.org/10.5061/dryad.n8pk0p35r) ## Description of the data and file structure The data were simulation data that are generated using the R software (version 3.6.1). R codes for generating the data are also attached in the zip file "Xiao_et_al_code_simulation_and_null_model.zip" ## Files and variables ##### **Xiao et al. Simulation of communities of different SADs to test the model** This dataframe contains simulation data for sampling from communities with four different species abundance distributions (SADs, including lognormal, gamma, exponential and truncated-hyperbolic distributions). Xiao_et_al_simumation_prediction_SAD.xlsx     -This dataframe contains α-diversity and β-diversity predicted from the model and observed in simulated communities of each SAD. Metadata_Xiao_et_al_simumation_prediction_SAD.docx ##### **Xiao et al. Simulation of different aggregation parameters** These dataframes contain simulation data for sampling from simulated communities with different values of proportion of species in the lowest abundance category (*P_L*) and different values of aggregation parameters (*k*). Xiao_et_al_a_simulation_PL_beta_relationship_different_k_ranges.xlsx     -This dataframe contains the values of r-square for the relationship between *P_L* and β-diversity under different ranges for randomly generating *k*. Xiao_et_al_simulation_k_from_-0.5_to_5.xlsx     -This dataframe contains β-diversity in one simulation where aggregation parameters are randomly generating between a range of -0.5~5. Metadata_Xiao_et_al_simulation_vary_k.docx ##### **Xiao et al. Codes for simulations and null model analyses** R codes for simulations and the null model analyses conducted in the current study. A detailed README.docx file is within the ZIP file that explains the codes in detail. Xiao_et_al_code_simulation_and_null_model.zip