Data and code for "Beyond 'few winners, many losers': land use drives contrasting impacts across the tree of life" — Pinho et al submitted

# Data and R scripts for “Beyond ‘few winners, many losers’: land use drives contrasting impacts across the tree of life” — Pinho et al submitted

Description:This repository contains data and R codes used in the analyses for the above manuscript. The work is based on data produced by the Synthesis Core Project of the Biodiversity Exploratories program (DFG Priority Program 1374).

Data Sources:The original synthesis datasets were assembled as described at:

https://github.com/biodiversity-exploratories-synthesis/Synthesis_dataset_diversity_grassland

https://github.com/biodiversity-exploratories-synthesis/Synthesis_dataset_diversity_forest

Data updates, such as the inclusion of recent datasets, were implemented in data_assembly.R (see /Rscripts).Individual datasets used to assemble the synthesis dataset are available via the Biodiversity Exploratories Information System (DOI: 10.17616/R32P9Q).Dataset identifiers are provided in Extended Data Table 1, and corresponding links are listed in the references section.

Repository Structure/DataContains all data used for niche modelling and analyses:

Abund_Synthesis_250804.csv — Abundances of each taxonomic unit (species, genera, or OTUs) per sample plot and year.

LUI_default_STD_2023-12-29.txt — Standardized land-use intensity index for grasslands.

LUI_default_component_2023-12-29.txt — Unstandardized component indices for grasslands.

ForMIX.csv — Land-use intensity metrics for forests.

/RscriptsContains analysis scripts used in the manuscript:

data_assembly.R — Updates synthesis datasets and assembles functional assignments.

niche_model_WinnerLoser.R — Runs niche modelling to estimate species responses to land-use and classify species as winners, losers, mid-specialists, or neutral.

output_analysis.R — Calculates diversity metrics and performs trait PCA.

diversity_LUI_models&plots.R — Analyses and plots for taxa–LUI relationships (Fig. 2).

niche_trait_models&plots.R — Trait-based analyses (Fig. 3; Extended Data Figs. 7–8).

Thresholds_models&plots.R — Threshold analyses (Fig. 4; Extended Data Table 2).

plots_WinnerLoser.R — Additional plots (e.g., Fig. 1 and extended figures).

/FunctionsIncludes custom R functions supporting the main scripts:

functions_diversity_LUI.R — Functions to run diversity analyses.

functions_thresholds.R — Functions for threshold analyses.

/ResultsContains outputs from scripts, including:

output_niche_WL.csv — Main output file from the niche analysis.

All analyses were run in R version 4.5.1. Required dependencies and libraries are listed within each R script (via library() calls).