Data and R code for "Land-use change reshapes host community composition and erodes biodiversity-mediated dilution of hantavirus exposure"

This repository contains the serological and community-composition dataset and the R analytical code supporting the manuscript "Land-use change reshapes host community composition and erodes biodiversity-mediated dilution of hantavirus exposure" by Vigueras-Galván et al. Study context. Small mammals (rodents and bats) were sampled between 2021 and 2023 at 12 localities across the Yucatán Peninsula (Mexico), distributed along an anthropization gradient encompassing four habitat types: conserved, diversified, rural and urban (n = 3 localities per type). Hantavirus IgG antibodies were detected by indirect ELISA using a recombinant Sin Nombre virus (SNV) nucleocapsid antigen. Data file. Vertebrados_2024_CURADA.xlsx contains three sheets: INFORMACIÓN GENERAL: metadata on the dataset. Claves: codebook describing variable codes used in the Registro sheet. Registro: individual-level capture records (one row per captured individual) including locality, habitat, date, taxonomic identification (Class, Order, Family, Genus, Species), morphometric measurements, sample collection metadata, and serological/molecular results for several pathogens. The column SH corresponds to hantavirus serology (ELISA), used as the primary exposure variable in the manuscript. R scripts. Three R scripts reproduce the main figures of the manuscript from the raw dataset. They expect the Excel file in a subfolder named data/ and write outputs to a figures_article/ folder: fig1_overview.R — sampling effort, host species richness, Jaccard community similarity and hantavirus seroprevalence by habitat type (overview panel). fig2_dilution.R — habitat-stratified binomial GLM relating community-level seroprevalence to host species richness; forest plot of slopes by habitat type. fig3_-_amplifier-diluters.R — leave-one-out classification of host species as amplifiers or diluters of community-level hantavirus exposure, by habitat type. Reproducibility. Scripts are written in R and rely on the packages dplyr, tidyr, purrr, broom, readxl, stringr, ggplot2, scales, patchwork and forcats. Missing packages are installed automatically on first run.