Proximity to seabird colonies and water availability shape moss distributions in Antarctica

Understanding species distributions across Antarctica is crucial for biodiversity conservation under climate change, but continental-scale analyses of key terrestrial species remain scarce. Here, we modeled distributions of 28 moss species across Antarctica using Log-Gaussian Cox Process models and environmental covariates, including topographic wetness index, distance to seabird colonies, and temperature. Broad-scale distributions were primarily driven by proximity to seabird colonies, while species exhibited distinct responses to water availability and temperature. Species exclusive to maritime Antarctica showed negative relationships with topographic wetness index, whereas continent-wide species responded positively to water accumulation potential, reflecting regional differences in water availability and habitat preferences. Bias-corrected predictions revealed the highest moss diversity in coastal regions, with inland areas supporting ecologically distinct assemblages. Our Bayesian ..., , # Proximity to seabird colonies and water availability shape moss distributions in Antarctica

Dataset DOI: [10.5061/dryad.wstqjq2zf](10.5061/dryad.wstqjq2zf)

This repository contains the data sources and the code used for the paper \"Proximity to seabird colonies and water availability shape moss distributions in Antarctica\", published in Ecography, 10.1002/ecog.08166.

The main results of the paper can also be visualized interactively here: [https://moss-app-c63b-prod.app.oceanum.io/](https://moss-app-c63b-prod.app.oceanum.io/)

#### Data Availability Note

The input data files required to run the code are not included in this repository due to licensing restrictions and file size constraints. All data can be obtained from the publicly available sources listed below. We provide direct links and access instructions for each data source to facilitate reproduction of our analysis.

#### Files

**sensitivity_analysis.xlsx:** The table shows sensitivity analysis for prior settings in a Bay..., , **Changes after Oct 27, 2025:**

The repository has been updated to include shapefiles containing the spatial predictions from our species distribution models. These files can be used to reproduce the maps presented in the paper without needing to re-run the computationally intensive modelling steps.

*Files included:*

\- **`all_pred_prob_SB.shp`**: Model predictions of all species presence probabilities **without** sampling bias correction

\- Use these predictions to see the raw environmental suitability without accounting for proximity to research stations

\- **`all_pred_prob.shp`**: Model predictions of species presence probabilities **with** sampling bias correction

\- These predictions exclude the distance to scientific stations as a covariate to account for sampling bias in the occurrence data

\- Use these predictions for understanding the actual distribution patterns after correcting for uneven sampling effort

Both shapefiles include predicted presence probabilities for the...