Galaxy workflow for Ecoregionalization: A Dumont D'Urville Sea Use Case

The transparency and reproducibility of research processes are critical to scientific activities. However, challenges such as data accessibility and interoperability often make data sharing and reuse difficult. This work presents a Galaxy ecoregionalization workflow using the Dumont D'Urville Sea region as a case study. By using R scripts transformed into modular Galaxy tools, the workflow ensures compliance with the FAIR (Findable, Accessible, Interoperable, Reusable) principles and promotes open science. This workflow allows users to analyze species distribution and identify ecoregions using a user-friendly interface. The Boosted Regression Trees (BRT) algorithm was used for species distribution modeling, capitalizing on the capabilities of machine learning to handle complex ecological data. The case study highlights the workflow's practical utility in real-world scenarios using data from the CEAMARC expedition, providing additional information on East Antarctic marine biodiversity. This approach facilitates improvements through collaboration and knowledge sharing among researchers.