Deliverable 2.5 - Workflow for detecting and prioritising emerging alien species based on GRIIS checklists and species occurrence cubes

This report details a reproducible, data-driven workflow for detecting and prioritizing emerging invasive alien species (IAS) in European Large Marine Ecosystems (LMEs). Leveraging occurrence cubes—a three-dimensional aggregation of biodiversity records across taxonomic, temporal, and geographic dimensions—the workflow integrates openly available data from infrastructures such as the Global Biodiversity Information Facility (GBIF) and the Catalogue of the European Alien Species Information Network (EASIN). The automated pipeline, fully implemented via GitHub Actions, identifies appearing and reappearing species while applying Generalized Additive Modelling (GAM) to assess statistically significant increases in the number of occupied grid cells (measured occupancy) and the number of occurrences (measured abundance).
Results for the Mediterranean, North, and Baltic Seas provide illustrative prioritized lists of species based on an emerging score that weights recent trends and occupancy increases. Notably, multiple species reached the maximum emerging score during the 2022–2024 assessment period. While current data representations for marine environments are less comprehensive than for terrestrial ones, the framework is designed to automatically benefit from ongoing data mobilization efforts. Future developments will focus on correcting research effort bias, expanding spatial and taxonomic scope and increasing the spatial and taxonomic granularity to better support evidence-based risk assessment and management decisions across Europe.