In this study, we demonstrate the potential of online citizen science platforms and their vast collection of images. These tools enable the tracking of the spread of a recently detected invasive gastropod species, both within and beyond the currently known invaded area. To achieve this, we utilized computer vision tools to train a supervised learning model. The goal of this model is the early detection and monitoring of the spread of this discrete invasive alien species by identifying unreported individuals. Our validation case focuses on a recently introduced invasive species in Europe, currently reported only along the coasts of Spain and Portugal. This species has recognized negative impacts on both native biodiversity and the commercial shellfish industry.

This study reinforces the importance of citizen science and emerging technologies in biodiversity monitoring, highlighting the crucial role of artificial intelligence in the early detection of ecological threats and the protection of ecosystems.