Title : Responsible application of artificial intelligence for Biodiversity (BD) conservation in Mauritius
Abstract:
Biodiversity is in decline globally, and the main causes are often habitat loss, climate change, invasive species and unmanaged human activity (Dasgupta, 2021, UN 2025). Invasive species have contributed to approximately 40% of animal extinctions since the 17th century, and its devasting effects have been intensified by climate change and habitat destruction (UNEP, 2022). Small island developing states (SIDS) face exceptional exposure to these drivers of biodiversity loss because they have high endemism rates and limited ecological buffers, resulting in significant impacts from minor environmental changes (Koenig & Deenapanray, 2024). The study done focuses on identifying Ravenala within a particular geographic area for its detection in The Valley Ferney, Mauritius. Remote sensing being the primary method in this study shows how invasive species have spread throughout the area thus endangering ecosystem services and creating long-term risks for wildlife and local communities. The exploratory analysis indicates that AI-based methods combining remote sensing and model for species detection can significantly enhance monitoring precision. The research demonstrates that emerging digital technologies can be applied with high degree of accuracy for identification of invasive species and lead biodiversity initiatives while providing a potential framework for other small islands dealing with comparable ecological threats.
