Résumé
GeoLifeCLEF 2025 competition, organized as part of the LifeCLEF and FGVC workshops, challenges participants to predict plant species composition at high spatial resolution across Europe using multimodal environmental data. The task builds on a large-scale dataset that combines 5 million Presence-Only (PO) observations and approximately 100,000 standardized Presence-Absence (PA) surveys, paired with Sentinel-2 imagery, Landsat time series, climate rasters, and soil descriptors. This year's edition introduced two major challenges: a geographically shifted test set with plots from previously unseen regions with different species distribution, thereby including many rare species that are under-reported by citizen scientists. These changes increased the modeling difficulty and emphasized the need for generalization under spatial shift and class imbalance. In this paper, we summarize the task design, dataset characteristics, evaluation protocol, participant approaches, and competition results, and discuss implications for scalable species distribution modeling and biodiversity monitoring.