Résumé
Accurate identification, monitoring, and understanding of species distribution is important for biodiversity conservation, invasive species control, understanding climate change, and ecosystem management. Current methodologies for species identification, animal re-identification, and large-scale population monitoring are both resource-intensive and technically complex, posing significant challenges for widespread implementation. This highlights a need for automated, scalable solutions to enhance efficiency and accuracy. Since 2011, the LifeCLEF lab has driven progress in this field by organizing annual challenges to promote innovation in biodiversity informatics. The 2025 edition introduces five – one new, and four continued – data-driven tasks aimed at addressing current challenges in species recognition: (i) AnimalCLEF: multi-species individual animal identification, (ii) BirdCLEF: bird species identification in soundscape recordings, (iii) FungiCLEF: few shot classification with rare fungi species, (iv) GeoLifeCLEF: multi-modal species prediction using remote sensing and large-scale biodiversity data, and (v) PlantCLEF: multi-species plant identification in vegetation plot images