Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity as well as for biodiversity conservation. In this context, using multimedia identication tools is considered as one of the most promising solutions to help bridging the taxonomic gap. With the recent advances in digital devices/equipment, network bandwidth and information storage capacities, the production of multimedia big data has indeed become an easy task. In parallel, the emergence of citizen sciences and social networking tools has fostered the creation of large and structured communities of nature observers (e.g. eBird, Xeno-canto, Tela Botanica, etc.) that have started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art multimedia analysis techniques on such data is still not well understood and is far from reaching the real world's requirements in terms of identi- cation tools. The LifeCLEF lab proposes to evaluate these challenges around 3 tasks related to multimedia information retrieval and fine-grained classification problems in 3 living worlds. Each task is based on large and real-world data and the measured challenges are dened in collaboration with biologists and environmental stakeholders in order to re ect realistic usage scenarios.