Dear Colleagues, Ecosystem management under changing conditions needs new tools to insight and forecast forest dynamic and management. Artificial intelligence is a game changer in forest management. Artificial intelligence (AI) encompasses a wide range of techniques and frameworks dating back to the mid twenty century. The use of AI in forestry is relatively new, especially when compared to the early adoption of AI in other fields. The irruption of AI spins researchers and practitioners to unfold the analysis of complex big data. Narrow AI, defined as an AI system that is specified to perform a limited task, is commonly applied in biometry (e.g., analysis of forest structure with 3D point cloud data) but no so common in other ecosystem management domains. Currently, adequate AI algorithms can be efficiently prototyped due to plenty of publicly available databases, open-source libraries and the accessibility to computing platforms. To insight on this topic and share last works, We, at the University of Valladolid (Campus at Palencia), are organizing a *Conference on Artificial Intelligence and Ecosystems Management *You can have update information at https://eventos.uva.es/92504/detail/artificial-intelligence-and-ecosystems-… *Registration is currently open* This conference is part o the IUFRO unit 4.01.02 - Growth models for tree and stand simulation, but is open to the whole Division 4 and the IUFRO community as a whole. Looking forward to seen you in Palencia Best regards -- Prof. Dr. Felipe Bravo Please note the new email:felipe.bravo@uva.es Catedrático de Planificación Forestal/Professor of Forest Management Chair SMART Global Ecosystems | Senior Researcher at iuFOR Instituto Universitario de Gestión Forestal Sostenible | Sustainable Forest Management Research Institute Universidad de Valladolid ETS Ingenierías Agrarias, Universidad de Valladolid Avda. de Madrid, 44 -- 34004 Palencia España-Spain Tl +34 979108424 Fx.+34 979108440 https://smartglobalecosystems.uva.es/ |http://www.research4forestry.eu https://orcid.org/0000-0001-7348-6695 |https://portaldelaciencia.uva.es/investigadores/181874/detalle