Further Information : Tel : , ; 1. Forest and Environmental Sciences and Management: What are they? Understanding Structure, Processes and Dynamics of Forests and the Environment: Characterisation and modelling of structure, biodiversity, timber, and populations in forest and environmental ecosystems. Inventory/Assessment of : Natural Resources, including land-use, water, timber, biomass, biodiversity, NTFPs. Forest and Environmental Management to: Ensure efficient production of natural resources products to society, to do so sustainably, and in a manner which conserves irreplaceable resources. To achieve these aims Forestry and Environmental Science involve interdisciplinary efforts from: The basic sciences of : botany, biology, physiology, soil science, ecology, climatology, geography, GIS. The methodological sciences of Statistics, Modelling and Informatics, both directly, and indirectly through the basic sciences. Statistics, Modelling and Informatics (SMI) for Forestry and the Environment (FE) SMIFE: A Distributed Virtual Institute (DVI) 2. What are Statistics, Modelling & Informatics? Statistics, Modelling and Informatics (SMI), are all concerned with information and knowledge discovery in all those sciences in which the study populations are large complex and heterogeneous. Modelling builds integrated mathematical and computer representations of discovered information and knowledge and enables simulation, prediction and analysis of the long-term dynamic behaviour of the models of real-world systems. Informatics uses machine-learning, AI and Knowledge-based methodologies to complement and extend Statistical and Modelling techniques, and to develop Decision Support Systems. Statistics focuses on the design of efficient and effective methods of data- collection in surveys and experiments, and the valid analysis of data to produce meaningful significant interpretable and useful information and knowledge. Sampling (Kleinn) Neural Networks (Rennolls) Growth Analysis (Garcia) 3. Areas where SMI ALREADY makes crucial contributions to forestry research and management: The design and analysis of assessments/inventories of carbon, biomass and biodiversity; the analysis of remotely sensed images and their use in map production; forest growth and yield modelling ; process-based forest models; See for further exampleswww.fbmis.infowww.forestmodelarchive.info 4. FUTURE areas in which SMI is CRUCIAL to Forest and Environmental Research and Management: Inventory: improved statistical/ANN classification methods for map making from RS images; the data-fusion challenge of combining remote sensing data which is obtained at different scales and for which there is incomplete coverage both over time, and space; accuracy measures for maps; data-mining and knowledge discovery from large distributed forest databases, etc… Growth Modelling: the model-fusion challenge of combining forest growth models which have each been developed for different scales to produce flexible hybrid models; a forest model archive,... Models for management: modelling the spread of forest diseases, animal/pest populations and fire; combining uncertain information and changing risk perceptions into management decision support systems; 6. PROBLEMS: 1. Currently, there is an insufficient infrastructure for SMI for FE in Europe to adequately support the future needs of Forestry and Environmental Research & Management, if it is to become world -leading. 2.The needs for and the insufficiency of SMI for Forestry & the Environment are not generally not recognised in European Forestry and Environmental Research. 7. SOLUTION: SMIFE is a proposal that there should be a consolidation of the distributed European expertise in the methodological SMI disciplines that will integrate with, support, and facilitate European Forestry and Environmental Science become world leading. The SMIFE consolidation would ensure both critical- mass and economies of scale in European SMI for Forestry and Environmental research. Such an infrastructure, based on the internet, would offer the expertise of an “Institute”, and the focused collaboration of team research…i.e. “A Distributed Virtual Institute” (DVI: SMIFE) Professor Keith Rennolls, University of Greenwich, Professor Dr. Christoph Kleinn, University of Göttingen. (European Deputy Leaders, IUFRO 4.11 [Statistical Methods, Mathematics and Computing]) Prepared by: 5. CONCLUSION: There is a crucial need for a wide infrastructure in SMI for F & E to provide support, collaboration, and training in research methodologies for F & E.