Environmental assessment needs of Decision Support Systems (DSSs) able to consider several aspects in a unique analysis framework. The complexity of interaction among ecological, economic and political variables and a widespread lack of data availability lead to difficulty in bringing together large scale analysis and local planning systems. This loop can be solved through flexible tools able to relate large scale environmental assessment with medium and small scale DSS, useful for local decisions makers. The present research aims at creating a spatial model, based on Geographic Information Systems (GISs), capable to quantify the potential amount of woody biomass from forest sector at several evaluation scales, to consider the theoretical impact of biomass removal on forest multifunctionality and to estimate the potential trade-off between forest functions in case of bioenergy chain development. The model is carried out basing on multifunctionality aspects and their potential relationship with biomass energy production. The forest functions considered in the model are: (i) soil and water protection, (ii) biodiversity and habitat conservation, (iii) fire risk prevention, (iv) tourist and recreational function and (v) economic evaluation related to timber and bioenergy processing. The structure of the model is based on sub-models that enable biomass chain analysis from large scale to small scale. Large scale analysis is developed using forest yield data, protected areas and main and forest roads localization, geomorphological variables and fire risk maps. An increase of input data (economic and logistic variables) is requested for medium and small scale analysis. The model is tested from national (Italy) to regional (Tuscany region in Central Italy) and provincial scale (province of Trento in North-Eastern Italian Alps). Results stress how the model can be able to depict territorial differences in several contexts and to consider respective influence on estimation of biomass availability. Finally, the Compromise Programming (CP) methodology permits defining the optimal quantity of residues removal in different compartments according to priority forest function. (C) 2012 Elsevier Ltd. All rights reserved.