Abstract
Maximum stand density index (SDIMAX) models were developed for important Pacific Northwest conifers of western Oregon and Washington, USA, based on site and species influences and interactions. Inventory and monitoring data from numerous federal, state and private forest management groups were obtained throughout the region to ensure a wide coverage of site characteristics. These observations include information on tree size, number and species composition. The effects and influence on the self-thinning frontier of plot-specific factors, such as climate, topography, soils and geology, as well as species composition, were evaluated based on geographic location using a multistep modelling approach. The influence of climatic variables was explored further in the context of potential future climate scenarios. Future climate projections based on global circulation models under different representative concentration pathways were utilized in a space-for-time substitution within an ensemble learning model to understand potential shifts, both magnitude and direction, in modelled SDIMAX. Further issues of model sensitivity to both spatial errors associated with input plot locations, as well as diameter cutoffs and calculations, were explored. The regional model of site-specific SDIMAX will support forest managers in decision making regarding density management and species selection to more efficiently utilize site resources toward healthy, productive forests.