Exploratory modeling of forest disturbance scenarios in central Oregon using computational experiments in GIS

Exploratory modeling is an approach used when process and/or parameter uncertainties are such that modeling attempts at realistic prediction are not appropriate. Exploratory modeling makes use of computational experimentation to test how varying model scenarios drive model outcome. The goal of exploratory modeling is to better understand the system of interest through delineation of plausible boundaries, description of patterns within multidimensional model space, and to the extent possible, quantification of the likelihood of occurrence of different model outcomes. This study makes use of exploratory modeling in GIS to delineate boundaries of likely and plausible variability in past Oregon forests due to natural fire disturbance processes interacting with climate change, and compares those with current forests modified by harvest disturbance and with a hypothetical forest scenario. The implications of different forest landscapes for biodiversity are quantified, using a rule base constructed from empirical data describing forest age class, elevation, and heterogeneity requirements by species. Results show: 1) a wide range of natural forest structure plausibly existed in the past, 2) portions of the current forest are outside of the most liberal models of the natural range of forest variability, and 3) large changes in forest structure produce relatively small changes in biodiversity indicators. These findings suggest that disturbance processes (natural or human) that retain forested land cover but alter forest age class structure do not have a strong impact on biodiversity. As an exploratory exercise, the findings are not the end objective; rather, they serve as a basis for dialogue about which forest landscape factors are most important for assessment of biodiversity impacts.