Modeling potential future individual tree-species distributions in the eastern United States under a climate change scenario: a case study with Pinus virginiana

摘要: Abstract We are using a deterministic regression tree analysis model (DISTRIB) and stochastic migration (SHIFT) to examine potential distributions of ∼66 individual species eastern US trees under 2×CO2 climate change scenario. This process is demonstrated for Virginia pine (Pinus virginiana). USDA Forest Service Inventory Analysis data more than 100 000 plots nearly 3 million east the 100th meridian were analyzed aggregated county level provide importance values each 2100 counties. County-level also compiled on climate, soils, land use, elevation, spatial pattern. Regression (RTA) was used devise prediction rules from current species–environment relationships, which then replicate distribution predict future two scenarios (2×CO2). RTA allows different variables control value predictions at regions, e.g. northern versus southern range limits species. outputs represent ‘environmental envelope’ shifts required by species, while predicts realistic based colonization probabilities varying abundances within fragmented landscape. The shows severely limited in regions high forest fragmentation, particularly when low abundance near boundary. These tools providing mechanisms evaluating relationships among various environmental landscape factors associated with tree-species changing global climate.