How the maps were generated
Combining aspects of traditional geographical information systems and statistical clustering techniques, multivariate spatio-temporal clustering (MSTC) statistically models environmental niche envelopes to forecast a species' geographic range under altered environmental conditions expected as a result of global climate change. Global in scope, it incorporates 17 spatial environmental variables and generates maps at a resolution of 4 km2.MSTC generates three sets of maps:
- Maps of currently acceptable habitat for each species based on the environmental characteristics of locations where it is known to exist. Forest Inventory and Analysis (FIA) data, collected from approximately 125,000 inventory plots across the conterminous United States and southeastern Alaska, is used as this training data for most species. For rare tree species not well sampled by FIA, training data are from other sources, including range boundaries and information available through the Global Biodiversity Information Facility.
- Maps of the future location and quality of habitat for North American forest tree species at two time steps (2050 and 2100), under two global climate models (Hadley model and Parallel Climate Model [PCM]), and under two emissions scenarios (higher emissions [A1] and lower emissions [B1]).
- Maps of the straight-line minimum required migration (MRM) distance from each 4 km2 grid cell in a species' current suitable habitat to the nearest favorable future habitat. The greater this distance, the less likely that the species will be able to reach the nearest refuge, and the more likely that the species will become locally extinct.
