Subalpine fir viability score, 2090 (GFDLCM21 GCM, A2 emissions scenario)
Dates
Original Data Basin Creation Date
2011-02-07 10:12:46
Original Data Basin Modified Date
2011-02-07 10:15:19
Summary
This dataset portrays the viability score (scale of 0 - 1.0) for Subalpine fir (Abies lasiocarpa) in western North America in 2090, using the Geophysical Fluid Dynamics Laboratory - Princeton University, NOAA Research (GFDLCM21) general circulation model (GCM) and A2 emission scenario (high emissions, regionally diverse world, rapid growth) to model future climate. (From Crookston et al. 2010): To develop the climate profile, we used a data from permanent sample plots largely from Forest Inventory and Analysis (FIA, Bechtold and Patterson, 2005) but supplemented with research plot data to provide about 117,000 observations (see Rehfeldt et al., 2006, 2009) describing the presence and absence of numerous species. The Random Forests [...]
Summary
This dataset portrays the viability score (scale of 0 - 1.0) for Subalpine fir (Abies lasiocarpa) in western North America in 2090, using the Geophysical Fluid Dynamics Laboratory - Princeton University, NOAA Research (GFDLCM21) general circulation model (GCM) and A2 emission scenario (high emissions, regionally diverse world, rapid growth) to model future climate.
(From Crookston et al. 2010): To develop the climate profile, we used a data from permanent sample plots largely from Forest Inventory and Analysis (FIA, Bechtold and Patterson, 2005) but supplemented with research plot data to provide about 117,000 observations (see Rehfeldt et al., 2006, 2009) describing the presence and absence of numerous species. The Random Forests classification tree of Breiman (2001), implemented in R by Liaw and Wiener (2002), was then used to predict the presence or absence of species from climate variables. The Random Forests algorithm outputs statistics (i.e., vote counts) that reflect the likelihood (proportion of the total votes cast) that the climate at a location would be suitable for a species. We interpret this likelihood as a viability score: values near zero indicate a low suitability while those near 1.0 indicate a suitability so high that the species is nearly always present in that climate.
