white oak (Quercus alba) Model Reliability: High Model Reliability High

Geographic Predictors (GP) Map

The regression-tree diagram along with the corresponding class-map shows what predictors are driving the distribution for this species.

The regression-tree diagram for white oak

The Geographic Predictors Maps are derived from Regression Tree Analysis, where each terminal node of the 'tree' corresponds to a legend and map color that is represented on the map. As such, one can determine what variables may be driving the species' distribution and abundance at a particular part of its range. For example, a precipitation variable may determine the western boundary and a temperature variable may determine the northern boundary for a species. Also note that variables important high in the tree diagram relate to larger portions of the species' range, while those variables lower (closer to the terminal nodes) relate to more localized variables driving the distribution.

IMPORTANT: It is important to note that if the model reliability is NOT high for the species, then the confidence that the predictors in a single regression tree are driving the distribution is LOW. It is therefore worthwhile to compare the predictor importance according to the RandomForest model also. In the species page, click the "Statistics, Tables & Interpretations" button in the "Current Distriubtion" panel for viewing the predictor importance table under RandomForest model.

NOTE: Example: If tavg >< 6.5 means that if tavg > 6.5 deg C, traverse the left branch and if tavg < 6.5 deg C traverse the right branch.
If tavg <> 6.5 means that if tavg is less than 6.5, traverse the left branch. and if tavg > 6.5 traverse the right branch.

Geographic Predictor Tree Diagram Explained

Acryonm Predictor Group
PHSoil pHSoil Characteristics
PPTAnnual precipitation (mm)Climate
TAVGMean annual temperature (°C)Climate
TJANMean January temperature (°C)Climate
TJULMean July temperature (°C)Climate
TMAYSEPMean May-September temperature (°C)Climate
SPODOSOLSpodosol (%)Soil Type
ELV_MINMinimum elevation (m)Elevation
ELV_MAXMaximum elevation (m)Elevation
ELV_RANGRange of elevation (m)Elevation
ELV_MEANAverage elevation (m)Elevation
ELV_CVElevation coefficient of variationElevation
ALFISOLAlfisol (%)Soil Type
ARIDISOLAridisol (%)Soil Type
ENTISOLEntisol (%)Soil Type
HISTOSOLHistosol (%)Soil Type
INCEPTISInceptisol (%)Soil Type
KFFACTSoil erodibility factor, rock fragment freeSoil Characteristics
SLOPESoil slope (%) of a soil componentSoil Characteristics
ULTISOLUltisol (%)Soil Type
VERITSOLVertisol (%)Soil Type
WATERWater (%)Land-Cover
AWCTotal available water capacity (cm, to 152 cm)Soil Characteristics
BDSoil bulk density (g/cm3)Soil Characteristics
CLAYPercent clay (< 0.002 mm size)Soil Characteristics
JULJANDIFFMean difference between July and January Temperature (°C)Climate
MOLLISOLMollisol (%)Soil Type
NO10Percent soil passing sieve No. 10 (coarse)Soil Characteristics
NONFORNonforest land (%)Land-Cover
OMOrganic matter content (% by weight)Soil Characteristics
ORDPotential soil productivity (m3 of timber/ha)Soil Characteristics
PERMSoil permeability rate (cm/hr)Soil Characteristics
PPTMAYSEPMean May-September precipitation (mm)Climate
ROCKDEPDepth to bedrock (cm)Soil Characteristics
FRAGFragmentation Index (Riitters et al. 2002)Land-Cover
FORESTForest land (%)Land-Cover
AGRICULTCropland (%)Land-Cover