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Table 2 Variables used as predictors in random forest models

From: Classifying forest inventory data into species-based forest community types at broad extents: exploring tradeoffs among supervised and unsupervised approaches

Category Variable Description
Climate Bio2 Mean diurnal range (Mean of monthly (max temp - min temp))
  Bio6 Minimum temperature of coldest month
  Bio8 Mean temperature of wettest quarter
  Bio15 Precipitation seasonality (coefficient of variation)
  Bio16 Precipitation of wettest quarter
  Bio18 Precipitation of warmest quarter
Landscape Landsc. cond. Landscape condition
  Prop. forest Forest area density
Landscape soil DI Soil drainage index
  PI Soil productivity index
Local soil Bedrock depth Depth to bedrock (cm
  Pct. clay Percent clay (< 0.002 mm size)
  Pct. org. Matt. Organic matter content (% by weight)
  Pct. sand Percent sand (0.05–2.0 mm size)
  Pct. silt Percent silt (0.02–0.05 mm size)
  pH Soil pH
  Sieve 10 Percent soil passing sieve No. 10 (coarse)
Topographic East Easting: sin(aspect)
  Elevation Elevation
  North Northing: cos(aspect)
  Slope Slope
  TPI Topographic Position Index
  1. See Additional file 1 for a list of all variables considered as well as data sources for all