Random Forest trained to estimate Amazon maximum height based on enviromental factors

The Random Forest model obtained MAE = 3.62 m, RMSE  = 4.92 m, and R² = 0.735. we initially considered a total of 18 environmental variables: (1) fraction of absorbed photosynthetically active radiation (FAPAR; in %); (2) elevation above sea level (Elevation; in m);  (3) the component of the horizontal wind towards east, i.e. zonal velocity (u-speed ; in m s^-1); (4) the component of the horizontal wind towards north, i.e. meridional velocity (v-speed ; in m s^-1); (5) the number of days not affected by cloud cover (clear days; in days yr^-1); (6) the number of days with precipitation above 20 mm (days > 20mm; in days yr^-1 ); (7) the number of months with precipitation below 100 mm (months < 100mm; in months yr^-1 ) ; (8) lightning frequency (flashes rate); (9) annual precipitation (in mm); (10) potential evapotranspiration (in mm); (11) coefficient of variation of precipitation (precipitation seasonality; in %); (12) amount of precipitation on the wettest month (precip. wettest; in mm); (13) amount of precipitation on the driest month (precip. driest; in mm); (14) mean annual temperature (in °C); (15)  standard deviation of temperature (temp. seasonality; in °C); (16) annual maximum temperature (in °C); (17) soil clay content (in %); and (18) soil water content (in %). Among the initial 18 environmental variables, two of them (precipitation on driest month and months < 100mm) were excluded due to high correlation (> 0.80) to other independent variables.