Abstract
Climatic and topographic factors control the distribution of forests across the globe. The present study investigated the impacts of these factors on spatial distribution of sub-tropical (scrub and pine) and moist temperate forests in Pakistan. The study used Digital Elevation Model (DEM), Sentinel-2 images and climatic data to quantify the impacts of climatic and topographic factors on distribution of forests. The data was statistically analyzed using correlation coefficient (R), liner regression and decision tree. Results specified six forest types during stratification. These types were significantly related to topographic (elevation) and climatic factors. Correlation coefficient (R) indicated strong positive relationship with elevation (R= 0.02) followed by annual mean temperature (R= 0.76). Similarly, annual precipitation indicated positive relation with R value of 0.53. Stepwise linear regression model showed that elevation, precipitation seasonality and annual temperature range were strongly significant with overall R-2 of 0.85. Decision trees were developed to explore passible interactions of predictors to determine imperative factors. Results of decision trees of both growing methods (Chi-squared Automatic interaction Detection (CHAID) and Classification and Regression Trees (CRT)) showed elevation was the most important factor that predicted particular forest type. Moreover, other factors such as temperature of the driest quarter, annual precipitation, precipitation seasonality and slope Were identified as important factors in CRT. The present study concluded that forest types were strongly influenced by climate and topography. However, elevation was the best predictor, has significant relative importance and can he used for detailed forest stratification.