Using phytogeomorphology, cartography and GIS to explain forest site productivity expressed as tree height in southern and central Finland

Using geomorphological knowledge, spatial data and GIS methods, one can obtain phytogeomorphological site variables describing interactions between landforms and vegetation. We used 15 site variables derived from maps to explain forest site productivity in southern and central Finland expressed as dominant height of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies [L.] Karst.) with ages of 30–110 years. These site variables were grouped into two: Group 1 with seven variables describing geographical conditions of sites including climate, and Group 2 with eight variables describing local morphometric and soil properties. We calculated slope and aspect from a 25 × 25 m DEM. The catchment area, calcium content in soil, length of the growing season, radiation index, sea index, lake index, past highest shoreline and total annual temperature sum with threshold + 5 °C were also obtained. Then we classified the landforms of 688 sample plots into four major types and 15 sub-types. We applied regression analysis to explain the tree height as a function of the tree age and the phytogeomorphological site variables. When the tree height was explained with the tree age and the Group 1 variables, the remaining standard error of the model was 16.6–17.9%. When the Group 2 variables were added to the analysis, the standard error decreased slightly. The most significant variables were the temperature sum, latitude coordinate and length of the growing season. Other significant variables were elevation, slope and aspect. The major landform types, sub-types and watershed area did not explain the tree height. Furthermore, if the forest site types determined in the field were included, the remaining standard error decreased by ca. 2%, showing the importance of field information.