Regional estimation of Japanese cedar (Cryptomeria japonica D. Don) productivity by use of digital terrain analysis

Abstract

Digital terrain modeling and spatial climatic data have been used to estimate the spatial distribution of Japanese cedar (Cryptomeria japonica D. Don) forest productivity on a regional-scale. The study was conducted on Japanese cedar forests in Himi city, Oyabe city, Takaoka city, and Imizu city (a total area of 683 km2) in northwestern Toyama Prefecture. On the basis of data from 146 sample stands, above-ground net primary productivity (ANPP) was calculated from tree height, age, and density using existing ANPP conversion equations for Japanese cedar stands. Six topographic factors (slope, profile curvature, plan curvature, openness, wetness index, and topographic radiation index) were calculated from a 10-m cell size digital elevation model. Three climatic factors (annual mean temperature, annual total precipitation, and annual maximum snow depth) were obtained from an existing spatial data set. Relationships between ANPP and environmental factors were analyzed by regression tree models. For the tree model with ANPP as a dependent variable, four environmental factors (annual mean temperature, wetness index, openness, topographic radiation index) were adopted as independent variables. Annual mean temperature was the first split variable in this model and explained 25.5% of the total deviance in ANPP. Wetness index, which represents soil moisture variation caused by lateral flow, explained 11.5% of the total deviance in ANPP. The resulting tree model explained approximately half of the total deviation in ANPP and indicated that the spatial distribution of Japanese cedar productivity was controlled by regional-scale interactions between climatic and topographic processes. A high-resolution map of productivity was prepared by use of the ANPP prediction model and vegetation information obtained from satellite data.