Picea abies site index prediction by environmental factors and understorey vegetation:: a two-scale approach based on survey databases

Relationships between site index, environmental variables, and understorey vegetation were examined for Norway spruce (Picea abies (L.) Karst.) in the eastern part of France. The study area concerns all the native range of Norway spruce in France and the northeastern plains. The analysis is based on 2087 plots from the French National Forest Inventory database. The data measured on each plot cover topography, soil, geology, and vegetation. Additional environmental variables were estimated using two methods: climatic data estimated from a climatic model developed by Meteo-France (AURELHY), and nutritional variables predicted from vegetation data and species indicator values. General linear model regression was used to predict site index as a function of environmental variables. The best model explains 64% of the site index variance and involves eight variables (elevation, mountain zone, topographic concavity, proportion of plot area occupied by rock outcrop, rock type, soil depth, pH, and C/N ratio). The two main results of this study are (i) the combination of large databases allowed the study of soil-site relationships and construction of a pertinent model, which covers a wide range of ecological conditions, and (ii) vegetation was found to be relevant to separate the effect of acidity from those of nitrogen nutrition on Norway spruce productivity.