PhD Scholar
Improving fine scale soil classification to support forest operational management
E-mail: jie-lian.beh@anu.edu.au

Knowledge of the spatial variation in soil properties is fundamental for the effective implementation of precision forestry. The scale required for precision forestry is fine (high resolution) and requires the ability to detect trends over a matter of metres rather than several hundred metres. Various approaches to model trends at this scale from process models have had only partial success.

In forest plantations, there is some standardisation in tree genetics, planting and establishment procedure and at a local scale, relative homogeneity of climate. The important variation in any site could thus be attributed to variation in soil properties (including depth, carbon content, water holding capacity etc.). It is hypothesised that variation in soil characteristics is reflected in some variation in the tree growing at that point. As a tree may be "exploring" the soil within a few metres of its main trunk, individual tree characteristics may therefore be effective predictors of soil characteristics at the appropriate scale.

The results of this research may have several potential applications including: enabling precision forestry even if soil properties are unknown, allowing tree shape to be predicted given soil properties are known, improving soil carbon assessment and improving water quality and erosion potential modelling.