Efficient thinning regimes for Eucalyptus fastigata: Multi-objective stand-level optimisation using the island model genetic algorithm

Abstract

A stand-level optimisation problem formulated to determine a set of efficient thinning regimes satisfying two objectives, i.e. value production for sawlog harvesting and volume production for a pulpwood market, was demonstrated for a Eucalyptus fastigata trial in Kaingaroa Forest, New Zealand. Genetic algorithms were used to estimate the set of efficient thinning regimes (i.e. regimes that occur when it is not possible to increase the achievement of one objective without reducing another) known as a Pareto frontier. Each thinning regime specified a unique combination of initial planting density; frequency, timing and intensity of thinning; final crop number; and rotation length. Specifications for the “best” regime in the Pareto set (i.e. the one that satisfied a balanced trade-off between value and volume production) were similar to those recommended through professional judgment based on pooled long-term field observations from different eucalypt species grown throughout New Zealand. The advantage of Pareto optimality was the ability of not only identifying a unique thinning regime, but equally efficient regimes each providing a different combination of value and volume production. Research on this approach has the potential of being applied to other forest sites, providing there is sufficient re-measurement data to reflect stand growth dynamics.