Impact of the New Zealand Emissions Trading Scheme on forest management 1

We evaluated the impact of carbon trading on forest management. Questions examined were: whether to plant at all; if so, what species and silviculture to use; and when to harvest. Revenue from annual sales of carbon units greatly increases the profitability of all species and regimes. Indeed, if the price remains at $30 per tonne of carbon dioxide equivalent then nearly all forestry investments regardless of site quality are capable of paying $3000/ha for the land and still achieving an 8% real rate of return or higher. If the price of carbon is zero, the most profitable species/regimes are, in order: radiata pine grown on a clearwood regime; radiata pine grown on a framing regime; radiata pine with a plant-and-leave regime; Douglas-fir; Eucalyptus nitens; and indigenous forestry. This ranking alters substantially with high carbon prices. Radiata regimes which have higher volume become favoured over regimes that produce trees of large piece-size or clearwood. Eucalypt regimes become relatively more profitable than low-volume radiata regimes. Radiata pine on a high-volume regime, however, remains the most profitable species under the scenarios we examined. With regard to the details of radiata pine regimes, a rising carbon price favours late thinning, and high final stocking and discourages pruning. As the carbon price increases, a plant-and-leave regime dominates and there is a general lengthening of optimum rotation age. These trends apply across all site qualities. The benefits of carbon trading are less obvious for stands that were planted in the 1990s compared with future stands, because much of the carbon sequestration has already taken place with no payment. Nevertheless, carbon trading is still worthwhile. Whatever the date of planting, there are still some risks in “opting in” to the ETS, particularly with regard to cash-flow difficulties at time of harvest. Most of these risks can be avoided or mitigated by careful estate planning, albeit with a reduction in profitability. Growers can choose to retain sufficient units to cover any future liabilities, and to avoid situations where carbon liabilities at harvest greatly exceed expected revenues from the sale of timber. Alternatively, they may choose to modify their estates (by mixing species, regimes, or age-classes) so as to smooth out the future profile of their carbon stocks. Planting a normal forest achieves almost zero risk because there are no further carbon losses anticipated but it is more profitable to achieve normality by harvesting rather than by planting alone. Tree-breeding promises some carbon advantages, particularly where the gain is through volume growth rather than the lesser benefit of increased wood density. management. To this end, a class of Year Four students at the School of Forestry, University of Canterbury was tasked, as part of their Management Case Study, with optimising profitability under a range of inputs in a carbon-trading environment. The following inputs were varied: discount rates, carbon price, rotation age, date of planting (1995 or 2008), site quality, and silvicultural regime (initial and final stocking, timing and intensity of thinning and pruning). Genotypes were simulated that gave more volume or higher wood density. Three standard regimes were specified for radiata pine to represent contrasting silviculture: • Clearwood (Plant 800 stems/ha, prune to 5.5 m in 2 lifts, thin to 250 stems/ha at age 7.8 years). • Framing (Plant 800 stems/ha, thin to 375 stems/ha at age 7.8 years). • Plant & leave (Plant 800 stems/ha, no thinning). Regimes adopted for other species: • Douglas fir (Plant 1650 stems/ha, thin to 500 stems/ha at age 15). 1 This is a summary of a 29-page MAF contract paper (MAF-POL/ CP03 Research-01, Climate Change “Plan of Action” Research Programme 2007/2008, Objective 1). 2 Clare Andrews, Cameron Branch, Rebecca Coles, Blair Cooper, Tim Crone, Joseph Dakin, Hamish Dennis, Leslie Dowling, Cameron Eyre, Sally Haddon, Josh Lee, Jamahl Mannan, William Marshall, Sarah Orton, Daniel Phillips, Lawrie Scott, Aaron Smith, Cong Xu, Chen Yang.