Physiological growth modelling of forests in New Zealand
What is the problem?
How fast can different forests grow? And will they grow faster or more slowly in future? These are important questions both in terms of current and future wood supply for the forestry industry and for assessing the potential of our forests to sequester carbon to mitigate the effects of climate change. In the past, such assessments used empirical modelling approaches to provide growth estimates, but such modelling approaches have limited scope and reliability.
How did we approach resolving the problem?
In collaboration with NIWA and Scion, we used, for the first time in New Zealand, a physiologically-based modelling approach to model the wood growth and carbon storage of radiata pine. The model had originally been developed in Australia1, 2 where it had been applied to pines1, 3, 4, 5 and native forests.6, 7 The generic structure of the model, and its solid base of known underlying scientific principles, allowed its application to these diverse vegetation types. It has been tested against a wide variety of measurements ranging from short-term daily water and CO2 exchange rates to growth rates assessed and measured over years to decades.
The New Zealand work allowed testing against unique datasets, particularly growth rates from across the country. This tightly constrained the environmental drivers of growth and carbon storage and specific plant-internal relationships.8 The work provided a physiologically-based description of pine productivity under current conditions in New Zealand9 and the likely response to climate change.10 It showed that pine stands can grow by about 10 tC ha–1 yr–1 in the fertile, warm, wet western half of the North Island but by only 2–4 tC ha–1 yr–1 in Central Otago and Canterbury.9
It showed that pine growth is often temperature limited, with optimal growth occurring under the highest temperatures found in New Zealand. With climatic warming, stands are therefore likely to grow faster in the cooler parts of the South Island. In contrast, growth is likely to be reduced in the north and in the drier regions on the east coast of both islands, where any warming can intensify water limitations. However, even these limitations could be overcome through increasing CO2, provided plant responses will be as strong as currently seen in experimental observations.
Who has adopted our innovation?
The work has only recently been completed, so has yet to be adopted by the forest industry and policymakers. The growth estimates have been used in national-scale assessments of ecosystem services and forests.11, 12, 13 The model is used by Scion in MPI-funded work for assessing the time course of soil-carbon changes after land-use change and in work funded by the NZ Agricultural Greenhouse Gas Research Centre for modelling gas exchange of pastures under different management regimes. The model has also been used for modelling the growth of kānuka/mānuka stands in other MPI-funded work.
What impact has this innovation had on adopters?
Physiologically-based modelling allows more accurate estimates of growth and carbon exchange of forests. Having more reliable growth estimates under both current and future climatic conditions will allow the industry and policymakers to make better-informed planning decisions.
1Kirschbaum MUF 1999. CenW, a forest growth model with linked carbon, energy, nutrient and water cycles. Ecological Modelling 118: 17–59.
2Kirschbaum MUF, Paul KI 2002. Modelling carbon and nitrogen dynamics in forest soils with a modified version of the CENTURY model. Soil Biology & Biochemistry 34: 341–354.
3Kirschbaum MUF, Guo LB, Gifford RM 2008. Observed and modelled soil carbon and nitrogen changes after planting a Pinus radiata stand onto former pasture. Soil Biology and Biochemistry 40: 247–257.
4Simioni G, Ritson P, McGrath J, Kirschbaum MUF, Copeland B, Dumbrell I 2008. Predicting wood production and net ecosystem carbon exchange of Pinus radiata plantations in south-western Australia: application of a process-based model. Forest Ecology and Management 255: 901–912.
5Simioni G, Ritson P, Kirschbaum MUF, McGrath J, Dumbrell I, Copeland B 2009. The carbon budget of Pinus radiata plantations in south-western Australia under four climate change scenarios. Tree Physiology 29: 1081–1093.
6Kirschbaum MUF, Keith H, Leuning R, Cleugh HA, Jacobsen KL, van Gorsel E, Raison RJ 2007. Modelling net ecosystem carbon and water exchange of a temperate Eucalyptus delegatensis forest using multiple constraints. Agricultural and Forest Meteorology 145: 48–68.
7Kirschbaum MUF, Harms B, Mathers NJ, Dalal RC 2008. Soil carbon and nitrogen changes after clearing mulga (Acacia aneura) vegetation in Queensland, Australia. Observations, simulations and scenario analysis. Soil Biology and Biochemistry 40: 392–405.
8Watt MS, Kirschbaum MUF 2011. Moving beyond simple linear allometric relationships between tree height and diameter. Ecological Modelling 222: 3910–3916.
9Kirschbaum MUF, Watt MS 2011. Use of a process-based model to describe spatial variation in Pinus radiata productivity in New Zealand. Forest Ecology and Management 262: 1008–1019.
10Kirschbaum MUF, Watt MS, Tait A, Ausseil A-GE 2012. Future wood productivity of Pinus radiata in New Zealand under expected climatic changes. Global Change Biology 18: 1342–1356.
11Dymond JR, Ausseil A-G, Ekanayake J, Kirschbaum MUF 2012. Tradeoffs between soil, water, and carbon – a national scale analysis from New Zealand. Journal of Environmental Management 95: 124–131.
12Ausseil A-GE, Dymond JR, Andrew R, Parfitt R, Kirschbaum MUF 2012. Spatial assessment of multiple ecosystem services in New Zealand, with a case study in the Manawatu catchment. Environmental Modelling and Software (In review).
13Dymond JR, Ausseil A-GE, Kirschbaum MUF, Carswell FE, Mason NWH 2013. Opportunities for restoring indigenous forest in New Zealand. New Zealand Journal of the Royal Society (In review).