Carbon accounting: forest growth rates and changing climates
Authors: Mason, E G; Woollons, R C; Manley, B R
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Executive summary
Global climate changes may impinge on the future growth of New Zealand plantation forests. Since the latter represent a major export industry, it is clearly expedient to consider mechanisms by which any growth changes can be identified and estimated as to their magnitude.
Irrespective of the size of climatic change, it is by no means straightforward to suggest methodology that will satisfactorily estimate potential changes in forest growth. This is so, because:
- More favourable weather conditions do not guarantee significant increased growth. Liebig's law suggests that many forest regions will be restrained by other limiting growth factors, for example nutrition.
- Contemporary evidence was that carbon dioxide levels are increasing and traditional thinking has been that this will result in faster plant growth. However, recent experiments at American universities question this. There is mounting evidence that in some years, additional tree growth is minimal, or trees quickly adapt to new environments, with only transient responses.
- NIWA has produced estimates of climate change in New Zealand. These will necessarily be regarded as benchmark figures and essentially, known constants.
- Any prediction of forest growth response will be associated with a significant risk factor.
- Changes in climate will have impacts on soils, for example the depth of the A-Horizon. The sizes of these changes will need to be estimated. Recent work at the School of Forestry (SOF), Canterbury University suggests that current estimates of plant available soil water may be inappropriate for forest modelling.
There is a huge empirical Pinus radiata database of stand growth available in New Zealand to supply, in part, data necessary to construct models of forest growth through climate change. Concurrent and matching climatic data are available though electronic splined data layers, developed by Landcare and NIWA.
Forest modellers utilise sigmoidal-type yield equations to estimate stand yield. Adoption of the sigmoid shape is well justified empirically as well as being easily vindicated on physiological grounds.
Sigmoid yield equations are usually expressed in so-called projection form, where initial yield and a known age are included as predictor variables. The practice achieves substantial gains in precision, but the models are not ideal for climate/growth studies. Inclusion of initial yield, for example basal area/ha7as a predictor variable, tends to make other climatic predictors superfluous. Basal area is an excellent surrogate for stand production and is very closely correlated with future yield. Fortunately, projection equations can be modified to accommodate climatic predictors, referred to here as hybrid models.
Three published studies describing climate and growth models are briefly summarised. Two of these relate to specific localised areas utilising age, temperature, annual rainfall, or solar radiation as predictor variables. The third work8 attempts a national growth model for Pinus radiata, using climatic variables. The paper describes methodology for circumventing the problem of initial yield masking climatic effects. Utilisation of stratification based on Landcare weather layers or utilising hybrid models involving solar radiation and available water potential, led to more efficient prediction compared to standard projection equations.
Two new climate growth models have been prepared for this report. The first takes further an earlier study9 looking at the prediction of stand top-height in terms of age and a set of topographic/climate predictor variables. A new basal area model for the North Island predicts net basal area/ha in terms of age, stems/ha, depth of the A-horizon and annual rainfall. An additional model predicts volume/ha in terms of top-height and basal area. The set of models are then applied to Central North Island (CNI) forests assuming small future increases in rainfall and A-horizon depth. The second new study addresses CNI forests and represents a hybrid growth model approach. Mechanistic prediction models are constructed for top-height and basal area.
Age variables are replaced by monthly accumulated light sums modified for temperature, recognising the minimum, optimum and maximum temperatures for photosynthesis. NIWA has recently released estimates of likely changes in New Zealand weather conditions10. The main implications for Forestry are that average temperature will be 0.9oC higher by 2040; by 2090 the figure is 2.1oC. Rainfall forecasts are mixed. For the CNI, little change is predicted. Wind levels are expected to increase. No estimates are given for solar radiation or vapour pressure deficit.
The new hybrid model equations are utilised to estimate increases in productivity using the NIWA 2040 climate predictions. Extra volume in a 30 year rotation in the order of 70-100 m3/ha is indicated but it is emphasised that these projections are subject to the full realisation of several assumptions.
This report has been developed in a short time frame and further work is desirable to produce more detailed and reliable estimates of productivity response through climate change. These include the development of hybrid models in regions where rainfall changes are predicted. These models will require water balance models but recent surveys show current estimates of plant available water are unrealistic for forest soils. Further sampling over the country is required to calibrate current estimates. There is also an urgent need to reconcile the apparent differences between NIWA and Landcare climate data.
7 Basal area/ha is an internationally adopted forestry expression for quantifying stand yield. Tree diameter is usually measured at 1.4 m above ground, so called DBH (Diameter at Breast Height). Assuming a circle, DBH can be expressed as an area. The sum of these areas for all trees occupying a stated area, but standardised to one hectare, defines basal area/ha.
8 Dzierzon, H. and Mason, E. G., 2006
9 Woollons et al., 2002.
10 Ministry for the Environment, 2008
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