Abstract

Background: Development of a relatively simple growth modelling approach for plantation species that allows derivation of cardinal (base, optimum and ceiling) air temperatures for growth, whilst accounting for changes in organism size, would represent a considerable advance over existing models. Such an approach would provide insight into species phenology and, in an agronomic setting, allow growers to closely match species to sites. Here, a model is described that can be used to predict seasonal variation in growth and cardinal air temperatures from simple seasonal measurements at a single site. Methods: The model was applied to data from an irrigated trial comprising two Eucalyptus species and three Eucalyptus crosses. Using measurements of mean daily air temperature data and stem volume, taken over a two year period, the model was fitted to the data and used to estimate cardinal air temperatures for the five species/crosses. Results: The model predictions corresponded well to the actual data for all five species/crosses, with R-2 ranging from 0.993 to 0.999. The optimum air temperature, To, for E. camaldulensis x E. globulus of 26.9 degrees C significantly exceeded To for the other four species/crosses, where To ranged from 15.4 to 18.7 degrees C. As To for E. camaldulensis x E. globulus was close to the highest mean daily air temperature recorded at the study site, the air temperature modifier for this species was almost always sub-optimal and consequently this cross was not well matched to the site. In contrast, To for the other four species/crosses were considerably closer to the mean air temperature of the site with T-o for E. nitens most closely approximating the mean air temperature (15.4 vs. 13.0 degrees C). Conclusion: The described approach can be used to account for complex variation in seasonal growth patterns and provides insight into how well a species may be matched to a particular site. As climatic information is available at a range of scales (from local to global), this type of model is likely to be useful for producing maps that describe species growth and areas of optimal suitability.