Task 9 – Adaptation and calibration of a process based model for Pinus pinea

This Task will provide a process-based model adapted and calibrated for stone pine in Portugal. Existing data from Permanent Sample Plots, biomass experiments and from the established irrigation and fertilization trial will be used for calibration and validation. The nut yield data which will be produced by the PINEA Project from the irrigation and fertilization trial. This will be particularly important for the model as it will allow the inclusion the fraction of cone biomass within the carbon allocation sub-model.

Within the current family of process-based models, the 3-PG model developed by Landsberg and Waring (Landsberg and Waring 1997) was a deliberate attempt to bridge the gap between conventional growth and yield models and detailed process-based models. It has been parameterized for a large number of species (Fontes et al. 2006) and results based on extensive work confirm that the principles underlying the model are sound and hold for a wide range of evergreen forests (Landsberg et al. 2005). 3-PG will, in principle, be the model to be used by the PINEA Project. 3-PG has been already calibrated and validated successfully for many forest species including several several pines (Landsberg et al. 2003) but it will be the first time this is done for Pinus pinea. In addition, it will be the first time that nut yield prediction will be added to the model.

For this Task it will be necessary to have stone pine, climate, soils and site data validated and organized in Task 5. The data expected to be produced by the PINEA Project follow the recommendations on the type of data required to develop and test the 3-PG model and to estimate its species-specific parameters (Sands 2004). 

The methodology needed to include the fraction of cone biomass within the carbon allocation sub-model of a process-based model will be explored. However, even without the prediction of nut yield, the process-based model will still be useful for new planting decisions in relation to stone pine since, despite some exceptions, the sites with high site indexes also have high stem biomass and nut yields(Montero et al. 2004b).

Calibration of 3-PG will use only a part of the Permanent Sample Plots data; the other part will be used for model validation. Therefore, with independent data there will be estimates of model accuracy (bias and precision). The validation will be carried out at the level of outputs in relation to empirical data relating to the whole system. It is often difficult to determine whether deviations from predicted performance are caused by variations in the system, by inadequacies of the model, or by incorrect values for sub-model parameters when a process-based model is validated. Spatial variability in forests causes variation in growth rates, even for forest stands regarded, for practical purposes, as homogeneous. Thus, corresponding variability in model predictions should not be mistaken for inaccuracy. On the other hand, problems with parameter estimation of process-based models caused by lack of precise data and an incomplete understanding of some important processes are known (Makela et al. 2000).

Finally, after 3-PG calibration and validation we will use the results to predict how Pinus pinea stands will respond under future climatic conditions. 3-PG uses data inputs ranging from climate variables and soil variables to stand age to calculate the amount of carbon converted to biomass. By using climate data to determine growth rates, 3-PG will be able to predict Pinus pinea growth under climate change in Portugal. As there has been a continuous evolution in terms of climate change scenarios for Portugal, the climate scenarios to be used, namely predictions in terms of rainfall and temperature, will be the ones considered most realistic when this work is done in 2014. A new version of the 3-PG model has already been developed to include responses to changing atmospheric CO2 concentrations (Landsberg and Sands 2011).


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