Plan and methods

PINEA project main objectives are:

(i) the calibration and validation of a process-based model for Pinus pinea in Portugal. This model will allow estimates of the productivity of existing stone pine plantations to be made in the context of climate change, considering different climatic scenarios. It will also be a tool to support decision-making regarding new plantings;
(ii) to evaluate the effects of water and nutrient availability on Pinus pinea growth and nut yields;
(iii) to improve existing Pinus pinea modeling equations regarding growth and nut yield.

The PINEA Project also has the following objectives:
(a) to analyze several fertilization alternatives in the establishment and early growth of Pinus pinea stands;
(b) to assess the success of grafting in response to several fertilization treatments;
(c) to analyze shifts in allocation of root, leaf and stem biomasses in response to water and nutrient availability;
(d) to develop a methodology to include the fraction of cone biomass within the carbon allocation of a process-based model;

The PINEA Project will be based on existing Pinus pinea data including permanent sample plots, previous biomass trials, and will use an established fertilization trial. New data will be obtained by the establishment of irrigation and fertilization trial where data will be collected as well as new data from the existing permanent sample plots and fertilization trial. All the existing and new data will be validated and organized in databases. Following the database development the data will be analyzed in different ways having in mind that one of the major objectives is to have a process-based model calibrated for Pinus pinea. The methodology which will be used is detailed in each respective task.

Process-based models have the ability to deal with aspects which have traditionally been difficult for forest empirical models such as decisions on fertilization, selection of land for the establishment of new plantations and strategic scenarios (e.g. long-term wood supply planning). Their application in forest management has been already demonstrated and reviewed (Fontes et al. 2010). Within the current process-based models a 3-PG model has been parameterized for a large number of species including Eucalyptus globulus, E. grandis x urophylla, E. grandis x camaldulensis, E. grandis, Pinus taeda, Pinus ponderosa, Pseudotsuga menziesii, Pinus patula, Picea sitchensis, Corymbia maculata, Araucaria cunninghamii, E. pilularis, E. delagatensis, Picea abies, Pinus radiata and P. elliottii (Fontes et al. 2006) and results based on such extensive work confirm that the principles underlying the model are sound and hold for a wide range of evergreen forests (Landsberg et al. 2005). One of the main challenges for calibrating and validating a process-based model for Pinus pinea is that one of the main interests in Pinus pinea is its nut yield. This will imply a very innovative approach, to include in a process-based model such as 3-PG an allocation to cone/fruit biomass. Fruiting bodies tend to be the highest priority sinks for carbohydrates from foliage. In extreme cases i.e. if there is a very heavy fruit (cone) load, the fruiting bodies will take virtually all available resources so that the leaves, particularly those in the immediate vicinity of the cones, may die back towards the end of the cone/nut growing season. The PINEA Project intends to insert another sink for carbohydrates into the 3-PG code and, in any growth interval (month) make the allocation to nuts the first priority, with the residual allocated to roots, stems and leaves on the same basis as in forest trees.

So we have
dwc/dt + dwr/dt + dws/dt + dwf/dt = dW/dt

where wc, wr, ws, wf = mass of cones, roots, stems and foliage, and W is total mass of the tree. If there are no cones then dwc/dt = 0 and partitioning is as in 3-PG. In finite difference form, with dt standard (say ?t is a month) the equation is
? wc + ? wr + ? ws + ? wf = ?W, the change in mass over ?t.

The PINEA Project will be set up to get the right data to test this hypothesis. The establishment of an irrigation and fertilization trial for stone pine will be an important step to get these data. 

The PINEA Project expects that tree and branch growth will be affected by the number of cones the tree/branch is carrying. So if 2 trees start out the same size, but one has (a significant number of) cones (+) and the other 0 cones, the + cones tree will grow more slowly – reflected in different diameter growth rates. Similarly, branches with and without cones will have different growth rates; it would be very useful to be able to pick this up in terms of foliage area/branch. These tree growth measurements provide the basis for the carbon allocation analysis that provides the basis for applying a 3-PG type mode. It will be interesting to see how cone growth interacts with fertilizer and irrigation: since these result in increased foliage growth we would expect nut growth to be increased. Do they take all the extra carbohydrate available?

The fertilization and irrigation trial will provide an understanding about how water and nutrient availability influence nut yield, root biomass, leaf biomass and stem biomass. This experiment imposes a range of conditions wider than the range likely to occur naturally. This allows the researchers to assess the responses of the trees to conditions that might not normally be encountered. This is called ‘filling the variable space’. It allows the factors that limit growth to be assessed without the, sometimes confounding, interactions that may result from water shortages. Irrigation to eliminate water stress in some treatments also allows the response functions of various processes to be determined and provides information essential for the parameterization and testing of process-based models, which is one of the objectives of this project. It would be important to impose irrigation treatments on this experiment whether or not widespread commercial irrigation of stone pine is likely in Portugal. The resulting model should allow evaluation of the potential growth and productivity of the pines in any area and it will be able to make predictions under different climate change scenarios.


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