Literature review

Pinus pinea, or stone pine is the 6th most important tree species in Portugal, covering an estimated area of 130,400 ha in 2006 of which 46,300 ha are young pure plantations. The largest increase in planted area since 1995 has been with Pinus pinea (Rego 2007). Portugal has the second largest area of Pinus pinea after Spain which has 456,600 ha (Ministerio de Agricultura Pesca y Alimentación 2007). Together the Iberian Peninsula accounts for approximately 75% of all stone pine stands. 

Environmentally the species is well adapted to the high temperatures and drought (Montero et al. 2004a) characteristic of Mediterranean climates. It is less sensitive to diseases and pests than other Mediterranean pines and particularly to the pine wilt nematode, Bursaphelenchus xylophilus. It has been in the country since 1999 and, from 2008 has affected the whole of Portugal. This resistance increases interest in Pinus pinea as a replacement for badly affected Pinus pinaster. Stone pine is indigenous to Portugal and is particularly important socially in the Sado river valley. It has long tradition of being grown there and provides local employment (ANSUB 2005). 

It is not a fast growing species, nor is its timber very valuable. Its value comes mainly from its nuts (Mutke et al. 2005a) which are the most important edible product of Mediterranean forests (Calama et al. 2007b). In 2011, cone/nut production represented 22 million euros (Calado 2012). Production by stone pine in Portugal is high; at on average 193 kg of cones per ha in 2006 (Gabinete de Planeamento e Políticas 2006) compared with 124 kg/ha in Spain (Ministerio de Agricultura Pesca y Alimentación 2007). Mechanical harvesting of cones has modernized cone collection and increased economic interest (Gonçalves 2006). 

For a particular stone pine stand nut yields depend on several factors including the age of the trees, site index, health, number of tress per hectare, pruning, thinning, etc. (Montero and Canellas 2000). Nut yields vary annually and it has been demonstrated that these are mainly due to climatic factors the most limiting being water stress (Mutke et al. 2005b). The number of flowers in a particular year depends on the winter of the previous year as this has a direct relationship to the formation and number of cone buds. Therefore a good cone initiation year is linked to the previous year’s rainfall. In addition, the size of the cones produced in the 3rd year, the year when they are harvested, varies. Nut weight/cone weight ratios depend upon the precipitation from late Spring to early Summer of that year. Good cone initiations to a good harvest in the 3rd year occur when there are neither extreme temperatures nor extreme droughts (Calama et al. 2007a). 

Mutke et al. (2007a) have reviewed the main stand management practices for stone pine cone production. For example, added fertilizer has been found to have a positive effect on stem growth (Lerena et al. 2000) and on nut yield (Calama et al. 2007b). Recent work based on a 4 year-old trial has shown that in an irrigated treatment, 50 liters per tree per week during June and July yielded four times more cones than the control (Mutke et al. 2007a; Mutke et al. 2007b). In addition, in Portugal, the positive effects of irrigation and fertilization of this species have been demonstrated in an unquantified manner on golf course greens where nut yields are higher than in unmanaged neighboring stands. 

In Portuguese stone pine stands grafted material has been used to create productive plantations. This technique anticipates the cone/nut production. Since the 1980s workshops and courses have been held to publicize this technique. A manual outlining grafting techniques has been available since 2007 (Carneiro et al. 2007).

Most Pinus pinea modeling including nut yields has been done in Spain and started mainly in the 1990s(Calama et al. 2007c). Current work has been done using the PINEA2 model. This is a single tree, distance independent model, parameterized for different regions in Spain (Calama et al. 2008b). It was developed for even aged stands and adapted for multi-aged ones (Calama et al. 2008a). In Portugal there is very recent work on modeling cone weights (Freire 2009). However this work has serious limitations due to the small dataset available. In addition, up to now there has been no process-based model calibrated and validated for Pinus pinea. Therefore, in the context of climate change, there is no model for evaluating how Pinus pinea might respond. Due to the importance of climate on Pinus pinea nut yields (Calama et al. 2007a; Mutke et al. 2005b) this is a crucial deficiency. 

It has been estimated, based on the increase in plantation area increase between the two most recent National Forest Inventories (1995/1996 – 2005/2006) using 2011 prices that about 39 million euros have been invested in afforestation of new stone pine plantations. Nevertheless the little research has been carried out during this period and little information is available to support the management of stone pine. Without the current funding it will be possible to increase the dataset slowly for improving empirical models, particularly in the growth of trees rather than in terms of cone and nut yields which are what stone pine managers want to know. Data collection for cones and nuts are more expensive than the traditional biometric data collection of diameters and heights for empirical growth models. Therefore it will be not possible to have reliable empirical models for cone and nut production or a process–based model at all.


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