Open access peer-reviewed chapter - ONLINE FIRST

Maritime Pine, Its Biological and Silvicultural Traits for the Basis of Natural Resources: An Overview

Written By

Teresa Fidalgo Fonseca, Ana Cristina Gonçalves and José Lousada

Submitted: September 13th, 2021 Reviewed: January 25th, 2022 Published: March 14th, 2022

DOI: 10.5772/intechopen.102860

Conifers - Recent Advances Edited by Ana Cristina Gonçalves

From the Edited Volume

Conifers - Recent Advances [Working Title]

Prof. Ana Cristina Gonçalves and Dr. Teresa Fidalgo Fonseca

Chapter metrics overview

48 Chapter Downloads

View Full Metrics


Maritime pine (Pinus pinaster Aiton) is a forest tree species with a high representation in southwestern European countries, in particular Portugal, Spain, and France. The species traits and their flexibility and plasticity are of importance both for timber and to the sustainability of the forest systems. Extensive research has been made on the maritime pine systems and productions. The aim of this study is to review the state-of-the art on the knowledge of the species, their forest systems, and their productions, to identify vulnerabilities and to summarize tools to help its management. The specific objectives of this review are: i) characterizing maritime pine, its distribution, genetic material and provenances, the biotic and abiotic disturbances, the diversity and sustainability of its forest systems; (ii) its management, encompassing the silvicultural systems and practices; (iii) to list existing growth models, simulators and decision support systems; and (iv) present information on wood technology, including sylvotechnology, wood properties, and their use.


  • species traits
  • distribution
  • silviculture
  • models
  • wood technology

1. Introduction

Maritime pine (Pinus pinasterAiton) is a conifer with a large area of distribution and of particular value, namely in terms of provisioning, regulating, and supporting ecosystem services. In Europe, its main distribution occurs in the Southwest Atlantic region (Portugal, Spain, and France), and to a lesser extent in other regions of Mediterranean influence. It has also been successfully introduced to other continents. One major benefit of the maritime pine forests, inherently associated with its expansion, is wood production and the supply of timber. The species plasticity and rusticity associated with its many functions, from production to protection, is linked to its wood quality and yields, make it a specie of primordial importance in several countries. Currently, it is prone to a suite of abiotic and biotic disturbances (e.g., fire, drought, pests, and diseases), which can act simultaneously or not. The forest system and production sustainability have to be thought holistically, with the selection of the better-suited management systems and sites to promote optimized yields and wood quality. The aim of this review is to provide information on the state of the technical knowledge of maritime pine and its forest systems. The objectives are fourfold: (i) distribution and ecology of maritime pine (Section 2); (ii) silviculture (Section 3); (iii) models, simulators, and decision support systems (Section 4), and (iv) wood technology (Section 5).


2. Distribution and ecology of P. pinaster

Maritime pine (P. pinasterAiton) is an evergreen conifer species belonging to Pinaceaeand Pinusgenera. It is a plastic specie characterized by its fast growth, shade intolerance, and being rustic ([1, 2] and references therein). Its area of distribution ranges from Portugal to Greece and from Morocco to Tunisia, whether as continuous ancient or recent areas (Figure 1, [3]). The specie is reported as native in France, Italy, Spain, Morocco, and Portugal [4]. It can be found outside its natural range in Australia, New Zealand, South Africa, Chile, Argentina or Uruguay [5], Turkey, the Balkans, United Kingdom, and Belgium (Figure 1, [3]). Its distribution is probably associated with the species traits’ plasticity and wood quality. The specie’s prolific seed production, wind-dispersed seed, and rapid growth rate, support the qualification of the species as an aggressive colonizer in some of the countries where it was introduced [4].

Figure 1.

Area of distribution of maritime pine (source: Caudullo et al. [3]).

Maritime pine develops for a range of mean annual temperature between 13 and 15°C, and 8 to 10° C in the colder months, mean annual precipitation larger than 800 mm (100 mm in the dry season), altitudes up to 800 m. It has low sensitivity to autumn and winter frosts, but high to spring ones, and has a high sensitivity to snow. It prefers soils of light texture, with good drainage and with a depth larger than 30 cm, where root systems develop better but do not tolerate, calcareous, saline, hydromorphic, and compacted soils. Its ability to grow in shallow and nutrient-poor sites is due to not being very demanding regarding mineral nutrition and by establishing ectomycorrhizal associations that improve its ability to uptake nutrients in soils with pH less or equal to 5 [1, 2, 6, 7, 8]. The root system consists of superficial roots, which ensure the stability of the tree and support the fine roots, responsible for the absorption of water and nutrients, and deep roots, which ensure the attachment to the soil and the tree’s access to water from deeper groundwater levels [6]. It provides good anchorage regardless of soil water content, except when in full saturation in sandy soils [9]. Nonetheless, the lower the nutrients’ availability the lower the potential growth of the trees [10, 11]. It reaches 30–40 m in height [12], its longevity is between 80 and 300 years [1, 2] and it is shade intolerant [2]. It resists well the summer water deficits, characteristic of the Mediterranean region, as due to the high sensitivity of the stomata to water deficit it is able to maintain tissue hydration at adequate levels [13, 14]. Its imminently pioneering character is notorious in the success of its use in the fixation of coastal dunes formed by sands poor in organic matter, minerals, and water retention capacity [2].

In France, maritime pine occupies an area of 1015 thousand hectares, with the Landes having the largest monospecific area. While it represents 5% of the metropolitan French forested area, it is the most harvested species with 6.7 Mm3/year of removals [15]. It is also widely distributed in northwest Spain, in the Autonomous Communities of Galicia and Asturias and the province of León, and is the most important coniferous tree species in terms of both surface cover, with an area of 433,754 ha, and wood production [16, 17] with a volume harvested in 2017 of 3.4 Mm3 [16]. In Portugal mainland, its distribution extends along a coastal strip of low altitude from North to South as well as in the inner North and Central regions, up to an altitude of 700–900 m mainly under Atlantic climatic influence, and mostly in the Southwest to North aspects. It is the most represented conifer species in northern and central Portugal, occupying an area of 713.3 thousand hectares and a growing stock of 67 Mm3 [18]. Wood availability is estimated at 1.8 Mm3, in 2018, with a consumption of 4.2 Mm3 [19]. Typical stands are shown in Figures 2-4.

Figure 2.

A mature stand ofPinus pinaster(Mata Nacional de Leiria, Portugal).

Figure 3.

Natural regeneration ofPinus pinasterafter clearcutting (Mata Nacional de Leiria, Portugal).

Figure 4.

Adult stand ofPinus pinaster(Vale do Tâmega, Portugal).

The importance of maritime pine is not confined to its area, but it is also related to its economic returns and goods and services its stands and forests provide. Maritime pine major products (wood and resin) have a wide variety of uses, involving a complex forestry-industrial sector and integrating, in addition to the set associated with the transformation of wood, a range of enterprises processing non-woody forest raw materials, with emphasis on resinous products. Its contribution to the national economies is relevant. For example, in Portugal, this sector has 8516 companies and is responsible for 57,843 employees (representing 88% of industrial companies and 81% of employment in the Forestry Sector) and generate 1225 € million of Gross Value Added, €4348 million of Turnover, and €1876 million of exports (3.1% of national exports of goods) [19, 20].

In Portugal, it is the main wood-producing species for general purposes, which, in addition to a medium wood density, combines good strength characteristics and easy working. According to [20], of the 4.5 million m3 of P. pinasterwood consumed in 2019 in Portugal, 1.82 million m3 corresponded to timber wood, 1.07 million m3 to pellets, 0.68 million m3 to wood panels, 0.56 million m3 for pulp and paper, 0.20 million m3 for biomass, and 0.15 million m3 for poles, pilings, posts, and sleepers. In addition, it has also to be highlighted the production of resin extracted from this species, which in the last 8 years has ranged from 6000 to 8000 t per year [20].

The importance of this sector goes far beyond the purely economic aspects, as its stands are essential for the populations life quality, with a direct impact on the quality of air, soil, and water and, in general terms, in the surrounding ecosystem. For example, P. pinasterforests constitute the largest carbon reservoir in the Portuguese forest (90.3 Gg CO2) and also the most carbon stored per hectare (119.4 t CO2/ha) [20].

Maritime pine stands, due to its low crown cover, result of its shade intolerance, enable the development of an herbaceous and shrub understorey. This understory encompasses a suite of species resulting in moderate to high species richness. Also, it serves as shelter and reproduction spots for several bird, mammal, and reptile species [21]. Diversity is also enhanced by the different stand structures, from pure even-aged to mixed uneven-aged [22, 23, 24].

The sustainability of the pine stands and their productions are dependent on their resilience to disturbances, which include type, intensity, and frequency. Silvicultural practices are disturbances of low intensity and high frequency, with the aim of promoting growth. In general, its effects promote the system sustainability. Inversely, high intensity and low-frequency disturbances, such as fires or storms, may endanger the system sustainability [25]. Maritime pine stands are prone to fires, especially when a well-developed understory promotes the continuity of the vertical profile of the stand. The effects of forest fires on forest stands in general, and on maritime pine in particular, are twofold: the destruction of the stand and effects on soil. The resilience of the stand is linked to the regeneration which in turn is associated with the intensity of destruction (total or partial), type of regeneration (sexual or asexual reproduction), and the availability of seeds (whether in the soil or in the tree crowns). Maritime pine regenerates by seed (it is not able to sprout) and as long as seed is available, stand regeneration occurs [26]. It is well known the effect of vegetation on soil conservation and reduction of erosion risk, which is especially relevant in climates subject to high-intensity rainfalls, such as the Mediterranean climate. Also, vegetation, especially the arboreal, gives a primordial contribution to the maintenance and improvement of the soil’s physical, chemical, and biological properties, thus contributing to maintain and improve site quality ([27] and references therein). Maritime pine stands are frequently in sites of low quality, many times in steep slopes areas with high-intensity rainfalls [28, 29]. Thus, its sustainability can be enhanced by disturbances of low intensity and high frequency, such as the silvicultural practices (thinning and pruning) that can prevent those of high intensity and low frequency, such as fires. Maritime pine is also vulnerable to wind damage [30]. Extreme wind events associated with severe extratropical cyclones (storms) have caused extensive damage in Europe. In France, Nouvelle-Aquitaine region, the damage of Martin and Klaus storms affected predominately maritime pine (37 million m3), which correspond to 15% and 32% of the maritime pine standing volume in the region in the former and latter storm, respectively [31]. The uprooting of trees and stem breakages have been reported for the species in Portugal [32, 33, 34], which may result from soil characteristics and individual tree social status, and the critical turning point at the base of the stem was correlated to tree size and particularly to stem weight or volume [35].

Among the biotic agents affecting the species, the pine processionary moth, Thaumetopoea pityocampa(Lepidoptera, Thaumetopoeidae) is referred to as the most serious pest in the Mediterranean region [4, 36]. The species is susceptible to Bursaphelencus xylophilus, the nematode that causes the pine wilt disease [4, 37], and to root rot pathogen Heterobasidion annosum[38]. Bark beetles (Ips sexdentatus, Orthotomicus erosus, Tomicus piniperdaand T. destruens) are also referred to as the main biotic agents causing economic losses to the species [37].

The maritime pine stands sustainability is also linked with climatic change. The increase in temperature and decrease of precipitation may result in a trend to its northwards distribution [28, 29]. Also, it seems that there will be a trend towards a longer dry season in the Mediterranean. One way to mitigate its effects is by reducing density through thinning in maritime pine stands and/or with mixed stands [39, 40] of maritime pine with other conifer or broadleaved species (Section 3.1).


3. Silviculture of maritime pine (P. pinaster)

3.1 Forest systems

Maritime pine is managed in high-forest stands [2] (see Figures 2 and 4). The structure is most frequently even-aged, whether from natural [41, 42, 43, 44] (Figure 3) or artificial [2, 40, 45, 46] regeneration. Traditionally, maritime pine is managed in pure stands. The preference for even-aged stands is related to easier management, promotion of wood quantity and quality [2, 40, 47, 48, 49, 50, 51], and disturbances, mainly fire or harvest events that usually result in one regeneration cohort shortly after disturbance, if seed is available [41, 42, 43, 44].

The uneven-aged structure is less frequent [22, 24, 42] probably due to the specie traits. Uneven-aged stands are more frequently developed with shade-tolerant species. Yet, uneven-aged stands have been successfully developed with shade-intolerant species with few cohorts (1 to 4) [52, 53, 54]. Several studies compare and discuss even and uneven-aged stands of maritime pine [55, 56, 57]. Uneven-aged stands of maritime pine are frequently originated from natural regeneration, whether as pure [22, 42, 47, 58] or mixed stands [23, 24, 59, 60].

The advantages of mixed stands in what concerns the stands’ sustainability while attaining similar or better yields than pure stands [52] enhanced the spread of maritime pine mixed stands. Examples are: P. pinasterand P. sylvestris[46, 50, 60]; P. pinasterand P. pinea, P. sylvestris, P. halepensisor P. nigra[39]; P. pinasterand Quercus pyrenaica[61]; P. pinasterand P. radiata[45]; P. pinaster, Castanea sativaand Quercus robur[23, 24]; and P. pinasterand Eucalyptusspp. [62]. While some mixed stands are originated from plantations [45] others are the result of natural regeneration [24, 42, 62]. Overall, mixed maritime pine stands have higher diversity [24, 50]; soil fertility is enhanced [50]; have a higher water holding capacity [63], and higher yields [60].

The development of maritime pine is determined by four broad factors; water availability, aerial growing space availability, tree “social” status (based on tree’s height relative to surrounding trees), and silviculture practices. Maritime pine stands in the Mediterranean climate are constrained by the available water. Several references [59, 61, 64, 65, 66, 67, 68, 69] indicate that growth occurs mainly in spring and autumn as a result of precipitation [67]. A study on the effect of precipitation on water uptake in maritime pine, stresses the effects of the temporal variability of rainfall and site on the water availability [67]. As the water absorption by maritime pine individuals does not occur immediately after the rainfall but has some delay in time [67, 68], it is better explained by a set of events of rainfall [67]. Also, summer precipitation (from May to September) seems to have low contribution to the absorption of water for two reasons: the precipitation amount is low and it is partially lost through evaporation. In mixed stands of P. pinaster and Quercus pyrenaica, spring growth of maritime pine is promoted in the early spring because leaf area is available prior to the oak’s [59, 61] and due to the maritime pine root system, which is able to develop in depth thus exploring a large volume of soil [70, 71]. Also, when under water deficit, maritime pine ceases growth both in spring and fall [59, 61, 64]. In fall, trees are able to grow if water is larger than what is needed for the rehydration [59, 64]. The geographic origin along with the climate influences the tree growth reaction to drought, with higher growth under Atlantic climates than under the Mediterranean ones, which is related to the xeric climate adaptation of the species [72].

All species have, to a lower or wider extent, plasticity which enables individuals to adapt to the available growing space, by maintaining or increasing light intersection, water and nutrients absorption, and reducing competition. Species plasticity results in the variation of tree allometry, which enables the maintenance of growth. Crown plasticity can be the result of stand structure and/or climatic conditions [52]. For maritime pine individuals the increase in density results in the reduction of crown size due to crowding, when individuals do not have enough aerial growing space, or when branch abrasion occurs. These phenomena constrain the lateral growth of the crown and being maritime pine shade-intolerant, the lower crown under shade dies, resulting in the regression of the crown [39, 73]. Drought also affects crown allometry. In sites prone to drought its crown tends to have a large volume. The larger crown volume can be explained by the stands’ low density, being trees in free growth thus expressing the growing habits characteristic of the specie; and as the main limiting factor is water; it is expected that belowground competition is higher than that above ground. As a consequence, the crown competition and the variability in its allometry are weaker on dry sites and stronger on humid ones [39]. Likewise, the increase of aridity decreases productivity both in pure and mixed stands, whether for volume [73] or for biomass [74].

Individual tree social status influences tree allometry and growth. In pure stands, the individuals in the lower social status (dominated) have lower sizes and growth rates, due mainly to the lower availability of growing space, light in particular. In mixed stands of P. pinasterand P. sylvestris, it was found a negative effect on dominated maritime pine individuals, probably due to the shade casted to those individuals. Inversely, in the admixtures of P. pineaand P. pinaster, and P. nigraand P. pinaster,the effects on the dominated trees were positive, which can be attributed to the different crown architecture of the species [39]. In P. pinasterand P. sylvestris, pure and mixed stands [60], maritime pine crowns in mixtures had smaller volumes (related to the specie shade intolerance), than in pure stands, and high competition for light was also found. Inversely, P. sylvestristends to keep its lower branches (as it is more tolerant to shade). Also, maritime pine tends to increase its height growth to enable the individuals to reach the upper canopy layer, and, thus to reach sunlight. This results in the ascension of its crowns, which is enhanced by the crown regression (i.e., the death of the shaded lower branches) and by the development of branches with steep angles in relation to the stem. The different behavior of the two species might promote the stand vertical stratification and the optimization of the available canopy space [60]. The former and the higher capacity to hold water off the mixed stands [63] may, at least partially, explain the increase in productivity [60], stocking, and total organic carbon [75] found in mixed stands when compared to pure maritime pine stands.

Defoliation in maritime pine individuals results in the reduction of growth, of −0.9% of increment in basal area per 1% reduction of leaf area. For 15–30% of defoliation, the reduction of growth is considerable [49]. In a drought study, Rodriguez-Vallejo [40] observed that leaf area reduction due to drought resulted in the reduction of tree growth and that in natural stands was lower than in plantations. The reduction of growth due to leaf area reduction is related to the decrease of transpiration, hydraulic conductivity, and increase in xylem embolisms as well as competition for water. Thinning reducing competition may mitigate drought impacts on tree vigor and growth in maritime pine plantations [40].

Differences in tree allometry can also be assessed based on the configuration of the tree stem profile and have a direct influence on stem volume. Calçada-Duarte [76] points to a large number of geometric volume shapes for the species, varying from paraboloid to a solid of intermediate features of cone and neiloid (stem form with high tapering), which can result in stem volume differences greater than 25% for trees with equal values of diameter at breast height and total tree height.

3.2 Silvicultural practices

The most frequent silvicultural practices in maritime pine stands are thinning and pruning. Thinning is used to regulate stand density. The goal is to maintain the best trees, that will reach the end of the production cycle and remove those that have lower growth rates (dominated), less desired stem shapes, or are dead or diseased [77] while providing intermediate economic revenues. The most frequent thinning method is from below (e. g., [2, 47]). This method is used because it is suited for shade-intolerant species and for sites with periodical drought season [77], which is the case of the maritime pine stands in the Mediterranean basin with an annual summer drought period. Thinning is of importance in these stands due to its effects on tree and stand growth; wood quality and quantity, especially when associated with pruning; and system sustainability, particularly to disturbances such as fire and drought. Due to its shade intolerance, their release should be done early in stand development [2, 78].

The thinning intensity can be based on empirical rules or defined by objective criteria, being usual to use of Wilson’s spacing factor [79] or Hart-Becking spacing index (H-B), widely used in France for coniferous trees (e.g., [80]), and Stand Density Index [81], the latter based on the self-thinning theory law. Density regulation based on SDI relies on the assumption that in monospecific even-aged populations of trees experiencing complete crown closure, mortality is density-dependent. The natural trajectory of the number of trees per tree size was defined by Luis and Fonseca [82] and revised by Enes et al. [44]. The use of relative values of SDI is suitable for management purposes, as it provides information on the appropriate number of living trees for given tree size, according to the management aims (e.g., optimum growth-density interval, maximization of stand volume, or maximization of mean tree size).

Arellano-Pérez [47] in maritime pine pure even-aged stands, used thinning from below with two intensities, light (removal of 20% of basal area) and heavy (removal of 40% of basal area), and compared them with unthinned plots. The authors observed that growth in diameter was the largest in the heavy thinning plots while total and crown base were similar in all treatments. Six years after thinning basal area was the largest in unthinned plots. The fuel load was lower in thinned plots, but that of the understorey had a slight increase in the thinned plots. Thinning reduces the probability of active crown fire probability but increases passive one. Overall, according to Arellano-Pérez [47] thinning did not affect fire severity and reduced potential fire risk. The effect of density on maritime pine growth is related to competition for growing space. The higher the density attained, the lower the growth, especially in diameter [58, 83]. Stands with high density are exposed to longer periods of hydric stress, especially during the drier months. Inversely, in low density stands, individual trees develop larger (deeper and wider) root systems, thus reaching water stored in the lower soil layers [83].

Nunes et al. [84] in a thinning from below experiment in maritime pine pure even-aged stands with intensity ranging from light to heavy, highlighted its importance in diameter growth while height growth was not affected. Another study in a mixed stand of P. pinasterand Quercus pyrenaica[59] observed the highest radial increments with heavy thinning intensity. The difference between treatments corresponded to the spring growth (earlywood) and was constrained especially by water availability, i.e., under drought, there was a reduction of radial growth. Inversely, the autumn radial growth (latewood) does not seem to be affected by thinning, probably because it is highly dependent on the precipitation amount [59].

Pruning is a silvicultural practice frequently associated with thinning. Its main goal is to form a knot-free wood stem as high as possible, the reduction of the knotty stem core (both in number and size) and to stop juvenile wood growth [2, 85]. Pruning is recommended for two reasons: to reduce the knots number and size, which is one of the most derogatory wood features when used for nobler applications (e.g., veneer, plywood, structural elements, and furniture), both in the wood appearance characteristics and their mechanical resistance [86, 87]; and the removal of the less photosynthetically efficient branches (frequently the lower), enabling an increase of the carbohydrate availability, thus increasing growth [88, 89]. Yet, pruning removes both dead and live branches, the latter reducing also leaf area, which may also reduce photosynthesis and thus growth [90]. Hevia et al. [45] evaluated the effect of light (12–15% crown removal) and heavy (29–37% crown removal) pruning in young (7–11 years old) pure even-aged stands of maritime pine, and compared the results with unpruned trees. The higher the pruning intensity is, the greater will be the reduction of diameter growth, while lower effects were detected for height growth. Similar results were attained by Courdier et al. [91]. The effects of pruning intensity are related to species traits, namely the architecture of the crown, leaf surface area, photosynthesis, shade tolerance, and growth rates; but also, to edaphic and climatic site characteristics [45]. Hevia et al. [45] observed that the increase of growth post pruning was related to site index, relative spacing index, age, and tree diameter, as well as stand structure prior to pruning. The authors mentioned that the better the site, the older the trees, and the larger the diameter, the higher the growth in diameter and height. The post pruning growth seems to be also linked to the reserves in carbohydrates; the larger the reserves the higher the growth ([45] and references therein).

3.3 Stand regeneration

The regeneration of a stand is linked to its forest system. Clear cutting is associated mainly with artificial regeneration while clear-cutting with standards, clear-cutting by strips and/or patches, and shelterwood systems are frequently linked to natural regeneration [92, 93]. The most frequently used regeneration systems in maritime pine stands are clear-cutting, clear-cutting with standards, and clear-cutting by strips [2, 46].

Natural regeneration encompasses a set of sequential steps, namely seed production, seed dispersal, germination, and seedling establishment. Maritime pine trees are self-fertile. Wind pollination helps to spread their pollen grains from the male sexual organs (cone) to the female ones. Flowering, fruiting, and seed production are dependent on the tree development stage, stand density, and climate. Maritime pine individuals start to fruit at about 10–15 years old, with a periodicity of masting cycles of 3–5 years [2]. Trees with larger dimensions produce higher cone yields. Trees with larger dimensions tend to be in the upper layer of the canopy, are more vigorous and the light crow area is larger, all of which contribute to the increase of cone production [43, 94]. The reduction of density through thinning, reducing competition, and promoting the increase of crown area, especially the outer one where flowering and fruiting occur, increases fruit yield [43, 94].

Cone full development needs 2 years to be achieved [2] and climate, especially precipitation, determines the number of mature cones per year [43, 95]. For maritime pines stands the seed production per year is enough to regenerate the stands, in spite of its interannual variability [94, 96]. Its seeds are mainly wind dispersed; thus, wind direction and intensity are key factors in its dispersal, which occurs in the summer, from June to August [2]. The mean and the maximum dispersal distances of the seed are circa 14–25 m and 54 m, respectively [97].

Germination is related to seed germination rate and predation both before and after dispersal. Maritime pine germination occurs either in spring or autumn [2] and it is dependent on nutrient availability as the seed have few reserves; water, the increase in water stress reduces the germination and survival rates; and light environment, as germination and early development of seedlings is promoted by semi-shade environments that reduce light intensity and soil temperature, and increase soil moisture [78, 94, 98]. Guignabert et al. [94] mentioned that drought in summer was the primary cause of death in seedlings, mainly due to the increase of the deficit in vapor pressure and transpiration of seedlings. Partial cutting reduced water stress, thus promoting seedling survival [94] and a crown cover of about 32% had higher germination and survival rate of seedlings when compared with a crown cover of circa 5% [98].

Guignabert et al. [94] comparing seedlings with partial cutting clearcutting observed that seed production and dispersal were not limiting factors to regeneration. Inversely, the storage and conservation of seed in the seedbank constrained germination because of the high predation after dispersal; harvest residues and litter layer did not allow seeds to reach the soil; the capacity of germination of seeds was lower on clearcutting, and the germination rate was high in the first year after seed rain (previous year to harvest) and drastically reduced in the two following years.

Seed predation is a primordial factor in maritime pine regeneration. Predation before dispersal occurs when fruits are in the maturation early stages, while predation after dispersal takes place in the ground prior to germination, mainly by birds and insects. Post dispersal seed predation happens mostly in autumn and winter and depends on seed and predators’ number, frequently having a trend towards a high spatial and temporal variability [99]. Ruano et al. [96] observed that predation reduced seed of maritime pine from 400,000–500,000 seeds/ha to 10,000 seeds/ha, and that the seed predation rate increased with the decrease of quantity of seed.

3.4 Stand structure dynamics

Stand structure dynamics is determined by the initial species composition and proportions and structure. The differences in stand structure, even if they are small, may be, and many times are, enlarged in time [25]. These differences are visible both in the estimates of the stand variables and their precision and accuracy, which reinforces the need to develop flexible models that accommodate the variability of growth patterns and interactions between individuals for the variability in stand structure [52]. Alegria [42] and Alegria and Tomé [22] developed growth models for maritime pine uneven-aged stands. In both studies, the authors referred that the existing models (developed for even-aged stands) are not able to accommodate the differences in structure, and the new models outperformed the existing ones. Gómez-García [100] developed height-diameter functions for P. pinastermentioning that mixed models were able to accommodate the variability in tree allometry as well as the limitations on the available data. Riofrío et al. [46] developed height-diameter functions for P. pinasterand P. sylvestris, pure and mixed even-aged stands. The model was able to accommodate the different patterns between trees and species, and account for the different species traits, allometry, and interactions. Also, the authors reported that these models had better performance than those existing for pure even-aged stands.

In maritime pine even-aged stands, rotation can be defined for a target age or diameter. Rotation age varies between 35 and 45 years [2], though longer rotations have been used, for example in coastal dunes of Mata Nacional de Leiria (see Figure 2), of 70 years for timber and 100–140 years for protection [101]. The target diameter is defined according to the use of wood with 7–14 cm of diameter at breast height for panels and pulp; 14–20 cm for timber and > 35 cm for veneer wood and large dimension timber [2]. Figure 5 presents P. pinasterwood logs, after logging.

Figure 5.

Pinus pinasterwood logs.

Stand structure, tree growth, and silvicultural practices have a key role in wood quantity and quality. High stand density, especially in the early stages of development, promotes height growth in maritime pine stands, which shortens the period of juvenile growth of wood enabling trees to develop mature wood at early stand development stages [87, 102, 103], as well as reducing stem taper and promoting stem straightness that reduces the amount of reaction (compression) wood, thus reducing the undesirable characteristics for most wood uses [104]. However, as it is a fast-growing specie and shade-intolerant, release through non-commercial or commercial thinning should be prescribed [2]. The reasons for the early release of competition are twofold. The release will increase diameter growth and tree mechanical stability. The mechanical tree stability is frequently accessed with the h/d ratio (ratio between total tree height and diameter at breast height, with both variables in the same units). Mechanical stability is attained for h/d lower than 85 ([105] and references therein). As already referred due to its shade intolerance maritime pine individuals, when in dense stands lose their lower branches [2] whether due to shading or branch abrasion, originating the crown regression and reduction of growth [25]. Two structure indices can be used as proxies of potential photosynthetic ability, vigor, and growth: crown ratio (cr: percent of crown length in relation to total height), which is also used for mechanical stability assessment; and linear crown ratio (lcr: percent of the crown in relation to stem diameter). For good vigor and growth cr ≥ 30% and lcr > 50%, while for a good mechanical stability cr ≥ 50% ([105] and references therein).

Spatial tree arrangements have also a determinant role in wood quality. In irregular spacing, especially in dense stands, trees can develop eccentric and tortuous or leaned stems, which reduce mechanical stability, in particular to wind and snow, and depreciate wood quality due to compression wood [85, 104].

Stem taper determines the quantity and quality of wood. Theoretically, trees in free growth tend to have stems more conical while those with narrower spacing tend to be more cylindrical. Also, maximum radial growth is higher near the crown base where carbohydrates are more available due to mechanical stress [85]. Thus, density should be suited to the development of cylindrical stems. Wood quality is also determined by the presence of branches and juvenile wood. Early pruning indicated for maritime pine [2] enables to increase in the length of the cylindrical stem, reduces the knotty stem core, and promotes the formation of mature wood [2, 85, 87, 102, 103]. Pruning in the early stand development stages, with few high-intensity interventions enables an easier and faster recovery of the tree growth. The goal is to attain a knotty stem core of 1/3 or less of the diameter at breast height at the end of the production cycle [2].

Annual radial growth and its variability also determine the quantity and quality of timber. The goals are attaining a radial growth as large and as constant as possible, that maintains good wood technological properties. Thinning, redistributing the growing space by the better-suited trees that are foreseen to reach the end of the production cycle, enables to achieve the two aforementioned goals. Thinning from below and selective (Schädelin) thinning can be used [2]. In the former the trees removed are predominantly the dominated ones, thus maintaining the upper canopy. The latter is characterized by the selection of the future trees which are released from completion in thinning. This results in a trend towards higher growth rates in the latter [77]. Regarding thinning intensity, the higher the larger the radial growth, but also increases annual radial growth variability [77]. Thus, the option is between thinning of lower intensity and higher frequency or of higher intensity and lower frequency.

When the objective of forest stands is the production of quality wood, it is advisable that they be installed with reduced spacing. With this practice, the height growth is promoted (in detriment to diameter growth), in order to release the influence of the crown at the lower levels of the stem as soon as possible, reducing the amount of juvenile wood in the stem and promoting the early development of the mature wood (of better quality) in the lower levels of the stem [87, 102, 103], which are the most valuable due to their larger dimension in diameter. At the same time, the stem taper is reduced and its straightness is increased, thus also reducing the amount of compression wood, which presents undesirable characteristics for most wood uses [104].

A profile of a radial section of maritime pine wood is shown in Figure 6.

Figure 6.

Radial section ofPinus pinasterwood.

3.5 Growth rate vs.wood quality

Given the great importance of the effect of the growth rate on wood quality, this topic has been studied for a long time, without, however, maintaining a great controversy, even allowing any bibliographic review to be forwarded to support any of the preconceived views. Initially, it was generally accepted that, in softwoods, rapid growth was associated with low densities, but this idea was based on a simple analysis of the cross-section of the stem by comparing the wide rings with low density, located in the center of the tree (juvenile wood), and the narrow rings with high density, located close to the bark (mature wood). However, the effects of ring width and age were confounded, so that most of the problems thought to be related to wide rings were, after all, due to the age of wood formation, that is, due to juvenile wood versus mature wood [106]. Regardless of the ring width, the juvenile wood is characterized by presenting a low density, which contrasts with the high density of the mature wood. Although the juvenile wood of softwood normally presents wide rings, the narrow rings of the juvenile wood also have low densities, as well as the wide rings of the mature wood show high densities [102]. Thus, the true effect of growth rate on density (as well as on other properties) can only be well evaluated in rings of the same age [106]. Currently, it is consensual that it is the occurrence of juvenile wood (age of the growth rings) and not the growth rate in diameter (ring width) that produces the worst quality wood.

Numerous studies carried out with resinous species in Portugal and Spain have repeatedly demonstrated the absence of correlation between ring width and wood quality characteristics [107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117] which are sufficiently clear to stop fearing, for this species growing in these regions, any hypothetical antagonism between the vigor and the wood quality. In this regard, also worth mentioning the work carried out by Fernandez-Golfin and Diez [107] on the influence of the ring width on the wood density and other physical-mechanical properties of wood in different species (among which P. pinaster). In addition to corroborating the reduced predictive capacity of ring width for wood density, the authors draw attention to the fact that the first research teams on wood technology were North European, so the most widespread wood quality standards came from studies carried out in these latitudes with slow and homogeneous species, as a result of reduced interannual variability. However, according to these authors, the woody material produced in Southern Europe is characterized by an enormous variability in the ring width, essentially induced by the great variability of precipitation, which, in this region, is the main limiting factor for growth. Thus, “The wood of these species and origins must be classified according to standards that take into account their growth characteristics and not using standards made to classify other species and/or provenances. In this sense, the use of the ring width as a limiting factor of wood quality (imposed by many European classification standards) only results in an unfounded technical barrier to wood from fast-growing species and/or from European southern climates, and open the doors to slow-growing species from more northern regions” [107].


4. Growth models, simulators, and decision support systems (DSS) for maritime pine (P. pinaster)

The importance of the maritime pine, both in area and yield, has led to the development of a large number of growth and production models to support the management of this forest resource. The first growth models for maritime pine - in the form of Yield Tables - were developed in Portugal, for the Leiria National Forest, by Santos Hall [118], and in Spain, in the 1940s, by Echeverría and De Pedro [119] in the Atlantic area. In France, the production tables developed by Décourt and Lemoine [120] for the pinewoods of the SW region (Landes) were the first models published for the specie. Significant development of models followed, attesting to the interest shown in this field of modeling applied to the species by researchers and technical experts. The evolution of the models since the production tables reflected the state of the art in the respective research area at the time, and documents the contemporary approach to forest growth prediction. In general, the models that have been proposed are empirical, at the stand or tree level, aiming at the application to pure and regular P. pinasterstands. The Dryads model [121], for uneven-aged, pure or mixed stands of P. pinasterand hardwoods (Castaneaspp. and Quercusspp.), the PBIRROL model [122], for uneven-aged stands, should be highlighted here, due to their distinctive application, as well as the tests performed with the hybrid models, physiologically based of FOREST-BGC [123] and 3-PG [124], calibrated for the species by Lopes [125] and Alexandre [126]. Additional information about growth models can be found in Fonseca [127] and Bravo et al. [128]. Fonseca [127] presents a list of 30 models developed for the species in Portugal, and Bravo et al. [128] summarize the main models developed for the Atlantic and the Mediterranean maritime pine forests in Spain. The FORMODELS database (available at containsa comprehensive list of 20 models developed for the species for different ranges of applicability in Portugal, Spain, and France, most of them referring to growth models and a few of other categories (biomass, mushrooms and fire behavior).

In this section we identify the simulators available for the species, presenting the references as to authorship or their reference documents and availability to users. Some of the models are hosted on platforms, namely, the CAPSIS (Computer-Aided Projection of Strategies in Silviculture) platform, see [129], the platform “Qforestry” (Quantitative forestry), the web-based application to simulate alternatives for sustainable forest management SIMANFOR [130], and the “sIMfLOR” platform, where the StandSim.dd simulator is located (Table 1) [131].

SimulatorReferenceMain charac-teristics and access (code)Platform
PBRAVO[132, 133]Stand level with disaggregation by diameter classes (Weibull function)CD Rom (Pbravo vs. 2.0).
ModisPinaster[32, 134, 135]Stand level with disaggregation by diameter classes (Johnson SB)CAPSIS (
PBIRROL[22, 122]Tree level, distance-dependentStandSim.dd simulator (
Additional references in sIMfLOR
Tree level, distance-dependent.StandSim.dd simulator (
FlorNExT[137]Online application developed for the simulation of the growth and production at stand level. Combines several models developed for the species. Additional references in FlorNExT. Application of ForesMTIS. Web productForesMTIS. (
GesMOGesMo 2005 1.0 na§
GesMO 2.0
Growth simulator and product classification for several species, including maritime pineCD-Rom.
SIMFORna§Simulator for maritime pine located on Qforestry Platform for results transfer related to quantitative methods for forest managementQforestry (
SIMANFOR[130, 139]Support system for the simulation of sustainable forest management alternatives which includes modules for maritime pineSIMANFOR (
PP3[140]Tree level, distance-independentCAPSIS (
Lemoine[141]A stand growth modelCAPSIS (
Afocelppna§Tree level, distance-independentCAPSIS (
Pinus pinasterna§Tree level, distance-independent. Adaptation of PP3, for the integration of spatialized processesCAPSIS (
SilmarSna§Growth modelCAPSIS (

Table 1.

Simulators and web products for Pinus pinaster.

Specific reference not available; see the Web reference for details.

Although each model has its own specificities, the models produced to describe the dynamics of growth and several of them make it possible to anticipate the results of silvicultural options or management scenarios, according to predefined objectives or those to be achieved.

To support forest management, optimization models are used, usually anchored in Decision Support Systems (DSS), with the objective of obtaining optimal solutions for a given objective - usually wood production - subject to a set of constraints. Examples of optimization models for P. pinasterare found in Pasolodos-Tato [142], Fonseca [143], Rodil [144], and Petucco et al. [145]. In terms of supporting decision, Costa et al. [146] and Garcia-Gonzalo et al. [147] present case studies of DSS to generate management plans aimed at the production of wood for common lands and national forests, respectively, in Portugal. Other references are Falcão and Borges [148] and Garcia-Gonzalo et al. [148, 149].


5. Wood traits

5.1 Anatomy

Concerning the anatomical characterization, P. pinasterwood shows particularly longer tracheids than most resinous woods, which gives it great axial cohesion during its mechanical performance in use. For example, while P. pinasterwood presents an average tracheids length of 4.35 ± 0.50 mm [150], P. nigraand Cupressus lusitanica, also growing in Portugal, present average values of 3.74 ± 0.45 mm and 1.60 ± 0.16 mm, respectively [151, 152], P. sylvestris1.73 ± 0.12 mm in Finland [153] and Picea abieswith average values of ~2.75 mm [154], much lower than P. pinaster. Another important anatomical wood feature is the dimension of the lumen diameter of the earlywood tracheids, which in maritime pine is approximately 33 μ, a significantly higher value than that of Picea abies(27μ) and P. sylvestriswood (29 μ) [155]. This characteristic is reflected in the good performance of P. Pinasterwood in its drying behavior and preservation treatments.

5.2 Physical properties

The usual air-dry wood density values of approximately 0.566 g/cm3 in 30-year-old trees are worth mentioning [156], but which can reach average values of 0.657 g/cm3 at 70 years old [150]. These values are identical to those of P. nigra(0.588 ± 0.096 g/cm3) [116, 117] and P. sylvestris(0.588 ± 0.101 g/cm3) [114, 115] with identical ages and growing in Portugal, but higher than P. sylvestriswood from Sweden, France and the Czech Republic (0.391–552 g/cm3) [157, 158, 159, 160], Picea abies(0.410–516 g/cm3) [157], and Abies balsamea(0.351 g/cm3) [161].

Another important aspect is that the difference between the wood density of the earlywood and the latewood is not very high, which results in a considerable homogeneity of density within rings [108, 151], with very advantageous repercussions in terms of its workability, namely in its transformation into sheet to plywood and veneer and in the easiness of receiving connection elements (e.g., nails, screws).

The fact that P. pinasterwood has a relatively high density, has consequently a great dimensional instability caused by the gain or lose water during the wood drying (sorption/desorption processes), which results in tangential shrinkage values (T) between 9.1% at 10.1%; Radial (R) between 4.7% and 6.0%; Axial (L) between 0.0% and 1.0% and volumetric (V) between 14.5% and 16.7% [156, 162]. This aspect may be particularly critical in situations where wood is used outdoors, heavily exposed to adverse weather conditions. Comparatively, in softwoods it is common to find lower shrinkages, whose mean T values are usually between 5.6% and 8.3%; R between 3.1% and 5.3%, and V between 9.4% and 13.4% [163, 164]. In this way, it is imperative not only special care during the drying process but also that it only be applied after its moisture content is stabilized in the air. Additionally, it is also recommended to periodically apply insulating products (e.g., paints, varnishes) to reduce these shrinkages [87, 103].

5.3 Chemical properties

In relation to chemical properties, the wide range of studies carried out on this theme has been unanimous in demonstrating a reduced variability, not only between different conifers species but even between trees of the same species. This lack of variability is notable not only in terms of variations in the macromolecule contents (cellulose, hemicelluloses, and lignin), but also in terms of the elemental chemistry. The only difference that is sometimes identified is related to the extractive content of some species, whose range values are usually from 1.5 to 5% [165, 166, 167]. In the case of maritime pine in Portugal, it usually presents relatively higher contents, between 4.2% and 9.6% [113, 168, 169, 170].

Even so, these values for P. pinasterare lower than those reported for the P. sylvestris(10.7–15.4%) and P. nigrawood (6.6–12.9%) growing in Portugal [115, 117]. In terms of the use of P. pinasterwood, these high extractive values give it some natural resistance to biodegradation (but do not prevent the need to apply preservative products in situations of outdoor use) but may cause some problems in surface finish operations.

Regarding the elementary chemistry contents, several studies have shown that the woody biomass of the P. pinaster, not only contain high heating value (HHV), between 20.15 and 21.60 Mj/kg, but also low undesirable elements contents, such as N, S, K, Na, Ca, Mn, Ni, Cr, Cu, F, Cl, and ashes [171, 172, 173, 174, 175, 176, 177]. Thus, the P. pinasterwood is one of the most suitable types of biomass for energy purposes, namely through combustion processes, given the high HHV and the low risk of sintering and corrosive effect of chloride salts and HCl on metal parts in furnace and boiler, that occurs when the halogen elements (F and Cl) are high [178, 179, 180, 181, 182, 183, 184, 185, 186]. Likewise, the low values of N and S also indicate a reduced risk of formation and release to the atmosphere of NOx and SOx [180, 187, 188, 189, 190].

5.4 Genetics and breeding

Although the studies on genetic improvement of P. pinasterin Portugal had started in the 60s of the last century, they were focused on the characteristics of growth, form, and resistance to pests and diseases, and only in the last 25 years did the first study on the genetic control and improvement of the wood qualitative characteristics. At the moment, there is enough knowledge to recognize the existence of high genetic variability (essential to ensure good genetic gains through an improvement program) for some wood characteristics. For example, there was a high genetic control of the characteristics associated with wood density (heritability between 0.60 and 0.98), much higher than that verified for the growth characteristics in diameter (between 0.15 and 0.17), height (0.34), as well as for other wood features, such as lignin content (0.34), Radial Modulus of Rupture (0.34) and Radial Modulus of Elasticity (0.30) [108, 110, 111, 113]. Furthermore, when analyzed separately, the earlywood (formed in spring) exhibits much greater genetic dependence and is controlled over several years by the same set of genes, being the one that better results will provide in the future selection and improvement programs. In the opposite situation, the latewood, showing the lowest and most unstable heritability values, reveals that this type of wood is more strongly affected by environmental conditions than the earlywood [108, 110, 111, 113].

With regard to ring width, no adverse genetic correlations were detected between this and the wood density components. The fact that ring width is genetically and consistently positively correlated with the ring density, earlywood density, latewood percentage, and negatively with the heterogeneity index, allows us to contest, once again, the erroneous idea, but unfortunately still deeply rooted in the thinking of many researchers and wood users, that trees with higher radial growth (higher ring width) produce lower wood quality, namely lower density and latewood percentage in xylem [109, 110, 113].

These results should be sufficiently enlightening for us not to fear, for this species, any possible antagonism between the vigor and wood quality. On the contrary, it is expected that selection by the ring width will have a correlated effect in a slight increase in ring density, earlywood density, and latewood percentage (which should make it possible to reconcile good radial growths with high density), but not being accompanied by any significant changes in the latewood density, which will indirectly allow to increase the homogeneity of the growth rings. This fact is one of the most valued attributes by some of the wood processing industries. For example, the greater the homogeneity within the rings, the easier and more profitable will be the production of veneers, the greater its mechanical strength, the easier it receives the connecting elements (nails and screws), and the lower the risk of wood cracking [109, 113].

One of the places where the genetic improvement of P. pinasteris most advanced is in Australia, which began in 1957 and is currently in its fourth phase. The first phase was the establishment of a preliminary test of provenances that took place between 1964 and 1984 which revealed that in the growing conditions of West Australia, the provenances from Leiria (Portugal) were the most vigorous, confirming, once again, the superiority of the Atlantic provenances for growth [191]. The development in height and diameter at 10 and 20 years old was much higher in the 2 origins from Leiria, compared to those from Corsica, Landes, and Italy and, in terms of volume, the origins from Leiria presented a value greater than twice that of any of the other provenances. Furthermore, the provenances from Leiria were also the most resistant to drought (0.8% mortality, compared to 9.7% for the Landes and 10.1% for Corsica), but little to frost and with frequent stem bifurcations. The provenances from Corsica were superior in the stem straightness, while those from Leiria did not differ significantly from those from Spain and did not show a good performance in this parameter.

In the second phase of the improvement program, an attempt was made to combine, in the same individuals, the vigor characteristic of the provenances from Leiria with the stem straightness of those from Corsica, having crossed these two provenances. However, the hybrids obtained by this cross kept these 2 characteristics apart in the same individuals: either a high vigor, or a good stem configuration, but never both, simultaneously [191].

Faced with this setback, the next phase aimed to improve the stem shape while maintaining its high vigor, using material from 86 selected trees in the Leiria pine forest, which provided considerable genetic gains. According to Butcher and Hopkins [192] and Hopkins and Butcher [193] at this stage of the program, an increase in total volume production of +36% was obtained, which represents, by itself, an average increase of about 3.5 m3 ha−1 year−1 and which, complemented by a significant improvement in the stem quality by increasing their straightness by around 40% and by reducing the size of the branches by 25%, allows for an even greater increase in the total volume of usable wood.

For the fourth phase of the program, which is still in progress, the main objectives were to improve the characteristics of the branches (reduction of the insertion angle and size) and to increase the wood density, having been selected the best individuals from the best families obtained in the previous phase of the program that showed good configuration of the stem and crown, and whose average density of juvenile wood was equal to or greater than 0.430 g/cm3 [193, 194, 195].

Thus, the current knowledge about the properties and characteristics of P. pinasterwood allowed to identify it as a type of wood with potential for a wide range of uses, which go beyond those with less added value (packaging, pallets, and briquettes). In fact, this wood has suitable characteristics for more noble applications, such as structural applications, floors, carpentry and furniture, veneer, particleboard and plywood, poles, and sleepers.


6. Conclusions

Maritime pine is a plastic species widely distributed. Its traits and stand structures as well as the quantity and quality of its wood allow a wide range of uses. The stands are managed for wood, non-woody products, and services, thus recognizing its importance both economical and as a provider service demanded by society, thus contributing to its well-being.

The large representation of the species, particularly in southern Europe, has allowed advanced research on silvicultural systems and cultural practices, and their effects on wood properties, providing clarification on less well-perceived aspects of wood quality, particularly when considering the development of the species in the Mediterranean region. In parallel with silvicultural studies, several growth models and simulators have been developed and proposed to support management.

The challenges facing the species in the future are known, including severe weather conditions, especially drought, rural fires, storms, pests, and diseases. In addition, the systems are under pressure due to the high demand for woody material. From the extensive review carried out on maritime pine, it is noticed these challenges are part of research conducted or underway and of joint initiatives through international research projects (e.g., ForManRisk, to ensure the definition and update of management guidelines for the sustainability of maritime pine systems in the long term.



Thanks are due to the Pinus Competence Center (CCPB), Pinus Center (Centro Pinus), and International Union of Forest Research Organizations (IUFRO), namely Division 1 (Silviculture), unit 1.01.10 Ecology and Silviculture of Pine, for promoting fruitful discussions on the silviculture and management of pine forests that have contributed to the organization of this chapter.


Conflict of interest

The authors declare no conflict of interest.



For the author integrated with the research center Forest Research Centre (CEF), the research was financed by National Funds through the Portuguese funding agency, FCT (the Portuguese Foundation for Science and Technology), within project UIDB/00239/2020. For the author integrated with the MED research center, this work is funded by National Funds through FCT—Foundation for Science and Technology under the Project UIDB/05183/2020. For the author integrated with the CITAB research center, it was supported by National Funds by FCT—Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020.


  1. 1. Ferreira AG, Gonçalves AC, Pinheiro ACA, Gomes CP, Ilhéu M, Neves N, et al. Plano específico de ordenamento florestal para o Alentejo [Specific Forest Planning Plan for Alentejo]. Évora: Universidade de Évora; 2001
  2. 2. Oliveira AC, Pereira JS, Correia AV. A Silvicultura do Pinheiro Bravo. Porto: Centro Pinus; 2000
  3. 3. Caudullo G, Welk E, San-Miguel-Ayanz J. Chorological maps for the main European woody species. Data in Brief. 2017;12:662-666. DOI: 10.1016/j.dib.2017.05.007
  4. 4. CABI.Pinus pinaster. In: Invasive Species Compendium. CAB International: Wallingford, UK; 2021. Available[Accessed: March 08, 2021]
  5. 5. Correia AV, Oliveira AC. Principais espécies Florestais Com Interesse Para Portugal: Zonas de influência atlântica [Main Forest Species with Interest for Portugal: Zones of Mediterranean Influence]. Lisboa: Direcção-Geral das Florestas; 2003
  6. 6. Maugé J. Le pin maritime. Premier résineux de France. Paris: IDF; 1987. p. 192
  7. 7. Arduini I, Kettner C, Godbold DL, Onnis A, Stefani A. pH influence on root growth and nutrient uptake ofPinus pinasterseedlings. Chemosphere. 1998;36(4-5):733-738
  8. 8. Perrin E, Parlade X, Pera J. Receptiveness of forest soils to ectomycorrhizal association: 1. Concept and method as applied to the symbiosis betweenLaccaria bicolor(Maire) Orton andPinus pinasterait orPseudotsuga menziesii(Mirb.) Franco. Mycorrhiza. 1996;6:469-476
  9. 9. Défossez P, Veylon G, Yang M, Bonnefond JM, Garrigou D, Trichet P, et al. Impact of soil water content on the overturning resistance of youngPinus Pinasterin sandy soil. Forest Ecology and Management. 2021;480:118614. DOI: 10.1016/j.foreco.2020.118614
  10. 10. Eimil-Fraga C, Sánchez-Rodríguez F, Álvarez-Rodríguez E, Rodríguez-Soalleiro R. Relationships between needle traits, needle age and site and stand parameters inPinus pinaster. Trees. 2015;29:1103-1113. DOI: 10.1007/s00468-015-1190-7
  11. 11. Eimil-Fraga C, Rodríguez-Soalleiro R, Sánchez-Rodríguez F, Pérez-Cruzado C, Álvarez-Rodríguez E. Significance of bedrock as a site factor determining nutritional status and growth of maritime pine. Forest Ecology and Management. 2014;331:19-24. DOI: 10.1016/j.foreco.2014.07.024
  12. 12. Humphries CJ, Press JR, Sutton DA. The Hamlyn Guide to Trees of Britain and Europe. London: Hamlyn Publishing Group Ldt; 1989
  13. 13. Picon C, Guehl JM, Ferhi A. Leaf gas exchange and carbon isotope composition responses to drought in a drought-avoiding (Pinus pinaster) and a drought-tolerant (Quercus petraea) species under present and elevated atmospheric CO2 concentrations. Plant, Cell and Environment. 1996;19:182-190
  14. 14. Granier A, Loustau D. Measuring and modelling the transpiration of a maritime pine canopy from sap-flow data. Agricultural and Forest Meteorology. 1994;71(1-2):61-80
  15. 15. IGN. Le mémento - Inventaire Forestier. Institut Nacional de l'Information Géographic et Forestiére. Édition 2020 [Internet]. 2020. 36 p. Available from:[Accessed: March 08, 2021]
  16. 16. MAPA. Anuario de Estadística Forestal. Ministerio deAgricultura, Pesca y Alimentación [Internet]. 2019. Available[Accessed: March 08, 2021]
  17. 17. Barrio-Anta M, Castedo-Dorado MF, Cámara-Obregón A, López-Sánchez CA. Predicting current and future suitable habitat and productivity for Atlantic populations of maritime pine (Pinus pinasterAiton) in Spain. Annals of Forest Science. 2020;77:41. DOI: 10.1007/s13595-020-00941-5
  18. 18. ICNF. 6.° Inventário Florestal Nacional 2015—Relatório Final [6th National Forest Inventory 2015—Final Report]. Instituto da Conservação da Natureza e das Florestal [Internet]. 2019. Available from:[Accessed: March 08, 2021]
  19. 19. Centro Pinus. Valorizar o Pinheiro-Bravo: A Perspetiva de Mercado [Valorisation of the Maritime Pine: A Market Perspetive]. 2020. Available from:[Accessed: June 14, 2021]
  20. 20. Centro Pinus. 2020. A Fileira do Pinho em 2019. Indicadores da Fileira do Pinho [the pine sector in 2019. Indicators of the pine sector]. Available from:[Accessed: June 14, 2021]
  21. 21. da Silva VS, Salami G, da Silva MIO, Silva EA, Monteiro Junior JJ, Alba E. Methodological evaluation of vegetation indexes in land use and land cover (LULC) classification. Geology, Ecology, and Landscapes. 2020;4(2):159-169. DOI: 10.1080/24749508.2019.1608409
  22. 22. Alegria C, Tomé M. A tree distance-dependent growth and yield model for naturally regenerated pure uneven-aged maritime pine stands in central inland of Portugal. Annals of Forest Science. 2013;70(3):261-276. DOI: 10.1007/s13595-012-0262-8
  23. 23. Gonçalves A, Oliveira Â. Regeneration in multi-species in Serra da Lousã. Forest Systems. 2011;20:444. DOI: 10.5424/fs/20112003-11055
  24. 24. Gonçalves A, Oliveira Â. Evolution in Multi-Species High Forest Stands in Serra da Lousã: Diversity Analysis 12. Silva Lusitana. 2010;special issue:79-90
  25. 25. Oliver CD, Larson BC. Forest Stand Dynamics, Update Edition. New York: John Wiley & Sons, Inc; 1996
  26. 26. Fernández-Guisuraga JM, Suárez-Seoane S, Calvo L. ModelingPinus pinasterforest structure after a large wildfire using remote sensing data at high spatial resolution. Forest Ecology and Management. 2019;446:257-271. DOI: 10.1016/j.foreco.2019.05.028
  27. 27. Gonçalves A, Sousa A. The fire in the Mediterranean region: A case study of forest fires in Portugal. In: Fuerst-Bjelis B, editor. Mediterranean Identities—Environment, Society, Culture. Rijeka: InTech; 2017. DOI: 10.5772/intechopen.69410
  28. 28. Alegria C, Roque N, Albuquerque T, Fernandez P, Ribeiro MM. Modelling maritime pine (Pinus pinasterAiton) spatial distribution and productivity in Portugal: Tools for Forest management. Forests. 2021;12:368. DOI: 10.3390/f12030368
  29. 29. Alegria C, Roque N, Albuquerque T, Gerassis S, Fernandez P, Ribeiro MM. Species ecological envelopes under climate change scenarios: A case study for the Main two wood-production Forest species in Portugal. Forests. 2020;11:880. DOI: 10.3390/f11080880
  30. 30. Colin F, Riou-Nivert P. Relations entre résistance au vent, descripteurs du peuplement et sylviculture. Innovations Agronomiques, INRAE. 2009;6:39-49
  31. 31. Hart E, Sim K, Kamimura K, Meredieu C, Guyon D, Gardiner B. Use of machine learning techniques to model wind damage to forests. Agricultural and Forest Meteorology. 2019;265:16-29
  32. 32. Fonseca TF. Modelling the Growth, Mortality and Diametric Distribution of Maritime Pine Forest in the Tâmega Valley (Modelação Do Crescimento, Mortalidade e Distribuição Diamétrica, Do Pinhal Bravo no Vale Do Tâmega) [Thesis]. Vila Real, Portugal: Universidade de Trás-os-Montes e Alto Douro; 2004
  33. 33. Ribeiro SL. Efeito das depressões de elevado impacto na floresta do Norte de Portugal: ensaio de metodologia para registo de danos e apresentação de propostas para minimização dos impactos [Master thesis]. Universidade de Trás-os-Montes e Alto Douro; 2019
  34. 34. Gonçalves A, Ribeiro S, Fonseca TF, Nieto R, Liberato M. Depressões extratropicais extremas e impactes na floresta portuguesa. In 27th APDR Congress Sustainable Management of the Sea for Sustainable Regional Development Proceedings; 10-11 September 2020; Angra do Heroísmo, Terceira, Azores: Angra do Heroísmo, Terceira; 2020. pp. 478-486. ISBN: 978-989-8780-08-9C
  35. 35. Cucchi V, Meredieu C, Stokes A, et al. Root anchorage of inner and edge trees in stands of maritime pine (Pinus pinasterait.) growing in different podzolic soil conditions. Trees. 2004;18:460-466. DOI: 10.1007/s00468-004-0330-2
  36. 36. Arnaldo PS. Contribuição para o conhecimento da processionária do pinheiro,Thaumetopoea pityocampa(Den. & Schiff.). Morfologia, bioecologia e proteçcção contra a praga [thesis]. Vila Real, Portugal: Universidade de Trás-os-Montes e Alto Douro; 2003
  37. 37. Sousa E, Naves L, Bonifácio ML, Inácio S, Carneiro S. Boas práticas fitossanitárias em pinhal. Porto: Centro Pinus; 2019
  38. 38. Prieto-Recio C. Biotic, Abiotic and Management Factors Involved in "Pinus pinaster" Decline in the Iberian Peninsula [Thesis]. Valladolid: Universidad de Valladolid; 2016
  39. 39. Condés S, Aguirre A, del Río M. Crown plasticity of five pine species in response to competition along an aridity gradient. Forest Ecology and Management. 2020;473:118302. DOI: 10.1016/j.foreco.2020.118302
  40. 40. Rodriguez-Vallejo C, Navarro-Cerrillo RM, Manzanedo RD, Palacios Rodriguez G, Gazol A, Camarero J. High resilience, but low viability, of pine plantations in the face of a shift towards a drier climate. Forest Ecology and Management. 2021;479:118537. DOI: 10.1016/j.foreco.2020.118537
  41. 41. Aguiar FC, Rodrigues C, Pina JP, Soares P. Regeneration of riparian and maritime pine forests after a large wildfire on the largest public Forest of Portugal. Forests. 2021;12:477. DOI: 10.3390/f12040477
  42. 42. Alegria C. Modelling merchantable volumes for uneven aged maritime pine (Pinus pinasterAiton) stands established by natural regeneration in the Central Portugal. Annals of Forest Research. 2011;54(2):197-214. DOI: 10.15287/afr.2011.90
  43. 43. Bravo F, Maguire DA, González-Martínez SC. Factors affecting cone production inPinus pinasterait.: Lack of growth-reproduction trade-offs but significant effects of climate and tree and stand characteristics. Forest Systems. 2017;26:e07S. DOI: 10.5424/fs/2017262-11200
  44. 44. Enes T, Lousada J, Aranha J, Cerveira A, Alegria C, Fonseca T. Size–density trajectory in regenerated maritime pine stands after fire. Forests. 2019;10:1057. DOI: 10.3390/f10121057
  45. 45. Hevia A, Álvarez-González JG, Majada J. Comparison of pruning effects on tree growth, productivity and dominance of two major timber conifer species. Forest Ecology and Management. 2016;374:82-92. DOI: 10.1016/j.foreco.2016.05.001
  46. 46. Riofrío J, del Río M, Maguire D, Bravo F. Species mixing effects on height–diameter and basal area increment models for scots pine and maritime pine. Forests. 2019;10:249. DOI: 10.3390/f10030249
  47. 47. Arellano-Pérez S, Castedo-Dorado F, Álvarez-González JG, Alonso-Rego C, Vega JA, Ruiz-González AD. Mid-term effects of a thin-only treatment on fuel complex, potential fire behaviour and severity and post-fire soil erosion protection in fast-growing pine plantations. Forest Ecology and Management. 2020;460(117895):2020. DOI: 10.1016/j.foreco.2020.117895
  48. 48. Augusto L, Achat DL, Bakker MR, Bernier F, Bert D, Danjon F, et al. Biomass and nutrients in tree root systems-sustainable harvesting of an intensively managedPinus pinaster(ait.) planted forest. GCB Bioenergy. 2015;7:231-243. DOI: 10.1111/gcbb.12127
  49. 49. Ferretti M, Bacaro G, Brunialti G, Calderisi M, Croisé L, Frati L, et al. Tree canopy defoliation can reveal growth decline in mid-latitude temperate forests. Ecological Indicators. 2021;127:107749. DOI: 10.1016/j.ecolind.2021.107749
  50. 50. López-Marcos D, Turrión M-B, Bravo F, Martínez-Ruiz C. Can mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? Annals of Forest Science. 2020;77:15. DOI: 10.1007/s13595-020-0919-7
  51. 51. Lόpez-Marcos D, Turriόn M-B, Bravo F, Martínez-Ruiz C. Characterization of mixed and monospecific stands of scots pine and maritime pine: Soil profile, physiography, climate and vegetation cover data. Annals of Forest Science. 2021;78:7. DOI: 10.1007/s13595-021-01042-7
  52. 52. Gonçalves AC. Influence of stand structure on forest biomass sustainability. In: Jhariya MK, Meena RS, Banerjee A, Meena SN, editors. Natural Resources Conservation and Advances for Sustainability. United States: Elsevier; 2022. pp. 327-352. DOI: 10.1016/B978-0-12-822976-7.00007-7
  53. 53. Lundqvist L. Tamm review: Selection system reduces long-term volume growth in Fennoscandic uneven-aged Norway spruce forests. Forest Ecology and Management. 2017;391:362-375. DOI: 10.1016/j.foreco.2017.02.011
  54. 54. Ph SJ. Sylviculture 2. La Gestion des Forêts Irrégulières et Mélangées. Lausanne: Presses Polytechniques et Universitaires Romandes; 1997
  55. 55. Orois SS, Chang SJ, von Gadow K. Optimal residual growing stock and cutting cycle in mixed uneven-aged maritime pine stands in Northwestern Spain. Forest Policy and Economics. 2004;6:145-152. DOI: 10.1016/S1389-9341(02)00103-X
  56. 56. Orois SS, Soalleiro RR. Modelling the growth and management of mixed uneven-aged maritime pine-broadleaved species forests in Galicia, North-western Spain. Scandinavian Journal of Forest Research. 2002;17:538-547. DOI: 10.1080/02827580260417198
  57. 57. Rojo JMT, Orois SS. A decision support system for optimizing the conversion of rotation forest stands to continuous cover forest stands. Forest Ecology and Management. 2005;207:109-120. DOI: 10.1016/j.foreco.2004.10.021
  58. 58. Fonseca T, Duarte J. A silvicultural stand density model to control understory in maritime pine stands. iForest—Biogeosciences Forestry. 2017;10:829-836. DOI: 10.3832/ifor2173-010
  59. 59. Aldea J, Bravo F, Bravo-Oviedo A, Ruiz-Peinado R, Rodríguez F, del Río M. Thinning enhances the species-specific radial increment response to drought in Mediterranean pine-oak stands. Agricultural and Forest Meteorology. 2017;237-238:371-383. DOI: 10.1016/j.agrformet.2017.02.009
  60. 60. Cattaneo N, Schneider R, Bravo F, Bravo-Oviedo A. Inter-specific competition of tree congeners induces changes in crown architecture in Mediterranean pine mixtures. Forest Ecology and Management. 2020;476:118471. DOI: 10.1016/j.foreco.2020.118471
  61. 61. Aldea J, Bravo F, Vázquez-Piqué J, Ruíz-Peinado R, del Río M. Differences in stem radial variation betweenPinus pinasterait. AndQuercus pyrenaicaWilld. May release inter-specific competition. Forest Ecology and Management. 2021;481:118779. DOI: 10.1016/j.foreco.2020.118779
  62. 62. Barreiro S, Fonseca TF, Nunes L, Pereira MG. Overview of mixed forests in Portugal. In Overview of mixed forests in Europe. WL Mason, M Lof, A Bravo-Oviedo (Coord.) COST Action FP1206 EuMIXFOR Country Report. 2016. p. 13
  63. 63. López-Marcos D, Turrión M-B, Bravo F, Martínez-Ruiz C. Understory response to overstory and soil gradients in mixed versus monospecific Mediterranean pine forests. European Journal of Forest Research. 2019;138:939-955. DOI: 10.1007/s10342-019-01215-0
  64. 64. Aldea J, Bravo F, Vázquez-Piqué J, Rubio-Cuadrado A, del Río M. Species-specific weather response in the daily stem variation cycles of Mediterranean pine-oak mixed stands. Agricultural and Forest Meteorology. 2018;256-257:220-230. DOI: 10.1016/j.agrformet.2018.03.013
  65. 65. Camarero JJ, Sánchez-Salguero R, Sangüesa-Barreda G, Matías L. Tree species from contrasting hydrological niches show divergent growth and water-use efficiency. Dendrochronologia. 2018;52:87-95. DOI: 10.1016/j.dendro.2018.10.003
  66. 66. Caminero L, Génova M, Camarero JJ, Sánchez-Salguero R. Growth responses to climate and drought at the southernmost European limit of MediterraneanPinus pinasterforests. Dendrochronologia. 2018;48:20-29. DOI: 10.1016/j.dendro.2018.01.006
  67. 67. Juhlke TR, Van Geldern R, Barth JAC, Bendix J, Bräuning A, Garel E, et al. Temporal offset between precipitation and water uptake of Mediterranean pine trees varies with elevation and season. Science of the Total Environment. 2021;755:142539. DOI: 10.1016/j.scitotenv.2020.142539
  68. 68. Szymczak S, Häusser M, Garel E, Santoni S, Huneau F, Knerr I, et al. How do Mediterranean pine trees respond to drought and precipitation events along an elevation gradient? Forests. 2020;11:758. DOI: 10.3390/f11070758
  69. 69. Szymczak S, Bräuning A, Häusser M, Garel E, Huneau F, Santoni S. The relationship between climate and the intra-annual oxygen isotope patterns from pine trees: A case study along an elevation gradient on Corsica, France. Annals of Forest Science. 2019;76:14. DOI: 10.1007/s13595-019-0860-9
  70. 70. Andivia E, Zuccarini P, Grau B, de Herralde F, Villar-Salvador P, Savé R. Rooting big and deep rapidly: The ecological roots of pine species distribution in southern Europe. Trees. 2019;33:293-303. DOI: 10.1007/s00468-018-1777-x
  71. 71. Saint Cast C, Meredieu C, Défossez P, Pagès L, Danjon F. Modelling root system development for anchorage of forest trees up to the mature stage, including acclimation to soil constraints: The case ofPinus pinaster. Plant and Soil. 2019;439:405-430. DOI: 10.1007/s11104-019-04039-4
  72. 72. Correia I, Almeida MH, Aguiar A, Alia R, David TS, Pereira JS. Variations in growth, survival and carbon isotope composition (13C) amongPinus pinasterpopulations of different geographic origins. Tree Physiology. 2008;28:1545-1552. DOI: 10.1093/treephys/28.10.1545
  73. 73. Aguirre A, del Río M, Condés S. Productivity estimations for monospecific and mixed pine forests along the Iberian Peninsula aridity gradient. Forests. 2019;10:430. DOI: 10.3390/f10050430
  74. 74. Aguirre A, del Río M, Ruiz-Peinado R, Condés S. Stand-level biomass models for predicting C stock for the main Spanish pine species. Forest Ecosystems. 2021;8:29. DOI: 10.1186/s40663-021-00308-w
  75. 75. López-Marcos D, Martínez-Ruiz C, Turrión M-B, Jonard M, Titeux H, Ponette Q, et al. Soil carbon stocks and exchangeable cations in monospecific and mixed pine forests. European Journal of Forest Research. 2018;137:831-847. DOI: 10.1007/s10342-018-1143-y
  76. 76. Calçada-Duarte JC. Estudos Biométricos em Pinheiro Bravo. Configuração do Perfil do Tronco, Volumes e Percentagem de Casca [master dissertation]. Vila Real: Universidade de Trás-os-Montes e Alto Douro; 2001. p. 129
  77. 77. Gonçalves AC. Thinning: An overview. In: Gonçalves AC, editor. Silviculture. London: IntechOpen; 2021. pp. 41-58. DOI: 10.5772/intechopen.93436
  78. 78. Ruano I, Pando V, Bravo F. How do light and water influencePinus pinasterait. Germination and early seedling development? Forest Ecology and Management. 2009;258:2647-2653. DOI: 10.1016/j.foreco.2009.09.027
  79. 79. Wilson FG. Numerical expression of stocking in terms of height. Journal of Forestry. 1946;44:758-761
  80. 80. Le R-NP. facteur d’espacement: un guide pour les premières éclaircies dans les peuplements résineux. Forêt-Entreprise. 1987;20:12-19
  81. 81. Reineke LH. Perfecting a stand-density index for even aged forests. Journal of Agricultural Research. 1933;46:627-639
  82. 82. Luis JS, Fonseca TF. The allometric model in the stand density management ofPinus pinasterin Portugal. Annals of Forest Science. 2004;61:1-8
  83. 83. Mazza G, Cutini A, Manetti M. Influence of tree density on climate-growth relationships in aPinus pinasterait. Forest in the northern mountains of Sardinia (Italy). iForest—Biogeosciences and Forestry. 2015;8:456-463. DOI: 10.3832/ifor1190-007
  84. 84. Nunes L, Tomé J, Tomé M. Prediction of annual tree growth and survival for thinned and unthinned even-aged maritime pine stands in Portugal from data with different time measurement intervals. Forest Ecology and Management. 2011;262:1491-1499. DOI: 10.1016/j.foreco.2011.06.050
  85. 85. Alves A, Pereira JS, Correia AV. Silvicultura. A Gestão dos Ecossistemas Florestais. Lisboa: Fundação Calouste Gulbenkian; 2012
  86. 86. Tsoumis G. Science and Technology of Wood—Structure, Properties, Utilization. Van Nostrand Reinhold; 1991. p. 494
  87. 87. Haygreen JG, Bowyer JL. Forest Products and Wood Science - an Introduction. Iowa: The Iowa State University Press/Ames; 1982. p. 495
  88. 88. Rodríguez H, Maiti R, Kumari CA. Experimental Ecophysiology and Biochemistry of Trees and Shrubs. Apple Academic Press; 2020. p. 244
  89. 89. Maiti R, Rodriguez H, Ivanova N. Autoecology and Ecophysiology of Woody Shrubs and Trees: Concepts and Applications. Wiley; 2016. p. 368
  90. 90. Forrester DI. Growth responses to thinning, pruning and fertiliser application in eucalyptus plantations: A review of their production ecology and interactions. Forest Ecology and Management. 2013;310:336-347. DOI: 10.1016/j.foreco.2013.08.047
  91. 91. Courdier F, Sindou C, Bert D. Effet de l’élagage artificiel sur la croissance et le statut social du Pin maritime dans les landes de Gascogne. Revue Forestiere Francaise. 2002;3:239-252. DOI: 10.4267/2042/4916
  92. 92. Assmann E. The Principles of Forest Yield Study. Oxford: Pergamon Press; 1970
  93. 93. Smith DM, Larson BC, Kelty MJ, Ashton PMS. The Practice of Silviculture. Applied Forest Ecology. 9th ed. New York: John Wiley & Sons, Inc; 1997
  94. 94. Guignabert A, Augusto L, Delerue F, Maugard F, Gire C, Magnin C, et al. Combining partial cutting and direct seeding to overcome regeneration failures in dune forests. Forest Ecology and Management. 2020;476:118466. DOI: 10.1016/j.foreco.2020.118466
  95. 95. Ruano I, Manso R, Fortin M, Bravo F. Extreme climate conditions limit seed availability to successfully attain natural regeneration ofPinus pinasterin sandy areas of Central Spain. Canadian Journal of Forest Research. 2015;45:1795-1802. DOI: 10.1139/cjfr-2015-0257
  96. 96. Ruano I, del Peso C, Bravo F. Post-dispersal predation ofPinus pinasterAiton seeds: Key factors and effects on belowground seed bank. European Journal of Forest Research. 2015;134:309-318. DOI: 10.1007/s10342-014-0853-z
  97. 97. Juez L, González-Martínez SC, Nanos N, de-Lucas AI, Ordóñez C, del Peso C, et al. Can seed production and restricted dispersal limit recruitment inPinus pinasterAiton from the Spanish northern plateau? Forest Ecology and Management. 2014;313:329-339. DOI: 10.1016/j.foreco.2013.10.033
  98. 98. Rodríguez-García E, Bravo F, Spies TA. Effects of overstorey canopy, plant–plant interactions and soil properties on Mediterranean maritime pine seedling dynamics. Forest Ecology and Management. 2011;262:244-251. DOI: 10.1016/j.foreco.2011.03.029
  99. 99. Castro J, Gomez JM, Garcia D, Zamora R, Hodar JA. Seed predation and dispersal in relict scots pine forests in southern Spain. Plant Ecology. 1999;145:115-123
  100. 100. Gómez-García E, Fonseca T, Crecente-Campo F, Almeida L, Diéguez-Aranda U, Huang S, et al. Height-diameter models for maritime pine in Portugal: A comparison of basic, generalized and mixed-effects models. iForest - Biogeosciences and Forestry. 2016;9:72-78. DOI: 10.3832/ifor1520-008
  101. 101. AFN. Plano de Gestão Florestal da Mata Nacional de Leiria. Autoridade Florestal Nacional. 2010. Available from:[Accessed: June 14, 2021]
  102. 102. Zobel BJ, Sprague JR. In: Timell TE, editor. Juvenile Wood in Forest Trees. Springer Series in Wood Science. Berlin, Heidelberg GmbH: Springer-Verlag; 1998. p. 300
  103. 103. Walker JCF. Primary Wood Processing—Principles and Practice. London: Chapman and Hall; 1993. p. 596. DOI: 10.1007/1-4020-4393-7
  104. 104. Timell TE. Compression Wood in Gymnosperms. Vol. 1-3. Berlin, Heidelberg: Springer; 1986. p. 2150
  105. 105. Gonçalves AC. In: Shukla G, Chakravarty S, editors. Effects of forest stand structure in biomass and carbon, Forest Biomass and Carbon. London, UK: InTechOpen; 2018. DOI: 10.5772/intechopen.76004
  106. 106. Zobel BJ, van Buijtenen JP. In: Timell TE, editor. Wood Variation—Its Causes and Control. Springer Series in Wood Science. Berlin, Heidelberg: Springer; 1989. p. 363
  107. 107. Fernandez-Golfin JI, Diez MR. Influencia de la anchura del anillo de crescimiento en la densidad y otras propiedades fisico-mecanicas de la madera estructural de diversas especies. Investigacion Agraria, Sistemas y Recursos Forestales. 1994;3(2):211-219
  108. 108. Louzada J, Fonseca F. The heritability of wood density components inPinus pinasterait. And the implications for tree breeding. Annals of Forest Science. 2002;59(8):867-873
  109. 109. Louzada J. Genetic correlations between wood density components inPinus pinasterait. Annals of Forest Science. 2003;60(3):285-294
  110. 110. Gaspar M, Louzada J, Aguiar A, Almeida H. Genetic correlations between wood quality traits ofPinus pinasterait. Annals of Forest Science. 2008;65(7):703
  111. 111. Gaspar M, Louzada J, Silva M, Aguiar A, Almeida H. Age trends in genetic parameters of wood density components in 46 half-sibling families ofPinus pinasterait. Canadian Journal Forest Research. 2008;38:1470-1477
  112. 112. Gaspar M, Louzada J, Rodrigues J, Aguiar A, Almeida M. Does selecting for improved growth affect wood quality ofPinus pinasterin Portugal? Forest Ecology and Management. 2009;258:115-121
  113. 113. Gaspar M, Alves A, Louzada J, Morais J, Santos A, Fernandes C, et al. Genetic variation of chemical and mechanical traits of maritime pine (Pinus pinasterAiton). Correlations with wood density components. Annals of Forest Science. 2011;68(2):255-265
  114. 114. Fernandes C, Gaspar MJ, Pires J, Silva ME, Carvalho A, Lima-Brito J, et al. Within and between-tree variation of wood density components inPinus sylvestrisat five sites in Portugal. European Journal of Wood and Wood Products. 2017;75(4):511-526. DOI: 10.1007/s00107-016-1130-2
  115. 115. Fernandes C, Gaspar MJ, Pires J, Alves A, Simões R, Rodrigues JC, et al. Physical, chemical and mechanical properties ofPinus sylvestriswood at five sites in Portugal. iForest—Biogeosciences and Forestry. 2017;10:669-679. DOI: 10.3832/ifor2254-010
  116. 116. Dias A, Gaspar M, Carvalho A, Pires J, Lima-Brito J, Silva ME, et al. Within- and between-tree variation of wood density components inPinus nigraat six sites in Portugal. Annals of Forest Science. 2018;75:58. DOI: 10.1007/s13595-018-0734-6
  117. 117. Dias A, Carvalho A, Silva M, Lima-Brito J, Gaspar M, Alves A, et al. Physical, chemical and mechanical wood properties ofPinus nigragrowing in Portugal. Annals of Forest Science. 2020;77:72. DOI: 10.1007/s13595-020-00984-8
  118. 118. Santos Hall FA. Tabela de Produção Lenhosa para o Pinheiro Bravo. Separata do Boletim do Ministério de Agricultura, Lisboa; 1931; Ano XIII; n° 1; 1ª Série
  119. 119. Echeverría I., de Pedro S. ElPinus pinasteren Pontevedra. Su productividad normal y aplicación a la celulosa industrial. Boletines del I.F.I.E.. N° 38. Madrid; 1948. p. 147
  120. 120. Décourt N, Lemoine B. Le Pin maritime dans le Sud-Ouest de la France: tables de production provisoires. Annals of Forest Science. 1969;26(1):3-44. DOI: 10.1051/forest/19690101
  121. 121. Gonçalves AC. Modelação de Povoamentos Adultos de Pinheiro Bravo com regeneração de folhosas na Serra da Lousã [thesis]. Lisboa: ISA; 2003. p. 232
  122. 122. Alegria C. Estudo da Dinâmica do Crescimento e Produção dos Povoamentos Naturais de Pinheiro Bravo na Região de Castelo Branco [thesis]. Lisboa: ISA; 2004. p. 498
  123. 123. Running SW, Gower ST. FOREST-BGC, A general model of forest ecosystem processes for regional applications. II. Dynamic carbon allocations and nitrogen budgets. Tree Physiology. 1991;9:147-160
  124. 124. Landsberg JJ, Waring RH. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management. 1997;95:209-228
  125. 125. Lopes D. Estimating Net Primary Production inEucalyptus GlobulusandPinus pinasterEcosystems in Portugal [PhD thesis] . School of Earth Sciences and Geography [thesis]. Kingston: Kingston University; 2005
  126. 126. Alexandre P. Calibração do Modelo 3-PG para Povoamentos de Pinheiro Bravo (Pinus pinaster) em Portugal [master dissertation]. Lisboa: ISA; 2009. p. 68
  127. 127. Fonseca TF. A utilização de modelos de crescimento e produção como suporte à gestão florestal. Projeto INEF-PINUS. Pinus Press n° 26. 2011. ISSN-0874-6109
  128. 128. Bravo F, González AJG, del Río M, Barrio M, Bonet Lledos JA, Bravo Oviedo A, et al. Growth and yield models in Spain: Historical overview, contemporary examples and perspectives. Instituto Universitario de Gestión Forestal Sostenible. 2012. Available from:[Accessed: June 14, 2021]
  129. 129. Dufour-Kowalski S, Courbaud B, Dreyfus P, Meredieu C, de Coligny F. Capsis: An open software framework and community for forest growth modelling. Annals of Forest Science. 2012;69(2):221-233. DOI: 10.1007/s13595-011-0140-9
  130. 130. Bravo F, Rodriguez F, Ordóñez C. A web-based application to simulate alternatives for sustainable forest management: SIMANFOR. Forest Systems. 2012;21(1):4-8
  131. 131. Barreiro S, Rua J, Tomé M. StandsSIM-MD: A management driven forest SIMulator. Forest Systems. 2016;25(2):eRC07. DOI: 10.5424/fs/2016252-08916
  132. 132. Estrutura PF. crescimento e produção em povoamentos de pinheiro bravo. Um modelo de simulação [thesis]. Lisboa: ISA/UTL; 1987
  133. 133. Páscoa F. Using Inventory Data to build growth and yield stand models. In: Proceedings on the IUFRO Conference on Forest Simulation Systems; 2-5 November 1988; Berkeley; 1988. pp. 279-286
  134. 134. Marques CP. Evaluating site quality of even-aged maritime pine stands in northern Portugal using direct and indirect methods. Forest Ecology and Management. 1991;41:193-204
  135. 135. Fonseca TF, Parresol B, Marques C, de Coligny F. Models to implement a sustainable forest management—An overview of the ModisPinaster model. Chapter 18. In: Martín García J, Diez Casero JJ, editors. Sustainable Forest Management. Book 1. London: InTechOpen Access Publisher; 2012. pp. 321-338. DOI: 10.5772/29808 ISBN: 978-953-51-0621-0
  136. 136. Nunes L. Modelo para a predição de indicadores de gestão florestal sustentável em povoamentos de pinheiro bravo em Portugal [thesis]. Lisboa: Universidade de Lisboa, ISA; 2011
  137. 137. Pérez-Rodríguez F, Nunes L, Sil Â, Azevedo J. FlorNExT®, a cloud computing application to estimate growth and yield of maritime pine (Pinus pinasterait.) stands in Northeastern Portugal. Forest Systems. 2016;25(2):eRC08. DOI: 10.5424/fs/2016252-08975
  138. 138. Diéguez-Aranda U, Rojo Alboreca A, Castedo-Dorado F, Álvarez González JG, Barrio Anta M, Crecente-Campo F, et al. Xunta de Galicia: Herramientas selvícolas para la gestión forestal sostenible en Galicia; 2009
  139. 139. Bravo F, Ordoñez C. SIMANFOR: Sistema de apoyo para la simulación de alternativas de manejo forestal sostenible. 2021. Available[Accessed: June 14, 2021]
  140. 140. Meredieu C. Intégration dans Capsis d'un modèle de croissance du Pin maritime développé par l'INRA. Convention n° 61.45.47/01, MAPA-DERF/INRA. Rapport final de cinquième tranche 28/11/2002. In: Auclair D editor. Modélisation et intégration logicielle: croissance, branchaison, qualité des bois. Aide à la décision pour la sylviculture et l'utilisation du bois des essences forestières françaises, Bordeaux; 2002. p. 4
  141. 141. Lemoine B. Modele de croissance pour les forets de dunes - Choix du modele - Proposition pour une validation. Bordeaux: Document Interne; 1996. p. 30
  142. 142. Pasalodos-Tato M, Pukkala T, Alboreca AR. Optimal management ofPinus pinasterin Galicia (Spain) under risk of fire. International Journal of Wildland Fire. 2010;19:937-948
  143. 143. Fonseca TF, Cerveira A, Mota A. An integer programming model for a forest harvest problem with temporal and constraints. Forest Systems. 2012;21(2):272-283. DOI: 10.5424/fs/2012212-02879
  144. 144. Rodil MA. Development of a Dynamic Stand Growth Model and Optimization of the Management of Pinus pinaster Ait. in Asturias [thesis]. Universidade de Santiago de Compostela; 2015
  145. 145. Petucco C, Andrés-Domenech P. Land expectation value and optimal rotation age of maritime pine plantations under multiple risks. Journal of Forest Economics. 2018;30:58-70. DOI: 10.1016/j.jfe.2018.01.001
  146. 146. Costa PD, Cerveira AC, Kašpar J, Marušák R, Fonseca TF. Forest management ofPinus pinasterait. in unbalanced forest structures arising from disturbances - a framework proposal of decision support systems (DSS). Forests. 2021;12:1031. DOI: 10.3390/f12081031
  147. 147. Garcia-Gonzalo J, Palma JHN, Freire JPA, Tome M, Mateus R, Rodriguez L, et al. A decision support system for a multi stakeholder’s decision process in a Portuguese national forest. Forest Systems. 2013;22:359. DOI: 10.5424/fs/2013222-03793
  148. 148. Falcão A, Borges JG. Designing decision support tools for Mediterranean forest ecosystems management: A case study in Portugal. Annals of Forest Science. 2005;62:751-760
  149. 149. Garcia-Gonzalo J, Borges JG, Palma J, Zubizarreta-Gerendiain A. A decision support system for management planning of eucalyptus plantations facing climate change. Annals of Forest Science. 2014;71:187-199
  150. 150. Louzada J. Variação Fenotípica e Genética em Características Estruturais na Madeira dePinus pinasterAit. O comprimento das fibras e a densidade até aos 80 anos de idade das árvores. Parâmetros genéticos na evolução juvenil-adulto das componentes da densidade da madeira. Vila Real: UTAD, Série Didáctica, Ciências Aplicadas n° 143; 2000. p. 293
  151. 151. Dias A. Ecology and management of pinus nigra in mountain areas [thesis]. Vila Real: Universidade de Trás-os-Montes e Alto Douro; 2021. p. 149
  152. 152. Martins DFG. Estudo das características físicas e fio da madeira de Cupressus lusitânica [Master thesis]. Vila Real: Universidade de Trás-os-Montes e Alto Douro; 2013
  153. 153. Gort J, Zubizarreta-Gerendiain A, Peltola H, Jaatinen R. Differences in fibre properties in scots pine (Pinus sylvestrisL.) genetic entries grown at different spacing and sites. Silva Fennica. 2009;43:355-368
  154. 154. Lundqvist S, Grahn T, Hedenberg O. Models for fibre dimensions in different softwood species. Simulation and comparison of within and between tree variations for Norway and Sitka spruce, scots and loblolly pine. In: IUFRO Fifth Workshop “Wood Quality Modelling” STFI-Packforsk report ART 05/54 Auckland, New Zealand. 2005
  155. 155. Lundqvist S, Ekenstedt F, Grahn T, Wilhelmsson L. A system of models for fiber properties in Norway spruce and scots pine and tools for simulation. In: Conference: IUFRO Workshop “Connection between Forest Resources and Wood Quality: Modelling Approaches and Simulation Software"; Harrison Springs, British Colombia, Canada. 2002
  156. 156. Fonseca T, Louzada J. Variação na madeira dePinus pinasterAit. O comprimento e as dimensões transversais das fibras. A densidade, o crescimento e a qualidade físico-mecânica da madeira. Série Técnica-Científica, Ciências Aplicadas n° 35. UTAD: Vila Real; 2000. pp. 242
  157. 157. Pritzkow C, Heinrich I, Grudd H, Helle G. Relationship between wood anatomy, tree-ring widths and wood density ofPinus sylvestrisL. and climate at high latitudes in northern Sweden. Dendrochronologia. 2014;32:295-302. DOI: 10.1016/j.dendro.2014.07.003
  158. 158. Toïgo M, Vallet P, Tuilleras V, et al. Species mixture increases the effect of drought on tree ring density, but not on ring width, inQuercus petraeaPinus sylvestrisstands. Forest Ecology and Management. 2015;345:73-82. DOI: 10.1016/j.foreco.2015.02.019
  159. 159. Gryc V, Vavrčík H, Horn K. Density of juvenile and mature wood of selected coniferous species. Journal of Forest Science. 2011;57:123-130. DOI: 10.17221/18/2010-JFS
  160. 160. Karlman L, Mörling T, Martinsson O. Wood density, annual ring width and latewood content in larch and scots pine. Eurasian Journal of Forest Research. 2005;8(2):91-96
  161. 161. Koga S, Zhang SY. Inter-tree and intra-tree variations in ring width and wood density components in balsam fir (Abies balsamea). Wood Science and Technology. 2004;38:149-162. DOI: 10.1007/s00226-004-0222-z
  162. 162. Carvalho A. Madeiras portuguesas: estrutura anatómica, propriedades, utilizações. Vol. II. Lisboa: Instituto Florestal; 1996. p. 415. ISBN 972-8097-26-3
  163. 163. Leonardon M, Altaner C, Vihermaa L, Jarvis M. Wood shrinkage: Influence of anatomy, cell wall architecture, chemical composition and cambial age. European Journal of Wood and Wood Products. 2010;68:87-94. DOI: 10.1007/s00107-009-0355-8
  164. 164. Han Y, Park Y, Park J, Yang S, Eom C, Yeo H. The shrinkage properties of red pine wood assessed by image analysis and near-infrared spectroscopy. Drying Technology. 2016;34(13):1613-1620
  165. 165. Sjöström E, Alén R. Analytical Methods in Wood Chemistry, Pulping, and Papermaking. Springer Series in Wood Science. Berlin Heidelberg: Springer-Verlag; 2013. p. 318. Available from:
  166. 166. Sable I, Grinfelds U, Jansons A, Vikele L, Irbe I, Verovkins A, et al. Properties of wood and pulp fibers from lodgepole pine (Pinus contorta) as compared to scots pine (Pinus sylvestris). BioResources. 2012;7(2):1771-1783. DOI: 10.15376/biores.7.2.1771-1783
  167. 167. Hannrup B, Cahalan C, Chantre G, Grabner M, Karlsson B, Le Bayon I, et al. Genetic parameters of growth and wood quality traits inPicea abies. Scandinavian Journal of Forest Research. 2004;19(1):14-29. DOI: 10.1080/02827580310019536
  168. 168. Fernandes C. Avaliação da Interacção Genótipo x Ambiente nas características de qualidade da madeira dePinus pinaster[master dissertation]. Vila Real: Universidade de Trás-os-Montes e Alto Douro; 2019. pp. 115
  169. 169. Reva V, Fonseca L, Lousada J, Abrantes I, Figueiredo R, Viegas X. Basic density, extractive content and moisture sorption properties ofPinus pinasterwood infected with the pinewood nematode, Bursaphelenchus xylophilus. Journal of Forestry Research. 2015;26:233-240. DOI: 10.1007/s11676-015-0024-1
  170. 170. da Silva PD, Guillemain A, Alazard P, Plomion C, Rozenberg P, Rodrigues JC, et al. Improvement ofPinus pinasterait. Elite trees selection by combining near infrared spectroscopy and genetic tools. Holzforschung. 2007;61(6):611-622. DOI: 10.1515/HF.2007.118
  171. 171. Telmo C, Lousada J, Moreira N. Proximate analysis, backwards stepwise regression between gross calorific value, ultimate and chemical analysis of wood. Bioresource Technology. 2010;101:3808-3815
  172. 172. Telmo C, Lousada J. Heating values of wood pellets from different species. Biomass and Bioenergy. 2011;35(7):2634-2939
  173. 173. Telmo C, Lousada J. The explained variation by lignin and extractive contents on higher heating value of wood. Biomass and Bioenergy. 2011;35(5):1663-1667. DOI: 10.1016/j.biombioe.2010.12.038
  174. 174. Reva V, Fonseca L, Lousada J, Abrantes I, Viegas X. Impact of the pinewood nematode,Bursaphelenchus xylophilus, on gross calorific value and chemical composition ofPinus pinasterwoody biomass. European Journal of Forest Research. 2012;131(4):1025-1033. DOI: 10.1007/s10342-011-0574-5
  175. 175. Viana HFS, Rodrigues AM, Godina R, Matias JCO, Nunes LJR. Evaluation of the physical, chemical and thermal properties of Portuguese maritime pine biomass. Sustainability (Switzerland). 2018;10(8):1-15
  176. 176. Enes T, Aranha J, Fonseca T, Matos C, Barros A, Lousada J. Residual agroforestry biomass–thermochemical properties. Forests. 2019;10:1072. DOI: 10.3390/f10121072
  177. 177. Enes T, Aranha J, Fonseca T, Lopes D, Alves A, Lousada J. Thermal properties of residual agroforestry biomass of northern Portugal. Energies. 2019;12(8):1418. DOI: 10.3390/en12081418
  178. 178. Kaczmarczyk R, Mlonka-mędrala A. Chloride corrosion in biomass-fired boilers – Fe-O-Cl system thermodynamic analysis. In: 1st International Conference on the Sustainable Energy and Environment Development (SEED 2016); 17 October 2016; E3S Web of Conferences 10, 00060. 2016
  179. 179. Nunes LJR, Matias JCO, Catalão JPS. Biomass combustion systems: A review on the physical and chemical properties of the ashes. Renewable and Sustainable Energy Reviews. 2016;53:235-242. DOI: 10.1016/j.rser.2015.08.053
  180. 180. Caillat SA, Vakkilainen E. Large-scale biomass combustion plants: An overview. In: Biomass Combustion Science, Technology and Engineering. Woodhead Publishing Limited; 2013. DOI: 10.1533/9780857097439.3.189
  181. 181. Johansen JM, Aho M, Paakkinen K, Taipale R, Egsgaard H, Jakobsen JG, et al. Release of K, Cl, and S during combustion and co-combustion with wood of high-chlorine biomass in bench and pilot scale fuel beds. Proceedings of the Combustion Institute. 2013;34(2):2363-2372. DOI: 10.1016/j.proci.2012.07.025
  182. 182. Aho M, Ferrer E. Importance of coal ash composition in protecting the boiler against chlorine deposition during combustion of chlorine-rich biomass. Fuel. 2005;84(2-3):201-212. DOI: 10.1016/j.fuel.2004.08.022
  183. 183. Sardans J, Peñuelas J. Trace element accumulation in the mossHypnum cupressiformeHedw. And the treesQuercus ilexL. andPinus halepensismill. in Catalonia. Chemosphere. 2005;60(9):1293-1307. DOI: 10.1016/j.chemosphere.2005.01.059
  184. 184. Franco C, Pinto F, Gulyurtlu I, Cabrita I. The study of reactions influencing the biomass steam gasification process. Fuel. 2003;82(7):835-842. DOI: 10.1016/S0016-2361(02)00313-7
  185. 185. Nielsen HP, Frandsen FJ, Dam-Johansen K, Baxter LL. Implications of chlorine-associated corrosion on the operation of biomass-fired boilers. Progress in Energy and Combustion Science. 2000;26(3):283-298. DOI: 10.1016/S0360-1285(00)00003-4
  186. 186. Riedl R, Dahl J, Obernberger I, Narodoslawsky M. Corrosion in Fire Tube Boilers of Biomass Combustion Plants. In: Proceedings of the China International Corrosion Control Conference '99; Nr.90129; October 1999; Beijing, China. pp. 2-6
  187. 187. Mandø M. Direct Combustion of Biomass. Biomass Combustion Science, Technology and Engineering. Cambridge, UK: Woodhead; 2013. pp. 61-83. DOI: 10.1533/9780857097439.2.61
  188. 188. Runge TM. Economic and environmental impact of biomass types for bioenergy power plants. In: Environmental and Economic Research and Development Program of Wisconsin’s Focus on Energy, Final Report August; 2013. Available from:
  189. 189. Clarke S, Preto F. Biomass burn characteristics. Ministry of Agriculture, Food and Rural Affairs 2011;(11):6. Available from:[Accessed: Jun 14, 2021]
  190. 190. Khan AA, de Jong W, Jansens PJ, Spliethoff H. Biomass combustion in fluidized bed boilers: Potential problems and remedies. Fuel Processing Technology. 2009;90(1):21-50. DOI: 10.1016/j.fuproc.2008.07.012
  191. 191. Hopkins ER, Butcher TB. Provenance comparisons ofPinus pinasterait. in western Australia. CALMScience. 1993;1(1):55-105
  192. 192. Butcher TB, Hopkins ER. Realised gains from breedingPinus pinaster. Forest Ecology and Management. 1993;58:211-231
  193. 193. Hopkins ER, Butcher TB. Improvement ofPinus pinasterait. in western Australia. CALMScience. 1994;1(2):159-242
  194. 194. Butcher TB. Tree Breeding Programmes ofPinus pinaster. Project Report. Camberra, AU: Winston Churchill Trust; 1999. p. 186
  195. 195. Butcher TB. Achievements in forest tree genetic improvement in Australia and New Zealand 7: Maritime pine and Brutian pine tree improvement programs in Western Australia. Australian Forestry. 2007;70(3):141-151

Written By

Teresa Fidalgo Fonseca, Ana Cristina Gonçalves and José Lousada

Submitted: September 13th, 2021 Reviewed: January 25th, 2022 Published: March 14th, 2022