Physical properties of thinning wood in maritime pine (Pinus pinaster Ait.): case study

ORIGINAL PAPER

Physical properties of thinning wood in maritime pine(Pinus pinaster Ait.): case study

Guillermo Riesco Munoz • Marcos Barrio Anta

Received: 26 September 2008 / Revised: 21 January 2010 / Accepted: 29 April 2010 / Published online: 28 May 2010

� Springer-Verlag 2010

Abstract Forty young trees from a stand of maritime pine

in the southern mountains of Galicia, Spain (42�210N:

8�010W) were felled to obtain the material required for

studying density and shrinkage in clear and small wood

specimens. The wood ranged from light to moderately

heavy, and the dimensions remained reasonably stable with

varying moisture content. The results were consistent with

those obtained in previous studies of adult trees, except for

axial shrinkage, which was very high and variable in this

study. The between-tree variation in wood properties was

high considering that the sampled trees came from the

same stand. However, the relationships between density

and height in the stem were similar in all trees. A general

model for the prediction of volumetric shrinkage was

developed, with oven-dry density and ring width as pre-

dictor variables. The model is feasible for estimation of

wood quality in living trees. It is applicable to tree selec-

tion for thinning and for genetic improvement of stock.

Resume Proprietes physiques du bois d’eclaircies de pin

maritime (Pinus pinaster Ait.). Des pieces en bois, petites

et sans defauts, provenant de 40 jeunes pins maritimes d0un

peuplement des montagnes du Sud de la Galicie, Espagne

(42�210N, 8�010W), ont ete testees. Le bois analyse etait

leger a demi-lourd et de dimensions relativement stables

face aux variations d0humidite. Leurs proprietes: densite et

retractibilite correspondent aux donnees citees pour les

arbres adultes; toutefois, la retractibilite axiale est tres

elevee et possede une tres grande dispersion. La variation

des proprietes entre arbres est tres significative; meme

entre les arbres qui procedaient d0un meme peuplement.

Par ailleurs, les relations entre les variables densite et

hauteur sur la grume sont tres similaires pour toutes les

grumes. Un modele est propose en vue d0estimer la

retractibilite volumetrique, a partir de la densite et de la

largeur de cerne. Le modele permet de determiner la qua-

lite du bois dans des arbres vivants en utilisant comme

critere de selection des sujets dans les eclaircies et dans

l0amelioration genetique.

Keywords Maritime pine � Pinus pinaster �Thinning wood � Volumetric shrinkage

Introduction

Maritime pine (Pinus pinaster Ait.) is the most abundant

pine species in Spain (DGCONA 2002). In Galicia

(northwestern Spain), maritime pine is the most extensive

forest tree, covering 383,000 ha in pure stands (Xunta de

Galicia 2001). The species is also economically important,

with an annual cut volume of 2,158,575 m3 in the period

1994–2005, i.e. 39% of all the harvested wood in the region

(Instituto Galego de Estatıstica 2008).

The spread of maritime pine stands in Galicia initially

took place during the intensive forestations carried out

Communicated by T. Seifert.

G. Riesco Munoz (&)

Departamento de Ingenierıa Agroforestal, Escuela Politecnica

Superior, Universidad de Santiago de Compostela,

Campus Universitario s/n, 27002 Lugo, Spain

e-mail: [email protected]

M. Barrio Anta

Departamento de Biologıa de Organismos y Sistemas,

Escuela Universitaria de Ingenierıas Tecnicas, Universidad de

Oviedo, C/Gonzalo Gutierrez de Quiros, 33600 Mieres, Spain

123

Eur J Forest Res (2010) 129:1037–1045

DOI 10.1007/s10342-010-0388-x

during the nineteenth and twentieth centuries with Pinus

pinaster and other highly productive species such as Pinus

radiata and Eucalyptus globulus (Molina 1993). However,

maritime pine is nowadays completely naturalised and

exhibits an excellent aptitude for natural regeneration (after

fire or after final harvest).

Naturally regenerated stands are initially extremely

dense and consist up to 30,000 stems per hectare (Alvarez

et al. 2002). Pre-commercial and commercial thinnings are

carried out in these zones to avoid stagnation and to

improve the vigour, growth, stability and log quality of the

remaining trees (Cameron 2002). The wood in these

intermediate cuts is harvested as small dimension timber,

mostly used as raw material in wood-based panel indus-

tries (particleboard and fibreboard manufacturing), which

have low technological requirements as regards timber

dimensions and quality (Remacha 1987). At an age of

10–15 years, maritime pine trees grown at low stand

densities yield useful logs for the production of glued

laminated timber (Carvalho 1994). To a minor extent, the

consumption of small-diameter roundwood in the manu-

facturing of scaffolding, fences and wood for agriculture-

related construction allows commercialisation of the

species at with relatively high market prices compared with

those in other Spanish regions.

Maritime pine wood has been investigated in several

studies in Spain and Portugal (e.g. Aguiar et al. 2003;

Carvalho 1994; Casado et al. 2001; Fernandez-Golfın and

Dıez 1996; Fonseca 1989; Louzada 2003; Prades et al.

2001) and also in France (e.g. Dumail and Castera 1997;

Dumail et al. 1998; Pot et al. 2002). However, limited

research on the quality of wood from thinned trees has been

carried out in Spain.

A complete assessment of maritime pine thinning

wood requires the analysis of wood density, because of

its value as a wood quality index (Fonseca 1989; Forest

Products Laboratory 1999; Pot et al. 2002; Zobel and

van Buijtenen 1989). The dimensional stability of wood,

linear and volumetric shrinkage, must be also analysed

because it affects the use of wood in many applications,

e.g. in construction timber and for poles and furniture.

These properties should be determined by single methods

in living trees, to yield criteria for tree selection in

thinning and breeding programmes (Louzada 2003;

Macdonald and Hubert 2002; Nicholls 1970; Pot et al.

2002).

The aims of the present study were as follows: (1) to

investigate the main physical properties—namely density

and dimensional stability—under varying moisture con-

tent, of maritime pine wood obtained from early thinnings

of stands in Galicia; (2) to establish a feasible criterion

for tree selection in early thinnings, based on wood

quality.

Materials and methods

The sampling area was the forest of San Trocado (42�210N,

8�010W, 375 m elevation), located in Punxın, in southern

Galicia (NW Spain). The stand is even-aged (10–15 years)

and originated from post-fire natural regeneration. Forty

young maritime pines were felled in conventional low

thinnings in order to obtain the test material. The variables

measured in the trees are listed in Table 1. Two cross-

sectional discs were obtained from each tree (at the stem

base and at 5.0 m height in the stem) for investigation of

the physical properties of the wood at both ends of the

mean merchantable bole of a young tree. The freshly sawn

discs (80) were cut into small prismatic specimens with, as

far as possible, the edges parallel to the main directions of

the wood grain (Fig. 1). Only 50% of the specimens

obtained from the discs were suitable for testing, i.e.

straight grain, absence or limited presence of defects as

knots, checks, bark, reaction wood and blue stain. Finally,

some 225 clear specimens were selected for testing, con-

sidering that pieces with juvenile wood and pith were also

defect-free specimens, with the following target dimen-

sions: 133 specimens of 4 cm length and 2 9 2 cm as the

Table 1 Biometric characteristics of the maritime pine trees

(n = 40)

Variable Mean Minimum Maximum

Breast height diameter outside bark

(cm)

10.6 5.2 17.4

Basal diameter inside bark (cm) 10.7 5.7 19.1

Diameter at 5 m inside bark (cm) 6.0 2.0 10.8

Height (m) 9.3 7.1 11.6

Height-dbh ratio 0.93 0.63 1.38

Age (year) 12.4 10 15

Diameter growth (mm per year) 9.1 5.9 13.9

Fig. 1 Pattern of sampling of specimens along the stem of a tree

1038 Eur J Forest Res (2010) 129:1037–1045

123

transverse section, 92 specimens of 2 cm length and

4 9 4 cm as the transverse section. Axial stability vari-

ables were only measured in specimens of 4 cm length

because it was difficult to detect changes in axial dimen-

sion in the specimens under 4 cm length. Similarly,

transverse (tangential and radial) stability properties were

only measured in the 4 9 4 cm specimens because it was

difficult to detect changes in transverse dimensions in the

specimens under that section. Some qualitative features

were recorded, e.g. presence of rings strictly parallel to

edges and presence of pith.

The quantitative wood properties studied are shown in

Table 2. The tests were carried out by the EN and ISO

standard methods for evaluating physical properties of

wood (European Committee for Standardization 2002,

2003, 2004; International Organization for Standardization

1975). The mass and the three main dimensions of each

specimen were measured at three successive wood mois-

ture contents: saturation, approximately 12% wood mois-

ture (equilibrium moisture content in the laboratory

environment) and 0% moisture (oven-dry wood). The mass

was measured to the nearest 0.01 g, and the three main

dimensions were obtained between centres of opposite

faces, to the nearest 0.01 mm. The width of annual growth

rings (RW) was also assessed in each saturated specimen

and was calculated as the dimension of the longest radial

segment in the section divided by the number of rings, and

averaging the measurements made on both faces.

The linear shrinkage in the three main grain directions

(Cl, Cr and Ct) and the volumetric shrinkage (Cv) were

calculated as the difference in dimension at saturation

moisture content and in the oven-dry state and expressed as

percentages of the dimension in the oven-dry state. The

volumetric shrinkage coefficient (v) and the three linear

coefficients (l, r and t) were computed on the basis of

differences in the dimensions between equilibrium mois-

ture content (12% approximately) and oven-dry state and

were expressed as percentages of the dimensions in the

oven-dry state and by the degree of moisture content. The

transverse stability was only tested in those 2 9 4 9 4 cm

specimens with rings parallel to edges and that were not

curved, because it would be difficult to differentiate

between tangential and radial shrinkage in specimens with

strong ring curvature. The axial shrinkage was only tested

in 4 9 2 9 2 cm specimens.

The difference between tangential and radial shrinkage

was evaluated as anisotropic shrinkage (tangential over

radial shrinkage ratio). The absolute anisotropy (tangential

minus radial shrinkage) was also calculated because this

difference gives a better indication of the risk of defor-

mation of the wood during drying than the ratio itself

(Rijsdijk and Laming 1994).

The relationships between quantitative variables were

tested with Pearson’s linear correlation coefficient (R). A

one-factor analysis of variance was carried out to test for

significant relationships between quantitative and qualita-

tive variables. Comparison of the estimates for the models

analysed was based on graphical and numerical analyses of

the residuals. Three statistical criteria were examined:

relative bias (E%), relative root mean square error

(RMSE%) and adjusted determination coefficient (Radj2 ).

Results and discussion

Basic statistics of the variables

The trees under study were very young, in the first third of

the usual rotation for the species (see main characteristics

in Table 1). The stems were almost cylindrical, as con-

cluded from the height-dbh ratio, and the diameter growth

was slightly below the growth in the yield table for the best

site index (Rodrıguez et al. 2000).

The main statistics of the wood properties studied are

shown in Table 2. Overall, the tested wood was moderately

stable and light-moderately dense. The results are consis-

tent with those of previous studies of adult maritime pine

trees (Casado et al. 2001; Fernandez-Golfın and Dıez 1996;

Fonseca 1989; Gutierrez and Plaza 1967; Ortiz and

Martınez 1991; Pot et al. 2002; Prades et al. 2001;

Remacha 1987). The notable exception was axial shrink-

age, which was much greater in the sampled thinning

wood. This is consistent with other reports concerning the

axial instability of juvenile wood (e.g. Forest Products

Laboratory 1999; Zobel and van Buijtenen 1989), largely

present in thinning trees (Aguiar et al. 2003). Specimens

with very round rings adjacent to the pith probably con-

tained juvenile wood, and this group of specimens was

included in the tests because juvenile wood is usual in the

core section of young trees.

Effect of density on the dimensional stability of wood

The linear correlation between the different density vari-

ables and the shrinkage properties was not high (Table 3).

Only volumetric and axial shrinkage variables were highly

significantly dependent on density. This result was partly

attributed to the larger size of the sample considered for

these variables. Consideration of the subsamples of wood

with or without pith separately did not improve the corre-

lations. The absence of more relevant correlations in these

subsamples could be also attributed to their small size,

specifically for the variables related to transverse stability

(Table 2).

Eur J Forest Res (2010) 129:1037–1045 1039

123

Table 2 Descriptive statistics for the physical properties of maritime pine wood

Variable n Mean Minimum Maximum CV (%)

All specimens

Ring width (mm) (RW) 225 6.6 3.0 11.4 29.0

Air-dry density (kg/m3) (q12) 225 497 364 621 11.4

Oven-dry density (kg/m3) (q0) 225 465 338 585 11.7

Basic density (kg/m3) (db) 225 408 307 527 10.4

Volumetric shrinkage (%) (Cv) 225 13.9 8.0 22.8 18.5

Volumetric shrinkage coef. (%) (v) 225 0.40 0.15 0.83 18.3

Axial shrinkage (%) (Cl) 133 0.9 0.0 3.4 78.6

Axial shrinkage coefficient (%) (l) 133 0.03 0.00 0.17 96.4

Radial shrinkage (%) (Cr) 22 4.7 3.4 6.3 17.2

Radial shrinkage coef. (%) (r) 22 0.15 0.09 0.22 23.5

Tangential shrinkage (%) (Ct) 22 7.7 5.9 9.8 13.0

Tangential shrinkage coef. (%) (t) 22 0.22 0.18 0.27 13.1

Anisotropic shrinkage (Ct/Cr) 22 1.68 1.28 2.41 17.1

Absolute anisotropy (%) (Ct - Cr) 22 3.0 1.4 5.7 34.2

With pith

Ring width (mm) (RW) 51 5.2 3.3 10.0 27.8














Without pith

Ring width (mm) (RW) 174 6.9 3.0 11.4 26.5














n = number of cases; CV (%) = coefficient of variation

1040 Eur J Forest Res (2010) 129:1037–1045

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The effect of density on the anisotropic dimensional

stability of wood was rather small, as reported for 17- and

20-year-old trees (Dumail and Castera 1997) and also for

other softwoods (Mazet and Nepveu 1991). In adult trees,

the gravimetric properties (namely air-dry density, oven-

dry density and basic density) are acknowledged to be the

best single predictors of other physical properties of soft-

wood (Boutelje 1962; Forest Products Laboratory 1999;

Kininmonth and Whitehouse 1991; Pot et al. 2002).

Fonseca (1989) reported correlation coefficients between

density and other physical properties ranging from 0.44 to

0.86. Similar relationships were observed in the present

study (Table 3), but they were not strong enough to

develop any shrinkage prediction model with only density

as the predictor variable. The three density variables

showed similar correlations with the other physical prop-

erties, but the R values were slightly better in the case of

oven-dry density. For that reason, the analyses involved in

the prediction of volumetric shrinkage will focus hereafter

on the oven-dry density as the main predictor variable.

The usual approach in which prediction models are used

for each individual tree was not applied in the present study

because of the small size of sample per tree and the lack of

generality of a model that is assumed to be only valid for

one specific tree.

Relationships between the physical properties of wood

and the annual growth ring width

Density and other analysed variables were weakly related

to ring width corresponding to the whole sample, without

grouping by individual trees or presence of pith (Table 4).

Considering absolute values, the strongest correlation was

between tangential shrinkage and ring width. However,

these results may be unrepresentative because of the small

subsample involving only the specimens in which ring

curvature was negligible. The graphical analysis indicated

that a nonlinear regression model would not fit properly

and thus, no predictive model of shrinkage properties based

only on ring width was obtained. Mazet and Nepveu (1991)

also reported only a slight correlation between ring width

and shrinkage in Pinus sylvestris, Abies alba and Picea

abies.

Although there was no significant relationship between

ring width and density, the relationship was notable when

only the subsample with the pith was considered, i.e. the

subsample in which the juvenile wood was probably

present (Table 4). This finding, also reported by Louzada

and Fonseca (1991) for Pseudotsuga menziesii, suggests

that juvenile wood exhibits similar patterns of variation in

density-ring width for all the sampled trees. Such patterns

diversify and take on specific traits within each tree when

the type of wood considered changes from juvenile to

mature. The negative sign of the linear correlation coeffi-

cient was also apparent, as is frequently cited for softwoods

(Fernandez-Golfın and Dıez 1996; Kininmonth and

Whitehouse 1991; Koga and Zhang 2004; Louzada 2003;

Louzada and Fonseca 1991; Remacha 1987).

In the subsample with pith, the density-ring width

relationship was not strong enough to justify developing a

model for predicting density based only on ring width. It is

Table 3 Correlation coefficients (R) between density and shrinkage

properties of maritime pine wood

Air-dry

density

Oven-dry

density

Basic

density

Volumetric shrinkage 0.64*** 0.67** 0.54**

Volumetric shrinkage

coefficient

0.35** 0.41** 0.33**

Axial shrinkage 0.44** 0.46** 0.40**

Axial shrinkage

coefficient

0.28** 0.30** 0.26**

Radial shrinkage 0.00 0.04 -0.15

Radial shrinkage

coefficient

-0.02 0.02 -0.05

Tangential shrinkage 0.50* 0.53* 0.35

Tangential shrinkage

coefficient

0.21 0.27 0.23

Anisotropic shrinkage 0.40 0.38 0.43*

Absolute anisotropy 0.48* 0.48* 0.46*

*, ** Significant at P B 0.050 or 0.010, respectively

Table 4 Correlation coefficients (R) between ring width and the

other physical properties, considering the presence or absence of pith

in the sample

Variable Ring width

With

pith

Without

pith

All

specimens

Air-dry density -0.46** -0.06 -0.06

Oven-dry density -0.46** -0.06 -0.07

Basic density -0.46** -0.04 -0.04

Volumetric shrinkage -0.39** -0.14 -0.16*

Volumetric shrinkage

coefficient

-0.20 -0.08 -0.11

Axial shrinkage -0.08 -0.01 0.02

Axial shrinkage coefficient 0.20 0.02 0.06

Radial shrinkage 0.10 0.16 0.04

Radial shrinkage coefficient -0.09 0.17 0.04

Tangential shrinkage -0.79 -0.59** 0.49*

Tangential shrinkage

coefficient

0.35 0.32 0.06

Anisotropic shrinkage -0.40 0.28 0.29

Absolute anisotropy -0.45 0.48* 0.45*

*, ** Significant at P B 0.050 or 0.010, respectively

Eur J Forest Res (2010) 129:1037–1045 1041

123

generally accepted that annual growth ring width is not

directly related to density in softwoods (Fernandez-Golfın

and Dıez 1996; Fonseca 1989; Leban et al. 1991; Louzada

2003). In fact, ring width has an indirect effect on density

through cambial age, i.e. the number of annual growth

rings from pith (Fonseca 1989; Kininmonth and White-

house 1991; Koga and Zhang 2004).

Along-stem variation in density

The physical properties varied significantly with the height

in the stem (Table 5). The relationship between density and

height in the stem was negative. It was consistent with

those reported for young maritime pines (Dumail et al.

1998) and adult conifers (Fonseca 1989; Kininmonth and

Whitehouse 1991; Kollmann 1951). The ratio of air-dry

density at the base of the tree to the air-dry density at 5 m

height was on average 1.21, with a minimum value of 1.00

and a maximum value of 1.35. The ratio was on average

1.22 for oven-dry density and 1.17 for basic density. The

variation in the ratio was low (CV = 7.1% for air-dry

density, 6.9% for oven-dry density and 6.8% for basic

density) and thus, the bottom-up density variation did not

differ very much from tree to tree. A general height-density

model could therefore be developed for all the sampled

trees. This should not be assumed with trees older than the

sampled age (15 years) because the height-density rela-

tionship is strongly affected by the tree effect in 20-year-

old maritime pines (Dumail et al. 1998).

Between-tree variation in density

Even with a sample of young trees from an even-aged stand

in a specific site, there were highly significant differences

among trees in all the analysed properties related to wood

density, volumetric shrinkage and axial stability (Table 5).

The effect of individual attributes on softwoods has been

reported by several authors for Pinus pinaster (Fonseca

1989; Louzada 2003), Abies balsamea (Koga and Zhang

2004), Pseudotsuga menziesii (Louzada and Fonseca 1991)

or Picea sitchensis (Macdonald and Hubert 2002). The

differences among trees in the present study cannot be

mainly attributed to the differences in age, because of the

narrow range of ages in the sample (10–15 years).

Effect of presence of pith on the physical properties

of wood

The presence of pith in the specimens affected the ring

width, the density properties and the axial shrinkage

(Table 5). This is probably because of the low cambial age

near the pith, i.e. the abundance of juvenile wood, as

pointed out elsewhere in this paper (Aguiar et al. 2003;

Forest Products Laboratory 1999; Zobel and van Buijtenen

1989). Mean oven-dry density was only 4.4% lower in

specimens with pith (4.6% for air-dry density and 4.3% for

basic density), and the density around the pith was not

much lower because the rest of the wood was also juvenile.

Prediction of volumetric shrinkage based on ring

width and oven-dry density

The correlation coefficients revealed that volumetric

shrinkage was significantly related to both density

(Table 3) and ring width (Table 4). The correlation with

density was slightly higher for the variable oven-dry den-

sity. The volumetric shrinkage may therefore be predicted

by means of a model with oven-dry density and ring width

as the predictor variables. As already pointed out in other

studies, ring width mainly depends on the site, whereas

density depends also on tree genetics (Louzada 2003;

Louzada and Fonseca 1991). The model would therefore

Table 5 Number of cases (n), high and very high significance levels (\0.050) and F-values (F) in the one-factor analysis of variance for the

physical properties of maritime pine wood

Quantitative variable Qualitative variable

Height in stem Tree Presence of pith

n Sig. F n Sig. F n Sig. F

Ring width 225 0.000 23.35 225 0.000 4.36 225 0.000 37.62

Air-dry density 225 0.000 153.61 225 0.000 4.19 225 0.010 6.70

Oven-dry density 225 0.000 170.17 225 0.000 4.17 225 0.014 6.07

Basic density 225 0.000 115.07 225 0.000 4.57 225 0.008 7.11

Volumetric shrinkage 225 0.000 293.25 225 0.000 2.38

Volumetric shrinkage coef. 225 0.000 76.41 225 0.000 2.38

Axial shrinkage 133 0.000 36.93 133 0.000 2.44 133 0.033 4.62

Axial shrinkage coefficient 133 0.000 14.89 133 0.000 3.46

Variables related to transverse stability were not considered because of a lack of data

1042 Eur J Forest Res (2010) 129:1037–1045

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include both the environmental and genetic sources of

variation in volumetric shrinkage, which is an important

trait in the physical characterisation of wood.

The stepwise fitting showed that linear correlation was

enhanced by considering the following transformed vari-

ables: natural logarithm of volumetric shrinkage ln(Cv),

squared ring width RW2 and inverse of squared oven-dry

density 1q2

0

. Tree age and diameter at breast height could be

included in the model as easily measurable predictor

variables. However, these variables were not significantly

correlated with volumetric shrinkage. This was attributed

to the narrow range of breast height diameters and ages in

the sample, because only one stand was used to provide the

material.

The correlations between volumetric shrinkage and the

predictor variables were not improved when the specimens

at the base of the tree and at 5 m height were considered

separately. On the other hand, the correlation between ring

width and other properties was largely dependent on the

presence of pith (Table 4), and the presence or absence of

pith also affected the correlation between oven-dry density

and volumetric shrinkage.

The above considerations justified the use of oven-dry

density, ring width and also presence/absence of pith as

predictor variables in the model. Furthermore, these vari-

ables are easy to obtain from increment cores taken from

living trees (the mean ring width can be also calculated

from the diameter inside bark if the age of the tree is

known). The sampled increment cores can include pith or

not. A model considering both possibilities is therefore

theoretically justified. Cambial age is one of the main

variables in density prediction, but it was not included in

the model because it is not an easy property to measure in

increment cores (if the pith is absent).

Surprisingly, two accuracy indicators (adjusted deter-

mination coefficient and relative root mean square error)

were poorer in the model considering the variable pres-

ence/absence of pith than those in the model in which the

variable presence or absence of pith is not considered

(Table 6). Furthermore, the collinearity between the pre-

dictor variables (RW2 and 1q2

0

) could be disregarded in the

complete sample because the existing linear correlation

(R = 0.10) was assumed to be small enough to be ignored,

but the collinearity was high in the subsample including

pith (R = 0.51**). In addition, it must be pointed out that

the coefficients for both fittings (presence and absence of

pith) were not significantly different, and estimated confi-

dence intervals for the coefficients were much wider in the

model in which the presence or absence of pith was con-

sidered. Therefore, the model including six parameters

(three for wood with pith and three for wood without pith)

did not have any apparent advantage over the model

including three parameters. The model including squared

ring width and inverse of squared oven-dry density as the

predictor variables, but not considering the presence or

absence of pith, was therefore finally selected.

Ring width played a minor role in diminishing the bias

and made little contribution to the precision of the model

(Table 6). Graphical analysis comparing the observed

versus the predicted volumetric shrinkage (Fig. 2) revealed

few outliers and also showed that further transformations of

the predictor variables would not improve the accuracy of

the proposed model.

The validity of the model Cv = exp(3.17 -

0.00079RW2 - 106,333.60/q02) was limited to values of

ring width below 12 mm (Fig. 3), because of the lack of

Table 6 Parameter estimates for the equation predicting volumetric shrinkage (Cv, in percentage) as a function of ring width (RW, in mm) and

oven-dry density (q0, in kg/m3) for the entire sample

Parameters of the model Coefficient Sig. level Confidence interval for the coefficient at 95% Radj2 E% RMSE%

Lower limit Upper limit

Equation Cv = exp(a ? bRW2 ? c/q02)

a 3.17 0.000 3.09 3.24

b -0.00079 0.020 -0.00145 -0.00012 0.47 0.92 13.44

c -106,333.60 0.000 -121,104.94 -91,562.26

Radj2 = adjusted determination coefficient; E = relative bias; RMSE = relative root mean square error

5

10

15

20

25

5 10 15 20

predicted volumetric shrinkage (%)

obse

rved

vol

umet

ric s

hrin

kage

(%

)

Fig. 2 Graphical representation of the residuals, observed volumetric

shrinkage minus predicted volumetric shrinkage, plotted against the

secondary predictor variable in the model

Eur J Forest Res (2010) 129:1037–1045 1043

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data corresponding to higher values. However, the limited

validity of the model is not important in practical terms

because maritime pines with ring width of more than

12 mm at 10–15 years age are not common (Rodrıguez

et al. 2000). The range of densities included in the model

was below 600 kg/m3, also because of a lack of data cor-

responding to higher values. The limited validity of the

model was again not relevant because it is not usual to find

trees with oven-dry density above 600 kg/m3 (Table 2).

The model showed that density has a positive effect on

volumetric shrinkage and that ring width has a negative and

less relevant effect on volumetric shrinkage. Volumetric

shrinkage in maritime pine may be low (under 10%) in

light wood, or high (above 15%) if the wood is heavier. On

the other hand, a fourfold increase in the ring width (from 3

to 12 mm) in dense wood (e.g. 550 kg/m3) only reduced

the volumetric shrinkage from 16.6 to 14.9%. As a result,

the selection of young trees with the best quality wood,

evaluated by volumetric shrinkage, will mainly be based on

the individual density. Ring width must be considered as a

secondary variable in the selection.

Conclusions

Maritime pine thinning wood in the analysed stand is light

to moderately dense, with intermediate dimensional sta-

bility, although more unstable than expected from the

density.

The mean values for the physical properties studied

differed significantly among tree individuals, as previ-

ously described for Pinus pinaster (e.g. Aguiar et al.

2003; Dumail and Castera 1997; Dumail et al. 1998;

Fonseca 1989; Louzada 2003; Nicholls 1970; Pot et al.

2002) and for many other softwoods (e.g. Kininmonth and

Whitehouse 1991; Koga and Zhang 2004; Leban et al.

1991; Mazet and Nepveu 1991; Zobel and van Buijtenen

1989). It would be useful to know if the physical prop-

erties are heritable, in order to enhance wood quality by

the implementation of selection and improvement pro-

grammes, provided that the goal is the production of

valuable timber (Nicholls 1970). The heritability of wood

density components has been already assessed in Pinus

pinaster (Aguiar et al. 2003; Louzada 2003; Pot et al.

2002), although further study of a complete set of wood

properties is necessary.

The relationship between height in the stem and density

was negative and highly significant, with the importance of

the relationship varying slightly from tree to tree in the

stand. A general but accurate height-density model can

therefore be developed for all the trees sampled within this

case study.

Both density and ring width were correlated with some

other physical properties, and the existing correlation was

strong enough to be able to develop a predictive model of

the volumetric shrinkage with oven-dry density and ring

width as the predictor variables, both of which are easy to

obtain from living trees. Estimation of volumetric shrink-

age, an important variable in the physical characterisation

of wood, can be used to predict the volumetric shrinkage

coefficient and the shrinkage in two main directions of the

wood grain (Ct, Cr), because of the strong correlation

between these variables and volumetric shrinkage.

The model may allow prediction of the quality of

standing timber in an individual stand of maritime pine,

specifically those properties related to the dimensional

stability of wood. Taking silvicultural practices into

account, predictable physical properties of wood can be

used as one of the early tree selection criteria for carrying

out thinnings.

Acknowledgments We thank the Xunta de Galicia and the CICYT

for supporting the project and Jorge Palacios Estremera for his

comments on the manuscript.

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Physical properties of thinning wood in maritime pine (Pinus pinaster Ait.): case study