L’éclaircie commerciale des peuplements d’épinette noire :

Qualité et valeur des sciages

Mémoire

Mikael Bernier

Maîtrise en sciences du bois

Maître ès sciences (M.Sc.)

Québec, Canada

© Mikael Bernier, 2016

L’éclaircie commerciale des peuplements d’épinette noire : Qualité et valeur des sciages

Mémoire

Mikael Bernier

Sous la direction de :

Alexis Achim, directeur de recherche

David Pothier, codirecteur de recherche

iii

Résumé

Cette étude vise à améliorer les connaissances reliées à la pratique de l’éclaircie

commerciale (EC) et à ses effets sur la qualité et la valeur monétaire des produits

transformés. Un dispositif de suivi de l’EC établi dans différentes régions a été

remesuré et des billes d’épinettes noires provenant de peuplements éclaircis 10 à 13

ans auparavant et non éclaircis ont été prélevées, puis sciées en madriers. Des essais

mécaniques en flexion (MOE, MOR) ont été réalisés. Les données ont été soumises

soit à une ANOVA, une régression linéaire ou une régression logistique. Les résultats

démontrent que l’EC a eu un effet sur l’accroissement des arbres (P < 0,001), sur leur

valeur (P < 0,001), et sur la quantité (P = 0,011) et la taille (P = 0,031) des nœuds,

sans avoir d’impact sur la résistance mécanique (P > 0.05) du bois. Ces résultats

indiquent que l’EC permet d’augmenter la valeur des arbres sur pied.

iv

Abstract

The main purpose of this study is to improve the knowledge related to commercial

thinning (CT), its application and its effects on the quality and economic value of

processed products. A network of plots that aimed to monitor the long-term effects of

CT was measured. Black spruce logs were harvested from treated stands (conducted

10-13 years before) and control stands and then processed in lumber. Bending

stiffness tests were performed to measure the moduli of elasticity (MOE) and rupture

(MOR). The quality and financial datas were submitted to different statistical

analysis: ANOVA, linear regression or logistic regression. The results show that

commercial thinning had a positive effect on the diameter growth of residual trees

(P = 0.001) and the total value of lumber products (P = 0.001). The treatment also

increased the quantity (P = 0.011) and size (P = 0.031) of knots, although no

significant effects were detected on MOE and MOR (P > 0.05). Tree volume and

their value increased with DBH in populations that had been subjected to a

commercial thinning. These results suggest that commercial thinning may be

included in forest management strategies that aim to increase the value of standing

trees.

v

Table des matières

Résumé ........................................................................................................................ iii

Abstract ....................................................................................................................... iv

Table des matières ........................................................................................................ v

Liste des tableaux ........................................................................................................ vi

Liste des figures ......................................................................................................... vii

Remerciements .......................................................................................................... viii

Avant-propos ................................................................................................................ x

Introduction .................................................................................................................. 1

Chapitre 1 - Effect of commercial thinning ................................................................. 4

1.1 Introduction ...................................................................................................... 4

1.2 Material and methods ....................................................................................... 8

1.2.1 Experimental site ...................................................................................... 8

1.2.2 Sampling ................................................................................................ 10

1.2.3 Material testing ...................................................................................... 12

1.2.4 Statistical analyses ................................................................................. 14

1.3 Results ............................................................................................................ 16

1.3.1 Commercial thinning and region effects ................................................ 16

1.3.2 DBH effect ............................................................................................. 22

1.4 Discussion ...................................................................................................... 24

1.5 Conclusion ...................................................................................................... 28

Conclusion générale ................................................................................................... 29

Bibliographie .............................................................................................................. 31

Annexes ...................................................................................................................... 34

vi

Liste des tableaux

Table 1.1 Charasteristics of studied plots. ................................................................ 10

Table 1.2 P-values obtained in the ANOVA tests. ................................................... 17

Table 1.3 p-values obtained in the logistic regression tests for the sizes and grades

of lumber pieces. ........................................................................................................ 22

Table 1.4 Parameters of the relationships between DBH and value indicators. ....... 22

Table 1.5 p-values obtained in the logistic regression tests when considering DBH

as a determining factor. .............................................................................................. 23

vii

Liste des figures

Figure 1.1 World’s black spruce distribution ........................................................... 6

Figure 1.2 Experimental sites of the study located thoughout Quebec .................... 9

Figure 1.3 Boxplots of the observed values of DBH. ............................................ 18

Figure 1.4 Growth for a same duration period before and after thinning. ............. 18

Figure 1.5 Boxplots of the value (CAD$) per tree. ................................................ 19

Figure 1.6 Boxplots of the value ($) per cubic meter of round wood. ................... 19

Figure 1.7 Boxplots of the MOE of lumber pieces of different dimensions. ......... 20

Figure 1.8 Boxplots of the MOE for lumber pieces of different dimensions. ........ 21

Figure 1.9 Quantity of lumber feet in each grade for each treatment. ................... 21

Figure 1.10 The DBH quartiles distribution ............................................................. 23

viii

Remerciements

Je tiens d’abord à remercier mon directeur Alexis Achim qui m’a approché car il

croyait en mes aptitudes. Sa confiance, ainsi que celle de mon co-directeur, David

Pothier, m’ont permis de m’accomplir au sein de l’univers de la recherche et des

études supérieures.

Je veux aussi remercier Marie-Pier Arsenault qui a su m’endurer pendant un été en

forêt, alors que le travail était exigeant. Merci aux employés de l’Université Laval:

Sylvain Auger, Guylaine Bélanger, Maryse Beaupré, Carmen Bilodeau, Daniel

Bourgault, Colette Boursier, Amélie Dauphinais, Luc Germain, Louise Joannette,

André Lapierre, David Lagueux, Martine Lapointe, Hélène Robitaille, Éric Rousseau

et Benoit St-Pierre. Je vous remercie tous pour votre disponibilité, votre incroyable

efficacité et votre constante bonne humeur.

Merci à David Auty pour son aide plus qu’appréciée en ce qui concerne la

programmation statistique. Sans lui, je serais encore à essayer de comprendre la

régression logistique. Merci à Julie Barrette et Normand Paradis, qui ont partagé avec

moi leurs connaissances et communiqué leur passion pour la recherche.

Je veux remercier les autres membres, partenaires ou organismes qui ont rendu

possible ce projet. Il s’agit de Jean-Claude Ruel (Université Laval), Cornelia Krause

(UQAC), Isabelle Duchesne (FPInnovations), Stéphane Tremblay (MFFP), Scierie

Leduc, le Fonds de recherche du Québec sur la nature et les technologies du et la

Chaire de recherche industrielle CRSNG - Université Laval en sylviculture et faune.

ix

Un immense merci à mes parents qui m’ont toujours encouragé et appuyé. La fierté

qu’ils démontrent à mon égard me touche énormément. Merci à Doris et Lyne qui

m’ont toujours traité comme si j’étais leur fils. Leur appui a sans contredit contribué à

ce que je me rende là où j’en suis.

Pour finir, un remerciement spécial à ma femme Janie. Elle est ma complice de tous

les jours, elle me comprend comme personne et sait toujours trouver les mots pour

m’encourager et m’aider à me dépasser.

x

Avant-propos

Le projet à l’origine de ce mémoire a été financé par le Fonds de recherche du

Québec sur la nature et les technologies et par la Chaire de recherche industrielle

CRSNG - Université Laval en sylviculture et faune.

Je certifie être le principal auteur de ce document. J’y ai participé, non seulement par

la rédaction, mais aussi lors de la planification de l’étude, de la prise de mesure en

forêt, de la transformation du bois, des tests expérimentaux et de l’analyse statistique.

Mon directeur Alexis Achim et mon co-directeur David Pothier figurent

respectivement à titre de second et dernier auteur du projet d’article inclus dans ce

mémoire. Ils ont élaboré le projet de recherche et m’ont supporté et conseillé à toutes

les étapes. David Auty est troisième auteur, car il a agi comme consultant statistique

et a ainsi rendu possible la programmation d’analyses qui ont répondu aux

questionnements énoncés dans l’étude. Stéphane Tremblay est quatrième auteur, car

il a contribué en fournissant les bases de données provenant du Ministère des forêts,

de la faune, et des parcs et en nous permettant d’échantillonner à proximité d’un

réseau de placettes mis en place par ce même Ministère.

Ce mémoire est présenté en un chapitre qui constitue une insertion d’un projet

d’article scientifique rédigé en anglais qui sera soumis à une revue de calibre

international en recherche forestière.

1

Introduction

Le monde forestier québécois est maintenant au tournant d’une nouvelle ère dans

laquelle les attentes sociales et industrielles se dirigent vers un aménagement axé sur

des pratiques qui maintiennent les diverses fonctions des écosystèmes tout en

permettant une récolte rentable de matière ligneuse. Ces objectifs qui peuvent

sembler contradictoires ont mené à l’adoption de différentes approches dont les

résultats anticipés devraient aider à faire progresser la quête d’un aménagement

forestier durable en maintenant l’approvisionnement des usines de première

transformation présentes sur le territoire québécois. Le nouveau régime forestier

récemment mis en place dans les forêts publiques de la province a regroupé ces

approches sous les vocables d’aménagement écosystémique et d’aménagement

intensif.

De manière générale, l’aménagement écosystémique s’inspire des perturbations

naturelles afin de maintenir les fonctions des écosystèmes forestiers naturels

(Gauthier et al., 2008). Or, plusieurs perturbations de faible ou moyenne sévérité

surviennent en forêt boréale, entraînant ainsi la mortalité d’arbres sur de faibles

superficies ou la mortalité d’arbres dispersés (Gauthier et al., 2008) Les coupes

partielles peuvent représenter un outil sylvicole permettant d’imiter ce processus

souvent associé aux épidémies légères d’insectes, aux feux de faible intensité ou aux

chablis partiels (Dhital et al., 2013). Donc, avec la mise en place d’un nouveau

régime forestier mettant l’emphase sur l’aménagement écosystémique, on peut

anticiper une augmentation de l’utilisation de coupes telles que l’éclaircie

commerciale, la coupe avec protection des petites tiges marchandes (CPPTM), la

coupe de jardinage, la coupe progressive d’ensemencement (CPE) et la coupe

progressive irrégulière (OIFQ, 2009). Chacune de ces interventions répond à des

besoins spécifiques qui prennent en compte la composition forestière, le stade de

développement, la structure diamétrale et les objectifs d’aménagement. Concernant ce

dernier, il est parfois difficile de clairement déterminer si le traitement sylvicole

répond bien aux attentes formulées par les divers intervenants du milieu forestier.

2

Au Québec, la pérennité de la ressource est assurée grâce au calcul des possibilités

forestières. Ce calcul détermine le volume maximum pouvant être récolté à perpétuité

sans affecter la productivité forestière (Forestier en chef, 2015). Pour ce faire, on fait

évoluer les peuplements sur un horizon de 150 ans, en reproduisant un calcul à toutes

les périodes de 5 ans. Le niveau minimal de volume rencontré parmi les périodes

constituant cet horizon de 150 ans constitue le « niveau critique », ou le niveau

maximal de récolte pour ce même horizon. Or, l’éclaircie commerciale est effectuée

dans des peuplements qui n’ont pas encore atteint l’âge d’exploitabilité absolue. Le

volume récolté n’étant pas considéré comme exploitable lors de la simulation, il en

résulte qu’il est additionné à celui du niveau critique. Ce rehaussement du niveau

critique, communément nommé « effet de possibilité » permet de récolter davantage

de volume pendant tout l’horizon calcul. Il est certain que cette mécanique joue un

rôle plus qu’important dans la stratégie d’approvisionnement des usines du Québec,

ce qui laisse d’autant plus envisager une hausse de l’utilisation de ce traitement dans

un avenir rapproché.

L’éclaircie commerciale, dont l’utilisation devrait être de plus en plus répandue,

suscite pourtant encore plusieurs interrogations. Comme l’éclaircie peut entraîner une

augmentation de la vitesse de croissance radiale des arbres (Vincent et al., 2009;

Schneider et al. 2008) , il est possible que le traitement soit contre-indiqué pour la

production de bois de qualité à valeur accrue (Zhang, 1995). Or, plusieurs projets de

recherche ont déjà été effectués pour déterminer l’influence de ce traitement sur la

croissance des arbres (Vincent et al., 2009, 2011), sur les propriétés mécaniques

(Gagné et al., 2012) ou sur la valeur économique du bois (Vincent et al., 2011).

Toutefois, la communauté scientifique possède encore peu d’informations concernant

l’effet de ce traitement sur l’interaction entre ces divers paramètres. Comme ces

interactions se trouvent au premier plan de la rentabilité du processus de production

forestière, il importe de procéder à des analyses plus poussées afin de mettre en

lumière les divers mécanismes qui influencent à la fois les propriétés du bois et la

valeur économique des produits finis.

3

De plus, puisque chaque essence se distingue par une anatomie qui lui est propre,

elles peuvent conséquemment réagir de façon différente aux stimuli auxquels elles

sont confrontées. Face à ce constat, il importe d’acquérir les connaissances permettant

de qualifier et quantifier les interactions pouvant influencer la valeur économique du

bois, et ce, pour chacune des essences commerciales d’importance. Le présent

mémoire a pour objet d’évaluer l’impact de l’éclaircie commerciale sur la réaction de

croissance et sur divers paramètres déterminant la qualité du bois d’épinette noire,

soit l’espèce commerciale la plus importante au Québec. Plus précisément, l’étude

porte sur l’effet de ce traitement sylvicole sur la croissance radiale des arbres

résiduels, les propriétés mécaniques du bois et la valeur monétaire des produits de

transformation primaire du bois.

4

Chapitre 1 - Effect of commercial thinning on the quality

and value of primary processing products

1.1 Introduction

Canada’s forest industry has recently been facing economic difficulties attributable to

the low value of lumber on the North American markets (Random Length, 2011), in

conjunction with high harvesting, transport and processing costs (CSPAF, 2009). In

order to bring a long-term solution to this situation, forest management strategies are

now oriented towards the intensification of silvicultural scenarios. One approach is to

use silvicultural treatments to reduce the competition between trees and increase

radial growth rates (Bowyer et al., 2007). The objective is to produce bigger stems for

the same rotation age, a factor which was shown to have an important effect on

lumber production costs (Tong et al., 2005). In parallel, the introduction of

ecosystem-based management (Gauthier, 2008) requires increased consideration for

ecological factors in the application of silvicultural strategies. This may stimulate a

more frequent use of partial cuttings in the boreal forest (Grenon, 2010), which can

mimic to some extent the effects of low severity natural disturbances on the

ecosystem. Thus, the use of commercial thinning (CT) is likely to rise significantly in

future years, as it can help meet both of these forest management objectives.

CT provides greater light availability to residual trees, which can stimulate the crown

activity and in turn increase stem growth (Gagné et al., 2012; Vincent et al, 2009;

Zeide, 2001) and branch development (Grah, 1961). The increased stem size,

combined to an optimized sawing system, can significantly increase lumber and value

recovery (Auty et al., 2014). Indeed, for a given volume, larger lumber pieces provide

a higher market value (Random Length, 2011). Larger stems may also allow the

production of an increased proportion of pieces situated away from the pith and hence

out of the juvenile core.

Considering the fact that mature wood has better wood properties than juvenile wood

(Koubaa et al., 2000, Yang and Hazenberg, 1994), its proportion in lumber pieces is a

5

major determinant of bending stiffness, and therefore value (Larson, 2001). However,

lumber recovery can also be affected by stem taper, which increases with growth rate

(Larson, 1963). This factor reduces the log sawing yield (Barbour, 1992) and

attenuates the positive effect of a faster radial growth on tree value. Moreover, the

number and size of knots may affect the mechanical strength of the material (Bowyer,

2007; Aubry, 1998). For this reason, knot characteristics are among the main

parameters evaluated for the visual classification of lumber (ASTM D-245, 2005).

Because the value of lumber from the Canadian boreal forest is often attributed based

on this visual grading system, knots can have an important effect on value (Grah,

1961). Also, the radial growth of the stem responds directly or indirectly to crown

expansion (Lemieux et al., 2000). For this reason, growth rings in the lower part of

conifer stems are susceptible to contain an increased earlywood proportion after

thinning (Larson, 1963, 1969). Since earlywood cells are composed of thinner walls

and larger lumen than latewood (Koubba, 2000; Larson, 1963, 1969), thinning may

cause a decline in wood density, which could have a similar effect on mechanical

properties. However, Gagné (2012) studied wood density, modulus of elasticity

(MOE) and modulus of rupture (MOR) and found no significant difference between

control and thinned trees in a white spruce (Picea glauca (Moench) Voss) plantation.

In Canada, black spruce (Picea mariana (Mill.) BSP) dominated stands cover a large

forest strip from the east to the west coast of the country (Figure 1.1) (Gagnon and

Morin, 2001). The omnipresence of black spruce throughout Canada makes it one of

the most commercially important species in the country (Vincent et al., 2009).

Moreover, it is a major reforestation species in eastern Canada (Liu et al. 2007).

6

Figure 1.1 World’s black spruce distribution (Gagnon and Morin, 2001).

Yang and Hazenberg (1994) have shown that spacing influences growth rate in black

spruce plantations. In turn, they also showed that growth rate was associated with a

decrease of wood density in the juvenile core, but did not influence tracheid length

either in mature or juvenile wood. Zhang and Lei (2005) led a similar study and

found that initial spacing in a plantation had an effect on DBH, crown size, tree

height, stem volume, tree taper, branch diameter, and height of the live crown. They

concluded that narrow spacing yields higher quality stems, but at the expense of the

diameter growth. Alteyrac et al. (2005) measured ring density in old natural stands

that had never been altered by any silvicultural treatments. They found that the

natural variation in stand density caused a small difference of wood density within the

ring.

For a given spacing, tree behaviour may differ because the current spacing may origin

from progressive changes due to competition-induced mortality, or from a sudden

change such as that created by a thinning intervention. Tong et al. (2009) found that a

pre-commercial thinning of 35% of the stand affected density, lumber bending

properties and machine stress-rated (MSR) lumber yield in a black spruce plantation.

7

The juvenile wood proportion can partly explain these results, because it has a

negative effect on lumber bending stiffness and strength. Conversely to pre-

commercial thinning, trees subjected to CT have terminated their juvenile wood

production on almost the totality of the merchantable length of the stem, leading to a

lower juvenile wood production after treatment. Vincent et al. (2009, 2011) studied

CT and found a positive radial growth response, but no significant effects on ring

density and MOE. Furthermore, Tong et al. (2009) showed that the proportion of

No.2 and better (visually attributed) lumber grades were not significantly affected by

pre-commercial thinning and tree diameter. It is thus conceivable that, through an

increase in the radial growth of individual stems, thinning increases the volume of

valuable lumber at stand level.

Several researchers have also evaluated the costs and the benefits of irregular

shelterwood, selection cutting (Liu et al. 2007) and commercial thinning (Zundel and

Lebel. 1992) on black spruce stands. However, they did not investigate wood quality

and grading as important parameters. Considering the anticipated increase in the use

of CT, it is necessary to quantify its impact on the quality and value of wood

products. The main objective of this study was to verify if commercial thinning, when

applied to black spruce natural stands, has an effect (i) on the radial growth of

residual trees, (ii) on lumber mechanical properties, and (iii) on lumber value.

According to the studies cited above, the hypotheses assert that CT will increase the

radial growth rate of residual stems, which will contribute to increase lumber volume

without affecting visual grading and mechanical properties.

8

1.2 Material and methods

1.2.1 Experimental site

The study was conducted in a network of plots provided by the Ministère des forêts,

de la faune et des parcs (MFFP) in Quebec. Several replications of the same

experiment were established throughout the public forest of the province to monitor

the effects of the industrial application of CT as a silvicultural treatment. In a given

region, plots were disposed by pair, one located in the thinned area of the stand and

one in the control area. The thinned area corresponded to a whole stand characterized

by uniform composition, age and structure except for a control area of 100 x 100 m

within the center of which a circular control plot (400 m²) was established. Stands of

black spruce, pure or combined with jack pine, were chosen in three regions where

this species is widely harvested, namely Côte-Nord, Abitibi-Témiscamingue and Lac-

Saint-Jean (figure 1.2). Plot pairs were selected randomly among those that had the

desired composition. In the selected plots, pre-thinning basal area ranged from 26.0 to

43.4 m²/ha, pre-thinning age from 49 to 83 and a harvest proportion of all species

from 13.8 to 44.1% (table 1.1). This variation of harvest proportion is elevated, but it

has for advantage to represent the reality of industrial practices. CT treatments were

conducted from 1997 to 2000, i.e. 10 to 13 years prior to tree sampling.

9

Figure 1.2 Experimental sites of the study located thoughout Quebec (Google

Earth, 2015). The yellow pins were located in Abitibi-Temiscamingue, the orange

pins in Lac-Saint-Jean and the green pin in Côte-Nord. The number beside each pin

represents the number of plot pair because they were too close to distinguish them at

this scale.

(2)

(3) (2)

10

Table 1.1 Charasteristics of studied plots.

For the plots names, CN corresponds to the Côte-Nord region, LSJ to the Lac-Saint-Jean

region and AT to the Abitibi-Témiscamingue region. The pre-thinning basal area and the

portion harvested were missing in the MFFP’s database for plot AT2.

Plot Treatment Pre-thinning

basal area

(m²/Ha)

Pre-thinning

age

Portion

harvested (%

of basal area)

CN1 Control 33.7 55 0.0

CN2 Treated 42.6 50 37.3

CN3 Control 31.8 57 0.0

CN4 Treated 26.8 49 28.5

CN5 Control 35.9 59 0.0

CN6 Treated 38.9 51 15.3

LSJ1 Control 37.1 60 0.0

LSJ2 Treated 40.1 66 26.0

LSJ3 Control 36.8 58 0.0

LSJ4 Treated 43.4 60 44.1

LSJ5 Control 34.6 50 0.0

LSJ6 Treated 29.0 52 13.8

AT1 Control 26.8 55 0.0

AT2 Treated ¤ 58 ¤

AT3 Control 36.8 63 0.0

AT4 Treated 36.3 63 36.7

AT5 Control 31.1 83 0.0

AT6 Treated 26.0 69 36.3

1.2.2 Sampling

To get sufficient samples to run a reliable analysis, three pairs of plots per region

were selected. Then, four trees per plot were harvested and measured. In total, 72

trees were collected (3 regions X 6 plots/region X 4 trees/plot) during the summer of

2010, from June to August. For thinned areas, the tree selection method consisted of

going 30 meters away from the center of a chosen MFFP plot in the North direction

to establish a new variable-radius plot.

11

At this point, a factor 2 forest prism was used, and the first, third, fifth and seventh

trees identified as fitting within the variable-radius plot were selected. The use of the

prism always started in the North direction with a clockwise rotation. If the variable-

radius plot was positioned in an inappropriate place (e. g. a creek or a swamp), a new

position was chosen by going back to the MFFP plot and then turning by 90°

clockwise. For control areas (100 x 100 m), the tree selection was different. Trees

were harvested from the corners of control areas to avoid making an important gap in

the plot located in its center. The selections were made at a distance of 30 m from the

center of the MFFP control plot, in a straight line to the control area corner, which

was located at a distance of 40.7 m. This method was applied to all corners, for a

total of four trees collected per plot. For each one of these points, the tree was

selected again by using a forest prism, aiming first in the North direction and rotating

clockwise rotation until a tree fitted inside the plot radius.

After the diameter at breast height (DBH) was measured, sample trees were felled

using a chainsaw. Crown length, total height, the diameter of the five biggest

branches and stem diameter at a one-meter interval were all measured on the felled

trees. The total length of the stem, including the crown, was then sawn in 2.54 m long

logs for a total number of 201 logs, representing a mean of 2.8 merchantable logs per

tree. Because the log sawing was scheduled to be done in a lumber sawmill, each log

was identified by a unique combination of colors and stamps so that each lumber

piece could be traced back to its log and tree of origin after debarking and sawing.

The processing was conducted in a modern sawmill located in Quebec City, which in

addition to saw lines has on-site debarking, chipping, drying and planing facilities.

Sawmill parameters were set to aim for the highest financial yield for each log. A

total of 381 lumber pieces were produced, which gave the following numbers for

each nominal cross-section: 107 “2 x 3” in; 248 “2 x 4” in; 26 “2 x 6” in. All pieces

were dried and planed following normal industrial practices.

Tree volume was calculated from the diameter at stump height (DSH) up to the level

where the stem reached a diameter of 7 cm.

12

The calculation was made with the Smalian’s formula (equation 1.1) by using all

measured diameters at a one-meter interval.

𝑉 = [𝐴1 + 𝐴2

2∗ 𝐿1−2] + [

𝐴1 + 𝐴22

∗ 𝐿1−2]…+ [𝐴𝑛−1 + 𝐴𝑛

2∗ 𝐿(𝑛−1)−𝑛]

(1.1)

V: Tree volume (m³)

An-1: Area at diameter n-1 (m²);

An: Area at diameter n (m²);

Ln-(n+1): Longitudinal distance between diameters n-1 and n.

Then, lumber volume proportions obtained from each tree were determined. The

excess of volume was attributed to sawdust and chips. These two by-products were

separated by using an industry’s standard percentage of 8.9% allocated to sawdust,

and then, a chip proportion was established for each tree by subtracting the lumber

and sawdust volumes from the volume of the merchantable stem.

1.2.3 Material testing

Because the trees had been felled and cut into logs, the radial growth of the tree was

studied on a disc collected at stump height. In the laboratory, a measurement was

made in four perpendicular directions from the year of thinning to the year before

sampling, which was the last complete ring. Moreover, to add a covariate in the

model, radial growth was also measured for the same number of rings before

thinning, which represents nine to twelve rings.

The totality of the 381 lumber pieces produced was subjected to visual grading and

mechanical tests. The visual grading was made by a professional grader using the

rules of the National Lumber Grades Authority (NLGA). Each piece was classified on

the four faces and then graded considering the worst defects.

13

During this classification process, average lumber prices (see appendix A) for the

2002-to-2007 period were used to identify the financial priority between a lumber

piece downgraded by a defect situated at one extremity and the same lumber piece

form which the extremity was cross-cut, and was consequently upgraded. This was

done to avoid using exceptional prices from the exceptional market conditions that

followed the economic downturn of 2008. For chips, a market price of 42.1 $/m³ was

used, which corresponds to an average from the year 2013 (appendix B). The lumber

and chips amounts were added to calculate a total price per tree and a total price per

unit volume of round wood ($/m³) per tree.

MOE and MOR were calculated using full-size static bending tests for each piece of

wood. The methodology was prepared following the American Society for Testing

and Materials (ASTM) D-198 standard. Pieces were conditioned to a 12% moisture

content before the test. They were disposed on the edge side over the framework,

which was characterised by a fixed plate and a bearing plate for a vertical support.

During the bending test, the counter-loading side represents the highest point of

tension in the piece. Therefore, the edge side surface containing the fewer defects

faced downward to avoid premature rupture, or large variability, caused by the

defect’s positioning. The tested length was determined by span-depth ratio of 21

times, which represents 1.33 m for “2 x 3” in, 1.87 m for “2 x 4” in and 2.93 m for “2

x 6” in. The tests were run using a third-point loading, where two loads were equally

spaced at the one-third and the two-thirds of the span. A gauge was installed on the

neutral axis of the piece at midspan to measure the bending deflection. MOE and

MOR were calculated using equations 1.2 and 1.3 provided by ASTM.

14

𝑀𝑂𝐸 =23𝑃𝐿3

108𝑏ℎ3∆

(1.2)

𝑀𝑂𝑅 =𝑃𝑚𝑎𝑥𝐿

𝑏ℎ2

(1.3)

P: increment of applied load below proportional limit (N);

Pmax: maximum load borne by lumber loaded to failure, (N);

L: span of lumber, (mm);

b: width of lumber, (mm);

h: depth of lumber, (mm);

Δ: increment of deflection of lumber’s neutral axis measured at midspan over

distance L and corresponding load P, (mm).

1.2.4 Statistical analyses

Firstly, a linear mixed model was used to assess differences between treatments.

Region and treatment were considered as fixed effects and plot pairs (nested within

regions) as random effects (equation 1.4).

𝑦 = 𝑋𝛽 + 𝑍𝛾 + 𝜀

(1.4)

X: vector of model matrix for fixed-effects, composed by region and treatment;

β: vector of fixed-effects;

Z: vector of design matrix;

γ: vector of random-effects (plot pairs);

ε: vector of independent and identically distributed Gaussian random errors.

The dependent variables 𝑦 submitted to this analysis were: volume growth (mm³),

DBH (cm), value ($CAD) per tree, value per unit volume of round wood ($CAD/m3),

lumber and chip volume proportions (dimensionless), average diameter of the five

largest branches (cm), crown length (m), MOE (GPa) and MOR (MPa).

15

Secondly, an analysis was performed to evaluate the impact of commercial thinning

on the cross-sectional dimensions of the lumber pieces produced and on their visual

grades. In this case, the treatment was the only independent variable in the model. A

logistic regression was run using the R statistical programming environment (R core

team, 2013). A “logit” link (equation 1.5) (Crawley, 2007) was used to take into

account the categorical nature of the dependent variables:

𝑝 =𝑒𝑎+𝑏𝑥

1 + 𝑒𝑎+𝑏𝑥

(1.5)

p : Probability of obtaining a given cross section or a given grade

a+bx : Linear predicator for logit transformation of p;

a: Intercept;

b: Parameter of the model;

x: Independent variable (CT).

Thirdly, a regression analysis (equation 1.6) was used to assess differences between

thinned and control trees of a given DBH. The latter represents an important variable

that has a major influence on the quantity of products generated by a tree, and

therefore, on its monetary value. A linear modelling approach was used to

demonstrate the relationship between tree value ($CAD), lumber proportion, lumber

volume (m³) and value per unit volume of round wood ($CAD/m³).

𝛾 = 𝛽1DBH + 𝛽2 log(DBH) + 𝛽3

(1.6)

16

1.3 Results

1.3.1 Commercial thinning and region effects

For the 72 sample trees, DBH varied from 9.2 to 25.0 cm (Figure 1.3) with a mean of

14.2 cm the control plots, which was significantly lower (p = 0.001) than the average

of 16.7 cm in thinned plots. The p-values obtained in the ANOVA tests are presented

in Table 1.2. The region and the interaction between the region and the treatment did

not influence DBH (Region: p = 0.18; Region*treatment: p = 0.17). For radial

growth, region (p = 0.010) and treatment (p = 0.003) taken separately had significant

effects (Figure 1.4), but the interaction between region and treatment was not

significant (p = 0.61). The financial value of the sample trees ranged from 1.3 CAD$

to 35.6 CAD$ with a mean of 8.4 CAD$ and 13.3 CAD$, in control and thinned

stands, respectively. Similarly to DBH, tree value was positively affected by

commercial thinning (p = 0.001) (Figure 1.5), but not by other factors (Region: p =

0.27; Region*treatment: p = 0.41). Value per unit volume ranged from 47.7 to 97.3

with means of 79.0 CAD$/m³ for control trees and 79.2 CAD$/m³ for thinned trees.

The distribution of values is also rather similar for trees of both origins (Figure 1.6).

Value per volume unit was not significantly influenced by commercial thinning (p =

0.92), region (p = 0.06) or the interaction between these two factors (p = 0.79).

Branch variables were significantly altered by commercial thinning. The average for

the maximum branch diameter ranged from 1.00 to 4.48 cm with a mean of 2.02 cm

for control and 2.29 cm for thinned trees. This difference between control and thinned

trees was significant, as was the case of the interaction between treatment and region

(p = 0.031 and 0.049, respectively). Crown length ranged from 1.35 to 12.73 m with

means of 6.36 m in control and 7.66 m in thinned plots. The treatment and region had

significant effect on this variable (p = 0.011 and 0.020, respectively). The volumetric

proportions of lumber varied from 0.0 to 66.0%. This variable did not differ

significantly between treatments or regions.

17

Table 1.2 P-values obtained in the ANOVA tests.

Note that the number of 2X6 lumber pieces was insufficient to test for the effect of the

interaction between treatments and regions

Variables treat Region region*treat

Radial growth 0.003 0.010 0,61

DBH 0.001 0.18 0.17

Value 0.001 0.27 0.41

Value/m³ 0.92 0.06 0.79

Volume lumber prop. 0.74 0.08 0.79

Volume chip prop. 0.82 0.09 0.86

Max Branch diameter 0.031 0.68 0.049

Crown length 0.011 0.020 0.43

MOE 2x3 0.57 0.90 0.42

2x4 0.08 0.24 0.19

2x6 0.34 0.23 NA

MOR 2x3 0.12 0.35 0.25

2x4 0.07 0.30 0.36

2x6 0.66 0.87 NA

18

Figure 1.3 Boxplots of the observed values of DBH. The rectangular boxes show the first,

second (median) and third quartiles; the extremity of each vertical line represents the

minimum and maximum observed values. The difference between the thinned and control

plots was significant (p < 0.001).

Figure 1.4 Growth for a same duration period before and after thinning. The difference

between the thinned and control plots was significant with p = 0.003.

5,0

10,0

15,0

20,0

25,0

Control Thinned

DB

H (

cm)

6,00

7,00

8,00

9,00

10,00

11,00

12,00

Before thinning After thinning

10

-ye

ar r

adia

l in

cre

me

nt

(mm

)

Control

Treated

Linear (Control)

Linear (Treated)

19

Figure 1.5 Boxplots of the value (CAD$) per tree. The difference between the thinned and

control plots was significant with p < 0.001.

Figure 1.6 Boxplots of the value ($) per cubic meter of round wood. The difference

between the thinned and control plots was non-significant (p = 0.89).

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

Control Thinned

Valu

e p

er t

ree

(CA

D $

)

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Control Thinned

Va

lue

per

vo

lum

e u

nit

(C

AD

$/m

³)

20

For the 381 lumber pieces produced, the MOE ranged from 4.6 Gpa to 27.9 Gpa and

the corresponding values for MOR were from 11.9 Mpa to 100.0 Mpa. These

variations were very high partly because lumber cross section is related to MOE (p =

0.007) and MOR (p < 0.001). Therefore, separate analyses were made for each

lumber cross section categories (Figures 1.7 and 1.8). For each case, treatment, region

and the interaction between the two were non-significant (p = 0.08 to 0.90 for MOE;

p = 0.07 to 0.87 for MOR) (Table 1.2).

Figure 1.7 Boxplots of the MOE of lumber pieces of different dimensions. None of the

differences between thinned and control stands were significant (p > 0.05).

0,0

5,0

10,0

15,0

20,0

25,0

30,0

MO

E (

Gp

a)

21

Figure 1.8 Boxplots of the MOE for lumber pieces of different dimensions. None of the

differences between thinned and control stands were significant (p > 0.05).

Figure 1.9 Quantity of lumber feet in each grade for each treatment.

0,0

20,0

40,0

60,0

80,0

100,0

MO

R (

Mp

a)

0,0

50,0

100,0

150,0

200,0

250,0

300,0

350,0

400,0

450,0

500,0

Premium No.1 No.2 No.3 Economy

Bo

ard

fe

et

Quantity of board feet per grade

Thinned

Control

22

The logistic regression confirmed, however, that commercial thinning is playing a

role in the distribution of lumber dimensions. The respective proportions of “2X3”

lumber and the group of “2X4” and 2X6” lumber pieces differed between treatments

(p = 0.028, Table 1.3). For grades, no significant differences were identified from the

logistic regression (p = 0.50), which means that CT cannot explain the possible

variations between grades (Figure 1.9).

Table 1.3 p-values obtained in the logistic regression tests for the sizes and grades of lumber

pieces.

Variables intercept treatment

Size vs treatment 0.06 0.028

Grade vs treatment <0.001 0.50

1.3.2 DBH effect

Results show that DBH is significantly related to all variables that represent the

financial value of standing trees (Table 1.4, Figure 1.10). The shapes of relationships

between DBH and each indicator of financial value are shown in Figure 1.10. DBH

was also significantly related to the size and grade variables (Table 1.5).

Table 1.4 Parameters of the relationships between DBH and value indicators.

Variables Intercept(β3) DBH(β1) log(DBH)(β2)

log(Value) -8.87 -0.12 4.74

log(Value/m³) 1.00 -0.10 1.81

log(Lumber volume prop.) -4.04 -0.24 4.27

log(Lumber volume tree) -18.51 -0.26 7.21

23

Table 1.5 p-values obtained in the logistic regression tests when considering DBH as a

determining factor.

Variables Intercept DBH log(DBH)

Size 0.001 0.022 0.002

Grade 0.51 0.003 NA

Figure 1.10 The DBH quartiles distribution and the effect of DHB on the financial value

indicators. Triangles represent control trees and circles represent thinned trees. Only one

model has been developed for the regression analysis. However, the figure highlights the

DBH median of each treatment to highlight the impact of stem size on financial value.

24

1.4 Discussion

In line with what has long been known from the literature (Larson, 1969; Grah,

1961), commercial thinning led to an expansion of the crown and an increase in

branch size, most likely as a result of the greater light availability. Also, the

regression analysis indicated that even if the treatment influenced both the size of

knots on the logs and stem diameter, neither the treatment nor the DBH had a

significant effect on the visual grading. Since the trees had already reached a

commercial diameter before the treatment was applied, the quantity of wood affected

by the large-sized branches was probably not sufficient to influence the grading

significantly. Otherwise, increased knot size may be a cause of downgrade (Lemieux

et al., 2002). The tree selection from each treatment can induce a bias on branch

variables. It is possible that the residual trees after CT had greater radial diameter and

branches diameter than those in control stands. A further analysis might be required

to analyze the treatment effect on the size of knots for a given DBH.

The effect of thinning on growth rate is well known and positive results have been

widely observed (Larson 1963, 1969; Tong et al. 2009; Vincent et al. 2009, 2011).

As the crown and the light availability increased, the photosynthesis activity was

amplified, which caused an acceleration of the radial growth. This sequence of events

is in accordance with the fact that treatment was significantly related to the radial

growth of the stem, branch size and DBH. Indeed, these tree characteristics appear to

have responded to the same factor, namely the increment of light following treatment.

Radial growth and crown length were significantly affected by the different sampling

regions. In both cases, the Lac-St-Jean region was associated with higher values,

followed by the Abitibi-Témiscamingue region and finally the Côte-Nord region.

25

In addition, the interaction between treatments and regions had significantly affected

the maximum branch diameter with the following descending order: Lac-St-Jean,

Côte-Nord and Abitibi-Témiscamingue. These differences were likely related to

differences in climate and soil fertility between regions, but have not been analyzed

extensively as it was beyond the scope of the present study. Moreover, branches were

larger in trees from treated plots in Lac-St-Jean region and in Abitibi-Témiscamingue

region. In the Côte-Nord region, the branches were larger in trees from controls plots.

This may also be explained by the selection of trees from the intermediate canopy

position.

As mentioned previously, the treatment affected both the growth rate and DBH of our

sample trees. However, the DBH increment is much larger than the measured radial

growth response to the thinning treatment. As shown in Figure 1.3, the DBH was on

average 2.55 cm higher in thinned plots, whereas in Figure 1.4, the radius growth was

only 2.2 mm higher in thinned plots. This implies that out of the 2.55 cm in DBH,

only 0.44 cm is attributable to the difference in radial growth, which represents

17.1% of the DBH increment. The remaining 82.9% missing can be explained by a

bias related to our stem selection method during the sampling. In treated plots, the

selected trees were almost always in dominant and codominant positions because the

thinning from below had removed several of the stems in supressed and intermediate

positions. In control plots, more trees from intermediate positions were present, and

thus selected as part of the sample. These trees tended to decrease the DBH average

for control plots. Caution must hence be used when interpreting the effect of the

treatment on DBH, which in turn was related to mechanical properties and other

wood quality indicators.

At the tree level, our analyses confirmed that DBH is a determining variable to

explain the variation of the value of standing trees. When included as a covariate in

the analyses, it neutralized the treatment effect and was even related to some

variables on which the thinning treatment did not have a significant effect. The

volume of lumber produced per tree was in the first category.

26

When figuring in separate models, both treatment and DBH affected this variable, but

when they were considered together, only DBH had an effect. In this case,

commercial thinning affected the DBH, which was in turn closely related to the

lumber volume. However, the situation was different for the proportions variables, on

which only DBH had an effect. The cause of these differences comes from the stem

form. Indeed, as mentioned by Larson (1963), growth rate induced a log taper

increment, and thus a decrease in yield. It follows that DBH also had an effect on the

size of lumber products. As observed in the result of the logistic regression, DBH had

an effect on the product basket of lumber sizes and grades, with both variables

increasing gradually from small to larger diameters. For grades, a larger DBH helps

avoid presence of wane on lumber pieces, which was the main cause of downgrading

in this study. Moreover, lumber size was affected by treatment as well, but not

grades. Therefore, lumber pieces from thinned stands had a similar lumber quality to

that of the control, but with larger cross sections on average. These two results are

then contributing to increase the value of standing trees.

MOE and MOR were not affected by treatment. This suggests that lumber from

commercial thinning will produce the same MSR grades than those from an

unmanaged forest. This is further supported by the fact that visual grading was not

influenced by treatment. In fact, the analysis of grading tends to demonstrate that the

amount of defects remained stable, which also signifies that there was not a

significant increase in the occurrence of weakness points in lumber pieces. However,

it remains possible that the wood produced after treatment contained weaker cellular

structures than those produced in control stands. Schneider et al. (2008) conducted

MOE and MOR tests on small wood specimens. They found a significant effect of

CT on these properties. However, in the present study, 10 to 13 years after CT, the

proportion of wood in growth rings formed after thinning within each full-size piece

was probably not enough to affect MOE and MOR.

27

Commercial thinning can increase the financial value of trees through many different

ways. Indeed, the results of the ANOVA demonstrated that the treatment influenced

the economic value of products, but did not alter the MOE or the MOR. Obtaining

wood of equal quality, combined to an increase in the quantity of wood products, led

to an increased value of standing trees. Further confirmation of the potentially

positive effect of CT on tree value came from the analysis of the lumber proportion

for each tree showing an increase with DBH. Logistic regression also demonstrated

that the proportion of large, valuable lumber pieces increased following CT.

Therefore, it is possible to state that in this experiment that CT allowed an upgrade

both in the quantity and quality of primary processing products contained in a given

tree. However, the absence of a significant difference in the value of lumber per unit

of round wood suggests that, on an area basis, there should be little difference

between the summed values of primary products harvested from the final cut of a

thinned or unthinned stand. Indeed, earlier results have shown that commercial

thinning has little effect on the volume of roundwood produced on a given area of

land (Bédard et al., 2003). In terms of economic value, the advantage of CT might

therefore not come from an increase of lumber value per hectare, but rather from the

decreased harvesting, transport and processing costs of larger stems (Soucy, 2011),

combined with the absence of a detrimental effect on wood quality. However, the cost

of the first harvest needs to be taken into account in the calculation to determine if

there is a real economic benefit associated with this treatment.

From Figure 1.10, it can be seen that the value per tree closely follows the pattern of

variation of lumber volume, and that the value per unit volume is very closely

associated to the lumber proportion per tree. Both the lumber proportion and value

per unit volume were unaffected by the treatment. Lumber proportion first increased

with DBH to reach an optimum and then decline slightly. This tendency can be

explained by the log taper that gives the stem a conical shape instead of a cylindrical

one, the additional volume permits the production of more lumber pieces in total, but

in a lower proportion of the round wood volume.

28

1.5 Conclusion

This study demonstrated that the use of commercial thinning as a silvicultural

strategy allows an increase of the radial growth of residual trees, which was not

associated with a significant reduction of the visual or mechanical properties of

lumber. Therefore, CT had a direct impact on the economic value of residual trees,

without diminishing their quality. The analyses indicated that DBH itself is a major

driver of wood value, even when assessed on the basis of a unit volume of round

wood. Although CT did not have a direct effect on this variable, the analyses showed

that the value per unit volume increased sharply between trees of approximately 10 to

18 cm of DBH.

Further studies will be necessary to assess the overall economic impact of CT. These

should include integrating the cost and revenues generated at the application of the

treatment and the harvesting and processing costs at the final harvest. Studies with

longer time periods after treatment should also contribute to improve our knowledge,

and therefore the use of this treatment. The present study was part of a wider research

project that aimed to characterize the overall cost-effectiveness of commercial

thinning in the Eastern boreal forest of Canada.

29

Conclusion générale

Les résultats obtenus dans le cadre de cette étude permettent d’affirmer que l’éclaircie

commerciale répond bien aux attentes que les aménagistes peuvent avoir lors de

l’application d’un tel traitement. En effet, l’apport additionnel de lumière disponible

aux arbres résiduels à la suite de l’éclaircie a permis aux tiges de connaître une

augmentation de leur accroissement radial, permettant ainsi une augmentation du

volume de produits transformés. De plus, la qualité des produits générés par les

arbres éclaircis n’était pas significativement différente de celle des arbres témoins. La

valorisation des arbres résiduels semble donc atteindre exactement l’effet recherché

par la mise en place d’un tel traitement. En effets, l’éclaircie a permis d’augmenter la

quantité de sciage contenu dans les arbres sur pied sans en affecter la qualité, ce qui

cadre avec les objectifs fondamentaux du traitement. Ces éléments s’avèrent d’autant

plus intéressants quand on considère l’utilisation de l’éclaircie commerciale comme

outil apportant un effet positif à la possibilité forestière par le biais de la récolte

devancée (éclaircie) ou reportée (coupe finale) à la période critique. Il est donc

possible d’avancer que l’utilisation de l’éclaircie commerciale permet de concilier

divers objectifs provenant des différentes sphères sociales ou industrielles. Ce

traitement pourra à la fois être utilisé dans les scénarios d’aménagement

écoystémiques ainsi que dans les stratégies d’aménagement intensif.

En considérant l’ensemble de ces informations, l’utilisation de l’éclaircie

commerciale apparaît un choix judicieux dans le contexte forestier québécois actuel.

De part sa valorisation des arbres et de son effet potentiel sur la possibilité forestière

ou sur le maintien d’attributs de forêts mûres, elle permet de jouer un rôle

déterminant dans la recherche de solutions face aux enjeux soulevés pas la mise en

œuvre de l’aménagement écosystémique. Pour l’industrie, son application pourrait

permettre de dégager un volume supplémentaire et ainsi d’assurer la continuité des

activités de transformation , surtout pendant le dégel des routes, un moment de fin de

période où les cours à bois se doivent d’être remplies.

30

Comme mentionné plus haut, le présent projet constitue un volet d’un projet d’une

plus grande envergure portant sur l’éclaircie commerciale. Un deuxième volet,

toujours en cours à ce jour, a pour objectif de déterminer la rentabilité du traitement

(Voudouhe, et al., 2015). Ce projet a démontré toutefois qu’une durée de 10 à 13 ans

entre l’éclaircie et la coupe finale ne permettait pas de rentabiliser le traitement.

Malgré une augmentation de valeur des arbres sur pieds, ceux-ci ne suffisent pas à

surpasser les coûts générés par l’éclaircie avant la coupe finale. Des travaux futurs

pourraient tenter de déterminer les facteurs permettant ou non de compenser pour les

coûts associés à l’éclaircie commerciale. Il est possible que des éclaircies menées plus

tôt dans la vie du peuplement donnent de meilleurs résultats puisque les arbres

résiduels devraient avoir une meilleure capacité de réaction au traitement. Afin de

limiter les pertes et de stimuler une réaction de croissance plus forte, l’éclaircie

pourrait aussi cibler les plus grosses tiges du peuplement. En effet, une éclaircie par

le bas telle que celle effectuée dans notre dispositif expérimental a tendance à retirer

des arbres en sous-étage dont la présence n’a que peu d’impact sur la croissance des

dominants. En se fiant aux résultats de notre étude, même une réaction de croissance

plus forte ne devrait pas avoir de conséquences très néfastes sur la qualité des bois

transformés. Même si on peut entrevoir que les enjeux reliés à l’aménagement

écosystémique et au maintien de la possibilité forestière seront les facteurs

prépondérants dans l’essor de l’éclaircie commerciale au Québec, il demeurera

important d’identifier quels scénarios sylvicoles permettraient de maximiser les

profits générés à l’échelle du peuplement.

31

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34

Annexes

Annexe A – Economic value of 1000 a thousand board feet. Price for the Montreal market.

Those prices were used to optimize considering a downgrade caused by a defect at the end of

the lumbers or a grade keeping, but with a shorter lumber. Board dimensions Value/quality ($/1000 board feet)

Depth X width (in.) Lenght (ft) Premium No. 2 No. 3 Economy

2x3 4 - 225 210 200

2x3 5 - 225 210 200

2x3 6 422 294 220 200

2x3 7 422 288 220 200

2x3 8 422 317 240 200

2x3 9 422 317 240 200

2x3 10 422 309 240 200

2x3 12 422 341 265 197

2x3 14 422 356 280 211

2x3 16 422 382 306 237

2x4 4 - 250 240 232

2x4 5 - 250 240 232

2x4 6 417 295 280 232

2x4 7 417 302 280 232

2x4 8 417 367 309 232

2x4 9 417 391 309 232

2x4 10 417 380 309 232

2x4 12 417 369 294 225

2x4 14 417 381 306 237

2x4 16 417 404 328 260

2x6 4 - 340 267 226

2x6 5 - 340 267 226

2x6 6 436 340 267 226

2x6 7 436 340 267 226

2x6 8 436 393 267 226

2x6 9 436 398 267 226

2x6 10 436 395 267 226

2x6 12 436 372 259 218

2x6 14 436 346 233 193

2x6 16 436 396 284 243

2x8 10 436 377 264 193

2x8 12 436 377 264 193

2x8 14 436 377 264 193

2x8 16 436 377 264 193

35

Annexe B – Chips pricing for the year 2013. Transformed in cubic meter from oven dry

metric tons (Random length, 2013).

Year Trimester Chip value ($/ODMT)

Average ($/ODMT) Chip value ($/m³) Average ($/m³)

2013

Q1 110.0

106.5

43.5

42.1 Q2 107.0 42.3

Q3 105.0 41.5

Q4 104.0 41.1