ORIGINAL PAPER

Variations in the radial growth and wood density componentsin relation to cambial age in 30-year-old Pinus brutiaTen. at two test sites

Bilgin Guller • Kani Isik • Senay Cetinay

Received: 29 October 2011 / Revised: 19 December 2011 / Accepted: 23 December 2011

� Springer-Verlag 2012

Abstract Radial growth and wood density are important

traits in assessing wood quality. Our objective was to

investigate patterns of variation of radial growth (ring

width, earlywood width, latewood width, latewood

proportion) and wood density (ring average density, ear-

lywood density, latewood density) components in a

30-year-old Pinus brutia at two test sites in Turkey. Wood

increment cores at a height of 1.30 cm (dbh) from 1,010

trees at age 30 years were evaluated at two test sites. The

radial growth and wood density traits of the individual

rings were measured using X-ray densitometry. The test

sites showed statistically significant differences in the

radial growth traits but not in the wood density traits,

suggesting that the wood density traits are less subject to

environmental changes. The ring average density was rel-

atively low (485 kg/m3) at early cambial ages (near the

pith) and increased to 501 kg/m3 at later cambial ages (near

the bark). The latewood density was 550 kg/m3 near the

pith, increased steadily to 630 kg/m3 at cambial age 12,

and remained stable thereafter. In contrast, the earlywood

density and latewood proportion were highest near the pith.

The twelfth ring from the pith appeared to represent the

transition from juvenile to mature wood. The unique rela-

tionships among early and latewood densities and latewood

proportion in the juvenile and mature wood contribute to

more uniform wood both within a given annual ring and

between the juvenile and mature portions of the stem in

P. brutia. Thinning increased the ring width, latewood

proportion, and ring average density.

Keywords Pinus brutia Ten. � Cambial age �Radial growth � Wood density � Juvenile wood �Mature wood � Thinning

Introduction

Pinus brutia is naturally distributed in the eastern Medi-

terranean region, including Turkey, Greece, Cyprus, Syria,

Israel, Palestine, Jordan, and Iraq (Boydak 2004). The

species has been given high priority in plantation forestry

in various countries with Mediterranean climates due to its

relatively fast growth rate and wide ecological adaptability

(Palmberg 1975; Fisher et al. 1986; Weinstein 1989).

P. brutia has a wide geographic distribution in area (more

than 5,500,000 ha forest land in eastern Mediterranean

region) and altitudinal range, from sea level up to 1,400 m

(asl), and is an important source of forest products in the

region (Erkan 1998; Guller 2007). Radial and axial varia-

tions in wood density and its relationships with annual ring

components (earlywood density, latewood density, and

latewood percentage) are essential in assessing wood

quality (Zobel and Sprague 1998; Savva et al. 2010). These

traits are important for establishing the quality of pulp,

paper, and sawn timber. They are also used to determine

the transition age from juvenile to mature wood in forest

tree species (Tassisa and Burkhart 1997; Lindstrom 2002).

Communicated by T. Fourcaud.

B. Guller

Department of Forest Products Engineering, Faculty of Forestry,

Suleyman Demirel University, Isparta, Turkey

K. Isik (&)

Department of Biology, Faculty of Sciences,

Akdeniz University, Antalya, Turkey

e-mail: kani@akdeniz.edu.tr

S. Cetinay

Southwest Anatolia Forest Research Institute,

Antalya, Turkey

123

Trees

DOI 10.1007/s00468-011-0675-2

A1

The portion of wood initiated near the pith at any height

within a tree is called juvenile wood (JW). Mature wood

(MW) is subsequently produced as the tree ages. Several

physical properties (such as annual ring width, ring density,

fiber length, cell wall thickness, and micro-fibril angle) and

mechanical properties may differ between JW and MW

(Zobel and Sprague 1998; Alteyrac et al. 2006). Wood

density, a relatively easy trait to measure, is generally used

to distinguish the JW-MW boundary.

To our knowledge, information on wood density and

annual ring components are limited for P. brutia. Adam-

opoulos et al. (2009) studied the ring width, latewood

proportion, and dry density of 16 dominant P. brutia trees

randomly chosen from two reforestation sites in North-

eastern Greece. Two different methods for measuring the

general wood density properties of P. brutia have been

published (Guller 2010; Guller and Yasar 2010). However,

there are no reports concerning the transition ages from

juvenile wood to mature wood in the species. Moreover,

additional information on radial growth and annual ring

properties based on higher number of trees from the opti-

mum distribution range of the species are needed.

The purpose of this study was to investigate the radial

variation of wood density and annual ring components in

P. brutia. The specific objectives were to (i) investigate

patterns of radial growth components (ring width, early-

wood width, latewood width, and latewood proportion), (ii)

determine the radial variation in wood density properties

(ring average density, earlywood density, and latewood

density) from pith to bark within trees, (iii) determine

possible transition ages from juvenile to mature wood,

(iv) examine the effects of test site on wood density and

radial growth traits by comparing trees of the same age

and similar seed sources planted at two test sites, and

(v) examine the effects of thinning on the overall wood

density and radial growth components.

Materials and methods

Plant material and experimental sites

The wood samples evaluated in this study were collected

from 30-year-old trees planted in 1979 at two provenance

test sites, Duzlercami (Dg) and Kepez (Kp) near Antalya

City in southwestern Turkey (Table 1). The trees sampled at

each test site represent six natural populations originating

from different elevations ranging from 60 to 1,050 m asl in

the Taurus Mountains along the Mediterranean Coast (Isik

1986; Isik et al. 2002). The experimental design at the test

sites was single-tree plots in a randomized complete block

with three interlocked replications, which allowed thinning

as the trees aged (Libby and Cockerham 1980; Isik 1988).

Initially, except for the border trees, 1,800 trees were planted

at each test site in 2.00 m 9 2.00 m distance in hexagonal

arrangement. The understory vegetation was cleared manu-

ally at the test sites every 2–5 years (more often in early

years) until crown closure. Two thinnings were applied at

each test site prior to wood sampling [first and second thin-

nings were performed at ages 13 (in Jan., 1991) and 17 (in

Feb., 1995) at Dg, and at ages 17 (in Feb., 1995) and 28 (in

May, 2007) at Kp, respectively]. After the second thinning,

distances between trees were 3.46 m 9 3.46 m in hexagonal

surroundings. The Duzlercami (Dg) site had a higher site

index and growth rate than the Kepez (Kp) site (Table 1).

Collection, care, and preparation of wood samples

In August 2007, one increment core (12 mm thick) per tree

was collected at breast height (1.3 m) in the north–south

direction from bark to bark, intersecting the pith. The trees

were 30 years in age from seed (29 growing seasons in the

field) at the time of sampling. The diameter at breast height

(dbh) for each tree was also measured. In total, 1,080 wood

cores were collected from the two test sites with a minimum

of six cores collected per family at each site. Immediately

after removal, the increment core was stored in a cooler bag,

subsequently vacuum-sealed in plastic bags, and stored at

?2�C. For evaluation, the cores were divided into two radii

and dried at room temperature. The radii of each core were

glued to core holders (poplar strips) and 2-mm thick radial

strips were cut. At the end of sample preparation process, a

total of 1,024 clear samples were obtained.

Variables (traits) studied

The primary wood properties used in this study were

components of annual ring width (radial growth) and

annual ring density. These traits were abbreviated and

defined as follows:

• WRW: whole annual ring width (width of an entire

annual ring, mm);

• EWW: earlywood width (width of earlywood portion of

an annual ring, mm);

• LWW: latewood width (width of latewood portion of

an annual ring, mm);

• LWP: latewood proportion (proportion of an annual

ring that is latewood, %);

• RAD: ring average density (mean density of a whole

annual ring, kg/m3);

• RWD: ring area weighted density (calculated by weight-

ing average ring density with ring area which was

computed assuming a circular shape of a stem, kg/m3);

• EWD: earlywood density (density of earlywood portion

of an annual ring, kg/m3);

Trees

123

A1

• LWD: latewood density (density of latewood portion of

an annual ring, kg/m3).

Measurement of radial growth and wood density

components

Annual ring widths and densities were determined using

X-ray densitometry. A fixed threshold density of 450 kg/m3

was used to set the boundary between earlywood and late-

wood within a ring (Guller 2010). The radial strips were

conditioned to 8% equilibrium moisture content and scanned

using an X-ray densitometer (Quintek Measurement Sys-

tems, Model QTRS-01X) integrated with a computer digital

analysis system. The first annual rings next to the bark of

each sample were not evaluated because they were usually

incomplete or damaged during bark removal.

The X-ray attenuation, measured by the densitometer,

was related to the density by ll = lm 9 q, where ll is the

measured attenuation of the X-ray beam passed through the

sample, lm is the sample mass attenuation coefficient, and

q is the density.

Therefore, the density calculation required knowledge

of the mass attenuation coefficient (cm2/g) of the wood.

The calibration to the appropriate mass attenuation coef-

ficient was conducted using a set of 35 radial strips from

cores with densities previously determined using the

maximum moisture content method (Smith 1954). The 35

mass attenuation coefficients were averaged to provide the

final value used to calculate the wood density.

Statistical analyses

After excluding the cores with extreme readings, a total

of 1,010 trees (1 core per tree) were used for the final

statistical evaluation from the two test sites (Table 2). The

number of rings for each core (each tree) ranged from 10 to

26 depending on the growth rate and age attained at breast

height. Cambial age 1 (i.e., ring number 1) at the pith was

not included in the analysis because of irregularities in the

X-ray readings. Similarly, ring numbers 23, 24, 25, and 26

were not included in the final evaluation due to relatively

low sample sizes (B140) or uneven representation at the

two test sites. Thus, the data used in the final analysis

included cambial age 2 (i.e., ring number 2, the closest ring

to the pith, with sample size n2 = 948) through cambial

age 22 (ring number 22, the closest ring to the bark, with

sample size n22 = 289).

The means and coefficient of variation (CV) for each

trait were calculated for each test site and cambial age. The

CV was a measure of variability for a given character. A

character with a low CV value was less variable (more

stable and uniform) across ring numbers and sites. The

mean values and CVs of the traits were plotted against the

ring numbers from pith to bark (referred to as cambial age

profiles). The ages of the transition from juvenile to mature

wood were determined by visual interpretation of cambial

age profiles of ring density traits.

Analysis of variance (ANOVA) was used to statistically

compare test sites for all traits studied. For the ANOVA

test of dbh, we used the following model:

Yij ¼ lþ Si þ eij; ð1Þ

where Yij is the dbh of the jth tree at the ith site; l is the

overall mean; Si is the effect of ith site (i = 1, 2) with

variance r2Si

; eij is the residuals with variance r2eij

.

For the ANOVA test of ring traits (whole ring width,

earlywood width, latewood width, latewood propor-

tion, ring average density, earlywood density, latewood

Table 1 Description of the two test sites and sampled trees for wood study in Pinus brutia

Attribute Test sites

Kepez, Kpa Duzlercami, Dga

Elevation (m, asl) 90 350

Latitude 36�5500000N 36�5802700N

Longitude 30�3605400E 30�3205600E

Size of the test site 0.78 ha 0.78 ha

Site indexb 13.7 19.8

Mean rainfall (mm)

(May; Aug.; Dec.; annual)c 30.7; 2.0; 261.3; 1,052.3 30.7; 2.0; 261.3; 1,052.3

Total trees evaluated 506 504

Number of rings evaluated per site per trait At least 9,248 At least 9,168

a The subscripts g and p were adopted in the article to easily distinguish the relatively good (g) site Dg from the relatively poor (p) site, Kpb Based on top height at age 25 (Usta 1991)c Climatic data from the nearest meteorological station [Antalya airport, 53 m asl; approximately 17 km (to Kp) and 25 km (to Dg), bird’s-eye

view]

Trees

123

A1

density), we compared test sites and cambial ages with

similar ring numbers [for example, a given trait of cam-

bial age 2 (ring no 2) at site Kp was compared with the

corresponding cambial age trait at site Dg]. The model

was as follows:

Yijk ¼ lþ Si þ RjðiÞ þ eijk; ð2Þ

where Yijk is the kth observation in the jth ring (jth cambial

age) at the ith site; l is the overall mean; Si is the effect of

ith site (i = 1, 2); Rj(i) is the effect of jth cambial age

within the ith site (j = 1…21, i.e., ring numbers 2 through

22); and eijk is the residuals.

We assumed that the site effects were fixed and the

cambial ages (ring numbers) were nested within sites. The

variance components [r2Si

, variances due to sites; r2RjðiÞ

due

to cambial ages within sites, r2eijk

due to residuals] for each

ring trait were estimated using the restricted maximum

likelihood (REML) method of PROC VARCOMP (SAS

Institute 1990).

We also performed ANOVA tests to compare the overall

(sites pooled) and individual juvenile and mature wood

within each test site. In addition, we compared the juvenile

wood (JW) in Kp with JW in Dg and mature wood (MW)

in Kp with MW at Dg. In all the three comparisons, the

model was as follows:

Yij ¼ lþMi þ eij; ð3Þ

where Yij is the value of the jth ring at the ith maturity

level; l is the overall mean (or, l is the site mean in the

case of within-site comparisons); Mi is the effect of ith

maturity level (i.e., juvenile or mature, i = 1, 2) (or, for the

third comparison JW at Kp vs. JW at Dg, and MW at Kp

vs. MW at Dg).

Results

Overall characterization in Pinus brutia

Overall, the mean diameter at breast height (dbh) of

30-year-old P. brutia trees from the two test sites was

161.1 mm (Table 2). The overall mean for the whole ring

width (WRW) was 2.93 mm, with relatively high vari-

ability (CV = 55%). The overall mean for early wood

width (EWW) was 1.58 mm and for latewood width

(LWW) was 1.38 mm. Latewood proportion (LWP) aver-

aged 46.9% and was less variable (CV = 31%) than dbh

and ring width characters.

The overall mean for the ring average density (RAD)

of breast height samples from the two test sites was

495.45 kg/m3. The mean latewood density (LWD) of

619.78 kg/m3 was approximately 60% larger than the mean

earlywood density (EWD) of 388.14 kg/m3. The ring

density components (EWD, LWD, and RAD) had mark-

edly lower variability than the ring width components

(EWW, LWW, and WRW) (Fig. 1). The variability of

LWP was in between these two groups.

Because of the strong relationship observed between the

RAD and the ring area weighted density (RWD) on an

individual core basis (r = 0.92, p \ 0.0001, n = 1,010),

we only used the ring average density (RAD) trait in our

subsequent analyses.

Relation of ring width (radial growth)

and its components to cambial age

The WRW was highest at cambial ages 2 and 3 (3.8 mm at

Kp, and 5.3 mm at Dg) (Fig. 2a). The ring width (radial

growth) subsequently declined gradually until cambial age 8

Table 2 The dbh, ring width and wood density statistics of Pinus brutia

Traitsa Overall species Kepez site, Kp Duzlercami site, Dg

Nb Mean ± SDc Nb Mean ± SDc Nb Mean ± SDc

dbh (mm) 1,010 161.1 ± 60.70 506 124.70 ± 29.63 504 197.64 ± 61.89

WRW (mm) 18,833 2.93 ± 1.63 9,523 2.18 ± 1.16 9,310 3.70 ± 1.68

EWW (mm) 18,423 1.58 ± 0.95 9,248 1.18 ± 0.74 9,175 1.99 ± 0.97

LWW (mm) 18,832 1.38 ± 0.93 9,530 1.02 ± 0.60 9,302 1.74 ± 1.06

LWP (%) 18,590 46.93 ± 14.57 9,422 47.73 ± 15.19 9,168 46.10 ± 13.86

RAD (kg/m3) 18,959 495.45 ± 44.99 9,632 496.20 ± 46.32 9,327 494.69 ± 43.55

EWD (kg/m3) 18,633 388.14 ± 24.15 9,439 389.42 ± 23.18 9,194 386.82 ± 25.05

LWD (kg/m3) 18,924 619.78 ± 55.40 9,611 614.74 ± 53.23 9,313 624.99 ± 57.10

a dbh Diameter at breast height, WRW whole ring width, EWW earlywood width, LWW latewood width, LWP latewood proportion, RAD ring

average density, EWD earlywood density, LWD latewood densityb Number of observationsc SD standard deviation

Trees

123

A1

and remained approximately at 2.0 mm at Kp and at 3.5 mm

at Dg. At cambial age 14, the radial growth began to grad-

ually decline again to a mean value of 1.4 mm at Kp and

2.7 mm at Dg until cambial age 22. Although the magnitudes

were different between the poor (Kp) and good (Dg) sites, the

trends within the cambial ages were similar at both sites.

The EWW and LWW showed parallel trends to that for

the WRW. Except for the first two rings at Dg site, the

EWW for all cambial ages were consistently larger than (or

rarely equal to) the LWW at both test sites (Fig. 2a). The

general trends in ring width components were similar at the

two test sites, and the good site (Dg) consistently had larger

values at each ring than the poor site.

The variability (i.e., CV) for WRW was initially low

(30% at Kp, 35% at Dg), but starting at cambial age 4,

gradually increased to 47% at cambial age 20 (Fig. 2b) with

regular oscillations. The WRW had lower variability than its

components (EWW and LWW) at both test sites. The var-

iability of EWW at any given cambial age at the poor site

(Kp) was higher than that at the good site. The rate of change

in the variability from early to later cambial ages was greater

in the WRW than in each of its components (Fig. 2b).

Relation of ring density and its components

to cambial age

The RAD was comparatively low (approximately 485 kg/m3)

at early cambial ages, reaching a mean value of 501 kg/m3

at cambial age 22 (Fig. 3a). The RAD values gradually

increased from pith to bark and were more or less similar at

both test sites at any given cambial age.

The EWD was greatest (approximately 410 kg/m3) at

the early cambial ages, declining steadily during the next

decade to a low of 380 kg/m3 (Fig. 3a). Thereafter, the

EWD became more or less stable, reaching 383 kg/m3 at

cambium age 22. The general trend of EWD variation from

pith to bark was parallel, and the values were similar at

both test sites at any given cambial age.

The LWD was lowest (approximately 550 kg/m3) at early

cambial ages, increasing sharply during the next decade at

both test sites (Fig. 3a). By cambial age 12, both sites had

nearly similar values and trends. However, after cambial age

12, the LWD became nearly stable with a mean of 628 kg/

m3 at the poor site (Kp) and a mean of 660 kg/m3 at the good

site (Dg). At early cambial ages, the LWD was greater at the

poor site than at the good site. However, starting at cambial

age 11, the LWD at the good site was consistently higher

than at the poor site. The differences between the poor and

good sites increased with increasing age.

The RAD variability (CV) gradually increased from

younger to older cambial ages at both test sites (Fig. 3b).

0

10

20

30

40

50

60

70

E

WD

LWD

RAD L

WPW

RWLW

WEW

W

CV

(%

)Dg Kp

Fig. 1 Variability profile to compare variability levels for ring width

and density traits in Pinus brutia at two different test sites (Kp Kepez,

Dg Duzlercami)

0

1

2

3

4

5

6

0 2 4 6 8 10 12 14 16 18 20 22 24

Ring no (pith to bark)

Wid

th m

m

Dg-WRW Kp-WRW

Dg-EWW Kp-EWW

Dg-LWW Kp-LWW

20

30

40

50

60

70

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Ring no (pith to bark)

CV

(%

)

Dg-WRW Kp-WRW

Dg-EWW Kp-EWW

a

b

Fig. 2 a Cambial age profile for mean values of ring width traits in

Pinus brutia at two different test sites (Kp Kepez, Dg Duzlercami).

b Cambial age profile for the coefficient of variation (CV, %) values

of ring width traits in Pinus brutia at two different test sites

Trees

123

A1

After cambial age 12, the RAD variability was less at the

good site than at the poor site.

The EWD had the lowest variability among all the wood

traits studied. As with other density traits, the CV was

lower at early cambial ages and increased, but with a less

steep trend, from 4.5% (at ring number 2) to 6.3% (at ring

number 22) (Fig. 3b).

The wood density variation for LWD increased at both

test sites from younger to older cambial ages (Fig. 3b). The

LWD was consistently less variable (more uniform) at the

good site than at the poor site.

The late wood proportion (LWP) was highest (approx-

imately 54%) at early cambial ages, declining gradually to

a mean of 46% at cambial age 22 (Fig. 4a). Thus, the LWP

showed a declining trend from pith to bark as the trees

aged. At earlier cambial ages (until the 6th ring from the

pith), the LWP in a given annual ring was consistently

higher at the good site than the poor site. However, starting

at cambial age 7, the LWP at the poor site was consistently

higher than at the good site. Thus, the proportion of wood

formed early in a growing season within an annual ring was

higher at the good site than at the poor site. After cambial

age 7, the general trend of LWP variation from younger

cambial ages to older cambial ages was nearly parallel at

both test sites.

The variability of the LWP proportion was high at early

cambial ages (32–37%) and gradually declined after ring

number 10 (Fig. 4b). The LWP was consistently less var-

iable at the good site than at the poor site, which was the

case also for LWD trait.

Comparisons of test sites in terms of radial growth

and wood density traits

The test sites differed significantly in radial growth traits

(dbh, WRW, EWW, LWW) (Table 3). The values of radial

350

400

450

500

550

600

650

700

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Ring no (pith to bark)

Den

sity

kg

/m3

Dg-RAD Kp-RADDg-EWD Kp-EWDDg-LWD Kp-LWD

3

4

5

6

7

8

9

10

11

12

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Ring no (Pith to bark)

CV

(%

)

Dg-RAD Kp-RAD

Dg-EWD Kp-EWD

Dg-LWD Kp-LWD

a

b

Fig. 3 a Cambial age profile for mean values of ring density traits in

Pinus brutia at two different test sites (vertical dashed line indicates

the transition age from juvenile wood to mature wood). b Cambial

age profile for the coefficient of variation (CV, %) values of ring

density traits in Pinus brutia at two different test sites

40

42

44

46

48

50

52

54

56

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Ring no (pith to bark)

LW

P (

%)

Dg-LWP

Kp-LWP

22

24

26

28

30

32

34

36

38

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Ring no (pith to bark)

CV

(%)

Dg-LWP

Kp-LWP

a

b

Fig. 4 a Cambial age profile for the mean value (%) of latewood

proportion (LWP) in Pinus brutia at two different test sites. b Cambial

age profile for the coefficient of variation (CV, %) of latewood

proportion (LWP) in Pinus brutia at two different test sites

Trees

123

A1

growth traits were clearly larger at the good site (Dg)

compared with those at the poor site (Kp) (Table 2). For

example, the partitioning of variance components indicated

that 53% of the variation in dbh was due to site differences.

Similarly, 33% of the variation in WRW, 28% in EWW,

and 23% in LWW were also due to site differences. For

each of these characters, the differences due to cambial

ages (within sites) had smaller variance components than

those of the site differences, the corresponding values

being 20, 12, and 22%, for WRW, EWW, and LWW,

respectively (Table 3).

The late wood proportion (LWP) differences between

the sites were not statistically significant. As a result, the

variance in LWP due to site differences was less than 1%

(Table 3). Similarly, the contribution of variance due to

cambial age differences in LWP was low (3.6%).

The wood density traits (RAD, EWD, LWD) at the two

sites were nearly equal with no statistically significant

differences (Tables 2, 3). Less than 1.11% of variance in

each of the RAD, EWD, and LWD traits was accounted

for by site differences. However, the cambial ages within

the sites were significantly different, as illustrated by the

cambial age profiles for each trait shown in Fig. 3a.

The contribution of variance due to cambial ages in RAD

was the smallest (3.8%) among the wood density traits

(Table 3).

Juvenile wood (JW)–mature wood (MW) transition

Several features of wood density and radial growth traits in

our study indicate that the cambial ages (i.e., ring numbers)

between 11 and 13 years might be considered the transition

zone between juvenile and mature wood in P. brutia. For

example, the LWD increased steadily from ring number 2

until ring number 12, after which it was stable at 646 kg/m3

(Fig. 3a). Similarly, the EWD and RAD values were nearly

stable following ring number 13 at 384 and 505 kg/m3,

respectively (Fig. 3a). The CV for EWD was also stable

after ring number 12 (Fig. 3b); the EWD was more uniform

among the rings after cambial age 12. The LWP declined

steadily until cambial age 9–12 and then gradually

increased, remaining at 46–48% (Fig. 4a). The mean val-

ues for each of the ring width components were relatively

high at ring 2, declined steadily until ring numbers 8–10,

and were more or less stable after ring number 12 (Fig. 2a).

Although site Kp (lower site quality) appeared to have an

earlier rate of change from the juvenile to mature wood

compared with site Dg, the general trends were nearly

similar at both test sites. These observations suggest that

the transition from JW to MW in P. brutia occurs at the

12th year from the pith.

Using the 12th cambial age as the transition age

between juvenile and mature wood, we compared the JW

and MW portions of the core samples at each test site for

ring width and density traits (Table 4; Fig. 5). The radial

growth traits (EWW, LWW and WRW) were significantly

higher in the JW than in the MW (Fig. 5a) overall and at

both test sites. Contrary to the ring width traits, two of the

ring density traits (RAD, and LWD) were significantly

higher in the MW than in the JW overall and at both test

sites. The EWD, however, differed from the two other ring

density traits because it was higher in the JW than in the

MW. The LWP was similar to the EWD with the excep-

tion that the differences between the LWP in the JW and

MW were not significantly different at the Kp test site

(Table 4).

Effects of thinning on radial growth and wood density

Thinning appeared to stimulate certain radial growth and

density traits of trees during the subsequent growing sea-

sons. For example, at test site Dg, the LWW increased

from 1.3 to 1.8 mm 1 year after the second thinning (in the

1996 growing season) with relatively high values in the

subsequent years (Fig. 6). The EWW (from 1.9 to 2.4 mm)

and WRW (from 3.2 to 4.2 mm) exhibited similar

responses. The response to thinning at the good site (Dg)

was more pronounced than that at the poor site (Kp). The

LWP and RAD also increased markedly at the Dg test site

in the years following thinning.

Discussion

Overall wood density and radial growth values

for Pinus brutia

Using X-ray densitometry, our results showed that the

overall wood density (i.e., RAD) in 30-year-old P. brutia

trees was 495 ± 45 kg/m3. This value was consistent

with previous findings measured using other methods

(Guller 2007; Guller and Yasar 2010). The mean LWD

(620 ± 24 kg/m3) was 60% higher than the mean EWD.

This difference might be due to various anatomical modi-

fications and variations in the structure and chemical

composition between the cell walls of late and earlywood

(Decoux et al. 2004). In particular, the high resin content in

P. brutia wood could be an important contributing factor to

higher latewood density (Raymond et al. 2004).

The radial growth (as expressed by WRW, EWW,

LWW) was higher in the annual rings closer to the pith

than those closer to the bark. The radial growth declined

sharply until cambial age 8 and subsequently remained

stable. Studies by Adamopoulos et al. (2009) on P. brutia

also indicate that the annual rings in early years are broader

than those formed in later years.

Trees

123

A1

The CVs for the density traits (ranging from 4.6 to

10.1%) were markedly smaller than those of the radial

growth traits (ranging from 28.0 to 65%). Thus, the wood

density components were less variable (more uniform) than

the radial growth traits. This result suggests that in oper-

ational forestry, although there might be greater variation

among trees in terms of their growth rates, the trees exhibit

less variation in terms of their wood density traits.

Wood density versus cambial age

The RAD in P. brutia increased with increasing cambial

age. This is consistent with previous observations in many

conifers (Zobel and Sprague 1998). Decoux et al. (2004)

suggested that this observation might be due to an increase

in the thickness of the cell wall and the number of cell rows

in the radial and tangential directions as the tree become

older. In our study, the LWD (starting at ring number 2)

and LWP (starting at ring number 9) also increased from

pith to bark. However, the EWD was essentially constant

from the 9th ring to the bark. Thus, the increase in RAD

from pith to bark appears to be primarily related to LWD

and LWP. Jyske et al. (2008) reported an increasing wood

density from the pith outward that was also related to

increasing latewood density and proportion in Norway

spruce.

Effects of site differences

The trees at the good site (Dg) had 60% more radial growth

than that at the poor site (Kp). In addition, the LWD, RAD

and LWP were generally more uniform at the good site

than at the poor site. This difference was more pronounced

in the mature wood portion. These results suggest that good

sites produce not only higher quantity but also higher

quality (more uniform) wood than poor sites.

Adamopoulos et al. (2009) reported that the ring width

and dry wood density traits from P. brutia samples taken

from the base of trees were significantly higher at a good

site than at a moderate site, although the differences

between the sites were small. In contrast, we did not find

any significant differences between sites in wood density

Table 3 Analyses of variance (ANOVA) results comparing the two test sites and cambial ages within test sites for growth and wood density

traits in Pinus brutia

Traitsa Source of variation dfb Mean square Prob. % variance component

dbh (mm) Between sites 1 1,343,402.7 \0.0001 53.04

Within 1,009 2,351.2 46.96

WRW (mm) Between sites 1 8,912.67 \0.0001 32.55

Cambial ages (site) 40 271.22 \0.0001 20.27

Within 18,791 1.49 47.18

EWW (mm) Between sites 1 2,469.00 \0.0001 28.05

Cambial ages (site) 40 51.48 \0.0001 12.28

Within 18,381 0.631 59.67

LWW (mm) Between sites 1 1,972.86 \0.0001 23.01

Cambial ages (site) 40 95.52 \0.0001 22.09

Within 18,790 0.539 54.90

LWPc (%) Between sites 1 1.938 0.0741 0.53

Cambial ages (site) 40 0.576 \0.0001 3.61

Within 18,548 0.031 95.86

RAD (kg/m3) Between sites 1 2,654.63 0.7915 0.00

Cambial ages (site) 40 37,468.70 \0.0001 3.83

Within 18,917 1,948.25 96.17

EWD (kg/m3) Between sites 1 24,942.86 0.3956 0.00

Cambial ages (site) 40 33,821.20 \0.0001 12.36

Within 18,591 510.24 87.64

LWD (kg/m3) Between sites 1 724,871.59 0.2399 1.11

Cambial ages (site) 40 509,383.88 \0.0001 35.27

Within 18,882 1,970.58 63.62

df Degrees of freedoma See Table 2 for abbreviationsb For LWP, ANOVA test was applied using arsin transformation

Trees

123

A1

traits (RAD, EWD, LWD) despite large differences

between the sites in radial growth. The least amount of

variance explained by site factors was 23.0% for the radial

growth components (WRW, EWW, LWW), while the

corresponding values for the wood density components

(RAD, EWD, LWD) and LWP were much smaller, less

than 1.2%. Our results indicate that the higher annual

growth increment associated with better site conditions

does not necessarily result in a lower wood density.

Nyakuengama et al. (2002) reported that for P. radiata, the

ring width is more responsive than the wood density to

fertilizer application. Berges et al. (2008) also reported that

the variances due to site factors were twice as high for the

radial growth components as for the wood density com-

ponents in Quercus petraea from locations with different

site indices. The results of these and several other studies

(Zobel and van Buijtenen 1989) support our findings on

P. brutia that environmental factors affect the radial

growth characters more than the wood density characters.

The variances due to sites were zero or near zero for the

EWD and RAD traits and was only 1.1% for LWD and not

significant. These results indicate that the LWD is more

sensitive to environmental differences than the EWD and

RAD. Indeed, although both test sites were similar in terms

of the EWD and RAD up to cambial age 12, the LWD

values at Kp were smaller than those at Dg at ages greater

than 12 (Fig. 3a). Furthermore, as observed in Fig. 3b, the

LWD was more variable at Kp than Dg, and trends from

pith to bark for LWD were steeper (i.e., more sensitive)

than other density traits. Raiskila et al. (2006) also

observed that the latewood components are relatively

sensitive to environmental and site effects within clones of

Picea abies.

Juvenile versus mature wood

In this study, several features of wood density and radial

growth traits indicated that the transition period between

juvenile and mature wood in P. brutia occurred at cambial

age 12. At cambial age 12 (ring number 12), density traits

became nearly stable. This period started approximately

2 years earlier at the poor site (Kp) compared with the

good site (Dg). In Pinus taeda, cambial ages 8–12 were

considered to be the transition period between juvenile and

mature wood where the wood that was produced after

cambial age 11 exhibited considerably different charac-

teristics than the wood produced at earlier ages (Megraw

1985). Burdon et al. (2004) suggested that rings 11–15

from the pith represented the transition period for Pinus

radiata.

The general consensus in conifers has been that the

quality of the juvenile wood is much poorer than the

mature wood (Zobel and Sprague 1998; Alteyrac et al.Ta

ble

4M

ean

s(±

stan

dar

dd

evia

tio

ns)

of

the

rad

ial

gro

wth

and

wo

od

den

sity

trai

tsin

juv

enil

e(J

W,ri

ng

sn

um

ber

s2

thro

ug

h1

1)

and

mat

ure

wo

od

(MW

,ri

ng

sn

um

ber

s1

2th

rou

gh

22

)in

Pin

us

bru

tia

Tra

itsa

Ov

eral

lsp

ecie

sc(s

ites

po

ole

d)

Kep

ezsi

te,

Kp

cD

uzl

erca

mi

site

,D

gc

JWd

MW

dJW

dM

Wd

JWd

MW

d

WR

W(m

m)

(N)

3.4

2A

±1

.67

(9,8

57

)2

.39

B±

1.3

9(8

,97

6)

2.6

9A

±1

.24

(4,8

92

)1

.65

B±

0.7

6(4

,63

1)

4.1

5A

±1

.73

(4,9

65

)3

.19

B±

1.4

6(4

,34

5)

EW

W(m

m)

(N)

1.8

0A

±0

.99

(9,6

67

)1

.34

B±

0.8

5(8

,75

6)

1.4

4A

±0

.82

(4,7

67

)0

.90

B±

0.5

0(4

,48

1)

2.1

4A

±1

.01

(4,9

00

)1

.81

B±

0.8

9(4

,27

5)

LW

W(m

m)

(N)

1.6

4A

±1

.05

(9,8

72

)1

.08

B±

0.6

8(8

,96

0)

1.2

6A

±0

.66

(4,9

10

)0

.77

B±

0.3

9(4

,62

0)

2.0

3A

±1

.21

(4,9

62

)1

.42

B±

0.7

5(4

,34

0)

LW

Pb

(%)

(N)

47

.55

A±

15

.24

(9,8

39

)4

6.2

2B

±1

3.7

5(8

,75

1)

47

.71

A±

15

.33

(4,9

43

)4

7.7

5A

±1

5.0

4(4

,47

9)

47

.39

A±

15

.14

(4,8

96

)4

4.6

2B

±1

2.0

6(4

,27

2)

RA

D(k

g/m

3)

(N)

48

8.4

8A

±4

2.3

5(9

,99

8)

50

3.2

4B

±4

6.5

4(8

,96

1)

49

0.6

1A

±4

2.5

2(5

,02

3)

50

2.2

8B

±4

9.4

3(4

,60

9)

48

6.3

2A

±4

2.0

7(4

,97

5)

50

4.2

6B

±4

3.2

5(4

,35

2)

EW

D(k

g/m

3)

(N)

39

2.7

5A

±2

3.1

3(9

,85

3)

38

2.9

6B

±2

4.2

3(8

,78

0)

39

3.3

2A

±2

1.6

1(4

,94

8)

38

5.1

3B

±2

4.0

7(4

,49

1)

39

2.1

8A

±2

4.5

5(4

,90

5)

38

0.6

9B

±2

4.2

0(4

,28

9)

LW

D(k

g/m

3)

(N)

59

7.3

4A

±4

8.7

7(9

,99

4)

64

4.9

0B

±5

1.4

6(8

,93

0)

60

0.2

6A

±4

9.3

3(5

,01

8)

63

0.5

7B

±5

2.8

3(4

,59

3)

59

4.4

0A

±4

8.0

3(4

,97

6)

66

0.0

8B

±4

5.2

7(4

,33

7)

aS

eeT

able

2fo

rab

bre

via

tions

bF

or

LW

P,

the

AN

OV

Ate

stw

asap

pli

edu

sin

gar

sin

tran

sfo

rmat

ion

cD

ata

are

bas

edo

nin

div

idu

alri

ng

val

ues

.N

num

ber

of

rings

(num

ber

of

obse

rvat

ions)

are

giv

enin

par

enth

esis

dF

or

ag

iven

trai

t,th

eJW

and

MW

mea

ns

that

hav

ed

iffe

ren

tu

pp

erca

sele

tter

sw

ith

inth

esa

me

test

site

(or

wit

hin

the

ov

eral

lsp

ecie

sle

vel

)ar

esi

gn

ifica

ntl

ydif

fere

nt

atle

ast

atth

e5%

level

Trees

123

A1

2006). In P. brutia, we found that the LW formed in

juvenile wood was significantly lighter than the LW

formed in mature wood, as might be expected. In contrast,

the EW formed in juvenile wood was significantly denser

than the EW formed in mature wood. Furthermore, the

LWP in juvenile wood was also significantly higher than

the LWP in mature wood. These relationships among

EWD, LWD, and LWP in the juvenile and mature wood

J

M

J

M

J

MJ

M

J

M

J

M

0

1

2

3

4

5

Wid

th m

m

Dg Dg Dg Dg Dg Dg Kp Kp Kp Kp Kp Kp

EWW LWW WRW

JM

J M

J

M

J

M

JM

JM

300

320

340

360

380

400

420

440

460

480

500

520

540

560

580

600

620

640

660

680

kg/m

3

Dg Dg Dg Dg Dg Dg Kp Kp Kp Kp Kp Kp

EWD LWD RAD

a

b

Fig. 5 a Chart to compare the ring width traits (EWD, LWW and

WRW) in juvenile (J) and mature wood (M) in Pinus brutia at two

different test sites. b Chart to compare the wood density traits (EWD,

LWW and WRW) of juvenile (J) with mature wood (M) in Pinusbrutia at two different test sites (Dg Duzlercami, Kp Kepez)

Trees

123

A1

are unique to P. brutia and contribute to a more uniform

wood (and thus, improved wood quality) within a given

annual ring and between the juvenile and mature wood

portions of the stem. As a result, the difference between the

RAD values in the mature and juvenile wood in P. brutia

was not large.

Effects of thinning

We found no clear effect of the first thinning on tree growth

at either test site. This observation was probably due to the

competition among trees had not yet started at the time of

the first thinning. By the time of the second thinning,

however, the crown closure and competition among the

trees were well advanced at the good site, Dg. As a result,

the response to thinning at the good site was more pro-

nounced than that at the poor site, Kp. The ring width and

latewood proportion increased during the four subsequent

growing seasons after the second thinning at Dg. Studies of

P. brutia plantations indicate that thinning, especially

heavy thinning, significantly increased the radial growth

rate (Guller 2007). Similarly, Jaakkola et al. (2006) showed

that thinning in Picea abies stands significantly increased

the radial growth rate of the individual trees but had no or

only a slight effect on the wood density. The ring average

density (RAD) in the years following the second thinning

at site Dg also increased, which appears to be an indirect

effect of the increase in the latewood proportion.

Conclusions

• The ring growth components (whole ring growth, ear-

lywood growth, and latewood growth) were higher in

the rings closer to pith than those near the bark. Thin-

ning appeared to increase ring width, latewood pro-

portion, and ring average density in subsequent growing

seasons.

• The ring density traits (ring average density, earlywood

density, latewood density) were much less variable (and

less subject to changes by environmental variables)

than the ring growth traits.

• The ring average density showed a gradual increase

from pith to bark. This increase appears to be primarily

related to latewood density and latewood proportion.

• Test site differences did not influence the magnitude of

the ring density traits significantly. However, the ring

density traits were more uniform among the rings at the

good site compared with the poor site. An increased

radial growth associated with better site conditions does

not necessarily have an adverse effect on the wood

density. Improving site quality would result in more

uniform wood.

• Several features of wood density and radial growth

traits reveal that the transition between juvenile and

mature wood in P. brutia might occur at cambial age

12. This transition process takes place a few years

earlier at poor sites compared with good sites.

0

1

2

3

4

5

6

7

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

Year

Wid

th m

m

Dg-WRW Dg-EWW Dg-LWW

Kp-WRW Kp-EWW Kp-LWW

Only Dg Both Dg and Kp

Fig. 6 Trends in latewood (LWW), earlywood (EWW) and ring (WRW) widths over the years in Pinus brutia at two different test sites

(Kp Kepez, Dg Duzlercami). Arrows and vertical dashed lines indicate thinning years

Trees

123

A1

• The radial growth traits (WRW, EWW, and LWW),

LWP and EWD had significantly greater values in the

JW than in the MW. In contrast, two ring density traits,

RAD and LWD, were significantly higher in the MW

than in the JW. Such unique relationships among LWP,

EWD, and LWD in juvenile and mature wood contrib-

ute to more uniform wood (i.e., better quality wood)

both within a given annual ring and between the

juvenile and mature wood portions of the stem in

P. brutia.

Acknowledgments The study was supported by The Scientific and

Technological Research Council of Turkey (TUBITAK) under Pro-

ject No: 106O442 and also by a post-doctoral research grant to Dr.

Bilgin Guller at North Carolina State University (NCSU), Raleigh,

NC, USA. We thank Dr. Steve McKeand, Dr. Fikret Isik and the staff

of the NCSU Tree Improvement Program for their helpful suggestions

and for providing X-ray facilities. Yusuf Kurt, Adnan Guller and Asli

Gocmen helped during the sampling of the wood cores, and Dr. Brad

St. Clair (USDA Forest Service, Corvallis, Oregon) thoroughly

revised the language of the manuscript. Dr. Kani Isik established the

test sites in 1979 and since then, the staff of the Forest Service and the

Southwest Anatolia Forest Research Institute in Antalya has main-

tained the test sites. The Akdeniz University Scientific Research Fund

and Suleyman Demirel University provided partial support and lab-

oratory facilities. Two anonymous reviewers made precious sugges-

tions on an earlier draft of the manuscript. The authors are grateful to

all these persons and institutions.

References

Adamopoulos S, Milios E, Doganos D, Bistinas I (2009) Ring width,

latewood proportion and dry density in stems of Pinus brutiaTen. Eur J Wood Prod 67:471–477

Alteyrac J, Cloutier A, Zhang SY (2006) Characterization of juvenile

wood to mature wood transition age in black spruce (Piceamariana (Mill.) BSP) at different stand densities and sampling

heights. Wood Sci Technol 40:124–138

Berges L, Nepveu G, Franc A (2008) Effects of ecological factors on

radial growth and wood density components of sessile oak

(Quearcus petraea Lielbl.) in Northern France. For Ecol Manag

255:567–579

Boydak M (2004) Silvicultural characteristics and natural regenera-

tion of Pinus brutia Ten.—a review. Plant Ecol 171:153–163

Burdon RD, Kibblewhite RP, Walker JCF, Megraw RA, Evans R,

Cown DJ (2004) Juvenile versus mature wood: a new concept,

orthogonal to corewood versus outer wood with special reference

to Pinus radiata and P. taeda. For Sci 50(4):399–415

Decoux V, Varcin E, Leban JM (2004) Relationships between the

intra-ring wood density assessed by X-ray densitometry and

optical anatomical measurements in conifers: consequences for

the cell wall apparent density determination. Ann For Sci

61:251–262

Erkan N (1998) Fast growing species and Pinus brutia. Workshop,

Orman Bakanligi Yayin Dairesi Baskanligi no:63, Ankara (in

Turkish, English abstract)

Fisher JT, Neuman RW, Mexal JG (1986) Performance of Pinushalepensis/brutia group in southern New Mexico. For Ecol

Manag 16:403–410

Guller B (2007) The effects of thinning treatments on density, MOE,

MOR and maximum crushing strength of Pinus brutia Ten.

wood. Ann For Sci 64:467–475

Guller B (2010) Determining wood density of Turkish red pine (Pinusbrutia Ten.) by using X-ray densitometer. SDU For Fac J 2:97–109

Guller B, Yasar S (2010) Estimation of Pinus brutia Ten. wood

density from Fourier Transform Infrared (FTIR) spectroscopic

bands by Artificial Neural Network (ANN). Sci Res Essays

5:1765–1769

Isik K (1986) Altitudinal variation in Pinus brutia Ten.: seed and

seedling characteristics. Silvae Genet 35:58–66

Isik K (1988) Interlocked honeycomb design with three replications

and its application on a population genetics analysis of Turkish

red pine (Pinus brutia Ten.) (in Turkish, English summary).

Turk J Agric For 12:377–386

Isik F, Isik K, Yildirim T, Li B (2002) Annual shoot growth

components related to growth of Pinus brutia. Tree Physiol

22:51–58

Jaakkola T, Makinen H, Saranpaa P (2006) Wood density of Norway

spruce: responses to timing and intensity of first commercial

thinning and fertilization. For Ecol Manag 237:513–521

Jyske T, Makinen H, Saranpaa P (2008) Wood density within Norway

spruce stems. Silva Fenn 42:439–455

Libby WJ, Cockerham CC (1980) Random non-contiguous plots in

interlocking field layouts. Silvae Genet 29:183–190

Lindstrom H (2002) Intra-tree models of juvenile wood in Norway

spruce as an input to simulation software. Silva Fenn 36:521–534

Megraw RA (1985) Wood quality factors in loblolly pine. Tappi

Press, Atlanta

Nyakuengama JG, Downes GM, Ng J (2002) Growth and wood

density responses to later-age fertilizer application in Pinusradiata. IAWA J 23:431–448

Palmberg C (1975) Geographic variation and early growth in south-

eastern semi-arid Australia of Pinus halepensis Mill. and Pinusbrutia species complex. Silvae Genet 24:150–160

Raiskila S, Saranpaa P, Fagerstedt K, Laakso T, Loija M, Mahlberg

R, Paajanen L, Ritschkoff AC (2006) Growth rate and wood

properties of Norway spruce cutting clones on different sites.

Silva Fenn 40:247–256

Raymond CA, Dickson R, Rowell D, Blakemore P, Clark N, Williams

M, Freischmidt G, Joe B (2004) Wood and fiber properties of

dry-land conifers. RIRDC Publication No 04/099, p 69

SAS Institute (1990) SAS/STAT User’s Guide. Version 6, 4th edn,

SAS, Cary

Savva Y, Koubaa A, Tremblay F, Bergeron Y (2010) Effects of radial

growth, tree age, climate, and seed origin on wood density of

diverse jack pine populations. Trees 24:53–65

Smith DM (1954) Maximum moisture content method for determin-

ing specific gravity of small wood samples. US Forest Service,

Forest products Lab. Report No:2014

Tassisa G, Burkhart HE (1997) Juvenile—mature wood demarcation

in loblolly pine trees. Wood Fiber Sci 30:119–127

Usta HZ (1991) A study on the yield of Pinus brutia Ten. Plantations.

Turkish Forest Research Institute, Technical Bulletin No: 219,

Ankara, Turkey, p 138

Weinstein A (1989) Geographic variation and phenology of Pinushalepensis, P. brutia and P. eldarica in Israel. For Ecol Manag

27:99–108

Zobel BJ, Sprague JR (1998) Juvenile wood in forest trees. Springer

Series in Wood Science, Springer-Verlag

Zobel BJ, Van Buijtenen JP (1989) Wood Variation—its causes and

control. Springer Series in Wood Science, Springer-Verlag,

p 363

Trees

123

A1

6 issues/year

Electronic access

▶ springerlink.com

Subscription information

▶ springer.com/librarians

TreesStructure and FunctionEditors-in-Chief: U. Lüttge; R.D. Guy

▶ Covers physiology, biochemistry, functional anatomy, structure andecology of trees and other woody plants

▶ Also presents research articles on pathology and technologicalproblems that contribute to basic understanding of tree structureand function

▶ Publishes reviews on selected topics

Trees - Structure and Function publishes original papers on the physiology, biochemistry,functional anatomy, structure and ecology of trees and other woody plants. Alsopresented are articles concerned with pathology and technological problems, when theycontribute to the basic understanding of structure and function of trees. In addition tooriginal papers and short communications, the journal publishes reviews on selectedtopics concerning the structure and function of trees.The Founding Editor of Trees - Structure and Function is Hubert Ziegler.The Editors-in-Chief are Robert D. Guy, Department of Forest Sciences, University ofBritish Columbia, Vancouver, Canada, and Ulrich E. Lüttge, Botanisches Institut der TU,Darmstadt, Germany.5-Year Impact Factor: 1.900 (2010)*

Impact Factor: 1.444 (2010), Journal Citation Reports®, Thomson Reuters

On the homepage of Trees at springer.com you can

▶ Read the most downloaded articles for free▶ Sign up for our Table of Contents Alerts▶ Get to know the complete Editorial Board▶ Find submission information

A1

Editorial Board Founding Editor Hubert Ziegler Managing Editors

for papers from the Americas:

Robert D. Guy

The University of British Columbia

Department of Forest Sciences

Faculty of Forestry

# 3041-2424 Main Mall

Vancouver BC V6T 1Z4, Canada

e-mail: guy@interchange.ubc.ca

for papers from all other countries:

Ulrich E. Lüttge

Botanisches Institut der TU

Schnittspahnstrasse 3-5

64287 Darmstadt, Germany

e-mail: luettge@bio.tu-darmstadt.de

Tel.: +49-6151-163200

Fax: +49-6151-164630

Editorial Assistant

Verena Kastrup

Botanisches Institut der TU

Schnittspahnstrasse 3-5

64287 Darmstadt, Germany

Editors

Mark Adams

Faculty of Agriculture

Food and Natural Resources

University of Sydney

Sydney, NSW 2006

Australia

e-mail: mark.adams@usyd.edu.au

Roni Aloni

Tel Aviv University

Department of Plant Sciences

69978 Tel Aviv, Israel

e-mail: alonir@post.tau.ac.il

Erwin Beck

Lehrstuhl Pflanzenphysiologie

Universität Bayreuth

Universitätsstrasse 30

95440 Bayreuth, Germany

e-mail: erwin.beck@uni-bayreuth.de

Wolfgang Bilger

Botanisches Institut

Abt. Ökophysiologie der Pflanzen

Am Botanischen Garten 3-9

A1

24118 Kiel, Germany

e-mail: wbilger@bot.uni-kiel.de

Marcos Buckeridge

Department of Botany

Institute of Biosciences

Rua do Matao, 277

Sao Paulo, SP Brazil

PO Box 11461

Postal Code 05422-970

e-mail: msbuck@usp.br

Thomas Buckley

School of Biological, Earth and

Environmental Science UNSW

Sydney NSW 2052, Australia

e-mail: Thomas.Buckley@ensisjv.com

Francisco M. Cánovas

Unidad asociada UMA-CSIC

Universidad de Málaga

Campus de Teatinos

29071 Málaga, Spain

e-mail: canovas@uma.es

John E. Carlson

The School of Forest Resources

Pennsylvania State University

323 Forest Resources Building

University Park, PA 16802, USA

e-mail: jec16@psu.edu

Herv?Cochard

UMR - Physiologie Intégréede l'Arbre Frutier et Forestier

INRA, Site de Crouelle

63039 Clermont-Ferrand, France

e-mail: cochard@clermont.inra.fr

Bettina Engelbrecht

Department of Biology

San Francisco State University

1600 Holoway Ave

San Francisco, CA 94132, USA

e-mail: bettina.engelbrecht@gmail.com

Thierry Fourcaud

UMR AMAP

botAnique et bioinforMatique de l'Architecture des Plantes

TA A-51/PS2 (Bat. PSII, Bur. 105)

Boulevard de la Lironde

34398 Montpellier Cedex 5, France

e-mail: thierry.fourcaud@cirad.fr

Arthur Geßler

University of Freiburg

Core Facility Metabolomics

Centre for System Biology (ZBSA)

Habsburgerstr. 49

A1

79104 Freiburg, Germany

e-mail: arthur.gessler@sonne.uni-freiburg.de

Thorsten Grams

Technische Universität München

Department of Ecology, Ecophysiology of Plants

Am Hochanger 13

85354 Freising, Germany

e-mail: grams@wzw.tum.de

Rüdiger Hampp

Universität Tübingen

Botanisches Institut

Auf der Morgenstelle 1

72076 Tübingen, Germany

e-mail: ruediger.hampp@uni-tuebingen.de

Taizo Hogetsu

The University of Tokyo

Asian Natural Science Center

Midori-cho 1-1-8

Nishtokyo-shi

Tokyo 188-0002, Japan

e-mail: ho@fr.a.u-tokyo.ac.jp

Hamlyn G. Jones

Plant Research Unit

Div. Environmental and Applied Biology

University of Dundee at SCRI

Dundee DD2 5DA, U.K.

e-mail: h.g.jones@dundee.ac.uk

Olavi Junttila

University of Troms?BR>9037 Troms? Norway

olavi.junttila@ib.uit.no

Steven W. Leavitt

University of Arizona

Laboratory of Tree-Ring Research

Tucson, AZ 85721, USA

e-mail: sleavitt@ltrr.arizona.edu

Sune Linder

Southern Swedish Forest Research Centre

Swedish University of Agricultural Sciences

P.O. Box 49

230 53 Alnarp, Sweden

e-mail: sune.linder@ess.slu.se

Catherine Lovelock

Centre for Marine Studies

University of Queensland

St Lucia QLD 4072, Australia

e-mail: c.lovelock@uq.edu.au

John E. Major

Canadian Forest Service

Atlantic Forestry Centre

PO Box 4000, Room 3-506

A1

Fredericton NB, E3B 5P7, Canada

jmajor@nrcan.gc.ca

Rainer Matyssek

Lehrstuhl für Forstbotanik der Universität München

Am Hochanger 3

85354 Freising, Germany

e-mail: matyssek@bot.forst.tu-muenchen.de

Wolfgang Oßwald

WZW - Department für Ökologie

Am Hochanger 3

85375 Freising, Germany

e-mail: osswald@wzw.tum.de

Hardy Pfanz

Institut für Angewandte Botanik

Universität Duisburg-Essen

Campus Essen

Universitätsstr. 5

45117 Essen, Germany

e-mail: hardy.pfanz@uni-essen.de

Heinz Rennenberg

Institut für Forstbotanik und Baumphysiologie

Universität Freiburg

Am Flughafen 17

79085 Freiburg, Germany

e-mail: here@uni-freiburg.de

Thomas Speck

Universität Freiburg

Institut für Biologie II/III

Schänzlestr. 1

79104 Freiburg, Germany

e-mail: thomas.speck@biologie.uni-freiburg.de

Keiji Takabe

Kyoto University

Laboratory of Structure of Plant Cells

Division of Forest and Biomaterial Sciences

Graduate School of Agriculture

Kyoto 606-8502, Japan

e-mail: kjtakabe@kais.kyoto-u.ac.jp

Dieter Treutter

Technische Universität München

Fachgebiet Obstbau

Alte Akademie 16

85350 Freising, Germany

e-mail: dieter.treutter@wzw.tum.de

Klaus Winter

Smithsonian Tropical Institute

P.O. Box 2072

Balboa, Rep. Panama

e-mail: winterk@tivoli.si.edu

A1

Maciej A. Zwieniecki

The Arnold Arboretum of

Harvard University

Biological Laboratories

16 Divinity Ave.

Cambridge, MA 02138, USA

e-mail: mzwienie@oeb.harvard.edu

Hubert Ziegler

Managing Editors for papers from the Americas: Robert D. Guy The University of British Columbia Department of Forest Sciences Faculty of Forestry # 3041-2424 Main Mall Vancouver BC V6T 1Z4, Canada e-mail: guy@interchange.ubc.ca for papers from all other countries: Ulrich E. Lüttge Botanisches Institut der TU Schnittspahnstrasse 3-5 64287 Darmstadt, Germany e-mail: luettge@bio.tu-darmstadt.de

Tel.: +49-6151-163200 Fax: +49-6151-164630

Editorial Assistant Verena Kastrup Botanisches Institut der TU Schnittspahnstrasse 3-5 64287 Darmstadt, Germany

Editors Mark Adams Faculty of Agriculture Food and Natural Resources University of Sydney Sydney, NSW 2006 Australia e-mail: mark.adams@usyd.edu.au

Roni Aloni Tel Aviv University Department of Plant Sciences 69978 Tel Aviv, Israel e-mail: alonir@post.tau.ac.il Erwin Beck Lehrstuhl Pflanzenphysiologie

A1

Universität Bayreuth Universitätsstrasse 30 95440 Bayreuth, Germany e-mail: erwin.beck@uni-bayreuth.de

Wolfgang Bilger Botanisches Institut Abt. Ökophysiologie der Pflanzen Am Botanischen Garten 3-9 24118 Kiel, Germany e-mail: wbilger@bot.uni-kiel.de Marcos Buckeridge Department of Botany Institute of Biosciences Rua do Matao, 277 Sao Paulo, SP Brazil PO Box 11461 Postal Code 05422-970 e-mail: msbuck@usp.br Thomas Buckley School of Biological, Earth and Environmental Science UNSW Sydney NSW 2052, Australia e-mail: Thomas.Buckley@ensisjv.com

Francisco M. Cánovas Unidad asociada UMA-CSIC Universidad de Málaga Campus de Teatinos 29071 Málaga, Spain e-mail: canovas@uma.es

John E. Carlson The School of Forest Resources Pennsylvania State University 323 Forest Resources Building University Park, PA 16802, USA e-mail: jec16@psu.edu

Herv?Cochard UMR - Physiologie Intégréede l'Arbre Frutier et Forestier INRA, Site de Crouelle 63039 Clermont-Ferrand, France e-mail: cochard@clermont.inra.fr Bettina Engelbrecht Department of Biology San Francisco State University 1600 Holoway Ave San Francisco, CA 94132, USA e-mail: bettina.engelbrecht@gmail.com

A1

Thierry Fourcaud UMR AMAP botAnique et bioinforMatique de l'Architecture des Plantes TA A-51/PS2 (Bat. PSII, Bur. 105) Boulevard de la Lironde 34398 Montpellier Cedex 5, France e-mail: thierry.fourcaud@cirad.fr Arthur Geßler University of Freiburg Core Facility Metabolomics Centre for System Biology (ZBSA) Habsburgerstr. 49 79104 Freiburg, Germany e-mail: arthur.gessler@sonne.uni-freiburg.de

Thorsten Grams Technische Universität München Department of Ecology, Ecophysiology of Plants Am Hochanger 13 85354 Freising, Germany e-mail: grams@wzw.tum.de

Rüdiger Hampp Universität Tübingen Botanisches Institut Auf der Morgenstelle 1 72076 Tübingen, Germany e-mail: ruediger.hampp@uni-tuebingen.de Taizo Hogetsu The University of Tokyo Asian Natural Science Center Midori-cho 1-1-8 Nishtokyo-shi Tokyo 188-0002, Japan e-mail: ho@fr.a.u-tokyo.ac.jp Hamlyn G. Jones Plant Research Unit Div. Environmental and Applied Biology University of Dundee at SCRI Dundee DD2 5DA, U.K. e-mail: h.g.jones@dundee.ac.uk

Olavi Junttila University of Troms?BR>9037 Troms? Norway olavi.junttila@ib.uit.no

Steven W. Leavitt University of Arizona Laboratory of Tree-Ring Research Tucson, AZ 85721, USA e-mail: sleavitt@ltrr.arizona.edu

A1

Sune Linder Southern Swedish Forest Research Centre Swedish University of Agricultural Sciences P.O. Box 49 230 53 Alnarp, Sweden e-mail: sune.linder@ess.slu.se

Catherine Lovelock Centre for Marine Studies University of Queensland St Lucia QLD 4072, Australia e-mail: c.lovelock@uq.edu.au

John E. Major Canadian Forest Service Atlantic Forestry Centre PO Box 4000, Room 3-506 Fredericton NB, E3B 5P7, Canada jmajor@nrcan.gc.ca

Rainer Matyssek Lehrstuhl für Forstbotanik der Universität München Am Hochanger 3 85354 Freising, Germany e-mail: matyssek@bot.forst.tu-muenchen.de Wolfgang Oßwald WZW - Department für Ökologie Am Hochanger 3 85375 Freising, Germany e-mail: osswald@wzw.tum.de

Hardy Pfanz Institut für Angewandte Botanik Universität Duisburg-Essen Campus Essen Universitätsstr. 5 45117 Essen, Germany e-mail: hardy.pfanz@uni-essen.de

Heinz Rennenberg Institut für Forstbotanik und Baumphysiologie Universität Freiburg Am Flughafen 17 79085 Freiburg, Germany e-mail: here@uni-freiburg.de

Thomas Speck Universität Freiburg Institut für Biologie II/III Schänzlestr. 1 79104 Freiburg, Germany e-mail: thomas.speck@biologie.uni-freiburg.de

A1

Keiji Takabe Kyoto University Laboratory of Structure of Plant Cells Division of Forest and Biomaterial Sciences Graduate School of Agriculture Kyoto 606-8502, Japan e-mail: kjtakabe@kais.kyoto-u.ac.jp Dieter Treutter Technische Universität München Fachgebiet Obstbau Alte Akademie 16 85350 Freising, Germany e-mail: dieter.treutter@wzw.tum.de

Klaus Winter Smithsonian Tropical Institute P.O. Box 2072 Balboa, Rep. Panama e-mail: winterk@tivoli.si.edu Maciej A. Zwieniecki The Arnold Arboretum of Harvard University Biological Laboratories 16 Divinity Ave. Cambridge, MA 02138, USA e-mail: mzwienie@oeb.harvard.edu

A1

A1

Thomson Reuters Master Journal List JOURNAL LIST

Search terms: TREES Total journals found: 1

1. TREES-STRUCTURE AND FUNCTION Bimonthly ISSN: 0931-1890 SPRINGER, 233 SPRING ST, NEW YORK, USA, NY, 10013

1. Science Citation Index 2. Science Citation Index Expanded 3. Current Contents - Agriculture, Biology & Environmental Sciences 4. BIOSIS Previews

Page 1 of 1Journal Format For Print Page: ISI

12.04.2012http://ip-science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi

A1