Modeling structural lumber quality for

Pinus pinaster Ait. in northwestern Spain

using standing tree acoustic assesment,

tree characteristics and stand variables

Oscar Santaclara , Juan Gabriel Álvarez, Esther Merlo

Sopron, 2011

oscar.santaclara@gmail.com

juangabriel.alvarez@usc.es

esther.merlo.sanchez@gmail.com

Location of sample plots

within the 2 ecoregions

defined for the species in

Galicia

Coast

MATERIAL

MATERIAL AND METHODS

Standing Tree

Measurements

• DBH

• Total tree height

• Crown height

• Acoustic velocity

STANDING TREE MEASUREMENTS

MATERIAL AND METHODS

410 trees measured

IML Hammer

STRESS WAVE VELOCITY MEASUREMENT

MATERIAL AND METHODS

• 4 Acoustic Velocity measurements

• 1m separation between probes and centred at

breast height

• AVtree = average of 4 AV

• 10 trees selected at each sample plot: - Covering all the variability of velocity

- DBH: 25 to 45 cm

- Good Straightness

• Competitors of selected trees identified

• Crown area measured

SELECTED TREES

MATERIAL AND METHODS

99 large dimension pieces:

• 55 : 200x200x5000 mm

• 44 : 200x150x5000 mm

MILL CONVERSION AND BENDING TEST

MATERIAL AND METHODS

Bending Test: EN 408:2010

• MOE in green condition

Main dasometric variables of sample plots

Stand

N

(stems/ha)

G

(m2/ha)

H0

(m) age

IS

(m)

Hmean

(m)

Dmean

(cm)

dg

(cm)

Camariñas 477,49 44,35 20,31 45,4 11,79 19,67 33,61 34,39

Covelo 330,32 47,45 25,14 51,1 14,24 23,43 42,01 42,77

Dodro 633,38 69,14 22,74 51,2 12,88 21,94 36,33 37,28

Entrimo 425,73 58,89 26,61 Desc. 25,02 41,10 41,97

Guitiriz 329,70 49,06 25,43 54,8 14,00 23,64 42,66 43,53

Parderrubias 448,06 44,60 21,17 59,4 10,81 19,20 35,20 35,60

Portas 287,98 37,37 23,73 65,5 12,14 23,62 40,36 40,65

Ribas 726,60 57,79 20,96 43,4 12,44 19,18 30,81 31,82

Saiáns 358,73 44,69 23,31 55,9 12,75 22,18 38,84 39,83

Toén 708,24 51,50 24,82 44,8 14,94 22,34 29,59 30,43

Viveiro 356,98 61,99 19,59 60,9 9,49 18,23 46,04 47,02

MAIN DASOMENTRIC VARIABLES OF SAMPLE PLOTS

RESULTS

Variable Correl.

coef.

diameter (cm) - 0,2389 **

Crown height hc

(m) 0,4311 **

Total height

h (m) 0,3173 **

Crown ratio

Rc (hc/h) 0,2981 **

Basal Area

G (m2/ha) - 0,2433 **

Slenderness (h/d) 0,4336 **

Crown area (m2) - 0,1324 *

Velocidad onda - Dn

Dn (cm)

Ve

l o

nd

a (

m/s

)

0 200 400 600 800

2200

2600

3000

3400

3800

R2 =5.70

p< 0.001

Velocidad onda - Htotal

Htotal (m)

Ve

l o

nd

a (

m/s

)

13 17 21 25 29

2200

2600

3000

3400

3800

R2 =10.07

p< 0.001

Velocidad onda - Hcopa

Hcopa (m)

Ve

l o

nd

a (

m/s

)

7 10 13 16 19 22 25

2200

2600

3000

3400

3800

R2 =18.59

p< 0.001

Velocidad onda - Razón de copa

Hcopa/Htotal

Ve

l o

nd

a (

m/s

)

0,45 0,55 0,65 0,75 0,85 0,95

2200

2600

3000

3400

3800

R2 =8.89

p< 0.001

Velocidad onda - Esbeltez

Htotal/Dn

Ve

l o

nd

a (

m/s

)

0 20 40 60 80 100 120

2200

2600

3000

3400

3800

R2 =18.80

p< 0.001

CORRELATION ANALYSIS FOR THE ACOUSTIC VELOCITY

RESULTS

ik

t

k

k ddd

1

2

4

)/( 2 parcelamg

BALi

ji iji

j

Distd

d

ji

ij

ji i

j

dd

Dist

d

d 16exp

ji

j

i

d

nd

2

2

ji ijj

i

Disth

h

ji iji

j

DistCC

CC

Index Expression

Basal area in larger

trees (BAL)

Modified BAL

Hegyi (1974)

Martin-Ek (1984)

Daniels et al. (1986)

Pukkala y Kolström

(1987)

Crown cross-sectional

area (CCS)

Index Corr. Coef.

BAL -0,0034

BAL mod. 0,1615

Hegyi 0,0698

Martin-Ek -0,1527

Daniels et al. -0,0459

Pukkala y Kolstrom 0,0316

CCS 0,2031*

Would it be possible to asses the

competition effect with the acoustic

technics ???

EFFECT OF COMPETITION ON ACOUSTIC VELOCITY

RESULTS

Variable Corr. Coef.

Acoustic Velocity 0,3794**

diameter (cm) -0,5391**

Total height h (m) 0,2648*

Crown height hc (m) 0,4017**

Rc (hc/h) 0,4031**

Crown Area (m2) -0,1979

Slenderness (h/d) 0,5569**

Stems/ha 0,0118

Basal Area (m2/ha) -0,5389**

Mean height (m) 0,5149**

Dominant height (m) 0,4155**

Site index (m) 0,4059**

Age (years) 0,0406

Variable Corr. Coef.

BAL -0,0840

BAL mod. 0,1742

Hegyi 0,0938

Martin y Ek 0,1071

Daniels et al. -0,2630*

Pukkala y Kolstrom -0,0863

CCS 0,1367

Correlation analysis

Competition effect

INFLUENCE OF TREE AND STAND VARIABLES ON MOE

RESULTS

Parámetr

o

Estimado

r

Error RMSE R2 Índice

condició

n

a0 1,2266 0,0293

1515,9 0,6301 29,93

a1 -0,0180 0,0035

a2 -0,0090 0,0019

a3 0,0429 0,0133

VARIABLE SELECTION METHOD “STEPWISE”

ISaGadaeVaMOE

321

0

MOE = modulus of elasticity (N/mm2)

V = acoustic velocity (m/s)

d = DBH (cm)

G = basal area (m2/ha)

IS = site index (m).

63%

MODEL DEVELOPMENT

RESULTS

• Important influence of dendro- and dasometric variables on the structural

quality of wood

• The acoustic technology is effective to evaluate the structural quality of

standing tree due to the good estimation of MOE and the influence of

dendro- and dasometric variables on it.

• Possibility of modelling the structural quality of wood based on acoustic

techniques and simply variables commonly used in forest inventories.

• Great opportunity for growers and processors to develop new silvicultural

models oriented to industrial destination, optimizing the resource and

increasing the yield

CONCLUSIONS

CONCLUSIONS

Thank you for your attention!!

This work was funded within the following projects:

-Galician regional project PIDGT (07MRU004CT)

- National project MICINN PSE.310000-2008

co-financed with FEDER funds of the European Union