Transcript Comparing ORGANON & SPS - Growth Model Users Group

Comparing ORGANON & SPS
Using the Bakuzis Matrix
Growth Model Users Group
December 15, 2005
Dave Hamlin
The Bakuzis Matrix
 Egolfs Bakuzis
U. Minnesota
Synecological Coordinates
Named by Rolfe Leary
North Central Station, St. Paul. (retired)
The Bakuzis Matrix
A framework for examining models
In the context of biological ‘laws’
Useful for side-by-side comparisons
 Leary, R.A. 1997. Testing models of unthinned red pine
plantations using a modified Bakuzis matrix of stand
properties. Ecological Modelling 98 (1997) 35-46
Full Matrix
Plots Stand
Parameters
against Time
and Each Other
by Site Quality
Full Matrix
Age
Stems
Height
Basal
Area
Mean
DBH
Volume
Age
Stems
Sukachev
Effect
Height
Height
Site Curves
Basal Area
Reineke’s
Rule
Spacing
Percent
Ht-DBH
SI Class
Stocking Guide
Framework
Mean
DBH
Volume
Volume
Site Curves
Volume
Increment
Yield Class
Yield – Density
Effect
Eichorn's
Rule
Assman’s
Density
Italics identify relationships involving increment and thinning
Langsaeter’s
Hypothesis
Volume
Increment
Simplified Matrix
Leary’s Triangular Form
Age
Mean
DBH
Height
Stems
Mean
DBH
Height
Height
Site
Curves
Ht-DBH
Site Class
Stems
Sukachev
Effect
Reineke’s
Rule
Spacing
Percent
Basal
Area
Volume
Stocking
Guide
Volume
Site Class
Eichorn’s
Rule
Yield-Density Effect
Italics indicate cells from which relationships can be derived.
Basal
Area
Volume
Interpreting Cells
Sukachev Effect
‘stands on good sites self-thin faster than
stands on poor sites.’
Reineke’s Rule
sd = a(dbh)b
b is approximately -1.6
b is independent of site quality
a reflects stockability of the site
Interpreting Cells
Percent Spacing
Stands self-thin when their mean inter-tree
distance approaches 10% to 20% of height.
Eichorn’s Rule
Relationship between volume and height is
independent of site.
Models
SPS 4.1H
 January 1999
ORGANON
SMC Beta, April 2005.
Stand Projected
100% DF
 400 TPA at age 15
SI 65, 105, 145
(merchandised with the same functions)
20
Bakuzis Matrix
ORGANON (SMC beta)
400 Initial TPA
QDBH (inches)
15
10
5
Observations
2000
SI Curves
Legend
Top HT (feet)
150
• AGE relationships make
sense
SI 65
100
SI 105
•Sukachev as expected
SI 145
50
4000
•Reineke as expected
TPA
335
•Eichorn looks good
(except SI 65)
270
205
Sukachev
Reineke
Basal Area (sqft/acre)
140
400
300
200
100
220000
CVTS/acre
16500
11000
5500
Eichorn
0
10
20
30
40 50
AGE
60
70
80
0
5
10
15
QDBH (inches)
20
0
50
100
150
Top HT (Feet)
200
140
205
270
TPA
335
400
20
Bakuzis Matrix
SPS 4.1h
400 Initial TPA
QDBH (inches)
15
10
5
Observations
2000
SI Curves
Top HT (feet)
• AGE relationships make
sense
Legend
150
SI 65
100
SI 105
•Sukachev as expected
SI 145
50
•Reineke shows a bit of SI
effect
4000
TPA
335
270
•Eichorn looks good
205
Sukachev
Reineke
Basal Area (sqft/acre)
140
400
300
200
100
220000
CVTS/acre
16500
11000
5500
Eichorn
0
10
20
30
40 50
AGE
60
70
80
0
5
10
15
QDBH (inches)
20
0
50
100
150
Top HT (Feet)
200
140
205
270
TPA
335
400
20
Bakuzis Matrix
SI 105 Compared
400 Initial TPA
QDBH (inches)
15
10
5
SI Curves
Legend
Top HT (feet)
SPS
100
•Identical HT-Age
•Mortality Very Different
2000
150
Observations
ORGANON
•QDBH-TOPHT differ
•CVTS-Age Similar
50
4000
•Has value implications
TPA
335
270
205
Sukachev
Reineke
Basal Area (sqft/acre)
140
400
300
200
100
220000
CVTS/acre
16500
11000
5500
Eichorn
0
10
20
30
40 50
AGE
60
70
80
0
5
10
15
QDBH (inches)
20
0
50
100
150
Top HT (Feet)
200
140
205
270
TPA
335
400
Compare TPA
Sukachev
Observations
•ORGANON Little SI effect in
Reineke
Reineke
400
TPA
335
•SPS 4.1 –
Some SI Effect
270
205
ORGANON
140
400
TPA
335
270
205
SPS 4.1
140
10
20
30
40 50
Age
60
70
80
0
5
10
QDBH
15
20
Compare QDBH & TopHT
200
Observations
TopHT
150
100
• ORGANON taller for a
given QDBH.
50
•Expected, given denser
stands.
ORGANON
200
0
TopHT
150
100
50
SPS 4.1
0
0
5
10
QDBH
15
20
Thoughts
Mortality model drives much of the
difference between SPS and ORGANON
Both models conform reasonably well to
‘law like’ expectations.
It is interesting that CVTS is as similar as
it is, given differences in TPA.
What are the value implications?
Questions?