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,“, :13 .-'" \ F‘ITI
anTfiAv .2

b RLY EVALUATION OF HEIGHT GROWTH IN SEVEN

PINE PROVEKANCE TESTS
by Warren L. Nance

Height growth data from seven pine provenance tests
located in lower Michigan were analysed in order to determine
the feasibility of early evaluation of height growth. The
seven plantations ranged in age from eight to ten years old.
and included one eastern white pine (Pinus strobug L.)
plantation, one ponderosa pine (Pinus ponderosa Laws.)
plantation, and five Scotch pine (Pinus sylvestris L.)
plantations. Three of the Scotch pine plantations were part
of a range—wide study. The other two Scotch pine tests were
made up of provenances from the northern latitudes.

Three methods of analyses were used: simple correlation;
multiple linear regression; and Pearce's growth analysis. The
latter method is essentially a variance-covariance analysis
designed to determine growth patterns in trees.

Simple correlation analysis revealed that nursery
performance was a good indicator of future growth in the field
for the Scotch pine range-wide study and the white pine test.
However, in the ponderosa pine test and the Scotch pine
northern latitude study. nursery performance was not a
reliable indicator of future growth. Winter injury was
considered responsible for the poor age-age correlations in

height growth in the ponderosa pine test.

Jarren L. Lance
fiultiple regression analysis revealed that in most cases
height measurements spaced at three-year intervals are
sufficient for height growth evaluation in field tests. In
the case of ponderosa pine, multiple regression also proved
useful in determining the influence of winter injury on height
growth predictability.

Pearce's analysis was performed on the Scotch pine
northern latitude plantations. The analysis revealed that
temporary nursery effects were still detectable in the field
and had declined very slowly over the eight-year test period.
The analysis also showed that planting site had an affect on
the pattern of growth exhibited by the trees.

The present results indicate that early selection for
height growth is feasible provided that the species is adapted
to the site and the test conditions are precise enough to

eliminate most of the temporary variation induced in the

nursery.

EARLY EVALUATION OF HEIGHT GRONTH IN SEVEN

PINE PROVENANCE TESTS

by

Warren L. Nance

A THES IS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Forestry

1969

ACKNOWLEDGEMENTS

The author wishes to acknowledge the special assistance
of the guidance committee: Drs. Jonathan W. Wright, Charles
E. Cress, James W. Hanover, and Victor J. Rudolph.

A special debt of gratitude is due Dr. Jonathan w.
Wright, the major professor, for his diligent efforts in

the author's behalf.

ii

ACK £0331va

(«tsp-y {fr-r1“
KIA-4U; '1‘ J. O O O I O O O O C 0

LIST OF TAEL533 O O O O O I O O O O 0

LIST OF ILLUSLRATIONS . . . . . . .

LIST CF APPENDICES I o o o o o o o 0

Chapter
I.

II.

III.

IV.

V.

INTRODUCTION 0 o a o o o 0

REVIEW OF LITERATURE . . .

Age-age correlations

Nursery selection studies

MATERIAL AND METHODS . . .

Katerial
Measurements
Analysis

Pearce's analysis

RESULTS 0 O O O O O O 0 O O

Scotch pine
Range-wide study
Northern latitude study
White pine
Ponderosa pine

Pearce's analysis

LITERATURE CITED . . . . . . . . . .

iii

PRACTICAL APPLICATICNS OF RESULTS . . .

\u‘j

L-J

LIST OF TABLES
Table rage

1. Summary of phenotypic correlations between
height at different ages reported in the
literature 0 o o o o o o o o o o o o o o o o o o o f

2. Establishment details of seven pine provenance

teStS O O O O O O O O O O O O O O O O O O O O O O «M

3. Number of sources maintaining a selection
differential of one standard deviation (S. D.)
above the mean height in seven provenance

teStS o o o o o o o o o o o o o o o o o o o o o o 20

u. Number of individual trees maintaining a
selection differential of one standard
deviation (S. D.) above the mean height
in seven provenance LGSLS o o o o o o o o o o o o 55

iv

Figure

1.

9.

10.

11.

LIST OF ILLUSTRATICRS

Simple correlations between source mean heights
in the Scotch pine range-wide study . . . . . .

Simple correlations between individual-tree
heights in the Scotch pine range-wide study . .

Simple correlations between source mean heights
in the Scotch pine northern latitude study . .

Simple correlations between individual-tree
heights in Scotch pine plantation 15-62 . . . .

Simple correlations between individual-tree
heights in Scotch pine plantation 17~62 . . . .

Simple correlations between source mean heights
in eastern white pine plantation 3-60 . . . . .

Simple correlations between individual-tree
heights in eastern white pine plantation 3-60 .

Simple correlations between source mean heights
in ponderosa pine plantation 1-62 . . . . . . .

Simple correlations between individual—tree
heights in ponderosa pine plantation 1-62 . . .

Results of Pearce's analysis for Scotch pine
plantation 15‘62 o o o o o o o o o o o o o o 0

Results of Pearce's analysis for Scotch pine
plantation 17‘62 o o o o o o o o o o o o o o o

Page

m
...A

21

'A) ’)
r, r-

LIST OF APPENDICES

Appendix

A.

F.

Scotch pine provenance test No. 11-61.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source means and
individual-tree data 0 o o o o o o o o o o o

Scotch pine provenance test No. 2—61.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source means and
indiVidual-tree data 0 0 0 o o o o o o o o o

Scotch pine provenance test No. 12-61.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source means and
individual-tree data . . . . . . . . . . . .

Scotch pine provenance test No. 15-62.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source means and
indiVidual-tree data 0 o o o o o o o o o o o

Scotch pine provenance test No. 17-62.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source means and
individual-tree data . . . . . . . . . . . .

White pine provenance test No. 3-60.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source means and
individual-tree data 0 o o o o o o o o o o o

Ponderosa pine provenance test No. 1-62.--
Simple correlation coefficients and multiple
regression analyses of height and annual
increment for both source and
individual-tree data 0 o o o o o o o o o o o

Scotch pine provenance test No. 15-62.--
Pearce's analysis of variance and covariance

Scotch pine provenance test No. 17-62.--
Pearce's analysis of variance and covariance

vi

Page
\

46

61

’7’?
a:

m
M

INTRODUCTION

Time is critical in a forest tree improvement program.
The long life cycle in trees makes field-testing procedures
in forestry much longer than in other agricultural creps.

The result has been relatively slow progress in the genetic
improvement of forest tree species. How can the tree
breeder overcome this basic problem and produce improved
planting stock in a fraction of the time now consumed? One
promising method is early evaluation of performance; that is,
early selection for a quantitative trait based on performance
early in the life cycle.

If early selection methods are to be practical, they
must produce reliable and lasting gain. This means that only
traits which are under relatively strong genetic control are
eligible for early selection. More heritability studies are
needed to identify these traits and determine the strength of
their genetic control. Also, the phenotypic correlations in
performance throughout the life cycle must be high enough for
reliable selection.

Forest genetic field tests offer a good Opportunity for
the study of phenotypic correlations in performance,
provided they meet three basic requirements. First, they
must be well designed; that is, replicated, randomized, and
locally restricted (blocked). Second, they must be old
enough to provide useful information. Finally, accurate
records must be available for past performance in the traits

under study.

2

The objectives of this study were two:

1. Determine the feasibility of early selection for
height growth.
2. Establish methods of analysis for early evaluation

studies.

Three species were selected for study: eastern white
pine (Pinus gtrobus L.), Scotchpine (Pinus sylvestgig L.),
and ponderosa pine (Pinus ponderosa Laws.). Phenotypic
correlations in height growth were investigated in seven
provenance tests of these three species in lower Michigan.
In addition, multiple regression and analysis of variance
and covariance were examined for their utility in determining
the reliability of early performance in height growth within

the seven tests.

REVIEW OF LITERATURE

An extensive review of the literature related to early
evaluation in forestry is included in a recent publication
by Nanson (1968). Of the more than 250 papers reviewed by
Nanson covering all phases of early evaluation, only 43
contained data on age-age correlations in height growth of
forest trees. Obviously, early evaluation has been a popular
subject, but few of the papers contained experimental data.
Many early forest researchers either accepted the validity of
early evaluation and terminated their studies in the nursery,
or rejected it's validity and failed to measure juvenile
growth.

lost of the existing knowledge on phenotypic correlations
in height growth is a by-product of early provenance tests of
pines. The IUFRO (International Union of Forest Research
Organizations) experiments in the early 1900's are among the
most valuable of the early tests. More recently established
tests have included provisions for detailed study of early
selection methods. The work of Callaham gt g; (1961, 1962)
is typical of efforts in this direction.

A third source of information is the nursery selection
studies initiated in the United States in the past two decades.
These studies were designed to test the efficiency of mass
selection for height growth in commercial nursery beds.
Superior seedlings were selected within nursery beds at a
rate of 1/30,000 or more and outplanted with a nearby seedling

of average height. Height superiority of the select trees was

3

L;
used as a measure of the effectiveness of mass selection.

Age-age correlations.-— Age-age correlations in height
growth taken from provenance and progeny tests are summarized
in Table 1. This summary points out three important facts
about the status of our knowledge in this field. First,
with the possible exception of four Scotch pine plantations
reported by Nansen (1968), there are no replicated tests
which have reached rotation age. One can conclude from this
that any improved planting stock produced up to the present
time is a result of an early evaluation of the results.

A second feature is the paucity of species studied.
Results for Scotch pine and ponderosa pine make up the bulk
of our knowledge on the subject. As more tests become older,
the list of species should become more representative.

Finally, the case for early evaluation based on the
limited amount of information available is undeniably strong.
With few exceptions, the early height growth was a reliable
indicator of future growth.

Nursegy selection studies.-- The suoess of mass
selection for height growth in commercial seedbeds has been
inconsistent. The oldest nursery selection study in the
United States was initiated by Ellertsen (1955) and later
reported on by Zarger (1963). The authors selected 70 2~year
old eastern white pine seedlings over a 5-year period. After
11 to 14 years in the field, the selected seedlings were

significantly taller than their controls.

 

 

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They also selected 210 loblolly (Finus taeda L.) and 45
shortleaf (Pinus echinata Mill.) 1-year-old pine seedlings
during the same period. After 11 to 14 years, the selected
trees were not significantly different from the controls in
either species.

In a similar study initiated by Barber and Van
Haverbeke (1961), 582 slash (Pinus elliotti Engelm.) and
571 loblolly pine seedlings were selected. After nine years,
Hunt (1967) reported that the selected trees were still
taller than their controls, but the height advantage had
decreased after age four.

King 31 g; (1965) selected 357 superior white spruce
(Eigga glauca (Moench) Voss.) seedlings from 4—year-old
transplants. The selected seedlings were significantly
taller than the controls after eight years in the field. A
smaller study by Bengston (1963) showed that 34 slash pine
selected seedlings had outgrown their controls after eight
years in the field.

Some researchers have arbitrarily graded nursery stock
into height classes and compared their growth after
outplanting. In all cases, the tallest class was still the
tallest after 4 to 12 years in the field (Bethune gt g;
(1966), Clausen (1963). Curtis (1955), Fowells (1963), Funk
(1964), Hunt gt_al (1967), Schfitt (1962), and Shipman (1960)).

10
The preceeding studies show that early height growth can
be a reliable indicator of future height growth. Emphasis
should be placed on obtaining more information on those
important species which are not represented. Also, methods
of early selection must be defined to allow the researcher
to make predictions of future growth based on early

performance.

MATERIAL AND METHODS

The seven plantations included in this study are among
the oldest Michigan State University provenance tests
located in Michigan. With one exception, they were
established with stock grown in the Bogue nursery at East
Lansing, Michigan. The exception was one white pine test
which was transplanted for one season in the Bogue nursery.
The design for all plantations is a randomized complete
block with row plots. The seed source collections were all
made from several trees of "average" phenotype located in a
native stand.

Material.—- A summary of the details for each study
follows. Additional details for each planting appear in
Table 2.

The five Scotch‘pigg plantations are all part of the
North Central NC-51 regional project. The seed was requested
from European researchers and seed dealers by J. W. Wright
in the summer of 1958. Seeds were recieved from natural
stands in 19 Eurasian countries. Each seedlot consisted of
seed from ten or more average trees from one stand.

The seed were sown in two separate nursery tests. One
test consisted of 108 seedlots sown in the nursery in the
spring of 1959. These seedlots represented a range-wide
sample of Scotch pine. The second test consisted of 59
seedlots from northern latitudes sown in the spring of 1961.
Both tests were sown in five replicates. The fifth, non-

randomized replicate provided most of the planting stock.

11

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The range-wide study produced excellent planting stock
superior in size and uniformity to that produced locally in
commercial nurseries. In contrast, the northern latitude
study produced more variable stock. The stock from both
studies was outplanted as 2-0 seedlings, the former in the
spring of 1961 and the latter in the fall of 1962.

The white pine plantation is part of a range-wide study
initiated by the U. S. Forest Service in cooperation with
other Canadian and United States tree breeders. Seedlots were
collected from 26 natural stands, each seedlot consisting
of seed from 3 to 10 average trees in a native stand. The
seed was sown in the nursery in the spring of 1957. In 1959
and 1960 more than 30 permanent test plantations were
established throughout the natural range with 2-0 or 2-1
seedlings. Weed control varied from slight to intensive.
There were 4 to 25 replicates within each plantation and
1 to 81 trees per plot within each replicate. Three
plantations were established in lower Michigan, one of which
was selected for use in this study.

The ponderosa plgg plantation is part of a range-wide
study initiated by the U. S. Forest Service in cooperation
with Michigan State University. Seed was collected from
298 individual trees in 57 native stands in 1955 and 1956.
The seed was sown in the nursery in a compact family design

with 3 replications and outplanted in the spring of 1962.

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In addition, individual-tree height growth records wwr»
obtained in the fall of 1968 by measuring past internode
length of approximately 100 trees in each of six plantaiiw~
and every tree in the seventh plantation. The 100 trees par
plantation is enough to calculate simple correlations witr
0.05 confidence limit of t 0.20. To obtain the necessary *r,
trees in a planting, I measured the tallest tree in every
plot of one to seven replicates. By measuring only the
tallest tree in a planting, most of the variation betweer

plots due to insect damage and mortality was removed.

 

Analysis.-- The three classes of data (source mgayg.
plot means, and individual-tree data) were analysed WILL

aid of Michigan State University's CDC 3600 digital comhi

a ll rar, ' e ntit e1 LQu L {w ittec r . L.
‘“ ' , . Ah)“: ”Ti" - ' " 9" ~t’tiCC, 1"" ‘ "r1; .7: ‘
“rr all analyses. with this routirr I fi-d Lie ic=1nwirs
«zaiy3£3 for ee‘« Class cf data for each plantat on:

1. All possible simple correlations for both total
height and annual increment.
2. multiple regression with total height in 1963

the dependent variable and total heights

AV

multiple regression with 1968 increment

3;

dependent variable and previous increments

independent variables.

Pearce's analysis.--

previous years as independent variables.

5“
it?"
5&8 (1w

‘ '~
-'~ 1. in

A separate type of analysis ma.

done for the height growth data of plantations 15-62 and

17-62. This analysis, developed by S. C. Pearce
designed to answer specific questions concerning
of relative growth rate in a group of developing

The basic features of this analysis are outlined

til" DH ii +4 f‘
6
OT‘S’VE Ill 5""? .

a)

‘D e 1 0V} .

Basically, Pearce's analysis of the manner of erowin

utilizes three standard errors to reveal patterns in the

relative growth rate of a group of developing organisms.

These standard errors are:

16
1. Cir, that of logarithm of total height (= log(height))
at time t.
2. (and that of increment in log(height) between time
zero and time t.
3. (Sf? that of log(height) at time t after adjustment
for covariance on the corresponding values at time

zerOo

The first standard error is taken from the error line of
the analysis of variance of log(height) at time t after
adjustment for block and source effects. The second standard
error is taken from the error line of the analysis of the
analysis of variance for increment in log(height) between
time zero and time t, after correction for block and source
effects. The variable t takes on the values 1,2,...n, where
n is the total age of the tree in years. Finally, the third
standard error is taken from the error line of the analysis
of covariance for log(height), after correction for block,
source, and covariate. The covariate is log(height) at time
zero.

These standard errors are obtained for each time t in
which measurements were taken for total height and then
plotted over time. The resulting pattern can provide answers

to the following questions:

17
1. Is the relative growth rate of individual trees
constant or dynamic?
2. Does the initial height at time of outplanting
affect the future relative growth rate of the tree?
3. If the future growth rate is influenced by initial

height, how does this influence change with time?

A further explanation of the method will be given in
the results section along with the answers to these questions

for the Scotch pine plantations analysed.

RESULTS

The results of analyses for the three classes of data
were compared for each plantation. The analyses based on
plot means were eliminated from consideration. They did not
contribute any significant information beyond that obtained
from the analysis of source means and individual-tree data.

Scotch.p;g_.-- As noted previously, the range-wide
provenance study was superior in height growth to the northern
latitude study in the nursery. When the two studies were
outplanted, the 2-0 stock of the former averaged 28
centimeters in height compared to an average of 15 centimeters
in height for the 2-0 stock of the latter. Average height at
age eight for the three range-wide plantations (Nos. 11-61,
12-61, and 2—61) was 209 centimeters compared to an average
height of 145 centimeters for the two northern latitude
plantations (15-62 and 17-62). Thus the early height growth
differences between the two studies has persisted to the
present time.

Four sources of variation between the two studies
contributed in varying degrees to the observed differences

in height growth. These are:

1. Differences in range of geographic origin between
the two studies.

2. The studies were outplanted in different seasons:
fall plantings for the northern latitude study and

spring plantings for the range-wide study.

18

3. The stmniies wewxatscwn iJi the ruirserfx in uifkiarenf
years.

4. There are differences in site quality between the
plantations of the two studies, although they are
minor in comparison to the other sources of
variation.

Range-wide study.-- The three plantations stocked with
seedlings from the range-wide study were remarkably similar
in height growth. Apparently, site quality differences
between the plantations within this group were of minor
importance in their effect on growth rate. For this reascn.
the analysis of individual plantations within this study were
combined with little loss of information.

Source differences in height growth were clearcut in the
nursery (Wright, 1963). More important from the standpoint
of early selection, these early differences in the nursery
were indicative of future performance in the field. Figure
shows the simple correlation matrix for mean source height in
different years from seed, pooled for the three plantations.
To find the value of the simple correlation coefficient
between height at age one and height at age four, for exampl ,
simply locate the ”age 1" curve on the right-hand side of
the graph and follow it to the "X" above age four on the
lower axis. The value of the "X" on the left-hand axis is

the correlation coefficient between the two variables.

20

Figure 1. Simple correlations between source mean heights
in the Scotch pine range-wide study. Each "X"
represents a pooled value for plantations 2-61,

11-61, and 12-61.

Figure 2. Simple correlations between individual-tree
heights in the Scotch pine range-wide study.
Each "X" represents a pooled value for

plantations 2-61, 11-61, and 12-61.

AGE

 

 

 

 

32‘ m
.9

5......

R

in

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. D

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. M

4o

R

.3...

...u.

12‘
1 a a A 1 0
522333 2023238

 

AGE

..7‘ I. 4 3

 

 

 

 

m
.9
.8”
R
.7”
Y
3
D
E
.58.
s
. M
4o
R
var
m.
I2A
.. m. a .... m a
:22333 22:25.8

21

Figure 3. Simple correlations between source mean heights
in the Scotch pine northern latitude study.

Each "X" represents a pooled value for plantations

15—62 and 17-620

Figure 4. Simple correlations between individual-tree

heights in Scotch pine plantation 15-62.

 

 

 

 

E
G .
A165 4‘3 2 I 8
.7
_ 9.
. .6“
E
Y
15(
D
E
.14.!
5
3%
R
.7
All.
6
A
.I 0 k~ .# $ 0
hZu.U—muu00 20—h<am¢¢OU

 

 

 

i 3 I 5 6 7
AGE mom sup (YEARS)

i

 

 

1

hZu—

e
or:

5 .¢

d.

. . “J O
uOU 20—h<eu¢¢OU

22

Figure 5. Simple correlations between individual—tree

heights in Scotch pine plantation 17-62.

Figure 6. Simple correlations between source mean heights

in white pine plantation 3-60.

AGE

 

2 3 J 5 6 7
AGE EROM SEED (YEARS)

i

 

 

I

...Zu—

a
u.mg

.0 4.4

ado z

. 2 o
O.h<uu¢¢00

.6973 2

AGE

 

 

ééds'isiéém
(YEARS)

T

 

 

d d

.. 3 A A
~22u2uu0u 20:

3 O
<.— m¢¢OU

AGE FROM 5 £50

23

Figure 7. Simple correlations between individual-tree

heights in white pine plantation 3-60.

Figure 8. Simple correlations between source mean heights

in ponderosa pine plantation 1-62.

AGE

..7.5 32

 

i 5 4' 5' 5 i 5 9 10
AGE FROM SEED (YEARS)

I

 

 

 

1 S A A 1 o
hZu.U.umuOu 20:<._u¢¢Ou

 

 

 

 

6

5

 

7

(YEARS)

i ii A
AGE FROM SEED

i

 

4

h z EUIEOU 10.2358.

1. B .0. &. at 0 «I 4.

24

Figure 9. Simple correlations between individual-tree

heights in ponderosa pine plantation 1-62.

Figure 10. Results of Pearce's analysis for Scotch pine

plantation 15-62.

(EIENT
e 0.0 -

"e

"P

 

 

CORRELATION CQE FF

0

STANDARD ERROR

i

2 3 J 5 6
AGE ERDM SEED (YEARS)

 

7 8

 

0.5+

 

 

 

 

 

 

fm

25

Figure 11. Results of Pearce's analysis for Scotch pine

plantation 17-62.

1.0

 

 

 

MSFGP I 7-62

 

 

 

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who mo Hmflpcmnoewflc cofleooamm m mcflcflmecflms moose Hmscfi>flccfl mo copesz .: macaw

28

The close correspondence between nursery performance
and field performance shows that selection of superior
sources in the nursery was feasible. To view these results
from another standpoint, I considered those sources which
were at least one standard deviation above the mean height
at the end of the nursery phase and followed their
performance in later years in each field test. The results
appear in Table 3. Of the top sources included in each of
the three plantations, approximately two—thirds maintained
their superior position through the 1968 growing season.

I performed the same analyses as for source means on
the data from 500 individual trees in the same three
plantations. The results appear in Figure 2 and in Table 4.
Comparison with Figure 1 shows that the correlations between
height at different ages were lower for the individual-tree
data than for the source means analysis. This is further
reflected in the smaller fraction (five-eighths) of selected
trees which had maintained their height superiority through
the 1968 growing season.

Multiple regression analyses were performed on both the
source means and the individual-tree data to determine the
preciseness with which future height and annual increment
could be predicted from previous height measurements. The
general significance of these analyses can be summarized as

follows:

29

1. Height at ages 1, 2, and 3 accounted for 67 to 83
percent of the variation in total height among
sources at age 10 (R2 = .67, .74, and .83 for
plantations 2-61, 11-61, and 12-61 respectively).

2. Total height for the first and second year in the
field accounted for 56 to 68 percent of the
variation among individual trees at age 10 (R2 =
.68, .59. and .56 for plantations 2-61, 11-61, and
12-61 respectively).

3. Annual increment in 1968 could not be predicted
accurately (R2 = less than .30) from previous
increments either for source means or individual-tree
data (one exception: R2 = .49 and .53 for source and
individual-tree data respectively in plantation
2-61).

4. At least 92 percent of the variation in total height
at age 10 for source and individual-tree data could
be predicted from only three previous height

measurements spaced at three—year intervals.

Northern latitude study.-- Differences in height growth
between sources was not pronounced in the nursery (Wright,
1963). This was due in part to the fewer number of sources
sampled from a more limited part of the natural range.

Simple correlation coefficients between heights at different
ages were similar enough to allow pooling for the source mean

data from the two plantations. These appear in Figure 3.

30

The figure reveals that the nursery height was not a good
indicator of future height growth in the field for this study.
However, heights in the field after the end of the first year
were closely related (r values above 0.80). The fact that
these plantations were fall planted could have resulted in
the low correlations between nursery and field height.

Table 3 shows the same relationship in a different way.
Only about one-third of the sources maintained at least one
standard deviation above the mean height both in the nursery
and in the field after eight years of growth.

Individual-tree analyses for the two plantations were
too disimilar to allow pooling. Figures 4 and 5 show the
simple correlations for heights at different ages for
plantations 15-62 and 17-62 respectively. The differences in
the two figures are not great; plantation 15—62 showing
slightly higher correlations than plantation 17-62. Part of
this difference may be due to the increased mortality in the
latter plantation as a result of poor weed control.

Table 4 reveals that even though the correlations were
lower in plantation 17-62, a greater proportion of the trees
above the selection criterion initially had maintained that
position by age 8. Comparison of Figures 4 and 5 with Figure
3 suggests that individual—tree correlations are higher than
the source mean height correlations. Table 4 shows that
selection of individual trees in the field would have been

more feasible than source selection in this study.

1 ’“ 1‘ r“, ,‘
.mdl ”4-: -v -

u-
,.

- -' . .“ z . ‘ r ‘ \.-. e 1‘ ' ‘ 1“.“ :' \ 1' I " - ‘ ‘ - 'V ‘ v V ‘
and indIViduai—tree data in in the Tfir’R-WldP study. .5

z
0.

general they show:

1. height at age 1 and 2 accounted for 39 to 41 yer er
of the variation between total height of source

means at age 8 (n2 = .41 and .39 for plantation
15-62 and 17—62 respectively).

2. height the first and second year in the field
accounted for 45 to 66 percent of the variation 1:
individual-tree heights at age 8 (R2 = .66 and .49
for plantation 15-62 and 17-62 respectively}.

3. Height increment in the nursery accounted for fit tr
77 percent of the variation in eighth-year heirn‘

. . 2 w
increment between sources (R = .77 and .50 fc~

plantation 15-62 and 17—62 respectively).

L.”

White O ne.-- The white pine plantation is the fastex‘

growing plantction in the study. Excellent planting stoct

;

and good site conditions were in part responsible for the

° N .. * -.; : .. °+, .' :-
apid growth. in addition, white pine, unl

L—
:‘N
(D
(J j-
(I
”3
.)

ponderosa pine, is native to lower
inherentlv fast growth rate. The combined factors resujtwu

. vv r\r~¢- . rv‘ I (~- .-r‘ <‘ n.
in an average height at age 10 Cl 4.c meters.

32

Differences between sources in the nursery were
significant, although relatively small. Figure 6 shows the
simple correlations between heights at different years.
These results show that nursery performance was not highly
indicative of future performance. Also, correlations
between early and late performance in the field are somewhat
erratic; a condition not noted in the previous Scotch pine
data.

Only one source, from Tennessee, met the selection
criterion (one standard deviation above the mean) in the
nursery. This source maintained it's position through age
10 in the field.

Why the erratic behavior in the correlations between
source mean heights in this study? Further investigation
revealed that only two sources were responsible for this
result; Georgia and Ontario. The Georgia source initially
ranked second in total height, but steadily declined in
rank and now occupies the seventh position. In contrast,
the Ontario source ranked sixth initially and now ranks
second. The rank of the remaining 11 sources remained

essentially unchanged.

Seventy ln01v10uai trees were measured within plantaticn
3-ou. The simple correlati n coefficients between heights
different ages are shown in figure 7. To show these resui’
in a different light, I followed the height growth of those
trees which were superior in height the first year in the
field. The results (Table 4) show that individual—tree dat'
are more reliable than source mean data in this plantation.

Multiple regression analysis was performed on source

and individual-tree data as before. They show that:

1. Nursery height accounted for 53 percent of the
variation in source mean height at age 10.

2. height the first and second year in the fielc
accounted for 36 percent of the variation between
individual-tree height at age 10.

3. Tenth-year height increment could not be predicted
accurately from previous annual increments with
the individual-tree data (R2 = .14).

4. Tenth-year height increment was predictable from
previous annual increments for source mean data
(R2 = .80).

5. Three previous height apisurements spaced at thrc»
year intervals were all the measurements needed it
obtain essentially the same amount of information
on height variation provided by all previous hPlfh‘

measurements.

Pogderogg pine.-- from tne standpoint of early selectp

 

methods, this plantation is the most interesting of the ones
studied. The reason for this is the fact that visible
evidence of non-adaptation, in the form of winter injury, 1
present in this species when planted in lower Michigan.
Wells (1964) noted the prescence of winter injury in
some ponderosa pine origins during the nursery phase. The
sources included in the southern ecotypes were more severei;
damaged by winter injury in the nursery than sources fcwm
the northern ecotypes. This relationship remained true in
the plantations. Wells also reported that sources from the
southern part of the range, the same ones which suffered tr«
heaviest winter injury, were also the fastest growing at
one. This relationship changed drastically after the sour ~
were outplanted. Apparently the effects of winter injur:
were so severe in the field that the southern ecotypes coul'
no longer maintain the rapid rate of growth they exhibited

their first year.

figure 7 lLIUSErateS the change in height growth which
occurred alter outplanting. hOte the negative correlations
between height at age one in the nursery and subsequent
field heights. This condition was brought about by the
sharp decline of the southern ecotypes after outplanting
along with a steady increase in relative performance of the
injury-free northern ecotypes. The graph also reveals that
the effects of winter injury had largely stabilized by the
end of the third year from seed. In general, the
correlations between winter injury and total height for
source means was highly significant, ranging between -o.ue
-O.6S (with a rating of 20 for severe winter injury and zero
for none).

With these correlations one would expect little or no
success with attempts to select superior sources on the
basis of early height growth without regard for the effects
of winter injury. Table 4 supports this expectation. Only
one of the original nine sources maintained it's original
superiority.

The results of the individual tree correlations appnfi“
in Figure 8 and Table 5. Due to the stabilized effects 0“
winter injury, the individual-tree correlations appear much
larger than the source means correlations. Also, a larger
prOportion of the select individuals maintained their

original superiority than was the case with source means.

'C
¥—-’

1.

3.

regression analyses revealed the fUiiCNlbgl

A combination of winter injury and nursery height
accounted for 85 percent of the variation in total
height between source means at age v.

First and second year height in the field accountec
for 70 percent of the variation in total height
between individual trees at age 8.

Total height in the third, sixth, and seventh year

accounted for 73 percent of the variation between

individual trees in eighth-year height.

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variarée and covariance for niantaticns iq-E? and 17-6?

#13
p.10

10 and ‘3. The main obiective of this

appear in t

sures
analysis was to evaluate the effectiveness of the method
early evaluation studies. For this reason, the analysis w;
restricted to these plantations. Analysis of all the tests
by this method would require extensive computer time.

The graphs were constructed in the following manner.
All standard errors were made relative to CST'at time 0.
Time 0 corresponds to age 2 from seed for trees in each
planting. The three relative standard errors at each
time t were then plotted over time. The time scale is
such that f(C) and f(1.C) correspond to age 2 and age 9
respectively for each plantation. The former represents
age of trees at time of establishment and the latter
corresponds to current time.

The results for plantation 15-62 are similar to that

obtained by Pearce (1960) in apples. The slope of the C37

curve .3 negative, showing that the smaller trees at time
of outplanting have grown faster than the taller trees.
This is analagous to a convergence of growth curves, fer

trees which were short and tall at time of outplanting,
when plotted on semi-log paper.

The curve for 6101.5 steadily rising, except fer '2
short period near the end of the time interval. This shim,

that the trees were growing at di ferent growth rate:

F

c D 4' . . . J' ‘ ‘\ 1
rest 0, the time inuezvai.

..:‘t: 6T’UUI‘V8 is sluwiy’ UUliVefi'gslfi.'; «with the 6T QUL‘J'J.
.Ize EEC-lift v'v'fiul‘t: 1.11%; LVN; inst”- {signals L118 end pi Lilr: infra)“: H
A: initial height on relative growth rate. in other words,
covariance adjustment no longer affects the size of (ST .
from this point on, the trees would perform on their cur
merit, no longer influenced by short—term nursery effects.

Figure 11 is obviously different. The curve for
does not rise, indicating the trees do not have different
growth rates thus far. The rate of convergence for 6T0 and
(ST should be negligible in this case. Inspection of the
graph shows this to be true. Therefore, the present heights
are merely magnifications of the initial heights, and most m
the variation in present height in this planting is related
to initial size differences. One would expect the simple
correlations between height at different ages after
outplanting to be high. This is true for both plantings,
with the correlation coefficients between heights after ag»
three ranging from 0.79 to 0.99.

What does the analysis contribute to the results of 1'-
simple correlation and multiple regression analyses pFQSwfifw
previously? First, it shows the tremendous effect of initl
nursery effects on future results. Temporary nursery effect:
have thus far overshadowed the seed source effect in these
plantings. Second, the planting site can be shown to inflt.~
relative growth rate. The extreme stresses in one plantatiu~
did have a lasting effect on the performance of surviving

trees. Finally, this analysis can show the exact time or

age at wnich nursery influences have ceased. This point bdo

not been reached in either of the plantations analysed.

rhAUTlJAL ArPLlCATlUH UF H:5ULT5

The forest researcher is faced with a difficult quesij
can he safely make an early evaluation of the tree
performance in the field? Based on these results as well
those of previous studies, the answer for height growth is
qualified yes.

The major qualification appears to be whether or flat in
species under test is suitably adapted to the test environs : .
The ponderosa pine in this study is a good example. This
species shows evidence of non-adaptation to test sites in lem‘
Michigan in the form of winter injury. The result was

‘7‘:' .

negative correlation between height growth in the nurs

('0

>‘4

later growth in the field. However, once the basis for t
performance was recognized and taken into account, future
height growth was highly predictable.

A second qualification is: how precise are the test
conditions? The northern latitude study in Scotch pine gnvw
different results in the nursery than in the field. In
contrast, the range-wide Scotch pine study gave essentially
the same results in the nursery as in the field. a ma
difference between the two studies was the low precision of
the former compared to the latter. high mortality and hignl
variable growth in field tests should be considered danger
signals for early evaluation of height growth.

A final qualification is necessary: has the Species and»;
test exhibited strong age-age correlations in height growf~
previous studies when planted under suitable test conni*1r~
fret; MS experiments in Scotch pine, ans tr - mafia

4r

ei;c t ponderosa pine, have shown strong age-age correlativr
in height growth. until such experience has been accumuiw'
for other species, early evaluation of height growth in 8%».
species should be approached with caution.

Even when the qualifications appear to be satisfied,
in the range-wide Scotch pine study, early selection will n('
be perfectly reliable. The mistakes made in early selectin>

must be balanced against the expected gains for the long rub.

wrm

Li’l‘iiRATUnE Li 1 ED

.lr‘

garter, J. C. and van naVerbeke, L. F. 3901. GrOWth of
outstanding nursery seedlings of rinus elliottii bngela.
and Pinus taeda L. Southeast. Forest Exp. Sta., Sta.
Pap. 126. 12pp.

Bengston, G. W. 1963. Slash pine selected from nursery
beds: 8 year performance record. J. Forestry 61: Q2;-

Bethune, J. E. and Langdon, 0. G. 1966. Seed source, seen
size and seedling grade relationships in South Florida
slash pine. J. Forestry 6b: 120—124.

Bialobok, S. 1963. The progress of seedling growth of
poplar hybrids in relation to their selection. FAB/
FCRGEA-é}, 2b/u, 17pp.

Callaham, R. Z. and Duffield, J. W. 1962. Heights of
selected ponderosa pine seedlings during 20 years.
pp. 10-13. Proc. Forest Genet. WorkshOp, Macon, Seecvi

Callaham, R. Z. and Easel, A. A. 1961. Pinus ponderosa—-
height growth of windpollinated progenies. Silvae
Genetica 10: 33-42.

Clausen, K. E. 1953. Lursery selection affects survival nan

growth of birch. U. S. Forest Service Res. Note Ls-3z,

4L

2 pp.

Curtis, R. U. 1955. Use of graded nursery stock for red

pine plantations. J. Forestry 53: 171-173.

~~A

Jersey, K. J. and hough, L. F. 1943. nelaticn between
seedling vigor and tree vigor in apple hybrids. Amer.
Soc. hort. Sci. Proc., “3: 106-114.

Ellertsen, B. W. 1955. Selection of pine superseedlings —-
an exploratory study. Forest Sci. 1: 111-11“.

Fowells, H. A. 1953. The effect of seed and stock sizes on
survival and early growth of ponderosa and Jeffrey pine.
J. Forestry 51: 504-507.

Funk, David T. 1964. Premium yellow—poplar seedlings 8
years after planting. U. S. Forest Service Res. Note
03-20. Upp.

Hunt, David L. 1967. Ninth-year performance of slash and
loblolly pine nursery selections in Georgia. Southern
Forest Tree Imp. Conf. Proc. 9: 92—94.

Johnsson, helge. 1955. Untvecklingen 15-arigra
fbrsbksodlingar av tall i relation till proveniens a-r
odlingsort. Svenska Skogsvardsforeningen Tidskrift 53:
58-88.

King, J., Kienstaedt, 1. and M con, J. 1965. Super-spruce
seedlings show continued superiority. U. S. Forest
Service Res. hote LS-66. 2 pp.

Kriebel, H. 1962. Second-year versus ninth—year height
growth in sugar maple provenance tests. Central "tates
Forest Tree Imp. Conf. Proc. 3: 23-30.

Lester, D. T. and Barr, G. R. 1966. Shoot elongation in
provenance and progeny tests of red pine. Silvae

Genetics 15: 1-6.

- ' W ' 6“: ,o-n 1 ‘.- An ‘ 1 . .rfipu. ~‘
”core, A. no 19Uw. rinxs DCAG“TCDJ ocgalas, a comparison «.

1':
(J.
7+
1)
.4.
fi

various types grown experimentally on naingaro:
Forest. flew Zealand J. Forestry F: 42-47.

Ranson, A. 1968. La valeur des tests precoces dans la
selection des arbres forestiers, en particulier au poi:
de vue de la croissance. Ph. D. Thesis. Faculte Des
Sciences Agronomiques de L'etat. Gembloux, France.

Pearce, S. C. 1960. A method for studting manner of growth.
Biometrics 16: 1-6.

Schreiner, E. J., Littlefield. E. W. and Eliason, E. J.
1962. Results of 1938 IUFRO Scotch pine provenance
tests in Kew York. Northeast. Forest Exp. Sta., Sta.

Pap. 166. 22 pp.

 

Schdtt, P. 1962. Ergibnese einer Auslesevorwuchsiger ELLE:
Sylvestris -Samlinge aus dem Langtag. Silvae Genoti;:
11: 39-42

Shipman, R. D. 1960. Survival and growth of graded lonrler-
pine nursery stock. J. Forestry 58: 38-39.

Squillace, A. E. and Silen, R. R. 1962. Racial variation
in ponder sa pine. Forest Sci. Nonog. 2. 27 pp.

Vincent, G. 1963. dachstumsquotienten als Frdhtests.
Zuchter Spec. 6: 39-35.

wakeley, P. C., and Bercaw, T. E. 1965. Loblolly pine
provenance test at age 35. J. Forestry 63: 168-77u,

'Jells, C. O. 1964. Geographic variation in ponderosa pirr.
I. The ecotypes and their distribution. Silvae

'3’]

Genetics 13: o9-law.

"wright, u. n. and Baldwin, 5. J. 19:77. The 193?: inte'r‘z'miti or:
Union Scotch pine provenance test in Lew hampsnire.
Silvae Genetics 6: 2-19.

Wright, J. W. and Bull, W. Ira. 1953. Geographic variation
in Scotch pine. Silvae Genetics 12: 1-25.

Zarger, T. G. 1965. Performance of loblolly, shortleaf,
and eastern white pine super-seedlings. Silvae Genetics

#6

Appendix A
Scotch pine provenance test No. 11-61.-- Simple correlation

coefficients and multiple regression analyses of height and
annual increment for both source means and individual tree data.

4?

Plantation MSFGP 11-61
Scotch pine provenance test

 

 

 

 

 

 

 

 

 

1. Source means analyses (72 sources)
' 4gp. Key to Variables M
Variable Date Description of Variables
Number Measured
1 -- source number
2 10/18/62 leader growth of plot 1962 (cm)
3 10/18/62 leader growth of best tree 1962 (cm)
6/24/65 height 1965 gin.)
5 9/19/68 height 1968 ft. x u)
6 1959 nursery height 1959 Ecm)
7 1960 nursery height 1960 cm)
8 1961 nursery height 1961 ‘
VStatistics on Vgriables Transformed.to Meters
Variable Mean Standard Deviation
Number
2 0.095 0.023
3 0.120 0.028
4 1.021 0.288
5 2.193 0.624
6 0.092 0.020
7 0.278 0.066
8' 0.483 00109
. Simple Correlation Coefficients
Variables
2 1.00
3 0.95 1.00
4 0.90 0.90 1.00
5 0.86 0.84 0.98 1.00
6 0.67 0.66 0.82 0.85 1.00
7 0.71 0071 0.87 0.90 0.96 1000
8 0.75 0.74 0.90 0.93 0.92 0.96 1.00
2 3 4 5 6 7 8

Multiple Reggession Analyses

 

48

 

 

 

DEpendent Independent Variables R square
Variable
5 2.3.4.6.7.8.9.10 0.9527
*-
5 2,4 ("Best Equation") 0.9495
5 7.8 0.7394
5 79809 0.7416
5 7.8.9.10 0.7437

 

*Determined by stepwise deletion of variablesgincluded

in the equation immediately preceeding.

Deleted variables

did not contribute significantly (0.05 level) to the equation.

2. Individual-tree analyses (98 trees)

Key to Characters

 

 

 

 

 

 

 

 

 

Variable Date A Description of Variables
Number Meagured
1 -- tree number
2 10/10/68 mean height of plot 1968 (ft. X 4)
3 10/10/68 height 1968 (ft. x 4)
4 10/10/68 height 1967 (ft. x 4)
5 10/10/68 height 1966 (ft. x 4)
6 10/10/68 height 1965 (ft. X 4)
7 10/10/68 height 1964 (ft. X 4)
8 10/10/68 height 1963 (ft. x 4)
9 -- increment 1968 (cm)
10 -- increment 1967 (cm)
11 -- increment 1966 (cm)
12 —- increment 1965 (cm)
|__;3 " increment 1964 (gm)
Statistics on Variables TransfggmegAto Meters
Variable Mean Standard DeViation
Numbgg 1
2 1.790 0.475
3 2.224 0.475
4 1.737 0.360
5 1,325 0.284
6 0.948 0.227
7 0.594 0.159
8 0.361 0.110
9 0.488 0.170
10 0.412 0.107
11 0.377 0-090
12 0.354 0.100

 

Simple Correlation Cogificientg

 

 

49

 

 

Variable

2 1.00

3 0.61 1.00

4 0.61 0.96 1.00

5 0.62 0.92 0.97 1.00

6 0.57 0.87 0.93 0.96 1.00

7 0.53 0.77 0.83 0.88 0.93 1.00

8 0.37 0.64 0.71 0.74 0.79 0.87 1.00

9 0.40 0.78 0.56 0.52 0.48 0.38 0.27 1.00

10 0.41 0.77 0.78 0.61 0.56 0.45 0.41 0.49 1.00

11 0.53 0.71 0.73 0.73 0.52 0.44 0.36 0.43 0.52

12 0.47 0.79 0.81 0.80 0.81 0.54 0.42 0.50 0.58

13 0.51 0.62 0.65 0.70 0.74 0.76 0.34 0.37 0.31

2 3 4 5 6 7 8 9 10

11 1.00

12 0.50 1.00

13 0.36 0.48 1.00

11 12 13

_yg Multiple Regpession Analyses #_
Dependent f ndependent arlables . R square
Variable

3 405960708 (all) 009165

3 4.8 ("Best Equation")* 0.9162

3 7.8 0.5913

3 6.7.8 0.7844

3 5.6.7.8 0.8607

9 10.11.12,13.(a11)

~11.

in the equation immediately preceeding.

10.12 LFBest

"*

0.3397

etermined by stepwise deletion of variables included
Deleted variables

did not contribute significantly (0.05 level) to the equation.

o

a .

.-. r
\

50

Appendix B
Scotch pine provenance test No. 2-61.-- Simple correlation

coefficients and multiple regression analyses of height and
annual increment for both source means and individual tree data.

51

Plantation MSFGP 2—61
Scotch pine provenance test

1. Source means analyses (109 sources)

Key to Characters _

 

 

 

 

 

Variable Date Description of Variables
Number Measured
1 -- source number
2 1962 leader growth for plot 1962 (cm)
3 1962 leader growth of best tree in plot(CM)
4 1964 height 1964 (ft. x 10)
5 10/01/68 height 1968 (ft. X 4)
6 10/01/68 height 1967 (ft. x 4)
7 1959 nursery height 1959
8 1960 nursery height 1960
9 1961 nursery height 1961
10 -- increment 1960 (cm)
11 -- increment 1961 (cm
12 -- increment 1962 196; 1964 (cm)
13 increme”. increment 1968 (cm _
1 Statistics on Variables Transformed to Meters
Variable Mean Standard Deviation
Number
2 0.127 0.034
3 0.159 0.044
4 0.859 0.223
5 2.703 0.700
6 2.183 0.554
7 0.092 0.019
8 0.277 0.065
9 0.484 0.109
10 0.185 0.047
11 0.207 0.051
12 0.375 0.145
13 0.519 0.217

 

Simple Correlation Coefficients

 

 

52

 

 

12222212
2 1.00
3 0.92 1.00
4 0.79 0.80 1.00
5 0.72 0.74 0.96 1.00
6 0.75 0.77 0.94 0.96 1.00
7 0.50 0.54 0.76 0.76 0.74 1.00
8 0.54 0.56 0.80 0.79 0.77 0.96 1.00
9 0.58 0.61 0.83 0.82 0.80 0.91 0.95 1.00
10 0.54 0.56 0.79 0.78 0.75 0.90 0.99 0.95 1.00
11 0.55 0.58 0.75 0.74 0.74 0.73 0.76 0.92 0.75
12 0.77 0.77 0.91 0.86 0.84 0.48 0.51 0.52 0.51
13 0.37 0.39 0.65 0.72 0.50 0.51 0.56 0.55 0.57
2 3 4 5 6 7 8 9 10
11 1.00
12 0.46 1.00
13 0.46 0.58 1.00
11 12 Q 13
‘5 Multiple Regression Analyses
Dependent Independent Variables R square
Variable
5 2039406070899 009598
5 2,6,4 (“Best Equation")* 0.9590
5 7.8 0.6301
5 7.8.9 0.6729
5 4079899 0.9293
13 2,3,10,11,12 0.4931
13 10,11 ("Best Equation")* 0.3261
13 ' 10,11.12 0.4395

 

7Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables
did not contribute significantly (0.05 level) to the equation.

53

2. Individual-tree analyses (126 trees)

 

 

Key to Characters

 

 

 

 

 

Variable _Date . Description of Variables
Number Measured
1 -- tree number A
2 10/01/68 mean height of plot 1968 (ft. x 4)
3 10/01/68 height 1968 (ft. x 4
4 10/01/68 height 1967 (ft. x 4
5 10/01/68 height 1966 (ft. x 4)
6 10/01/68 height 1965 (ft. x 4
7 10/01/68 height 1964 (ft. x 4)
8 10/01/68 height 1963 (ft. X 4)
9 10/01/68 height 1962 (ft. x 4
10 -- increment 1968 (cm)
11 -- increment 1967 (cm)
12 -- increment 1966 (cm)
13 -- increment 1965 (cm)
14 -- increment 1964 (cm)
15 -- increment 1963 (cm
Statistics on Variables Transformed to Meters ' .
Variable , . Mean Standard.Dev1ation
Number
2 2.632 0.759
3 3-059 0.852
4 2.340 0.674
5 1.864 0.522
6 1.402 0.406
7 0.971 0.294
8 0.667 0.214
9 0.400 0.140
10' 0.660 0.228
11 0.535 0.182
12 0.462 0.149
13 0.430 0.140
15 0.267 0.101

 

Simple Correlation Coefficients

 

54

 

 

Vgpigblet
2 1.00
3 0.95 1.00
4 0.94 0.98 1.00
5 0.92 0.96 0.98 1.00
6 0.89 0.95 0.96 0.98 1.00
7 0.86 '0.90 0.92 0.95 0.97 1.00
8 0.78 0.83 0.85 0.89 0.92 0.96 1.00
9 0.69 0.74 0.77 0.80 0.82 0.88 0.92 1.00
10 0.80 0.83 0.71 0.69 0.66 0.64 0.57 0.48 1.00
11 0.84 0.87 0.87 0.78 0.75 0.69 0.60 0.55 0.66
12 0.79 0.83 0.83 0.84 0.71 0.68 0.60 0.57 0.63
13 0.78 0.83 0.86 0.85 0.86 0.72 0.66 0.55 0.58
14 0.80 0.84 0.85 0.84 0.84 0.84 0.66 0.57 0.63
15 0.70 0.73 0.74 0.77 0.83 0.83 0.84 0.57 0.53
2 3 4 5 6 c7 8 9 10
11 1.00
12 0.69 1.00
13 0.73 0.63 1.00
14 0.71 0.69 0.67 1.00
15 0.52 0.48 0.64 0.60 1.00
11 12 13 14 15
.2 Multiple Regression Analyses” _
Dependent Independent Variable R square
Variable A
3 49596970809 0.9665
3 4 ("Best Equation")* 0.9648
3 8.9 0.6862
3 7.8.9 0.8343
3 6079819 0.8936
10 11.12.13.14,15 0.5322
10 11,12,15 ("Best Equation")* 0.5240
10 13,14,15 0.4531

 

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables
did not contribute significantly (0.05 level) to the equation.

55

Appendip C
Scotch pine provenance test No. 12-61.-- Simple

correlation coefficients and multiple regression analyses
of height and annual increment for both sources means and
individual tree data.

56

Plantation.MSFGP 12-61
Scotch pine provenance test

1. Source means analyses (76 sources)

 

 

 

Key to Characters
Variable Date Description of Variables
Number Measured
-- source number
10/10/62 leader growth for plot (cm)
10/09/62 leader growth for best tree in plot (cm)
10/29/62 height 1964 (in.)
5/20/67 height 1966 (in.)
1/26/68 height 1967 (ft. x 5)
1959 height 1968 (ft. x 4)
1960 nursery height 1959
1961 nursery height 1960

hHHb—‘HH
(ruNHoxooo-qoxmtumw

I Statistics on Variables Transformed to Meters

 

nursery height 1961

increment 1968 (cm)

increment 1967 (cm)

mean increment for 1965 and 1966 (cm)
increment 1959 (cm) . -

° or

60 m)

 

 

Variable Mpap 7 StandardiDeviation
Number '
2 0.111 0.027
3 0.142 0.036
4 0.843 0.218
5 1.746 0.412
6 2.555 0.635
7 2.866 0.675;
8 0.092 0.018
9 0.282 0.062
10 0.491 0.105
11 0.312 0.104
12 0.808 0.239
13 0.452 0.102
14 0.209 0.049
15 0.189 0.045

 

1

Simple Correlation Coefficients

57

 

 

 

 

Yariable
2 1.00
3 0.90 1.00
4 0.87 0.77 1.00
5 0.84 0.75 0.98 1.00
6 0.82 0.72 0.97 0.98 1.00
7 0.83 0.72 0.97 0.98 0.99 1.00
8 0.71 0.60 0.87 0.86 0.85 0.85 1.00
9 0.71 0.60 0.89 0.89 0.89 0.89 0.95 1.00
10 0.75 0.63 0.91 0.90 0.91 0.91 0.90 0.96 1.00
11 0.32 0.22 0.34 0.36 0.31 0.45 0.35 0.33 0.33
12 0.75 0.64 0.90 0.89 0.96 0.93 0.79 0.84 0.86
13 0.77 0.69 0.91 0.98 0.95 0.95 0.80 0.84 0.85
14 0.71 0.59 0.82 0.81 0.82 0.81 0.74 0.79 0.93
15 0.69 0.58 0.88 0.88 0.88 0.88 0.90 0.99 0.95
2 3 4 5 6 7 8 9 10
11 1.00
12 0.21 1.00
13 0.35 0.84 1.00
14 0.28 0.78 0.70 1.00
15 0.31 0.83 0.84 0.78 1.00
11 12 13 14 15
Multiple Regression Analyses
Dependent Independent Variables R square
‘ZégigELe 2,3,4,5,6;§,9,10 (all) 0.9819
7 5,6 ("Best Equation")* 0.9806
7 8.9 0.7955
7 8,9,10 0.8296
11 12.13.14.15 (all) 0.1705
11 13 ("Best Equation")* 0.1251
_;;_g 15.14 0.1001

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables
did not contribute significantly (0.05 level) to the equation.

2. Individual-tree Analyses (153 trees)

Key to Characters

58

 

 

 

 

 

 

 

Variable Date Description of Variables
Number Measured

1 -- tree number

2 9/20/68 mean height of plot 1968 (ft. X 4)

3 9/20/68 height 1968 (ft. X 4)

4 9/20/68 height 1967 (ft. X 4)

5 9/20/68 height 1966 (ft. x 4)

6 9/20/68 height 1965 (ft. X 4)

7 9/20/68 height 1964 (ft. X 4)

8 9/20/68 height 1963 (ft. X 4)

9 9/20/68 height 1962 (ft. X 4)

10 9/20/68 height 1961 (ft. x 4)

11 -- increment 1968 (cm)

12 -- increment 1967 (cm)

13 -- increment 1966 (cm)

14 -- increment 1965 (cm)

15 -- increment 1964 (cm)

16 -- increment 1963 (cm)
_17 -- increment 1962 (cm)_

Statistics on Variables Transformed to Meters
Variable * Mean Standard Deviation
Number

2 2.991 0.768
3 3.483 0.839
4 2.730 0.702
6 1.484 0.412
7 0.980 0.297
8 0.648 0.202
10 0.264 0.094
11 0.752 0.240
12 0.689 0.281
13 0.557 0.172
14 0.504 0.142
15 0.332 0.118
16 0.250 0.096
17 0.234 0.070

 

.
\

1

u. o
.

..--

Variables

\oooximvt-{ruw

:4 haua +4 F414 2:14
woxm-{rth-AO

11
12
13
14
15
16
17

1.00
0.92
0.90
0.88
0.87
0.83
0.80
0.73
0.64
0.57
0.58
0.64
0.77
0.73
0.67
0.52
2
1.00
0.19
0.40
0.48
0.48
0-39
0.30
11

Simple Correlation Coefficients

1.00
0.97
0.93
0.92
0.89
0.85
0.75
0.62
0.66
0.66
0.66
0.81
0.79
0.73
0.59

1.00
0.16
0.43
0.46
0.45
0.36
12

1.00
0.93
0.93
0.90
0.85
0.75
0.62
0.45
0.74
0.64
0.82
0.81
0.74
0.60

1.00
0.56
0.48
0.42
0.28
13

1.00
0.96
0.92
0.87
0.79
0.67
0.53
0.45
0.77
0.85
0.84
0.74
0.69

1.00
0.69
0.56
0.45
14

1.00
0.97
0.92
0.84
0.70
0.49
0.53

0.57
0.86

0.86

0.73
0.64

1.00

0.60

0.47
15

1.00
0.96
0.87
0.72
0.47
0.50
0.52
0.72
0.87
0.81
0.70

1.00
0.54
16

1.00
0.92
0.74
0.46
0.47
0.48
0.66
0.70
0.83
0.75

1.00
17

1.00
0.86
0.42
0.39
0.43
0.59
0.63
0-55
0.74
9

1.00
0.37
0.28
0.40
0.51
0.54
0.37
0.31
10

59

60

Multiple Regression Analyses

 

 

 

figpendent Independent Variable R square
Variable
3 “0506070809010 0.9425
3 4,5 ("Best Equation")* 0.9422
3 9010 0.5638
3 809910 0.7124
3 79809.10 0.7892
11 12.13.14.15,16,17 ' 0.2824
11 13,14 ("Best Equation")* 0.2501
11 16.17 0.1621
11 15.16.17 ' 0.1979

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables
did not contribute significantly (0.05 level) to the equation.

61

Appgndix D
Scotch pine provenance test No. 15-62.-- Simple

correlation coefficients and multiple regression analyses
of height and annual increment for both source means and
individual tree data.

Plantation MSFGP 15-62
Scotch pine provenance test

1. Source means analyses (46 sources)

Key to Charactgrs

62

 

 

Variable Date Description of Variables
Number ieasured

1 -- source number

2* 9/19/68 height 1968 (ft. X 10)

3 10/20/68 height 1968 (ft. X 10)

4 10/20/68 height 1967 (ft. X 10)

5 10/20/68 ‘height 1966 (ft. X 10)

6 10/20/68 height 196~ (ft. X 10)

7 10/20/68 height 196 (ft. X 10)

8 10/20/68 height 1963 (ft. X 10)

9 1961 nursery height 1961 (cm)
10 1962 nursery height 1962 (cm)
11 —- increment 1968 (cm)

12 -- increment 1967 (cm)
13 -- increment 1966 (cm)
14 -- increment 1965 (cm)
15 -- increment 1964 (cm)
16 -- increment 1963 (cm;
_;7 -- 1pcrement 1962 (cm

 

*This measurement based on mean of 4-tree plot.
others are based on the tallest tree in the plot.

 

Statistics on Variables Transformed to Meters

All

 

 

 

Variable ,mEgn Standard Deviation
Number _1_
“*2 1.302 0.354

3 1.454 0.339

4 1.025 0.296

5 0.698 0.194

6 0.475 0.132

7 0.317 0.085

8 0.226 0.062

'9 0.044 0.011

10 “0.151 0.043

11 0.429 0.109

12 0.328 0.109

13 0.222 0.067

14 0.158 0,057

15 0.092 0.032

16 0.075 0.060
_17 0.106 ___ 0.034

 

Simple Correlation Coefficients

63

 

 

 

Variable
2 1.00
3 0.96 1.00
4 0.94 0.99 1.00
5 0.90 0.98 0.99 1.00
6 0.87 0.95 0.97 0.98 1.00
7 0.84 0.92 0.93 0.95 0.96 1.00
8 0.77 0.85 0.86 0.89 0.90 0.95 1.00
9 0.55 0.46 0.43 0.37 0.31 0.35 0.30 1.00
10 0.67 0.60 0.58 0.50 0.45 0.47 0.38 0.91 1.00
11 0.96 0.97 0.94 0.90 0.87 0.86 0.79 0.52 0.65
12 0.95 0.96 0.95 0.89 0.86 0.83 0.74 0.52 0.67
13 0.89 0.94 0.94 0.94 0.87 0.86 0.79 0.45 0.54
14 0.77 0.83 0.86 0.87 0.90 0.73 0.67 0.21 0.35
15 0.75 0.82 0.82 0.81 0.81 0.82 0.62 0.35 0.52
16 0.31 0.44 0.47 0.55 0.60 0.63 0.75 -0.36 -o.33
17 0.68 0.63 0.60 0.52 0.48 0.5 0.40 0.86 0.99
2 3 4 5 6 7~ 8 9 10
11 1.00
12 0.93 1.00
13 0.89 0.89 1.00
14 0.74 0.77 0.74 1.00
15 0.77 0.77 0.76 0.65 1.00
16 0.34 0.28 0.42 0.44 0.25 1.00
17 0.66 0.70 0.55 0.38 0.56 -0.31 1.00
a. 11 +12 13 14 15 A 16. 17 .
‘y Multiple Regpession Analyses _
Dependent Independent.Variable R square.
Variable
3 “9576070809910 0.9929
3 4,6 ("Best Equation”)* 0,9922
3 9.10 0.4128
3 8.9.10 0.8310
11 12913914015016917 0.9038
11 12,13 ("Best Equation")* 0,8924
11 16.17 1 0.7712
_;;g 515.16g17 0:81gg__

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables
did not contribute significantly (0.05 level) to the equation.

‘2. Individual-tree analyses

Key_to Characters

64

 

 

Variable Date Description of Variables
flpmber Measured
1 -- tree number
2 10/20/68 mean height of plot 1968 (ft.:X 10)
3 10/20/68 height 1968 (ft. X 10)
4 10/20/68 height 1967 (ft. X 10)
5 10/20/68 height 1966 (ft. X 10)
6 10/20/68 height 1965 (ft. X 10;
7 10/20/68 height 1964 (ft. X 10
8 10/20/68 height 1963 (ft. X 10)
9 -- increment 1968 (cm)
10 -- increment 1967 (cm)
11 -¢ increment 1966 (cm)
12 -- increment 1965 (cm)
131 -- increment 1964,(cm)

 

 

 

 

 

Statistics on Variables Transformed to Meters

 

Variable Mpgp Standard Deviation
Number
2 1.278 0.370
3 1.420 0.397
4 0.996 0.298
5 0.676 0.202
6 0.459 0.140
7 0.311 0.094
8 0.221 0.072
9 0.424 0.116
10 0.321 0.112
11 0.217 0.080
12; 0.147 0.066
13_, 0.909 1 ’0.041

 

Simple Correlation Coefficients

 

 

65

 

 

Variable
2 1.00
3 0.90 1.00
4 0.87 0.98 1.00
5 0.82 0.94 0.97 1.00
6 0.77 0.88 0.92 0.96 1.00
7 0.70 0.79 0.82 0.86 0.92 1.00
8 0.55 0.64 0.67 0.72 0.80 0.91 1.00
9 0.84 0.90 0.80 0.73 0.67 0.60 0.48 1.00
10 0.83 0.92 0.90 0.78 0.72 0.62 0.48 0.82 1.00
11 0.74 0.83 0.85 0.86 0.67 0.57 0.44 0.67 0.71
12 0.64 0.76 0.79 0.81 0.82 0.53 0.40 0.57 0.64
13 0.62 0.68 0.69 0.70 0.70 0.69 0.33 0.54 0.58
2 3 4 5 6 7 8 9 10
11 1.00
12 0.62 1.00
13 0.54 0.52 1.00
11 12 13
‘; Multiple Regpession Analyses
Dependent Independent Variables R square
.12222219
3 “95,607!8 0097,44
3 4,5 (”Best Equation")* 0.9741
3 8'7 0.6581
6,7,8
3 0.7947
3 5'6'7'8 0.8912
9 10,11,12,13 0.6942
9 10,11 (”Best Equation")*. 0.6509

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding.
did not contribute significantly (0.05 level) to the equation.

Deleted variables

66

Appendix E
Scotch pine provenance test No. 17-62.-- Simple

correlation coefficients and multiple regression analyses
of height and annual increment for both source means and
individual tree data.

67

Plantation MSFGP 17-62
Scotch pine provenance test

1. Source means analyses (51 sources)

Key to Characters

 

 

 

 

Variable Date Description of Variables
Nppber Measured ___

1 -- source number

2 4/06/64 height 1963 (in. X 2)

3 6/30/65 height 1965 (in.)

4 10/01/68 height 1966 (ft. X 4)

5 10/01/68 height 1967 (ft. X 4)

6 10/01/68 height 1968 (ft. X 4)

7 1961 nursery height 1961 (cm)

8 1962 nursery height 1962 (cm)

9 -- increment 1968 cm)

10 -- increment 1967 cm)

11 -- increment 1966 (cm

12 1. We -- 7 mean increment 1964 and.1965 (cm)
...1; -- .1_inazsm2ni_1222_ism)

Statistics on Variables Transformed to Meters-:

 

 

Variable ‘Mggp Standard Deviation

Number
2'L 0.221 0.047
3 0.602 0.129
4 0.859 0.176
5 1.156 0.224
6 1.578 0.300
7 0.043 0.001
8 0.145 0.043
9 0.421 0.084
10 0.298 0.058
11 0.257 0.057
12 0.381 0.096,

__13» 0.1027 0.034

 

Simple Correlation Coefficients

 

68

 

 

Variablg
2 1.00
3 0.80 1.00
4 0.79 0.98 1.00
5 0.81 0.96 0.98 1.00
6 0.82 0.93 0.96 0.99 1.00
7 0.54 0.42 0.44 0.47 0.62 1.00
8 0.61 0.53 0.53 0.56 0.62 0.92 1.00
9 0.78 0.77 0.81 0.87 0.93 0.61 0.69 1.00
10 0.72 0.71 0.75 0.85 0.89 0.49 0.56 0.90 1.00
11 0.61 0.75 0.88 0.87 0.86 0.39 0.44 0.75 0.70
12 0.59 0.96 0.93 0.89 0.85 0.31 0.41 0.65 .0.60
13 0.62 0.54 0.54 0.58 0.62 0.87 0.99 0.69 0.57
2 3 4 5 6 7 8 9 10
11 1.00
12 0.71 1.00
13 0.45 0.43 1.00
_1 Multi le Re ession Anal ses __
Dependent Independent Variables . R square
Variable
‘7— 2.3.4.5773 0.9917“
6 4,5,8 ("Best Equation")* 0.9913
6 7,8 0.3917
6 2,7,8 0.7047
9 10,11,12,13 0.8860
9 10.11.12 ("Best Equation")* 0.8842
:9nm 12113 7 0.6379.

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding.
did not contribute significantly (0.05 level) to the equation.

Deleted variables

2.

Individual-tree analyses (425 trees)

Keyflto Characters

69

 

 

 

 

Variable Date Description of Variables
Number Measured

1 -- “tree number

2 4/06/64 height 1963 (in. X 2)

3 6/30/65 height 1965 (in.)

4 10/01/68 height 1966 (ft. X 4)

5 10/01/68 height 1967 (ft. X 4)

6 10/01/68 height 1968 (ft. X 4)

7 10/01/68 stem dieback (0=none, 1=some dieback)

8 -- mean increment 1964 and 1965 (cm)

9 -- increment 1966 (cm;

10 -- increment 1967 (cm ,
_1}7 -- increment 1268 (pm)

Statistics on Variables Trénsformed to Meters 1 -

 

 

 

 

 

Variable Mggp Standard Deviation
Number
"'2 "" 0.216 07077?—
3 0.596 0.205
4 0.854 0.268
5 1.148 0.333
6 1.564 0.425
7* 0.289 0.958
8 0.380 0.170
9 0.257 0.122
10 0.295 0.102
.11 0151; _L_i____0"‘ 1 1'
' SimpleCorrelation Coefficients
Variable
2 1.00
3 0.62 1.00
4 0.60 0.90 1.00
5 0.57 0.85 0.96 1.00
6 0.55 0.80 0.91 0.97 1.00
7 -0.01 -0.22 -0.29 -0.28 -0.26 1.00
8 0.32 0.94 0.83 0.78 0.73 -0.27 1.00
9 0.26 0.29 0.68 0.68 0.65 -0.26 0.24 1.00
10 0.30 0.42 9.53 0.73 0.78 —0.15 0.38 0.44 1.00
11 0.34 0.42 0.49 0.60 0.78 -0.13 0.36 0.37 0.66
2 3 4 5‘ 6 7 8 9 10

*Not transformed

70

 

 

 

 

__, Multiple Regpessign Analyses Jr
Dependent lndependent Variable . R square
Variable
2.3.4.5.? 0.9499
6 2,4,5 9'best Equation“)* 0.9499
6 2.3 0.6428
6 2,3,4 . . 10.8283
6 7 0.0689

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables ,
did not contribute significantly (0.05 level) to tne equation.

71

Appendix F
White pine provenance test No. 3—60.-- Simple

correlation coefficients and multiple regression analyses
of height and annual increment for both source means and
individual tree data.

Plantation MSFGP 3-60
White pine provenance test

1. Source means analyses (15 sources)

‘_Key 39 Characters

72

 

 

 

 

 

 

 

Variable ’Date Description of Variables
Number Measured
1 source number
2 11/16/61 height 1961 (in. X 2)
3 7/24/62 height 1962 (ft. X 10)
41964 height 1964 (cm)
5 9/16/65 height 1965 (in.)
6 10/13/66 height 1966 (ft. X 10)
7 10/19/67 height 1967 (ft. X 10)
8 10/09/68 height 1968 (ft. X 4)
9 1960 height in nursery 1960 (cm)
10 -- increment 1961 (cm)
11 -- increment 1962 (cm)
12 -- increment (mean)1 cm763 and 1964 (cm)
13 -- increment 196 5(
14 -- increment 1966 (cm)
15 -- increment 1967 (cm)
__;6 -- incrgmgnp 1968 (cmll
Statistics on Variables Transfgpmed to Metepg
Variable Mean Standard DeViation
Npmber _l_
2 0:467 08085
3 0.767 0.124
4 1.727 0.190
5 2.579 0.330
6 3.201 0.285
7 4.131 0.342
8 4.780 0.374
9 0.238 0.065
10 0.229 0.045
11 0.300 0.046
12 0.480 0.041
13 0.851 0.192
14 0.622 0.123
15 0.930 0.132
16 0.645_ 0.149

 

Variable

2

O\OCD'\IO\U'\-F'\JJ

H

11
12

13

1.00
0.97
0.90
0.82
0.86
0.81
0.85
0.86
0.66
0.76
0.62
0.52

14 -0.21

15
16

11
12
13
14
15
16

0.14
0.28
2

1.00
0.72
0.29
0.14
0.38
0.08

Simple Correlation Coefficients

1.00
0.95
0.82
0.91
0.87
0.89
0.83
0.64
0.89
0.70
0.47

-0.09

0.30
0.22
3

1.00

0.4L}
-0010

0.26
0.30

1.00
0.86
0.96
0.92
0.95
0.76
0.60
0.89
0.88
0.50

-0.10

0.31
0.27

1.00

-0.81
-0027

0.43

1.00
0.93
0.78
0.88
0.60
0.70
0.68
0.77
0.86

-0553

0.03
0.41

1.00
0.50

-0-37

1.00
0.93
0.97
0.73
0.58
0.85
0.84
0.65

-O.18

0.24
0.31

1.00

-0.67

1.00
0.92
0.69
0.54
0.86
0.81
0.44
0.04
0.59
0.01

1.00

1.00
0.73
0.56
0.82
0.86
0.58

-0311

0.27
0.40
8

1.00
0.17
0.64
0.53
0.27
0.09
0.21
0.25
9

1.00
0.52
0.41
0.60

—0.52

0.14
0.16
10

73

74

Multiple Regpession Analyses

 

 

 

Dgpendent

 

 

Independent Variables R square
12212216
8 2.3.4.5.6.7.9 0.9786
8 6 ("Best Equation")* 0.9468
8 299 0.7218
8 2.3.9 0.7936
8 2.3.4.9 0.9061
16 10,11,12,13,14,15 0.8020
16 12,15 (”Best Equation”)* 0.7007
16 10.11 0.0266
16 10.11.12 0.1494
16 10,11,12,13 0.2474

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding.
did not contribute significantly (0.05 level) to the equation.

2. Individual-tree analyses (70 trees)

Variable
Number

F‘HFJPH4P*H+JPH4
\OCD'\JO\U'\«P'\JJNHO\OCIJ'\10\Kn-P'WNH

Date
Measured

10/09/68
10/09/68
10/09/68
10/09/68
10/09/68
10/09/68
10/09/68
10/09/68
10/09/68
10/09/68

Keygto Characters
Description of Variables

tree number
mean height of

height

1968 (ft

Deleted variables

plot 1968 (ft. X 4)

I.

height
height
height
height
height
height
height
height

1967
1966
1965
1964
1963
1962
1961
1960

(ft.
(ft.
(ft.
(ft.
(ft.
(ft.
(ft.
(ft.

x><rn4wux><x><

increment
increment
increment
increment
increment
increment
increment
increment

1968
1967
1966
1965
1964
1963
1962
1961

(cm)
(cm)
(cm)
(cm

(cm

(cm)
(cm)

(cm)

Statistics on Variables Transformed to Meters

 

 

 

 

 

 

 

Variable ‘Mgap. Standard Deviatipp
4202221 ._
2 4.916 0.591
3 5.375 0.632
4 4.443 0.624
5 3.520 0.503
6 2.763 0.448
7 1.963 0.370
8 1.366 0.288
9 0.880 0.245
10 0.497 0.158
11 0.272 0.110
12 00932 00195
13 0.923 0.183
14 0.758 0.131
15 0.800 0.148
16 0.600 0.126
17 0.487 0.107
18 0.382 0.130
19 0.225 0.089
Simple Correlation Coefficients
Variable
2 1.00
3 0.84 1.00
4 0.87 0.95 1.00
5 0.84 0.91 0.97 1.00
6 0.80 0.87 0.93 0.97 1.00
7 0.75 0.80 0.85 0.89 0.95 1.00
8 0.67 0.77 0.79 0.82 0.89 0.96 1.00
9 0.56 0.68 0.67 0.71 0.78 0.87 0.93 1.00
10 0.43 0.58 0.56 0.61 0.67 0.74 0.79 0.88 1.00
11 0.45 0.55 0.52 0.52 0.57 0.63 0.68 0.73 0.83
12 -0.06 0.19 -0.11 -0.16 —0.16 -0.13 -0.05 0.05 0.08
13 0.68 0.75 0.74 0.56 0.51 0.46 0.44 0.35 0.25
2 3 4 5 6 7 8 9 10

76

*Simple Correlation Coefficientlecont.)

 

 

 

 

Variable
14 0.46 0.52 0.54 0.53 0.30 0.16 0.01 0.05 0.04
15 0.56 0.62 0.69 0.70 0.64 0.38 0.31 0.18 0.17
16 0.64 0.60 0.70 0.74 0.76 0.75 0.53 0.43 0.36
17 0.56 0.50 0.59 0.59 0.61 0.58 0.55 0.21 0.12
18 0.54 0.58 0.59 0.60 0.66 0.74 0.79 0.82 0.45
19 0.20 0.34 0.35 0.43 0.48 0.52 0.56 0.65 0.73
2 3 4 5 6 7 8 9 10
11 1.00
12 0.12 1.00
13 0.36 0.04 1.00
14 0.05 —0.05 0.39 1.00
15 0.13 -0.18 0.40 0.50 1.00
16 0.31 -0.26 0.34 0.24 0.41 1.00
17 0.17 -0.24 0.39 0.16 0.41 0.43 1.00
18 0.36 -0.01 0.36 0.03 0.14 0.38 0.26 1.00
19 0.24 -0.01 -0.01 0.02 0.15 0.26 0.01 0.35 1.00
11 12 13 14 15 16 17 18 19
.1 Multiple Regression Analyses I“. __,
Dependent independent Variablgg R square
Vgriable
3 “9506079809010011 0.9201
3 4,7,9 ("Best Equation")* 0.9175
3 10.11 0.3540
3 9.10.11 0.4825
12 13,14.15,16,17,18.19 0.1413
12 16 ("Best Equation)* 0.0705
12 18.19 0.0000
12 __1le§112 30.0634

 

 

*Determined by stepwise deletion of variables included

in the equation immediately preceeding. Deleted variables

did not contribute significantly (0.05) to the equation.

77

Appendix G
Ponderosa pine provenance test No. 1-62.-- Simple

correlation coefficients and multiple regression analyses
of height and annual increment for both source means and
individual tree data.

78

P antation MSFGP 1:62
Ponderosa pine provenance test

1. Source means analyses (53 sources)

Key to Characters

 

 

VEEiable Date Description of Variables
Number Measured

1 -- source number

2 11/14/64 height 1962 (in.)

3 10/06/66 height 1966 Eft. X 10)

4 12/11/67 height 1967 ft. X 4)

5 10/10/68 height 1968 (ft. X 4) .

6 4/10/64 winterburn 1964 (0=none, 24=severe)

7 11/22/63 height 1963 (in. X 6)

8 1961 nursery height 1961 (cm)

9 1962 nursery height 1962 (cm)
___0 1962 ° b 2 0=no e

 

0=seve e)

Statistics on Variables Transformed to Meters i_1

 

 

 

 

Variable Eggg; §tandard DeviatiOn

‘Number '
2 0.473 0.107
3 1.002 0.195
4 1.227 0.251
5 1.627 0.332
6* 0.363 0.448
7 0.280 0.061
8 0.046 0.011
9 0.155 0.039

__;0* 0.077 0.070

 

*Not transformed

Simple CorrelatiOp Coefficients
Variab1e

2 1.00
3 0.88 1.00
1+ 0.84 0.94 1.00
5 0.78 0.91 0.97 1.00
6 -0.48 -0.53 -0.60 -0.58 1.00
7 0.91 0.86 0.84 0.79 -O.37 1.00
8 -0.05 -0.23 -0.24 -0.28 0.58 0.07 1.00
9 0.49 0.36 0.34 0.27 -0.08 0.54 0.38 1.00
10 -0.52 -0.57 -0.60 -0.58 0.90 -0.41 0.65 -0.04 1.00
2 3 4 5 6 7 8 9 10

79

VMultiple Regpession AnalySes

 

 

._-_

 

Dependent Independent Variables R square
1&212219
5 2,3,4,6,7,8 0.9806
5 3,4,8 ("Best Equation)* 0.9745
5 6.7 0.8217
’5 6.7.8 0.8814‘

 

*Determined by stepwise deletion of variables included
in the equation immediately preceeding. Deleted variables

did not contribute significantly (0.05 level) to the equation.

 

 

 

 

2. Individual-tree analyses
Key to Variables
Variable Date Description of Variables” ”
Number Measured
1 -- tree number
2 9/19/68 mean height of plot 1968 (ft. X 4)
3 10/05/68 height 1968 (ft. X 4)
4 10/05/68 height 1967 (ft. X 4
5 10/05/68 height 1966 (ft. X 4)
6 10/05/68 height 196 2ft. X 4;
7 10/05/68 height 196 ft. X 4
8 10/05/68 height 1963 (ft. X 4)
9 10/05/68 height 1962 (ft. X 4
10 10/05/68 height 1961 (ft. X 4)
11 -- increment 1968 (cm)
12 -- increment 1967 (cm)
13 -- increment 1966 (cm)
14 -- increment 1963 (cm;
15 -- increment 196 (cm
16 -- increment 1963 (cm)
17. -- increment 1962 (cm)~

 

 

Statistics on Variables Transformed to Meters~

Standard Deviation

 

 

Variable

Number flgggi
2 2.201
3 2.596
4 2.012
5 1.512
6 1.145
7 0.792
8 0.561
*9 * 0.423

0.656
0.741
0.580
0.438
0.345
0.240
0.179
-~ 0.135

 

Statistics on Variables Transformed to'Meters (cont.)

 

80

 

 

 

 

Variable Mpgp Standard Deviation
Number

10 0.305 0.108

11 0.508 0.184

12 0.504 0.172

13 0.336 0.112

14 0.353 0.126

15 0.231 0.087

16 0.138 0.062

17 0.118 0.069

Simple Correlation Coefficients

Variables

2 1.00

3 0.94 1.00

4 0.92 0.99 1.00

5 0.89 0.96 0.98 1.00

6 0.87 0.94 0.96 0.99 1.00

7 0.84 0.91 0.93 0.95 0.97 1.00

8 0.81 0.90 0.88 0.90 0.92 0.96 1.00

9 0.79 0.83 0.84 0.85 0.87 0.91 0.96 1.00

10 0.67 0.72 0.72 0.72 0.73 0.78 0.82 0.86 1.00

11 0.89 0.90 0.84 0.79 0.76 0.73 0.72 0.70 0.63

12 0.84 0.88 0.87 0.76 0.74 0.71 0.68 0.69 0.60

13 0.80 0.87 0.87 0.87 0.78 0.72 0.68 0.65 0.56

14 0.78 0.85 0.87 0.89 0.88 0.74 0.68 0.63 0.51

15 0.66 0.73 0.76 0.78 0.79 0.80 0.59 0.55 0.47

16 0.62 0.68 0.69 0.73 0.76 0.77 0.80 0.59 0.49

17 0.49 0.50 0.53 0.54 0.56 0.56 0.60 0.61 0.13

2 3 4 5 6 7 8 9 10

Simple Correlation Coefficient {cont.)

 

81

 

 

Variables
11 1.00
12 0.81 1.00
13 0.76 0.72 1.00
14 0.68 0.66 0.76 1.00
15 0.55 0.57 0.61 0.64 1.00
16 0.56 0.46 0.53 0.60 -.50 1.00
17 0.38 0.40 0.40 0.44 0.33 0.38 1.00
11 12 13 14 15 16 17
‘1 Multiple Regpession Analyses
Dependent Independent Variables R square
Variable
3 4.5.6.7.8.9.10 0.9842
3 4.6 (“Best Equation")* 0,9834
3 9.10 0.6970
3 8.9.10 0.7515
3 7.8.9.10 0.8250
11 12.13.14,15,16,17 0.7342
11 12.13.16 (”Best Equation")* 0.7334
11 16.17 0.3469
11 15016917 0.4254
11 14,15,16,17 0.5132

 

*Determined by stepwise deletion of variables included

in the equation immediately preceeding.

Deleted variables

did not contribute significantly (0.05 level) to the equation.

Appendix H
Scotch pine provenance test No. 15-62.-- Pearce's

analysis of variance and covariance.

82

Plantation MSFGP 15-62

83

Scotch pine provenance test

Key1to Characters

Pearce's Analyses of Variance and Covariance

 

 

Variable Date Description of Variables
Number Measured
1 —- replicate number
2 10/20/68 height 1968 (ft. X 10)
3 10/20/68 height 1967 (ft. X 10)
4 10/20/68 height 1966 (ft. X 10)
5 10/20/68 height 1965 (ft. X 10)
6 10/20/68 height 1964 (ft. X 10)
7 10/20/68 height 1963 (ft. X 10)
150 -- *variable 2 minus variable 7
151 -- *variable 3 minus variable 7
152 -- *variable 4 minus variable 7
153 -- *variable 5 minus variable 7
“154 -- *variable 6 minus variable 7

 

* Indicated subtractions made after transformation to meters.

Statistics on Variables Transformed to Meters
and then to Logarithm of Base 10

 

 

 

 

 

£33319 M W
2 0.13522 0.12391
3 -Q.02113 0.13217
4 -0.18986 0.13218
5 -0-35889 0.13557
6 -0.52801 0.14181
7 -0.68125 0.16108

150 0.05939 0.13217
151 -0.13472 0.14735
152 -0.36966 0.15646
153 -0.65827 0.17434
154 -1,22113 0.22367

84

Analysis of Variance for xgz) Height 1963

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Total 236

 

§5urce of Variation D F. S uare F Value
Replicate 4 0.012495 0.61
Source ‘57 0.043854 2.16**
Between plot 175 0.020296
Total ' 236

Analysis of Variance for X(6) Height 1964
Replicate 4 0.002351 0.17
Source 57 0.039883 2.86**
Between plot ~175 0.013923
Total 236

Analysis of Variance for X§52 Height 1965
Replicate 0. 005037 0.44
Source 57 0.039984 3,53**
Between plot 175 0.011325
Total *236 _

Anglysis of Vgpi gpce f0; X54) Height11966

Replicate 0. 006527 0.75
Source 57 0.044270 5.08**
Between plot 175
Total 236

Analysis df Variance for X13) Hgight 1967 __
Replicate 4 0.007178 0.89
Source 57 0.046423 5.79**
Between plot 175 0.008023
Total 236

Analysis of Variance for X§22 Height 1968
Replicate 4 0.016886 2.66**
Source 57 0.042104 6.64**
Between plot 175 0.006338

Analysis of Covariance for X(é) Height 1964

 

85

 

 

 

 

 

 

 

 

 

 

 

 

T otal 236

 

 

Source of Variation ‘Qyfiy Mean Square F Value
Replicate 4 0.00118602 0.36
Source 57 0.00681865 2.05**
Bavariate (1963 Ht.) 1 1.85692661 557.38**
Between plot 174 0.00333151
Tptal 236

Analysis of Covarianpe for X‘s) Height 1965
Replicate 4 0.00095405 0.18
Source 57 0.01335038 2.52**
Covariate (1963 Ht.) 1 1.06080471 200.39**
Between plot 174 0.0052937?
Total ' 236
1 Analysis of Covarigpce fpp5XL4) Height 1966
Replicate 4 0.00366008 0.63
Source 57 0.01996929 3.44**
Covariate (1963 Ht.) 1 0.51530045 88.71**
Between plot 174 0.00580833

’ Total 236

Analysis of Covariance for X‘j) Height 1967
Replicate 0. 00355779 0. 59“
Source 57 0.02428621 4.05“
Covariate (1963 Ht.) 1 0.36080973 60.17**
Between plot 174 0.00599646
Total 236

Anagysis of Covariance for X(2) Heightl968
Replicate 4 0.01182516 2.39
Source 57 0.0233375? 4.71**
Covariate 1 0.24839533 50.21**
Between plot 174 0.00494750

86
Analysis of Variance for X(154) Ht. 1964-Ht.11963

 

 

Source of Variation D. F. Mean Square F Value
Replicate 4 0.004221 0.87
Source 57 0.006869 1.41*
Between plot 175 0.004869

29.12.; 236

 

Analysis of Variance for X§1§32 Ht. 1965-Ht.31963

 

Replicate 4 0.003231 0.34
Source 57 0.013332 1.41*
Between plot 175 0-009437

Total 236 ,

 

Analvgis of Vapiance for X(152)1Ht.y1966-Htpfi1963

Replicate ' 4 0.006741 0.50
Source 57 0.016602 1.22
Between plot 175 0.013554

223g; 236

 

 

Analysis of Variance for X§1512 Ht.11967:Ht.71963

Replicate 0. 004379 0. 28
Source 57 0.020048 1.30
Between plot 175 0.015382

Total 236

 

Analysis of Vgpigpce for X§1502 Ht. 1968-Ht.1963

 

Replicate 4 0.007245 0.45
Source 57 0.019754 1.24
Between plot 175 0.015901

Total 1236

 

A single asterisk indicates significance at the 0.05
level. The indicated subtractions were made after
transformation to Log Base 10.

Appendix I
Scotch pine provenance test No. 17-62.-- Pearce's

analysis of variance and covariance.

87

88

Plantation.Msfgp 17-62
Scotch pine provenance test

Pearce's Analyses of Variance and Covariance

Key togharacters

 

 

 

 

Variable Date Description of Variables
Number Measured
1 -- replicate number
2 4/06/64 height 1963 (in. X 2)
3 6/30/65 height 1965 (in.)
4 10/01/68 height 1966 (ft. X 4)
5 10/01/68 height 1967 (ft. X 4)
6 10/01/68 height 1968 (ft. X 4)
150 -- * variable é minus variable 2
151 -- * variable minus variable 2
152 -- * variable j minus variable 2
153 -- * variable 3 minus variable 2

 

; Indicated subtractions made after transformation to meters.

Statistics on Variables Transformed to Meters
and Then to Logarithm of Base 10 -

 

 

 

Variable Mean Standard Deviation
EEEEEE
2 -0.69010 0.15318
3 -0.25392 0.16874
4 -0.09233 0.14919
5 0.03971 0.13883
6 0.17641 0.129399
150 0.10907 0.13927
151 -0.05629 0.15772
152 -0.23097 0.19086

153 -0.45503 0.24247

 

89

Analysis of Variance for X(2) Height 1962

 

 

 

Source of Variation 2;§; Mean Square F Value
Replicate 14 0.059140 3.79**
Source 55 0.065414 4.19**
Between plot 355 0.015560

Total 424

 

Analysis of Variance for X(3) Height 1965

Replicate 14 0.099769 5.48**
Source 55 0.074456 4.09**
Between plot 355, 0.018204

Tptal 424

 

 

Analysis of Variance for X(4) Height 1966

Replicate 14 0.061608 4.52**
Source 55 0.067046 4.91**
Between plot 355 0.013643

Total 424

 

Analysis of Variance for X(5) Height 1962

Replicate 14 0.043049 3.70**
Source 55 0.061553 5-29**
Between plot 355 0.011627

Tptal 424 '

 

Analysis of Variance for X§62 Height 1968

 

Replicate 14 0.029076 3.01**
Source . 55 0.058171 6.02**
Between plot 355 0.009658

Tptal 424

 

The above analyses were done on data transformed to Log
Base 10 of height in meters. A single asterisk represents
an F-value significant at the 0.05 level and a double asterisk
represents significance at the 0.01 level.

90

Analysis of Covariance for X(3) Height 1965
Source of Variatlon D.F. Mean Square F Value

 

 

 

 

 

 

 

 

 

 

 

Replicate 14 0.069348 4.69 **
Source 55 0.027611 1.87 **
09*
Covariate (1963 Ht.) 1 1.227543 83.00
Between plot 354 0.014788
29432.1 424
Analysis of Covariance for X(4) Height 1966
Replicate 14 0.045124 4.11H
**
Source 55 0.024639 2.34
Covariate (1963 Ht.) 1 0.956420 87.10**
Between plot 354 0.010980
Total 424
Analysis of Covariancefpr X(5) Height 1967
**
Replicate 14 0.038641 4.02
Source 55 0.023466 2.44**
Covariate (1963 Ht.) 1 0.727153 75.69 **
Between plot 354 0.009606
Total 424
Analysis of Covariance for X(6) Height 1968
Replicate 14 0.029811 3.64**
Source 55 0.023129 2.82**
*4?
Covariate (1963 Ht.) 1 0.529379 64-63
Between plot 354 0.008190
Total 424 '

 

 

The above analyses were done on data transformed to Log
Base 10 of height in meters. including the covariate. The
between plot differences represent between tree differences
because of the one-tree plots in this plantation. A single
asterisk represents an F-value significant at the 0.05 level,
and a double asterisk represents significance at the 0.01
level. As before, no substitutions were needed or made for

missing plots.

91

Analysis of Variance for x(150) Ht. 1968-Ht 1963

 

Source of Variation Dyfiy Mean Square F Value
Replicate 14 0.073104 4.69**
Source 55 0.015762 1.01
Between plot 355 0.015584

Total 424

 

Analysis of Variapce for Xg151) Ht. 1967-Ht. 1963

 

Replicate 14 0.068717 4.32**
Source 55 0.017323 1.09
Between plot 355 0.015896

Total 424

 

Analysis of Varignce for X5152) Ht. 1966-Ht._1963

Replicate 14 0.056812 3.49**
Source 55 0.020343 1.25
Between plot 355 0.016254

Tqigi 424

 

Analysis of Variance for X§153> Ht.p1965-Ht. 1963

Replicate , 14 0.067947 3.56**
Source 55 0.021937 1.15
Between plot 355 0.019094

Total

 

The above data were analysed after being transformed
to Log Base 10 of height in meters. A single asterisk
represents an F-value significant at the 0.05 level. and a
double asterisk represents an F-value significant at the 0.01
level. As before, no substitutions were made or needed for
missing plots.

VITA

Warren Louis Nance was born in San Diego, California.
July 5, 1944. At the age of nine his family moved to Jackson.
Mississippi. There he completed grade school and graduated
from Central High School in 1962. Mr. Nance enrolled the
same year at Mississippi State University, State College.
Mississippi and majored in Forestry. He received his
Bachelor of Science degree in 1966.

Mr. Nance worked for the U. S. Forest Service as research
technician for the Southern Hardwoods Laboratory, Stoneville,
Mississippi before enrolling in the graduate program of the
School of Forestry at Michigan State University in 1968.

Nance is married to the former Charlotte Ann Coulter
and is the father of one child, Robert Louis, age 2. He is

presently employed by the U. S. Forest Service, Institute of

'11

orest Genetics, Gulfport, Mississippi.

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