36 ( 1990) 205-232
Elsevier Science Publishers B.V., Amsterdam Forest Ecology and Management,
205
Geographic variation in growth and phenology of
seedlings of the Abies proceralA. magnifica
complex
Frank C. Sorensen 1, Robert K. Campbell 1 and Jerry F. Franklin2 1
USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR 97331 (U.S.A.) 2College ofForest Research, AR-10, University of Washington, Seattle, WA 98195 (U.S.A.) (Accepted 3 July 1989)
ABSTRACT
Sorensen, F.C., Campbell, R.K. and Franklin, J.F., 1990. Geographic variation in growth and phen­
ology of seedlings of the Abies procera/A. magnifica complex. For. Ecol. Manage., 36: 205-232.
Seedlings whose source origins extended over 12 of latitude (about 1300 km), 1800 m of eleva­
tion, and 250 km of longitude were grown for three years at Corvallis, Oregon, U.S.A. The sampled
area included an interfertile complex of taxa, noble fir (Abies procera Rehd. ), Shasta red fir (A. mag­
nifica var. shastensis Lemm.) and California red fir (A. magnifica A. Murr.) from north to south.
Size and phenological traits were measured in a common garden test, and analyzed to investigate the
pattern of geographic variation.
Division of the complex into three regions accounted for essentially all the latitudinal variation and
strongly indicated a stepped cline. Elevation and longitude contributed lesser amounts of source vari­
ation. Lack of fit to the regression model indicated that other local factors also were important.
Change in mean elevation of the sample sites with latitude was linear and closely followed Hopkins'
'bioclimatic law'. Northern sources had the greatest relative elongation rates. Source variation within
taxa was smaller than for comparable geographic ranges of some other western conifers. Based on
field observations Shasta fir had been regarded as highly variable, but in this test its genetic variability
was not greater than that of noble and California red firs. Genetic variance, estimated from families­
in-locations and based on seedling traits, indicated ample opportunity for genetic gain.
°
INTRODUCTION
Noble fir (Abies procera Rehd.), Shasta red fir (A. magnifica var. shasten­
sis Lemm.), and California red fir (A. magnifica A. Murr.) form an impor­
tant interfertile complex of western conifers. The natural range of the com­
plex is a relatively narrow band (about 200 km maximum width at any one
latitude) extending about 1300 km (roughly 36 ° N to 48 ° N) along the Pacific
coast (Powells, 1 965, pp. 16-18, 25-30).
Noble fir is the northernmost representative of the complex. It generally
206
F.C. SORENSEN ET AL.
occupies middle- to high-elevation sites (1000-1700 m) in the Cascade Range
from about 44°N (central Oregon) to about 48°N (northern Washington).
It also occurs in patches at somewhat lower elevations in the Coast Range of
southwest Washington and northwest Oregon. Shasta fir occurs in northern
California and in the southern Oregon Cascade Range south of 44°N at ele­
vations of 1400-2000 m. Shasta-fir populations are absent from the northern
and central Sierra Nevada, but populations with at least some similar char­
acteristics (e.g. exserted bracts) reappear in the southern end of the range.
Typical California red-fir populations occur in the Shasta-fir range, but the
former is the sole representative of the complex in the central and northern
Sierra Nevada, where its elevational range is generally 1800-2700 m (Frank­
lin et al., 1978).
Distinctions between the three taxa have been based on differences in cone
and leaf morphology and geographic distribution. Particular problems in
identification and questions about the validity of the taxa have arisen in
southern Oregon and the northern California Coast Range, where popula­
tions appear highly variable. Individuals morphologically assignable to two
or even all three of the taxa may be present in some populations (Franklin et
al., 1978 ). Noble fir and California red fir are interfertile and produce off­
spring similar to Shasta fir in cotyledon number (Silen et al., 1965).
This study was done to add to our understanding of relations within the
complex by analyzing genetic variation in seedling growth and phenology. We
wanted specifically to determine ifthe genetic variation along the north-south
axis was better described as a stepped dine or a smooth dine with latitude. A
stepped dine would better support the taxonomic distinction between noble
fir and California red fir with an intermediate form, possibly hybrid. A smooth
dine would suggest a stronger role for selection along a major environmental
gradient related to latitude. We also wished to determine if genetic variation
is associated with elevation or distance from the crest of the mountains. The
hypothesis that the latitudinal trend is a function of selection would be sup­
ported by evidence that variation is related to elevation and other environ­
mental indexes.
MATERIALS AND METHODS
Included in the test were 156 families from 43 locations. Cones for loca­
tions 1-37 (Table 1) were collected by one of us and by several cooperators
of the USDA Forest Service, National Forest Administration, in Oregon and
Washington in 1967 and 1968, depending upon location. Collections were
generally made during good-to-bumper seed crops at the specific locale. Har­
vested cones were brought to Corvallis, Oregon, where the seed lot for each
tree was carefully extracted by hand. Filled seeds were identified from X-ray
plates and were stored at -13°C until used in the test. Cones for locations
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
207
TABLE 1
Location information for the seed origins
Location number
and name•
Elevation
(m) Latitude
(N)
Longitude
(W)
Cresth
(km)
Families<
<n) I Stevens Pass 2 Cedar River
3 Burley Mtn.
4 Red Mtn.
5 Yacholt Burn
6 Mt. Defiance
7 Tillamook Burn
8 Government Camp
9 Post Camp
10 Mt. Wilson
11 South Fork Mtn.
12 Graham Pass
13 Monument Peak
14 Snow Peak
15 Bingham Ridge
16 Iron Mtn.
17 Bear Pass
18 Bunchgrass Mtn.
I 9 Indian Ridge
20 Winchester
21 Gold Lake
22 WolfMtn.
23 Willamette Pass
24 Logger Butte
25 Reynolds Ridge
26 Windigo Pass
27 Black Rock
28 Hershberger Mtn.
29 Abbott Butte
30 Cavern Creek
31 Crater Lake Park
32 Fiddler Mtn.
33 Mt. Baldy
34 Bigelow Lake
35 Sanger Lake
36 Trail Mtn.
37 Mendocino Pass
38 Monarch Mine
39 Bunker Hill Lookout
40 Bunker Hill
41 Packsaddle Pass
42 Bourland Mtn.
43 Rabbit Meadow
975 490 1525
1220
1160
1220
855
1265
1295
1450
1480
1370 1220
1280
1295
1415
1220
1370
1220
1525
1540
1615
1370 1675 1600
1645
1645
1770
1675
1585
1935
1450
1830
1740
1525
1310
1830
1995
2195
2040
2165
2225
2345
47°45'
47°25'
46°25'
45°55'
45°49'
45°37'
45°27'
45°18'
45°12'
45°05'
45°05'
44°55'
44°42'
44°38'
44°36'
44°24'
44°19'
44°19'
44°00'
43°49'
43°38'
43°37'
43°36'
43°34'
43°24'
43°21'
43°10'
43°02'
43°57'
42°54'
43°53'
42°15'
42°15'
42°05'
41°55'
41°27'
39°45'
39°36'
39°03'
39°03'
38°45'
38°06'
36°42'
121°07'
121°45'
121°52'
121°50'
122°09'
121 °43'
123°35'
121°44'
121°31'
121°40'
122°14'
121°59'
122°19'
122°35'
121°55'
122°09'
122°17'
122°04'
122°16' 122°07'
122°04'
122°13'
122°04'
122°21'
122°30'
122°10'
122°28' 122°28'
122°33'
121°59'
122°08'
123°47'
122°17'
123°22'
123°39'
123°37'
122°53'
120°40'
120°23'
120°22'
120°10'
119°56'
118°52'
1
23
38
12
25
-I
121
4
- 13
3
46
16
42
62
8
25
33
21
34
II
4
21
0
13
32
9
34
32
32
-15
-2
129
5
91
116
127
233
50
22
22
19
43
51
6
5
2
6
2
6
3
3
3
3
3
3
3
3
3
3
3
3
3
2
3
3
3
3
3
3
3
3
4
4
4
3
3
3
1
3
1
6
7
7
5
7
6
Regiond l
1
I
I
I
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
•Location name indicates the nearest significant geographic feature; locations 1-5 are in Washington, 6-34 in Oregon and 35-43 in California. bDistances are shortest straightline to the crest of the Cascade-Sierra chain; negative value indicates east of Cascade crest. <Families are the number of open-pollination single-tree seedlots representing each seed origin. d Regions correspond approximately to the three taxa, 1=noble fir, 2=Shasta fir, and 3=California red fir. 208
F.C. SORENSEN ET AL.
38-43 were collected in 1973 and seeds extracted and cleaned by personnel
at the USDA Forest Service, Institute of Forest Genetics, Placerville,
California.
Experimental design for the seedling test was a randomized complete block
with 156 four-tree family rowplots and five blocks. Seed spots were on 10.2
cm (4 in) centers. Seedling beds, which were raised cold frames, were sown
14 seeds across the bed- each row including three 4-tree plots oftest seedlings
and two 1-tree borders. Two border rows were planted at each end of the
blocks.
The test was established at Corvallis, OR, latitude 44°34'N, elevation 75
m. Pregerminated seeds were sown to give full stocking and to eliminate pos­
sible seed storage and age effects on rate of emergence. There was no resow­
ing. Seedling survival was 96.7% at the end of the 3-year nursery test. Obser­
vations or measurements were made on one seed trait and several seedling
growth and phenological traits. In all, 22 directly measured or derived traits
were analyzed (Table 2).
Because we wished to compare the alternative hypothesis that genetic vari­
ation was stepped clinal vs. clinal, the data were analyzed in a classification
model (hierarchal analysis ofvariance (Snedecor and Cochran, 1967, p. 285))
TABLE 2
Measurement units and symbols (in parentheses) for measured and derived growth and phenological
traits observed in a 3-year common-garden nursery test of noble-fir California-red seedlings
Cotyledon number (COT)
Date of bud burst (BB)"
number of cotyledons per seedling
data of first appearance of green needles between scale of
terminal bud; observations made every other day
Date of final bud set (BS) date of first appearance of bud scales on terminal bud; if a
seedling second-flushed, the dates of both first (FBS) and final
bud set were recorded; observations made every 7 days
percentage of seedlings within a plot which had second flushing
Second flushing (FL)
of the terminal (FL) or ofsubterminal lateral (LFL) buds;
percentages were transformed to arcsins (Snedecor and
Cochran, 1967, p. 327) using Bartlett's (1947) correction for
zero and I 00 percentages
number of days between bud burst and bud set or between first
Extension period (EP)
and final bud sets
measured in mm from cotyledons to base of terminal bud
Epicotyl length (H I ) measured in mm from ground level to base of terminal bud
Total height (TH) Relative height elongation In total height yearn minus In total height yearn - I; expressed
in cm cm-1 year-1
rate (RHER)
Factorscores (F S)
derived from direct observations (COT, BB, BS, FL, H I , TH) as
explained in the text
•symbols may be identified by year of observation, I, 2, or 3. For example BB2 refers to date of bud
burst in year 2.
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
209
and in a regression model (backward stepwise elimination (Draper and Smith,
1966, p. 177) )
.
Classification model
This phase of the analysis had two purposes: first, to reduce the variation
among correlated traits to fewer dimensions using principal components, and
second, to partition total genetic variation into its hierarchal parts. For the
first purpose, the analysis of sources and families-in-sources provided com­
ponents of variance and covariance (Kempthome, 1957, p. 264 ) By substi­
tuting these components into the standard equation for the product-moment
correlation coefficient, genetic correlations were calculated among the twelve
nonderived growth and phenological traits. Genetic correlation coefficients
indicated a correlated system (Table 3), both among seed sources (above
diagonal) and pooled among families-in-sources (below diagonal). The ma­
trix of genetic correlation coefficients derived from source components of
variance and covariance was used as input in a principal component analysis
(Morrison, 1967). The analysis of variance was based on plot means.
The principal-component analysis transformed the original set of variables
into a new set. The new set included all the variation in the original set; fur­
thermore, one or two of the new variables, the principal components (PCs),
accounted for most of the variation in the original set. Use of a genetic cor­
relation matrix as input ensured that all variables in the original set were scaled
according to their genetic contribution to the total phenotypic variation.
.
TABLE 3
Genetic correlation coefficients for seed sources (above diagonal) and for families-in-sources (below
diagonal)
COT"
BB2
0.967
COT
BB2
0.275
883
0.179
BS1 -0.390
FBS2
0.476
BS2 -0.444
FL2
-0.596
FL3
-0.898
LFL2 -0.291
H,
0.548
TH2
0.463
0.321
TH3
0.811
-0.193
-0.121
-0.045
0.066
-0.587
-0.102
0.536
0.578
0.430
BB3
0.982
0.992
-0.264
-0.125
-0.100
0.025
-0.583
0.030
0.310
0.355
0.253
BSI
0.758
0.743
0.739
FBS2
BS2
FL2
0.011 -0.724
0.850
0.851 -0.038 -0.748
0.863 -0.039 -0.775
0.973
0.641 -0.155
0.424 -0.412
0.138
0.682 1.091
0.651
0.773 0.199
1.000
1.344b 0.794
1.651
2.364
0.430 0.416
0.562
0.510
-0.049 0.167 -0.294 -0.494
0.139 0.231 -0.026 -0.146
0.347 0.462
0.014
0.020
HI
TH3
FL3
LFL2
-0.334
-0.358
-0.324
0.245
0.155
0.839
0.724
0.658 0.424 -0.267
0.226
0.174
0.620 0.375 -0.328
0.174
0.621 0.384 -0.338
0.950 0.844
0.296
0.812
0.007
0.819 0.663
0.569
0.729
0.951
0.612 0.748
0.686
0.484 -0.100 0.143
0.364 0.567
0.758
0.770
0.606
0.689 0.750
0.533
0.022
0.961
0.742
0.850
0.289
0.590
0.633 0.902
1.692
-0.210
1.004
1.442
TH2
•Abbreviations are explained in Table 2. hOverlarge coefficients for FL3 (families in sources) are due to a barely significant family effect and large standard errors. 210
F.C. SORENSEN ET AL.
Transformed factor scores for each plot were obtained for each significant
PC by the equation:
where: Y;n is factor score for the ith PC (i=1-11), the nth plot (n= 1-780),
and eigenvectors having coefficients a;k> for the ith PC and kth original vari­
able, xk; k= 1-1 1 . Factor scores were then analyzed as independent variables
in the analyses of variance (Table 4)
Components of variance derived from the analysis of variance were also
used for our second purpose, to determine how total variance was distributed
among the genetic and experimental effects given in Table 5. This was done
at three levels: (1) proportion of total test variance associated with genetic
effects was determined from the ratio (uS;s + u§ ) /u?, where: u2 indicates
component of variance; F /S identifies families-in-sources; S, sources; and T,
.
TABLE 4
Hierarchical analysis ofvariance used for partitioning source variance into its region, latitudes-in­
regions, and sources-in-latitudes-in-regions components
Sources ofvariation
Blocks
OF
4
Expected mean squares•
a2+ l S6uB
Families
ISS
Sources
42
Regions
2
u2+ SuC/S/L/R + 22.73u§/L/R + 100.94u[,R + 2S4. l 3ui
Latitudes-in-R
7
u2+ SuC/S/L/R + 20.69u§1L/R + 67.S0u[1R
Sources-in-L-in-R
33
u2+ SuC
u2+ SuC1s + l 8.06u§
u2+ SuC/S/L/R + l 7.23u§/L/R
Families-in-S
113
u2+ SuC1s
Experimental error
620
u2
Total
779
•subscripts are: B, blocks; R, regions; L/R, latitudes-in-regions; S/L/R/, sources-in-latitudes-in-re­
gions; F/S/L/R, families-in-sources-in-latitudes-in-regions. The regions encompass approximately 4°
oflatitude and correspond to the three taxa (see text). Latitudes include the sources located between
even degrees oflatitude, for example between 44°00' N and 44°S9' N.
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
211
TABLE 5
Proportions of family- and source-related variation and coefficients of variation for several traits in a nurs­
ery test of seedlings of the noble-fir/California-red-fir complex
7
Traits•
8
Measured
Cotyledon number
0.730
0.949
0.374
0.929
0.007 0
0.123 0.092
Date of bud flush, year 2
0.869
0.910
0.579
0.932
0
0.068
0.055 0.085
Date of bud flush, year 3
0.842
0.927
0.519
0.950
0
0.050
0.056 0.072
Date of final bud set, year I
0.402
0.790
0.784
0.895
0
0.105**
0.090 0.072
Date of first bud set, year 2
0.477
0.921
0.188
0.914
0.007 0.079
Date of final bud set, year 2
0.320
0.638
0.602
0.610
0
0.390
0.231 0.200
Second flushing, terminal bud, year 2
0.262
0.840
0.328
0.589
0
0.411
0.605 0.301
0.434
0.483
0
0.517
0.657 0.448
0
0.371"'
1.163 0.250
0.202 0.066
Second flushing, lateral bud, year 2
0.285
0.785
Second flushing, terminal bud, year 3
0.048**
0.876* 0.355* 0.629*
Epicotyl length, year 1
0.579
0.617
0.762
0.862
0.032 0.106*
0.166 0.261
Total height, year 2
0.352
0.598
0.643
0.717**
0.051 0.232**
0.180 0.188
Total height, year 3
0.421
0.750
0.448
0.623
0
0.157 0.150
0.377
Mean values
Bud burst
0.856
0.918
0.549
0.941
0
0.059
0.056 0.078
Bud set
0.400
0.783
0.525
0.806
0
0.191
0.174 0.113
Height
0.451
0.655
0.618
0.734
0
0.238
0.168 0.200
0.253
0.762
0.447
0.632
0
0.368
0.170 0.099
0.310
0.723
0.559
0.684
0
0.316
0.719 0.520
0.403
0.716
0.548
0.654
0
0.346
0.205 0.187
Midpoint for extension period-I
0.692
0.981
0.184
0.941
0.003 0.056**
0.064 0.027
Midpoint for extension period-2
0.402
0.782
0.522
0.741
0
0.209
0.129 0.101
Midpoint for extension period-I + 2
0.399
0.711
0.668
0.807
0
0.193**
0.105 0.091
Relative height elongation rate, year 2
0.229
0.472
0.941
0.906
0
0.094"'
0.129 0.109
0.143 0.112
Derived
Extension period-I, bud flush
to first bud set, year 2
Extension period-2, first bud set
to final bud set, year 2
Extension period-I
+ 2, bud flush
to final bud set, year 2
Relative height elongation rate, year 3
0.325
0.793
0.701
0.888
0
0.112**
Factor score-I
0.756
0.950
0.437
0.945
0
0.055
0.027 0.032
Factor score-2
0.423
0.746
0.505
0.670
0
0.330
0.095 0.109
•Traits are grouped according to whether they are phenological or growth and whether they are from direct measurement or derived.' "The eight measures of variation in the numbered columns are: ( uMis + u§ ) / u?.
u§ / ( uMis + u§ ) .
I ) Proportion of total variance due to families and sources:
2) Proportion of total genetic variance due to sources:
3) Proportion
of
family
variance
within
regions
due
to
families-in-sources:
( uM/S/L/R + u§/L/R + ultR ) .
uMistLtR /
4) Proportion of source-related variance due to regions: Uk I ( u§/L/R + ul1R +Uk ) .
5) Proportion of source-related variance due to latitudes-in-regions:
6) Proportion
of
source-related
( u§/L/R +ULtR +Uk )
variance
·
7) Coefficient of variation for error mean square:
due
to
ul1R I ( u§1LtR + ultR +Uk ) .
sources-in-latitudes-in-regions:
u§1L/R /
uN /x. 8) Coefficient of variation associated with additive genetic variation estimated from families-in-sources: 4uM1sf.X.
cNumerators in the proportions in these columns are very highly significant (P<0.001) except as indicated: **, P<0.01; *, P<0.05; n.s. P>0.05. dNumerator in the proportions in this column are all nonsignificant, P>0.05. 212
F.C.
SORENSEN ET AL.
total; (2) the proportion of genetic variance associated with sources was cal­
culated as u§/ (uS;s + u§ ); and (3) variance components associated with re­
gions (uT, latitudes-in-regions (u[;R), and sources-in-latitudes-in-regions
(u§;L/R ) were calculated as proportions of the total source-related variance
(u§ ).
Regional classes in the hierarchal breakdown extended about 4° in latitude
and corresponded with the ranges of the three taxa, sources between 36°42'N
and 39°45'N representing California red fir, sources between 41°27'N and
43°49'N representing Shasta fir, and sources between 44°00'N and 47°45'N
representing noble fir (Fig. 1). A class entry in the latitudes-in-regions clas­
sification represented the average of the sources found within a single degree
oflatitude; e.g. sources between 42° and 42°59'N latitude.
Regression model
In the regression analysis, the mean factor scores for the 156 parent trees
for each of the significant principal components were fitted to three location
variables, latitude (L ) , elevation (£), and distance from the Sierra Cascades
I
'.
'
: .....
•'
-_ _,
.
·-
.\
.s
..\
ci-,
'
. \
'
'
''
•F . \'
--- ',
\'
N
I
Fig. 1. Distribution of the sample locations (solid circles with lines) and selected geographic
features (solid squares) in Washington (WA), Oregon (OR), and California (CA). Abbrevia­
tions are MR, Mount Rainer; C, Corvallis (the nursery test site); WP, Willamette Pass; CL,
Crater Lake; ML, Mount Lassen; S, Sacramento; F, Fresno.
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
213
crest (D). There was a strong association between latitude and the elevation
where the species were found. In our sample of locations, calculated local el­
evation (E 1) decreased with increasing latitude according to the equation
E1 = 1571.6-136.7 (L-42.94) ( r= -0.87,DF= 41, P < 0.001)
In the regression analysis, we therefore introduced elevation as deviation (Ed)
from calculated local elevation
Ed = E-E,
The preliminary model in regression analyses included L, L 2, L 3, L 4, Ed,
D, and linear interaction terms. From the preliminary model, an equation in
which all variables significantly reduced sums of squares in factor scores was
selected by backward elimination (Draper and Smith, 1966, p. 67). Lack of
fit of data to the selected equation was tested by use of data from the several
trees collected at each location as 'repeats' (Draper and Smith, 1966, p. 76).
RESULTS
Relationship between sample elevation and latitude
We list 43 sample locations and elevations in Table 1. Zavarin et al. (1978)
give similar information for 40 populations that they sampled for monoter­
pene analyses. Regressions of elevation on latitude for the samples are
Elev= 7210.9-131. l Lat
Elev= 7880.7-145.3 Lat
Elev= 7760.4-143.3 ( ±7.8) Lat
(our Table 1 data), (Zavarin et al., 1978), and (combined data) where elevation is expressed in m, and latitude in degrees. The combined data are plotted in Fig. 2. The relations are linear and significant (P < 0.001). Classification model
Distribution of variation among different genetic levels of sampling is sum­
marized in Table 5 for all traits. Mean values for three important trait groups
- bud burst (2 years), bud set (3 years), and height (3 years) - are included
at the end of the list of measured traits.
Distributions differed among the three groupings. Date of bud burst had a
much larger proportion of total test variance (u? ) associated with genetic
effects than did date of bud set or height (Table 5, column 1). Of the total
genetic variance (u§ +uR15), most was source related (u§) for all traits (Ta­
ble 5, column 2).
The main geographic dimension of distribution for the species complex was
214
F.C. SORENSEN ET AL.
2880
f
i
1940
c •
0
0
0
- 1660
g
!
i!
0
1380
0
·É
ÊoO
•
1100
0
820
540
0
a
Latitude (degrees N.)
Fig. 2. Relation between latitude and elevation for 83 sample locations in the noble-fir/Califor­
nia-red-fir complex. Sample locations:
( 0)
from this study;
( e ),
from Zavarin et al. ( 1 978 ).
Elevation and latitude are on equivalent scales in the graph, as determined from the regression
equation: Elevation= 7760- 1 43.3 ( ± 7.8 ) latitude.
latitudinal. In the ANOVAs, both region and latitude-in-region reflect latitu­
dinal effects. Region accounted for most of the source variation - mean pro­
portions were 0.941, 0.806, and 0.734 for the three groups of traits mentioned
previously (Table 5, column 4). Essentially all variance associated with lati­
tude of origin was explained by regions. In no case did the average variation
among classes oflatitude in each region (Table 5, column 5) exceed the vari­
ation among sources located in the individual classes of latitude (column 6).
The remaining source variance was due to sources-in-latitudes, the differ­
ences among sources within the individual degrees of latitude. This compo­
nent ofvariance as a proportion of total source variance averaged 0.059, 0.191,
and 0.238 for bud flush, bud set, and height, respectively (Table 5, column
6).
Regional relations for seedling height changed with age. At the end of the
first growing-season, southern plants were tallest and northern plants were
intermediate. Relative height elongation rates (RHERs) the next two seasons
favored the northern plants. Southern plants had the lowest elongation rates;
in the 3rd year, for example, RHERs were 0.827, 0.723, and 0.64 1 cm cm-1
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
215
year-' for plants of northern, central, and southern origin, respectively. By
the end of the 3rd growing-season, plants of northern origin were tallest and
those from the southern region were intermediate. Differential elongation rates
indicated that southern plants eventually would have been shortest in the beds
at Corvallis.
The apportioning of source-related variation in height was influenced by
age. At the end of the first year most source-related variation was associated
with latitude; only 10.6% was due to differences among sources within the
same latitude (Table 5, column 6). After two more years, 37.7% of the vari­
ation was due to differences among sources within the same latitude.
The proportion of total genetic variation in plant height associated with
families-in-sources also changed with age (or seedling size). At the end of the
first 2 years, the figure was about 40%, but it dropped to a little over 25%
after the 3rd year's elongation (Table 5, column 2). The additive coefficient
of variation also decreased with seedling age (Table 5, footnote to column 8).
The trait complex analyzed above as individual traits was summarized as
principal components. The genetic correlation matrix for sources, rather than
for families-in-sources, was used as input, because variation among sources
more clearly pertains to genetic variation that is likely to emphasize adaptive
differences among the species. The first two principal components were sta­
tistically significant (P < 0.001), and together they explained 93% ofthe source
variation in the traits (Table 6). Factor scores in the first principal compo­
nent were about 40% more variable (eigenvalue=6.40) than in the second
(eigenvalue= 4.76). Trait communalities (the proportion of a trait's vari­
ance held in common with the factor scores) were calculated as the sum of
the squared loadings for the two PCs. They indicated that the two PCs ac­
counted for most of the variation in all traits (Table 6). Because of errors in
estimates, some genetic correlations were larger than 1 . This contributed to
the one overlarge communality (as1) in the table.
The relation of individual traits and factor scores can be seen by examining
the trait loadings (correlations of observed with created variates) in Table 6.
Factor scores for the first PC (PC-1) are larger the greater the number of
cotyledons and the later the bud burst and bud set, especially for time of first
and final bud sets in the 2nd year. The factor scores are larger for sources with
larger seedlings in years 1 and 2. Factor scores for the second PC (PC-2) are
larger the fewer the number of cotyledons, the earlier the bud burst, and the
later the time of first bud set in the 2nd year. PC-2 is larger for sources that
are taller, especially after the 3rd growing-season, and for sources with more
second flushing.
The variation patterns were quite different for factor scores of the two PCs,
which by definition are not correlated. Genetic variation accounted for more
total variation in PC- 1 (Table 5, 75.6%) than in PC-2 (Table 5, 42.3%). Most
of the genetic variation in PC- 1 was related to source (Table 5, column 2)
216
F.C. SORENSEN ET AL.
TABLE 6
Principal components (PC) with trait, loadings, communalities, and eigenvalues
Trait"
COT
BB2
BB3
BS!
FBS2
BS2
FL2
LFL2
FL3
HI
TH2
TH3
Communality
Loadings
PC-1
PC 2
0.760
0.732
0.738
l.006
0.937
0.617
-0.179
0.747
0.315
0.958
0.869
0.331
-0.627
-0.667
-0.670
-0.007
-0.254
0.743
0.954
0.579
0.870
0.113
0.373
0.838
6.398
53.3
4.762
39.7
Eigenvalue
Percent variation -
0.971
0.981
0.994
l.011
0.942
0.932
0.942
0.893
0.856
0.930
0.894
0.812
93.0
"Trait code as in Table 2.
and most source variation was found among regions (Table 5, column 4 ) .
Experimental error in PC-1 was very small (Table 5, column 7) . Compared
with PC- 1 , more of the variance within regions in PC-2 was due to families­
in-sources (Table 5, column 3 ), and a much larger proportion of source var­
iance was due to variation among sources within classes oflatitude (Table 5,
column 6). The first principal component was therefore more closely associ­
ated with the major regional differentiation among sources, and the second
was more closely associated with local differentiation among sources and
families. The experimental error for PC-2 (Table 5, cv=9.5%) was larger
than for PC-1 (CV=2.7%) .
Regression model
The regression models selected by backward elimination accounted for 85%
of sums of squares for factor scores of PC- 1 and 47% of sums of squares for
PC-2 (Table 7, bottom). In both models, latitude explained most of the vari­
ation, but elevation and distance from the crest, or interactions involving el­
evation and distance, also made minor contributions (Table 7, standard coef­
ficients indicate the relative contributions of variables).
Coefficients for the regression equations are listed in Table 7 (partial coef­
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
217
TABLE 7
Regression analyses of factor scores from principal components
Variable" Principal component l
Variable" Principal component 2
Significance Standard
Partial
coefficient (P< ... )
coefficient
L
Li
LJ
L4
D
-0.4561
0. 0462
0.0068
-0.0010
-0.0089
0.0001
0.0001
0.0001
0.0200
0.0001
- 1.25
0.42
0.41
- 0.29
- 0.30
EL
-0.0002
0.0001
- 0.17
14.8619
0.0001
CONST
L
Li
LJ
L4
D
E
ED
LD
CONST
Partial
coefficient
Significance Standard
(P<... )
coefficient 0.2910
0.2267
-0.0177
- 0.0063
0.0088
-0.0021
0.36E- 04
0.0030
9.0488
0.0010
0.0001
0.0001
0.0001
0.0120
0.0080
0.0070
0.0080
0.0001
0.64
1.66
-0.85
- l.50
0.24
-0.26
0.32
0.28
R2
for PC-1=0.85; probability oflack of fit to model for PC-1 is P<0.001.
to model for PC-2 is P<0.001.
•E =elevation deviation from local elevation in m; D=distance from the Sierra-Cascade crest in km;
L=latitude - 42.94 in degrees; EL, ED, LD=interaction terms including elevation, latitude,or dis­
tance; CONST= constant.
R2 for PC-2=0.47; probability of lack offit
18
-
-15 km
0
40 km
17
I
c 16
•
.,...-·- ·-·-·-
.,,.---- --- ­
c
0
Q.
E 15
0
-------­
u
ii
.!!u
-E
a.
14
.
Q
............ .....
.
........ ... .... ....
.... ......
...
..............___ _
""'·
-
---
-
�-�
---------
13
1 2'
37
38
39
40
41
42
43
44
latitude (degrees N.) 45
46
47 Fig. 3. The relation between values of principal component-1 (scaled on the y-axis) and latitude
and distance from the crest of the Cascade Range for seedlings of the noble-fir/Califomia-red­
fir complex. The lines represent values at mean 'local' elevation associated with the Cascade
crest (--),1 S km east (-·-·-·),and 40 km west (----). See text for determination of'local'
elevation.
ficients). Patterns of source variation for the three arbitrary distances or ele­
vations are illustrated in Figs. 3-5. All effects except that of latitude are lin­
ear, so change in PCs associated with elevation and distance may be directly
21 8
F.C. SORENSEN ET AL.
13 12
11
110
I9
- 150 kmkm
-·-·-
N
40
---
J..
c
8
i
,'
_
_
8
39
38
_
_
...
·
,
,,
"
·
-\
-
"
·
-
·
,
....
...
..
...
·
.,... ---
'
_
41 42 43 44 45
...
40
_
,
,,
,,
'
/, -
- ,-'
latitude (degrees N.)
46
47
Fig. 4. The relation between values of principal component-2 ( scaled on the y-axis ) and latitude
and distance from the crest of the Cascade Range for seedlings of the noble-fir I California red
fir complex. The lines represent values at mean 'local' elevation associated with the Cascade
crest ( -- ) , 1 5 km east ( -·-·-· ) and 40 km west ( ---- ). See text for determination of
'local' elevation.
13
12
11
10
N
----- 200m0 m
-·-·-·
....
. -·-·-·
-200
-
-
!0
··-
·-· -.
Q.
E
;
8
u
·L
CL
9
8
Latitude (degrees NJ
Fig. 5. The relation between values of principal component-2 ( scaled on the y-axis ) and latitude
and elevation for seedlings of the noble-fir /California-red-fir complex. The lines represent val­
ues at mean 'local' elevation ( -- ), 200 m below mean 'local' elevation ( -·-·-·- ) , and 200 m
above mean 'local' elevation ( ---- ). See text for determination of'local' elevation.
interpolated on the figures.
Most of the source variation in PC-1 was associated with latitude and only
minor amounts with distance from the crest (Fig. 3). The effect of elevation
was so small that it was not illustrated. Most of the variation in PC-2 was also
related to latitude. The relation of factor scores with distance from the crest
depended on whether sources were from the northern or southern regions (Fig.
4). Factor scores for sources above the 'local' elevation were consistently larger
than were factor scores for sources below the local elevation (Fig. 5) . In both
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
21 9
models, lack of fit was highly significant; the average deviation of sources
from the model was larger than would be expected given the amount of vari­
ation among trees within sources.
DISCUSSION
Sample distribution and test site
Of the 43 sample locations, 33 were between 41°27 ' N and 45°55 ' N, or
about seven locations per degree oflatitude. North and south of this area, the
sampling intensity was much less, averaging about one sample location per
degree latitude and with no samples between 36°42'N and 38°06'N and be­
tween 39°45'N and 41°27'N. The latter gap is probably the more serious,
because of the generally different performance of sources north and south of
it. These weaknesses in sample distribution will be noted where needed for
clarity.
The test was conducted in only one environment. Different environments
can expose somewhat different patterns of genetic variation (Campbell and
Sorensen, 1978; Worrall, 1983). Worrall's paper indicated that provenance
performance, at least for bud burst, can be quite different at different planta­
tions, but that ranking of provenances stayed consistent. More test sites might
have increased the amount of variation that we observed.
Relation between sample elevation and latitude
To the extent that the sample sites are representative of the main distribu­
tion of the species complex, mean elevation for parent trees changes by 143
m (469 ft) for each degree of change in latitude. The change is linear across
taxa despite the different ecologies of noble and red firs. Compared with other
forest life-zone charts, this rate of change in elevation with latitude is about
1.5 times that indicated for the idealized mixed coniferous forest between the
same latitudes in North America (Wolfe, 1979, fig. 7), about 0.85 times the
gradient given for coastal mainland China (Wolfe, 1979, fig. 5), and about
0.75 times the gradient indicated for mixed coniferous forest in Japan (Wolfe,
1979, fig. 4). Thus, the elevation/latitude gradient for noble-fir/Califomia­
red-fir seems to have an intermediate position between mainland and coastal
or island mixed-coniferous-forest gradients. This may reflect the maritime
influence on the climate of the Cascade/Sierra ranges (Manley, 1945). This
rate of change in elevation zone with latitude also indicates control by tem­
perature-mediated factors (for example, snow depth and duration); Hop­
kins' ( 1918) bioclimatic 'law' suggests a change in elevation of 400 ft (122
m) for each degree oflatitude.
The confidence interval (P=0.05) about the regression line at the mean
220
F.C. SORENSEN ET AL.
latitude of the samples, 42°33'N, is ±46 m. Three degrees north or south of
the mean latitude the confidence interval is ±65 m. The elevational spread
at any one latitude is thus quite narrow. Temperature, moisture, and snow
regime might limit species distribution at higher elevations through direct
influence on internal physiological or reproductive processes. The healthy de­
velopment of young noble fir in Christmas tree and research plantations at
elevations below its natural range suggests, however, that the species may be
often restricted at lower elevations by competitors effectively excluding it.
Variation with latitude - stepped or smooth dine
Classification of the species complex into northern, central, and southern
regions accounted for most of the source variance. However, three factors
argued against the conclusion that the latitudinal variation was general or
smooth. First, none of the variation in either component appeared to be con­
nected with latitude within regions (Table 5, column 5). Second, although
regional means for the first principal component followed a north-south trend
(x: N=13.79, C=14.55, S= 16.19), means for the second principal compo­
nent did not (x: N= 11.32, C=9.70, S=11.32). Third, a highly significant
(P < 0.001) part of the source variation was found among sources within lat­
itudes and regions (Table 5, column 6). This constituted lack of fit to a model
composed of terms that reflected only latitude, the primary axis of the species
range. Variation among sources that was associated with variables other than
latitude therefore existed within the three regions.
The choice between the alternative hypotheses, smooth vs. stepped dine,
was hampered by the significant lack of fit in both classification and regres­
sion models. A comparison of the relative amounts of variation by the two
models is helpful, but not entirely satisfactory, because classification analysis
is based on plot means and regression analysis on family means. Family means
(regression model) included some error that was removed from plot means
(classification model); however, this mainly affected comparison of pure er­
ror (or families-in-sources) with lack of fit (or sources-in-latitudes) and
therefore should not have been a serious defect in discriminating between
clinal types.
The full regression model (Table 7), which included terms for latitude, el­
evation, and distance from the crest, explained only slightly more of sums of
squares for PC-1 than did the full classification model, 85.2% vs. 84. 7% (Ta­
ble 8). When a restricted model (L, L 2, L 3, L 4) was used in regression, the
model explained less variation than did the 'regions' term in the classification
model, 81.3% vs. 83.6% (Table 8). The classification into regions assumes
no latitudinal trend within regions; any difference among regions is stepped;
therefore, some lack of fit in the full regression model may reflect the fitting
of stepped data to a continuous trend line.
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
221
TABLES
The percent of sums of squares in factor scores accounted for by the several sources of variation in
alternative regression and classification models
Regression Variation
source
Classification Full model Latitude only Full model
DF
%
DF
%
Regions only
Variation source DF
%
Variation source
DF
%
Principal component-I
Regression
6
85.2
4
81.3 Region +
latitude
Lack offit 36 7.0 38 10.8 Sources in
latitude
Pure error 113 7.9 113 7.9 Families
9 84. 7 Regions
2 83.6
33 7.7 Latitude+
40 8.8 sources in latitudes 113 7.6 Families 113 7.6
Principal component-2
Regression
46.5
39.0 Region+
latitude
Lack of fit 34 23.6 38 31.1 Sources in
latitudes
Pure error 113 29.9 113 29.9 Families
8
4
9 42.0 Regions
2 39.4
40 31.4
33 29.0 Latitude+
sources in latitudes
113 28.9 Families
113 28.9 The evidence from PC-2 also does not conflict with the hypothesis of a
stepped cline, except that the central region does not have an intermediate
factor score. The full regression model explained more variation than the full
classification model (Table 8, 46.5% vs. 42.0%), but the additional explained
variation can be attributed to elevation and distance from the crest. The
regression model with latitude alone explained only as much as the 'regions'
term in the classification model (Table 8, 39.0% vs. 39.6%). The restricted
regression model did not explain as much as the full classification model,
though both models included terms only in latitude, because the classification
model assigned five more degrees of freedom to latitude.
Comparison ofvariation in seedling traits with variation in seed weight and
monoterpene composition
Geographic differentiation in the nobel fir-California red fir complex has
been described previously for seed weight (Franklin and Greathouse, 1968a,b;
own unpubl. results, 1968) and for monoterpenes (Zavarin et al., 1978). The
pattern of differentiation in seed weight and in some monoterpenes is similar
to that found in our PC-1 (Fig. 6). (The scale in our Fig. 6 has been inverted
from fig. 3 in Zavarin et al. 1978, so that the slopes of the lines for the three
traits will be in the same direction. The index values for beta-phellandrine are
a measure of similarity to A. procera, larger values indicate greater similar-
222
0
" 20 .. I
J
È
40
c
,g!
60
..
a
al
80
100
F.C. SORENSEN ET AL.
Ci
§.
"'
en
·
1l.,
80
+
60
al
= 40
u..
.... ·•····
.
I
.....L..... . ...K
20
0
i
....
35
37
'X
39
41
43
Latitude (degrees N.)
Fig. 6. Relation between seed weight
45
47
0
( X ), beta-phellandrine index ( + ), factor score 1
( o), and
latitude. Vertical scales have been adjusted to comparable ranges. Each circle represents a mean
for a half-degree interval; crosses represent individual locations. Seed weights are taken from
Franklin and Greathouse ( l 968a, b); beta-phellandrine index has slope reversed from Zavarin
et a!. (1 978).
ity). The agreement at individual latitudes is not perfect; for example the
beta-phellandrene index ( + ) compared with seed weight ( X ) shows a some­
what more gradual change up to 44°N (Fig. 6). Nevertheless, overall geo­
graphic patterns concur quite well. Other monoterpenes show similar as well
as somewhat different patterns of geographic variation (Zavarin et al., 1978),
which is also true of the traits described in this paper and for geographic pat­
terns of genetic differentiation in plants in general (Hamrick and Libby, 1972;
Hillel et al., 1973; Jain, 1976 ) .
Although there is no direct test for comparing fit to stepped vs. smooth
latitudinal trend, subjective evaluation indicates that a stepped cline depicts
well the genetic variation and seems to coincide with the taxonomic descrip­
tion. Other reports on stepped variation have been on a smaller geographic
scale than we have sampled (Snaydon, 1963; Ford, 1964, pp. 72-84; Jewett,
1964; Jain, 1976 ) , but results have been comparable - steps apparent for some
traits adaptive to a sharp environmental change, smooth dines for other traits
that are presumably not adaptive to the sharp change (Antonovics, 1971). It
has been proposed on theoretical bases that leptokurtic seed and pollen dis­
persal associated with strong selection pressure on certain traits or coadapted
clusters of traits are important reproductive and evolutionary processes that
result in this type of differentiation (Jain and Bradshaw, 1966; Kettlewell and
Berry, 1969; Allard et al., 1972; Snaydon and Davies, 1972; Endler, 1973;
Levin and Kerster, 1974; Nagylaki and Lucier, 1981; Loveless and Hamrick,
1984).
It is not clear from the paleobotanical evidence how the latitudinal differ­
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
223
entiation of the California-red-fir/noble-fir complex originated, particularly
the differentiation of the intermediate group, whether the "product of pro­
longed hybridization and introgression between A. procera and A. magnifica,
or as divergence outward from an intermediate central group" (Zavarin et
al., 197 8). This study does not provide additional evidence as to origin; but
agreement of the quantitative morphological traits with the terpene analysis
in indicating steep gradients in some traits at about 40°30'N and 44°N does
suggest that strong selection may be an important factor in maintaining the
pattern of differentiation. Acting with selection could be genetic and ecologic
barriers to gene exchange. Even though the species complex is interfertile,
there seem to be some genetic barriers to crossing, and, at least at the Califor­
nia-red-fir/Shasta-fir transition, there do not appear to be stands containing
clearly identifiable representatives of both taxa (the late W.B. Critchfield,
USDA Forest Service, Pacific Southwest Research Station, personal com­
munication, 1987).
Seed weight and relative height elongation rate
There were large differences in seed weight associated with latitude (Fig.
6), heaviest seeds occurring in the south. All seeds were sown as germinants,
thus they had the same starting date the first year. Average dates of budset the
first year were the same for noble fir and Shasta fir, but about 2 weeks later
for California red fir. California red-fir seedlings had the longest epicotyls at
the end of the first year (4.9 cm vs. 3.8 and 3.4 cm for noble fir and Shasta
fir, respectively), presumably due to larger seeds and longer elongation sea­
son (Grime and Jeffrey, 1965; Pollard and Wareing, 1968).
During the next 2 years, RHER decreased with decreasing latitude, a differ­
ence previously observed by Lines (1979) in British tests and with grand fir
(Abies grandis (Dougl. ex D. Don) Lindl.) in north German nursery evalu­
ations (Kleinschmit, 1986). During the three growing-seasons, California red
fir shifted from tallest to intermediate and noble fir from intermediate to tall­
est. By the 3rd year, California red fir had the lowest RHER. Extrapolations of
3rd-year RHER for two more years indicated that California red-fir seedlings
would be shortest, Shasta fir intermediate, and noble fir tallest in one or two
more years.
Interpretations of the adaptive significance of seed weight and relative
growth rate ( RGR) have suggested that both large seeds and low RGR can be
indicative of more stressful or of more stable but unproductive habitats (Par­
sons, 1968; Baker, 1972; Grime and Hunt, 197 5). In our nursery test, the
lower RHER (in cm cm 1 year- 1 ) of California red-fir seedlings was not the
result of a shorter elongation season, at least as measured in the 2nd year
(elongation season was not determined the 3rd year), but of a real reduction
in rate of elongation. Climatic data for habitats within the sample range are
-
224
F.C. SORENSEN ET AL.
scarce, but generally they indicate milder climate with greater summer pre­
cipitation in the noble-fir range than in the California red-fir range (Powells,
1965, pp. 16-18, 25-30).
Elevational distribution of the species complex had a linear trend with lat­
itude (Fig. 2) that, as discussed earlier, followed bioclimatic 'law' and other
temperate, coniferous-forest life-zone trends. However, the latitude/eleva­
tion adjustment did not result in equivalent climatic habitat over the length
of the transect. The habitats occupied by the species apparently increased in
stressfulness from north to south, and the plants showed adaptation to that
change. In the north, noble fir occupies an elevation band restricted at moist
lower elevation by vigorous competitors and intolerance to shade (Baker,
1949) and at high elevation by cold, snowpack, and short growing-season. In
the south, competitive stress is less because oflower precipitation, which, to­
gether with greater shade tolerance, allows California red fir to form stable,
climax forests (Oosting and Billings, 1943) on sites that would not be avail­
able at the northern end of the range. We suggest that the elevational change
with latitude involves a compromise in the sense that the climatic change
associated with the change in latitude is only partly compensated by change
in elevation. Competition and different ecologies also have roles in the
compromise.
Finally, we draw attention to the complications in use of plant size and
components of growth for evaluating provenance variation. Components of
dry-matter production such as RHER, length of growing-season, etc., have ac­
cumulating importance with age (Pollard and Wareing, 1968). In our test,
RHER was negatively associated with seed weight. The accumulating effect of
RHER on plant height over three years should partly compensate for initial
seed-weight differences. This can be illustrated by comparing the region and
sources-in-latitude-in-region proportions of source-related variance for H1
(0.862 and 0.106, respectively), TH3 (0.623 and 0.377), and RHER3 (0.888
and 0.112). If we assume that Hl primarily reflects seed weight, then the
components of growth (Hl and RHER3) both show more regional differentia­
tion than does the final height measurement (TH3). The conclusion of Pol­
lard and Wareing (1968) suggests that regional differentiation will again in­
crease and approach the distribution shown by RHER. A longer-term test would
have been worthwhile. The example shows that negative association of com­
ponents of growth can increase the difficulty of interpreting patterns of geo­
graphic variation, and that intermediate measurements as well as final size
measurements can be important in such tests.
Location ofthe 'steps'
Our results and those based on chemical constituents (Zavarin et al., 1978)
agree in indicating at least partially stepped dines with latitude. Because of
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
225
the lack of samples, particularly Cascade/Sierra transition samples between
about 40° and 42°15'N, we cannot say the a steep latitudinal dine might not
exist between these latitudes rather than a 'step'. In either case, the steps or
the midpoints of steep sections appear to be close to 40°30'N and 44°N.
Topography of the sampled transect includes parallel north-south coastal
and inland (Cascade Range or Sierra Nevada) mountain ranges north of about
43°45'N and south of 40°30'N and the Klamath Mountains, a complex of
steep, sharp ranges intruding from the coast between those latitudes ( Garrett,
1985). The locations of the steps or steep dines seem to coincide with the
north and south limits of the Klamath Mountain complex. It is not known
whether the Klamath influence is primarily climatic, edaphic, or both.
Source-related variation at common latitudes
In addition to latitude, our source locations were characterized by eleva­
tion and distance from the Cascade/Sierra crest. Compared to the latitudinal
distribution of our samples (about 1300 km), the distribution of samples in
the other dimensions was small, particularly if elevation was adjusted for
latitude.
Four sources over 90 km from the crest between 41°27'N and 42°15' N
(Fig. 1 ) did not deviate more than others from the general north/south trends,
nor were they associated with increased variance among locations-in-lati­
tudes. Two other sources were distant from the crest. These were one source
at 45°27'N and a single-family source at 39°45'N. Only the single-family
source seemed to be out of the general pattern.
Despite small sample range in elevation and distance from crest, compared
to latitude, both made significant contributions to regression for the principal
components (Table 7 and Figs. 3, 4, and 5). Furthermore, source variation
associated with locations-in-latitudes was significant for most traits and large
for several ( Table 5, column 6). This was probably best exemplified by PC­
2, for which the location-in-latitude component was almost half as large as
the region component ( Table 5, lines 4 and 6).
We conclude that considerable local geographic variation exists in this spe­
cies complex. Some is associated with distance from the crest and elevation
( upfting, 1967), but a larger proportion is not. The inclusion of the two vari­
ables in the full regression model reduced lack of fit by only one-third. A num­
ber of important geographic variables, such as slope, aspect, landform, shade
profile of nearby mountains, and soil characteristics (Franklin, 1964) were
not recorded for our locations. These variables may be associated with adap­
tive genetic variation in this species complex, just as they are in other Pacific
slope species (Campbell, 1979, 1986). Because the complex grows predomi­
nantly at high elevations, microgeographic variables may be of even greater
226
F.C. SORENSEN ET AL.
importance than they are at lower elevations (Campbell and Sorensen, 1 978;
Sorensen, 1 979; Paule, 1 986).
Zavarin et al. ( 1 978) concluded that California red fir has less among-pop­
ulation variability than does noble fir. Our results show the same, particularly
if the single-family source at 39° 45' N is excluded. Principal component-2,
which expresses in general a large amount of variation among sources within
latitudes, seems to have more variability among sources within latitudes north
of 40°N than south. A point of caution is that only six of our samples, exclud­
ing the single-family source, came from south of 40°N.
Within- and among-source variability
Because the latitudinal dine is stepped with steps coinciding with our re­
gions, partitioning of genetic variance within and among sources is based on
regions, rather than on the species complex as a whole. On the average, total
variance within regions is about equally divided between the two levels: among
sources-in-regions and among families-in-sources. For the two principal com­
ponents, the proportion due to sources was 0.563 and 0.495, respectively (Ta­
ble 5, column 3).
Source variation as a fraction of total variance is smaller for our fir species
than for some other western conifers. The ratios are about the same within
regions of the complex as for sugar pine in southwest Oregon (Campbell,
1 987). A single region in the complex represents about the species range for
California red fir or noble fir, whereas southwest Oregon is only a small part
of the species range for sugar pine. In a sample of Douglas fir (Pseudotsuga
menziesii (Mirb.) Franco) in southwest Oregon, about 70% of total variance
was found among sources (Campbell, 1 986).
Genetic differentiation is often associated with elevation (Worrall, 1 983).
The California-red-fir/noble-fir complex has comparatively little elevational
range, other than that compensated by latitude. This may partly explain the
small source variance.
Genetic variability within the transition zone compared with the pure species
Regions 1 , 2, and 3 coincide fairly well with the ranges of noble fir, Shasta
fir, and California red fir, respectively. Taxonomically, Shasta fir has been
considered a variety of California red fir. In southern Oregon it has been re­
ferred to as a 'morphologically variable complex' (Franklin, 1 965) or as hav­
ing 'highly variable populations' (Franklin et al., 1 978). These statements are
based primarily on field observations over time, from which we infer that the
variety is perhaps more variable genetically than are the pure species.
Increased variability in this region, ifpresent, could be due to hybridization
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
227
between noble fir and California red fir, with continuing genetic recombina­
tion following hybridization and backcrossing (Anderson, 1949, ch. 3; Soule,
1971; Manley, 1 972; Zobel, 1973; Roughgarden, 1979, pp. 237-238), or sim­
ply to more environmental complexity in the Siskiyou Mountains of northern
California and southern Oregon than either north or south of there (Snaydon,
1973; Nevo, 1976; Gregorius et al., 1985 ).
Zavarin et al. (1978) constructed a 'variability index' based on analyses of
several terpenes and concluded that "A. magnifica proved to be appreciably
less variable than A. procera, both within and between populations" and that
the transitional population (Shasta fir)) had about the same variability as
noble fir.
For seedling morphological traits, we could compare within-region varia­
bility at three levels - variation among sources-in-regions, families-in-sources,
and within plots. Variability among source means within regions, based on
examination of Fig. 7, appears to be about the same for all three regions. In
fact, the variance among source means is larger for region 3 than for 1 and 2
if all sources are included, but smaller if the two one-family sources (located
at 41 ° 55 ' N and 39 ° 45'N) are deleted from regions 2 and 3 or if the one­
family source at 39 ° 45'N is considered as belonging to region 2.
The second measure of variability, variation among families within sources,
is also shown in Fig. 7 for two traits. Vertical lines give ranges in family means
e
"
..,..
,..
[
"
•
I
f
Ç
J
45
40
35
30
25
20
15
0
I! I
I
il l
I
P I\ 1 1 1 '.1 !f I
I 11
,,
36 37 38 39 40 41 42 44 45 46 47 48
Latitude (degrees N.)
Fig. 7. Source means (solid dots ) and range of family means (vertical lines ) for each seed
source for two traits: top, date of bud set in year l ; bottom, total height in year 3.
228
F.C. SORENSEN ET AL.
TABLE 9
Within-plot variances for second-year bud-burst and bud-set dates, and for height after I , 2 and 3
years
Trait
Bud-burst date
Bud-set date
Height, I year
Height, 2 years
Height, 3 years Regions1 4.58
22.4
0.95
3.26
5.97
2
3
4.49
18.2
0.99
3.17
5.12
3.08
18.8
1.19
3.08 4.69 1Region numbers l , 2, and 3 represent noble fir (A. procera ), Shasta fir (A. magnifica var. shastensis),
and California red fir (A. magnifica ) , respectively.
for each source. There is no consistent difference among the regions in the
lengths of the vertical lines.
Finally, we determined within-plot variability for several traits. Within-plot
variance included three-quarters of the additive and all the dominance vari­
ance in a test of true half-sib families. If there is a difference in genetic varia­
tion within breeding populations, it should show up in this measure. Within­
plot variances by region are listed for the five traits in Table 9. There is no
evidence that within-plot variability differs among regions.
In summary, this comparison does not show more genetic variability in the
transition zone than elsewhere. It does not provide evidence for hybrid origin
of Shasta fir, or for greater heterogeneity among fir sites in the Klamath­
Mountains/Cascade-Range than north or south of there.
Practical implications
Variance in additive genetic effects, as estimated from families-in-sources,
is quite large, particularly for the size traits (Table 5, column 8). To the ex­
tent that variation in seedling traits reflects the magnitude of variation among
mature individuals, there should be ample opportunity for genetic gain by
selection and testing of material from local populations.
The results ofthis study indicate that environmental factors are not directly
responsible for the current northern range limit of noble fir. Franklin (1965)
stated that "Noble fir does not appear to be limited in the Stevens Pass area
by climate or soils. The trees are healthy, vigorous, and reproducing well in
open areas". Results from our seedling test show no evidence of a change in
performance or a decrease in vigor in plants of the most northern origin (see,
for example, Fig. 7), as might be expected if the northern sources were at or
near an environmental margin. Furthermore, the relation of elevation to lat­
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
229
itude (Fig. 2) indicates that there should be suitable environments for noble
fir beyond its current northern limit.
The lack of evidence for an environmental constraint strengthens the hy­
pothesis that competition and disturbance regimes are key factors determin­
ing the northern range of noble fir. Key ecological characteristics of noble fir
relative to many of its associates are (1) a modest life-span, rarely exceeding
400 years; (2) intolerance, i.e. inability to reproduce under a forest canopy;
(3) slow initial growth rates, particularly in relation to Douglas fir; and (4)
a heavy seed that may be a constraint on long-distance dispersal. Natural
wildfire return intervals seem to be less frequent on the western slopes of the
northern Cascade Ranges than in areas to the south; thus, fires recur at inter­
vals longer than the life-span of noble fir at this edge of its range. Competitors
may also be more effective at reaching and dominating recently disturbed
sites in the wet, mild sites found below 900 m elevation at and to the north of
the current noble fir range. Noble fir can dominate the young stands that de­
velop following disturbance at its northern limits, as in the case of the land
denuded by the construction and operation of the Great Northern Railroad
on the western slopes of Stevens Pass.
It seems unlikely that time since glaciation is a major factor in the current
distribution of noble fir. Suitable sites for its persistence during the last gla­
ciation almost certainly existed in northern Washington. The 11 000 years of
this interglacial period have been sufficiently long and varied (e.g. occurrence
of the hypsithermal maximum) for noble fir to expand its range.
Most recommendations for seed-movement guidelines or breeding-zone
delineation would be premature. Our sampling of locations, particularly in
southern Oregon and northern California, was not intensive enough for such
a purpose; nevertheless, two preliminary conclusions are indicated. First, seed
transfer across the 'steps' (between regions) should be avoided until evidence
from field tests shows it is safe. Steps, or regional boundaries, based on Fig. 6
are tentatively placed at 44 ° N (a little south of Eugene, OR) and about
40 ° 30 ' N (Redding and Lassen National Park, California). The differentia­
tion at 44 ° N appears particularly striking. Similarly, inclusion of selections
from more than one region (more than one taxon) in a common seed or­
chard, or the establishment of seed orchards where intertaxa pollination would
be promoted, also should be avoided. Second, source variation within taxa is
a smaller component of total variation than for some other conifers in the
Pacific Northwest, and it does not seem to be associated with latitude, the
main dimensional gradient. Within a taxon, relatively wide seed transfer north
or south may be possible with small risk. Restrictions may be necessary for
local transfers in elevation or in distance from the crest. Also important may
be lack of fit to the regression model. This indicates that other local factors,
such as aspect, drainage, etc., that we did not quantify may have adaptive
significance for this high-elevation species complex. We recommend further
230
F.C. SORENSEN ET AL.
sampling with experiments designed specifically to evaluate the role that these
factors play in adaption.
ACKNOWLEDGMENTS
R.S. Miles supervised and cared for the nursery test, W.B. Critchfield, R.G.
Petersen, W. Randall, and D.B. Zobel provided reviews. Dr. Zobel also pro­
vided helpful information on growth rate and plant geography. We appreciate
these efforts.
REFERENCES
Allard, R.W., Babbel, G.R., Clegg, M.T. and Kahler, A.L., 1 972. Evidence of coadaptation in
Avena barbata. Proc. Nat. Acad. Sci. USA, 69: 3043-3048.
Anderson, E., 1 949. Introgressive Hybridization. Wiley, New York, 1 09 pp.
Antonovics, J., 1 97 l . The effects of a heterogeneous environment on the genetics of natural
populations. Am. Sci., 59: 593-599.
Baker, F.S., 1 949. A revised tolerance table. J. For., 47: 1 79- 1 8 1 .
Baker, H.G., 1 972. Seed weight in relation to environmental conditions in California. Ecology,
53: 997- 1 0 1 0.
Bartlett, M.S., 1 947. The use of transformations. Biometrics, 3: 39-52.
Campbell, R.K., 1 979. Genecology of Douglas-fir in a watershed in the Oregon Cascades. Ecol­
ogy, 60: 1 036-1 050.
Campbell, R.K., 1 986. Mapped genetic variation of Douglas-fir to guide seed transfer in south­
west Oregon. Silvae Genet., 35: 85-95.
Campbell, R.K., 1 987. Seed zones and breeding zones for sugar pine in southwestern Oregon.
USDA For. Serv. Res. Pap. PNW-RP-383, 1 8 pp.
Campbell, R.K. and Sorensen, F.C., 1 978. Effect of test environment on expression of dines
and on delimitation of seed zones in Douglas-fir. Theor. Appl. Genet., 5 1 : 2 33-246.
Draper, N.R. and Smith, H., 1 966. Applied Regression Analysis. Wiley, New York, 407 pp. Endler, J.A., 1 973. Gene flow and population differentiation. Science, 1 79: 243-250. Ford, E.B., 1 964. Ecological Genetics. Methuen, London, 335 pp. Fowells, H.A. (Compiler ) , 1 965. Silvics of Forest Trees of the United States. USDA Handbook, 27 1 , 762 pp.
Franklin, J.F., 1 964. Some notes on the distribution and ecology of noble fir. Northwest Sci.,
38: 1 - 1 3.
Franklin, J.F., 1 965. Tentative ecological provinces within the true fir-hemlock forest areas of
the Pacific Northwest. USDA For. Serv. Res. Pap. PNW-22, 3 1 pp.
Franklin, J.F. and Greathouse, T.E., l 968a. Identifying noble fir source from the seed itself: a
progress report. In: Western Reforestation. Western Forestry and Conservation Association,
Portland, OR, pp. 1 3- 1 6.
Franklin, J.F. and Greathouse, T.E., l 968b. Seed origin studies - noble-California red fir spe­
cies complex. In: Proceedings, Western Forest Nursery Council. Western Forestry and Con­
servation Association, Portland, OR, pp. 1 1 - 1 6.
Franklin, J.F., Sorensen, F.C. and Campbell, R.K., 1 978. Summarization of the ecology and
genetics of the noble and California red fir complex. In: Joint IUFRO Meeting of Working
GEOGRAPHIC VARIATION IN AB/ES SEEDLING COMPLEX
231
Parties. British Columbia Ministry of Forests, Information Service Branch, Victoria, B.C.,
Vol. 1 , pp. 1 33-1 39.
Garrett, W.E. ( Editor ) , 1 985. Atlas of North America: Space Age Portrait of a Continent. Na­
tional Geographic Society, Washington, DC, 264 pp.
Gregorius, H.-R., Hattemer, H.H., Bergman, F. and Miiller-Starck, G., 1 985. Umweltbelastung
und Anpassungsfiihigkeit von Baumpopulationen. Silvae Genet., 34: 230-241 .
Grime, J.P. and Hunt, R., 1 975. Relative growth rate: it's range and adaptive significance in a
local flora. J. Ecol., 63: 393-422.
Grime, J.P. and Jeffrey, D.W., 1 965. Seedling establishment in vertical gradients of sunlight. J.
Ecol., 53: 621-642.
Hamrick, J.L. and Libby, W.J., 1 972. Variation and selection in western U.S. montane species.
I. White fir. Silvae Genet., 21 : 29-36.
Hillel, J., Feldman, M.W. and Simchen, G., 1 973. Mating systems and population structure in
two closely related species of the wheat group. I. Variation between and within populations.
Heredity, 30: 1 41 -1 67.
Hopkins, A.D., 1 91 8. Periodical
events and natural law as guides to agricnltural research and
practice. USDA Monthly Weather Review, Suppl. 9, 44 pp.
Jain, S.K., 1 976. Patterns of survival and microevolution in plant populations. In: S. Karlin and
E. Nevo ( Editors ) , Population Genetics and Ecology. Academic Press, New York, pp. 49­
89.
Jain, S.K. and Bradshaw, A.D., 1 966. Evolutionary divergence among adjacent plant popula­
tions. I. Evidence and its theoretical analysis. Heredity, 21 : 407-441 .
Jewett, D., 1 964. Population studies on lead-tolerant Agrostis tenuis. Evolution, 1 8: 70-81 .
Kempthorne, 0., 1 957. An Introduction to Genetic Statistics. Wiley, London.
Kettlewell, H.B.D. and Berry, R.J., 1 969. Gene flow in a dine, Amathes glariosa Esp., and its
melanic form. Heredity, 24: 1 -1 4.
Kleinschmit, J., 1 986. Nursery results of the Abies grandis ( Lindi. ) provenance experiment in
Northern Germany. In: A.M. Fletcher ( Editor ) , IUFRO Abies grandis Provenance Experi­
ments: Nursery Stage Results. For. Comm. Res. Devel. Pap., 1 39, pp. 39-58.
Levin, D.A. and Kerster, H.W., 1 974. Gene flow in plants. Evol. Biol., 7: 1 39-220.
Lines, R., 1 979. Natural variation within and between silver firs. Scott. For., 33: 89-1 01.
upfting, E.C.L., 1 967. Abies magnifica, the variety shastensis and the intermediate forms be­
tween the latter and Abies procera. Nor. Skogforsksves., 23: 33-39.
Loveless, M.D. and Hamrick, J.L., 1 984. Ecological determinants of genetic structure in plant
populations. Annu. Rev. Ecol. Syst., 1 5: 65-95.
Manley, G., 1 945. The effective rate of altitudinal change in temperate Atlantic climates. Geogr.
Rev., 34: 408-417.
Manley, S.A.M., 1 972. The occurrence of hybrid swarms of red and black spruces in central
New Brunswick. Can. J. For. Res., 2: 381-391 .
Morrison, D.F., 1 967. Multivariate Statistical Methods. McGraw-Hill, New York, 338 pp.
Nagylaki, T. and Lucier, B., 1 981 . Numerical analysis of random drift in a dine. Genetics, 94:
497-517.
Nevo, E., 1 976. Adaptive strategies of genetic systems in constant and varying environments.
In: S. Karlin and E. Nevo ( Editors ) , Population Genetics and Ecology. Academic Press,
New York, pp. 1 41 -1 58.
Oosting, H.J. and Billings, W.D., 1 943. The red fir forest of the Sierra Nevada: Abietum mag­
nificae. Ecol. Monogr., 1 3: 260-274.
Parsons, R.F., 1 968. The significance of growth rate comparisons for plant ecology. Am. Nat.,
1 02: 595-597.
Paule, L., 1 986. Strategy of choice of Norway spruce provenances for high altitudes. In: D.
232
F.C. SORENSEN ET AL.
Lindgren ( Editor ) , Provenances and Forest Tree Breeding for High Latitudes. Swed. Univ.
Agric. Sci., Dep. For. Genet. Plant Physiol., Rep. No. 6, pp. 33-56.
Pollard, D.F.W. and Wareing, P.F., 1 968. Rates of dry-matter production in forest tree seed­
lings. Ann. Bot., 32: 573-5 9 1 .
Roughgarden, J . , 1 979. Theory o f Population Genetics and Evolutionary Ecology: an Introduc­
tion. MacMillan, New York, 634 pp.
Silen, R.R., Critchfield, W.B. and Franklin, J.F., 1 965. Early verification of a hybrid between
noble and California red firs. For. Sci., 1 1 : 460-462.
Snaydon, R. W., 1 963. The diversity and complexity of ecotypic differentiation within plant
species in response to soil factors. In: Genetics Today, Proc. XI International Congress of
Genetics, The Hague, The Netherlands, Vol. I, p. 1 43.
Snaydon, R.W., 1 973. Ecological factors, genetic variation and speciation in plants. In: V.H.
Heywood ( Editor ) , Taxonomy and Systematics ( The Systematics Association, Special Vol­
ume No. 5). Academic Press, New York, pp. 1 -29.
Snaydon, R.W. and Davies, M.S., 1 972. Rapid population differentiation in a mosaic environ­
ment. II. Morphological variation in Anthoxanthum odoratum. Evolution, 26: 390-405.
Snedecor, G.W. and Cochran, W.G., 1 967. Statistical Methods, Iowa State University Press,
Ames, IA, 6th edn., 593 pp.
Sorensen, F.C., 1 979. Provenance variation in Pseudotsuga menziesii seedlings from the var.
menziesii-var. g/auca transition zone in Oregon. Silvae Genet., 28: 96- 1 03.
Soule, M., 1 97 1 . The variation problem: the gene flow-variation problem. Taxon, 20: 37-50.
Worrall, J., 1 983. Temperature-bud-burst relationships in Amabilis and subalpine fir prove­
nance tests replicated at different elevations. Silvae Genet., 32: 203-209.
Wolfe, J.A., 1 979. Temperature parameters of humid to mesic forests of eastern Asia and rela­
tion to forests of other regions of the Northern Hemisphere and Australia. USDI Geol. Surv.
Prof. Pap. No. 1 1 06, 37 pp.
Zavarin, E., Critchfield, W.B. and Snayberk, K., 1 978. Geographic differentiation of monoter­
penes from Abies procera and Abies magnifica. Biochem. Syst. Ecol., 6: 267-278.
Zobel, D.B., 1 973. Local variation in intergrading Abies grandis-Abies concolor populations in
the central Oregon Cascades: needle morphology and periderm color. Bot. Gaz., 1 34: 209­
220.