An analysis of growth, growth increments, and the integration of growth increments in a fertilizer test of Picea engelmannii in south-central British Columbia - =

JACK MAZE' Department of Botany, The Universio of British Columbia, Vancouver, BC V6T 124, Canada

AND

ALAN VYSE British Columbia Ministry of Forests, 515 Columbia Street, Kamloops, BC V2C 2T7, Canada

Received February 19, 1993

MAZE, J., and VYSE, A. 1993. An analysis of growth, growth increments, and the integration of growth increments in a fertilizer test of Picea engelmannii in south-central British Columbia. Can. J . Bot. 71: 1449- 1457.

This study describes a 3-year study of growth in seedlings of Picea engebnannii planted in south-central British Columbia in 1986. Four different seedlots were used and each was subjected to six different levels of fertilization in the nursery and two on planting in the field; they were planted in three blocks. The seedlots planted as well as the interaction between blocks and the seedlots planted had a significant effect on seedling survival. The seedlot that showed the lowest rate of survival was the one displaced upward approximately 1180 m from its origin. The largest seedlings on planting, and in 1989, were from the same seedlot that showed the lowest rate of survival. Despite having the largest seedlings, that seedlot did not have the highest rate of growth. The greatest amount of variation in size, growth rate, and increments of growth is within each combi- nation of treatments. Fertilization in the field was the experimental factor that had a consistent effect on growth and size, aside from size on planting where seedlot and nursery treatment were important. Field fertilizer treatments affected the integration of increments of growth in height and diameter. This treatment also affects energy flow through plants by its impact on growth rate, thus arguing for a correlation between the flows of energy and information. We are unsure if this correlation is causal or casual.

Key words: growth rate, integration, Picea engelrnannii trials

MAZE, J., et VYSE, A. 1993. An analysis of growth, growth increments, and the integration of growth increments in a fertilizer test of Picea engelmannii in south-central British Columbia. Can. J. Bot. 71 : 1449- 1457.

Les auteurs ont CtudiC pendant 3 ans la croissance de plantules de Picea engelmannii plantees dans le centre-sud de la Colombie-Britannique, en 1986. 11s ont utilisC quatre lots de graines diffCrents, et chacun a regu six intensites de fertilisation en pkpinkre et deux sur le terrain; ils ont CtC plant& en trois blocs. Les lots de graines utilisCs ainsi que I'interaction entre les blocs et les lots de graines utilists, ont un effet significatif sur la survie des plants. Le lot de graines qui montre la survie la plus faible est celui qui a CtC dCplacC en altitude, 1180 m plus haut que son origine. Les plants les plus forts au moment de la plantation, et en 1989, appartiennent au m&me lot de graines qui a montrC le taux de survie le plus faible. Bien qu'il donne les plants les plus gros, ce lot de graines ne donne pas le taux de croissance le plus ClevC. La plus forte variation dans la dimension, le taux de croissance, et l'augmentation de la croissance se retrouvent a 1'intCrieur de chaque combinaison de traitements. La fertilisation aux champs constitue le facteur exphimental qui montre un effet constant sur la croissance et la dimension, independamment de la dimension au moment de la plantation oh du lot de graines; les traitements en pCpiniere sont importants. Les fertilisations aux champs affectent 1'intCgration des augmentations de croissance en hauteur et en diamktre. Ce traitement affecte Cgalement le flux dlCnergie dans la plante par son impact sur le taux de croissance, ce qui suggkre qu'il y aurait une corrClation entre les flux d'Cnergie et l'information. I1 n'est pas certain si cette correlation est causale ou fortuite.

-. Mots clPs : taux de croissance, intkgration, essais sur le Picea engel~nannii.

[Traduit par la rCdaction]

Introduction Studies on the early response of tree seedlings to various fer-

tilizer regimes constitute a common and valuable component of forestry research, since they contribute significantly to making informed decisions on reforestation. These studies focus on such things as survival, size attained, and seedling form as influenced by various treatments including source of seed. Growth rate is usually not a part of such studies, overall size being easier to assess and a more obvious way to evaluate seedling performance. Regardless, a comparison of growth rates is of value, as it allows an analysis of the mechanism whereby overall size is attained. Such an analysis allows an uncoupling of size on planting and growth response in the field. Large seedlings, which may be the result of better response to greenhouse or nursery conditions, may retain a larger size at early stages of establishment but show slower growth rates.

'Author to whom all correspondence should be addressed. Prinwd in Canada / Imprim6 au Ginad;,

In trials based on early testing, such seedlings may be judged, wrongly, to be superior. Annual increments of growth in length or diameter are also usually not part of studies on the response of tree seedlings. Regardless, they are also of poten- tial importance, as they allow testing for variation in year to year response. From such an analysis it can be determined how long a certain treatment has an effect. It would seem that transient effects, especially those expensive to administer, may not be worth the effort and G-xpense of implementation.

There is another feature that can be addressed through the analysis of increments of growth, namely the relationship among the amounts of growth that occur in different years and in different tissues. When addressing the relationship among parts in a biological system it is the nature of integration within that biological system that is being assessed, namely, how do the various parts of that system interact with each other? Is there a pattern to the integration among parts that departs from randomness? Do different treatments have an effect on integra- tion? Integration, or organization,. is.~biolo@iAly important, as

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TABLE 1. Nursery treatments

Amt. of Days Treatment fertilizer" release

"The amount of fertilizer is measured in kilo- grams per 0.76 m'.

it determines many properties of biological systems (Atchley 1987; Maze et al. 1987; Nagel 1961 ; Polanyi 1969; Rosenberg 1985). As well, integration is becoming the focus of studies from different perspectives, e.g., quantitative genetics (Atchley and Hall 1991 ; Atchley et al. 198 1, 1984; Atchley and Rutledge 1980; Cheverud et al. 1983a, 1983b; Leamy and Cheverud 1984; Maze et al. 1992; Venable and Burquiz M 1990) and development (Maze et al. 1986, 1987, 1990; Ray 1990; Scagel et al. 1985b; Zelditch 1987, 1988; Zelditch et al. 1990).

This study thus has two general purposes. The first purpose is to assess the im~act of various treatments in the field and pretreatments in a nursery on the response of seedlings from different seedlots of Engelmann spruce (Picea engeltnannii Parry) in terms of survival, increments of growth, and growth rate. We feel this will add to an understanding of seedling response, since we will be emphasizing the events from which total size emerges. Such a study may also give some insight into the most appropriate combination of seedlot, nursery, and field treatment in reforestation in central British Columbia.

The second purpose is to survey the impact of various treat- ments on the integration among growth increments in different tissues and different years. The focus here will be the change in information expression manifested as integration as effected by experimental -manipulations that modify a phenomenon, energy flow, that may be related to information flow. Plants that have different growth rates will be different sizes, or at a more abstract level, plants that have trapped different amounts of energy. At least some of this energy that is incorporated into plants occurs as the energy of chemical bonds in cell wall constituents. The formation of cell walls occurs under control of the information in a plant, i.e., the means whereby energy is distributed in a plant is under informational (genetic) control. This apparent relationship between energy and information may be abstracted even further through the general statement that as a plant grows and develops, both energy and informa- tion "flow" into cell walls.

The argument for some sort of relationship between energy and information is not unique to this study but seems to be accepted (Hariri et al. 1990; Wicken 1987). However, the nature of that relationship is vague and lacks a clearly stated theoretical reason why it should exist aside from qualitative statements relating the incorporation of chemicals and their bonds (energy), into cell walls that form a specific configura- tion (information) (Banerjee et al. 1990). Regardless, organisms are both information- and energy-processing systems, and attempts to relate information and-energy may give added

insight into the nature of organisms. The basic question we want to answer is whether or not _a change in energy flow will affect information flow as it is &pressed in the integration of the parts of a plant, i.e., their organization.

Materials and methods

Study sire 'The site of this study, British Columbia Ministry of Forests

SX86126K, is in the upper Ross Creek drainage at 1580 m, 25 km north of Anglemont (5Oo34'N, 119"05'W), on the north side of Shushwap Lake. The study site has a neutral aspect and the seedlings were planted in an area subjected to wild fire in 1967, the Mag burn, and windrowed and blade scarified in 1986. This is in the wc2 variant of the Engelmann spruce - subalpine fir biogeoclimatic zone (ESSF) (Krajina 1969).

Source of seedlings Four different seedlots were used in this study: 4020 collected in

1979 from 1200 m, Upper Raft River just south of Wells Gray Provin- cial Park, British Columbia (51°54'N, 1 19"40fW); 4027, also collected in 1979, from 1350 m at Blanket Creek just south of Revelstoke, B.C. (50°45'N, 1 18"501W); 4060 from 952 m at Harbour Lake in the Adams River drainage, B.C., (5 1 "401N, 1 19"20fW), collected in 1979; and 8032 from Birch Island along the North Thompson River in B.C. (5lo45'N, 119O55'W) at 400 m, collected in 1980. These seedlot numbers are those of the British Columbia Ministry of Forests. The last is a seedlot that was shown to grow well in various sites in the ESSF and for that reason was included here, even though its origin is 1180 nl below the study site.

Treatment The seedlings were started in cavities 3 cm in diameter and 13 cm

deep in styroblocks containing 160 cavities in the nursery at Pelton Reforestation Ltd., Maple Ridge, B.C., from seed planted in 1984. Each of the four different seedlots received two treatments, one in the nursery and one on planting in the field. The nursery treatment con- sisted of six different soil fertilizer mixes in which the seeds were sown. These six soil mixtures were made up of various amounts of a slow-release fertilizer (Nutricote 16: 10: 10 N -P-K) with three different release periods (180, 270, and 360 days release). The nursery treatments are in Table I .

The trial was planted as 2 + 0 stock at the study site on 3 September 1986 and was measured on planting and at the end of growing seasons in 1987 - 1989. The planting treatment was fertilized and unfertilized with Osmocote 18:6: 12 NLP-K, 270-day release, at 30 g per seed- ling spread evenly within a 15-cm radius of the seedling. In the field the seedlings were planted in three blocks of 48 rows randomized within each block. There were 20 seedlings per row, each of which consisted of one combination of seedlot, nursery treatment, and field treatment. Rows were 2-3 m apart, and the seedlings within each row were separated by 1 m. The varying distance between rows is the result of planting two rows per windrow trial.

Variables The variables measured were height and diameter at the root collar

on planting and in subsequent years, height increments, and diameter at the root collar. The variables analyzed were seedling survival to 1989, height and diameter in 1986 and 1989, increments of growth in height and diameter for'1987- 1989, and growth rate over the 3 years of the study. Increments in diameter were calculated from diameters measured in different years. We chose increments of growth over size attained at the end of each growing season to avoid the strong correlations between overall size in contiguous years. For growth rate we used relative growth rate (Evans 1972) calculated over the 3 years for which we had data. We did not calculate relative growth rate with time, 3 years in our case, since that would have simply been dividing all values by a-constant and was considered to be an unnecessary extra step. We realize that relative growth rates are usually calculated using dry weights, but:therc appears to be no botanical reason why relative growth.rates.'tannot be calculated using

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other estimators of size increase. There is, as well, the added advan- tage to using lengths and diameters to assess relative growth, since the sampling is nondestructive and the same individual can be measured at different times. This means that growth rate is the property of an individual rather than of a population. Growth rate was considered important, since a positive relationship between plant size and growth rate is not assured, i.e., one cannot assume that the largest seedlings will be those undergoing the fastest rate of growth.

This is a data set consisting of many individuals, over 2500, for which there are two levels of field treatment, six of nursery, and four different seedlots. Many possible comparisons exist: four main effects, six two-way interactions, four three-way interactions, and one four-way interaction. All these were not done for practical reasons. The pro- gram used (SYSTAT; Wilkinson 1988) was not capable of making all comparisons and the data were not sufficient, too few cases, for some comparisons. Thus, we calculated all possible two-way interactions.

Analyses Analysis of variance (ANOVA) was used to assess seedling response

in terms of survival, growth increments, size, and rate. The model used was

where y, the dependent variable, is seedling response (survival, increments, size, or growth rates); B is block; F is treatment in the field; N is nursery treatment; S is seedlot; and e is the error term. The interaction terms are given in parentheses. We had two purposes in mind. The first was to assess the effect of various factors on seed- ling response (survival, increments of growth, size on planting in 1986, size at the termination of the study in 1989). The second was to compare the results from increments of growth in different years or feature measured, height or diameter. This second comparison allowed us to estimate the level of consistency in responses over time.

These ANOVAs were used mainly to describe our results through the statistic ?I' (the ratio SS,,,,, to SS,,,;,,), which apportions the amount of variation accounted for by the factors in the model. An indication of statistical significance was also calculated using the error mean squares as the denominator in determining F-values. This was done for consistency in a data set in which the block tcmm in many ANOVAs was significant.

We also presented a graphical summary of height and diameter on planting (1986) and at the end of the experiment (1989), and growth rate for height and diameter. This was done for each combination of field and nursery treatment and seedlot to present a visual summary of the growth data.

Correlation matrices were the basis for describing the integration among increments of growth in height and diameter for 1987 - 1989. These were calculated for cach combination of nursery and field treatment and seedlot over all three blocks. The decision to combine blocks was the outcome of the death of seedlings, resulting in some combinations of block, nursery and field treatment, and seedlot having too few seedlings, less than 12, to produce statistically stable correla- tion matrices, a prerequisite for calculating valid statistics (Pimentel 1979). Adequate sample size was determined using the program developed by Scagel et al. (1985a).

We wanted to assess the two components of integration: order, the strength of relationships among parts, and organization, the similarity of those relationships (Banerjee et al. 1990). Order gives an indica- tion of within-system predictability. As order increases, the ability to predict one state of the system knowing another increases. Organiza- tion estimates within-system heterogeneity; as the number of compo- nents or types of relationships within a system change, there is a concomitant change in organization. This characterization of integra- tion was derived from the views of Denbigh (1975), who contrasted a crystal, which is ordered but not organized, with a cell, which is organized but not ordered.

As an estimator of order we used the determinant of a correlation matrix, a measure of the values of the Pearson product-moment

TABLE 2. Number of seedlings that survived for each seedlot in each year from 1986

to 1989 .--: .

Seedlot 1986 1987 1988 1989

correlation coefficients along the off diagonals of a correlation matrix. When all variables are perfectly correlated, i.e., have correlation coefficients of 1, the determinant is 0. As the individual correlation coefficients decline in absolute value, the determinant approaches 1. The assumption used is that a highly ordered system will produce a determinant close to 0, whereas less highly ordered systems will be characterized by a determinant greater than 0, the less ordered, the closer to 1.

Organization was estimated using first eigenvectors from a principal components analysis of a correlation matrix. The first eigenvector derived from a correlation matrix is a function of the correlation coefficients along the off diagonal in a correlation matrix, i.e., the more similar those coefficients in sign and value, the more similar the components in the first eigenvector. As the off diagonal elements in a correlation matrix become more different, so too will the compo- nents of the first eigenvector.

To describe the organization in any one combination of treatments, we compared the first eigenvector derived from each treatment with a vector of isometry, a theoretical vector consisting of equal values and one derived from a correlation matrix in which all off diagonals are equal. The statistic to describe organization was the angle between first eigenvectors and a vector of isometry. Such angular c&nparisons were used in studies addressing the impact of shape, an expression of organization (Bryant and Meffert 1988; Creighton and Strauss 1986; Cheverud et al. 1983b; Kohn and Atchley 1988; Maze et al. 1987, 1990).

To analyze our descriptors of integration, we used the ANOVA model

[2] y = constant + F + N + S + e + (F X N) + (F X S) + (N X S)

where J) is either the determinant of the correlation matrices or the angle between first eigenvectors and a vector of isometry, F is field treatment, N is nursery treatment, S is seedlot, and e is error or residual term. The interaction terms are given in parentheses. This allowed us to assess the effect of the various treatments and seedlots on integration.

All analyses were done using SYSTAT 4.1 (Wilkinson 1988).

Results Seedling survival

Table 2 presents seedling survival at the end of each year of the study for each seedlot. T h e maximum potential number of seedlings per seedlot was 720; deviations f rom that number in the year the seedlings were planted in the upper Ross Creek drainage (1986) a re the result of loss in the nursery.

T h e best nursery performer-in terms of survival is seedlot 8032. There is n o appreciable difference among the other three seedlots in terms of nursery survival. There is some seedling loss in all seedlots over the course o f the experiment; the greatest number of seedlings lost is seen in seedlot 8032.

A dissection of the effects o f the various treatments is presented in Table 3 , an ANOVA o f seedling survival for each unique combination o f block, nursery and field treatment, and seedlot. There was a potential fo r 144 such combinations but only 143 were realized, resulting in a n unbalanced design. This was because there were no seedlingskfor the combination

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nursery

FIG. 1. Averages for each field and nursery treatment and seedlot for heights of seedlings on planting and at the end of 1989, and relative growth rate for height. The two rows of numbers on the x-axis indicate field and nursery treatments as follows: the top row identifies field treatments as 1, unfertilized, and 2, fertilized; the bottom row identifies the nursery treatments 1-6 as described in Table 1. Different seedlots are indicated by the four inflection points in the line above each combination of field and nursery treatments, with seedlot 4020 being at the left and seedlot 8032 at the right.

TABLE 3. Analysis of variance for seedling survival as number of seed- lings that survived until 1989, for each combination of block, field, nursery,

and seedlot treatment

Source SS d f o2

B F N S B x F B X N B x S F x N F x S N x S e

NOTE: Terms are as follows: SS, sums of squares; r)', variation accounted for by sources as SS,,,, to SS,,,,,; B, block effect; F, treatment in the field; N, nursery treatment; S, seedlot; B x F, block - field treatment interaction; B x N, block - nursery treatment interaction; B x S, block-seedlot inter- action; F x N, field - nursery treatment inter- action; F X S, field treatment - seedlot interaction; N x S, nursery treatment - seedlot interaction; e , error; +, 0.01 < p < 0.05; +*, 0.001 < P < 0.01.

of seedlot 4020, nursery treatment number two, fertilized in the field in block three because of an inadequate supply of seedlings.

The experimental factors that account for most of the varia- tion in survival are the seedlot and block-seedlot and nursery - seedlot interactions; the first two are statistically significant.

The single largest factor, however, is the error term; the greatest amount of seedling loss is seen within any combina- tion of treatments.

Seedling growth Figures 1 and 2 present a summary of seedling heights and

diameters in 1986 and 1989 and relative growth rate. The double label along the x-axes identifies the fertilizer treatments. The top row is for the treatment applied in the field, in which 1 identifies those seedlings not fertilized and 2 those that were. The bottom row identifis the six nursery treatments presented in Table 1. The four different seedlots are indicated by the four inflection points along a line immediately above the code for each combination of field and nursery treatment. Combining seedlots together for various treatments allows a ready com- parison of both size and growth rate among seedlots. Although using a line results in some loss of accuracy, it does serve to link the four seedlots from any combination of field and nursery treatments together. The field and nursery treatments and seed lots were averaged over the different blocks. This was done for simplicity and clarity; inclusion of the three blocks would have produced appallingly complicated graphs. The y-axis has two different scales. At the bottom is size in centimetres for height (Fig. I ) and millimetres fordiameter (Fig. 2). The top scale is for relative growth rate for 1986- 1989.

From the height data, seedlot 8032 produced the largest seedlings in the nursery and at the study site but was one of the poorest in terms of growth rate, especially those seedlings that were fertilized on planting (Fig. 1). The diameter data give a different picture in that seedlot 8032 did not produce the largest seedlings in the nursery or in the upper Ross Creek drainage. It did, in one instance for the unfertilized and one for the fertilized treatments, produce seedlings with the greatest

- , growth rate in diameter. . - ~ -._ -..

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FIG. 2. Averages for each field and nursery treatment and seedlot for diameter on planting and at the end of 1989, and relative growth rate in diameter. The rows of numbers on the x-axis indicate field and nursery treatments as follows: the top row identifies field treatments as 1, unfertilized, and 2, fertilized; the bottom row identifies the nursery treatments 1-6 as described in Table I . Different seedlots are indicated by the four inflection points in the line above each combination of field and nursery treatments, with seedlot 4020 being at the left and seedlot 8032 at the right.

TABLE 4. Average increments for seedlings based on field treatment for height and diameter

Ht. increments (cm) Diam. increments (mm)

Field treatment 1987 1988 1989 1987 1988 1989

Unfertilized 9.286 4.298 6.566 1.360 1.139 1.576 Fertilized 11.312 8.665 7.893 1.896 1.777 1.873

Table 4 presents average increments of growth in height and diameter for 1987 - 1989 averaged over all experimental factors for each seedlot. Increments i n height tend to decline with time, more uniformly for the fertilizid than the unfertilized, whereas increments in diameter remain more or less constant (Table 4).

ANOVAs of relative growth rate are presented in Table 5, and height, diameter, and increments thereof in Tables 6 and 7. There are many experimental factors in these ANOVAs, and in some cases virtually all are statistically significant. Thus we chose to comment on only the four factors that account for most of the variation in the data. We realize a secure relation- ship between the amount of variation and biological relevance does not exist. However, when there are many different factors in an ANOVA, 10 in our case, some criterion is needed to avoid attributing biological significance to factors that are con- gruent with preconceived notions.

For the relative growth rate for both height and diameter (Table 5), the error term accounts for the greatest amount of

TABLE 5. Analysis of variance of growth rates for height and diameter

Height Diameter

Source ss df v 2 ss df v2

NOTE: Terms are as given in Table 3. *. 0.01 < p < 0.05: **. 0.001 < [J < 0.01; ***. p < 0.001.

variation in the model. Of the experimental factors, the field treatment accounted for most variation for both height and diameter, and the nursery treatment was the factor ranked fourth. The difference in growth rate for height and diameter is in the third ranked factor. It is the seedlot for height and the nursery - seedlot interaction for diameter.

Of the experimental factors in the ANOVA for height on planting (1986) and in 1989, the error term is the largest and it increases from planting to 1989 (Tables 6and 7). On plant- ing, the nursery, seedlot, and nurse$-sedlot interaction terms

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TABLE 6. Analysis of variance of height and height increments

Ht. when planted 1986 Ht. at end of study 1989 Ht. increment 1987 Ht. increment 1988 Ht. increment 1989

Source ss df v2 ss d f v2 ss df v2 ss df v2 ss d f v2

B F N S B x F B X N B x S F x N F x S N X S e

NOTE: Terms are as given in Table 3. *, 0.01 < p < 0.05; **, 0.001 < p < 0.01; ***, p < 0.001.

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TABLE 7. Analysis of variance of diameter and diameter increments

Diam. when planted 1986 Diam. at end of study 1989 Diam. increment 1987 Diam. increment 1988 Diam. increment 1989

Source SS df v2 ss df v2 ss d f V? ss df v2 ss df v2

B 1 061.458 2 0.007*** 3 601.740 2 ; 0.003** 95.657 2 0.0004ns 4 502.479 2 0.012*** 495.854 2 0.001ns F 29.168 1, 0.0002ns 145 741.699 1 ' 0.1 17*** 20 609.781 1 0.078*** 23 727.569 1 0.062*** 48 223.066 1 0.058*** N 4 026.588 51 0.026*** 16 789.332 5 0.014**" 6424.023 5 0.024*** 3 906.727 5 0.010"** 10311.648 5 0.012*** S 2810.127 5 0.018*** 36 975.558 3 0.030*** 2699.589 3 0.010** 4 923.926 3 0.013*** 17 626.393 3 0.021*** B x F , 418.000 2 0.003"" 3 657.052 2 0.003** 2 358.324 2 0.009*** 349.079 2 0.001ns 1874.615 2 0.092"

.;B x N 2248.079 10 0.015*** 23 499.686 10 0.019*** 2481.880 10 0.009** 6002.258 10 0.016*** 13 797.135 10 0.0'f7*** ,,B x S 1854.787 6 0.012*** 6453.157 6 0.005** 1 85 1.422 6 0.007** 3 322.066 6 0.009*** 7416.228 6 0.009*** 'E. X N 1 074.377 5 0.007** 4 105.989 5 0.003ns 3 036.771 5 0.012*** 801.012 5 0.002ns 1 055.552 5 0.001ns F 'x S 660.345 3 0.004** 3 675.094 3 0.003* 1 701.874 3 0.006*** 5226.303 3 0.014*** 5 699.207 3 0.007*** N x S 6036.469 15 0.039*** 24547.492 15 0.020*** 11 559.412 15 0.044*** 5448.450 15 0.014*** 9460.741 15 0.011** e 33 390.104 2753 0.868 972 666.206 2592 0.783 210 594.792 2633 0.799 324 191.021 2584 0.848 717 612.447 2539 0.861

NOTE: Terms are as given in Table 3. *, 0.01 < p < 0.05; **, 0.001 < p < 0.01; ***, p < 0.001.

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are those ranked second through fourth. By 1989 ranking had changed, so the field treatment was ranked second, the seedlot third, and the nursery -seedlot interaction fourth.

The results for diameter on planting are fairly similar to those for height except the seedlot and nursery -seedlot inter- action effects are reversed. By 1989, the ranking of the factors was the same as for height. Like the data for height, the error term is by far the largest. The difference in total degrees of freedom between height and diameter in 1989 reflects leader damage on surviving trees, rendering height measurement impossible.

For the increments in height from 1987 to 1989, the error term, again, is the single largest factor and there appears to be an increase in the error term over time. The only experimental factor ranked in the top four over all increments of height is the field treatment, and its ranking drops from second to fourth between 1988 and 1989. The second ranked term for the incre- ments formed in 1989 is the nursery treatment. All the other terms ranked in the top four for increments in height are inter- action terms, different ones for each year.

The error term is also the largest for increments in diameter and also shows an increase over time. Of the experimental factors, the field treatment is consistently ranked second over all three increments. The other factors ranked in the top four are nursery and nursery -seedlot interaction for 1987, block - nursery and nursery-seedlot interactions for 1988, and block- nursery interaction and seedlot for 1989.

The different degrees of freedom for the ANOVAs in Tables 6 and 7 are the result of missing data because of seedlings dying or leaders being damaged beyond measurement.

Integration in growth irzcrernents The effects of various treatments on measures of integration

are presented in Table 8 as two ANOVAs describing the parti- tioning of variation in the angles of first eigenvectors with a vector of isometry and the determinants of correlation matrices. For the former, the field treatment accounts for the greatest amount of variation in the data; for the latter it was the treat- ment in the nursery. The sole statistically significant effect was the field treatment for angles between first eigenvectors and a vector of isometry.

Discussion Seedling szlrvival

The major impact on seedling survival is the seedlot planted, especially as affected by blocks and nursery treatment. That there should be a seedling effect is hardly surprising. The liter- ature is replete with examples of different levels of performance of seed from different areas (see Magnussen and Yeatman 1988; Rehfledt 199 1 and references cited therein).

Seedlot 8032 deserves some special comment. It is the one that does best in the nursery environment of this study but poorest when planted at the study site. Its relatively poor sur- vival is not surprising; it is the seedlot that has undergone the greatest elevational displacement. One recommendation that might be forthcoming from this study would be to limit the

I altitudinal range over which seedlot 8032 is used in artificial reforestation projects. However, any opinion relating to treat- ment or seedlot must be presented with the awareness that the largest single term in the ANOVA used to analyze seedling survival is the error term. Perhaps there is so much variation in seedling response, likely the effect of variation among (Chen et al. 1986; Maze et al. 1989, and references cited therein) and within organisms (Maze et al. 1992) and within the environ-

TABLE 8. Analysis of variance for descriptors of correlation matrices for each field and nursery treatment and seedlot -

Rdet Oiso

Source ss df t12 ss df tl?

NOTE: Terms are as given in Table 3. Rdet, determinants for each correlation matrix; Oiso, angle between first eigenvectors and a vector of isometry. These two esti~nators of correlation matrices arc those that are uncorrelated with each other but with other descriptors of correlation propcrtics. **, 0.001 < p < 0.01.

ment, that unambiguous responses to specific treatments are in the realm of a favored but unattainable result when studying trees in a forest environment.

Seedling growth There is a caution that must be mentioned before discussing

seedling growth. This study was designed to be continued for a number of years and to be done on many seedlings. This design carries two conditions. First, sampling had to be nondestructive. Second, relatively few variables could be measured for any one plant. The advantages gained from measuring many and the same seedlings year after year are offset by not knowing the response of any other part of the plant, especially the roots. As well, meas"ring leaders or diameter at the root collar alone will not allow an assessment of the allocation of growth to other aerial parts of the seedling, e.g., needles, branches, or buds. Despite these problems, we assume that the variables measured will give an acceptable assessment of seedling response. However, we cannot discount the possibility that variables representing more plant parts may give a different picture of the response of these seedlings to the treatments administered.

It is clear that seedlot 8032 has the largest seedlings on plant- ing in 1986. They remain- the largest in 1989. The superior performance of seedlot 8032, in terms of overall size, is the result of faster growth in a nursery environment and not its response in the ESSF at 1580 m near Aglemont. As well, the growth rates of seedlot 8032, especially in those seedlings fer- tilized in the field, are usually inferior. Like the results based on seedling survival, these indicate that planting seedlot 8032 at the study site, or possibly at other high-altitude sites, may not be the best strategy for artificial ref;restation. In terms of assessing the response of seedlings, these results would seem to argue for using a statistic such as growth rate as opposed to absolute size. Based on size. seedlot 8032 would be the preferred source of seed to plant in the upper Ross Creek drainage; based on growth rate, .it.would be the poorest choice.

All the ANOVAs assessing growth rate, size, and incre- ments of growth show two consistent responses: (i) the vast majority of the variation is seen in the error term, i.e., within any one combination of block, seedlot, field, and nursery treat- ment; and (ii) statistical significance occurs for practically all experimental factors. Not surprisingly, fertilization in the field has a large effect in most analyses, with the exception of size on planting. Nursery treatment andseedlot, either alone or as part of interaction terms, also have 1arge:effects.

The statistical significance of practicall) all factors, includ-

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ing block effects, likely reflects some degree of subtle, but not surprising, environmental heterogeneity. The increasing error term for increments from 1986 to 1989 likely reflects the response of seedlings to the microhabitat differences within each combination of treatments. This increasing amount of within-group variation would seem to homogenize initial differ- ences among seedlots and treatments as seedlings adjust to the environment in which they have been planted. This, in turn, could imply that decisions based on early response of seedlings should be made only after seedlings have had time to respond to the environment in which they have been planted; in the case of Engelmann spruce growing at the study site, it would seem to take at least 3 years to see adjustment to the environment.

The height and diameter data show somewhat different trends in relative growth rate and increments of growth. This differ- ence is seen in the seedlot effects, which are much smaller for growth rate in diameter than they are for height. The same can be seen when sizes at the beginning and end of the study are graphed. For increments of growth, the difference between height and diameter data is in the amount of variation for which the seedlots account, i.e., it declines for increments in height and increases for increments of diameter. For the effect of nursery treatment, it increases slightly for increments in height but decreases for increments in diameter. These different responses could well reflect the activity of different meristems and their derivatives, i.e., apical for growth in height, the vas- cular cambium for growth in girth. These different responses in diameter and height are not congruent with results on a study of Abies amabilis (Dougl.) Forbes (Funck et al. 1990) in which the two variables showed similar responses. We do not know whether we are seeing differences related to species, age and size of seedlings (the seedlings of A. amabilis were ger- minated in 1978, planted in 1980, but not analyzed until 1983), different sites (south-central B.C as opposed to Vancouver Island), or greater difficulty in measuringroot collar (this study) or leader (Funck et al. 1990) diameter.

In terms of forestry, the relevant question would seem to be whether or not it is useful to use various fertilizer treatments on seedlings. In terms of increments of growth, the effect of adding fertilizer in the field declines with the passing of years; the effect of nursery fertilizer treatments remains more or less constant for increments in height but declines for increments in diameter. This implies that the reaction of Engelmann spruce to fertilizer, especially when added in a heterogeneous natural environment, is very complex and may defy meaningful sum- marization. One benefit that seems to accrue to fertilizing, either in the field or nursery, is increased size, an effect that may carry several years beyond the application of fertilizer, all other things being equal. However, as with the results on seedling survival, the vast majority of variation in growth is still unaccounted for by any of the experimental terms. As stated above, this likely reflects a high level of heterogeneity in the seedlings and the environment. When dealing with both a vari- able crop and environment, as does forestry in western Canada, perhaps the operative solution in artificial reforestation would be to seek the survival of relatively healthy and normal seed- lings. In the upper Ross Creek drainage, this would mean plant- ing seedlot 4020 without fertilization in the field.

Integration of growth increments The addition of fertilizer, especially in the field, results in

changing the integration among years and tissues. This result

can be placed in an informational context using both informa- tion and biological theory. Applying concepts from algorithmic information theory (Chaitin 1987);'when. integration changes, the algorithm used to describe the previous state requires modifi- cation as a result of the expression of more information. The same could be stated in terms of Quastler's (1956) concept relating information to uncertainty: when integration changes, uncertainty has been generated in the system relative to-the previous state and information is required (must be added to the system) to eliminate, or reduce, that uncertainty. Applying these concepts to our results it would seem that in information theoretical terms, a change in integration means there has been an increase in information in the svstem. since the information required to describe correlation matrices derived from incre- ments of growth under one fertilizer regime is inadequate to describe correlation matrices ~roduced under a different one. This increase in information in the system is the result of infor- mation expression, i.e., the continuous production of mRNA.

Biologically, the information that integrates the incremental growth in plants is expressed differently under different fer- tilizer regimes. The penultimate source of that information is, of course. DNA. Its ultimate source. however. is found in the cytoplasm that elicits a response from the DNA, and the cyto- plasm may well be responding to the environment. Regardless of the source of information, we have systems defined by different fertilizer regimes but made up of similar, although highly variable, objects that have expressed information in different wavs.

The idea that fertilization changes the informational proper- ties of plants is neither surprising nor unique. Changes in means or variances for increments of growth under different fertiliza- " tion regimes is a univariate manifestation of a change in the information expressed. What we demonstrate here is that change in information expression related to fertilizer regimes and change of growth rate is seen also in properties related to integration.

The association between growth rates and change in infor- mation expression argues for a relationship between information and energy through coexistent flows. Of the energy that flows into a plant, some becomes incorporated into cell walls. The formation of cell walls occurs as information in the plant flows from DNA out into the cellular apparatus, which mediates cell division and wall formation. If there is a causal association between energy and information, then perhaps the tie between energy and information is through concepts derived from non- equilibrium thermodynamics (Banerjee et al. 1990; Brooks and Wiley 1989; Wicken 1987). Hariri et al. (1990) question a specific relationship between energy and information, although they do demonstrate a relationship between information and energy, expressed as entropy. It is also possible that we may have encountered an accidental attribute. a casual affiliation. Our data will not allow us to decide-between these two alterna- tives; it is likely that at this-iime the current theoretical and technical competence of biology precludes the collection of such data.

What we describe here is an expression of a biological truism, i.e., when growth occurs information will be expressed. This information is expressed not only in parts but also in how those parts are integrated. It is the integration that results in mature form; perhaps it is integration that forms Polanyi's (1969) boundary conditions or the material basis for an organismic interpretation of form (Kaplan and Hagemann 1991).

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