0233-B4

Genetic variation in stone pine half-sib progenies

Ioan Blada ¹

Abstract

Total height, annual height growth, root collar diameter, total number of branches and total number of buds around the leader bud were recorded at age 6.

The experimental material comprised 136 half-sib families originating from a stone pine natural population from the Carpathian Mountains. Population samples were included in a randomized complete block experiment with four replications and ten seedlings per family per replication. Highly significant (p<0.001) family variation for all traits was detected. Very high family heritabilities were estimated for total height (h_f ² =0 .968), root collar diameter (h_f ² = 0.938) and total number of branches (h_f ² = 0.966). Genetic correlations between total and annual height growth and root collar diameter were high or very high ranging between 0.804 and 0.969; this indicated favorable conditions for obtaining substantial genetic gain for a combination of these traits. Selecting the best 30 to 45 families a genetic gain in total height growth and diameter between 28.8 % and 23.4 % and between 18.8 % and 15.3 %, respectively could be achieved. Suggestions for breeding strategy are made.

Introduction

Stone pine (Pinus cembra L.) is naturally distributed at high elevations of the Alps and Carpathians, including Tatra Mountains. (Georgescu & Ionescu 1932; Beldie 1941; Critchfield & Little 1966; Sauermoser 1994; Konak 1994). The species is important from the following points of view: ecological (Holzer 1972; Frey 1994); silvicultural (Frey 1994; Holzer 1994; Blada 1996); industrial (Holzer, 1972; Contini & Lavarelo 1982); genetic (Bingham 1972; Holzer 1975; Blada 1994); landscaping, tourism and other recreation functions (Gordon 1994; Blada 1997 b)

Although stone pine is a very slow growing species, it is of particular importance for forestry in the Carpathian subalpine zone. Due to lack of improved planting material, a genetic improvement program including intra- and interspecific crosses was developed in Romania (Blada 1990). Improving growth traits was the main objective of the Program.

This paper reports nursery stage variation among 136 stone pine half-sib progenies.

Materials and Methods

Initial material and nursery progeny test

Open pollinated seeds were collected from 136 stone pine trees growing in several natural populations from the Carpathian and Alps Mountains. Only the availability of cones per tree was taken into account in parent selection. To reduce the likelihood of relatedness, the trees were separated by minimum 50-meters. In September 1991 two seeds were sown per polyethylene pot (22 cm x 18 cm) filled with spruce humus. After sowing, the seeded pots were placed in nursery beds where they were arranged in a randomized complete block design The second seedling, if present, was removed in the second year of growth. A 10-seedling row plot in each of four blocks represented each of the 136 families. As the stone pine is a very slow growing species, the seedlings were grown, in the initial pots, throughout the six years nursery-testing period.

Traits measured

Five traits (Table 1) were measured in the autumn of 1995 when the plants were six years old. Plot means comprised the basic data for statistical analysis.

Statistical analysis

Two-way ANOVA based on plot means was performed. The following mathematical model was applied:

X_ik = m + a_i + b_k + e_ik(1)

where: X_ik = plot average from the i -th open - pollinated family in the k-th replication; m = the general mean of the whole experiment; a_i = the random effect of the i-th half-sib progeny (i = 1,2...I); b_k = the effect of the k-th replication (k = 1,2...K); e_ik = the random error. Replications and families were considered to be random effects. Variance components of the random effects were estimated by equating mean squares to expected mean squares. Standard errors (SE) of the variance components were computed with the formula given by Anderson & Bancroft (1952). Genetic coefficients of variation (GCV) were calculated with the formula:

GCV = ( ² _f / x) 100 (2)

where: ² _f =the family genetic variance ; x = the population mean

Narrow-sense family heritabilities (h ² _f) were calculated as:

h ² _f = ² _f /( ² _f + ² _e / k)(3)

The confidence intervals (95%) were estimated for heritability by Knapp's et al. (1985) formulas. Genetic gain (G) was calculated by Falconer's (1981) formula:

G = ih ² _{f Ph1} (4)

where: i = intensity of selection taken from Becker (1984), and _Ph1 = phenotypic standard deviation.

Results and Discussions

Genetic variation

The analyses of variance of plot means showed highly significant (p<0.001) differences among the 136 families in all traits at both ages (Table 2, row 2). As a full table of family means cannot be presented here, the table 3 shows family means of 10 best and 10 poorest families for each trait, indicating the magnitude of family variation. A large variation among family means was found. For total height growth and root collar diameter, the poorest groups had averages (X₂) of 13,4 cm and 7.7 mm, respectively while the averages of the best groups (X₁) were 29.6 cm and 13.0 mm, respectively, i. e. a difference (D₁) of 120.7 % and 69.3 %. At the same time the difference between the two groups of families accounted for 152.6 % in total number of branches and 120.3 % in total number of buds around the leader. Differences (D₂) between the top group (X₁) and the test mean (X) were smaller but still significant (Table 3, last line). As expected, differences among individual families were much greater. For example, at six years of age, the worst family was 11.5 cm tall, while the best family measured 35.4 cm, i.e. a difference of 204.3%. The genetic coefficients of variation for total height, annual height growth, root collar diameter and total number of branches was 22.0%, 25.8%, 14.6% and 26.3%, respectively (Table 2, last line). Thus, it has been demonstrated that stone pine half-sib families posses considerable genetic variation in the analysed traits, suggesting that selection for improvement will be effective.

Variance components

Analyses of the trait data have yielded estimates of variance components and their standard errors presented in the lower part of table 2. At age 6, the family additive genetic variance was 88% for total height growth, 80 % for annual height growth, 79 % for root collar diameter and 88 % for total number of branches. Therefore, a significant high contribution of genetic variance was noticed not only for total height but for the other traits, as well. The data do suggest that additive genetic control is high in all traits. Rather than relying on a constructed F-test, Snyder & Namkoong (1978) recommended that the magnitude of a variance component be compared with its standard error. The variance component is deemed to be important if it is estimated to have a standard error less than half the magnitude of the component. In this experiment, the variance components for all traits had standard errors about seven times lower than the estimated components themselves (Table 2, line 5). This indicates that the genetic variances and heritabilities were reliable and that a selective breeding program using additive variation will be effective in improving any tested trait.

In summary, because the amount of variation was considerable, an improvement program with stone pine would be practical.

Genetic and phenotypic correlation

Highly significant (p<0.001) phenotypic correlation were found among all but two traits (Table 4). Genetic correlation among growth characteristics, i.e. total and annual growth in height and root collar diameter were high or very high ranging between 0.804 and 0.969. These correlations suggest that selection for one trait should lead to strong positive indirect responses in the others. Both total height and diameter at root collar were moderate and highly associated with the total number of branches, with genetic correlations ranging from 0.571 to 0.713. Phenotypic correlations for the same traits, were highly significant (p<0.001) and positive. Selection for total height growth or growth in root collar diameter should lead to an indirect increase in the total number of branches; but this is a negative feature of trees because an increased number of branches means a lower quality of wood. Therefore, reduction in the incidence of the total number of branches in the next generation is likely to be achieved most readily by selection against this trait. Consequently, the breeder should act towards breaking this undesirable positive correlation and to select in favour of fast growing trees with a small number of branches. Similar genetic correlations were reported for the full-sib family test (Blada 1999).

Heritability

Table 5 presents a summary of the heritability estimates and their 95% confidence intervals for the open-pollinated families. All estimates of heritability in this study may be somewhat upwardly biased because the experiment was restricted to a single nursery where family-site interactions were not accounted for. Since the additive genetic variance of all analysed traits was high, family narrow-sense heritabilities were also high, ranging between 0.870 and 0.968. The heritability estimate for root collar diameter was 938 and was about the same magnitude as the corresponding estimates for growth in height. Similar high estimates were obtained for annual growth in height, total number of branches and total number of buds around the leader bud. High heritability has also been observed in the P. cembra full-sib progeny test carried out in the same nursery (Blada 1999). All estimates calculated here fell within the 95% confidence interval suggesting their reliability.

In conclusion, all analysed traits were under a strong genetic control and thus, appeared quite amenable to genetic selection.

Expected genetic gain

Table 5 presents estimates of gain, as a percentage of the nursery test mean, which might be expected in growth and other traits after one generation of selection. If the best 30, 35, 40 or 45 of the 136 families were selected and used in a planting program, a genetic gain in total height growth and diameter at root collar of 28.8%, 26.8%, 25.1% and 23.4% and 18.8%, 17.6%, 16.4% and 15.3%, respectively could be expected. More or less similar genetic progress can be made in the other traits tested. This genetic gain could result in substantial returns if large planting programs were developed. These results suggest that the growth improvement through family selection, in slow-growing stone pine is possible. An increasing use of stone pine may lead to a situation where trees having faster growth become commercially valuable.

Implications for breeding

As stated earlier, the stone pine is a very slow-growing species. But according to our previous report (Blada 1999) and to the nursery testing results presented in this study, growth traits of stone pine were under a strong genetic control. Consequently, selection on the basis of progeny performance in the nursery test could provide substantial improvement in diameter, height growth and total number of branches. Improving height and diameter growth in stone pine is the main objective to be achieved. Therefore, action will concentrate on the production of improved seed for operational planting, based on the results acquired over a six year of nursery testing of 136 half-sib progenies. This population was divided in two equal parts. One part was already planted out in field trails to be used for estimation of genetic variation including juvenile-mature genetic correlations and the other one will be used for seed orchard development according to Zobel & Talbert (1984) recommendations.

After field testing the breeding strategy will be improved according to the new estimated genetic parameters.
The task was to incorporate the early testing procedures into an operational improvement program.

Two types of production seed orchards are planned:

(i) A clonal seed orchard will be developed using as ortets, 45 female trees -the best in height and diameter growth; selection was based on the performances of their open pollinated families. The commercial F₁ seedlings will be planted in regions to which they are adapted e.g. on sites relatively similar to those of the wild female parents. Taking into account our previous observations (Blada 1990, unpublished data), this clonal seed orchard will have the first crop about seven years after grafting.

(ii) A seedling seed orchard will be established by planting the fastest growing seedlings selected from best 45 tested families out of the 136 tested. In other words, the best offspring of the trees planted in the clonal seed orchards. This is a first generation seed orchard. To maintain a large genetic base, 80 seedlings of each family will be planted at 3 x 3 m, requiring an area of 3.2 ha. It is expected that the first commercial F₂ crop will be available about 20 years after planting.

By planting improved material from the two types of seed orchards, significant genetic gains should be obtained. In estimating these gains, one can use the procedures indicated by Namkoong et al. (1966); Shelbourne (1992).

If the best 45 tested progenies were used directly in operational planting, a genetic gain in total height of 23.4% could be expected (Table 5, row 1).

The provenance test (Blada 1997a) did demonstrate that the improvement of growth in height and diameter by provenance selection is also possible even if the species is a very slow growing one.

It should be pointed out that our decision to utilise early selection to develop production seed orchards after only six years of testing was encouraged by similar work reported by others. For example, Lambeth et al. (1983) suggested that most selection in loblolly pine (Pinus taeda L.) is currently carried out between ages five and ten years. Also, Lowe & Van Buijtenen (1989); Bridgwater & McKeand (1997) were in favour of early selection.

Conclusions

Although stone pine is a very slow growing species, high genetic variation among half-sib families in growth traits and total number of branches was found.

The additive genetic variation detected in this breeding population can be incorporated into an operational program or as a base for an advanced breeding population.

Genetic and phenotypic correlations suggest that correlated responses for growth traits and total number of branches should be obtained through indirect selection.

The high variability of the material and comparatively high heritability estimates showed that consistent genetic gain in growth and total number of branches is possible.

Results of this experiment indicated that early height growth could be used as an early testing trait for stone pine; consequently, early evaluation trials will permit making crosses among the best parent trees after only a few years of testing.

By using results of this early testing, corroborated with previously results, an operational improvement program for stone pine was developed.

Acknowledgements

The authors express their gratitude to Professor C. G. Tauer from the Oklahoma State University, United States and to Dr C. J. A. Samuel from Northern Research Station, Roslin, Midlothian, United Kingdom for reviewing the draft of this paper and for their useful suggestions. Thanks are also due to Dr. N. Popescu & to the following technicians S. Tanasie, A. Dragila, D. Pepelea, G. Sarbu & C. Dinu for their technical assistance. Also, our thanks are extended to Dr Roman Amat & Mr D. Fournier (France) who kindly collected stone pine seed from the French Alps.

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Table 1. Traits measured at age six

Table 2. ANOVA, variance components ( 2 ) (percents in brackets), standard errors (SE) and genetic coefficient of variation (GCV) for 136 open-pollinated stone pine families

Table 3. Ranking of the best and the poorest 10 stone pine families based on nursery performance

Table 5. Family narrow-sense heritability estimates (hf 2) with 95 % confidence interval (CI) and expected genetic gain (G) at family level

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