Modeling the Effects of Genetic Improvement on Diameter and Height Growth

1. Modeling the Effects of Genetic Improvement on Diameter and Height Growth Greg Johnson Weyerhaeuser Company

2. Credits This work was made possible by the Vernonia Tree Improvement Cooperative: BLM, Crown Zellerbach, Hampton,International Paper, Oregon Department of Forestry, Longview Fibre, Stimson Lumber, Willamette Industries and was supported by Willamette Industries

3. Study Objectives • To determine if the growth of improved genotypes differs in quantifiable ways from Woods-Run stock. • If differences are apparent, to describe the nature and magnitude of the effect. • Make recommendations for the adjustment of growth models to account for genetic effects.

4. The Vernonia 1st Generation Tree Improvement Program • Initiated by Roy Silen and Joe Wheat in 1968 as a cooperative between Longview Fibre, International Paper Company, Crown Zellerbach Corporation, and the Oregon Department of Forestry. • 900 trees were selected from wild stands using roadside selection. The working assumption was that this population approximated woods-run performance - i.e., there was little, if any, selection pressure during the identification of the parents. • Progeny tests consisted of open-pollinated progeny of the 900 parents planted on twelve test sites.

5. Parent Tree Distribution

6. The Vernonia 1st Generation Tree Improvement Program • Three spacings were used (8.5'x8.5', 12'x12', and 14'x14') with each location receiving a single spacing assignment (spacing confounded with location). • There are four locations at each of the spacings. • Test design was reps-in-sets, where sets of approximately 50 families (creating 18 sets) were treated as separate experiments with replication within each experiment. • Each set was replicated five times at each test location for all but three of the twelve locations, where two replicates were installed.

7. The Data • Sets 8, 10, and 14 were used from 11 of the 12 sites. These sets were part of a study on the long-term stability of family rankings. • Periodic data from measurements at 7, 10, 15, 20, 25, and 30 years were used. • Only two sites were measured at age 7, with the remaining nine sites measured at age 10.

8. The Data • A common method of selecting parents for advanced generation breeding using a reps-in-sets design is to pick the top ranking families from each set. • For this analysis, an elite subset of families was defined as the top five families (based on height at age 15 from seed) from each set (top 10%).

9. Heights for each Set at Selection Age (15) NOTE: Test design does not allow sets to be compared.

10. Selection age Selection Effect

11. Analytical Procedure • Fit height and diameter growth equations to entire test population (Woods-Run). • Test the hypothesis that the Elite subset’s growth can be explained by the Woods-Run equations. • If the hypothesis is rejected, quantify the differences.

12. Height Growth • Modeled height growth as a function of height and CCH: • Reliable estimates of site index were not available. Location was treated as a fixed effect.

13. Height Growth Equation Performance - Woods-Run

14. Woods-Run Height Growth Performance - Elite Subset Elite height growth is under-predicted by the woods-run equation. Woods-Run Elite

15. Woods-Run Height Growth Performance - Elite Subset

16. Height Growth • No significant correlations found between gain and tree, stand, location, or age variables. • Average ratio of Elite height growth to Woods-Run Prediction: 1.024 • The initial conditions (starting heights) need to be known prior to growth projection (cannot assume equal distributions). • Recommendation: use a simple ratio adjustment to individual-tree height growth prediction.

17. Adjusted Elite Height Growth Prediction Residuals

18. Diameter Growth • Modeled diameter growth as a function of DBH, BA, and BACL: • Crown ratios were not available. • Reliable estimates of site index were not available. Location was treated as a fixed effect.

19. Diameter Growth Equation Performance - Woods-Run

20. Woods-Run Diameter Growth Performance - Elite Subset Woods-Run Elite

21. Woods-Run Diameter Growth Performance - Elite Subset

22. Woods-Run Diameter Growth Performance - Elite Subset

23. Diameter Growth • Elite trees’ diameter growth does not differ from Woods-Run when tree size, stand density and social position are considered. • Elite diameters are larger than Woods-Run at any given age. • Gain in DBH may be due to trees reaching breast height earlier, or a genetic effect prior to measurements taken in this study.

24. Diameter Growth • Recommendation: do not adjust diameter growth equations IF diameter growth prediction is uncoupled from height. • If height growth is increased and diameter growth is not, improved trees should develop with less taper (larger height to diameter ratio).

25. Height - Diameter Relationship at Age 30

26. What’s Next? • Realized Gains Trials • Large plots with an elite family or elite mixture) are being installed. • Can test the effect of an improved “neighborhood”. • Allows examination of multiple gain levels. • Provides an opportunity to observe growth at early ages (find out where DBH and early height gain come from).

27. What’s Next? • Measure additional growth traits: • Crown length • Crown width • Test Genetics X Density interaction. • “Calibrate” growth models.