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Genetic Gain Multipliers for Douglas-Fir Height and Diameter Growth: A Comprehensive Study

This study estimates genetic gain multipliers for height and diameter growth in Douglas-fir. By comparing average tree growth with individual family performance, the research evaluates how these multipliers relate to breeding values, determining their impact on tree growth models. Using data from multiple cooperatives over a decade, the analysis includes random effects modeling to account for site variations and identifies effective strategies for optimizing breeding. The results will inform future breeding practices and improve growth projections for Douglas-fir.

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Genetic Gain Multipliers for Douglas-Fir Height and Diameter Growth: A Comprehensive Study

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  1. Estimation of Genetic Multipliers for Douglas-Fir Height- and Diameter-Growth Models Peter J. Gould, David D. Marshall, Randy Johnson and Greg Johnson

  2. Study Objectives 1. Estimate growth differences between average (wood’s-run) tree and individual families in terms of genetic-gain multipliers.2. Relate multipliers to breeding value (BV = percent gain at age 10).3. Evaluate multipliers effects in model.

  3. Effect of Multipliers Initial Size Advantage Gain Multiplier= 0.05 Typical Tree

  4. SET 1 SET 2 SET 3 Rep 1 Rep 1 Rep 1 Rep 2 Rep 2 Rep 2 Rep 3 Rep 3 Rep 3 Rep 4 Rep 4 Rep 4 NWTIC 1st-Generation Progeny Tests Coop: breeding zone. Completely independent families.Sites: Geographical locations within coops.

  5. DBH Data: Variation between Coops 10-YR GROWTH PERIOD

  6. DBH Data: Variation between Sites 10-YR GROWTH PERIOD

  7. DBH Data: Variation between Sets 10-YR GROWTH PERIOD

  8. DBH Data: Breeding Values BV = Age 10 Gain 1 (percent)

  9. Modeling Strategy: Assumptions 1. Average growth = wood’s run.2. Multipliers work with any unbiased growth model.3. Removing sources of variation other than genetics is very important.

  10. Strategy:1. Fit models with random effects at site-set level.2. Calculate genetic multiplier (m) for each family at coop level. Obs = m ∙ Pred3. Estimate m from BV. m = A0 + A1 ∙ BV

  11. 10-YR Modeling Dataset: HT Model >16 coops> 109 sites> 513 site-sets> 2485 families> 222 818 observations

  12. HT Model 1 ∆HT = b1∙HTb2∙b3HTrandom effects on b1,b2,b3Fixed Effects: ∆HT = 231.7∙HT0.94∙0.86HT

  13. HT Model 1

  14. HT Model Results: Family M

  15. Modeling Datasets: DBH Model >7 coops> 45 sites> 193 site-sets> 1160 families> 76 012 observations

  16. DBH Model 1 ∆DBH = b1∙DBHb2∙b3DBH∙b4BA REPrandom effects on b1,b2,b3Fixed Effects: ∆DBH = 3.7∙DBH0.3∙1.01DBH∙0.97BA REP

  17. DBH Model 1

  18. DBH Model Results: Family M

  19. 10-yr A1 estimates:

  20. Other Periods • Ht data for 5-yr (167,000 obs) and 15-yr (7600 obs) growth. • DBH data for 5-yr (7,700 obs) and 15-yr growth (20,000). • Estimates of m are higher for 5-yr, but about the same for 15-yr growth.

  21. What’s Next? • Manuscript on multipliers. • ORGANON interface. • Test multipliers.

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