Title: Estimation and Application of GeneticGain Multipliers for DouglasFir Height and Diameter Growth
1Estimation and Application of Genetic-Gain
Multipliers for Douglas-Fir Height and Diameter
Growth
- Peter J. Gould1, David D. Marshall2,
- Randy Johnson1 and Greg Johnson2
- 1USDA Forest Service Pacific Northwest Research
Station - 2Weyerhaeuser Co.
2Outline
- Issues, concepts, objectives
- Data and modeling approach
- Results
- Applications for projecting yield
3Why Model Genetic Gain?
- Improved Douglas-fir is a reality in the PNW.
- Insight into stand development and return on
investment (without waiting 20 yrs). - Genetics studies have not focused on stand-level
growth and yield.
4Genetic-Gain Multipliers
Predicted growth with genetic-gain
Predicted growth from woods-run model
- Example ?DG M ?DWR
- Extrapolates information from genetics studies
to existing growth models. - Other approaches include refitting equations and
SI adjustments.
5Genetics Studies Questions Asked
- Geneticist What is the total height and diameter
of a genotype at a given age relative to
woods-run? - Single-tree plots
- Families tested on multiple sites interested in
mean across sites. - Select best parents for seed orchards / breeding
6Genetics Studies Questions Asked
- Modeler What is the rate of height and diameter
growth of an individual tree for a given period
based on its pedigree and site, stand, and tree
characteristics? - Interested in growth within a stand.
- Genetics is one of many factors controlling
growth.
7Concepts from Genetics
- Breeding value the value of a parent for
passing some trait to its progeny (estimated from
progeny tests). - Genetic worth the expected level of gain for
some trait of an improved seedlot. -
- GW f(BVorchard, outside pollen)
- Both expressed as percentage difference from
population (woods-run) mean in traits such as
total height and diameter at a given age.
8NWTIC 1st Generation Progeny Tests
- Seed collected from wild, woods-run parents to
test half-sib families. - BV calculated for mother trees at age 10 yrs
(genetics perspective). - We used same data (up to age 20 yrs). Half-sib
families treated as individual seedlots where
9Study Objectives
- Estimate genetic-gain multipliers for height and
diameter growth for improved DF seedlots when GW
is known. - M f (GW, stand age)
- Evaluate multiplier effects in growth models
(ORGANON and FVS).
10Modeling Strategy
- 1. Estimate growth of individual trees (e.g.,
?DWR) in progeny tests using woods-run models. - 2. Calculate seedlot-level multipliers (M) from
observed growth and expected growth under the
woods-run model. - ?DG M ?DWR
- M ?DG / ?DWR
- 3. Estimate M from seedlots GW.
11NWTIC 1st Generation Progeny Tests
Breeding zone area of relatively uniform
environment ( 50,000 ha) Site Geographical
location within breeding zone.Set Group of
families tested together. A more-or-less random
sample of woods-run population.
12DBH Data Variation Between Breeding Zones
13DBH Data Variation Between Sites
10 to 15 yr DBH Increment (cm)
10-yr DBH (cm)
14DBH Data Variation Between Sets
10 to 15 yr DBH Increment (cm)
10-yr DBH (cm)
15Challenges of Progeny Test Data
- Limited individual-tree measurements
- No crown ratios or crown class
- Single-tree plots
- No stand density (e.g., basal area)
- No site index
-
- Mixed genotypes
- Superior trees may perform better
- Inferior trees may perform worse
16Modeling Strategy
- Could not use an existing model
- Unmeasured variables
- Precision needed to estimate small effects
- Created custom woods-run models
- Ex ?HT b1HTb2b3HT
- random effects on b1,b2,b3 at set level
- Separate models fit for 5- 10-, and 15-yr
periods.
17Mixed Genotypes
- Probably not very important
- much overlap between seedlots in size /
competitive position. - Woods-run models account for differences in
initial size.
18NWTIC 1st Generation Progeny Tests
19Woods-run Model Height Growth
20Woods-run Model Height Growth
21Woods-run Model Height Growth
22Woods-run Model Height Growth
23Estimating Height-Growth Multipliers
- M a0 a1 GW
- OLS, WLS and method-of-moments regression fits
(error in GW). - WLS fits
- Period Equation
- 5 1 0.006277GW
- 10 1 0.003112GW
- 15 1 0.004474GW
24Estimating Diameter-Growth Multipliers
- WLS fits
- Period Equation
- 5 1 0.010105GW
- 10 1 0.003370GW
- 15 1 0.002944GW
25We Have Multipliers Now What?
- ORGANON (Mark Hanus and David Hann).
- FVS PN and WC (FIXHTG and FIXDG keywords).
- Tested virtual seedlot with 10 GW for height
and diameter at 10 yrs.
26We Have Multipliers Now What?
- Tree list for 10-yr-old stands generated with
FGROW (Flewelling and Marshall). - Adjusted 10-yr height and diameters by
multiplying by 1.10. - Tested adjusted tree list with and without
genetic-gain multipliers.
27Projections
Woods-Run Volume (cuft)
Gain with Treelist (cuft)
Gain with Multipliers (cuft)
28Projections 40-yr Rotation
29Projections 60-yr Rotation
30Conclusions
- Multipliers can put genetic information in
models right now, though many questions remain. - Genetic effects are relatively small, but
significant. - Modelers need more information and more precise
estimates than tree breeding programs. - Operational and controlled experiments are
needed.