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Table 2 Akaike information criterion (AIC), estimated additive genetic variance (\( {\hat{\sigma}}_a^2 \)), additive direct genetic variance (\( {\hat{\sigma}}_{a_d}^2 \)), additive competition genetic variance (\( {\hat{\sigma}}_{a_c}^2 \)), dominance genetic variance (\( {\hat{\sigma}}_d^2 \)), check lot effect variance (\( {\hat{\sigma}}_s^2 \)), block effect variance (\( {\hat{\sigma}}_b^2 \)), plot effect variance (\( {\hat{\sigma}}_p^2 \)), environmental competition effects variance (\( {\hat{\sigma}}_{p_c}^2 \)), residual variance (\( {\hat{\sigma}}_e^2 \)), and single-site individual narrow- (\( {\hat{h}}_s^2 \) and\( {\hat{h}}_c^2 \)) and broad-sense (\( {\hat{H}}_s^2 \) and \( {\hat{H}}_c^2 \)) heritability for diameter at breast height (DBH), total tree height (TH), and normal score of stem straightness (NSTR) from the multi-environment standard (MSM) and competition (MCM) individual-tree mixed models of sites 1 and 2 (the lowest AIC are highlighted in bold)

From: Accounting for competition in multi-environment tree genetic evaluations: a case study with hybrid pines

Models

Site

Parameters

DBH

TH

NSTR

MSM

 

AIC

16,515

13,086

8,015

1

\( {\hat{\sigma}}_{a_1}^2 \)

4.46 (2.09)

1.05 (0.54)

0.17 (0.05)

\( {\hat{\sigma}}_{d_1}^2 \)

6.78 (3.23)

0.44 (0.77)

0.15 (0.06)

\( {\hat{\sigma}}_{s_1}^2 \)

46.38 (29.97)

6.69 (4.65)

0.07 (0.07)

\( {\hat{\sigma}}_{b_1}^2 \)

0.27 (0.28)

0.96 (0.72)

0.00 (0.00)

 

\( {\hat{\sigma}}_{p_1}^2 \)

0.70 (0.65)

0.82 (0.27)

0.03 (0.02)

  

\( {\hat{\sigma}}_{e_1}^2 \)

12.45 (2.60)

5.47 (0.67)

0.55 (0.06)

 

\( {\hat{h}}_{s_1}^2 \)

0.19 (0.08)

0.15 (0.08)

0.20 (0.06)

 

\( {\hat{H}}_{s_1}^2 \)

0.47 (0.12)

0.21 (0.11)

0.37 (0.06)

2

\( {\hat{\sigma}}_{a_2}^2 \)

7.24 (2.15)

1.07 (0.36)

0.12 (0.04)

\( {\hat{\sigma}}_{d_2}^2 \)

3.19 (1.55)

0.71 (0.36)

0.07 (0.03)

\( {\hat{\sigma}}_{s_2}^2 \)

49.87 (35.79)

7.44 (4.93)

0.19 (0.16)

\( {\hat{\sigma}}_{b_2}^2 \)

0.20 (0.18)

0.21 (0.14)

0.00 (0.00)

 

\( {\hat{\sigma}}_{p_2}^2 \)

0.06 (0.48)

0.01 (0.11)

0.00 (0.00)

  

\( {\hat{\sigma}}_{e_2}^2 \)

15.34 (1.78)

3.89 (0.37)

0.69 (0.04)

  

\( {\hat{h}}_{s_2}^2 \)

0.28 (0.07)

0.19 (0.06)

0.14 (0.04)

  

\( {\hat{H}}_{s_2}^2 \)

0.40 (0.08)

0.31 (0.07)

0.22 (0.05)

MCM

 

AIC

16,511

13,056

8,033

1

\( {\hat{\sigma}}_{a_{d1}}^2 \)

4.91 (2.09)

1.15 (0.50)

0.18 (0.07)

\( {\hat{\sigma}}_{a_{c1}}^2 \)

0.13 (0.80)

0.20 (0.55)

0.00 (0.00)

\( {\hat{\sigma}}_{d_1}^2 \)

6.99 (3.28)

0.46 (0.63)

0.14 (0.08)

\( {\hat{\sigma}}_{s_1}^2 \)

50.02 (32.96)

5.70 (4.01)

0.07 (0.06)

\( {\hat{\sigma}}_{b_1}^2 \)

0.33 (0.33)

0.73 (0.58)

0.00 (0.01)

\( {\hat{\sigma}}_{p_1}^2 \)

0.57 (0.66)

0.12 (0.22)

0.03 (0.02)

\( {\hat{\sigma}}_{p_{c1}}^2 \)

0.24 (5.33)

1.81 (1.80)

0.01 (0.02)

\( {\hat{\sigma}}_{e_1}^2 \)

11.77 (2.66)

4.02 (0.60)

0.54 (0.08)

 

\( {\hat{h}}_{c_1}^2 \)

0.21 (0.10)

0.18 (0.10)

0.21 (0.08)

 

\( {\hat{H}}_{c_1}^2 \)

0.50 (0.17)

0.24 (0.13)

0.37 (0.10)

2

\( {\hat{\sigma}}_{a_{d2}}^2 \)

10.52 (2.41)

1.05 (0.35)

0.12 (0.04)

\( {\hat{\sigma}}_{a_{c2}}^2 \)

0.29 (0.87)

0.04 (0.24)

0.00 (0.00)

\( {\hat{\sigma}}_{d_2}^2 \)

2.89 (1.44)

0.66 (0.36)

0.06 (0.04)

\( {\hat{\sigma}}_{s_2}^2 \)

43.25 (28.64)

7.72 (5.11)

0.19 (0.15)

\( {\hat{\sigma}}_{b_2}^2 \)

0.20 (0.18)

0.20 (0.14)

0.00 (0.00)

\( {\hat{\sigma}}_{p_2}^2 \)

0.05 (0.49)

0.01 (0.13)

0.00 (0.00)

\( {\hat{\sigma}}_{p_{c2}}^2 \)

0.13 (3.60)

0.43 (0.89)

0.01 (0.01)

\( {\hat{\sigma}}_{e_2}^2 \)

13.15 (1.84)

3.51 (0.37)

0.68 (0.05)

  

\( {\hat{h}}_{c_2}^2 \)

0.40 (0.09)

0.19 (0.07)

0.14 (0.05)

  

\( {\hat{H}}_{c_2}^2 \)

0.51 (0.10)

0.31 (0.09)

0.21 (0.06)

  1. Subscripts represent sites 1 and 2