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Table 10 Parameter estimation (standard errors in parentheses) for nonlinear RBAI models using MEI index where competition effect is discriminated as described in Eq. 3

From: Quantifying competition in white spruce (Picea glauca) plantations

 

Parameters

White spruce

Balsam fir

Other conifers

Broadleaves

Fixed part

b 30

0.0350 (0.0031)

0.0431 (0.0032)

0.0381 (0.0062)

0.0510 (0.0076)

b 31

−0.0545 (0.0776)

0.5828 (0.1155)

0.3629 (0.1363)

1.2712 (1.4528)

b 32

0.0225 (0.0083)

n.s.

n.s.

n.s.

b 33

−18.0355 (2.5395)

10.4629 (1.3265)

−10.2557 (2.7621)

3.1874 (1.5634)

b 34

1e

1e

1e

1e

b 37

1.4262 (0.4141)

0.9568 (0.3652)

n.s.

n.s.

b 38

1e

1e

n.s.

n.s.

b 39

0.8886 (0.1014)

0.9020 (0.1273)

0.8211 (0.1710)

n.s.

b 40

1e

1e

1e

n.s.

Random effects

σ jk a

0.0146

0.0139

0.0208

0.0242

σ k b

0.0094

x

x

x

σ 2c

4.4431

2.7921

1.3400

1.2093

δ d

−1.2263

−1.0582

−1.0101

−0.8599

  1. n.s. not significant parameter (p value >0.05)
  2. aPlot random effect standard deviation
  3. bPlantation random effect standard deviation
  4. cResidual variance
  5. dVariation function parameter estimate
  6. eFixed value to 1 (e.g. not estimated by the regression)