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Table 6 Parameter estimation (standard errors in parentheses) for linear RBAI models using MEI where competition effect is discriminated as described in Eq. 2

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

 

Parameters

White spruce

Balsam fir

Other conifers

Broadleaves

Fixed part

b 20

0.1523 (0.0203)

0.2623 (0.0191)

0.1493 (0.0236)

0.0687 (0.0410)

b 21

0.0043 (0.0015)

n.s.

n.s.

0.0111 (0.0028)

b 22

−0.0279 (0.0021)

−0.0388 (0.0036)

−0.0188 (0.0044)

−0.0280 (0.0056)

b 24

−0.0162 (0.0039)

−0.0231 (0.0059)

n.s.

n.s.

b 25

−0.0143 (0.0013)

−0.0149 (0.0021)

−0.0099 (0.0027)

n.s.

Random effects

σ jk a

0.0157

0.0094

0.0205

0.0000

σ k b

0.0107

0.0109

0.0063

0.0178

σ 2c

4.4393

5.1239

3.2521

4.5534

δ d

−1.2243

−1.191969

−1.1840

−1.1880

  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