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Table 4 Parameters estimated and statistics of the six candidate regression functions tested to predict total dry weight (tDW) of the moist evergreen forest in MFR in Mozambique

From: Biomass allometric equation and expansion factor for a mountain moist evergreen forest in Mozambique

Parameter

Alternative biomass allometric models

Model 1ab

Model 2b

Model 3

Model 4bc

Model 5

Model 6

AIC

436

438

453

454

533

540

RSE (kg tree−1)

61

62

75

77

213

233

MPE (kg tree−1)

− 4.7

− 4.9

− 5.1

− 4.3

− 17

− 21.4

RMPE (%)

− 1.2

− 1.2

− 1.3

− 1.1

− 4.3

− 5.4

b0

0.0912***

0.0969***

0.0865**

0.0613***

0.0941ns

0.0441ns

95% conf. inter. of b0

(0.0603 to 0.1359)

(0.0572 to 0.1597)

(0.0469 to 0.1533)

(0.0378 to 0.0963)

(0.0281 to 0.2716)

(0.0109 to 0.1483)

b1

2.8131***

− 0.2612***

2.6416***

2.7133***

0.9608***

1.0112***

95% conf. inter. of b1

(2.7135 to 2.9166)

(− 0.3827 to − 0.1398)

(2.5070 to 2.7857)

(2.5983 to 2.8358)

(0.8599 to 1.0750)

(0.8978 to 1.1385)

b2

− 0.2698***

2.7945***

0.3057ns

   

95% conf. inter. of b2

(− 0.3816 to − 0.1583)

(2.6585 to 2.9391)

(− 0.0512 to 0.6786)

   

b3

 

0.0596ns

    

95% conf. inter. of b3

 

(− 0.2468 to 0.3748)

    
  1. TH is total height, RSE is residual standard error, AIC is Akaike’s information criterion, b0 and b1 are the regression coefficients
  2. a Equation that fitted better to the data, based on lowest RSE and AIC values
  3. b Equation selected for further analysis
  4. *** significant at α = 0.001, ** significant at α = 0.01, * significant at α = 0.05, ns not statistically significant at α = 0.05