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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
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