Predicting total and component biomass of Chinese fir using a forecast combination method

Abstract

Accurate estimates of tree biomass are critical for forest managers to assess carbon stock. Biomass of Chinese fir (Cunninghamia lanceolata [Lamb.] Hook.) in southern China was assessed by three alternative methods. In the Separate model approach, total and component tree biomass was directly predicted from a regression equation as a function of tree diameter and height. In the Additive model approach, total biomass was predicted as the sum of predictions from all component biomass equations. The Forecast Combination method involved combining predictions from the total biomass equation with the sum of predictions from component biomass equations. Results indicated that the Separate model method outperformed the Additive model method in predicting total and component biomass. The drawback of the Separate model method is that the total is not equal to the sum of its components. The Forecast Combination method provided the overall best prediction for total and component biomass, and still ensured additivity of component biomass predictions.