Application Of Allometric Equations And Biomass Expansion Factor For Estimating Cunninghamia Lanceolata Forest Biomass On Large Scale

Cunninghamia lanceolata is one of the largest planted tree species in southern China and plays an important role in contributing to carbon storage on regional scale. Hence, it is imperative to establish reliable methods for biomass estimation and carbon storage dynamic monitoring in C. lanceolata forests on large scale, using the national forest inventory data.We collected allometric equations published to date in the literature for estimating C. lanceolat trees biomass, and developed general allometric tree component biomass equations of C. lanceolat trees by using meta-analysis to generate pesudoobservations data. The volume-biomass expansion equation for different age classes of C. lanceolat forests were generated. The above three types of equations or methods could be chosen to estimate the C. lanceolat forests biomass, according to the availability of the forest inventory data. The main results showed as follows:1. Based on the collection of allometric equations, the equations developed at closest local site could be selected to estimate forest biomass using the plot data in different locations. The general allomitric equation developed in our study is an alternative approach to estimate biomass by using plot data collected in national forest inventory data. The stem volume-biomass equation could be applied with the stand volume and area data from forest inventory to estimate the biomass at large scale.2. The plot data from Hunan forest inventory in 2004 were used to estimate the total biomass of C. lanceolata forests. The total biomass ranged between 124.0 and 96.4Tg, averaged to 47.11～36.60t·ha-1. The C. lanceolata forests biomass density was found to be high in the west and south of Hunan, but low in the central and north Hunan. As the majority of C. lanceolata forests were at young age class and middle age class, the biomass density was lower than 60t.ha-1, suggesting that there is a high potential in improvement of carbon storage.3. The two estimating methods (allometric equations and biomass expansion factors) combined with forest inventory data to estimate forest biomass carbon storage at large scale were feasible. Based on the large plot data, general allometric equation method could produce a more accuracy estimation and provide a spatial distribution of forest biomass, compared to the volume-derived-biomass method. When it is difficult to obtain plot data, the volume-derived-biomass method is an alternative to estimate biomass by using forest inventory data of stand volume and area. When the total biomass at large scale is required to be estimated, the volume-to-biomass linear transformation equation without consideration of age class could be used, but the impact of forest age class and the volume-biomass equation for each age class should be used to assess changes in forest carbon storage or compare the difference of stand biomass of different age class.