Study On Forest Biomass And Productivity In China

With the whole forest area of China as study area, a systematic study was conducted on the quantity and spatial patterns of biomasses and productivities of China forests based on the national forest inventory data. Analysis was also performed on factors affecting timber volume increases and productivities of China forests to determine the contributions of these factors based on the inventory data and climatic data from 300 weather stations. The results indicate that:1.The total biomass of forest in China is 1.0666×10¹⁰Mg with unit biomass of 74.7 Mg hm^-2, which mainly distributes in the Daxinganling Mountains, Xiaoxinganling Mountains, Changbai Mountain, Qinling Mountain, Daba Mountain, Transverse Mountain and southeast Tibet. The biomass is also concentrated in Wuyi Mountain and Nanling Mountains. In northwest China, the biomass mainly distributes in Tian Mountain and Altai Mountain. The biomasses of Tibet, Sichuan, Yunnan, Heilongjiang, Jilin and Inner Mongolia account for 69.3% of the national total. Five of the above six provinces except Jilin have biomass over 1.0×10⁹Mg, among which Tibet, Heilongjiang and Inner Mongolia are ranked at the top three. In addition, Fujian, Jiangxi, Hunan, Guangdong, Guangxi, Shananxi and Xijing have forest biomasses over 2.0×10⁸Mg, accounting for 18.1% of the national total. The rest 18 provinces account for only 12.6% of the national total, where Shanghai, Tianjin and Nixia have the least biomasses.2. The total forest productivity of China is 3.331×10⁸ Mg.a^-1 with unit productivity of 2.33 Mg hm^-2 a^-1. The following regions have relatively high productivities: Changbai Mountain, Wuyi Mountain, Hainan Island, Nanling Mountains, Qinling Mountain, Daba Mountain, Xiaoxinganling Mountains, Yan Mountain, and Yunan. Yunnan and Heilongjiang have the highest productivity in China, accounting for 24.6% of the national total, followed by Sichuan, Inner Mongolia, Jilin, Guangxi, Guangdong, Hunan, accounting for 49.9% of the natinal total. All these provinces have forest productivity more than 1.5×10⁷ Mg.a^-1 . The rest 21 provinces account for only 25.5% of the national total. Shanghai, Tianjin and Ningxia have the least productivity.3. At large scales, either over climate zones or within climate zones, forest productivity is significantly correlated with forest stand factors such as stand age, height, closure and density, climatic factors such as annual mean temperature, annual precipitation,topographic factors such as elevation, and soil factors such as soil thickness. Although the relationships are much weaker than those at smaller scales, the multi-variable models can significantly improve them, which also indicates that forest productivity can be expressed as the exponential combination of multi-variables.A multi-variable forest productivity model was established with predictive factors such as forest stand factors and environmental factors using stepwise multiple regression. The complex correlation coefficient is 0.406 and the adjusted determination coefficient is 0.164, which means that less than 20% of the variance of forest productivity of China forest can be explained by the model.The multiple forest productivity models within climate zones can further improve the models' explaining capacity. The model for warm temperate zone has the strongest explaining capacity, which can account for 31.9% of the variance of forest procucti vity.4. The contributions of the predictive factors to forest productivity vary. As for the whole distribution area of forest in China, stand factors, climatic factors, togographic fators and soil factors accounts for 56.3%, 16.5%, 24.4%, 2.3% of the variance of forest productivity explained by the model respectively. This shows that stand characters are still the most important factors, among which stand age prevails. The contributions of these factors vary among climatic zones while stand age remains the most important one.In the dissertation, it is the first time in China that the spatial patterns of forest biomass and productivity of China were analyzed by ground true data, which is also the first time in the world of this kind of research conducted based on ground true data at such a large scale. The more realistic and reliable results in the dessertation can provide valuable basis for validation of estimations of biomass and productivity by remote sensing data. It is also the first time that by taking advantage of the national forest inventory system, the same method and systematic design can be applied for data collection in more than ten thousand plots in this kind of research. It is also the first time that multivariable forest productivity model was established at such a large scale, which can provide useful tools for studing effects of climatic changes on productivities of forest ecosystems.