| Chinese fir (Cunninghamia lanceolata (Lamb.) hook) has been planted for more than1000years in China, which is the special and native and fast growing tree species dominated in subtropical southern China. In the past three decades, more than9.21million hectares of C. lanceolata have been established in Southern China. Since1970s, lots of research projects have been conducting to monitor and calculate the changes in structure, function and productivity of C. lanceolata at all temporal-spatial scales. Biomass and productivity are the important indicators of functions in forest ecosystems and have been used to evaluate forest production potential, to estimate carbon storage and reduction on the greenhouse effect at large scale. Long term research of biomass was a key role in maintaining stand productivity and sustainable management of C. lanceolata. However, how to accurately estimate biomass production and potential in C. lanceolata has attracted more major attentions in recent years in terms of complexities. The research content and range concerning global change at large scale is far beyond the traditional ecosystem study at forest stand level. It requires the technical breakthrough. Extrapolation from the results of forest stand level to landscape, region or even whole biosphere has been the current important ecological issues. For a long time, the study of forest production mostly focus on stand or national scale, but the data at regional scale are limited.Here a hybrid model, TRIPLEX, was employed to simulate the long-term regional potential of standing biomass and net primary productivity (NPP) on C lanceolata in Hunan province, subtropical southern China. About10years of continuous climate data (2000-2010), the forest inventory records of2009from the study area, the dataset of climate, hydrology, soil and vegetation as well as a set of site-and specific-parameters, were used to initialize and parameterize the model. Simulated values of average stand diameter at breast height (DBH) and height (H) were validated against the data of702permanent plots of C. lanceolata forest stands, with stand age ranging from1to47year old, in Hunan Province, China. Simulated DBH and H values are consistent with observed data. The main results were as the follows:The total biomass accumulation was the lowest in2010, with the average value for all sites of28.97t ha-1, and with the total value for Hunan province of 72.99x106t. Then increased gradually to the value of235.66t ha-1and593.63x106t for sites averaged value and province total value, respectively, until the end of simulation period (year2060). Whereas the average net primary productivity (NPP) of C. lanceolata forest was higher before2020and decreased until the end of2060. Averaged over the simulated60-years period (year2010-2060), the NPPof the total702permanent plots of C. lanceolata forest stands was6.96t ha-1year-1and17.53x106t year-1, respectively. The net production was composed mainly of young and middle-age forest s and had some differences between different regions with the NPP higher in northeast and southwest, and lower in other regions. From2010to2018, the NPP of all sample sites of C. lanceolata forest increased from6.28t ha-1year-1to the maximum value of8.09t ha-1year-1, with the total NPP for Hunan province of15.81x106t year-1and20.38x106t year-1, respectively. Then, the NPP decreased as the forest aged, thereafter. Till2060, the NPP for average value of all sites was6.26t ha-1year-1and the value for Hunan province was14.793x106t year-1. The average biomass in C. lanceolata forest stands ranged from6.96to8.09t ha-1year-1.Our results indicated that the TRIPLEX model could be applied to simulate forest growth and biomass dynamics in subtropical forest ecosystems, and had ability to extrapolate outcomes at regional scales and to simulate carbon storage in subtropical forests. |
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