Analyzing And Simulating The Growth Of Picea Schrenkiana Forests In Xinjiang Under Global Climate Change

During the period from 1961 to 2000, the annual mean temperature increased and precipitation varied markedly in four study sites in the northern slope of the Tianshan Mountain. These historical climate changes may have had significant impacts on the growth of regional Picea schrenkiana forests that have not been previously quantified. We used the process-based biogeochemistry model BIOME-BGC and the dendroecological method to examine the impacts of climate change and the historical rises in atmospheric [CO2] on the growth of the Picea schrenkiana forests in the northern slope of the Tianshan Mt., Xinjiang during the period from 1961 to 2000, and to predict the potential changes in the productivities of Picea schrenkiana forests based on the future climatic change scenario. Four sites representing different climatic conditions were selected for this study: Zhaosu (ZS) in the west Tianshan, Tianchi (TC) and Xiaoquzi (XQZ) in the central Tianshan, and Yiwu (YW) in the east Tianshan, respectively. Using the BIOME-BGC model, we simulated the net primary productivity (NPP) of Picea schrenkiana forests in the four study sites under the current climatic conditions. The simulated results showed good agreement with observations of net primary productivity, and the trends in NPP were consistent with observed tree-ring width standard index (RWSI) in all sites. When the atmospheric CO2 was increased from 355 to 710 ppmv without changing other climatic factors, equilibrium simulations of the model suggested an increase of net primary production by 4.44% to 6.60% across the four study sites. This result agreed with the other studies. All the validations suggested that BIOME-BGC model could be used as a diagnostic tool to investigate the response of Picea schrenkiana forest to climatic change and CO2 concentration elevation. After the validation, BIOME-BGC was used to simulate NPP changes during the study period. The tree-ring width standard index was used to estimate, for each stand, an observed series of changes in productivity. The annual NPP and RWSI showed substantial interannual variations, with the temporal patterns differed among the different study sites. The trend analysis showed that in response to climate variability and increasing atmospheric CO2 concentration over the period of 1961-2000, the growths of Picea schrenkiana forests increased in all the study sites except Zhaosu. The period from 1987 to 2000 had greater changes in NPP and diameter increment than from 1987 to 2000, corresponding to an abrupt change in climate pattern since 1986. Sensitivity analysis suggests that Picea schrenkiana forests are sensitive to climate variability and increasing atmospheric CO2, especially changes in annual precipitation. Our analysis indicated that changes in both precipitation and temperature affected the forest productivity by influencing soil moisture and nutrient availability, and that the increased atmospheric CO2 attributed to improved plant water use efficiency. It is clear that global climate change as reflected by increasing temperatures and changes in the patterns of precipitation, as well as altered atmospheric composition already have, and will continue to impose, profound effects on the functioning and productivity of terrestrial ecosystems. In this study, BIOME-BGC was used to simulate the responses of forest productivity to doubled [CO2] scenario. The future climate scenario was derived from a second-generation regional climate model (RegCM2). For all the study sites, the model simulations showed that the productivity would increase slightly (from –2.50 to 8.62%) when only the fertilizing effect of the doubled [CO2] was considered, increase moderately (from 13.33 to 29.11%) when climate change were taken into account, and increase markedly (from 26.43 to 37.24%) when both climate change and the [CO2] increase were considered. The results indicated that climate change and elevated CO2 had strongly interactive effects on NPP. It is well know that tree-ring chronologies could provide long-term records ofgrowth under natural environmental conditions and could be used to evaluate biogeochemistry model. Simulation models, when coupled with carefully planned field experiments such as dendroecological method, could assist in understanding the impact of CO2 increase and climatic change on forest productivity. Picea schrenkiana forest is one of the most productive and widespread forest types in the boreal forest of Northwestern China, and its growth increased based on the climate change. Thus the Picea schrenkiana forest region is likely to be a major potential carbon sinks in the future.