摘要
天气模型中应用随机模拟方法,产生以天或小时为时间间隔的气温、降水、相对湿度、云量、太阳辐射等天气要素的动态变化时间序列。利用北京地区近30年天气资料进行了模拟验证,模拟结果与实际的天气变化进程相符。生理生态模型描述了净光合速率、气孔传导度、蒸腾速率、水分利用效率的变化机理。结合开顶式CO_2浓度倍增大豆(Glycine max(L.)Merr.)生长实验,分析了这些生理生态特性在全球变化下的动态响应机制,并进行了模拟预测。结果表明:CO_2浓度倍增情况下,净光合速率提高45％,其中光量子效率显著增加,而CO_2传导系数略有下降;气孔传导度、蒸腾速率下降约30％;水分利用效率随CO_2浓度增加几乎呈线性增长,倍增后提高近一倍。
Plant growth is affected by atmospheric CO2 concentration in two ways. On one hand, CO2, as a substrate of assimilation, has a direct effect on plant physiological process, such as photosynthesis , respiration, transpiration and so on. On the other hand, as a green house gas, the variation of CO2 concentration can induce climatic change, which can indirectly influence plant growth. In the last decade, a large body of studies were done on the direct effects of CO2 increasing on plant growth. However,only a few of them considered the combined effects of increased CO2 and climatic change on plant growth. Since it is very difficult to experiment with both the direct and indirect effects of CO2 , using a simulation model, if not the only way, is a very important approach in the global change study. The authors presented first a stochastic weather generator in which stochastic simulation was applied to produce the daily or hourly time series of the weather factors, such as temperature, precipitation, relative humidity, etc. The monthly data of 1951 to 1980 and daily data of 1981 to 1983 from Beijing Meteorological Station were used to parameterize and validate the weather generator. The results showed that the simulated series conformed to the observed ones very well. The second part of this work was the establishment of a plant ecophysiological model at leaf scale. The model consisted of a mechanistic leaf photosynthesis model, a stomatal conductance model, a transpiration model and a model of water use efficiency (WUE). On the basis of results obtained from an experiment in which C3 plant soybean ( Glycine max (L.) Merr.) was grown in an open-top chamber with both ambient (350 mol mol-1) and doubled (700 mol mol-1) CO2 concentrations, the key parameters were estimated by fitting the model to the measured data using nonlinear regression. The predicted values of photosynthesis, stomatal conductance, transpiration and WUE by the model were shown to be in close agreement with observations. Parameter analyses showed that the quantum efficiency, a, was significantly increased by CO2 enrichment while the CO2 conductance coefficient , was slightly decreased by elevated CO2. When temperature and soil water content were not limiting factors for plant growth, the prediction by the model showed that the net photosynthesis rate would increase by about 45% , stomatal conductance decrease by 30% , transpiration rate reduce by 30% ,and water use efficiency increase by 100% , as CO2 concentration doubled from 350 mol mol-1 to 700 mol mol-1.
基金
国家自然科学基金
