论文部分内容阅读
本文逐日计算了土壤的生物学活动,使用的是非洲气象站的标准气象数据、一个简单的土壤水分模型,并且使用了关于温度、土壤含水量和生物学活动之间关系的一般性假设。活动系数r_(e_clim)由日土壤湿度和温度计算得出,从而考虑了温度与湿度之间的交互作用。瑞典中部(粘壤土,无作物)r_(e_clim)的年均值标准化为1,在那里进行了最初的校准。由于土壤在储水能力和植物覆被上的差异会对蒸腾作用产生影响,所以我们选择的样地均为无作物的该土壤,这样就只包括了气候差异。瑞典r_(e_clim)值,1,相当于诸如表土中含有的谷类秸杆等的年质量亏损约50%。非洲r_(e_clim)年均值在干热地点(法亚,乍得)为1.1,温湿地点(布拉柴维尔,刚果)为4.7之间变动。肯尼亚样地的r_(e_clim)值为2.1(高海拔,Matanya)至4.1(肯尼亚西部,Ahero)。这意味着假如土壤类型和经营相同,那么必须有4.1倍于瑞典的碳输入才能将Ahero的土壤碳水平维持在瑞典水平。对每一块样地都绘制了r_(e_clim)日动态图,并讨论了年内动态差异。模拟实验表明,如果将土壤碳平衡的瑞典土壤移至肯尼亚的Ahero,30年内其土壤碳将损失41%。如果将Ahero保持碳平衡的土壤移至瑞典,30年内其土壤碳含量将增加64%。本文讨论了方法与结论的有效性,并将r_(e_clim)与其它气候指数进行了对比。本文还提出了一种对r_(e_clim)值进行粗略估计的简易方法。
This paper calculates daily soil biological activities using standard meteorological data from an African meteorological station, a simple model of soil moisture, and uses general assumptions about the relationship between temperature, soil water content and biological activity. The activity coefficient r_ (e_clim) is calculated from the daily soil moisture and temperature, accounting for the interaction between temperature and humidity. The annual average of r_ (e_clim) in central Sweden (clay loam, no crop) is normalized to 1, where the initial calibration was performed. Since differences in soil water storage capacity and plant cover will have an effect on transpiration, we selected all samples to be crop-free so that only climate variability was included. The Swedish r_ (e_clim) value, 1, corresponds to about 50% of annual mass loss such as cereal straw contained in the topsoil. The annual average of r_ (e_clim) in Africa is 1.1 between dry and hot locations (Faia, Chad) and 4.7 between warm and humid locations (Brazzaville, Congo). The r_ (e_clim) values for the Kenyan sample range from 2.1 (Matanya) to 4.1 (Ahero, Western Kenya). This means that if soil types and operations are the same, there must be 4.1 times the Swedish carbon input to maintain Ahero’s soil carbon levels at the Swedish level. The r_ (e_clim) daily dynamic plot was plotted for each plot and the dynamic differences during the year were discussed. Simulations have shown that if soil from Swedish soil with balanced soil carbon is moved to Ahero, Kenya, soil carbon losses will be 41% for 30 years. Moving Ahero’s soils that remain carbon-balanced to Sweden will increase soil carbon content by 64% in 30 years. This paper discusses the effectiveness of the methods and conclusions, and compares r_ (e_clim) with other climatic indices. This article also presents a simple method for rough estimation of r_ (e_clim) values.