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干湿交替格局下黄土高原小麦田土壤呼吸的温湿度模型
引用本文:张红星,王效科,冯宗炜,宋文质,刘文兆,李双江,朱元骏,庞军柱,欧阳志云.干湿交替格局下黄土高原小麦田土壤呼吸的温湿度模型[J].生态学报,2009,29(6):3028-3035.
作者姓名:张红星  王效科  冯宗炜  宋文质  刘文兆  李双江  朱元骏  庞军柱  欧阳志云
作者单位:1. 中国科学院生态环境研究中心城市与区域生态国家重点实验室,北京,100085
2. 中国科学院水土保持研究所长武黄土高原农业生态试验站,陕西,722400
基金项目:国家自然科学基金,国家重点基础研究发展规划(973计划),中国科学院创新工程重大项目 
摘    要:全球气候变化的直接后果是气温升高,同时还可能引起强降雨增多和干旱频发,形成干湿交替的格局.土壤呼吸在全球变化过程中发挥着重要作用.以黄土高原沟壑区小麦田土壤为研究对象,采用3个全自动多通量箱以及相应的气象监测系统,对土壤呼吸和环境因子全天候连续测定,利用已有的单因子模型、双因子模型对测定的土壤呼吸与气温和湿度的关系进行了拟合,通过优化,根据实际情况提出E-Q(exponential-quadratic)模型.结果表明:(1)干湿交替格局下,基于气温的单因子模型(指数模型,幂函数模型和线性模型)不适合模拟土壤呼吸;(2)基于土壤湿度的单因子模型中,二次曲线模型最适合模拟干湿交替格局下土壤呼吸的响应情况;(3)基于气温和土壤湿度的双因子模型中,E-Q模型SR=aebT(c+dW+fW2)g,既能反映土壤呼吸随气温的正向指数变化,又能表现土壤湿度对土壤呼吸的双向调节作用,解释了土壤呼吸73.05%的变化情况,比其他双因子模型和单因子模型更能有效描述干湿交替情况下土壤呼吸对气温和土壤湿度协同变化的响应特征.

关 键 词:干湿交替  黄土高原  小麦田  土壤呼吸  温度  湿度  模型
收稿时间:2008/11/20 0:00:00
修稿时间:3/3/2009 12:00:00 AM

Modeling soil respiration using temperature and soil moisture under alteration of dry and wet at a wheat field in the Loess Plateau, China
ZHANG Hong-Xing,WANG Xiao-Ke,FENG Zong-Wei,SONG Wen-Zhi,LIU Wen-Zhao,LI Shuang-Jiang,ZHU Yuan-Jun,PANG Jun-Zhu,OUYANG Zhi-Yun.Modeling soil respiration using temperature and soil moisture under alteration of dry and wet at a wheat field in the Loess Plateau, China[J].Acta Ecologica Sinica,2009,29(6):3028-3035.
Authors:ZHANG Hong-Xing  WANG Xiao-Ke  FENG Zong-Wei  SONG Wen-Zhi  LIU Wen-Zhao  LI Shuang-Jiang  ZHU Yuan-Jun  PANG Jun-Zhu  OUYANG Zhi-Yun
Institution:Research Center for Eco-environmental Sciences, Chinese Academy of Sciences,Research Center for Eco-environmental Sciences, Chinese Academy of Sciences,,
Abstract:Soil heterotrophic respiration is a major way leading to losses of soil carbon into the atmosphere and plays an important role in global carbon cycle. Global warming may cause increases in rainfall or droughts that would enhance the variation of soil moisture. However, it is unclear that how the soil respiration will respond the co-effects of the simultaneous changes in air temperature and soil moisture. Our experimental site was located in a wheat field in the Loess Plateau of China. Rainfall was the sole way to deliver water into the soil at the site. It was observed that three heavy rainfall events caused significant alterations of the soil moisture in the period from spring to summer in 2005. During the same period, the air temperature increased significantly due to the monsoon climate. Soil respiration rates were measured in situ with three chambers of an automated multi-channel chamber system; relevant environmental factors were also simultaneously recorded. Correlations of the soil respiration rates with (1) the air temperature, (2) the soil moisture, and (3) both the air temperature and soil moisture were calculated. Temperature dependent models, soil moisture dependent models and double predictor models which based on both air temperature and soil moisture were used to fit the data. Through the tests against our field data sets, we built a E-Q model as SR=aebT(c+dW+fW2)g. Our conclusions are as flows: (1) the single predictor models based on only air temperature were not capable of predicting the soil respiration rates for the experimental field due to the significant alterations in the soil moisture; (2) among the soil moisture dependent models, the quadratic model was better than the linear model or the exponential model; (3) the E-Q model, which predicted soil respiration rates based on the exponential relation with air temperature as well as the opposite effect of soil moisture, was more capable for soil respiration predictions for the fields in this climate zone.
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