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土壤氧化亚氮排放时空变异性及其方法研究进展 被引量:9

Spatiotemporal variability of soil nitrous oxide emission and its study methods: A review
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摘要 氧化亚氮(N2O)是一种具有很大增温潜能的温室气体,大气中N2O浓度正处于持续不断的增长过程中。陆地生态系统尤其是农业生态系统为重要的排放源。陆地生态系统土壤N2O排放不仅具有时间变异性还具有较强的空间变异性,因此,研究不同土地利用类型土壤N2O排放的空间变异性,对于准确估算区域N2O排放总量具有重要的意义。本文通过综合分析土壤N2O排放的空间变异性,阐述了影响其排放量的主要驱动因子,如气候、地形地貌、土壤性质以及人类管理活动,总结了不同陆地生态系统N2O排放的空间变异性特征及其相应的研究方法。指出,应该不断改进和完善空间变异性的现有研究方法,并运用其他新颖的时空统计方法如小波分析等开展探索研究;在研究土壤N2O排放空间变异性的同时,需要综合时间变异性的研究;加强对不同土地利用类型下土壤N2O排放时空变异特征的研究,提高估算土壤N2O总排放量的准确度。 Nitrous oxide (N2O) is one of the greenhouse gases with great potential of increasing temperature, and its concentration in atmosphere continues to rise steadily. Terrestrial ecosystems, especially agro-ecosystem, are one of the important sources of N2O emission. The soil N2O emission of terrestrial ecosystems not only shows great temporal variability, but also has strong spatial variability. To investigate the spatial variability of soil N2O emission under different land uses is of significance to accurately estimate the soil total N2O emission at regional scale. Based on the comprehensive analysis on the spatial variability of soil N2O emission, this paper expatiated the main driving factors of soil N2O emission, such as climate, topography, soil properties, and human activities, and summarized the characteristics of the spatial variability of soil N2O emission of different terrestrial ecosystems and related study methods. It would be necessary to unceasingly improve and develop related methods, and use innovative methods such as wavelets method for studying the spatial variability of soil N2O emission, integrating the temporal dimension. In addition, more attention should be paid to the spatiotemporal variability of soil N2O emission of different land use types, and to the accuracy of the estimation of soil total N2O emission.
作者 付晓青 李勇
出处 《生态学杂志》 CAS CSCD 北大核心 2012年第3期724-730,共7页 Chinese Journal of Ecology
基金 中国科学院"百人计划"和国家自然科学基金项目(41171200)资助
关键词 氧化亚氮 空间变异性 驱动因子 研究方法 nitrous oxide spatiotemporal variability driving factor study method.
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参考文献49

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