| 亚高山草甸土壤呼吸的空间异质性研究 |
| 摘要点击 2288 全文点击 1167 投稿时间：2013-01-16 修订日期：2013-04-20 |
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| 中文关键词 土壤呼吸 空间异质性 地统计学 半方差分析 亚高山草甸 |
| 英文关键词 soil respiration spatial heterogeneity geostatistics semi-variance analysis subalpine meadow |
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| 中文摘要 |
| 运用传统和地统计学的方法,对山西云顶山亚高山草甸的土壤呼吸、土壤温度、土壤水分和土壤有机碳的空间异质性以及它们的关系进行了分析. 传统统计分析表明,土壤呼吸及环境因子均呈正态分布,变异系数在 12%~24%之间,属于中等变异; 土壤呼吸和土壤有机碳的相关系数(r=0.61)大于和温度(r=0.27)、水分(r=0.26)的相关系数,表明土壤有机碳对土壤呼吸空间分布的影响要远大于土壤温度和水分的影响. 地统计学分析结果表明,线性模型能很好地反映土壤呼吸以及环境因子的空间结构特征. 土壤呼吸、土壤温度、土壤水分及土壤有机碳的 C0/(C0+C)值分别为 41%、3%、77%、57%,表明土壤温度具有高度的空间自相关性,土壤呼吸和土壤有机碳具有中等程度的空间自相关性,土壤水分表现出较弱的空间自相关性,结构因素对土壤温度和土壤呼吸的空间分布起着主导作用,而随机因素对土壤水分和土壤有机碳的空间变异则起着主导作用; 土壤呼吸、温度和水分的变程均为 53.2 m,有机碳的变程为 52.1 m; 土壤呼吸和土壤温度具有较好的分形特征,存在尺度上的依赖性. 分维数从大到小依次为:土壤水分(1.96)>土壤有机碳(1.95)>土壤呼吸(1.85)>土壤温度(1.60),表明土壤水分依赖于尺度的变异最小,空间分布结构最复杂,而土壤温度的空间分布格局最简单; 土壤呼吸的空间分布表现出与土壤水分和有机碳相似的特点,并表现出自己的规律性. 随着置信水平和估计精度的降低,土壤呼吸及其影响因子所要求的采样数量均出现较大幅度的下降. |
| 英文摘要 |
| We measured soil respiration (Rs) and the environmental factors influencing Rs including soil temperature (T10), soil water content (SWC) and soil organic carbon (SOC) in a subalpine meadow in Yundin mountain of Shanxi province, and performed an analysis of the heterogeneity of Rs, T10 and SWC and SOC as well as their relationships using both traditional statistics and geostatistics methods. The results from traditional statistics showed that the measured data of Rs and the environmental factors exhibited a normal distribution with variation coefficients ranging between 12% and 24%. The variation of all the measured factors was in the middle range. The fact that the correlation coefficient between Rs and SOC (r=0.61) was larger than that between Rs and T10 (r=0.27) and SWC (r=0.26) indicates that the heterogeneity of Rs was controlled mainly by SOC. The results from geostatistics analyses showed that linear model could reflect the spatial characteristics of Rs and the environmental factors. The C0/(C0+C) values for Rs, T10, SWC and SOC were 41%, 3%, 77%, and 57%, respectively, indicating that the spatial heterogeneities of both Rs and T10 were resulted mainly from structural factor, but the spatial heterogeneities of SWC and SOC were controlled mainly by random factor. The range of semi-variogram function was 53.2 m for Rs, T, and SWC, and 52.1 m for SOC. The fractal dimension value of Rs, T10, SWC, and SOC was 1.85, 1.60, 1.96, and 1.95, respectively, indicating that SWC had the weakest spatial dependence on scale and the most complicated spatial distribution pattern, while T10 had the simplest spatial distribution pattern. The spatial distribution of Rs showed a similar distribution character to both SWC and SOC, but had its own regularity. With the decrease of the confidence level and the estimated accuracy, the required sampling number of the Rs and the environmental factors measurements declined substantially. |
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