福建西部山地水土流失区土壤呼吸的空间异质性

土壤呼吸(Rs)作用的空间异质性对于准确估算水土流失区碳收支具有重要意义.通过对长汀县河田镇59个样地的土壤呼吸及土壤全氮(TN)、碳氮比(C/N)、有机碳含量(SOC)、叶面积指数(LAI)、土壤温度(T_(10))、土壤湿度(W)等影响因子测定的基础上,运用传统和地统计学的方法分析了土壤呼吸及其影响因子的空间异质性.结果表明,Rs及其影响因子的变异程度大小依次为:LAISOCTNRsC/NT_(10)W;Rs与T_(10)呈极显著正相关(P0.01),与TN呈显著正相关(P0.05),与其他因子的相关性不显著(P0.05);TN、SOC和T_(10)这3个因子可以解释土壤呼吸27%的空间变化.地统计学分析结果表明:Rs具有中等程度的空间自相关性,结构性因子引起的空间异质性占52.89%,与随机因素的占比(47.11%)相当;Rs及其影响因子的分维数大小依次为:RsLAIC/NT_(10)SOCWTN;Rs的空间分布格局与TN和T_(10)的空间分布格局较为一致,而与C/N、SOC、LAI的空间分布格局不同.在95%置信水平和90%估计精度下,Rs的合理采样数量为62个.

Spatial Heterogeneity of Soil Respiration in the Soil Erosion Area of West Mountains in Fujian Province, China

The spatial heterogeneity of soil respiration (R_s) is of great significance in accurately estimating the carbon budget in erosion areas. This study investigated the soil respiration (R_s), total nitrogen (TN), carbon-nitrogen ratio (C/N), soil organic carbon content (SOC), leaf area index (LAI), soil temperature (T₁₀), and soil moisture (W) in 59 soil samples collected from Hetian Town in Fujian Province. Both classical statistics and geostatistics were used to analyze the spatial heterogeneity of soil respirations and other measured factors. The variability of R_s and other measured factors in the samples ranked from the largest to the smallest: LAI > SOC > TN > R_s > C/N > T₁₀ > W. R_s was positively correlated with T₁₀ (P<0.01) and with TN (P<0.05), but not significantly correlated with other factors (P>0.05); TN, SOC and T₁₀ could be used to explain the spatial variation of soil respiration among the samples. The results from geo-statistical analysis showed that R_s was in a medium spatial autocorrelation, with 52.89% of spatial heterogeneity caused by structural factors and 47.11% of spatial heterogeneity resulted from random factor; the fractal dimensions of soil respiration and its interacted factors were ranked as: R_s > LAI > C/N > T₁₀ > SOC > W > TN; the spatial distribution patterns of R_s were similar with those of TN and T₁₀, but different from those of C/N, SOC or LAI. At the 95% confidence level and 90% estimation accuracy, the reasonable sampling number of R_s was 62.