| 山西高原落叶松人工林土壤呼吸的空间异质性 |
| 摘要点击 2266 全文点击 1122 投稿时间：2014-10-27 修订日期：2014-12-23 |
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| 中文关键词 土壤呼吸 空间特征 半方差函数 落叶松人工林 庞泉沟自然保护区 |
| 英文关键词 soil respiration spatial characteristics semi-variance analysis larch plantation Pangquangou Nature Reserve area |
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| 中文摘要 |
| 基于对华北落叶松(Larix principis-rupprechtii)人工林样地3个取样尺度(4、2、1 m)土壤呼吸(Rs)及其影响因子的观测,运用传统和地统计学的方法分析了Rs的空间变异性及其与影响因子之间的内在联系. 传统统计分析表明: Rs及其它相关因子的空间变异均属于中等变异; Rs与10 cm、15 cm深度的土壤温度(T10、T15)和全氮(N)呈极显著正相关(P<0.01),与凋落物含水量(Lm)呈显著正相关(P<0.05),与碳/氮比(C/N)呈显著负相关(P<0.01),与5 cm深度的土壤温度(T5)、土壤水分(Ws)、凋落物量(Lw)和全碳(C)相关性不显著(P>0.05); 多元逐步回归分析表明: Lm、T10、N和Ws 这4个因子能解释土壤呼吸空间变化的36%. 地统计学分析表明: Rs具有中等程度的空间自相关性,随机部分引起的空间异质性占39.5%,结构因素占60.5%,气候、地形、土壤等结构因素起着主导作用; 不同土壤指标的变程不相同,Rs和T10的变程差异不大,在25 m左右; 土壤各指标的分维数大小依次为: Lw(1.95)=C/N比(1.95) > N(1.91) > C(1.89) > Rs(1.78) > Lm(1.77) > Ws(1.69) > T10(1.42). Rs的空间分布模式与T10、Lm、C和N的空间分布模式较为一致,而与Ws、C/N比的空间分布模式不同; 在同一置信水平和估计精度下,不同土壤指标的必要采样数量不相同,取决于该指标的空间变异程度. |
| 英文摘要 |
| Based on the data from a planted larch forest in Panquangou Natural Reserve of Shanxi Province, at three sampling scales (4, 2, and 1 m, respectively), soil respiration (Rs) and its affecting factors including soil temperature at 5 cm (T5), 10 cm (T10), and 15 cm (T15) depths, soil water content (Ws), litter mass (Lw), litter moisture (Lm), soil total carbon (C), and soil total nitrogen (N) were determined. The spatial heterogeneities of Rs and the environmental factors were further analyzed and their intrinsic correlations were established. The results of traditional statistics showed that the spatial variations of Rs and the all measured factors were in the middle range; Rs were highly significantly positively correlated with T10, T15, and N (P<0.01); significantly positively correlated with Lm (P<0.05); highly significantly negatively correlated with C/N ratio (P<0.01); and not significantly correlated with T5, Ws, Lw and C (P>0.05). Multiple stepwise regression a2015-4-21 factors of Lm, T10, N, and Ws together accounted for 36% of Rs heterogeneity. The results of geo-statistical analysis demonstrated that Rs was in a medium spatial autocorrelation; random and structural factors accounted for 39.5% and 60.5% of Rs heterogeneity, respectively. And the factors such as climate, landform, and soil played a leading role. The results also illustrated that the ranges for soil factors were different and the range for both Rs and T10 was 25 meters. The fractal dimension of the soil index was in the following order: Lw and C/N ratio (1.95) > N (1.91) > C (1.89) > Rs (1.78) > Lm (1.77) > Ws (1.69) > T10 (1.42). The spatial distribution of Rs was in consistent agreement with those of T10, Lm, C, and N; but different with those of Ws and C/N ratio. With a fixed cofidence level and certain estimated accuracy, the required sampling number of each item differed, corresponding to its spatial variation degree. |
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