Spatial distribution of soil carbon and nitrogen storage and forest productivity in a watershed planted to Japanese cedar (Cryptomeria japonica D. Don)
Spatial distribution of soil carbon and nitrogen storage and forest productivity in a watershed planted to Japanese cedar (Cryptomeria japonica D. Don)
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种植日本柳杉（Cryptomeria japonica D. Don）的流域土壤碳氮储存量和森林生产力的空间分布
DOI：
10.1007/s10310-006-0222-y
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发表时间：
2006
影响因子：
1.5
通讯作者：
K. Zushi
中科院分区：
文献类型：
--
作者：
K. Zushi
利用数字地形模型研究了柳杉林地土壤碳、氮储量和立地生产力的空间变异。唐）站起来。在富山县205公顷Myougodani流域的29个日本雪松林分表层土壤（0 - 25 cm深）中测定了土壤C和N贮量。地位指数（C. 40年生的高度）作为森林生产力的量度。七个地形属性（海拔，坡度，方面，剖面曲率，平面曲率，开放性和湿度指数）计算从数字高程模型。土壤C、N贮量与坡度呈负相关，与开阔度呈正相关。立地指数的变化与湿润指数密切相关。以地形属性为解释变量的预测模型解释了土壤碳储量变异的50%、土壤氮储量变异的53%和立地指数变异的75%。这一结果表明，该技术是有用的估计土壤性质和生产力的空间分布在森林景观。地位指数与土壤C、N贮量无相关性。在地理信息系统中使用的预测模型显示，森林生产力的空间分布有很大的不同，从土壤碳和氮储量。
Digital terrain modeling was used to evaluate landscape-level spatial variation of soil C and N storage and site productivity in Japanese cedar (Cryptomeria japonicaD. Don) stands. Soil C and N storage were measured in samples from surface soils (0–25 cm depth) of 29 Japanese cedar stands in the 205-ha Myougodani watershed, Toyama Prefecture. The site index (C. japonicatree height at age 40 years) was used as a measure of forest productivity. Seven terrain attributes (elevation, slope gradient, aspect, profile curvature, plan curvature, openness, and wetness index) were calculated from a digital elevation model. Soil C and N storage were negatively correlated with slope gradient and positively correlated with openness. Variation in the site index was closely related to the wetness index. The prediction models using terrain attributes as explanatory variables explained 50% of the variability in soil C storage, 53% of the variability in soil N storage, and 75% of the variability in site index. This result demonstrated that this technique is useful for estimating the spatial distribution of soil properties and productivity in forest landscapes. On the other hand, there was no correlation between site index and soil C and N storage. Use of the prediction models in a geographic information system revealed that the spatial distribution of forest productivity differed considerably from those of soil C and N storage.