Spatial variations in throughfall in a Moso bamboo forest: sampling design for the estimates of stand‐scale throughfall
Spatial variations in throughfall in a Moso bamboo forest: sampling design for the estimates of stand‐scale throughfall
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DOI：
10.1002/hyp.7473
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发表时间：
2009-09
影响因子：
3.2
通讯作者：
Yoshinori Shinohara;Yuka Onozawa;M. Chiwa;T. Kume;H. Komatsu;K. Otsuki
中科院分区：
文献类型：
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作者：
Yoshinori Shinohara;Yuka Onozawa;M. Chiwa;T. Kume;H. Komatsu;K. Otsuki
我们调查了穿透雨（Tf）的空间和季节变化与冠层结构和总降雨量（Rf）的空间和季节变化的关系，并评估了Tf变化对林分尺度Tf估计的影响。在毛竹林中设置25个网格，每月观测一次叶面积指数（LAI）和每周观测一次转铁蛋白（Tf），观测一年。平均叶面积指数和叶面积指数的空间变异有一定的季节变化。Tf的空间变异随着Rf的增加而减小，且Tf的空间变异与Rf的关系在全年都保持不变。这些结果表明，叶面积指数的季节变化对转铁蛋白的空间变异影响不大，而转铁蛋白是决定研究地点转铁蛋白空间变异的关键因子。我们使用Monte Carlo抽样，基于实测Tf数据评估了林分尺度Tf估计值的潜在误差。结果表明，当样本量小于1008时，误差随样本量的增加而显著减小，而当样本量大于8时，误差基本稳定。基于Student t值分析，样本量为8的Tf估计值误差小于10%，考虑到Rf数据中包含的误差，这对于拦截损失估计值是令人满意的。版权所有© 2009约翰威利父子有限公司。
We investigated the spatial and seasonal variations in throughfall (Tf) in relation to spatial and seasonal variations in canopy structure and gross rainfall (Rf) and assessed the impacts of the variations in Tf on stand‐scale Tf estimates. We observed the canopy structure expressed as the leaf area index (LAI) once a month and Tf once a week in 25 grids placed in a Moso bamboo (Phyllostachys pubescens) forest for 1 year. The mean LAI and spatial variation in LAI did have some seasonal variations. The spatial variations in Tf reduced with increasing Rf, and the relationship between the spatial variation and the Rf held throughout the year. These results indicate that the seasonal change in LAI had little impact on spatial variations in Tf, and that Rf is a critical factor determining the spatial variations in Tf at the study site. We evaluated potential errors in stand‐scale Tf estimates on the basis of measured Tf data using Monte Carlo sampling. The results showed that the error decreases greatly with increasing sample size when the sample size was less than ∼8, whereas it was near stable when the sample size was 8 or more, regardless of Rf. A sample size of eight results in less than 10% error for Tf estimates based on Student's t‐value analysis and would be satisfactory for interception loss estimates when considering errors included in Rf data. Copyright © 2009 John Wiley & Sons, Ltd.