短距离样点对土壤呼吸空间变异预测精度的影响

不同采样设计会对土壤呼吸空间变异特征的预测精度产生重要影响。本研究选取黄淮海平原北部潮土区1 km×1 km夏玉米样地,在7×7单元规则格网(样点间距167 m)、完全随机(样点平均间距433 m)以及3×3单元规则格网+完全随机(样点平均间距405m)3种布点方式的基础上,保持样本总量(49)不变,以占总样点2%～14%的短距离样点(样点间距4m)随机替换原方案相应样点个数的方法优化布点方式,应用普通克里金法插值,以均方根误差(RMSE)和确定系数(R2)作为验证指标,检验基于3种布点方式设置的短距离样点对土壤呼吸空间变异预测精度的影响。结果表明:研究区土壤呼吸平均速率为2.65μmol·m?2·s?1,空间分布均呈西高东低,表现出中等程度变异。采样设计对土壤呼吸空间分布的预测精度影响显著,基于3种布点方式设置短距离样点可提高预测精度7%～13%。无短距离样点替换时,规则格网+完全随机的布点方式最优,比完全随机布点和规则格网布点的空间插值预测精度分别提高10%和22%;设置短距离样点替换后,在最优布点方式(规则格网+完全随机)中,对土壤呼吸空间变异的预测精度可再提高4%～7%,其中短距离样点个数占样本总量10%对土壤呼吸空间变异预测精度的提高最为明显。研究发现,基于相同的样本数量设置短距离样点可增加区域范围内样点密度,提高土壤呼吸空间变异预测精度及试验结果的可靠性。因此,在黄淮海平原北部潮土区100 hm2尺度的夏玉米样地中,规则格网+完全随机+10%短距离样点的布点方式是预测土壤呼吸空间变异最适宜的采样布点方式。

Effects of short distance sampling on the prediction accuracy of the spatial variability of soil respiration

Sampling design is important for the prediction accuracy of the spatial variability of soil respiration. In this study, a plot of 1 km×1 km was selected in a summer maize field from the northern part of the Huang-Huai-Hai Plain. Each of the forty-nine sampling sites were set on the basis of three different sampling designs, including a regular grid of 7×7 unit rule (with a spacing of 167 m), completely random (with an average spacing of 433 m), and a regular grid of 3×3 unit rule combined with completely random (with an average spacing of 405 m). To optimize the layout, based on the 3 designs, we maintained the total number of samples (49) and replaced the original sampling with short-distance sampling points for 2% to 14% of the total number of samples (with a spacing of 4 m). The spatial interpolation was finished with the ordinary Kriging interpolation method. The root mean square error (RMSE) and determination coefficient (R²) were chosen as indicators to investigate the effects of short distance sampling on the prediction accuracy of the spatial variability of soil respiration. The results showed that the spatial distribution of soil respiration under the three sampling designs was high in the west and low in the east, with moderate variation. Different sampling designs had significant impacts on the prediction accuracy of the spatial variability of soil respiration. The short distance sampling under the three sampling designs increased the prediction accuracy of the spatial variability of soil respiration by 7%-13%. Without short distance samples, the sampling design of the regular grid combined with completely random had the highest prediction accuracy, which was 10% and 22% higher than the regular grid and completely random sampling designs, respectively. Upon the replacement with short distance sampling, the prediction accuracy of the optimal sampling design (regular grid combined with completely random) was increased by 4%-7%. The prediction accuracy of the spatial variability of soil respiration was most obviously improved when the proportion of short distance samples was 10% of the whole size. This study found that setting short distance samples based on the same sample size could increase the sample density within a region and improve the prediction accuracy of soil respiration spatial variation and the reliability of experimental results. Therefore, a completely random sampling design combined with a regular grid and 10% short distance samples is a better choice for the soil respiration spatial variation estimation of a 1 km×1 km plot in a summer maize field from the northern part of the Huang-Huai-Hai Plain. The results of this study provide guidance for relevant research and field sampling designs.