塞罕坝华北落叶松人工林生产力及其空间分布预测

doi:10.31497/zrzyxb.20190702

摘要/Abstract

摘要： 准确预测森林立地生产力是进行高效森林经营的关键。立地指数是森林生产力可靠的评价指标之一。基于地形、气候和土壤因子以及220块样地解析木数据,采用回归克里格（RK）模型对塞罕坝机械林场华北落叶松（Larix principis-rupprechtii）人工林立地指数（SI）进行空间插值预测,并分析了不同半变异函数对RK模型精度的影响。拟合结果表明：基于高斯半变异函数的RK模型精度优于球状和指数RK模型,且具有较小的残差（RMSE=0.82 m,MAE=0.66 m）,表明高斯RK模型具有很强的预测SI能力;高斯半变异函数分析表明研究区华北落叶松人工林SI存在较强的空间自相关性,且在724.89 m变程内差异显著;影响华北落叶松立地指数分布的主要环境因子有土壤全氮、土壤pH、夏季降水量和春季降水量;立地生产力较高区域一般分布在春季降水适中、夏季降水较多、土壤为中性及偏酸性且全氮含量较高的东南部地区,占研究区总面积的32.00%,而在春、夏季降水量少或者春季降水量过多、土壤全氮含量过低且偏碱性的北部边缘地区立地生产力较低,仅占研究区总面积的8.90%。研究区土壤、气候因子与树木生长习性共同决定了华北落叶松人工林生产力的分布格局。通过降低土壤酸碱度和适当施加氮肥等措施,可以提高华北落叶松人工林生产力。

关键词: 地统计学, 立地指数, 华北落叶松, 环境因子

Abstract: The accurate prediction of forest site productivity is crucial for the effective forest management. Site index (SI) is one of the main measures of forest productivity. In this study, we integrated 220 field inventory, topography, climate and soil factors to predict SI of Larix principis-rupprechtii using regression Kriging (RK) model in Saihanba Mechanized Forest Farm, Hebei province. The influence of different semivariograms on the accuracy of RK model was also analyzed. Fitting results showed that the accuracy of RK model based on Gaussian semivariogram was higher than that based on spherical and exponential semivariogram, and had little residual variation (RMSE=0.82 m and MAE=0.66 m), indicating RK model based on Gaussian semivariogram had a highly predictive power to predict SI in the study area. Gaussian semivariogram analysis showed that there was a strong spatial autocorrelation in SI in the study area, and the spatial variation was significant in the range of 724.89 m; The major environmental factors affecting spatial variation in SI of L. principis-rupprechtii plantations included: soil total nitrogen (TN), soil pH, mean summer precipitation (SUP) and mean spring precipitation (SPP). The sites with high productivity of L. principis-rupprechtii might tend to potentially occur in the southeast part with suitable SPP, relatively high SUP, neutral or acidic soil and relatively high TN, accounting for 32.00% of the total area of the study region. However, sites with low productivity of L. principis-rupprechtii were typically found at the northern edge with excessive SPP or lower SUP, high soil pH and extremely low TN, only accounting for 8.90% of the whole region. Accordingly, the distribution patterns of productivity for L. principis-rupprechtii plantation were jointly determined by climatic and soil factors as well as tree growth characteristics in the study area. Improving productivity of L. principis-rupprechtii plantation can be realized by soil pH reduction and appropriate nitrogen increase in the study area.

Key words: environmental factors, Larix principis-rupprechtii, geostatistics, site index

李文博, 吕振刚, 黄选瑞, 张志东. 塞罕坝华北落叶松人工林生产力及其空间分布预测[J]. 自然资源学报, 2019, 34(7): 1365-1375.

LI Wen-bo, LYU Zhen-gang, HUANG Xuan-rui, ZHANG Zhi-dong. Predicting productivity and spatial distribution of Larix principis-rupprechtii plantation[J]. JOURNAL OF NATURAL RESOURCES, 2019, 34(7): 1365-1375.

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