运用改进Richards模型预测马尾松人工林立地指数——以广西高峰林场为例  

Prediction of Pinus massoniana Plantation Site Index Using Improved Richards Model--Take Guangxi Gaofeng Forest Farm as An Example

作　　者：范阔 苏晓慧 张艺超 赵天忠[1] Fan Kuo;Su Xiaohui;Zhang Yichao;Zhao Tianzhong(Beijing Forestry University,Beijing 100083,P. R. China)

机构地区：[1]北京林业大学

出　　处：《东北林业大学学报》2019年第9期48-51,共4页Journal of Northeast Forestry University

基　　金：国家重点研发计划项目(2017YFD0600906)

摘　　要：以广西高峰林场的马尾松人工林为研究对象,选取森林资源二类调查中的海拔高、坡度、坡向、坡位、土层厚度为立地影响因子,采用打分法和灰色关联度分析法计算各立地因子的权重和总得分,将立地因子的总得分与Richards立地指数模型相结合,借助SPSS对模型进行参数估计。结果表明:模型改进后的平均误差和均方根误差比改进前分别降低了7.96%和10.59%,说明改进后的模型,预测林分的优势木高更精准。因此,考虑立地因子影响的Richards模型,为立地质量评价提供了技术支撑。Taking Pinus massoniana plantation in Gaofeng Forest Farm of Guangxi as the research object, considering the influence of site factors synthetically, we selected elevation, slope gradient, slope direction, slope position and soil layer thickness as the main site impact factors in the second type of forest resources survey. The weight and total score of site factors were calculated by scoring method and grey correlation analysis method, and the total score of site factors was calculated. Combining with Richards site index model and using SPSS to estimate the parameters of the model and establish the improved model, the test results show that the average error and root mean square error after the model improvement were reduced by 7.96% and 10.59%, respectively, before the improvement. The Richards model can predict the height of dominant trees more accurately. Considering the influence of site factors, Richards model can provide theoretical support for site quality evaluation.

关 键 词：立地指数 Richards模型 立地因子 关联度 

分 类 号：S750[农业科学—森林经理学]