欢迎访问林业科学,今天是

林业科学 ›› 2016, Vol. 52 ›› Issue (2): 10-16.doi: 10.11707/j.1001-7488.20160202

• 论文与研究报告 • 上一篇    下一篇

角尺度判断林木水平分布格局的新方法

赵中华, 惠刚盈, 胡艳波, 张弓乔   

  1. 中国林业科学研究院林业研究所 国家林业局林木培育重点实验室 北京 100091
  • 收稿日期:2015-03-13 修回日期:2015-10-26 出版日期:2016-02-25 发布日期:2016-03-25
  • 通讯作者: 惠刚盈
  • 基金资助:
    国家自然科学基金项目(31370638)。

The New Method Judged Horizontal Distribution Pattern by Uniform Angle Index

Zhao Zhonghua, Hui Gangying, Hu Yanbo, Zhang Gongqiao   

  1. Key Laboratory of Tree Breeding and Cultivation, State Forestry Administration Research Institute of Forestry, CAF Beijing 100091
  • Received:2015-03-13 Revised:2015-10-26 Online:2016-02-25 Published:2016-03-25

摘要: [目的] 提出角尺度判断林木水平分布格局的检验方法,以期进一步完善角尺度判断林木水平分布格局理论。[方法] 采用林分空间结构分析软件Winkelmass模拟产生面积为70 m×70 m、不同密度、不同水平分布格局的模拟林分6000个,东北阔叶红松林实测林分2个,验证新方法判断林木水平分布格局的准确性,并与聚集指数R及Ripley's L判断结果进行比较。[结果] 依据随机分布林分角尺度均值(W)符合正态分布的结论及其与标准差的关系,提出通过正态分布检验林分(树种)平均角尺度判断林木水平分布格局的方法。运用正态分布检验林分(树种)平均角尺度的方法判断林木水平分布格局结果与模拟林分水平分布格局的符合率达到了100%,而运用聚集指数R显著性检验判断林木水平分布格局结果的符合率则随着林分密度的增加而增加;面积为70 m×70 m、密度为50株·hm-2时不同水平分布格局的模拟林分判断结果表明,通过正态分布检验林分(树种)平均角尺度判断林木水平分布格局方法不受林木间的距离影响,而相邻单株之间的平均距离是影响聚集指数R判断林木水平分布格局结果的关键因素。甘肃小陇山松栎混交林每木定位数据和吉林蛟河阔叶红松林每木定位数据判断结果表明,在置信水平α为0.05时,新方法对松栎混交林的判断结果与Ripley's L函数点格局分析方法判断结果一致,对阔叶红松林中水曲柳和红松种群水平分布格局判断为随机分布,对林分及其他树种水平分布格局的判断结果与Ripley's L函数一致;而聚集指数R则将松栎混交林中的华山松水平分布格局判断为随机分布,将阔叶红松全林的水平分布格局判断为聚集分布,核桃楸的水平分布格局判断为随机分布;在置信水平α为0.1时,正态分布检验林分(树种)平均角尺度判断林木水平分布格局方法对2个林分/种群的判断结果与Ripley's L函数点格局分析方法判断结果完全一致,而聚集指数R与Ripley's L检验的判断结果的差别明显增加,说明置信水平对水平分布格局判断结果影响比较明显。[结论] 研究提出的正态分布检验林分(树种)平均角尺度判断林木水平分布格局的方法克服了统一的置信区间不适用于评判抽样调查或群落中数量较少的种群水平分布格局问题,进一步完善了角尺度判断林木水平分布格局理论,提升了角尺度判断林木水平分布格局的准确性与适用范围。

关键词: 角尺度, 水平分布格局, 正态分布检验, 方法

Abstract: [Objective] This paper proposed a new method to judge tree horizontal distribution pattern by uniform angle index in order to further improve the theory of the uniform angle index to judge tree horizontal distribution pattern.[Method] 6000 simulated stands with an area of 70 m×70 m and with different densities and distribution patterns were produced by stand spatial structure analysis software (Winkelmass), the 2 field-tested broad-leaved korean pine forests in northeast China were then used to verify the accuracy of the new method for judging the stand and population horizontal distribution pattern, and the results were also compared with R aggregation index and Ripley's L.[Result] According to the conclusion of the mean value of uniform angle index (W) of random distribution stand conform to the normal distribution and its relationships with the standard deviation, this contribution proposed the new method of judgment stand/population spatial horizontal distribution pattern by uniform angle index. The 6000 simulated stands with different density and horizontal distribution patterns were produced by Winkelmass with an area of 70 m×70 m. The results of simulation data showed that the coincidence rate of uniform angle index normal distribution test method was 100% to different density in the same area,and the coincidence rate of aggregation index R increased with the increasing stand area. The judgment results of 70 m×70 m stand area and 50 trees showed that the average distance between adjacent trees was the key factor affecting the judgments results of aggregation index R to tree horizontal distribution pattern and the distance didn't affect the judgment results by the uniform angle index mean value normal distribution test. The results of stand data of temperate pine oak mixed forests on Xiaolongshan showed that stand and population horizontal distribution pattern was consistent with that judged by the new method and Ripley's L test when the confidence level was 0.05, however, the R aggregation index judged Pinus armandii horizontal distribution was random pattern. The results of stand data for Pinus koreansis broad-leaved forest in Jiaohe exhibited that Fraxinus mandshurica and Pinus koreansis horizontal distribution patterns were random by new method, other trees' population were consistent with Ripley's L test. The R aggregation index judged results showed that the stand distribution was cluster pattern, whereas Juglans mandshuric horizontal distribution pattern was random. When the confidence level was 0.1, the results of horizontal distribution pattern judged by the uniform angle index mean value normal distribution test were consistent with Ripley's L test, however, the difference increased significantly when judged by the R aggregation index with Ripley's L test, the confidence level influenced the pattern of the judgment results obviously.[Conclusion] Using the normal distribution test of uniform angle index mean value to judge the stand/population horizontal distribution pattern overcome the two problems.Firstly, uniform confidence interval is not suitable for evaluating the horizontal distribution pattern of sample surveys;Secondly,the distribution pattern of community in less population number might be soloved.Furthermore,this study could improve the theory of the uniform angle index to judge distribution pattern of trees, and enhance the accuracy and application scope.

Key words: uniform angle index, horizontal distribution pattern, the normal distribution test, method

中图分类号: