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森林资源系统自组织特征研究
  • 期刊名称:南京林业大学学报Vol.32.No5,Sep51-55., 2008
  • 时间:0
  • 分类:S757[农业科学—森林经理学;农业科学—林学]
  • 作者机构:[1]南京林业大学森林资源与环境学院,江苏南京210037, [2]国家林业局调查规划设计院,北京100714, [3]浙江省森林资源监测中心,浙江杭州310020
  • 相关基金:国家自然科学基金资助项目(30571491)
  • 相关项目:森林资源二类调查方法的改进及其动态监测体系的研究
中文摘要:

森林系统演化过程是一个自组织的过程,人类对森林系统的作用是影响森林系统的众多因子之一。为说明森林资源系统属于自组织系统,笔者借助3个临界性指标进行检测,即空间尺度的分形结构、时间尺度的1/f涨落和等级尺度的齐夫定律,并以浙江省森林资源清查数据为样本,对森林资源系统的上述指标进行定量分析。结果表明森林资源系统服从上述3个判据,因此森林资源系统是自组织的,可采用森林资源清查数据定量分析森林资源系统自组织特征。

英文摘要:

The evolution of forest system was a process of self-organization. The impact of human was one of the factors which affected the forest system. There were three critical indices, i. e. , the fractal structure in the dimension of space, the 1/f fluctuation in the dimension of time, and the Zipf law in the dimension of ranking, which could be used to test whether the forest resource system was a self-organized system. According to the data of national forest inventory and forest resource inventory of Zhejiang province, this paper discusses the three indices. To analyze the fractal structure of space, we divide all the sample plots into 20 groups by forest volume. The first group is made up with all the sample plots have w)lume of 0. 511.0 m^3 , and plots with 1. 0--1.5 m^3 volume make up the second group, and so forth. Then turn the numbers of every group into frequency sequence. By studying the relation between volume and frequency, the result that the forest spatial structure obeys power-law and is fi'actal can be drawn. Next we transform the sequence of different age class volume into time series, and find the time series of forest system show 1/f fluctuation. The third part, we sort the forest volume data of 74 unites in Zhejiang province by descending order and get the result that there is Zipf law in the dimension of ranking by analyzing the log-log plot of data. To sum up, forest resource system is inconformity with the three indices. The supposition that forest resource system is a self-organized system can be verified. What' s more, we find that it is feasible to analyze self-organization characters by forest inventory data.

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