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基于Ripley L和O-ring函数的森林景观空间分布格局及其关联性

董灵波1,刘兆刚1**,张博2,袁野1,孙云霞1   

  1. (1东北林业大学林学院, 哈尔滨 150040; 2吉林省林业勘查设计研究院, 长春130022)
  • 出版日期:2014-12-18 发布日期:2014-12-18

Forest landscapes’ spatial point patterns and associations based on Ripley L and O-ring functions.

DONG Ling-bo1, LIU Zhao-gang1, ZHANG Bo2, YUAN Ye1, SUN Yun-xia1   

  1. (1College of Forestry, Northeast Forestry University, Harbin 150040, China; 2Forest Saevey and Design Institute of Jilin Province, Changchun 130022, China)
  • Online:2014-12-18 Published:2014-12-18

摘要: 采用空间点格局分析中的Ripley L和O-ring函数,以大兴安岭盘古林场森林资源二类调查数据为例,对比分析2种方法在森林景观类型的空间分布格局及其关联性研究中的差异.结果表明: 2种方法获得的景观空间分布格局在整体趋势上反映一致,都是在中小尺度上呈聚集分布,之后随着尺度的增大主要表现为随机分布特征;景观类型间的关联性存在显著差异,其中,Ripley L函数结果表明,天然落叶松林、天然白桦林分别与针阔混交林在中小尺度上呈负相关,而在更大尺度上整体表现出无关联性或正关联性的趋势,其余景观类型间在所有研究尺度上呈显著负相关; O-ring函数结果则表明,4种森林景观类型两两之间均呈现出相似的关联性变化趋势,即在小尺度上均表现为负相关,在中等尺度上均呈现出不相关性,但在更大尺度上呈正相关趋势;对同一景观类型(或景观类型组),2种方法在不同尺度等级上的空间分布格局及其关联性的判别一致率存在较大差异,其一致性判别率在所有研究尺度上整体呈现出基本不变、先下降后增加和一直下降3种趋势.

Abstract: Based on the data of forest resource inventory in Pangu Forest Farm of Great Xing’an Mountains in northeastern China, the spatial distribution pattern and associations of the main forest landscape types [natural Larix gmelini forest (NLG), natural Betula platyphylla forest (NBP), natural coniferous mixed forest (NCM) and natural mixed broadleafconifer forest (NCB)] were studied by the two main spatial point pattern analysis methods (Ripley L and O-ring functions). The results showed that the spatial distribution pattern of the four forest landscape types were all consistent with each other the whole, which were all significantly clumped at small scale, and then mainly the obvious characteristics of random distribution with the increase of scale. Spatial associations of the four forest landscape types differed significantly with the Ripley L and O-ring functions. The results of Ripley L function showed that NLG and NCB, NBP and NCB had the obvious negative correlations at small and medium scales, and then mainly showed the trend of noncorrelations or even positive correlations at medium and large scales, however, there were significantly negative correlations for the other forest landscape types at all the research scales. Unlike the results of Ripley L function, the results of O-ring function showed that the main forest landscape types were all significantly negative at small scale, no at medium scale, and positive at large scale with each other. Meanwhile, there were also significant differences for the spatial distribution patterns and associations for the same forest landscape type (or group) at the same level of scale with two different methods, and the rate of consistency of the two methods  at all levels of scale mainly exist three forms, i.e. basically remain unchanged, reduced firstly and then increased, and almost always reduced, respectively.