随机区块法在空间点格局分析中的应用

Spatial points pattern analysis using random square-quadrats method

利用一种以随机模拟技术为基础的空间点格局分析方法——随机区块法对长白山阔叶红松林中5个主要树种的空间格局及空间关系进行了分析。随机区块法利用ICS(t)=s2(t)/(t)-1来衡量不同尺度t上空间点的分布格局,并通过随机模拟技术构建零假设的95%或99%置信区间,以确定空间点格局偏离零假设的显著性程度。结果表明,除蒙古栎、山荆子、怀槐为随机分布外,其它树种均在局部空间尺度上呈聚集分布;并且绝大多数种对或种组在局部空间尺度上呈正相关关系。随机区块法克服了小样方统计法研究尺度单一的问题,也避免了以空间点距离为基础的点格局分析过程中边缘效应带来的影响和误差,尤其是在多变量点格局分析中具有明显的优势。

A new method of Random Square-quadrats Method（RSQM）is used to characterize the spatial patterns and spatial associations of five dominant tree species in a Korean pine broadleaved old-growth forest in Changbai Mountains in this paper.RSQM is developed based on the formula ICS（t）==s2（t）/（t）-1,and can measure the spatial distribution patterns at a range of spatial scales t.The confidence intervals of 95% and 99% are constructed using random simulation technique to test the significance of any deviations from the null hypothesis of complete spatial randomness or type independence.Results show that,Quercus mongolica,Malus baccata and Maackia amurensis are randomly distributed in the study plot,and the other tree species are significantly aggregated at local scales.Most of species pairs and species groups exhibit significantly positive spatial associations at local scales.The results demonstrate that RSQM differs from the traditional small plot method as well as from point pattern analysis method（Riply＇s K）.The traditional small plot method measures the spatial pattern using aggregated indices of dispersion,but it can only characterize the spatial pattern at a given scale.Point pattern analysis method based on distance of points is very popular but susceptible to edge effects since one can not count points outside of the study plot.RSQM can avoid these disadvantages.It can describe the distribution patterns at a set of distances and isn＇t influenced by edge effect.Especially,it is very effective in describing the spatial relathionship whitin multi-species.