摘要
利用分形理论中的计盒维数、信息维数探讨了浙江省舟山市桃花岛砂砧薹草Carex kobomugi与假牛鞭草Parapholis incurva种群的分形特征。结果表明:砂砧薹草和假牛鞭草种群分布格局存在分形特征;假牛鞭草种群分布格局计盒维数为1.454 2~1.745 6;砂砧薹草样地种群空间格局的计盒维数为1.318 1~1.614 1;两者均值均大于1.500 0,具有较强的占据空间的能力,而且前者比后者具有更强的占据空间的能力。砂砧薹草样地种群空间格局的信息维数为1.027 0~1.263 4,假牛鞭草种群分布格局信息维数为1.022 7~1.381 2,假牛鞭草种群信息维数均值大于砂砧薹草,表明假牛鞭草种群空间格局更复杂,群聚指数更高。研究结果对进一步探讨分形理论在草本植物种群空间结构中应用具有重要意义。
It is very important to study the application of fractal theory to further explore the spatial structure of herb populations,which applied the significance of fractal theory in the spatial structure of herbaceous plant populations.Fractal characteristics of two herb populations,Carex kobomugi and Parapholis incurve,on Taohua Island of Zhoushan City were studied using the contiguous grid quadrate sampling method from pattern research and the box-counting and information dimensions from fractal theory.Adjacent grid method to take four random quadrats for quadrat area 1 m×1 m in transects C.kobomugi and P.incurva populations.Results showed that fractal dimensions could describe the distribution pattern of the populations with the box-counting dimension ranging between 1.454 2 and 1.745 6 for P.incurva and between 1.318 1 and 1.614 1 for C.kobomugi. Both populations had means greater than 1.500 0,and both had strong ability to occupy the space with P.incurva being stronger than C.kobomugi.The information dimension for populations of C.kobomugi ranged from 1.027 0 to 1.263 4 and of P.incurva from 1.022 7 to 1.381 2 with the mean of P.incurva populations greater than C.kobomugi.Also,the cluster index was higher.Thus,P.incurva population space had a more complex pattern but the difference was not significant.It is great significant to study the application of fractal theory for further exploring the spatial structure of the herb populations.
出处
《浙江农林大学学报》
CAS
CSCD
北大核心
2013年第2期220-225,共6页
Journal of Zhejiang A&F University
基金
国家星火计划项目(2011GA700182)
关键词
植物生态学
砂砧薹草
假牛鞭草
计盒维数
信息维数
分布格局
plant ecology
Carex kobomugi
Parapholis incurva
box-counting dimension
information dimension
distribution pattern