文献类型：期刊文献

中文题名：一种新的基于混交度的林木种群分布格局测度方法

英文题名：A new method for measuring population distribution patterns of forest trees based on the mingling degree

作者：胡艳波[1] 惠刚盈[1]

第一作者：胡艳波

机构：[1]中国林业科学研究院林业研究所,国家林业局林木重点培育实验室

年份：2015

卷号：37

期号：1

起止页码：9-14

中文期刊名：北京林业大学学报

外文期刊名：Journal of Beijing Forestry University

收录：CSTPCD;;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：国家自然科学基金项目(31370638)

语种：中文

中文关键词：混交度;格局测度方法;林分空间结构;种群分布格局

外文关键词：mingling; distribution test method; stand spatial structure; population distribution pattern

分类号：S758.53

摘要：种群的空间格局分析是研究种群特征、种群间相互作用以及种群与环境关系的重要手段,一直是生态学中的研究热点之一。混交度用来说明混交林中树种空间隔离程度,表明了混交林中任意一株树的最近相邻木为其他种的概率。迄今为止,国内外文献中还未见到有关直接利用在表达树种隔离程度方面科学明了、在数据获取方面简单有效的混交度来成功分析种群分布格局的报道。本文通过研究树种混交度期望值与观测值的关系,提出了一种新的基于混交度的种群分布格局测度方法 DM,并给出了统计显著性检验方法。将这一方法应用于中国西北甘肃小陇山天然混交林中树种分布格局检验,与经典的聚集指数R相比,格局判断准确率达100%,明显克服了聚集指数的理论缺陷。这一方法的提出进一步完善了基于相邻木关系的林分空间结构研究。
Analysis of spatial patterns of populations is an important approach to study the characteristics of populations, interaction among populations and relations between a population and its environment and has been a research focus in ecology for some time. The mingling degree is an index to describe spatial segregation among tree species, i. e. , the probability that the nearest adjacent tree, a random occurrence in a mixed forest, belongs to another species. As yet, we are not aware of publications of any analysis of population distribution patterns by a direct use of this mingling degree, recognized not only as a clear and scientific index for describing tree species segregation, but is also a simple and effective way for data collection and measurements. We propose a new method, DM, of testing population distributions by analyzing the relationship between expected and observed values of this mingling degree. A statistical significance test method was introduced. The method was applied to measure the distribution pattern of tree species in a natural mixed forest in Xiaolong Mountain, Gansu Province, northwestern China. Compared with the classic aggregation index R, the test accuracy of DM is 100% , suggesting that the theoretical defect of the aggregation index R has been avoided. Application of this method will enhance research on the spatial structure of stands, based on the relationships between adjacent trees.