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作 者:王鑫厅[1,2] 侯亚丽[1] 梁存柱[2] 王炜[2] 刘芳[1,2]
机构地区:[1]内蒙古工业大学能源与动力工程学院,呼和浩特010051 [2]内蒙古大学生命科学学院,中美生态、能源及可持续性科学内蒙古研究中心,呼和浩特010021
出 处:《生物多样性》2012年第2期151-158,共8页Biodiversity Science
基 金:国家重点基础研究发展计划(973计划)(2010CB950602);内蒙古自治区重大科技项目(20091403和20101405);内蒙古自然科学基金(2011MS0517)
摘 要:在种群空间格局研究中,定量分析格局及其形成过程已成为生态学家的主要目标。在量化分析的众多方法中,点格局分析是最常用的方法,而在选择零模型时,完全空间随机模型以外的复杂零模型很少使用,实际上,这些零模型可能有助于认识格局的内在特征。为此,我们在研究实例中,选择完全空间随机模型(complete spatial randomness)、泊松聚块模型(Poisson cluster process)和嵌套双聚块模型(nested double-cluster process)对典型草原处于不同恢复演替阶段的羊草(Leymus chinensis)种群空间格局进行了分析。结果发现:完全空间随机模型仅能检测种群在不同尺度下的格局类型;而通过泊松聚块模型和嵌套双聚块模型检验表明,在恢复演替的初期阶段,羊草种群在小尺度范围内偏离泊松聚块模型,而在整个取样范围内完全符合嵌套双聚块模型;随着恢复演替时间的推移,在恢复演替的后期,在整个取样尺度上,羊草种群与泊松聚块模型相吻合。这是很有意义的生态学现象。这一实例表明在应用点格局分析种群空间格局时,仅通过完全空间随机模型的检验来分析格局特征,或许很难论证复杂的生态过程,而选择一些完全空间随机模型以外的较复杂的零模型,可能发现一些有价值的生态学现象,对揭示格局掩盖下的内在机制有所裨益。Understanding spatial distribution patterns has been a central focus of plant ecology since its inception.Spatial patterns of individuals within populations are closely linked to processes;determining these underlying processes remains a major objective of ecological research.Spatial patterns are often determined using a point pattern,a data set consisting of a series of mapped point locations within a study area.The simplest and most widely used null model for analyzing point patterns is the complete spatial randomness(CSR) model.In fact,other null models are rarely used.This paper aims to provide guidance to ecologists when quantifying the underlying processes responsible for spatial patterns of ecological phenomena using point patterns and null models.Photography orientation was used to estimate the point pattern of Leymus chinensis in different restored successional stages in a typical steppe,and complete spatial randomness,Poisson and double-cluster processes were used to analyze spatial patterns of L.chinensis based on this data set.In the early stages of succession,the distribution of L.chinensis fit well with the nested double-cluster process for all scales in the community block of 10 m×10 m.Over time,the distribution fits better with the Thomas process at all scales.This ecological succession phenomenon may be induced by intra-specific competition,but cannot be explained by density interactions.Population territory density could possibly explain the phe-nomenon.Our study is an important example of successful analysis of population spatial patterns using point patterns and complex null models.
关 键 词:完全空间随机模型 泊松聚块模型 嵌套双聚块模型 LEYMUS CHINENSIS 恢复演替 摄影定位法 种群领地密度
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