生物多样性 ›› 2013, Vol. 21 ›› Issue (6): 765-768.DOI: 10.3724/SP.J.1003.2013.04133

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生态学多元数据排序分析软件Canoco 5介绍

赖江山*()   

  1. 中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
  • 收稿日期:2013-05-31 接受日期:2013-08-22 出版日期:2013-11-20 发布日期:2013-12-02
  • 通讯作者: 赖江山
  • 基金资助:
    国家自然科学基金(31200403)

Canoco 5: a new version of an ecological multivariate data ordination program

Jiangshan Lai*()   

  1. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
  • Received:2013-05-31 Accepted:2013-08-22 Online:2013-11-20 Published:2013-12-02
  • Contact: Lai Jiangshan

摘要:

基于样方单元的生物群落调查多元数据是生物多样性研究中最基本的数据类型之一。排序(ordination)作为多元统计最常用的方法之一, 目的是在可视化的低维空间展示多维数据的结构。Canoco是数据排序分析最流行的软件之一。Canoco 4.5自从2002年发布以来, 凭借简单的操作界面和功能齐全的绘图工具, 得到广泛的应用。但随着计算机技术的不断发展和新的排序方法不断出现, Canoco 4.5已经无法满足生态学研究人员对于多元数据深入分析的需求。作为Canoco 4.5的升级版本, Canoco 5于2012年10月发布。Canoco 5在Canoco 4.5基础上做了很多改进,主要体现在简化数据输入、提供更完善的帮助系统和绘图工具、简化方差分解和显著性检验的步骤, 并增加了一些新的分析方法(例如PCNM、NMDS、功能性状关联分析等)。本文概述了Canoco 5所做的这些改进, 并对有些重要操作步骤进行提示, 供同行参考。

关键词: 方差分解, 邻体矩阵主坐标分析, 非度量多维尺度分析, 谱系, 功能属性

Abstract

Ordination of multidimensional data on community composition is one of the most important multivariate statistical methods used in biodiversity research. The aim of ordination is to visualize multidimensional data structure at a low-dimensional ordination space. Canoco is one of the most popular programs for ordination analysis and Canoco 4.5 was widely used for such analysis after its release in 2002, because of its simple user interface and powerful graphic tools. A new version of Cannoco, Canoco 5 was released in October 2012. This new version simplifies data entry, provides a better help system and graphics tools, simplifies steps of variation partitioning and significance tests, adds some new methods (e.g. PCNM, NMDS, association analysis of functional traits, etc.). This paper provides an overview of the major improvements to ??Canoco 5, and addresses important steps required for particular analyses.

Key words: variation partitioning, PCNM, NMDS, functional traits, phylogenetic