Canonical Correspondence Analysis: A New Eigenvector Technique for Multivariate Direct Gradient Analysis

排序 去趋势对应分析 梯度分析 典型对应分析 对应分析 典型相关 主成分分析 环境梯度 多元统计 环境数据 环境分析 多元分析 数学 变量(数学) 典型分析 统计 生态学 丰度(生态学) 栖息地 生物 化学 数学分析 色谱法
作者
Cajo J. F. ter Braak
出处
期刊:Ecology [Wiley]
卷期号:67 (5): 1167-1179 被引量:5919
标识
DOI:10.2307/1938672
摘要

EcologyVolume 67, Issue 5 p. 1167-1179 Article Canonical Correspondence Analysis: A New Eigenvector Technique for Multivariate Direct Gradient Analysis Cajo J. F. ter Braak, Cajo J. F. ter BraakSearch for more papers by this author Cajo J. F. ter Braak, Cajo J. F. ter BraakSearch for more papers by this author First published: 01 October 1986 https://doi.org/10.2307/1938672Citations: 3,883AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract A new multivariate analysis technique, developed to relate community composition to known variation in the environment, is described. The technique is an extension of correspondence analysis (reciprocal averaging), a popular ordination technique that extracts continuous axes of variation from species occurrence or abundance data. Such ordination axes are typically interpreted with the help of external knowledge and data on environmental variables; this two—step approach (ordination followed by environmental gradient identification) is termed indirect gradient analysis. In the new technique, called canonical correspondence analysis, ordination axes are chosen in the light of known environmental variables by imposing the extra restriction that the axes be linear combinations of environmental variables. In this way community variation can be directly related to environmental variation. The environmental variables may be quantitative or nominal. As many axes can be extracted as there are environmental variables. The method of detrending can be incorporated in the technique to remove arch effects. (Detrended) canonical correspondence analysis is an efficient ordination technique when species have bell—shaped response curves or surfaces with respect to environmental gradients, and is therefore more appropriate for analyzing data on community composition and environmental variables than canonical correlation analysis. The new technique leads to an ordination diagram in which points represent species and sites, and vectors represent environmental variables. Such a diagram shows the patterns of variation in community composition that can be explained best by the environmental variables and also visualizes approximately the "centers" of the species distributions along each of the environmental variables. Such diagrams effectively summarized relationships between community and environment for data sets on hunting spiders, dyke vegetation, and algae along a pollution gradient. Citing Literature Volume67, Issue5October 1986Pages 1167-1179 This article also appears in:Centennial Special: Notable Papers in ESA History RelatedInformation
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
蓝梦诗音完成签到 ,获得积分10
1秒前
Moonchild完成签到 ,获得积分10
1秒前
Lianna完成签到 ,获得积分10
4秒前
tough_cookie完成签到 ,获得积分10
5秒前
青水完成签到 ,获得积分10
6秒前
西山菩提完成签到,获得积分10
8秒前
工藤完成签到,获得积分10
10秒前
nhanvm完成签到,获得积分10
12秒前
dra7vu完成签到,获得积分10
16秒前
vothuong完成签到,获得积分10
17秒前
lamer完成签到,获得积分10
19秒前
爱我不上火完成签到 ,获得积分10
20秒前
穿肠酒完成签到,获得积分20
21秒前
GTR的我完成签到 ,获得积分10
22秒前
24秒前
行云流水完成签到,获得积分10
27秒前
科研通AI6.1应助朱大帅采纳,获得10
28秒前
纸条条完成签到 ,获得积分10
29秒前
风趣朝雪完成签到,获得积分10
30秒前
30秒前
科科完成签到,获得积分10
36秒前
渔渔完成签到 ,获得积分10
37秒前
kk完成签到,获得积分10
38秒前
42秒前
aikeyan完成签到,获得积分10
46秒前
lucky完成签到 ,获得积分10
47秒前
狼道发布了新的文献求助10
48秒前
48秒前
吉吉完成签到,获得积分10
50秒前
acat完成签到 ,获得积分10
53秒前
zwx完成签到 ,获得积分10
54秒前
Dogged完成签到 ,获得积分10
54秒前
凡凡完成签到,获得积分10
55秒前
56秒前
Kkkk完成签到 ,获得积分10
56秒前
kaifangfeiyao完成签到 ,获得积分10
59秒前
xiaobin完成签到 ,获得积分10
1分钟前
乐空思应助Maestro_S采纳,获得30
1分钟前
橙子发布了新的文献求助30
1分钟前
Ding-Ding完成签到,获得积分10
1分钟前
高分求助中
Clinical Epidemiology: The Essentials, 6e 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Graphene Handbook (2019 Edition) 800
Adhesion Science: Principles & Practice 800
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
久松真一著作集〈第5巻〉禅と芸術 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6554050
求助须知:如何正确求助?哪些是违规求助? 8338925
关于积分的说明 17864778
捐赠科研通 5670458
什么是DOI,文献DOI怎么找? 2939840
邀请新用户注册赠送积分活动 1915746
关于科研通互助平台的介绍 1785018