arrow
返回

Functional rarefaction: estimating functional diversity from field data

delete2007-11-22
delete36
PRE
AI
S
Steven C. Walker *
M
Mark S. Poos
D
Donald A. Jackson
DOI:10.1111/j.2007.0030-1299.16171.xdelete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Studies in biodiversity-ecosystem function and conservation biology have led to the development of diversity indices that take species' functional differences into account. We identify two broad classes of indices: those that monotonically increase with species richness (MSR indices) and those that weight the contribution of each species by abundance or occurrence (weighted indices). We argue that weighted indices are easier to estimate without bias but tend to ignore information provided by rare species. Conversely, MSR indices fully incorporate information provided by rare species but are nearly always underestimated when communities are not exhaustively surveyed. This is because of the well-studied fact that additional sampling of a community may reveal previously undiscovered species. We use the rarefaction technique from species richness studies to address sample-size-induced bias when estimating functional diversity indices. Rarefaction transforms any given MSR index into a family of unbiased weighted indices, each with a different level of sensitivity to rare species. Thus rarefaction simultaneously solves the problem of bias and the problem of sensitivity to rare species. We present formulae and algorithms for conducting a functional rarefaction analysis of the two most widely cited MSR indices: functional attribute diversity (FAD) and Petchey and Gaston's functional diversity (FD). These formulae also demonstrate a relationship between three seemingly unrelated functional diversity indices: FAD, FD and Rao's quadratic entropy. Statistical theory is also provided in order to prove that all desirable statistical properties of species richness rarefaction are preserved for functional rarefaction.
Keyword:
ECOSYSTEM FUNCTION
SPECIES-DIVERSITY
BIRD COMMUNITY
BIODIVERSITY
RICHNESS

期刊

Oikos 封面图
Oikos
IF:
3
论文数:
6.4K
被引数:
2.2W

机构

U
university of toronto
学者数:
14.8W
论文数: 12.0W
被引数: 165
引用论文

引用论文

err分享
err收藏
A Methodology for Neural Spatial Interaction Modeling
err2010-11-16
err0
errOAAI
errManfred M. Fischer; Martin Reismann
err分享
err收藏
A practical alternative to the hunsdiecker reaction
err1983-01-01
err0
PREAI
errDerek H.R. Barton; David Crich; William B. Motherwell
err分享
err收藏
On dendrogram-based measures of functional diversity
err2006-07-12
err222
errOAAI
errPodani, Janos; Schmera, Denes
err分享
err收藏
Potential of electrodialytic techniques in brackish desalination and recovery of industrial process water for reuse
err2017-05-01
err0
errOAAI
errAlexander M. Lopez; Meaghan Williams; Maira Paiva; Dmytro Demydov; Thien Duc Do; Julian L. Fairey; YuPo J. Lin; Jamie A. Hestekin
err分享
err收藏
Functional diversity: back to basics and looking forward
err2006-04-25
err2.0K
PREAI
errPetchey, Owen L.; Gaston, Kevin J.
err分享
err收藏
学者 查看更多内容