Design and analysis of experiments testing for biodiversity effects in ecology

R. A. Bailey; Julia Reiss

doi:10.1016/j.jspi.2012.09.008

Design and analysis of experiments testing for biodiversity effects in ecology

R. A. Bailey^*, Julia Reiss

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

It is now widely believed that biological diversity is good for the natural environment. One way that ecologists test this is to place random collections of species in mini-environments and then measure some outcome. Statisticians have been working with fresh-water ecologists to improve this in two ways. The first is that the subsets of species are carefully chosen, not random. The second is that a nested family of plausible models is fitted. The results of three experiments suggest that biodiversity can have no effect at all, but that there are other plausible underlying mechanisms.

Implications for the design of such experiments, the understanding of the family of models, and the analysis of the data are discussed.

Original language	English
Pages (from-to)	69-80
Number of pages	12
Journal	Journal of Statistical Planning and Inference
Volume	144
Early online date	21 Nov 2013
DOIs	https://doi.org/10.1016/j.jspi.2012.09.008
Publication status	Published - Jan 2014
Event	3rd International Conference on Design of Experiments, Memphis, Tennessee, - Duration: 10 May 2011 → 13 May 2011

Keywords

Biodiversity
Design of experiments
Family of models
Hasse diagram

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title = "Design and analysis of experiments testing for biodiversity effects in ecology",

abstract = "It is now widely believed that biological diversity is good for the natural environment. One way that ecologists test this is to place random collections of species in mini-environments and then measure some outcome. Statisticians have been working with fresh-water ecologists to improve this in two ways. The first is that the subsets of species are carefully chosen, not random. The second is that a nested family of plausible models is fitted. The results of three experiments suggest that biodiversity can have no effect at all, but that there are other plausible underlying mechanisms.Implications for the design of such experiments, the understanding of the family of models, and the analysis of the data are discussed. ",

keywords = "Biodiversity, Design of experiments, Family of models, Hasse diagram",

author = "Bailey, \{R. A.\} and Julia Reiss",

note = "The experiments reported here were supported by a grant (reference NE/D013305/1) from the Natural Environment Research Council, UK. This paper was written while the first author was at the Isaac Newton Institute, Cambridge, UK, during the 2011 programme Design and Analysis of Experiments, supported by the Engineering and Physical Sciences Research Council, UK.; 3rd International Conference on Design of Experiments, <br/>Memphis, Tennessee, , ICODOE ; Conference date: 10-05-2011 Through 13-05-2011",

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doi = "10.1016/j.jspi.2012.09.008",

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AU - Bailey, R. A.

AU - Reiss, Julia

N1 - The experiments reported here were supported by a grant (reference NE/D013305/1) from the Natural Environment Research Council, UK. This paper was written while the first author was at the Isaac Newton Institute, Cambridge, UK, during the 2011 programme Design and Analysis of Experiments, supported by the Engineering and Physical Sciences Research Council, UK.

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N2 - It is now widely believed that biological diversity is good for the natural environment. One way that ecologists test this is to place random collections of species in mini-environments and then measure some outcome. Statisticians have been working with fresh-water ecologists to improve this in two ways. The first is that the subsets of species are carefully chosen, not random. The second is that a nested family of plausible models is fitted. The results of three experiments suggest that biodiversity can have no effect at all, but that there are other plausible underlying mechanisms.Implications for the design of such experiments, the understanding of the family of models, and the analysis of the data are discussed.

AB - It is now widely believed that biological diversity is good for the natural environment. One way that ecologists test this is to place random collections of species in mini-environments and then measure some outcome. Statisticians have been working with fresh-water ecologists to improve this in two ways. The first is that the subsets of species are carefully chosen, not random. The second is that a nested family of plausible models is fitted. The results of three experiments suggest that biodiversity can have no effect at all, but that there are other plausible underlying mechanisms.Implications for the design of such experiments, the understanding of the family of models, and the analysis of the data are discussed.

KW - Biodiversity

KW - Design of experiments

KW - Family of models

KW - Hasse diagram

UR - https://www.scopus.com/pages/publications/84888032106

U2 - 10.1016/j.jspi.2012.09.008

DO - 10.1016/j.jspi.2012.09.008

M3 - Article

SN - 0378-3758

VL - 144

SP - 69

EP - 80

JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

T2 - 3rd International Conference on Design of Experiments, <br/>Memphis, Tennessee,

Y2 - 10 May 2011 through 13 May 2011

ER -

Design and analysis of experiments testing for biodiversity effects in ecology

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Keywords

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