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Assessing group differences in biodiversity by simultaneously testing a user‐defined selection of diversity indices
Author(s) -
Pallmann Philip,
Schaarschmidt Frank,
Hothorn Ludwig A.,
Fischer Christiane,
Nacke Heiko,
Priesnitz Kai U.,
Schork Nicholas J.
Publication year - 2012
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12004
Subject(s) - biology , false positive paradox , resampling , selection (genetic algorithm) , diversity (politics) , statistics , group (periodic table) , biodiversity , diversity index , computer science , data mining , mathematics , machine learning , ecology , species richness , chemistry , organic chemistry , sociology , anthropology
Comparing diversities between groups is a task biologists are frequently faced with, for example in ecological field trials or when dealing with metagenomics data. However, researchers often waver about which measure of diversity to choose as there is a multitude of approaches available. As J ost (2008, M olecular E cology , 17 , 4015) has pointed out, widely used measures such as the S hannon or S impson index have undesirable properties which make them hard to compare and interpret. Many of the problems associated with the use of these ‘raw’ indices can be corrected by transforming them into ‘true’ diversity measures. We introduce a technique that allows the comparison of two or more groups of observations and simultaneously tests a user‐defined selection of a number of ‘true’ diversity measures. This procedure yields multiplicity‐adjusted P ‐values according to the method of W estfall and Y oung (1993, Resampling‐Based Multiple Testing: Examples and Methods for p‐Value Adjustment , 49, 941), which ensures that the rate of false positives (type I error) does not rise when the number of groups and/or diversity indices is extended. Software is available in the R package ‘simboot’.