APPLICATION OF CANONICAL VARIATE ANALYSIS IN THE EVALUATION AND PRESENTATION OF MULTIVARIATE BIOLOGICAL RESPONSE DATA

Citation
Sm. Adams et al., APPLICATION OF CANONICAL VARIATE ANALYSIS IN THE EVALUATION AND PRESENTATION OF MULTIVARIATE BIOLOGICAL RESPONSE DATA, Environmental toxicology and chemistry, 13(10), 1994, pp. 1673-1683
Citations number
24
Categorie Soggetti
Toxicology,"Environmental Sciences",Chemistry
ISSN journal
07307268
Volume
13
Issue
10
Year of publication
1994
Pages
1673 - 1683
Database
ISI
SICI code
0730-7268(1994)13:10<1673:AOCVAI>2.0.ZU;2-K
Abstract
We have applied canonical variate analysis procedures for evaluating m ultivariate responses of fish populations to various contaminant stres sors. Using examples of fish populations experiencing high levels of P CBs in a reservoir and mixed contaminants in a stream, the significanc e of integrated stress responses among sample populations was compared statistically and graphically using two- and three-dimensional data p resentations. For fish from both systems, the most powerful axis of di scrimination among sample populations was correlated with the activity of the detoxification enzyme, EROD (7-ethoxyresorufin O-deethylase). Indicators of organ dysfunction were the variables most correlated wit h the second axis of discrimination among sites in the PCB-contaminate d reservoir study. Indicators of lipid metabolism were the variables m ost correlated with the second and third axes of discrimination among stream fish. Canonical variate analysis procedures are useful for eval uating multi-variate response data because they take into account the interrelations and associations among response variables and reveal th e integrated nature of organism responses to stress. Using this proced ure, the significance of integrated stress responses among different s ample populations can be graphically compared and evaluated using two- or three-dimensional data presentations. These types of graphical dis plays help provide an understanding of the relationships among sample populations that may not be evident from tabular or other types of dat a summaries. In addition, this approach can be useful in helping to id entify factors such as toxicants or other environmental stressors whic h impair the health of aquatic ecosystems.