Application of canonical variate analysis in the evaluation and presentation of multivariate biological response data

Autor: S. Marshall Adams, Kenneth D. Ham, John J. Beauchamp
Rok vydání: 1994
Předmět:
Zdroj: Environmental Toxicology and Chemistry. 13:1673-1683
ISSN: 1552-8618
0730-7268
DOI: 10.1002/etc.5620131018
Popis: The authors have applied canonical variate analysis procedures for evaluating multivariate responses of fish populations to various contaminant stressors. Using examples of fish populations experiencing high levels of PCBs in a reservoir and mixed contaminants in a stream, the significance of integrated stress responses among sample populations was compared statistically and graphically using two- and three-dimensional data presentations. For fish from both systems, the most powerful axis of discrimination 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 with the second axis of discrimination among sites in the PCB-contaminated reservoir study. Indicators of lipid metabolism were the variables most correlated with the second and third axes of discrimination among stream fish. Canonical variate analysis procedures are useful for evaluating multivariate response data because they take into account the interrelations and associated among response variables and reveal the integrated nature of organism responses to stress. Using this procedure, the significance of integrated stress responses among different sample populations ca be graphically compared and evaluated using two- or three-dimensional data presentations. These types of graphical displays help provide an understanding of the relationships among sample populations thatmore » may not be evident from tabular or other types of data summaries. In addition, this approach can be useful in helping to identify factors such as toxicants or other environmental stressors which impair the health of aquatic ecosystems.« less
Databáze: OpenAIRE
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