To examine the relationships among liver element concentrations, principal component analysis (PCA) was performed on data from a case series of 54 common loons collected in Michigan during the period from July 1988 to February 1993. Data available for each bird included season and district of collection, age, sex, necropsy findings, and liver concentrations of twelve elements as determined by spectrophotometry. The first three principal components (PC) accounted for 86% of the total variability of the data, which made possible a substantial reduction in dimensionality. Within PC1-PC3, calcium, iron, mercury and lead were the most influential elements in accounting for variation. The possibility of a competitive interaction between mercury and lead for selenium is suggested, with consideration given to possible alterations in bioavailability due to environmental acidification. PCA can generate hypotheses that subsequently can be investigated under conditions which allow causal inference and better control of confounding factors. Consequently, sparse field data can be used efficiently to generate information on risk factors for environmental diseases, and to provide bases for intervention strategies.
- Exploratory data analysis
- Principal component analysis (PCA)
ASJC Scopus subject areas
- Animal Science and Zoology
- Food Animals