Fish mercury levels in lakes - adjusting for Hg and fish-size covariation

Abstract

Accurate estimates of lake-specific mercury levels are vital in assessing the environmental impact on the mercury content in fish. The intercepts of lake-specific regressions of Hg concentration in fish vs. fish length provide accurate estimates when there is a prominent Hg and fish-size covariation. Commonly used regression methods, such as analysis of covariance (ANCOVA) and various standardization techniques are less suitable, since they do not completely remove the fish-size covariation when regression slopes are not parallel. Partial least squares (PLS) regression analysis reveals that catchment area and water chemistry have the stronaest influence on the Hg level in fish in circumneutral lakes. PLS is a multivariate projection method that allows biased linear regression analysis of multicollinear data. The method is applicable to statistical and visual exploration of large data sets, even if there are more variables than observations. Environmental descriptors have no significant impact on the slopes of linear regressions of the Ha concentration in perch (Perca fluviatilis L.) vs. fish length, suggesting that the slopes mainly reflect ontogenetic dietary shifts during the perch life span. (C) 2003 Elsevier Science Ltd. All rights reserved

Published in

Environmental Pollution
2003, Volume: 125, number: 2, pages: 255-265 Publisher: ELSEVIER SCI LTD

SLU Authors

• Sonesten, Lars

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Environmental Sciences related to Agriculture and Land-use


Publication identifier

DOI: https://doi.org/10.1016/S0269-7491(03)00051-4

Permanent link to this page (URI)

https://res.slu.se/id/publ/688