Assessing covariate-dependent contaminant time-series in the marine environment

Abstract

This paper describes a method for assessing contaminant time-series when contaminant levels vary with some covariate and the contaminant-covariate relationship changes over time. At each time point, the contaminant data are split into two groups according to whether the corresponding values of the covariate are smaller or larger than some specified value, leading to two contaminant time-series, for small and large values of the covariate respectively. Smoothers are then used to model the small and large time-series, and to construct analyses of variance that test for any change over time, any covariate effect, and whether the pattern of temporal change in the small time-series is the same as in the large time-series. The smoothers can also be displayed graphically, allowing easy interpretation of the results. The method is applied to four time-series of mercury concentrations in fish muscle from monitoring sites around the UK.