Trend analysis of mercury in fish using nonparametric regression
2005 (English)Report (Other (popular science, discussion, etc.))
The International Council for the Exploration of the Sea (ICES) has longcompiled extensive data on contaminants in biota. We investigated how trendassessment of mercury in muscle tissue from fish (flounder and Atlantic cod)might be facilitated by using nonparametric regression to normalise observedlevels of this contaminant with respect to body length and weight. Specifically,we examined response surfaces and annual normalised means obtained byemploying purely additive models (AM), thin plate splines (TPS), andmonotonic regression (MR) to model mercury levels as functions of samplingyear and one or two covariates. Our analysis showed that TPS and MR modelscan be more satisfactory than purely additive models, because the formertechniques enable estimation of time-dependent relationships between themercury concentration and the covariates. However, the major obstacle fortrend assessment of the collected mercury data was a substantial interannualvariation that was related to factors other than body length and weight.Nevertheless, several time series of flounder data that started in the 1970s and1980s showed obvious downward trends, and these trends were particularly2strong in the Elbe estuary. When the analysis was limited to data collected after1990, an overall Mann-Kendall test for all sampling sites revealed astatistically significant downward trend for flounder, whereas it was notsignificant for cod.
Place, publisher, year, edition, pages
2005. no 7
, LIU-MAI-R, Department of Mathematics, Division of Statistics , 2005-07
additive models, thin plate splines, monotonic regression, trend assessment, normalisation, mercury, fish
IdentifiersURN: urn:nbn:se:liu:diva-13602OAI: oai:DiVA.org:liu-13602DiVA: diva2:21034