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A Statistical Model and National Data Set for Partitioning Fish-Tissue Mercury Concentration Variation Between Spatiotemporal and Sample Characteristic Effects

By Stephen P. Wente

U.S. GEOLOGICAL SURVEY
Scientific Investigations Report 2004-5199

Prepared by the U.S. Geological Survey, Minnesota District, Toxic Substances Hydrology Program, and Geographic Analysis and Monitoring Program in cooperation with the National Institute of Environmental Health Sciences.

This report is also available as a pdf.


Abstract

Many Federal, Tribal, State, and local agencies monitor mercury in fish-tissue samples to identify sites with elevated fish-tissue mercury (fish-mercury) concentrations, track changes in fish-mercury concentrations over time, and produce fish-consumption advisories. Interpretation of such monitoring data commonly is impeded by difficulties in separating the effects of sample characteristics (species, tissues sampled, and sizes of fish) from the effects of spatial and temporal trends on fish-mercury concentrations. Without such a separation, variation in fish-mercury concentrations due to differences in the characteristics of samples collected over time or across space can be misattributed to temporal or spatial trends; and/or actual trends in fish-mercury concentration can be misattributed to differences in sample characteristics. This report describes a statistical model and national data set (31,813 samples) for calibrating the aforementioned statistical model that can separate spatiotemporal and sample characteristic effects in fish-mercury concentration data. This model could be useful for evaluating spatial and temporal trends in fishmercury concentrations and developing fish-consumption advisories. The observed fish-mercury concentration data and model predictions can be accessed, displayed geospatially, and downloaded via the World Wide Web (http://emmma.usgs.gov). This report and the associated web site may assist in the interpretation of large amounts of data from widespread fishmercury monitoring efforts.

Contents

Abstract

Introduction

Purpose and scope

Acknowledgements

Methods

Model description

Model assumptions

National fish-mercury data set

Model performance assessment

Model evaluation and applications

Model fit

Fish-mercury concentration prediction

Prediction accuracy

Model applications

Future studies

Summary

References cited

Appendix

Suggested Citation:

Wente, S.P., 2004, A statistical model and national data set for partitioning fish-tissue mercury concentration variation between spatiotemporal and sample characteristic effects: U.S. Geological Survey Scientific Investigation Report 2004-5199, 15 p.


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