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6 - Ecological monitoring and assessment of pollution in rivers

Published online by Cambridge University Press:  05 June 2012

By
J. Iwan Jones ,
John Davy-Bowker ,
John F. Murphy  and
James L. Pretty
Edited by
Lesley C. Batty  and
Kevin B. Hallberg
J. Iwan Jones
Affiliation:
Centre for Ecology and Hydrology, Wallingford, United Kingdom
John Davy-Bowker
Affiliation:
Centre for Ecology and Hydrology, Wallingford, United Kingdom
John F. Murphy
Affiliation:
Centre for Ecology and Hydrology, Wallingford, United Kingdom
James L. Pretty
Affiliation:
Centre for Ecology and Hydrology, Wallingford, United Kingdom
Lesley C. Batty
Affiliation:
University of Birmingham
Kevin B. Hallberg
Affiliation:
University of Wales, Bangor
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Summary

Introduction

Many organisms respond to pollution in a predictable way, and it has long been realised that the biota can be used to determine the extent of pollution at a site, a technique termed biomonitoring. Much of the science of biomonitoring developed in aquatic systems, driven by concerns about the impact of industrial and domestic pollution on potable water resources. Over the past century, aquatic biomonitoring has travelled a long way from the early methodologies, and much about the pitfalls and benefits of using biota to assess pollution or other stressors has been discovered. Here we describe the history of biomonitoring and how our understanding has developed, with particular focus on RIVPACS (River InVertebrate Prediction And Classification System). This system marked a major advance in biomonitoring techniques, introducing the reference condition approach, where the physical and geographical characteristics of the river were taken into account when determining what taxa would be expected to be present if the site were not polluted. Assessment of a site was then based on a comparison of the observed community and derived scores, to that expected if the site were not polluted. RIVPACS was also the first biomonitoring tool to incorporate a measure of uncertainty; any assessment is based on spatially and temporally variable samples and it is necessary to calculate the confidence associated with the quality class derived using these samples.

Type
Chapter
Information
Ecology of Industrial Pollution , pp. 126 - 146
Publisher: Cambridge University Press
Print publication year: 2010

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