Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-18T06:00:03.531Z Has data issue: false hasContentIssue false

6 - Ecological monitoring and assessment of pollution in rivers

Published online by Cambridge University Press:  05 June 2012

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
Get access

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
Publisher: Cambridge University Press
Print publication year: 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Armitage, P. D., Moss, D., Wright, J. F. and Furse, M. T. (1983) The performance of a new biological water quality score system based on macroinvertebrates over a wide range of unpolluted running water sites. Water Research 17, 333–347.CrossRefGoogle Scholar
Barbour, M. T., Gerritsen, J., Snyder, B. D. and Stribling, J. B. (1999) Revision to Rapid Bioassessment Protocols for Use in Streams and Rivers: Periphyton, Benthic Macroinvertebrates and Fish. 2nd edn. EPA 841-B-99–002, US Environmental Protection Agency, Office of Water, Washington, DC.Google Scholar
,Biological Monitoring Working Party (1978) Final Report: Assessment: A Presentation of the Quality of Rivers in Great Britain. Unpublished report, Department of the Environment, Water Data Unit.
Carlisle, D. M., Hawkins, C. P., Meador, M. R., Potapova, M. and Falcone, J. (2008) Biological assessments of Appalachian streams based on predictive models for fish, macroinvertebrate, and diatom assemblages. Journal of the North American Benthological Society 27, 16–37.CrossRefGoogle Scholar
Céréghino, R., Park, Y.-S., Compin, A. and Lek, S. (2003) Predicting the species richness of aquatic insects in streams using a limited number of environmental variables. Journal of the North American Benthological Society 22, 442–456.CrossRefGoogle Scholar
Chandler, J. R. (1970) A biological approach to water quality management. Water Pollution Control 69, 415–422.Google Scholar
Chutter, F. M. (1972) An empirical biotic index of the quality of water in South African streams and rivers. Water Research 6, 19–30.CrossRefGoogle Scholar
Clarke, R. T. (1997) Uncertainty in estimates of biological quality based on RIVPACS. In: Assessing the Biological Quality of Fresh Waters (eds. Wright, J. F., Sutcliffe, D. W. and Furse, M. T.), pp. 39–54. Freshwater Biological Association, Ambleside, UK.Google Scholar
Clarke, R. T. (2004) STAR Deliverable. Error/Uncertainty Module Software STARBUGS (STAR Bioassessment Uncertainty Guidance Software. User Manual. http://www.eu-star.at.
Clarke, R. T. and Davy-Bowker, J. (2006) Development of the Scientific Rationale and Formulae for Altering RIVPACS Predicted Indices for WFD Reference Condition. Scotland & Northern Ireland Forum for Environmental Research. Project WFD72B report.Google Scholar
Clarke, R. T., Furse, M. T., Gunn, R. J. M., Winder, J. M. and Wright, J. F. (2002) Sampling variation in macroinvertebrate data and implications for river quality indices. Freshwater Biology 47, 1735–1751.CrossRefGoogle Scholar
Clarke, R. T., Wright, J. F. and Furse, M. T. (2003) RIVPACS models for predicting the expected macroinvertebrate fauna and assessing the ecological quality of rivers. Ecological Modelling 160, 219–233.CrossRefGoogle Scholar
Cohn, F. (1853) Über lebende Organismen im Trinkwasser. Günzberg Z Klin Med, 4, 229–237.Google Scholar
Davies, P. E. (1994) River Bioassessment Manual: Monitoring River Health Initiative. Department of the Environment, Sport, Territories, Land and Water Resources R and D Corporation, Commonwealth Environment Protection Agency, Canberra, Australia.Google Scholar
Davy-Bowker, J., Clarke, R. T., Corbin, T.et al. (2007c) River Invertebrate Classification Tool. Scotland & Northern Ireland Forum for Environmental Research. Project WFD72C report.
Davy-Bowker, J., Clarke, R. T., Furse, M. T.et al. (2007a) RIVPACS Pressure Data Analysis. Scotland & Northern Ireland Forum for Environmental Research).Google Scholar
Davy-Bowker, J., Clarke, R. T., Furse, M. T.et al. (2007b) RIVPACS Database Documentation. Scotland & Northern Ireland Forum for Environmental Research. Project WFD46 report.Google Scholar
Davy-Bowker, J., Clarke, R. T., Johnson, R. K., Kokes, J., Murphy, J. F. and Zahradkova, S. (2006) A comparison of the European Water Framework Directive physical typology and RIVPACS-type models as alternative methods of establishing reference conditions for benthic macroinvertebrates. Hydrobiologia 566, 91–105.CrossRefGoogle Scholar
Davy-Bowker, J., Murphy, J. F., Rutt, G. R., Steel, J. E. C. and Furse, M. T. (2005) The development and testing of a macroinvertebrate biotic index for detecting the impact of acidity on streams. Archiv für Hydrobiologie 163, 383–403.CrossRefGoogle Scholar
,DIN 38410(Deutsche Einheitsverfahren zur Wasser- und Abwasser- und Schlamm-untersuchung) T.2, 1990. Bestimmung des Saprobien index, Berlin.
Dines, R. A. and Murray-Bligh, J. A. D. (1997) Quality assurance and RIVPACS. In: Assessing the Biological Quality of Fresh Waters (eds. Wright, J. F., Sutcliffe, D. W. and Furse, M. T.), pp. 70–78. Freshwater Biological Association, Ambleside, UK.Google Scholar
Fausch, K. D., Lyons, J., Karr, J. R. and Angermeier, P. L. (1990) Fish communities as indicators of environmental degradation. American Fisheries Society Symposium 8, 123–144.Google Scholar
Flanagan, P. J. and Toner, P. F. (1972) The National Survey of Irish Rivers. A Report on Water Quality. An Foras forbartha, WR/R1, Dublin.Google Scholar
Furse, M. T., Herring, D., Brabec, K., Buffagni, A., Sandin, L. and Verdonschot, P. F. M. (2006) The Ecological Status of European Rivers: Evaluation and Intercalibration of Assessment Methods. Developments in Hydrobiology 188. Springer, Dordrecht, the Netherlands.CrossRefGoogle Scholar
Furse, M. T., Moss, D., Wright, J. F. and Armitage, P. D. (1984) The influence of seasonal and taxonomic factors on the ordination and classification of running-water sites in Great Britain and on the prediction of their macroinvertebrate communities. Freshwater Biology 14, 257–280.CrossRefGoogle Scholar
Furse, M. T., Wright, J. F., Armitage, P. D. and Moss, D. (1981) An appraisal of pond-net samples for biological monitoring of lotic macro-invertebrates. Water Research 15, 679–689.CrossRefGoogle Scholar
Gevrey, M., Rimet, F., Park, Y.-S., Giraudel, J.-L., Ector, L. and Lek, S. (2004) Water quality assessment using diatom assemblages and advanced modelling techniques. Freshwater Biology 49, 208–220.CrossRefGoogle Scholar
Giraudel, J. L. and Lek, S. (2001) A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination. Ecological Modelling 146, 329–339.CrossRefGoogle Scholar
Haase, P., Murray-Bligh, J., Lohse, S.et al. (2006) Assessing the impact of errors in sorting and identifying macroinvertebrate samples. Hydrobiologia 566, 505–521.CrossRefGoogle Scholar
Hawkins, C. P., Norris, R. H., Hogue, J. N. and Feminella, J. W. (2000) Development and evaluation of predictive models for measuring the biological integrity of streams. Ecological Applications 10, 1456–1477.CrossRefGoogle Scholar
Hawkins, C. P., Paulsen, S. G., Sickle, J. and Yuan, L. L. (2008) Regional assessments of stream ecological condition: scientific challenges associated with the USA's national Wadeable Stream Assessment. Journal of the North American Benthological Society 27, 805–807.CrossRefGoogle Scholar
Hilsenhoff, W. L. (1988) Rapid field assessment of organic pollution with a family-level biotic index. Journal of the North American Benthological Society 7, 65–68.CrossRefGoogle Scholar
Holmes, N. T. H., Newman, J. R., Chadd, J. R., Rouen, K. J., Saint, L. and Dawson, F. H. (1999) Mean Trophic Rank: A User's Manual. Research and Development, Technical Report E38. Environment Agency, Bristol, UK.Google Scholar
Johnson, R. K. (2003) Development of a prediction system for lake stony-bottom littoral macroinvertebrate communities. Archiv für Hydrobiologie 158, 517–540.CrossRefGoogle Scholar
Kelly, M. G. (1998) Use of community-based indices to monitor eutrophication in European rivers. Environmental Conservation 25, 22–29.CrossRefGoogle Scholar
Kokeš, J., Zahradkova, N. D., Hodovsky, J., Jarkovsky, J. and Soldan, T. (2006) The PERLA system in the Czech Republic: a multivariate approach for assessing the ecological status of running waters. Hydrobiologia 566, 343–354.CrossRefGoogle Scholar
Kolkwitz, R. and Marsson, M. (1902) Grundsätze für die biologische Beurteilung des Wassers nach seiner Flora und Fauna. Mitt. aus d. Kgl. Prüfungsanstalt für Wasser versorgung u. Abwässerbeseitigung 1, 33–72.Google Scholar
Kolkwitz, R. and Marsson, M. (1908) Ökologie der pflanzlichen Saprobien. Ber Deutsch Bot Ges 26a, 505–519.Google Scholar
Kolkwitz, R. and Marsson, M. (1909) Ökologie der tierischen Saprobien. International Reviews in Hydrobiology 2, 126–152.CrossRefGoogle Scholar
Mez, C. (1898) Mikroskopische Wasseranalyse. Anleitung zur Untersuchung des Wassers mit besonderer Berücksichtigung von Trink- und Abwasser J. Springer, Berlin.Google Scholar
Moss, D. (1997) Evolution of statistical methods in RIVPACS. In: Assessing the Biological Quality of Fresh Waters (eds. Wright, J. F., Sutcliffe, D. W. and Furse, M. T.), pp. 25–37. Freshwater Biological Association, Ambleside, UK.Google Scholar
Moss, D., Furse, M. T., Wright, J. F. and Armitage, P. D. (1987) The prediction of the macro-invertebrate fauna of unpolluted running-water sites in Great Britain using environmental data. Freshwater Biology 17, 41–52.CrossRefGoogle Scholar
Moss, D., Wright, J. F., Furse, M. T. and Clarke, R. T. (1999) A comparison of alternative techniques for the protection of the fauna of running water sites in Great Britain. Freshwater Biology 41, 167–181.CrossRefGoogle Scholar
Murphy, J. F. and Davy-Bowker, J. (2005) Spatial structure in lotic macroinvertebrate communities in England and Wales: relationship with physicochemical and anthropogenic stress variables. Hydrobiologia 534, 151–164.CrossRefGoogle Scholar
Murphy, J. F. and Davy-Bowker, J. (2006) The predictive modelling approach to biomonitoring: taking river quality assessment forward. In: Biological Monitoring of Rivers: Applications and Perspectives. (eds. Ziglio, M., Siligardi, M. and Flaim, G.), pp. 383–399. Wiley & Sons, Chichester, UK.CrossRefGoogle Scholar
Murray-Bligh, J. A. D., Furse, M. T., Jones, F. H., Gunn, R. J. M., Dines, R. A. and Wright, J. F. (1997) Procedure for Collecting and Analysing Macroinvertebrate Samples for RIVPACS. Environment Agency, Bristol and IFE, Wareham, UK.Google Scholar
Neale, M. W., Kneebone, N. T., Bass, J. A. B.et al. (2006) Assessment of the Effectiveness and Suitability of Available Techniques for Sampling Invertebrates in Deep Rivers. EU INTERREG IIIA Ireland/Northern Ireland, North South Share River Basin Management Project Report.
Norris, R. H and Hawkins, C. P (2000) Monitoring river health. Hydrobiologia 435, 5–17.CrossRefGoogle Scholar
Ormerod, S. J., Lewis, B. R., Kowalik, R. A., Murphy, J. F. and Davy-Bowker, J. (2006) Field testing the AWIC index for detecting acidification in British streams. Archiv für Hydrobiologie 166, 99–115.CrossRefGoogle Scholar
Ostermiller, J. D. and Hawkins, C. P. (2004) Effects of sampling error on bioassessments of stream ecosystems: application to RIVPACS-type models. Journal of the North American Benthological Society 23, 363–382.2.0.CO;2>CrossRefGoogle Scholar
Pantle, E. and Buck, H. (1955) Die biologische Überwachung der Gewässer und die Darstellung der Ergebnisse, Gas und Wasserfach 96, 604.Google Scholar
Patrick, R., Hohn, M. H. and Wallace, J. H. (1954) A new method for determining the pattern of the diatom flora. Notulae Naturae 259, 2–12.Google Scholar
Reynoldson, T. B, Bailey, R. C., Day, K. E. and Norris, R. H. (1995) Biological guidelines for freshwater sediment based on BEnthic Assessment of SedimenT (the BEAST) using a multivariate approach for predicting biological state. Australian Journal of Ecology 20, 198–219.CrossRefGoogle Scholar
Rolauffs, P., Hering, D., Sommerhäuser, M., Rödiger, S. and Jähnig, S. (2003) Entwicklung eines leitbildorientierten Saprobienindexes für die biologische Fließgewässerbewertung. Umweltbundesamt Texte 11/03, pp. 1–137.
Rutt, G. P., Weatherley, N. S. and Ormerod, S. J. (1990) Relationships between the physicochemistry and macroinvertebrates of British upland streams – the development of modelling and indicator systems for predicting fauna and detecting acidity. Freshwater Biology 24, 463–480.CrossRefGoogle Scholar
Scardi, M., Tancioni, L. and Cataudella, S. (2006) Monitoring methods based on fish. In: Biological Monitoring of Rivers: Applications and Perspectives (eds. Ziglio, M., Siligardi, M. and Flaim, G.), pp. 135–153. Wiley & Sons, Chichester, UK.CrossRefGoogle Scholar
Simpson, J. C. and Norris, R. H. (1997) Biological assessment of river quality: development of AusRivAS models and outputs. In: Assessing the Biological Quality of Fresh Waters (eds. Wright, J. F., Sutcliffe, D. W. and Furse, M. T.), pp. 125–142. Freshwater Biological Association, Ambleside, UK.Google Scholar
Sládeček, V. (1967) The ecological and physiological trends in the saprobiology. Hydrobiologia 30, 513–526.CrossRefGoogle Scholar
Sládeček, V. (1973) System of water quality from the biological point of view, Ergebnisse der Limnologi 7, 1–128.Google Scholar
Tuffery, G. and Verneaux, J. (1968) Méthode de détermination de la qualité biologique des eaux courantes. Exploitation codifiée des inventaires de fauna du fond. Ministère de l'Agriculture (France). 23 pp.Google Scholar
Turak, E., Flack, L. K., Norris, R. H., Simpson, J. and Waddell, N. (1999) Assessment of river condition at a large spatial scale using predictive models. Freshwater Biology 41, 283–298.CrossRefGoogle Scholar
Walley, W. J. and O'Connor, M. A. (2001) Unsupervised pattern recognition for the interpretation of ecological data. Ecological Modelling 146, 219–230.CrossRefGoogle Scholar
Woodiwiss, F. S. (1964) The biological system of stream classification used by the Trent River Board. Chemistry Industry 11, 443–447.Google Scholar
Wright, J. F.(1997) An introduction to RIVPACS. In: Assessing the Biological Quality of Fresh Waters (eds. Wright, J. F., Sutcliffe, D. W. and Furse, M. T.), pp. 1–24. Freshwater Biological Association, Ambleside, UK.Google Scholar
Wright, J. F., Moss, D., Armitage, P. D. and Furse, M. T. (1984) A preliminary classification of running-water sites in Great Britain based on macroinvertebrate species and the prediction of community type using environmental data. Freshwater Biology 14, 221–256.CrossRefGoogle Scholar
Yuan, L. (2006) Theoretical predictions of observed to expected ratios in RIVPACS-type predictive model assessments of stream biological condition. Journal of the North American Benthological Society 25, 841–850.CrossRefGoogle Scholar
Zelinka, M. and Marvan, P. (1961) Zur Präzisierung der biologischen Klassifikation der Reinheit fließender Gewässer. Archiv für Hydrobiologie 57, 389–407.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×