Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
Marine and Freshwater Research Marine and Freshwater Research Society
Advances in the aquatic sciences
Shopping Cart: ( empty )
You are here: Home > Journals > MF > MF09263
RESEARCH ARTICLE
Contents Vol 61(10)

Influence of the choice of physical and chemistry variables on interpreting patterns of sediment contaminants and their relationships with estuarine macrobenthic communities

Anthony A. Chariton A C , Anthony C. Roach B , Stuart L. Simpson A and Graeme E. Batley A
+ Author Affiliations
- Author Affiliations

A Centre for Environmental Contaminants Research, CSIRO Land and Water, Locked Bag 2007, Kirrawee, NSW 2232, Australia.

B Ecotoxicology and Environmental Contaminants Section, Department of Environment, Climate Change and Water, Lidcombe, NSW 1232, Australia.

C Corresponding author. Email: Anthony.Chariton@csiro.au

Marine and Freshwater Research 61(10) 1109-1122 https://doi.org/10.1071/MF09263
Submitted: 19 October 2009  Accepted: 14 April 2010   Published: 14 October 2010

Abstract

A primary objective of contaminated sediment risk assessments is to identify if contaminant enrichment is eliciting an ecological response. Using complementary environmental and biotic datasets, we examined five scenarios with respect to: dataset complexity; metal extraction; normalisation of organics; the inclusion/exclusion of acid-volatile sulfide data, and iron and manganese concentrations. Spatial distributions of abiotic variables were examined by principal components analysis, with canonical correspondence analysis used to examine the total and partitioning of biological variation. Metals were the dominant contaminant and explained the largest proportion of variation in the macrobenthic data. Extraction procedure and carbon normalisation of organics had little influence on the overall analysis. Porewater metal data was essential for interpretation, with excess of acid-volatile sulfide over simultaneously extractable metals being a poor surrogate. In the canonical correspondence analyses, the inclusion of Fe/Mn accentuated the covariation between the ecological and contaminant variables. Multimodel comparisons aided interpretation by emphasising specific relationships among environmental variables and their interactions with the biotic data. Furthermore, for future examinations of the described system, the findings can be used to reduce the collection of redundant environmental variables or variables that are poorly correlated with changes in macrobenthic assemblages.

Additional keywords: benthos, bioavailability, canonical correspondence analysis, environmental risk assessment, porewater, principal component analysis, sediment.


Acknowledgements

We wish to thank Cheryl Tang, Steve Jacobs, Richard Gardiner, Tim Ingleton, Max Carpenter, Chris Rush and Joanne Ling who assisted in biological survey work and biota identification. David Spadaro and Ian Hamilton undertook most of the physico-chemical characterisation, chemical analyses and assistance with biological survey work, and we thank Edwin Peeters (Wageningen University) for his statistical advice. We also wish to thank our CSIRO colleagues Jenny Stauber and Merrin Adams for editorial comments and advice. Funding for this research was provided by the NSW Environmental Trust (Research Project 22003/RD/G0002).


References

Ankley, G. T. , Katko, A. , and Arthur, J. W. (1990). Identification of ammonia as an important sediment-associated toxicant in the lower Fox River and Green Bay, Wisconsin. Environmental Toxicology and Chemistry 9, 313–322.
| Crossref | GoogleScholarGoogle Scholar | CAS | ANZECC/ARMCANZ (2000). ‘Australian and New Zealand Guidelines for Freshwater and Marine Water Quality Vol. 1.’ (Australian and New Zealand Environment and Conservation Council and Agriculture and Resource Management of Australia and New Zealand: Canberra.)

Batley, G. E. (1987). Heavy metal speciation in waters, sediment and biota from Lake Macquarie, New South Wales. Australian Journal of Marine and Freshwater Research 38, 591–606.
| Crossref | GoogleScholarGoogle Scholar | CAS | Clarke K. R., and Warwick R. M. (1994). ‘Changes in Marine Communities: An Approach to Statistical Analysis and Interpretation.’ (Plymouth Marine Laboratory: Plymouth, UK.)

Cline, J. D. (1969). Spectrophotometric determination of hydrogen sulfide in natural waters. Limnology and Oceanography 14, 454–458.
| Crossref | GoogleScholarGoogle Scholar | CAS | Legendre P., and Legendre L. (1998). ‘Numerical Ecology.’ 2nd edn. (Elsevier: Sydney.)

Lepš J., and Šmilauer P. (2003). ‘Multivariate Analysis of Ecological Data Using CANOCO.’ (Cambridge University Press: Melbourne.)

Long, E. R. , Field, L. J. , and McDonald, D. D. (1998). Predicting toxicity of marine sediments with numerical sediment quality guidelines. Environmental Toxicology and Chemistry 17, 714–727.
| Crossref | GoogleScholarGoogle Scholar | CAS | ter Braak C. J. (1996). ‘Unimodel Models to Relate Species to Environment.’ (DLO-Agricultural Mathematics Group: Wageningen.)

ter Braak, C. J. , and Verdonschot, P. F. M. (1995). Canonical correspondence analysis and related multivariate methods in aquatic ecology. Aquatic Sciences 57, 255–289.
| Crossref | GoogleScholarGoogle Scholar | US Environmental Protection Agency (1996). ‘Test Methods for Evaluating Solid Waste, Physical/Chemical Methods.’ Methods and Risk Analysis Division SW-846. (US Environmental Protection Agency: Washington, DC.)

US Environmental Protection Agency (2003). ‘Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms: PAH Mixtures.’ Office of Research and Development Report EPA-600-R-02-013. (US Environmental Protection Agency: Washington, DC.)

US Environmental Protection Agency (2005).‘Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks (ESBs) for the Protection of Benthic Organisms: Metal Mixtures (Cadmium, Copper, Lead, Nickel, Silver and Zinc).’ Office of Research and Development Report EPA-600-R-02-011. (US Environmental Protection Agency: Washington, DC.)

Wang, F. , and Chapman, P. M. (1999). Biological implications of sulfide in sediment – a review focusing on sediment toxicity. Environmental Toxicology and Chemistry 18, 2526–2532.
|  CAS | Wenning R. J., Batley G. E., Ingersoll C. G., and Moore D. W. (2005). ‘Use of Sediment-quality Guidelines and Related Tools for the Assessment of Contaminated Sediments.’ (Society of Environmental Toxicology and Chemistry: Pensacola, FL.)