Register      Login
Marine and Freshwater Research Marine and Freshwater Research Society
Advances in the aquatic sciences
RESEARCH ARTICLE

Response of stream macroinvertebrates to changes in salinity and the development of a salinity index

Nelli Horrigan A C , Satish Choy A , Jonathan Marshall A and Friedrich Recknagel B
+ Author Affiliations
- Author Affiliations

A Department of Natural Resources and Mines (NR&M), 120 Meiers Rd, Indooroopilly, Qld 4068, Australia.

B School of Earth and Environmental Sciences, University of Adelaide, SA 5000, Australia.

C Corresponding author. Email: nelli.horrigan@nrm.qld.gov.au

Marine and Freshwater Research 56(6) 825-833 https://doi.org/10.1071/MF04237
Submitted: 9 September 2004  Accepted: 27 May 2005   Published: 27 September 2005

Abstract

Many streams and wetlands have been affected by increasing salinity, leading to significant changes in flora and fauna. The study investigates relationships between macroinvertebrate taxa and conductivity levels (µS cm−1) in Queensland stream systems. The analysed dataset contained occurrence patterns of frequently found macroinvertebrate taxa from edge (2580 samples) and riffle (1367 samples) habitats collected in spring and autumn over 8 years. Sensitivity analysis with predictive artificial neural network models and the taxon-specific mean conductivity values were used to assign a salinity sensitivity score (SSS) to each taxon (1—very tolerant, 5—tolerant, 10—sensitive). Salinity index (SI) based on the cumulative SSS was proposed as a measurement of change in macroinvertebrate communities caused by salinity increase. Changes in macroinvertebrate communities were observed at relatively low salinities, with SI rapidly decreasing to ~800–1000 µS cm−1 and decreasing further at a slower rate. Natural variability and water quality factors were ruled out as potential primary causes of the observed changes by using partial canonical correspondence analysis and subsets of the data with only good water quality.

Extra keywords: anthropogenic impacts, aquatic invertebrates, dryland salinity, ecological indicators, salt pollution.


Acknowledgments

Authors would like to acknowledge Glenn McGregor (NR&M), Jason Dunlop (NR&M) for their valuable comments and Ben Stewart Koster (Griffith University) and Mark Kennard (Griffith University) for suggestions regarding partial CCA. Financial support for this study was provided by the National Action Plan for Salinity and Water Quality.


References

Ball G. R., Palmer-Brown D., and Mills G. E. (2000). A comparison of artificial neuronal network and conventional statistical techniques for analysing environmental data. In ‘Artificial Neural Networks: Application to Ecology and Evolution’. (Eds S. Lek and J. F. Guégan.) p. 262. (Springer Verlag: Berlin.)

Bayly, I. A. E. (1969). The occurrence of calanoid copepods in athalassic saline waters in relation to salinity and ionic proportions. Vernandlungen Internationale Vereinigung fur Theoretische and Angewandthe Limnologie 17, 449–455.
Bishop C. M. (1995). ‘Neural Networks for Pattern Recognition.’ (Oxford University Press Inc.: New York.)

Bloedel L., Wilhelm G., Clarke R., Horn T., and Churchill R. (2000). Water quality exceedence, trend and status assessment for Queensland. Report 42. Queensland Department of Natural Resources, Brisbane.

Brosse, S. , Giraudel, J. L. , and Lek, S. (2001). Utilisation of non-supervised neural networks and principal component analysis to study fish assemblages. Ecological Modelling 146, 159–166.
Crossref | GoogleScholarGoogle Scholar | Conrick D., and Cockayne B. (2000). Queensland Australian River Assessment System (AusRivAs) sampling and processing manual. Queensland Department of Natural Resources. Freshwater Biological Monitoring Unit, Brisbane.

Department of Environment and Heritage and Department of Natural Resources (1999). Testing the waters. A report of the quality of Queensland waters. Report 21. Queensland Government, Brisbane.

Hart, B. T. , Bailey, P. , Edwards, R. , Hortle, K. , James, K. , and McMahon, A. (1991). A review of the salt sensitivity of the Australian freshwater biota. Hydrobiologia 210, 105–144.
Haykin S. (1999). ‘Neural Networks: A Comprehensive Foundation.’ (Prentice Hall: Englewood Cliffs, NJ.)

Hoang, H. , Recknagel, F. , Marshall, J. , and Choy, S. (2001). Predictive modelling of macroinvertebrate assemblages for stream habitat assessments in Queensland (Australia). Ecological Modelling 146, 195–206.
Crossref | GoogleScholarGoogle Scholar | Hoang H., Recknagel F., Marshall J., and Choy S. (2003). Elucidation of hypothetical relationships between habitat conditions and macroinvertebrate assemblages in freshwater streams by artificial neural networks. In ‘Ecological Informatics. Understanding Ecology by Means of Biologically-inspired Computation’. (Ed. F. Reckangel.) pp. 179–192. (Springer-Verlag: New York.)

Goetsch, P. A. , and Palmer, C. G. (1997). Salinity tolerance of selected macroinvertebrates of the Sabie River, Kruger National Park, South Africa. Archives of Environmental Contamination and Toxicology 32, 32–41.
Crossref | GoogleScholarGoogle Scholar | PubMed | Principe J. C., Euliano N. R., and Lefebvre W. C. (2000). ‘Neural and Adaptive Systems. Fundamentals Through Simulations.’ (John Wiley & Son, Inc.: New York.)

Poff, N. L. (1996). Stream hydrological and ecological responses to climate change assessed with an artificial neural network. Limnology and Oceanography 41(5), 857–863.
Ter Braak C. J. F. (1988). Partial canonical correspondence analysis. In ‘Classification and Related Methods of Data Analysis’. (Ed. H. H. Bock.) pp. 551–558. (Elsevier: Amsterdam.)

Ter Braak, C. J. F. , and Verdonschot, P. F. M. (1995). Canonical correspondence analysis and related multivariate methods in aquatic ecology. Aquatic Sciences 57(3), 255–285.
Crossref | GoogleScholarGoogle Scholar |

Williams, W. D. , Boulton, A. J. , and Taaffe, R. G. (1990). Salinity as determinant of salt lake fauna: a question of scale. Hydrobiologia 197, 257–266.
Crossref | GoogleScholarGoogle Scholar |

Williams, W. D. , Taaffe, R. G. , and Boulton, A. J. (1991). Longitudinal distribution of macroinvertebrates in two rivers subject to salinization. Hydrobiologia 210, 151–160.