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Adjusting the effect of seasonal variability in the bioassessment of streams

  • Sónia R. Q. Serra
  • Ana Raquel Calapez
  • Amaia Pérez-Bilbao
  • Maria João Feio
Article
  • 208 Downloads

Abstract

Bioassessment tools should distinguish between the effects of anthropogenic degradation in communities and natural temporal changes. The present study tests the influence of natural seasonal variability on macroinvertebrate stream communities assessed by a predictive model (PORTRIV) and a multimetric index (IPtI) calibrated for spring. The scores of PORTRIV decreased significantly between spring and autumn, and between spring and winter (ca. 37 to 53 %, respectively), while those of IPtI did not change significantly between seasons. For non-reference samples, the results of the predictive model also indicate no significant differences. A correction factor (CF) was calculated to adjust the existing differences in the model assessments between seasons, based on the percentage of variation of reference site scores from spring to autumn and winter. After the application of the CF to the OE50 scores of spring reference samples, the differences were no longer significant. Independent reference validation sites confirmed this tendency. This method has the advantage of avoiding large efforts required for the construction of databases from other seasons and the development of new models to allow the assessment of streams in seasons other than spring. Further tests with models developed in regions with more marked seasonal changes should be done to confirm its wider applicability.

Keywords

Streams Rivers Invertebrates Predictive model Multimetric index Seasonality 

Notes

Acknowledgments

This study was possible by funding from the Fundação para a Ciência e Tecnologia to the AQUAWEB project (PTDC/AACAMB/105297/2008). We acknowledge the Institute of Water (INAG IP) and all teams involved in the collection of data for the use of the national database and the software AMIIB@ (2011 Beta version. Application for calculating benthic invertebrate metrics and indices), and Dr. John Van Sickle to make the “best subsets” R scripts available that were adapted here for model building and under his additional clarifications.

References

  1. Alba-Tercedor, J., & Sánchez-Ortega, A. (1988). Un método rápido y simple para evaluar la calidad biológica de las águas corriente basado en el de Hellawell (1978). Limnetica, 4, 51–56.Google Scholar
  2. Bady, P., Dolédec, S., Dumont, B., & Fruget, J.-F. (2004). Multiple co-inertia analysis: a tool for assessing synchrony in the temporal variability of aquatic communities. Ecology, 327, 29–36.Google Scholar
  3. Barbour, M. T. (1997). The re-invention of biological assessment in the U.S. Human and Ecological Risk Assessment, 3, 933–940.CrossRefGoogle Scholar
  4. Buffagni, A., Erba, S., Cazzola, M., Murray-Bligh, J., Soszka, H., & Genoni, P. (2006). The STAR common metrics approach to the WFD intercalibration process: full application for small, lowland rivers in three European countries. Hydrobiologia, 566, 379–399.CrossRefGoogle Scholar
  5. Callanan, M., Baars, J.-R., & Kelly-Quinn, M. (2008). Critical influence of seasonal sampling on the ecological quality assessment of small headwater streams. Hydrobiologia, 610, 245–255.CrossRefGoogle Scholar
  6. Chessman, B. C., Jones, J. A., Searle, N. K., Grows, I. O., & Pearson, M. R. (2010). Assessing effects of flow alteration on macroinvertebrate assemblages in Australian dryland rivers. Freshwater Biology, 55, 1780–1800.Google Scholar
  7. Clarke, R. T., & Murphy, J. F. (2006). Effects of locally rare taxa on the precision and sensitivity of RIVPACS bioassessment of freshwaters. Freshwater Biology, 51, 1924–1940.CrossRefGoogle Scholar
  8. Clarke, R. T., Furse, M. T., Gunn, J. M., Winder, J. M., & Wright, J. F. (2002). Sampling variation in macroinvertebrate data and implications for river quality indices. Freshwater Biology, 47, 1735–1751.CrossRefGoogle Scholar
  9. Clarke, R. T., Wright, J. F., & 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
  10. Cortes, R. M. V., Oliveira, S. V., Cabral, D. A., Santos, S., & Ferreira, T. (2002). Different scales of analysis in classifying streams: from a multimetric towards an integrate system approach. Archiv für Hydrobiologie, 141, 209–224.Google Scholar
  11. Dallas, H. F. (2013). Ecological status assessment in Mediterranean rivers: complexities and challenges in developing tools for assessing ecological status and defining reference conditions. Hydrobiologia, 719, 483–507.CrossRefGoogle Scholar
  12. Dolédec, S., & Statzner, B. (2010). Responses of freshwater biota to human disturbance: contribution of J-NABS to developments in ecological integrity assessments. Journal of the North American Benthological Society, 29, 286–311.CrossRefGoogle Scholar
  13. Environmental Agency. (2003). River Habitat Survey in Britain and Ireland: Field Survey Guidance Manual. River Habitat Survey Manual: version 2003. Bristol.Google Scholar
  14. Feio, M. J., Reynoldson, T. B., & Graça, M. A. S. (2006). Effect of seasonal changes on predictive model assessment of streams water quality with macroinvertebrates. International Review of Hydrobiology, 91, 509–520.CrossRefGoogle Scholar
  15. Feio, M. J., Coimbra, C. N., Graça, M. A. S., & Nichols, S. J. (2010). The influence of extreme climatic events and human disturbance on macroinvertebrate community patterns of a Mediterranean stream over 15 y. Journal of the North American Benthological Society, 29, 1397–1409.CrossRefGoogle Scholar
  16. Ferreira, J., Bernardo, J. M., & Alves, M. H. (2008). Exercício de Intercalibração em rios no âmbito da Directiva Quadro da Água – Associação Portuguesa de Recursos Hídricos. Lisboa: 9° Congresso Da Água, Centro de Congressos do Estoril.Google Scholar
  17. Furse, M. T., Moss, D., Wright, J. F., & 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 prediction of their macro-invertebrate communities. Freshwater Biology, 14, 257–280.CrossRefGoogle Scholar
  18. Gasith, A., & Resh, V. H. (1999). Streams in Mediterranean climate regions: abiotic influences and biotic responses to predictable seasonal events. Annual Review of Ecology and Systematics, 30, 51–81.CrossRefGoogle Scholar
  19. Hawkins, C. P., Norris, R. H., Hughes, J. M., & Feminella, J. W. (2000). Development and evaluation of predictive models for measuring the biological integrity of streams. Ecological Applications, 10, 1456–1477.CrossRefGoogle Scholar
  20. Hawkins, C. P., Olson, J. R., & Hill, R. A. (2010). The reference condition: predicting benchmarks for ecological and water-quality assessments. Journal of the North American Benthological Society, 29, 312–343.CrossRefGoogle Scholar
  21. Hilsenhoff, W. L. (1988). Seasonal correction factors for the biotic índex. Greaf Lakes Entomologist, 21, 9–13.Google Scholar
  22. INAG. (2008). Tipologia de rios em Portugal Continental no âmbito da implementação da Directiva-Quadro da Água. I - Caracterização abiótica. Portugal: Ministério do Ambiente, do Ordenamento do Território e do Desenvolvimento Regional. Instituto da Água, I. P.Google Scholar
  23. INAG. (2009). Critérios para a Classificação do Estado das Massas de Água Superficiais: Rios e Albufeiras. Lisboa: Ministério do Ambiente, do Ordenamento do Território e do Desenvolvimento Regional. Instituto da Água, I.P.Google Scholar
  24. Karr, J. R. (1981). Assessment of biotic integrity using fish communities. Fisheries, 6, 21–27.CrossRefGoogle Scholar
  25. Karr, J. R. (1999). Defining and measuring river health. Freshwater Biology, 41, 221–234.CrossRefGoogle Scholar
  26. Lenat, D. R. (1993). A biotic index for the southeastern United States: derivation and list of tolerance values, with criteria for assigning water-quality ratings. Journal of the North American Benthological Society, 12, 279–290.CrossRefGoogle Scholar
  27. Linke, S., Bailey, R. C., & Schwindt, J. (1999). Temporal variability of stream bioassessments using benthic macroinvertebrates. Freshwater Biology, 42, 575–584.CrossRefGoogle Scholar
  28. Mazor, R. D., Purcell, A. H., & Resh, V. H. (2009). Long-term variability in bioassessment: a twenty-year study from two northern California streams. Environmental Management, 43, 1269–1286.CrossRefGoogle Scholar
  29. Mendes, T., Calapez, A. R., Elias, C. L., Almeida, S. F. P., & Feio, M. J. (2013). Comparing alternatives for combining invertebrate and diatom assessment in stream quality classification. Marine and Freshwater Research. doi: 10.1071/MF13135.Google Scholar
  30. Metzeling, L., Robinson, D., Perriss, S., & Marchand, R. (2002). Temporal persistence of benthic invertebrate communities in south-eastern Australian streams: taxonomic resolution and implications for the use of predictive models. Marine and Freshwater Research, 53, 1223–1234.CrossRefGoogle Scholar
  31. Moss, D., Furse, M. T., Wright, J. F., & Armitage, P. D. (1987). The prediction of the macro-invertebrate fauna of unpolluted running-water sites in Great Britain using environmental variables. Freshwater Biology, 17, 41–52.CrossRefGoogle Scholar
  32. Munné, A., & Prat, N. (2011). Effects of Mediterranean climate annual variability on stream biological quality assessment using macroinvertebrate communities. Ecological Indicators, 11(2), 651–662.CrossRefGoogle Scholar
  33. Oliveira, S. V., & Cortes, R. M. V. (2005). A biologically relevant habitat condition index for streams in ern Portugal. Aquatic Conservation: Marine and Freshwater Ecosystems, 15, 189–210.CrossRefGoogle Scholar
  34. Poquet, J. M., Alba-Tercedor, J., Puntí, T., del Sánchez-Montoya, M., Robles, S., Álvarez, M., Zamora-Muñoz, C., Sáinz-Cantero, C. E., Vidal-Abarca, M. R., Suárez, M. L., Toro, M., Pujante, A. M., Rieradevall, M., & Prat, N. (2008). The MEDiterranean Prediction And Classification System (MEDPACS): an implementation of the RIVPACS/AUSRIVAS predictive approach for assessing Mediterranean aquatic macroinvertebrate communities. Hydrobiologia, 623, 153–171.CrossRefGoogle Scholar
  35. Project FCT: AQUAWEB (PTDC/AACAMB/105297/2008). (2011). The predictive model PORTRIV – PORTtuguese River Invertebrates model. http://aquaweb.uc.pt/vermodelo.php?id=101462 Accessed 11 July 2012.
  36. Reece, P. F., & Richardson, J. S. (1998). Seasonal changes of benthic communities in southwestern British Columbia. Environment Canada Fraser River Action Plan’s. Vancouver: Environment Canada DOE-FRAP 1998–33. 87pp.Google Scholar
  37. Reece, P. F., & Richardson, J. S. (2000). Benthic macroinvertebrates assemblages of coastal and continental streams and large rivers of southwestern British Columbia, Canada. Hydrobiologia, 439, 77–89.CrossRefGoogle Scholar
  38. Reece, P. F., Reynoldson, T. B., Richardson, J. S., & Rosenberg, D. M. (2001). Implications of seasonal variation for biomonitoring with predictive models in the Fraser River catchment, British Columbia. Canadian Journal of Fisheries and Aquatic Science, 58, 1411–1418.CrossRefGoogle Scholar
  39. Reynoldson, T. B., Norris, R. H., Resh, V. H., Day, K. E., & Rosenberg, D. M. (1997). The reference condition: a comparision of multimetric and multivariate approaches to assess water-quality impairment using benthic macroinvertebrates. Journal of the North American Benthological Society, 16, 833–852.CrossRefGoogle Scholar
  40. Reynoldson, T. B., Rosenberg, D. M., & Resh, V. H. (2001). Comparison of models predicting invertebrate assemblages for biomonitoring in the Fraser river catchment, British Columbia. Canadian Journal of Fisheries and Aquatic Science, 58, 1395–1410.CrossRefGoogle Scholar
  41. Scarsbrook, M. R. (2002). Persistence and stability of lotic invertebrate communities in New Zealand. Freshwater Biology, 47, 417–431.CrossRefGoogle Scholar
  42. Sporka, F., Vlek, H. E., Bulánková, E., & Kron, I. (2006). Influence of seasonal variation on bioassessment of streams using macroinvertebrates. Hydrobiologia, 566, 543–555.CrossRefGoogle Scholar
  43. Stark, J. D., & Phillips, N. (2009). Seasonal variability in the Macroinvertebrate Community Index: are seasonal correction factors required? New Zealand Journal of Marine and Freshwater Research, 43, 867–882.CrossRefGoogle Scholar
  44. Stoddard, J., Larsen, D. P., Hawkins, C. P., Johnson, R. K., & Norris, R. H. (2006). Setting expectations for the ecological condition of streams: the concept of reference condition. Ecological Applications, 16, 1267–1276.CrossRefGoogle Scholar
  45. Underwood, A. J. (2009). Spatial and temporal problems with monitoring. In P. Calow & G. E. Petts (Eds.), The Rivers Handbook: Hydrological and Ecological Principles (Vol. 1, pp. 101–123). Oxford: Blackwell Science.Google Scholar
  46. Van Sickle, J., Hawkins, C. P., Larsen, D. P., & Herlihy, A. T. (2005). A null model for the expected macroinvetebrates assemblage in streams. Journal of the North American Benthological Society, 24, 178–191.CrossRefGoogle Scholar
  47. Van Sickle, J., Huff, D. D., & Hawkins, C. P. (2006). Selecting discriminant function models for predicting the expected richness of aquatic macroinvertebrates. Freshwater Biology, 51, 359–372.CrossRefGoogle Scholar
  48. Wright, J. F., Moss, D., Armitage, P. D., & Furse, M. T. (1984). A preliminary classification of running-water sites in Great Britain based on macro-invertebrate species and the prediction of community type using environmental data. Freshwater Biology, 14, 221–256.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Sónia R. Q. Serra
    • 1
  • Ana Raquel Calapez
    • 1
  • Amaia Pérez-Bilbao
    • 1
  • Maria João Feio
    • 1
  1. 1.IMAR–CMA, Marine and Environmental Research Centre, A/c Department of Life Sciences, Faculty of Science and TechnologyUniversity of CoimbraCoimbraPortugal

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