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What is it?
Predictive models used by AQUAWEB are based on the concept that the difference between the aquatic communities of a river and the communities of a set of reference sites with similar biotic characteristics (hydromorphological, geological, climatic or others) represents that river water quality.
That difference may be given by taxa diversity (presence/absence data) or by the diversity and the abundance of taxa (abundance data with or without transformation). The type of biological data required to use a model is given by that model Description.
The environmental variables used by each model are in the model Description along with the respective methodology and transformation.
For each model the sampling process for the target community is also indicated (see Description in List models).
Predictive models used in AQUAWEB follow the methodology of RVPACS/AURIVAS (Wright 1995, Wright et al. 1996, Simpson & Norris 2000) and BEAST models (Reynoldson et al.1995, 97, 2001), and user may choose one or both methods to assess its sites (test sites). In RIVPACS/AUSRIVAS type models (the approach designated as Probabilities in Use Models) the output of a new site assessment is: the list of taxa expected in that site in the absence of stress (with the respective probability of being found in that site); the ratio between the observed and expected taxa (O/E); and a band attributed to the site, that quantifies the stress in 5 categories (Band X, more biological diverse than reference, Band A, in reference condition, Band B, significantly impaired, Band C, severely impaired, to Band D, extremely impaired).
In the BEAST type models (aproach designated as Ellipses in Use Models) the output produces is a graph with the spatial ordination (nonmetric Multidimensional Scaling, MDS) of the reference communities and the communities of the sites to be assessed (test site). The quatification of stress is given by the band attributed by the model to the sites.
More details about both approaches used in AQUAWEB can be found in the Info section.
Acknowledgements:
The coordinator of this project (Maria João Feio, Marine and Environmental Research Centre IMAR-CMA) thanks to:
- Whole IEETA team (University of Aveiro) responsible for the construction of this site, including Carlos Costa, Joana Melo, Samuel Campos and Carlos Ferreira.
- Miguel Alves and Paulo Marques (Dept. of Computer Science, University of Coimbra), who developed the first version of the software and site in for the development and application of predictive models.
- Foundation for Science and Technology for the national funding through the Ministry of Science, Technology and Higher Education, Science 2008, and the co-financing guaranteed through the Structural Fund Reference Framework (QREN) and the Community Program: Operational Program for Competitiveness Factors (POFC) - COMPETE.
- Marine and Environmental Research Centre IMAR-CMA for the entire logistic support and to all participants all over the years in the collecting and processing data used in the construction of predictive models in IMAR, particularly A. Marcotegui, C. Mieiro, T. Alves, M. Boavida, Ana Calapez, Sónia Serra, Verónica Ferreira e Nuno Coimbra.
- INAG, I.P., the use of databases built during the implementation ot the WFD in Portugal, in the construction of predictive models, and to all those that contributed to the preparation of them, including M.A.S. Graça, P. Pinto, R.V. Cortes, M.T. Ferreira, N. Formigo, M. Morais.
- P.Pinto and R.Cortes, consultants of the AQUAWEB project.
- R.H. Norris, consultant of the AQUAWEB project, and for his cooperation essential in the understanding of RIVPACS/AUSRIVAS models. And Sue Nichols also fundamental in the knowledge of the mentioned models.
- B.C. Chessman, consultant of the AQUAWEB project
- T.B. Reynoldson for his collaboration in the development of BEAST models.
- J. Van Sickle for the availability of ''best-subsets scripts’ applied to RIVPACS models.
- M.A.S. Graça for his continued support and encouragement to the development of this site.
- Sónia Serra for her participation in the various phases of AQUAWEB project, especially in the the development of the taxonomic keys.
Some references:
ADRIENSSENS, V., GOETHALS, P.L.M., CHARLES, J. & DE PAUW. N. 2004a. Application of Bayesian Belief Networks for the prediction of macroinvertebrate taxa in rivers. Ann. Limnol. - Int. J. Lim. 40: 181-191.
AGUIAR, F.C., FEIO, M.J., FERREIRA, M.T. 2011. Choosing the best method for streams bioassessment using macrophyte communities: indices and predictive models. Ecological indicators. 11: 379-388.
ALMEIDA S.F.P. & FEIO M.J. (in press) DIATMOD: Diatom predictive model for quality assessment of Portuguese running waters. Hydrobiologia.
FEIO, M.J. & DOLEDEC, S. (under revisions) Integration of invertebrate traits into predictive models for indirect assessment of stream ecological functioning: a case study in Portugal. Ecological Indicators.
FEIO, M.J. & POQUET, J.M. 2011. Predictive models for freshwater biological assessment: statistical approaches, biological elements and the iberian peninsula experience. International Review of Hydrobiology. 96:321-346.
FEIO, M.J., AGUIAR, F.C., ALMEIDA, S.F.P., FERREIRA, M.T. (under revisions) AQUAFLORA: a predictive model based on diatoms and macrophytes for streams water quality assessment. Ecological indicators.
FEIO, M.J., ALMEIDA, S.F.P., CRAVEIRO, S.C. & CALADO, A.J. 2007. Diatoms and macroinvertebrates provide consistent and complementary information on environmental quality: A predictive model approach. Fundamental and Applied Limnology (Archiv für Hydrobiologie) 169: 247–258.
FEIO, M.J., ALMEIDA, S.F.P., CRAVEIRO, S.C. & CALADO, A.J. 2009. A comparison between biotic indices and predictive models in stream water quality assessment based on benthic diatom communities. Ecological indicators. 9: 497 – 507.
FEIO, M.J., ALVES, T., BOAVIDA, M., Medeiros, A. & Graça, M.A.S. 2010. Functional indicators of stream health: a river basin approach. Freshwater biology. 55: 1050–1065.
FEIO, M.J., NORRIS, R.H., GRAÇA, M.A.S. & NICHOLS, S. 2009. Water quality assessment of Portuguese streams: regional or national predictive models? Ecological indicators. 9: 791 – 806.
FEIO, M.J., REYNOLDSON T.B., & GRAÇA, M.A.S. 2006. Effect of seasonal and inter-annual changes in the predictions of the Mondego river model at three taxonomic levels. International Review of Hydrobiology. 91: 509–520.
FEIO, M.J., REYNOLDSON T.B., & GRAÇA, M.A.S. 2006. The influence of taxonomic level on the performance of a predictive model for water quality assessment. Can. J. Fish. Aquat. Sci. 63: 367-376.
FEIO, M.J., REYNOLDSON, T.B., FERREIRA, V. & Graça, M.A.S. 2007. A predictive model for the water quality bioassessment of the Mondego catchment, central Portugal. Hydrobiologia, 589:55–68.
LINKE, S., NORRIS, R. H., FAITH, D. P., & STOCKWELL, D. 2005. ANNA: A new prediction method for bioassessment programs. Freshwater Biology. 50: 147-158.
REYNOLDSON, T.B., BAILEY, R.C, DAY, K.E. & 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. Aust. J. Ecol. 20: 198–219.
REYNOLDSON, T.B., NORRIS, R.H., RESH, V.H., DAY, K.E. & ROSENBERG, D.M. 1997. The reference condition: a comparison of multimetric and multivariate approaches to assess water-quality impairment using benthic macroinvertebrates. J. North Am. Benthol. Soc. 16: 833–852.
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. Can. J. Fish. Aquat. Sci. 58: 1395–1410.
SIMPSON, J.C. & NORRIS, R.H. 2000. Biological assessment of river quality: development of AUSRIVAS models and outputs. In WRIGHT, J.F., SUTCLIFFE, D.W. & FURSE, M.T. (eds.): Assessing the biological quality of fresh waters: RIVPACS and other techniques. pp. 125-142.
WRIGHT, J.F. 1995. Development and use of a system for predicting the macroinvertebrate fauna in flowing waters. Aust. J. Ecol. 20: 181–197.
WRIGHT, J.F., BLACKBURN, J.H., GUNN, R.J.M., FURSE, M.T., ARMITAGE, P.D., WINDER, J.M. & SYMES, K.L. 1996. Macroinvertebrate frequency data for the RIVPACS III sites in Great Britain and their use in conservation evaluation. Aquat. Conserv. Mar. Freshw. Ecosyst. 6: 141–167.
