The Swan Coastal Plain is situated along the Western Australian seaboard and accommodates a large number of permanently, seasonally and episodically flooded wetlands. Many of these wetlands are affected by eutrophication and hydrological changes. A systematic monitoring program has been conducted between 1989 and 1990 to assess the environmental status of 41 selected wetlands based on measurements of 19 physical-chemical attributes and the collection of 253 macroinvertebrate taxa samples (Davis et al. 1993). This study analysed 35 wetlands with consistent data collected in Nov 1989 and Nov 1990 by means of Gradient Forest (GF) and the Hybrid Evolutionary Algorithm (HEA). Whilst GF allows identifying macroinvertebrate taxa with the “strongest overall response” to gradients in “important” physical-chemical attributes, HEA allows to model population dynamics of the taxa depending on “important” attributes identified by GF along all 35 wetlands. HEA models are represented by IF-THEN-ELSE rules whereby IF-conditions disclose attribute thresholds that indicate changes in the species abundance across the wetlands. GF suggested different ranking of the attributes EC, TN and DIP for both years as well as different taxa assemblages for same attributes in 1989 and 1990. Since results for merged data were also different, only the year-by-year specific results have been taken into account. When inferential models have been built for the 4 species that responded “strongest” to EC, DIP and TN in 1989 and 1990 by HEA, the threshold conditions fall in the range of overall gradients of these attributes discovered by GF. GF and HEA proved to be complementary tools for identifying overall attribute gradients and species- and site-specific thresholds in complex ecological data sets. Davis, J.A., Rosich, R.S., Bradley, J.S., Growns, J.E., Schmidt, L.G. and F. Cheal, 1993. Wetlands of the Swan Coastal Plain. Vol. 6: Wetland classification on the basis of water quality and invertebrate community data. Water Authority of Western Australia.