Development of diatom-based tools for assessing stream water quality in south-eastern Australia: assessment of environmental transfer functions

Abstract

Models were developed of relationships among water quality, geospatial and species-level diatom data for 465 samples collected from stream sites across south-eastern Australia. Transfer functions were derived from weighted averaging and artificial neural network approaches. Analysis of spatial variations in species assemblages was used to divide the sites into two groups according to site elevation. The strongest predictive models for the upland group associated diatom assemblages with conductivity, longitude, altitude, and to a lesser extent pH, NO x and TKN. The strongest predictors for the lowland group were longitude and conductivity, but artificial neural network models performed well for NO x and temperature. The importance of the geospatial variables suggests that there may be a capacity to develop diatom sub-regions within which robust models for other water quality variables important to management can be generated.