Applicability of Chronic Multiple Linear Regression Models for Predicting Zinc Toxicity in Australian and New Zealand Freshwaters

Bioavailability models e.g., multiple linear regressions (MLRs) of water quality parameters, are increasingly being used to develop bioavailability-based water quality criteria for metals. However, models developed for the Northern Hemisphere cannot be adopted for Australia and New Zealand without first validating them against local species and local water chemistry characteristics. This study investigated the applicability of zinc chronic bioavailability models to predict toxicity in a range of uncontaminated natural waters in Australia and New Zealand. Water chemistry data were compiled to guide a selection of waters with different zinc toxicity modifying factors (TMFs). Predicted toxicities using several bioavailability models were compared to observed chronic toxicities for the green alga Raphidocelis subcapitata and the native cladocerans Ceriodaphnia cf. dubia and Daphnia thomsoni. The most sensitive species to zinc in five New Zealand freshwaters was R. subcapitata (72-h growth rate), with toxicity ameliorated by high DOC or low pH, and hardness having a minimal influence. Zinc toxicity to D. thomsoni (reproduction) was ameliorated by both high DOC and hardness in these same waters. No single trophic level-specific EC10 MLR was the best predictor of chronic toxicity to the cladocerans, and MLRs based on EC10 values both over- and under-predicted zinc toxicity. EC50 MLRs better predicted toxicities to both the Australian and New Zealand cladocerans to within a factor of 2 of the observed toxicities in most waters. This suggests that existing MLRs may be useful for normalising local ecotoxicity data to derive water quality criteria for Australia and New Zealand. The final choice of models will depend on their predictive ability, level of protection and ease of use.