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Abstract: Long-term data from the perch population of the north basin of Windermere, UK, were combined with effects data from laboratory toxicity studies of survival, growth and reproduction in other species to assess the likely impact on fish populations of different levels of exposure to nonylphenol (NP) and ethinylestradiol (EE2). A multi-stage Delay Differential Equation fish population model was used to simulate the perch population during two periods when it showed contrasting population structures (1968–1973 and 1983–1988) as the result of a disease outbreak in 1976, and to extrapolate the effects of chemical exposure to EE2 and NP observed in the laboratory to the environment. In the absence of chemical exposure, model simulations predicted population numbers (females) in line with those derived from field survey data. Effects predictions were made for long-term exposure (20 years) to low and high doses of EE2 (1 and 10ngl−1) and NP (1 and 30μgl−1). The sustained high-level exposure of EE2 had a high probability of causing the extinction of a confined fish population such as that in Windermere, however, such an exposure scenario is unlikely. Far greater uncertainty surrounds the prediction of effects due to low-level exposure of fish populations and even though effects may appear to be significant in laboratory studies, such as fecundity lowered by 30%, they may not necessarily translate into significant population effects in the field. This is especially true if life-history data show high natural variability in terms of individual vital rates. Our work suggests that for a decline in the perch population numbers to be significant in Windermere, it would have to be substantially more than 50%. Our model predictions indicated that the post-disease population was generally more vulnerable than the pre-disease population and had a significantly greater probability of declining by 50% following single chemical exposure, but both populations were equally likely to decline following multiple chemical exposure. Rate of population recovery was shown to be a more sensitive measure in terms of differentiating the effects of low and high chemical exposure as well as the vulnerability of populations with contrasting structures, histories or levels of background stress. [Copyright &y& Elsevier]

A post-processor of model output, EQUIP (Environmental QUality Information Processor), has been created and applied to effluent discharges to the Tees estuary in the north east of England. EQUIP is not a modelling system, but a statistical post-processor, which uses results from a compressed database of pre-run model scenarios. The system requires the results of a small number of model runs, which are selected using a statistical experimental design. A statistical response surface is used to summarise the model results for the PC database and to reconstruct plume predictions within EQUIP for user selected values of the tidal range and river inflow, or for annual average conditions. The method provides interpolation between model results assuming a smooth variation of the results with variations in the input parameters. The method is implemented on a PC and is much faster than running the full water quality model, producing spatial, temporal and vertical section plots for different states of the tide within a few minutes. In addition, maximum plume movement and tidal average concentrations are computed. Plumes from different outfalls are rapidly combined to give overall concentration fields within the estuary. The system is adaptable for outputs from different types of model, such as atmospheric dispersion models, groundwater models and other non-environmental applications. The methodology is also adaptable to simulate plume uncertainty, if input parameter variability is known. [Copyright &y& Elsevier]