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This study evaluated the usefulness of energy reserves as an early warning system in Folsomia candida when exposed to the pesticide dinoseb. After different exposure times, survival, reproduction, growth (weight and length), lipid and protein content of the organisms were determined. After six days of exposure at 15– of dinoseb/g dry soil, the weight, lipid, and protein content of the exposed organisms were higher than the controls. This stimulation seems to indicate that Collembola adopt a strategy of increasing their growth in order to improve their reproduction. This hypothesis was confirmed by the number of eggs laid which was greater in exposed organisms. After 21 days, all measured parameters decreased. The results show that after having produced an effort to increase growth and reproduction, lethality increases. The selected energy reserves are not more sensitive than the classically measured parameters such as reproduction, but can be more predictive for a pollutant stress encountered by the organisms. [Copyright &y& Elsevier]

Abstract: Models describing dose–response relationships are becoming increasingly popular in ecotoxicology. They allow simple and thorough evaluations of toxicity test results, including inter- and extrapolations to concentrations or exposure times other than those tested. Simple parametric regression models are of particular interest because their parameters may be attributed mechanistic meanings and they can be applied without sophisticated mathematical and computational support. We recently proposed a four-parameter logistic regression model to fit the survival data of Daphnia magna under dinoseb stress. The model parameters are the maximum survival time, the minimum time required for an individual to die, effect concentration, EC50, and a curve shape parameter. This model has now been applied to compare the lethality and reproduction toxicity of D. magna and the growth inhibition of Pseudokirchneriella subcapitata under dinoseb stress. It can be fitted adequately to all the measured data and the parameters can be attributed biological meanings in any of the three endpoints. A comparison of the modeled concentration–response functions of all three endpoints for dinoseb toxicity shows that the range of ECs with respect to both D. magna and algae is steep (a decrease of between 0.1 and 0.6mg/L). The survival and reproduction of D. magna exhibit similar characteristic concentration–response functions and toxicities. The statistical no-effect concentration (SNEC) is 0.14 (survival) and 0.11 (reproduction)mg/L, respectively. On the other hand, algae seem to be less sensitive to dinoseb than D. magna (SNEC: 0.48mg/L). However, further investigations of individual algae may lead to a more suitable comparison. We speculate that the four parameters of the model function can be related to specific properties of chemicals and organisms. Characterization of these properties would allow simple and appropriate estimation of the toxic effects of these chemicals. [Copyright &y& Elsevier]

Risk assessment is in urgent need of more accurate toxic effect endpoints than those currently in use, especially for low concentrations. Often such endpoints are estimated by analysis of variance, linear interpolation, or smoothing. As these statistical methods are not always satisfactory, some authors have proposed to describe the entire dose--response curves by fully formalized parametric regression models whose parameters have toxicological meaning. These models allow a better evaluation of pollutant effects, including inter- and extrapolation to any other than the measured effect values. Following this line, a four-parameter logistic regression model (standard model) was fitted to survival data of Daphnia magna under pesticide (dinoseb) stress. The heterogeneity of the variance was taken into account with a both-sides logarithmic transformation. Besides the standard model, a hormesis and a threshold model were tested too. These two others models have been described in the literature and might better represent the dose--response function we are looking for. All three models showed a good fit to our data, and the statistics gave no hints as to which model is the most appropriate. As no evidence was seen for hormesis or for the existence of a threshold concentration, we used the simplest, namely, the standard model, for most of our calculations. Model calculations allow the quantification of the effects on individuals' longevity as well as on mean survival time of the population. We used them to define a no-effect value, the statistical-no-effect concentration (SNEC). The SNEC is based on the confidence bands of the modeled regression and represents the highest value for which an effect is statistically not different from the control. The SNEC is an alternative to classical endpoints, like the no-observed-effect concentration (NOEC) or the low-effect concentrations (e.g., EC10, EC5, EC1). [ABSTRACT FROM AUTHOR]