Statistical analysis of regulatory ecotoxicity tests.

ANOVA-type data analysis, i.e.. determination of lowest-observed-effect concentrations (LOECs), and no-observed-effect concentrations (NOECs), has been widely used for statistical analysis of chronic ecotoxicity data. However, it is more and more criticised for several reasons, among which the most important is probably the fact that the NOEC depends on the choice of test concentrations and number of replications and rewards poor experiments, i.e., high variability, with high NOEC values. Thus, a recent OECD workshop concluded that the use of the NOEC should be phased out and that a regression-based estimation procedure should be used. Following this workshop, a working group was established at the French level between government, academia and industry representatives. Twenty-seven sets of chronic data (algae, daphnia, fish) were collected and analysed by ANOVA and regression procedures. Several regression models were compared and relations between NOECs and ECx, for different values of x, were established in order to find an alternative summary parameter to the NOEC. Biological arguments are scarce to help in defining a negligible level of effect x for the ECx. With regard to their use in the risk assessment procedures, a convenient methodology would be to choose x so that ECx are on average similar to the present NOEC. This would lead to no major change in the risk assessment procedure. However, experimental data show that the ECx depend on the regression models and that their accuracy decreases in the low effect zone. This disadvantage could probably be reduced by adapting existing experimental protocols but it could mean more experimental effort and higher cost. ECx (derived with existing test guidelines, e.g., regarding the number of replicates) whose lowest bounds of the confidence interval are on average similar to present NOEC would improve this approach by a priori encouraging more precise experiments. However, narrow confidence intervals are not only linked to good experimental practices, but also depend on the distance between the best model fit and experimental data. At least, these approaches still use the NOEC as a reference although this reference is statistically not correct. On the contrary, EC50 are the most precise values to estimate on a concentration response curve, but they are clearly different from the NOEC and their use would require a modification of existing assessment factors.

Comparison of four chronic toxicity tests using algae, bacteria, and invertebrates assessed with sixteen chemicals.

The performances of four chronic toxicity tests, comprising the Daphnia magna 21-day (d) (crustacean), Brachionus calyciflorus 2-d (rotifer), Pseudokirchneriella subcapitata 72-h (green algae), and the Microtox chronic 22-h (bacteria) tests, were compared. Sixteen chemicals with toxicity covering 6 orders of magnitude were studied. Very high correlations were found between the NOEC/EC(10) Pseudokirchneriella 72-h, NOEC/EC(10) Brachionus 2-d, and the NOEC Daphnia 21-d tests. The toxicological response of rotifers and microalgae were within the same order of magnitude as the response of Daphnia in 80% of cases (13/16 chemicals). The Microtox chronic test also anticipated the overall results of the Daphnia 21-d test, but the prediction was rather imprecise, compared with microalgae and rotifers. The test measuring the algal growth inhibition of P. subcapitata after 72h was the most sensitive bioassay. Toxicity on microalgae after 72h could be estimated after 5h by measuring either the direct fluorescence of either photosynthetic pigments or fluorescein diacetate in 56 and 43% of cases, respectively. The median value of the ratio between EC(10) and EC(50) was 3.75, 2, and 1.5 with the algae, the rotifers, and the bacteria, respectively.