Evaluation of suitable endpoints for assessing the impacts of toxicants at the community level
- First Online:
- Cite this article as:
- Sánchez-Bayo, F. & Goka, K. Ecotoxicology (2012) 21: 667. doi:10.1007/s10646-011-0823-x
Assessment of ecological impacts of toxicants relies currently on extrapolation of effects observed at organismal or population levels. The uncertainty inherent to such extrapolations, together with the impossibility of predicting ecological effects of chemical mixtures, can only be resolved by adopting approaches that consider toxicological endpoints at a community or ecological level. Experimental data from micro- and mesocosms provide estimates of community effect levels, which can then be used to confirm or correct the extrapolations from theoretical methods such as species sensitivity distributions (SSDs) or others. When assessing impacts, the choice of sensitive community endpoints is important. Four community endpoints (species richness, abundance, diversity and similarity indices) were evaluated in their ability to assess impacts of two insecticides, imidacloprid and etofenprox, and their mixture on aquatic and benthic communities from artificial rice paddies. Proportional changes of each community endpoint were expressed by ratios between their values in the treatment and control paddies. Regression lines fitted to the endpoint ratios against the time series of chemical concentrations were used to predict percentile impacts in the communities. The abundance endpoint appears to be the most sensitive indicator of the communities’ response, but the Czekanowski similarity index described best the structural changes that occur in all communities. Aquatic arthropods were more sensitive to the mixture of both insecticides than zooplankton and benthic communities. Estimated protective levels for 95% of aquatic species exposed to imidacloprid (<0.01–1.0 μg l−1) were slightly lower than predicted by SSD, whereas for etofenprox the protective concentrations in water (<0.01–0.58 μg l−1) were an order of magnitude lower than SSD’s predictions.