Pollution-induced community tolerance (PICT) as a tool for monitoring Lake Geneva long-term in situ ecotoxic restoration from herbicide contamination.

Chemical monitoring revealed a regular decrease in herbicide concentration in Lake Geneva since last decades that may be linked to an ecotoxic restoration of nontarget phytoplanktonic communities. The Pollution-induced community tolerance (PICT) approach was tested as a tool to monitor the ecotoxic restoration of Lake Geneva for herbicides from 1999 to 2011. We conducted monthly assessments in 1999 and in 2011 for the tolerance of the phytoplankton communities to two herbicides (atrazine and copper), using PICT bioassays. The taxonomical composition of the communities was determined on the same collecting dates. The herbicide concentration decrease during the 12 years significantly influenced the composition of communities. The PICT monitoring indicated that a significant tolerance decrease in the community to both herbicides accompanied the herbicide concentration decrease. PICT measurements for atrazine and copper also changed at the intra-annual level. These variations were mainly due to community composition shifts linked to seasonal phosphorus and temperature changes. PICT monitoring on a seasonal basis is required to monitor the mean tolerance of communities. PICT appeared to be a powerful tool that reflected the toxic effects on environmental communities and to monitor ecotoxic ecosystem restoration.

Comparison of specific versus literature species sensitivity distributions for herbicides risk assessment.

Species sensitivity distributions (SSDs) are an important predictive tool in risk assessment. Usually, literature data are used to build SSDs that are mostly based on planktonic species. But, to get adequate protective thresholds for environmental communities, one could argue that SSD should be built on ecotoxicological data obtained from species found in the ecosystem that should be protected. This is particularly true when benthic algae are of concern. Due to the lack of literature data, building SSD on benthic microalgae is difficult. This paper aims in comparing SSDs, and thus protective thresholds (hazardous concentration that affects 5% of the species of a community, HC5), built on ecotoxicological data obtained (1) from literature and (2) with specific bioassays on benthic diatoms from a lake. Thresholds were derived for protection against four herbicides separately and for a mixture of them. Sensitivity data obtained from literature were statistically lower than the specific data for all herbicides: Species tested in the literature were usually more sensitive (mainly chlorophytes), leading to more protective lower HC5. The HC5 thresholds (literature or specific) derived for protection against the mixture were also compared to the observed sensitivity of an assemblage of benthic diatom species exposed to an increasing range of herbicide mixture concentrations. We observed that one species within the assemblage (Fragilaria rumpens) was affected at a concentration below both the literature and the specific HC5 thresholds.

Critical issues in using the common mixture toxicity models concentration addition or response addition on species sensitivity distributions: a theoretical approach.

The risk of chemical mixtures to ecosystems is often assessed by applying the model of concentration addition or response addition combined with species sensitivity distribution (SSD) curves. Mixture effect predictions have been shown to be consistent only when these models are applied for a single species, however, and not with several species simultaneously aggregated to SSDs. The more stringent procedure for mixture risk assessment would hence be to apply first the concentration addition or response addition models to each species separately and, in a second step, to combine the results to construct an SSD for a mixture. Unfortunately, this methodology is not applicable in most cases because the large data sets it requires are usually unavailable. Based on theoretical data sets generated, the authors aimed to characterize the difference that can exist between these 2 methodologies. Results show that the use of concentration addition on SSD directly may lead to underestimations of the mixture concentration affecting 5% or 50% of species, especially when substances present a large standard deviation in ecotoxicity data constructing their SSD. The application of response addition can lead to over- or underestimations, depending mainly on the slope of the dose­response curves of the individual species. When assessing the risk of mixtures, one must therefore keep in mind this source of error when applying concentration addition or response addition to SSDs directly.

Risk of herbicide mixtures as a key parameter to explain phytoplankton fluctuation in a great lake: the case of Lake Geneva, Switzerland.

Mixture risk assessment predictions have rarely been confronted with biological changes observed in the environment. In this study, long-term monitoring of a European great lake, Lake Geneva, provides the opportunity to assess to what extent the predicted toxicity of herbicide mixtures explains the changes in the composition of the phytoplankton community next to other classical limnology parameters such as nutrients. To reach this goal, the gradient of the mixture toxicity of 14 herbicides regularly detected in the lake was calculated using concentration addition and response addition models. A temporal gradient of toxicity was observed which decreased from 2004 to 2009. Redundancy analysis and partial redundancy analysis showed that this gradient explains a significant portion of the variation in phytoplankton community composition with and without having removed the effect of all other co-variables. Moreover, species that are significantly influenced, positively or negatively, by the decrease of toxicity in the lake over time are highlighted. It can be concluded that the herbicide mixture toxicity is one of the key parameters to explain phytoplankton changes in Lake Geneva.