RL2. Evaluation of the effects of the contaminants on the organisms and their functions

  • Biomarkers/bioindicators. Biomarkers and biological tests have been developed on i) oligochetes (earthworms and enchytraeids), from sub-individual to population level and ii) microorganisms, mainly at the community level. These organisms are deeply involved in soil functions (i.e. organic matter turnover, biogeochemical and nutrient cycles), and thus being relevant ecological and ecotoxicological models. Various endpoints have been investigated in relation with biochemical and cellular state and also their growth, behavior and activities. The importance of using representative species in ecotoxicological tests of pesticides have been underlined, due to significant differences in sensitivity to pesticides among earthworm species (Pelosi et al., 2013, 2014, 201;, Rombke et al., 2017). The observed difference in sensitivity can be explained by different ecological traits, relating to feeding activity and behavior that could influence the route of exposure to contaminants.
    Individual scale cannot be applied to the soil microbial compartment, while microorganisms provide numerous soil functions and have short-term response to environmental changes. Several indicators of the soil quality were thus developed in a specific or generic way through descriptive approaches. In order to have proxies of these functions, bioassay based on enzymatic activities of the whole soil or specific microbial groups were chosen and developed. However, in an ecotoxicological point of view, many microbial or enzymatic activities were poorly specific or sensitive to the contamination, being poorly robust to confounding factors (i.e. organic matter content or soil pH) and they are supported by a wild diversity of microorganisms (high functional redundancy). Thus for more specific concerns about exposure of the microbial communities to contaminants, the PICT approach have been developed due to the specificity of underlying mechanisms of response to a class of contaminant (i.e. community tolerance acquisition). It appeared as a suitable tool to highlight long term effect or recurrent exposure to a given contaminant. We developed several microbial bioassays with different endpoints depending on the contaminants and its modes of action (i.e soil algae assay for herbicides, nitrification assay for metals and antibiotics, Crouzet and Berard, 2017). A main result in relation with organic waste recycling showed no impact of ABs and TE on soil microbial communities, in long term field experiments (CEMABS project). 
  • Long-term relationship fate-exposition-effect. We worked on the long-term effects where the residual but ongoing exposition to contaminants is hypothesized to decrease with time until sublethal levels of bioavailable contaminants for organisms. Confounding factors are thus expected to have greater importance. In such context, we showed that the classical indicators based on the concept of toxicity are not adapted because not enough robust to confounding factors, little sensitive showing no effect, and non-pertinent to integrate the adaptation capacity of the organisms and the communities (change in the community structures associated or not to functional redundancy). In the field and at the scale of the microbial community, the application of the PICT concept allowed to assess that chronical low doses exposition of one contaminant induced a functional tolerance that could be assessed in the laboratory (CEMABS project). Results are consistent with the fact that even on the long-term selection pressure does exist and that the contaminant is still bioavailable while no effects can be simply shown.
fig 20

Figure 20. Log ratio of LC50 (species s vs.

E. fetida fetida (●)or E. fetida andrei (o)) for: (a) all

species, (b) s = L. terrestris, (c) s = A. caliginosa,

and (d) s = L. rubellus. The error bars correspond

to the 95% confidence intervals computed either

from the LC50 standard deviations reported by

the authors when available (6 pubs) or from the

highest LC50 standard deviation (9 pubs).

  • Choice of biological models and observation in natura: A large work was done to better evaluate the relevance of our ecological  models used  in ecotoxicology. More specifically, we evaluated both the sensitivity of ubiquitous earthworms found in agricultural soils compared to those used in homologation tests (Pelosi et al., 2013), and the interest of using Enchytraeids as bioindicators of anthropic disturbances or practices of agricultural management (Pelosi and Römbke, 201;, Römbke et al., 2017) (Fig. 20). We were also interested in producing data evaluating the differences in sensitivity to various contaminants between earthworms and Enchytraeids, at the biological scale of population and communities, issued from comparisons of observations in the field and ex situ (Bart et al., 2017; Amossé et al., 2018, ANSES project). We also initiated studies at the spatial scale of landscapes to assess the impact of semi-natural vegetation features on the transfer of pesticides and the related accumulation in various compartments linked to the food chain including soil, earthworms, carabidaes and micromammals) (RESCAPE and PING projects; Bertrand and Pelosi, 2017).
  • Modeling and risk assessment. In order to evaluate the impact of contaminants on the ecological functions fulfilled by earthworms, i.e. the non-intentional effects on contaminants, we adopted a strategy aiming at conducting in parallel laboratory and field experiments. These experiments were used to acquire data on the life cycle of the chosen earthworm and compute a bioenergetic model in the absence then in the presence of contaminant (Bart et al., 2017; 2018). New data, especially in terrestrial ecotoxicology were thus obtained on impact of pesticides on the reproduction and on the health of the following generations, as well as the influence of the age of the earthworm when exposed. The data are then used to parametrize a biological model coupled to a toxicocinetic-toxicodynamic model that will give access to the impact on specific ecological functions linked for example to the C or N cycles (ANSES project).

Modification date: 06 July 2023 | Publication date: 28 September 2018 | By: Sophie Formisano