The adverse effects of 158 pesticides to the Honey bee (Apis mellifera), the alfalfa leafcutting bee (Megachile rotundata) and the alkali bee (Nomia melanderi) were compared by means of various linear and non-linear multivariate analyses. A comparison exercise including the bumble bee (Bombus spp.) was also performed from a more restricted set of 32 pesticides. While no difference of sensitivity was found between A. mellifera and Bombus spp., M. rotundata appeared the most susceptible to pesticides followed by N. melanderi.

With the ever-growing number of xenobiotics that can potentially contaminate the environment, the determination of their mammalian toxicity is of prime importance. In this context, LD50 tests on rats and mice have been used for a long time to express the relative hazard associated with the acute toxicity of inorganic and organic chemicals. However, these laboratory tests encounter important hurdles. They are costly, time consuming and actively opposed by animal rights activists. Moreover, new legislation policies, such as REACH (Registration, Evaluation, Authorization and Restriction of Chemicals), aim at reducing the use of toxicity tests on vertebrates. Consequently, there is a need to find alternative methods for estimating the acute mammalian toxicity of chemicals. The quantitative structure–activity relationships (QSARs) and interspecies correlations appear particularly suited to reaching this goal. In this context, this paper reviews more than 150 models aiming at predicting rat and mouse LD50 values from molecular descriptors or (and) ecotoxicity data. The interest of these computational tools is discussed.

A number of xenobiotics by mimicking natural hormones can disrupt crucial functions in wildlife and humans. These chemicals termed endocrine disruptors are able to exert adverse effects through a variety of mechanisms. Fortunately, there is a growing interest in the study of these structurally diverse chemicals mainly through research programs based on in vitro and in vivo experimentations but also by means of SAR and QSAR models. The goal of our study was to retrieve from the literature all the papers dealing with structure-activity models on endocrine disruptor xenobiotics. A critical analysis of these models was made focusing our attention on the quality of the biological data, the significance of the molecular descriptors and the validity of the statistical tools used for deriving the models. The predictive power and domain of application of these models were also discussed.

Estimating exposure of wild birds to plant protection products is of key importance in the risk assessment process evaluating their harmful potential. In this paper, we propose an ecologically-relevant methodology to estimate potential exposure to active substances (ASs) of a farmland focal bird, the gray partridge Perdix perdix. It is based on bird habitat use of fields at the time of pesticide applications. It accounts for spatio-temporal heterogeneity at population and landscape scales. We identify and quantify the potential exposure to 179 ASs of 140 clutches during pre-laying, laying, and incubation phases, and of 75 coveys. The data come from a large scale field study combining radiotelemetry and a farmer survey. They were collected in 12 different representative sites. The proportion of clutches potentially exposed to a given chemical was ≥5% for 32 ASs; prothioconazole and epoxiconazole ranking first. 71% of clutches were potentially exposed to ≥1 AS and 67% to ≥2 ASs. Mixtures involved 2 to 22 ASs. They emerged from commercial formulations, tank mixtures, bird habitat use, and combinations. ASs were fungicides (53%), herbicides (25%), and insecticides (16%) used on a variety of crops in April-June, when ground-nesting birds are breeding. The European Food Safety Authority conclusions report a long-term first-tier toxicity-to-exposure ratio (TERlt) <5 for 11 out of 19 documented ASs, and higher-tier TERlt <5 for 5 out of 10 ASs. This suggests a potential risk for bird reproduction in farmlands. Globally 13% of coveys were potentially exposed to 18 ASs during the first month (1-4 coveys per AS). The use of our field data in future research and risk assessment is discussed.