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Using a conditioned proboscis extension response (PER) assay, honeybees (Apis mellifera L.) can be trained to associate an odor stimulus with a sucrose reward. Previous studies have shown that observations of conditioned PER were of interest for assessing the behavioral effects of pesticides on the honeybee. In the present study, the effects of sublethal concentrations of nine pesticides on learning performances of worker bees subjected to the PER assay were estimated and compared. Pesticides were tested at three concentrations. The highest concentration of each pesticide corresponded to the median lethal dose value (48-h oral LD50), received per bee and per day, divided by 20. Reduced learning performances were observed for bees surviving treatment with fipronil, deltamethrin, endosulfan, and prochloraz. A lack of behavioral effects after treatment with lambda-cyalothrin, cypermethrin, tau-fluvalinate, triazamate, and dimethoate was recorded. No-observed-effect concentrations (NOECs) for the conditioned PER were derived for the studied pesticides. Our study shows that the PER assay can be used for estimating sublethal effects of pesticides on bees. Furthermore, comparisons of sensitivity as well as the estimation of NOECs, useful for regulatory purposes, are possible.

T his chapter reviews the available data on the toxicity of neonicotinoid insecticides to bees that are the prominent and the most economically important group of pollinators worldwide. Classical and new methods developed to take into account the characteristics and different types of effects of the neonicotinoid insecticides to bees are described. The available toxicity results are critically analyzed. Thus, the nitro-substituted compounds (clothianidin, dinotefuran, imidacloprid and its metabolites, thiamethoxam, nitenpyram) appear the most toxic to bees. The cyano-substituted neonicotinoids seem to exhibit a much lower toxicity (acetamiprid and thiacloprid). The chapter ends with suggestions for additional studies aiming at better assess the hazard of this important insecticide family to bees.

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Losses of foraging bees are sometimes attributed to altered flight pattern between a meliferous plant treated with an insecticide and the hive. Only a limited number of studies has investigated the impact of pesticides on homing flight due to the difficulty of measuring the flight time between the food source and the hive. Monitoring the flights of the foraging bees needs their individual identification. The number of bees monitored simultaneously and the time span during which observations can be made limit most of the monitoring techniques. However, techniques of automatic tracking and identification of individuals have the potential to revolutionize the study of the ecotoxicological effects of xenobiotics on the bee behaviors. Radio Frequency Identification (RFID) offer numerous advantages such as an unlimited number of codes, a large number of simultaneous recording, and a quick reading, especially through materials (e.g., wood). The aim of this study was to show how the RFID device can be used to study the effects of pesticides on both the behavioral traits and the lifespan of bees. In this context, we have developed a method under tunnel to automatically record the displacements of foragers individualized with RFID tags and to detect the alteration of the flight pattern between an artificial feeder and the hive. Fipronil was selected as test substance due to the lack of information on the effects of this insecticide on the foraging behavior of free-flying bees. We showed that oral treatment of 0.3 ng of fipronil per bee (LD50/20) reduced the number of foraging trips. The strengths of our approach were briefly discussed.

The log-log relationship between the bioconcentration tendency of organic chemicals in fish and the n -octanol/water partition coefficients breaks down for very hydrophobic compounds. The use of parabolic and bilinear models allows this problem to be overcome. The QSAR equation log BCF = 0.910 log P - 1.975 log (6.8 10(-7) P + 1) - 0.786 (n = 154; r = 0.950; s = 0.347; F = 463.51) was found to be a good predictor of bioconcentration in fish.

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