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International audience; A substantial honeybee decline is being observed worldwide. Agricultural intensification and loss of wild floral resources rank among the main factors contributing to this decline. Landscape enhancement of floral resources has been proposed as an agro-environmental scheme intended to provide honeybees with compensatory food sources in intensive agrosystems. Floral scheme efficiency has rarely been evaluated with respect to landscape context. In this study, we developed and validated a modeling tool to delineate the landscape areas likely to be associated with higher efficiency of floral enhancement schemes. In particular, the proximity of some landscape elements used by honeybees, either as foraging habitat or as visual landmark for orientation, may partly determine floral scheme efficiency. We investigated this issue using resource selection functions (RSFs), i.e. models that aim to predict the occurrence of foraging honeybees at floral patches as a function of the presence of keystone landscape elements in their proximity. However, deciding which landscape elements are effectively in the proximity or not is mostly a matter of subjectivity. The novelty of our approach resides in its use of a distance-weighting function to explicitly account for the spatial location of surrounding landscape elements. In that respect, a distance function should be scaled on movement patterns of foraging organisms. Herein, we inferred movement patterns from the autocorrelative properties of honeybee foraging activity. This modeling approach was developed on Phacelia (Phacelia tanacetifolia) field margin strips, a typical “honeybeefriendly” floral scheme. A foraging survey conducted on 170 Phacelia plots (2 m × 2 m) from 17 Phacelia strips, all positioned within the foraging range of an experimental apiary, revealed that (i) the floral scheme efficiency is positively influenced by the presence of linear landscape elements such as hedgerows and forest edges, but negatively affected by the presence of alternative floral resources, and that (ii) weighting the relative importance of those landscape elements by incorporating a distance function into models considerably improved their predictive power. This modeling tool has the potential to help land managers optimizing their financial investment by avoiding low-efficiency landscape areas, or favoring high-efficiency ones, at the time of planning floral enhancement schemes

Summary Avoiding toxins in food is as important as obtaining nutrition. Conditioned food aversions have been studied in animals as diverse as nematodes and humans [1, 2], but the neural signaling mechanisms underlying this form of learning have been difficult to pinpoint. Honeybees quickly learn to associate floral cues with food [3], a trait that makes them an excellent model organism for studying the neural mechanisms of learning and memory. Here we show that honeybees not only detect toxins but can also learn to associate odors with both the taste of toxins and the postingestive consequences of consuming them. We found that two distinct monoaminergic pathways mediate learned food aversions in the honeybee. As for other insect species conditioned with salt or electric shock reinforcers [4–7], learned avoidances of odors paired with bad-tasting toxins are mediated by dopamine. Our experiments are the first to identify a second, postingestive pathway for learned olfactory aversions that involves serotonin. This second pathway may represent an ancient mechanism for food aversion learning conserved across animal lineages., Highlights ► Learned food avoidances arise from two independent reinforcement pathways ► Detection of toxins requires the responses of multiple gustatory neurons ► Learned avoidance of odors associated with aversive taste involves dopamine ► Learned avoidance of odors associated with toxin ingestion involves serotonin

The purpose of this study is to investigate the possibility to use acetylcholinesterase (AChE) as a biomarker of exposure to deltamethrin insecticide in the honeybee, Apis mellifera and to test its reliability in the presence of other contaminants, as carbamate insecticide. Joined actions of deltamethrin (pyrethroid) and pirimicarb (carbamate), alone or in association, are investigated on AChE activity in surviving and dead honeybees, with a special focus on the relative proportions of its membrane and soluble forms. At the 0.5X dose (12.5 ng of deltamethrin and/or 2.5 microg of pirimicarb per bee), the residual tissue AChE activity in dead bees was 78% with deltamethrin, 43% with pirimicarb and 33% with dual treatment. In surviving bees, tissue AChE activity represented 250%, and 270% of control AChE activity with deltamethrin and dual treatment, respectively. The analysis of membrane and soluble AChE forms revealed an increase in the soluble form in dead bees after deltamethrin and dual treatment. However, in vitro investigations showed no direct interaction of deltamethrin on soluble and membrane AChE activity. The results suggest that the action of deltamethrin on AChE activity, in honeybee intact organisms, could be due to indirect mechanisms. The duality of AChE response to deltamethrin exposure, exhibited by the possibility of increase (surviving bees) or decrease (dead bees) of its activity has been pointed out for the first time. The important increase in AChE activity in response to deltamethrin, not altered by pirimicarb treatment, suggests that AChE activity could represent a robust biomarker specific to deltamethrin exposure in living bees.

Correspondance : jmcornuet@supagro.inra.fr; International audience; Varroa destructor is a parasitic mite of the Eastern honeybee Apis cerana. Fifty years ago, two distinct evolutionary lineages (Korean and Japanese) invaded the Western honeybee Apis mellifera. This haplo–diploid parasite species reproduces mainly through brother–sister matings, a system which largely favors the .xation of new mutations. In a worldwide sample of 225 individuals from 21 locations collected on Western honeybees and analyzed at 19 microsatellite loci, a series of de novo mutations was observed. Using historical data concerning the invasion, this original biological system has been exploited to compare three mutation models with allele size constraints for microsatellite markers: stepwise (SMM) and generalized (GSM) mutation models, and a model with mutation rate increasing exponentially with microsatellite length (ESM). Posterior probabilities of the three models have been estimated for each locus individually using reversible jump Markov Chain Monte Carlo. The relative support of each model varies widely among loci, but the GSM is the only model that always receives at least 9% support, whatever the locus. The analysis also provides robust estimates of mutation parameters for each locus and of the divergence time of the two invasive lineages (67,000 generations with a 90% credibility interval of 35,000–174,000). With an average of 10 generations per year, this divergence time .ts with the last post-glacial Korea–Japan land separation