Sampling and decision rules used by honey bees in a foraging arena

Environmental influences on for-mediated oviposition decisions in Drosophila melanogaster

Deciding whether or not to lay an egg on a given substrate is an important task undertaken by females of many arthropods. It involves perceiving the environment (e.g. quality of the substrate, temperature, and humidity), formulating a decision, and then conducting the appropriate behaviours to oviposit. This oviposition site selection (OSS) provides a useful system for studying simple decision-making. OSS in fruit flies, Drosophila melanogaster, is influenced by both genetic and environmental variation. Naturally occurring allelic variation in the foraging gene (for) is known to affect OSS. Given a choice of high- and low-nutrient oviposition substrates, groups of rovers (for^R) are known to lay significantly more of their eggs on low-nutrient sites than sitters (for^s) and sitter mutants (for^s2). Here we ask three questions: (1) Is the role of for in OSS affected by the availability of alternate oviposition sites? (2) Is the role of for in OSS sensitive to the density of ovipositing females? and (3) Does the gustatory sensation of yeast play a role in for-mediated variation in OSS? We find a role of choice and female density in rover/sitter differences in OSS, as well as a role of for in response to glycerol, an indicator of yeast. The role of for in OSS decision-making is complex and multi-faceted and should prove fertile ground for further research into the factors affecting decision-making behaviours.

Reward foraging task and model-based analysis reveal how fruit flies learn value of available options

Foraging animals have to evaluate, compare and select food patches in order to increase their fitness. Understanding what drives foraging decisions requires careful manipulation of the value of alternative options while monitoring animals choices. Value-based decision-making tasks in combination with formal learning models have provided both an experimental and theoretical framework to study foraging decisions in lab settings. While these approaches were successfully used in the past to understand what drives choices in mammals, very little work has been done on fruit flies. This is despite the fact that fruit flies have served as model organism for many complex behavioural paradigms. To fill this gap we developed a single-animal, trial-based decision making task, where freely walking flies experienced optogenetic sugar-receptor neuron stimulation. We controlled the value of available options by manipulating the probabilities of optogenetic stimulation. We show that flies integrate reward history of chosen options and forget value of unchosen options. We further discover that flies assign higher values to rewards experienced early in the behavioural session, consistent with formal reinforcement learning models. Finally, we also show that the probabilistic rewards affect walking trajectories of flies, suggesting that accumulated value is controlling the navigation vector of flies in a graded fashion. These findings establish the fruit fly as a model organism to explore the genetic and circuit basis of reward foraging decisions.

Functional Gustatory Role of Chemoreceptors in Drosophila Wings

Neuroanatomical evidence argues for the presence of taste sensilla in Drosophila wings; however, the taste physiology of insect wings remains hypothetical, and a comprehensive link to mechanical functions, such as flight, wing flapping, and grooming, is lacking. Our data show that the sensilla of the Drosophila anterior wing margin respond to both sweet and bitter molecules through an increase in cytosolic Ca(2+) levels. Conversely, genetically modified flies presenting a wing-specific reduction in chemosensory cells show severe defects in both wing taste signaling and the exploratory guidance associated with chemodetection. In Drosophila, the chemodetection machinery includes mechanical grooming, which facilitates the contact between tastants and wing chemoreceptors, and the vibrations of flapping wings that nebulize volatile molecules as carboxylic acids. Together, these data demonstrate that the Drosophila wing chemosensory sensilla are a functional taste organ and that they may have a role in the exploration of ecological niches.

Honey Bee Location- and Time-Linked Memory Use in Novel Foraging Situations: Floral Color Dependency

Learning facilitates behavioral plasticity, leading to higher success rates when foraging. However, memory is of decreasing value with changes brought about by moving to novel resource locations or activity at different times of the day. These premises suggest a foraging model with location- and time-linked memory. Thus, each problem is novel, and selection should favor a maximum likelihood approach to achieve energy maximization results. Alternatively, information is potentially always applicable. This premise suggests a different foraging model, one where initial decisions should be based on previous learning regardless of the foraging site or time. Under this second model, no problem is considered novel, and selection should favor a Bayesian or pseudo-Bayesian approach to achieve energy maximization results. We tested these two models by offering honey bees a learning situation at one location in the morning, where nectar rewards differed between flower colors, and examined their behavior at a second location in the afternoon where rewards did not differ between flower colors. Both blue-yellow and blue-white dimorphic flower patches were used. Information learned in the morning was clearly used in the afternoon at a new foraging site. Memory was not location-time restricted in terms of use when visiting either flower color dimorphism.

Selenium accumulation in flowers and its effects on pollination

• Selenium (Se) hyperaccumulation has a profound effect on plant-arthropod interactions. Here, we investigated floral Se distribution and speciation in flowers and the effects of floral Se on pollen quality and plant-pollinator interactions. • Floral Se distribution and speciation were compared in Stanleya pinnata, an Se hyperaccumulator, and Brassica juncea, a comparable nonhyperaccumulator. Pollen germination was measured from plants grown with varying concentrations of Se and floral visitation was compared between plants with high and low Se. • Stanleya pinnata preferentially allocated Se to flowers, as nontoxic methyl-selenocysteine (MeSeCys). Brassica juncea had higher Se concentrations in leaves than flowers, and a lower fraction of MeSeCys. For B. juncea, high floral Se concentration impaired pollen germination; in S. pinnata Se had no effect on pollen germination. Floral visitors collected from Se-rich S. pinnata contained up to 270 μg g(-1), concentrations toxic to many herbivores. Indeed, floral visitors showed no visitation preference between high- and low-Se plants. Honey from seleniferous areas contained 0.4-1 μg Se g(-1), concentrations that could provide human health benefits. • This study is the first to shed light on the possible evolutionary cost, through decreased pollen germination in B. juncea, of Se accumulation and has implications for the management of seleniferous areas.

Decision-making under uncertainty: biases and Bayesians

Animals (including humans) often face circumstances in which the best choice of action is not certain. Environmental cues may be ambiguous, and choices may be risky. This paper reviews the theoretical side of decision-making under uncertainty, particularly with regard to unknown risk (ambiguity). We use simple models to show that, irrespective of pay-offs, whether it is optimal to bias probability estimates depends upon how those estimates have been generated. In particular, if estimates have been calculated in a Bayesian framework with a sensible prior, it is best to use unbiased estimates. We review the extent of evidence for and against viewing animals (including humans) as Bayesian decision-makers. We pay particular attention to the Ellsberg Paradox, a classic result from experimental economics, in which human subjects appear to deviate from optimal decision-making by demonstrating an apparent aversion to ambiguity in a choice between two options with equal expected rewards. The paradox initially seems to be an example where decision-making estimates are biased relative to the Bayesian optimum. We discuss the extent to which the Bayesian paradigm might be applied to the evolution of decision-makers and how the Ellsberg Paradox may, with a deeper understanding, be resolved.