Visual search and decision making in bees: time, speed and accuracy

An insect searching a meadow for flowers may detect several flowers from different species per second, so the task of choosing the right flowers rapidly is not trivial. Here we apply concepts from the field of visual search in human experimental psychology to the task a bee faces in searching a meadow for familiar flowers, and avoiding ‘‘distraction’’ by unknown or unrewarding flowers. Our approach highlights the importance of visual information processing for understanding the behavioral ecology of foraging. Intensity of illuminating light, target contrast with background (both chromatic and achromatic), and number of distractors are all shown to have a direct influence on decision times in behavioral choice experiments. To a considerable extent, the observed search behavior can be explained by the temporal and spatial properties of neuronal circuits underlying visual object detection. Our results also emphasize the importance of the time dimension in decision making. During visual search in humans, improved accuracy in solving discrimination tasks comes at a cost in response time, but the vast majority of studies on decision making in animals have focused on choice accuracy, not speed. We show that in behavioral choice experiments in bees, there is a tight link between the two. We demonstrate both between-individual and within- individual speed-accuracy tradeoffs, whereby bees exhibit considerable behavioral flexibility in solving visual search tasks. Motivation is an important factor in selection of behavioral strategies for a search task, and sensory discrimination capabilities may be underestimated by studies that quantify accuracy of behavioral choice but neglect the temporal dimension

Does quantity matter to a stingless bee?

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Application of Sunlight Mapping in Solar Car Design

The design of a solar car is a combination of trade-offs between the mechanical, aerodynamic, and photovoltaic systems. The mechanical and aerodynamic systems can be computationally modeled very well using commercial software. Clouds prevent the photovoltaic system from being modeled as well. This research explores a new way to accurately simulate almost every array configuration imaginable. Using this method, quantitative simulations are produced

Caution with colour calculations:Spectral purity is a poor descriptor of flower colour visibility

BACKGROUND: The colours of flowers are of key interest to plant and pollination biologists. An increasing number of studies investigates the importance of saturation of flower colours (often called "spectral purity" or "chroma") for visibility to pollinators, but the conceptual, physiological and behavioural foundations for these metrics as well as used calculations rest on slender foundations. METHODS: We discuss the caveats of colour attributes that are derived from human perception, and in particular spectral purity and chroma, as variables in flower colour analysis. We reanalysed seven published datasets encompassing 774 measured reflectance spectra to test for correlations between colour contrast, spectral purity and chroma. MAIN FINDINGS AND CONCLUSIONS: We identify several concerns with common calculation procedures in animal colour spaces. Studies on animal colour vision provide no ground to assume that any pollinator perceives (or responds to) saturation, chroma or spectral purity in the way humans do. A reanalysis of published datasets revealed that values for colour contrast between flowers and their background is highly correlated with measures for spectral purity and chroma, which invalidates treating these factors as independent variables as is currently commonplace. Strikingly, spectral purity and chroma - which both are metrics for saturation and are often used synonymously - are not correlated at all. We conclude that alternative, behaviourally validated metrics for the visibility of flowers to pollinators, such as colour contrast and achromatic contrast, are better in understanding the role of flower colour in plant-pollinator signalling

Adaptation, constraint, and chance in the evolution of flower color and pollinator color vision

Publisher version available from: http://www.cambridge.org/gb/knowledge/isbn/item5706557/Cognitive%20Ecology%20of%20Pollination/?site_locale=en_G

Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris

Strube-Bloss M, Brown A, Spaethe J, Schmitt T, Rössler W. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris. PLOS ONE. 2015;10(9): e0137413