measuring-flight-ability-ambrosia-beetle-platypus-quercivorus

Measuring the Flight Ability of the Ambrosia Beetle, <em>Platypus Quercivorus</em> (Murayama), Using a Low-Cost, Small, and Easily Constructed Flight Mill

The ambrosia beetle, Platypus quercivorus (Murayama), is the vector of a fungal pathogen that causes mass mortality of Fagaceae trees (Japanese oak wilt). ...

The honeybee can control its hive environment to survive drastic changes in the field environment. To study the control of multiple environmental factors by honeybees, in this experiment, we developed a continual and simultaneous monitoring system for the temperature, moisture, and carbon dioxide (CO2) concentration in a honeybee hive. Changes in hive weight, CO2 production rate, and honeybee behavior were also monitored to estimate energy costs and behavioral activity for the environmental regulation. Measurements were conducted in August 2008. We found that the honeybee hive has a microclimate different from the ambient climate, and that the difference was partly accompanied by changes in honeybee activity. Our results also suggest that hive temperature, humidity, and CO2 concentrations are controlled by different mechanisms. Additional monitoring of the hive environment and honeybee behavior for longer periods would enable us to understand the mechanisms of environmental control by honeybees, which is one of the behaviors that define honeybees as social insects.

Observation system for the control of the hive environment by the honeybee (Apis mellifera).

A computer program that tracks animal behavior, thereby revealing various features and mechanisms of social animals, is a powerful tool in ethological research. Because honeybee colonies are populated by thousands of bees, individuals co-exist in high physical densities and are difficult to track unless specifically tagged, which can affect behavior. In addition, honeybees react to light and recordings must be made under special red-light conditions, which the eyes of bees perceive as darkness. The resulting video images are scarcely distinguishable. We have developed a new algorithm, K-Track, for tracking numerous bees in a flat laboratory arena. Our program implements three main processes: (A) The object (bee's) region is detected by simple threshold processing on gray scale images, (B) Individuals are identified by size, shape and spatiotemporal positional changes, and (C) Centers of mass of identified individuals are connected through all movie frames to yield individual behavioral trajectories. The tracking performance of our software was evaluated on movies of mobile multi-artificial agents and of 16 bees walking around a circular arena. K-Track accurately traced the trajectories of both artificial agents and bees. In the latter case, K-track outperformed Ctrax, well-known software for tracking multiple animals. To investigate interaction events in detail, we manually identified five interaction categories; 'crossing', 'touching', 'passing', 'overlapping' and 'waiting', and examined the extent to which the models accurately identified these categories from bee's interactions. All 7 identified failures occurred near a wall at the outer edge of the arena. Finally, K-Track and Ctrax successfully tracked 77 and 60 of 84 recorded interactive events, respectively. K-Track identified multiple bees on a flat surface and tracked their speed changes and encounters with other bees, with good performance. 

Development of a new method to track multiple honey bees with complex behaviors on a flat laboratory arena.

The honeybee waggle dance communicates the location of profitable food sources, usually with a certain degree of error in the directional information ranging from 10-15° at the lower margin. We simulated one-day colonial foraging to address the biological significance of information error in the waggle dance. When the error was 30° or larger, the waggle dance was not beneficial. If the error was 15°, the waggle dance was beneficial when the food sources were scarce. When the error was 10° or smaller, the waggle dance was beneficial under all the conditions tested. Our simulation also showed that precise information (0-5° error) yielded great success in finding feeders, but also caused failures at finding new feeders, i.e., a high-risk high-return strategy. The observation that actual bees perform the waggle dance with an error of 10-15° might reflect, at least in part, the maintenance of a successful yet risky foraging trade-off. 

Article	Year
Observation system for the control of the hive environment by the honeybee (Apis mellifera). Behavior research methods\| PubMed ID: 19587192	2009
Development of a new method to track multiple honey bees with complex behaviors on a flat laboratory arena. PloS one\| PubMed ID: 24465422	2014
Error in the honeybee waggle dance improves foraging flexibility. Scientific reports\| PubMed ID: 24569525	2014

Ryuichi Okada

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