Heading variations resolve the heading-direction ambiguity in vertical-beam radar observations of insect migration

Vertical-beam entomological radars provide precise measurements of the body alignment of individual overflying insects but are unable to distinguish which of the two axial directions the insect is heading towards. Insects migrating at altitude typically show common alignment, although with a broad spread. We show here that when observations from multiple individual insects are available, and the insects have airspeeds of about 2 ms–1 or greater, the spread in heading directions allows the heading ambiguity to be resolved (though at the sample rather than the individual level). A vector analysis of radar-measured track direction, track speed, and heading will provide consistent results for all the insects in a sample only when the heading direction is chosen correctly. With the heading then resolved, the analysis can continue to estimation of representative values for the airspeed of the insects in the sample and for the speed and direction of the wind they were flying in. This general approach can be implemented in two different ways, which we term the ‘cluster’ and ‘projection’ methods. When applied to an intense migration of large insects, probably moths, these methods produced highly consistent results from hour to hour and from one 150 m height interval to the next. Simulations show that the methods are not liable to directional bias and reveal when they are rendered ineffective by small sample sizes or low insect airspeeds; they also indicate that the cluster method handles small sample sizes better than the projection method, and its use is therefore recommended. A comparison with two previously proposed methods that use meteorological data to resolve the ambiguity shows that the new methods are more reliable. Use of this objective means of resolving the heading ambiguity will increase confidence in radar-based studies of the orientation behaviour of insect migrants and their responses to cues like sky illumination patterns, the Earth’s magnetic field, and wind.