Continuous monitoring of aerial density and circadian rhythms of flying insects in a semi-urban environment

Abstract

Although small in size, insects are a quintessential part of terrestrial ecosystems due to their large number and diversity. While captured insects can be thoroughly studied in laboratory conditions, their population dynamics and abundance in the wild remain largely unknown due to the lack of accurate methodologies to count them. Here, we present the results of a field experiment where the activity of insects has been monitored continuously over 3 months using an entomological stand-off optical sensor (ESOS). Because its near-infrared laser is imperceptible to insects, the instrument provides an unbiased and absolute measurement of the aerial density (flying insect/m3) with a temporal resolution down to the minute. Multiple clusters of insects are differentiated based on their wingbeat frequency and ratios between wing and body optical cross-sections. The collected data allowed for the study of the circadian rhythm and daily activities as well as the aerial density dynamic over the whole campaign for each cluster individually. These measurements have been compared with traps for validation of this new methodology. We believe that this new type of data can unlock many of the current limitations in the collection of entomological data, especially when studying the population dynamics of insects with large impacts on our society, such as pollinators or vectors of infectious diseases.

Fig 1. Aerial view of the experiment location (40°47’09.8"N 74°03’28.1"W) and its surroundings, the US Northeast megalopolis (Manhattan Island top right corner).

The ESOS system and the co-located weather station are symbolized by a black marker. The position of the CDC light traps used for comparison are indicated by a red marker. Image courtesy of NASA’s Earth Observatory, NASA/GSFC/MITI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team.

Fig 2. Optical layout of the entomological stand-off optical sensor (ESOS).

Fig 3

Examples of insect signals as they transit through the laser beam of the ESOS system (A and B) along with their frequency analysis through fast Fourier transform (C and D).

Fig 4

Relative aerial density per bin of temperature and wingbeat frequency (A) along with the wingbeat frequency distribution for two ranges of temperature, 22 to 26°C and 8 to 12°C (respectively B and C). On figure A the aerial density was rescaled from 0 to 1, for each temperature bin by normalizing with the maximal value in order to emphasize local maximums. Black lines represent the linear fit of local maximal for each of the four insects cluster, illustrating the drift of the wingbeat frequency with the temperature.

Fig 5

Distribution of the wingbeat frequency corrected in temperature (A) with four Gaussian fits corresponding to each insect cluster, and the total reconstructed gaussian fit (dashed black line). Average transit time in function of the wingbeat frequency (B), the different cluster range are displayed, and their mean transit time indicated. Aerial density per bin of wing to body ratio and wingbeat frequency (C), the boundaries of the four insect clusters C1 to C4 are indicted by white lines. Distribution of the wing to body ratio separated per cluster (D).

Fig 6

Typical circadian rhythm for cluster C1, C2, C3 and C4 (respectively A, B, C and D). The dotted line displays the UV radiation measured on the field which relates to the sun activity. The aerial density is the one hour sliding average over 14 consecutive days of measurements.

Fig 7. Peaks of mosquito activity (Cluster C4) near sunset (orange stars) and sunrise (purple diamond) in relation with the actual sunset (blue plus) and sunrise (yellow disk) time.

Fig 8

Evolution of the aerial density for clusters C1, C2, C3 and C4 (respectively A, B, C and D) over the 80 days of the measurement campaign. Figure D also displays the normalized trap count (red dashed) of nearby traps for comparison purposes.