Monitoring the abundance of flying insects and atmospheric conditions during a 9-month campaign using an entomological optical sensor

Abstract

Monitoring the dynamics of insect populations is key to assessing the impact of human activities on insect populations. However, traditional methodologies relying on physical traps have inherent limitations in accurately monitoring insect abundance. Here, we present findings from a 9-month campaign conducted in New Jersey, USA, utilizing a near-infrared optical sensor known as eBoss. From April to December 2022, the eBoss derived the aerial density (insect/m³) and biomass density (mg/m³) with a 1-min resolution from a total of 302,093 insect observations. The data collected were analyzed in relation to air temperature, relative humidity, and wind speed. The results revealed that the abundance of flying insects exhibited an initial increase from April to June, reaching a peak of 0.094 insect/m³ and 1.34 mg/m³, followed by a subsequent decline towards the end of the year. Our investigation showed a surge in insect abundance above 12.5 °C, with particularly high levels observed between 19 and 31 °C. The impact of relative humidity and wind speed on insect populations was also explored. Overall, this campaign demonstrated the efficacy of photonic sensors in gathering novel and extensive data for the field of entomology, paving the way for improved understanding and management of insect populations.

Figure 1

Optical layout of the eBoss deployed during the 2022 field campaign.

Figure 2

Spatial beam profile of the laser beam (x-axis).

Figure 3

Typical signal recorded by the eBoss when an insect transits through the laser beam. The sharp drops in signal are caused by the rapid movement of the wings during the duration of the transit.

Figure 4

Aerial and biomass densities (A and B), and daily temperature and relative humidity (C).

Figure 5

Aerial (A), biomass density (B) and temperature (C) as a function of date and time of day (EST, UTC-05:00) with a 1-min time resolution. White color indicates times when the eBoss was not operating, grey lines indicate the sunrise and sunset time.

Figure 6

(A) Average aerial and biomass densities as a function of temperature (0.5 °C temperature interval). (B) Average aerial density as a function of wind speed (1 km\h interval). (C and D) Average aerial and biomass density as a function of temperature and relative humidity (0.5 °C and 1% intervals respectively), white color represents the absence of recorded data.