Insect biomass density: measurement of seasonal and daily variations using an entomological optical sensor

Temperature Dependency of Insect's Wingbeat Frequencies: An Empirical Approach to Temperature Correction

This study examines the relationship between the wingbeat frequency of flying insects and ambient temperature, leveraging data from over 302,000 insect observations obtained using a near-infrared optical sensor during an eight-month field experiment. By measuring the wingbeat frequency as well as wing and body optical cross-sections of each insect in conjunction with the ambient temperature, we identified five clusters of insects and analyzed how their average wingbeat frequencies evolved over temperatures ranging from 10 °C to 38 °C. Our findings reveal a positive correlation between temperature and wingbeat frequency, with a more pronounced increase observed at higher wingbeat frequencies. Frequencies increased on average by 2.02 Hz/°C at 50 Hz, and up to 9.63 Hz/°C at 525 Hz, and a general model is proposed. This model offers a valuable tool for correcting wingbeat frequencies with temperature, enhancing the accuracy of insect clustering by optical and acoustic sensors. While this approach does not account for species-specific responses to temperature changes, our research provides a general insight, based on all species present during the field experiment, into the intricate dynamics of insect flight behavior in relation to environmental factors.

Shifts in population density centers of a hibernating mammal driven by conflicting effects of climate change and disease

Populations wax and wane over time in response to an organism's interactions with abiotic and biotic forces. Numerous studies demonstrate that fluctuations in local populations can lead to shifts in relative population densities across the geographic range of a species over time. Fewer studies attempt to disentangle the causes of such shifts. Over four decades (1983-2022), we monitored populations of hibernating Indiana bats (Myotis sodalis) in two areas separated by ~110 km. The number of bats hibernating in the northern area increased from 1983 to 2011, while populations in the southern area remained relatively constant. We used simulation models and long-term weather data to demonstrate the duration of time bats must rely on stored fat during hibernation has decreased in both areas over that period, but at a faster rate in the northern area. Likewise, increasing autumn and spring temperatures shortened the periods of sporadic prey (flying insect) availability at the beginning and end of hibernation. Climate change thus increased the viability of northern hibernacula for an increasing number of bats by decreasing energetic costs of hibernation. Then in 2011, white-nose syndrome (WNS), a disease of hibernating bats that increases energetic costs of hibernation, was detected in the area. From 2011 to 2022, the population rapidly decreased in the northern area and increased in the southern area, completely reversing the northerly shift in population densities associated with climate change. Energy balance during hibernation is the singular link explaining the northerly shift under a changing climate and the southerly shift in response to a novel disease. Continued population persistence suggests that bats may mitigate many impacts of WNS by hibernating farther south, where insects are available longer each year.

Discrimination of Hover Fly Species and Sexes by Wing Interference Signals

Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin-film wing interference signals (WISs) can discriminate free-flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave-infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS-based surveillance is therefore a potent tool for remote insect identification and surveillance.

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

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.