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Lack of tools for detailed, real-time observation of mosquito behavior with high spatio-temporal resolution limits progress towards improved malaria vector control. We deployed a high-resolution entomological lidar to monitor a half-kilometer static transect positioned over rice fields outside a Tanzanian village. A quarter of a million in situ insect observations were classified, and several insect taxa were identified based on their modulation signatures. We observed distinct range distributions of male and female mosquitoes in relation to the village periphery, and spatio-temporal behavioral features, such as swarming. Furthermore, we observed that the spatial distributions of males and females change independently of each other during the day, and were able to estimate the daily dispersal of mosquitoes towards and away from the village. The findings of this study demonstrate how lidar-based monitoring could dramatically improve our understanding of malaria vector ecology and control options. [ABSTRACT FROM AUTHOR]

The article demonstrates in situ lidar classification of several insect families and their sexes based on their modulation signatures. It observed an increased insect activity during the eclipse attributable to mosquitoes, along with demonstrate how lidar-based monitoring of distinct mosquito activities could advance the understanding of vector ecology.

• We recorded a large number of insect signals using a novel photonic sensor, to create a library of known species. • We used the recorded insect signals to evaluate two different clustering algorithms to quantify species richness. • Richness estimates were correlated between sensors and conventional traps. To mitigate ongoing insect biodiversity declines, there is a need for efficient yet accurate monitoring methods. The use of traditional catch-based survey methods is constrained both by costs and need for expertise for manual taxonomic identification. Emerging methods, such as eDNA and robotic sorting, have the potential to reduce workload but still require resource-intensive sample collection in the field. Recently, remote sensing methods such as photonic sensors have shown promise for recording large numbers of insect observations. However, accurately determining species composition in collected data remains a challenge. In this study, we investigated the potential of photonic sensors for quantifying species richness of flying insects in the field and at five sites and compared the results with estimates based on conventional Malaise traps. Firstly, we evaluated two unsupervised clustering methods using a library of measured insect signals from 42 known species. Secondly, we correlated estimated number of clusters in data recorded at five sites with species richness assessment of catches from Malaise traps. This study is based on 84,770 library- and 238,584 field individual insect recordings. Our results demonstrate that both clustering methods perform well and reflect estimates obtained by Malaise traps, indicating the potential of automated insect biodiversity monitoring. This offers the possibility of more efficient but still accurate methods for studying insect biodiversity with broader temporal and spatial coverage. [ABSTRACT FROM AUTHOR]

Abstract: Despite numerous studies of selection on position and number of spectral vision bands, explanations to the function of narrow spectral bands are lacking. We investigate dragonflies (Odonata), which have the narrowest spectral bands reported, in order to investigate what features these narrow spectral bands may be used to perceive. We address whether it is likely that narrow red bands can be used to identify conspecifics by the optical signature from wing interference patterns (WIPs). We investigate the optical signatures of Odonata wings using hyperspectral imaging, laser profiling, ellipsometry, polarimetric modulation spectroscopy, and laser radar experiments. Based on results, we estimate the prospects for Odonata perception of WIPs to identify conspecifics in the spectral, spatial, intensity, polarization, angular, and temporal domains. We find six lines of evidence consistent with an ability to perceive WIPs. First, the wing membrane thickness of the studied Odonata is 2.3 μm, coinciding with the maximal thickness perceivable by the reported bandwidth. Second, flat wings imply that WIPs persist from whole wings, which can be seen at a distance. Third, WIPs constitute a major brightness in the visual environment only second after the solar disk. Fourth, WIPs exhibit high degree of polarization and polarization vision coincides with frontal narrow red bands in Odonata. Fifth, the angular light incidence on the Odonata composite eye provides all prerequisites for direct assessment of the refractive index which is associated with age. Sixth, WIPs from conspecifics in flight make a significant contribution even to the fundamental wingbeat frequency within the flicker fusion bandwidth of Odonata vision. We conclude that it is likely that WIPs can be perceived by the narrow red bands found in some Odonata species and propose future behavioral and electrophysiological tests of this hypothesis. [ABSTRACT FROM AUTHOR]

Identifying flying insects is a significant challenge for biologists. Entomological lidar offers a unique solution, enabling rapid identification and classification in field settings. No other method can match its speed and efficiency in identifying insects in flight. This non-intrusive tool is invaluable for assessing insect biodiversity, informing conservation planning, and evaluating efforts to address declining insect populations. Although the species richness of co-existing insects can reach tens of thousands, current photonic sensors and lidars can differentiate roughly one hundred signal types. While the retrieved number of clusters correlate with Malaise trap diversity estimates, this taxonomic specificity, the number of discernible signal types is currently limited by instrumentation and algorithm sophistication. In this study, we report 32,533 observations of wild flying insects along a 500-meter transect. We report the benefits of lidar polarization bands for differentiating species and compare the performance of two unsupervised clustering algorithms, namely Hierarchical Cluster Analysis and Gaussian Mixture Model. Our analysis shows that polarimetric properties could be partially predicted even with unpolarized light, thus polarimetric lidar bands provide only a minor improvement in specificity. Finally, we use the physical properties of the clustered observations, such as wing beat frequency, daily activity patterns, and spatial distribution, to establish a lower bound for the number of species represented by the differentiated signal types. [ABSTRACT FROM AUTHOR]

• Insects swarmed at the top of a wind farm. • The insect swarm persisted well past sunset on a warm night, despite significant predation pressure from bats. • Larger insects swarmed during two nights with lower wind speeds. • Bats engaged in both feeding and social interactions at the wind farm. Wind turbines have considerable impact on flying animals, particularly bats, which are sometimes killed in large numbers by the moving rotors. A longstanding question remains why bats are attracted to wind turbines and risk their lives among the moving rotor blades. One hypothesis is that they feed on insects swarming around the turbine towers and another is that they congregate there to court. The two are not mutually exclusive and may occur more or less simultaneously. It has been difficult to distinguish these hypothesis, because techniques that permit observations of small insects over the relevant distances (~100 m) in the dark are lacking. In this study, we monitored insects at the top of a wind turbine using a novel high-resolution Scheimpflug lidar. The instrument was employed around dusk during ten late summer nights in 2018, with the principal aim to evaluate its performance under real field conditions. Insect swarms were observed near the top of the turbine tower on every night. They appeared in short intervals and varied in density, timing, exact location and size of the swarming insects from day to day. Swarms formed in the afternoon and either dispersed around sunset before the emergence of bats, or remained until darkness, when bats arrived at the turbine. Some of the bats fed there, as indicated by ultrasonic feeding-buzzes, and also engaged in social interactions possibly including courtship, as indicated by song-flights. Daily variation in the formation, dispersal and behavior of the insect swarms appeared to be influenced by temperature and wind speed and also differed among the insect species. [ABSTRACT FROM AUTHOR]

Background: In recent years, our group has developed electro-optical remote sensing methods for the monitoring and classification of aerofauna. These methods include active lidar methods and passive, so-called dark-field methods that measure scattered sunlight. In comparison with satellite- and airborne remote sensing, our methods offer a spatiotemporal resolution several orders of magnitude higher, and unlike radar, they can be employed close to ground. Whereas passive methods are desirable due to lower power consumption and ease of use, they have until now lacked ranging capabilities. Results: In this work, we demonstrate how passive ranging of sparse insects transiting the probe volume can be achieved with quadrant sensors. Insects are simulated in a raytracing model of the probe volume, and a ranging equation is devised based on the simulations. The ranging equation is implemented and validated with field data, and system parameters that vary with range are investigated. A model for estimating insect flight headings with modulation spectroscopy is implemented and tested with inconclusive results. Insect fluxes are retrieved through time-lag correlation of quadrant detector segments, showing that insects flew more with than against the wind during the study period. Conclusions: The presented method demonstrates how ranging can be achieved with quadrant sensors, and how it can be implemented with or without active illumination. A number of insect flight parameters can be extracted from the data produced by the sensor and correlated with complementary information about weather and topography. The approach has the potential to become a widespread and simple tool for monitoring abundances and fluxes of pests and disease vectors in the atmosphere. [ABSTRACT FROM AUTHOR]

Insect pest management is a very important aspect for plant protection in crops production. Remote sensing provides a large number of techniques that are beneficial in entomological research. Although entomological radars have been used for studying migrations of insects for many years, most of entomological radar studies have been vertically tracing high‐altitude migration behaviour of insects. Light detection and ranging (lidar) is a counterpart to radar, now operating in the optical part of the electromagnetic spectrum, which has been recently applied for monitoring of insects at low altitude. Such techniques, in particular low‐cost continuous‐wave (CW) bi‐static systems based on the Scheimpflug arrangement, have been rapidly developing during the last decade. As a result, optical methods present new and fascinating possibilities. Based on experience from a 2‐week field campaign in rice paddy fields, we here present an overview of lidar remote sensing applied to the Chinese scene. The capability of a CW Scheimpflug lidar system in monitoring the insects was studied. We present results on insect abundance in relation to time of the day and weather conditions. We also identified insect species by analysing wing‐beat frequencies and studied their attraction to ultraviolet (UV) lamp located close to the horizontal laser sampling path during night time. Results showed that the insect species were abundant, that insects detected by the lidar system were attracted to light and that light rain increased the insect activity. The lidar detection system had a high read‐out frequency, enabling the estimation of insect wing‐beat frequencies. [ABSTRACT FROM AUTHOR]

Effective monitoring of flying insects is of major societal importance in view of the role of insects as indispensable pollinators, destructive disease vectors and economically devastating agricultural pests. The present paper reports on monitoring of flying agricultural pests using a continuous-wave lidar system in a rice-field location in Southern China. Using a Scheimpflug arrangement, range resolution over several 100 m long observational paths was achieved. The system operates with two perpendicularly polarized near-infrared lasers, which are activated intermittently, and back-scattered radiation from insects was recorded by a linear array detector placed after a linear polarizer. Our polarization sensitive system was used to monitor the flying insect diurnal activity and also the influence of changes in weather conditions, e.g., the occurrence of rain. Activity strongly peaked at dusk and rose again, although to a lower extent, just before dawn. At the onset of rainfall, a strong increase in insect counts occurred which was interpreted as the rain-induced bringing down of high-altitude migrant insects. [ABSTRACT FROM AUTHOR]