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ABSTRACT Anthropogenic change is predicted to result in widespread declines in insect abundance, but assessing long‐term trends is challenging due to the scarcity of systematically collected time series measurements across large spatial scales. We develop a novel continental‐scale dataset using a nationwide network of radars in the United States to generate a 10‐year time series of daily aerial insect density and assess temporal trends. We do not find evidence of a continental‐scale net decline in insect density over the 10‐year period included in this study; instead we find a mosaic of increasing and declining trends at the landscape scale. This spatial variation in density trends is associated with climatic drivers, where areas with warmer winters experience greater declines in insect density and areas with cooling winter trends see increases in density. Winter warming has a stronger negative effect on density at higher latitudes. After assessing temporal trends, we also use the 10‐year dataset and atmospheric variables to model insect aerial abundance, finding that on a typical summer day approximately a hundred trillion (10¹⁴) flying insects are present in the airspace, representing millions of tons of aerial biomass. Our results provide the first continental‐scale quantification of insect density and its response to anthropogenic warming and demonstrate the utility of weather surveillance radar to provide large‐scale monitoring of insect abundance. 

Avian migration has fascinated humans for centuries. Insights into the lives of migrant birds are often elusive; however, recent, standalone technological innovations have revolutionized our understanding of this complex biological phenomenon. A future challenge for following these highly mobile animals is the necessity of bringing multiple technologies together to capture a more complete understanding of their movements. Here, we designed a proof-of-concept multi-sensor array consisting of two weather surveillance radars (WSRs), one local and one regional, an autonomous moon-watching sensor capable of detecting birds flying in front of the moon, and an autonomous recording unit (ARU) capable of recording avian nocturnal flight calls. We deployed this array at a field site in central Oklahoma on select nights in March, April, and May of 2021 and integrated data from this array with wind data corresponding to this site to examine the influence of wind on the movements of spring migrants aloft across these spring nights. We found that regional avian migration intensity is statistically significantly negatively correlated with wind velocity, in line with previous research. Furthermore, we found evidence suggesting that when faced with strong, southerly winds, migrants take advantage of these conditions by adjusting their flight direction by drifting. Importantly, we found that most of the migration intensities detected by the sensors were intercorrelated, except when this correlation could not be ascertained because we lacked the sample size to do so. This study demonstrates the potential for multi-sensor arrays to reveal the detailed ways in which avian migrants move in response to changing atmospheric conditions while in flight. 

Aeroecology is an emerging discipline founded by Tom Kunz and colleagues in the early 2000s to address the challenges of studying animal flight in the lower atmosphere [...] 

The daytime atmospheric boundary layer is characterized by vertical convective motions that are driven by solar radiation. Lift provided by thermal updrafts is sufficiently ubiquitous that some diurnal birds and arthropods have evolved specialized flight behaviors to soar or embed in these atmospheric currents. While the diel periodicity of boundary-layer dynamics and animal flight has been characterized, rare disruptions to this cycle provide a chance to investigate animal behavioral responses to boundary layer motion and photoperiod that are disjointed from their expected circadian rhythm. To analyze these interactions, we couple radar-derived animal observations with co-located lidar measurements of the convective boundary layer over north-central Oklahoma, USA during the solar eclipse of 21 August 2017. Analysis of animal flight behavior confirmed that ascending and descending flight effort did change in the time period encompassing the solar eclipse, however, the response in behavior was coincident with proximate changes in boundary-layer turbulence. Both the animal behavioral response and decrease in atmospheric turbulence lagged changes in solar irradiance by approximately 30 min, suggesting that changes in flight activity were not cued by the eclipse directly, but rather by the modification of vertical air motions caused by the eclipse. 

Seasonal animal movement among disparate habitats is a fundamental mechanism by which energy, nutrients, and biomass are transported across ecotones. A dramatic example of such exchange is the annual emergence of mayfly swarms from freshwater benthic habitats, but their characterization at macroscales has remained impossible. We analyzed radar observations of mayfly emergence flights to quantify long-term changes in annual biomass transport along the Upper Mississippi River and Western Lake Erie Basin. A single emergence event can produce 87.9 billion mayflies, releasing 3,078.6 tons of biomass into the airspace over several hours, but in recent years, production across both waterways has declined by over 50%. As a primary prey source in aquatic and terrestrial ecosystems, these declines will impact higher trophic levels and environmental nutrient cycling. 

Abstract The fate of migrating insects that encounter rainfall in flight is a critical consideration when modelling insect movement, but few field observations of this common phenomenon have ever been collected due to the logistical challenges of witnessing these encounters. Operational cloud radars have been deployed around the world by meteorological agencies to study precipitation physics, and as a byproduct, provide a rich database of insect observations that is freely available to researchers. Although considered unwanted ‘clutter’ by the meteorologists who collect the data, the analysis method presented here enables ecologists to delineate co‐occurring signals from insects and raindrops.We present a method that uses image processing techniques on cloud radar velocity spectra to examine the fate of migrating insects when they encounter precipitation. By analysing velocity spectra, we can distinguish flying insects from falling rain and compare the relative density of insects in flight before, during and after the rainfall. We demonstrate the method on a case of insect migration in Oklahoma, USA.Using this method, we show the first reconstructed images of migrating insect layers in flight during rainfall. Our analysis shows that mild to moderate rainfall diminishes the number of insects aloft but does not cause full termination of migratory flight, as has previously been suggested.We hope this technique will spur further investigations of how changing weather conditions impact insect migration, and enable some of the first of such studies in regions of the world that are underrepresented in the literature.