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Radar Aeroecology


My research aims to gain an understanding of how organisms utilize the lower atmosphere. To do this I use tools like radar, thermal imaging, and acoustics. 

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Radar Aeroecology


My research aims to gain an understanding of how organisms utilize the lower atmosphere. To do this I use tools like radar, thermal imaging, and acoustics. 

Aeroecology


The United States upgraded the NEXRAD network to dual-polarization in 2013, providing new radar products for the description of migrant flight strategies. 

The United States upgraded the NEXRAD network to dual-polarization in 2013, providing new radar products for the description of migrant flight strategies. 

What is aeroecology? 

Aeroecology is the study of airborne organisms and their utilization of the lower atmosphere (i.e. aerosphere). Like any other habitat or ecosystem, organisms use the aerosphere in a multitude of ways. Whether for foraging or migrating, breeding or roosting, there is no debating that the aerosphere plays a critical role in the life histories of airborne organisms. However, our understanding of these uses is incomplete at best. 

Studying the aerosphere requires a unique suite of tools, naturally linking multiple disciplines together. Sensor systems like radar, thermal imaging, and acoustics are regularly employed by aeroecologists, particularly for describing nocturnal movements. Radar remote sensing offers an invaluable tool for quantifying large-scale animal movements, whereas acoustics provide fine-scale, species-specific records of migrant activity. Each of these tools provide a unique perspective to answer questions that improve our understanding of migratory systems and their association with abiotic and biotic phenomena. 

 

Aeroecology is a discipline that embraces and integrates the domains of atmospheric science, ecology, earth science, geography, computer science, computational biology, and engineering.
— Kunz et al. (2008)

Radar aeroecology

Radar, since it’s advent, has undergone numerous advances, prominently in hardware development. The use of radars in biology date back to the 1940s when David Lack, arguably the father of what we today call radar ornithology (or radar aeroecology), championed the use of radar for understanding large-scale nocturnal movements of birds. In aeroecology, radar is used for a multitude of uses: monitoring of migratory bird stopover sites, identification of species-specific bird and bat roosts, and tracking of broad migrations.

In 1988 the United States began a massive upgrade to its ageing radar network, installing what is known more commonly today as the NEXRAD (Next Generation Radar) network. Today the United States operates ~140 WSR-88D (Weather Surveillance Radar 1988-Dopper) radars in the continental US. These 10-cm wavelength radars possess a typical biological range of 80-120 km, and provide rapid updates of migration intensity, migration track, and more recently orientation direction.

Radar correlation coefficient revealing large-scale orientation fields of nocturnal migrants. 

Radar correlation coefficient revealing large-scale orientation fields of nocturnal migrants. 

WSR-88Ds until about 2013 collected three primary radar moments: reflectivity, radial velocity, and spectrum width. In 2013 the US upgraded the NEXRAD network to dual-polarization, an update that resulted in the collection of three additional data products: differential reflectivity, correlation coefficient, and differential phase. The incorporation of this second plane of polarization added another “dimension” for describing precipitation, atmospheric debris, and biological scatterers. Although the use of polarimetric weather surveillance radar data are relatively new in aeroecology, they have proven useful for describing migratory behaviors and characterizing biological scatters. This upgrade has allowed for a direct measure of migrant orientation, an important feature for determining migrant flight strategies regarding wind drift compensation. I am interested in how migratory birds cope with crosswinds and how these strategies may differ at large geographic scales. 


Locations of the study site in Lewes, Delaware, USA, where thermal infrared camera and acoustic recordings were made of nocturnal flying animals, and of the KDOX radar station. The gray circle denotes the 5–20 km radius area where radar data were used to calculate vertical profiles of reflectivity (VPR). 

Locations of the study site in Lewes, Delaware, USA, where thermal infrared camera and acoustic recordings were made of nocturnal flying animals, and of the KDOX radar station. The gray circle denotes the 5–20 km radius area where radar data were used to calculate vertical profiles of reflectivity (VPR). 

Abstract: There are several remote-sensing tools readily available for the study of nocturnally flying animals (e.g., migrating birds), each possessing unique measurement biases. We used three tools (weather surveillance radar, thermal infrared camera, and acoustic recorder) to measure temporal and spatial patterns of nocturnal traffic estimates of flying animals during the spring and fall of 2011 and 2012 in Lewes, Delaware, USA. Our objective was to compare measures among different technologies to better understand their animal detection biases. For radar and thermal imaging, the greatest observed traffic rate tended to occur at, or shortly after, evening twilight, whereas for the acoustic recorder, peak bird flight-calling activity was observed just prior to morning twilight. Comparing traffic rates during the night for all seasons, we found that mean nightly correlations between acoustics and the other two tools were weakly correlated (thermal infrared camera and acoustics, r = 0.004 ± 0.04 SE, n = 100 nights; radar and acoustics, r= 0.14 ± 0.04 SE, n = 101 nights), but highly variable on an individual nightly basis (range = −0.84 to 0.92, range = −0.73 to 0.94). The mean nightly correlations between traffic rates estimated by radar and by thermal infrared camera during the night were more strongly positively correlated (r = 0.39 ± 0.04 SE, n = 125 nights), but also were highly variable for individual nights (range = −0.76 to 0.98). Through comparison with radar data among numerous height intervals, we determined that flying animal height above the ground influenced thermal imaging positively and flight call detections negatively. Moreover, thermal imaging detections decreased with the presence of cloud cover and increased with mean ground flight speed of animals, whereas acoustic detections showed no relationship with cloud cover presence but did decrease with increased flight speed. We found sampling methods to be positively correlated when comparing mean nightly traffic rates across nights. The strength of these correlations generally increased throughout the night, peaking 2–3 hours before morning twilight. Given the convergence of measures by different tools at this time, we suggest that researchers consider sampling flight activity in the hours before morning twilight when differences due to detection biases among sampling tools appear to be minimized.


Nocturnal Flight Calls

Wood-warblers of eastern North American and their corresponding nocturnal flight calls spectrogram. Underlying flight call audio from Evans and O'Brien (2002).  

Wood-warblers of eastern North American and their corresponding nocturnal flight calls spectrogram. Underlying flight call audio from Evans and O'Brien (2002).  

Nocturnal flight calls are unique species-specific vocalizations given by many birds. Like the name entails, these calls are largely given during flight, particularly migratory flights. Because these calls are unique at the species level, they provide one of the few methods for documenting species-specifc nocturnal movements. From a monitoring standpoint the utility of these calls seems obvious, however the underlying function of these calls remains unknown. I am interested in the role these calls play in migratory flights and the cues that stimulate flight-calling. Additionally, I am interested in the interpretation of flight calls as a measure of migration intensity and the dependence of bird behavior and atmospheric properties on the detection of these calls from ground-based recorders.  


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Abstract: Avian migration monitoring can take on many forms; however, monitoring active nocturnal migration of land birds is limited to a few techniques. Avian nocturnal flight calls are currently the only method for describing migrant composition at the species level. However, as this method develops, more information is needed to understand the sources of variation in call detection. Additionally, few studies examine how detection probabilities differ under varying atmospheric conditions. We use nocturnal flight call recordings from captive individuals to explore the dependence of flight call detection on atmospheric temperature and humidity. Height or distance from origin had the largest influence on call detection, while temperature and humidity also influenced detectability at higher altitudes. Because flight call detection varies with both atmospheric conditions and flight height, improved monitoring across time and space will require correction for these factors to generate standardized metrics of songbird migration. 

Acoustic attenuation of a Black-and-white Warbler flight call at 150 m under variable atmospheric temperature and relative humidity profiles. Percent decibel change referenced from outlined call displayed in the lower right corner of each spectrogram. 

Acoustic attenuation of a Black-and-white Warbler flight call at 150 m under variable atmospheric temperature and relative humidity profiles. Percent decibel change referenced from outlined call displayed in the lower right corner of each spectrogram.