A weather surveillance radar view of Alaskan avian migration Sivakumar, Ashwin H; Sheldon, Daniel; Winner, Kevin ...
Proceedings - Royal Society. Biological sciences/Proceedings - Royal Society. Biological Sciences,
05/2021, Letnik:
288, Številka:
1950
Journal Article
Recenzirano
Odprti dostop
Monitoring avian migration within subarctic regions of the globe poses logistical challenges. Populations in these regions often encounter the most rapid effects of changing climates, and these ...seasonally productive areas are especially important in supporting bird populations-emphasizing the need for monitoring tools and strategies. To this end, we leverage the untapped potential of weather surveillance radar data to quantify active migration through the airspaces of Alaska. We use over 400 000 NEXRAD radar scans from seven stations across the state between 1995 and 2018 (86% of samples derived from 2013 to 2018) to measure spring and autumn migration intensity, phenology and directionality. A large bow-shaped terrestrial migratory system spanning the southern two-thirds of the state was identified, with birds generally moving along a northwest-southeast diagonal axis east of the 150th meridian, and along a northeast-southwest axis west of this meridian. Spring peak migration ranged from 3 May to 30 May and between, 18 August and 12 September during the autumn, with timing across stations predicted by longitude, rather than latitude. Across all stations, the intensity of migration was greatest during the autumn as compared to spring, highlighting the opportunity to measure seasonal indices of net breeding productivity for this important system as additional years of radar measurements are amassed.
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.
The timing of avian migration has evolved to exploit critical seasonal resources, yet plasticity within phenological responses may allow adjustments to interannual resource phenology. The diversity ...of migratory species and changes in underlying resources in response to climate change make it challenging to generalize these relationships.
We use bird banding records during spring and fall migration from across North America to examine macroscale phenological responses to interannual fluctuations in temperature and long‐term annual trends in phenology.
In total, we examine 19 species of North American wood warblers (family Parulidae), summarizing migration timing from 2,826,588 banded birds from 1961 to 2018 across 46 sites during spring and 124 sites during fall.
During spring, warmer spring temperatures at banding locations translated to earlier median passage dates for 16 of 19 species, with an average 0.65‐day advancement in median passage for every 1°C increase in temperature, ranging from 0.25 to 1.26 days °C−1. During the fall, relationships were considerably weaker, with only 3 of 19 species showing a relationship with temperature. In those three cases, later departure dates were associated with warmer fall periods. Projecting these trends forward under climate scenarios of temperature change, we forecast continued spring advancements under shared socioeconomic pathways from 2041 to 2060 and 2081 to 2100 and more muted and variable shifts for fall.
These results demonstrate the capacity of long‐distance migrants to respond to interannual fluctuations in temperatures, at least during the spring, and showcase the potential of North American bird banding data understanding phenological trends across a wide diversity of avian species.
The authors use a critically underutilized resource—bird banding data—to quantify and forecast changes in spring and fall migration across North America to ask the question of how migrants respond to macroscale phenological responses in interannual fluctuations in temperature.
Predicting bird‐window collisions with weather radar Elmore, Jared A.; Riding, Corey S.; Horton, Kyle G. ...
Journal of applied ecology,
August 2021, 2021-08-00, 20210801, Letnik:
58, Številka:
8
Journal Article
Recenzirano
Odprti dostop
Up to 1 billion birds die annually in the U.S. from window collisions; most of these casualties represent migratory native species. Because this major mortality source likely contributes to the ...decline of the North American avifauna, mitigation tools are needed that accurately predict real‐time collision risk, allowing hazards to be minimized before fatalities occur.
We assessed the potential use of weather surveillance radar, an emerging tool increasingly used to study and to predict bird migration, as an early warning system to reduce numbers of bird‐window collisions.
Based on bird‐window collision monitoring in Oklahoma, USA, we show that radar‐derived migration variables are associated with nightly numbers of collisions. Across the entire night, numbers of collisions increased with higher migration traffic rate (i.e. numbers of birds crossing a fixed line perpendicular to migration direction), and migration variables for specific periods within the night were also related to nightly collisions.
Synthesis and applications. Our study suggests that radar can be an invaluable tool to predict bird‐window collisions and help refine mitigation efforts that reduce collisions such as reducing nighttime lighting emitted from and near buildings.
Our study suggests that radar can be an invaluable tool to predict bird‐window collisions and help refine mitigation efforts that reduce collisions such as reducing nighttime lighting emitted from and near buildings.
As wind energy rapidly expands worldwide, information to minimize impacts of this development on biodiversity is urgently needed. Here we demonstrate how data collected by weather radar networks can ...inform placement and operation of wind facilities to reduce collisions and minimize habitat‐related impacts on nocturnally migrating birds. We found over a third of nocturnal migrants flew through altitudes within the rotor‐swept zone surrounding the North American Great Lakes, a continentally important migration corridor. Migrating birds concentrated in terrestrial stopover habitats within 20‐km from shorelines, a distance well beyond the current guidelines for construction of new land‐based facilities, and their distributions varied seasonally and at local and regional scales, creating predictable opportunities to minimize impacts from wind energy development and operation. Networked radar data are available across the United States and other countries and broad application of this approach could provide information critical to bird‐friendly expansion of this globally important energy source.
Abstract
The upgrade of the national network of next‐generation weather surveillance radars (
NEXRAD
) in the United States to dual polarizations has been completed, providing three additional ...routine data products: total differential phase (ψ
DP
), differential reflectivity (
Z
DR
), and copolar correlation coefficient (ρ
HV
). The application and interpretation of these products in the context of aerial bird, bat, and insect movements is an actively developing research front, with potential implications for ecological and conservation studies. The following conceptually derives the definition of these products specifically for
NEXRAD
weather surveillance radars in the case of biological scatterers. Several cases are presented that illustrate characteristic values and variability of polarimetric quantities for birds and insects, and highlight site‐specific differences within the
NEXRAD
network. Finally, a short prospectus of future directions and applications within the field of polarimetric radar aeroecology is outlined.
Abstract
Aim
A unique risk faced by nocturnally migrating birds is the disorienting influence of artificial light at night (ALAN). ALAN originates from anthropogenic activities that can generate ...other forms of environmental pollution, including the emission of fine particulate matter (PM
2.5
). PM
2.5
concentrations can display strong seasonal variation whose origin can be natural or anthropogenic. How this variation affects seasonal associations with ALAN and PM
2.5
for nocturnally migrating bird populations has not been explored.
Location
Western Hemisphere.
Time Period
2021
Major Taxa Studied
Nocturnally migrating passerine (NMP) bird species.
Methods
We combined monthly estimates of PM
2.5
and ALAN with weekly estimates of relative abundance for 164 NMP species derived using observations from eBird. We identified groups of species with similar associations with monthly PM
2.5
. We summarized their shared environmental, geographical, and ecological attributes.
Results
PM
2.5
was lowest in North America, especially at higher latitudes during the boreal winter. PM
2.5
was highest in the Amazon Basin, especially during the dry season (August–October). ALAN was highest within eastern North America, especially during the boreal winter. For NMP species, PM
2.5
associations reached their lowest levels during the breeding season (<10 μg/m
3
) and highest levels during the nonbreeding season, especially for long‐distance migrants that winter in Central and South America (~20 μg/m
3
). Species that migrate through Central America in the spring encountered similarly high PM
2.5
concentrations. ALAN associations reached their highest levels for species that migrate (~12 nW/cm
2
/sr) or spend the nonbreeding season (~15 nW/cm
2
/sr) in eastern North America.
Main Conclusions
We did not find evidence that the disorienting influence of ALAN enhances PM
2.5
exposure during stopover in the spring and autumn for NMP species. Rather, our findings suggest biomass burning in the Neotropics is exposing NMP species to consistently elevated PM
2.5
concentrations for an extended period of their annual life cycles.
Large networks of weather radars are comprehensive instruments for studying bird migration. For example, the US WSR‐88D network covers the entire continental US and has archived data since the 1990s. ...The data can quantify both broad and fine‐scale bird movements to address a range of migration ecology questions. However, the problem of automatically discriminating precipitation from biology has significantly limited the ability to conduct biological analyses with historical radar data.
We develop MistNet, a deep convolutional neural network to discriminate precipitation from biology in radar scans. Unlike prior machine learning approaches, MistNet makes fine‐scaled predictions and can collect biological information from radar scans that also contain precipitation. MistNet is based on neural networks for images, and includes several architecture components tailored to the unique characteristics of radar data. To avoid a massive human labelling effort, we train MistNet using abundant noisy labels obtained from dual polarization radar data.
In historical and contemporary WSR‐88D data, MistNet identifies at least 95.9% of all biomass with a false discovery rate of 1.3%. Dual polarization training data and our radar‐specific architecture components are effective. By retaining biomass that co‐occurs with precipitation in a single radar scan, MistNet retains 15% more biomass than traditional whole‐scan approaches to screening. MistNet is fully automated and can be applied to datasets of millions of radar scans to produce fine‐grained predictions that enable a range of applications, from continent‐scale mapping to local analysis of airspace usage.
Radar ornithology is advancing rapidly and leading to significant discoveries about continent‐scale patterns of bird movements. General‐purpose and empirically validated methods to quantify biological signals in radar data are essential to the future development of this field. MistNet can enable large‐scale, long‐term, and reproducible measurements of whole migration systems.
摘要
⼀、⼤規模的氣象雷達網路是研究⿃類遷徙的全⽅位⼯具。US WSR‐88D 氣象雷達網路 覆蓋美國⼤陸，存擋從 1990 年代⾄今的雷達數據。這些數據可被⽤來量化⼤尺度到細尺 度上的⿃類活動，從⽽回答⼀系列⿃類遷徙的⽣態問題。然⽽，過去雷達數據分析仰賴⼤ 量的⼈⼒以區分雷達影像上的降⾬及⽣態活動。這個缺點侷限了利⽤歷史數據以分析⽣ 態活動的可能性。
⼆、我們開發了 MISTNET，⼀個基於深度卷積神經網路的機器學習模型來分辨雷達數據 中的降⾬和⽣物訊號。不同於傳統的機器學習模型，MISTNET 可以做到細尺度的辨識， 並能從同時存在降⾬和⽣物訊號的雷達掃瞄中收集⽣物資訊。MISTNET 的設計基於影 像辨識的深度神經網路，並包含了針對雷達數據的特性所設計的架構。為了避免標記影 像所需的⼤量⼈⼒，我們使⽤從雙極化的雷達數據中獲得的帶有雜訊的影像標籤來訓練 MISTNET。
三、在歷史和近期的 WSR‐88D 雷達數據中，MISTNET 能辨識出⾄少 95.9% 以上的⽣ 物量，並且僅有 1.3% 假陽性錯誤率。透過保留和降⾬同時存在的⽣物訊號，MISTNET ⽐傳統過濾整張影像的⽅法多保留 15% 的⽣物量。MISTNET 實現了全⾃動化，能夠處 理多達百萬幅的雷達掃瞄數據集來產⽣空間上細尺度的辨識。這些特性成就 MISTNET 可廣泛⽤於各種應⽤，包含從⼤陸尺度到區域性的空域分析。
四、雷達⿃類學的發展迅速，並已經獲得了⼤陸尺度上⿃類活動的重⼤認識。通⽤於⼀般 ⽤途且可量化驗證的雷達⽣物訊號量化⽅法是這個領域未來發展的關鍵。MISTNET 可 ⽤於⼤規模且⾧時間的量測整體遷徙系統，且測量的結果是可以重複實現的。
Aim
Two important environmental hazards for nocturnally migrating birds are artificial light at night (ALAN) and air pollution, with ambient fine particulate matter (PM2.5) considered to be ...especially harmful. Nocturnally migrating birds are attracted to ALAN during seasonal migration, which could increase exposure to PM2.5. Here, we examine PM2.5 concentrations and PM2.5 trends and the spatial correlation between ALAN and PM2.5 within the geographical ranges of the world’s nocturnally migrating birds.
Location
Global.
Time period
1998–2018.
Major taxa studied
Nocturnally migrating birds.
Methods
We intersected a global database of annual mean PM2.5 concentrations over a 21‐year period (1998–2018) with the geographical ranges (breeding, non‐breeding and regions of passage) of 225 nocturnally migrating bird species in three migration flyways (Americas, n = 143; Africa–Europe, n = 36; and East Asia–Australia, n = 46). For each species, we estimated PM2.5 concentrations and trends and measured the correlation between ALAN and PM2.5, which we summarized by season and flyway.
Results
Correlations between ALAN and PM2.5 were significantly positive across all seasons and flyways. The East Asia–Australia flyway had the strongest ALAN–PM2.5 correlations within regions of passage, the highest PM2.5 concentrations across all three seasons and the strongest positive PM2.5 trends on the non‐breeding grounds and within regions of passage. The Americas flyway had the strongest negative air pollution trends on the non‐breeding grounds and within regions of passage. The breeding grounds had similarly negative air pollution trends within the three flyways.
Main conclusions
The combined threats of ALAN and air pollution are greatest and likely to be increasing within the East Asia–Australia flyway and lowest and likely to be decreasing within the Americas and Africa–Europe flyways. Reversing PM2.5 trends in the East Asia–Australia flyway and maintaining negative PM2.5 trends in the Americas and Africa–Europe flyways while reducing ALAN levels would likely be beneficial for the nocturnally migrating bird populations in each region.
The shortest possible migratory route for birds is not always the best route to travel. Substantial research effort has established that birds in captivity are capable of orienting toward the ...direction of an intended goal, but efforts to examine how free-living birds use navigational information under conditions that potentially make direct flight toward that goal inefficient have been limited in spatiotemporal scales and in the number of individuals observed because of logistical and technological limitations. Using novel and recently developed techniques for analysis of Doppler polarimetric weather surveillance radar data, we examined two impediments for nocturnally migrating songbirds in eastern North America following shortest-distance routes: crosswinds and oceans. We found that migrants in flight often drifted sideways on crosswinds, but most strongly compensated for drift when near the Atlantic coast. Coastal migrants' tendency to compensate for wind drift also increased through the night, while no strong temporal differences were observed at inland sites. Such behaviors suggest that birds migrate in an adaptive way to conserve energy by assessing while airborne the degree to which they must compensate for wind drift.
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