Autumn morning flights of migrant songbirds in the northeastern United States are linked to nocturnal migration and winds aloft

Doren, Benjamin M. Van; Sheldon, Daniel; Geevarghese, Jeffrey; Hochachka, Wesley M.; Farnsworth, Andrew

doi:10.1642/auk-13-260.1

Cited by 21 publications

(21 citation statements)

References 34 publications

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“…Recent studies of the behavior of birds that engage in migratory flights after sunrise (i.e., morning flight) highlighted a pattern in which migrants engaged in these flights after larger nocturnal movements and after the presence of stronger nocturnal crosswinds (Van Doren et al. , Horton et al. , Van Doren et al.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, birds may fly under the beam as they pass Boston (a 37.5 km radius from the Boston, Massachusetts, station barely reaches the Rhode Island coast and its stopover sites, with the beam height approximately 115–735 m above the ground) and move into more favorable habitat during the course of stopover periods (e.g., in morning flight, Van Doren et al. , 2016; concentrations of birds in higher quality stopover habitat during the day, Faaborg et al. , Wolfe et al.…”

Section: Discussionmentioning

confidence: 99%

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A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeasternUSA

Farnsworth

Doren

Hochachka

et al. 2016

Ecological Applications

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Billions of birds migrate at night over North America each year. However, few studies have described the phenology of these movements, such as magnitudes, directions, and speeds, for more than one migration season and at regional scales. In this study, we characterize density, direction, and speed of nocturnally migrating birds using data from 13 weather surveillance radars in the autumns of 2010 and 2011 in the northeastern USA. After screening radar data to remove precipitation, we applied a recently developed algorithm for characterizing velocity profiles with previously developed methods to document bird migration. Many hourly radar scans contained windborne "contamination," and these scans also exhibited generally low overall reflectivities. Hourly scans dominated by birds showed nightly and seasonal patterns that differed markedly from those of low reflectivity scans. Bird migration occurred during many nights, but a smaller number of nights with large movements of birds defined regional nocturnal migration. Densities varied by date, time, and location but peaked in the second and third deciles of night during the autumn period when the most birds were migrating. Migration track (the direction to which birds moved) shifted within nights from south-southwesterly to southwesterly during the seasonal migration peaks; this shift was not consistent with a similar shift in wind direction. Migration speeds varied within nights, although not closely with wind speed. Airspeeds increased during the night; groundspeeds were highest between the second and third deciles of night, when the greatest density of birds was migrating. Airspeeds and groundspeeds increased during the fall season, although groundspeeds fluctuated considerably with prevailing winds. Significant positive correlations characterized relationships among bird densities at southern coastal radar stations and northern inland radar stations. The quantitative descriptions of broadscale nocturnal migration patterns presented here will be essential for biological and conservation applications. These descriptions help to define migration phenology in time and space, fill knowledge gaps in avian annual cycles, and are useful for monitoring long-term population trends of migrants. Furthermore, these descriptions will aid in assessing potential risks to migrants, particularly from structures with which birds collide and artificial lighting that disorients migrants.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeasternUSA

Farnsworth

Doren

Hochachka

et al. 2016

Ecological Applications

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“…It is also interesting to notice that both Raven's and XBAT's false detections were sounds generated by abiotic factors (wind and rain), self-noise and insect activity. Similar types of sounds were false positives in other studies using these tools (Swiston and Mennill 2009;Brown et al 2013;Van Doren et al 2015 XBAT's detector was the fastest method and had good comprehensiveness, making it very useful in studies where finding all target sounds is not mandatory and time is a constraint. For instance, if a conservation study wants to determine whether a species is present in an area, this fast sound data analysis method would be more effective than other methods.…”

Section: Detection Comprehensiveness and False Positivesmentioning

confidence: 61%

“…Raven misclassified as target sounds those generated by wind, insects and microphone static (Figure 6), and the number of false positives was almost twice as high as the number of hits (true positives). Recent studies using Raven's Band Limited Energy Detector to find sounds of fin whales (Morano et al 2012) and migrant songbirds (Van Doren et al 2015) show high true positive percentages: 79% comprehensiveness for whales and 96% in low noise conditions for birds, although also capturing a large number of false positives in the bird study (more than 90% of detections). Raven's detector also showed high accuracy in detection of motor vehicle noise in a forested landscape (Brown et al 2013).…”

Section: Detection Comprehensiveness and False Positivesmentioning

confidence: 99%

An evaluation of manual and automated methods for detecting sounds of maned wolves (Chrysocyon brachyurusIlliger 1815)

et al. 2015

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Although bioacoustics is increasingly used to study species and environments for their monitoring and conservation, detecting calls produced by species of interest is prohibitively time consuming when done manually. Here we compared four methods for detecting and identifying roar-barks of maned wolves (Chrysocyon brachyurus) within long sound recordings: (1) a manual method, (2) an automated detector method using Raven Pro 1.4, (3) an automated detector method using XBAT and (4) a mixed method using XBAT's detector followed by manual verification. Recordings were done using a song meter installed at the Serra da Canastra National Park (Minas Gerais, Brazil). For each method we evaluated the following variables in a 24-h recording: (1) total time required analysing files, (2) number of false positives identified and (3) number of true positives identified compared to total number of target sounds. Automated methods required less time to analyse the recordings (77 -93 min) when compared to manual method (189 min), but consistently presented more false positives and were less efficient in identifying true positives (manual ¼ 91.89%, Raven ¼ 32.43% and XBAT ¼ 84.86%). Adding a manual verification after XBAT detection dramatically increased efficiency in identifying target sounds (XBAT þ manual ¼ 100% true positives). Manual verification of XBAT detections seems to be the best way out of the proposed methods to collect target sound data for studies where large amounts of audio data need to be analysed in a reasonable time (111 min, 58.73% of the time required to find calls manually).

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“…Many nocturnal migrants make additional movements during the morning hours in a phenomenon called “morning flight” (Baird and Nisbet , Gauthreaux , Bingman , Yaukey , Van Doren et al. , ). Morning flights are most commonly observed near coastal areas, where they are usually directed either toward the coast when migrants are over water or inland away from the coast.…”

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Morning flight behavior of nocturnally migrating birds along the western basin of Lake Erie

2018

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Many species of birds that normally migrate during the night have been observed engaging in so‐called morning flights during the early morning. The results of previous studies have supported the hypothesis that one function of morning flights is to compensate for wind drift that birds experienced during the night. Our objective was to further explore this hypothesis in a unique geographic context. We determined the orientation of morning flights along the southern shore of Lake Erie's western basin during the spring migrations of 2016 and 2017. This orientation was then compared to the observed orientation of nocturnal migration. Additionally, the orientation of the birds engaged in morning flights following nights with drifting winds was compared to that of birds following nights with non‐drifting winds. The morning flights of most birds at our observation site were oriented to the west‐northwest, following the southern coast of Lake Erie. Given that nocturnal migration was oriented generally east of north, the orientation of morning flight necessarily reflected compensation for accumulated, seasonal wind drift resulting from prevailingly westerly winds. However, the orientation of morning flights was similar following nights with drifting and non‐drifting winds, suggesting that birds on any given morning were not necessarily re‐orienting as an immediate response to drift that occurred the previous night. Given the topographical characteristics of our observation area, the west‐northwest movement of birds in our study is likely best explained as a more complex interaction that could include some combination of compensation for wind drift, a search for suitable stopover habitat, flying in a direction that minimizes any loss in progressing northward toward the migratory goal, and avoidance of a lake crossing.

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Autumn morning flights of migrant songbirds in the northeastern United States are linked to nocturnal migration and winds aloft

Cited by 21 publications

References 34 publications

A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeasternUSA

A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeasternUSA

An evaluation of manual and automated methods for detecting sounds of maned wolves (Chrysocyon brachyurusIlliger 1815)

Morning flight behavior of nocturnally migrating birds along the western basin of Lake Erie

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