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Quantifying nocturnal thrush migration using sensor data fusion between acoustics and vertical‐looking radar

Authors: Giuntini, Silvia; Saari, Juha; Martinoli, Adriano; Preatoni, Damiano G.; Haest, Birgen; Schmid, Baptiste; Weisshaupt, Nadja;

Quantifying nocturnal thrush migration using sensor data fusion between acoustics and vertical‐looking radar

Abstract

AbstractStudying nocturnal bird migration is challenging because direct visual observations are difficult during darkness. Radar has been the means of choice to study nocturnal bird migration for several decades, but provides limited taxonomic information. Here, to ascertain the feasibility of enhancing the taxonomic resolution of radar data, we combined acoustic data with vertical‐looking radar measurements to quantify thrush (Family: Turdidae) migration. Acoustic recordings, collected in Helsinki between August and October of 2021–2022, were used to identify likely nights of high and low thrush migration. Then, we built a random forest classifier that used recorded radar signals from those nights to separate all migrating passerines across the autumn migration season into thrushes and non‐thrushes. The classifier had a high overall accuracy (≈0.82), with wingbeat frequency and bird size being key for separation. The overall estimated thrush autumn migration phenology was in line with known migratory patterns and strongly correlated (Pearson correlation coefficient ≈0.65) with the phenology of the acoustic data. These results confirm how the joint application of acoustic and vertical‐looking radar data can, under certain migratory conditions and locations, be used to quantify ‘family‐level’ bird migration.

Keywords

Technology, Ecology, T, bird radar, Aeroecology, bioacoustics, machine learning, aeroecology, bird migration, Turdidae, QH540-549.5

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    popularity
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    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
Green
gold