Titre
A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Nussbaumer, Raphaël
Auteure/Auteur
Benoit, Lionel
Auteure/Auteur
Mariethoz, Grégoire
Auteure/Auteur
Liechti, Felix
Auteure/Auteur
Bauer, Silke
Auteure/Auteur
Schmid, Baptiste
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
2072-4292
Statut éditorial
Publié
Date de publication
2019-09-25
Volume
11
Numéro
19
Première page
2233
Peer-reviewed
Oui
Langue
anglais
Résumé
Quantifying nocturnal bird migration at high resolution is essential for (1) understanding the phenology of migration and its drivers, (2) identifying critical spatio-temporal protection zones for migratory birds, and (3) assessing the risk of collision with artificial structures. We propose a tailored geostatistical model to interpolate migration intensity monitored by a network of weather radars. The model is applied to data collected in autumn 2016 from 69 European weather radars. To validate the model, we performed a cross-validation and also compared our interpolation results with independent measurements of two bird radars. Our model estimated bird densities at high resolution (0.2° latitude–longitude, 15 min) and assessed the associated uncertainty. Within the area covered by the radar network, we estimated that around 120 million birds were simultaneously in flight (10–90 quantiles: 107–134). Local estimations can be easily visualized and retrieved from a dedicated interactive website. This proof-of-concept study demonstrates that a network of weather radar is able to quantify bird migration at high resolution and accuracy. The model presented has the ability to monitor population of migratory birds at scales ranging from regional to continental in space and daily to yearly in time. Near-real-time estimation should soon be possible with an update of the infrastructure and processing software.
PID Serval
serval:BIB_FC83CC4763E6
Open Access
Oui
Date de création
2019-07-30T10:00:29.124Z
Date de création dans IRIS
2025-05-21T05:10:01Z
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Nom
remotesensing-11-02233-v2.pdf
Version du manuscrit
published
Licence
https://creativecommons.org/licenses/by/4.0
Taille
10.28 MB
Format
Adobe PDF
PID Serval
serval:BIB_FC83CC4763E6.P001
URN
urn:nbn:ch:serval-BIB_FC83CC4763E62
Somme de contrôle
(MD5):a1f828445d857733e07d55c021345e85