Seasonal migration patterns of Siberian Rubythroat (Calliope calliope) facing the Qinghai-Tibet Plateau.

Archival GPS Central-China flyway Flight altitude GeoPressureR Geographical barriers Geolocation Loop migration Molt migration Multi-sensor logger

Journal

Movement ecology
ISSN: 2051-3933
Titre abrégé: Mov Ecol
Pays: England
ID NLM: 101635009

Informations de publication

Date de publication:
01 Aug 2024
Historique:
received: 09 01 2024
accepted: 15 07 2024
medline: 2 8 2024
pubmed: 2 8 2024
entrez: 1 8 2024
Statut: epublish

Résumé

Small songbirds respond and adapt to various geographical barriers during their annual migration. Global flyways reveal the diverse migration strategies in response to different geographical barriers, among which are high-elevation plateaus. However, few studies have been focused on the largest and highest plateau in the world, the Qinghai-Tibet Plateau (QTP) which poses a significant barrier to migratory passerines. The present study explored the annual migration routes and strategies of a population of Siberian Rubythroats (Calliope calliope) that breed on the north-eastern edge of the QTP. Over the period from 2021 to 2023, we applied light-level geolocators (13 deployed, seven recollected), archival GPS tags (45 deployed, 17 recollected), and CAnMove multi-sensor loggers (with barometer, accelerometer, thermometer, and light sensor, 20 deployed, six recollected) to adult males from the breeding population of Siberian Rubythroat on the QTP. Here we describe the migratory routes and phenology extracted or inferred from the GPS and multi-sensor logger data, and used a combination of accelerometric and barometric data to describe the elevational migration pattern, flight altitude, and flight duration. All light-level geolocators failed to collect suitable data. Both GPS locations and positions derived from pressure-based inference revealed that during autumn, the migration route detoured from the bee-line between breeding and wintering grounds, leading to a gradual elevational decrease. The spring route was more direct, with more flights over mountainous areas in western China. This different migration route during spring probably reflects a strategy for faster migration, which corresponds with more frequent long nocturnal migration flights and shorter stopovers during spring migration than in autumn. The average flight altitude (1856 ± 781 m above sea level) was correlated with ground elevation but did not differ between the seasons. Our finding indicates strong, season-dependent impact of the Qinghai-Tibet Plateau on shaping passerine migration strategies. We hereby call for more attention to the unexplored central-China flyway to extend our knowledge on the environment-migration interaction among small passerines.

Sections du résumé

BACKGROUND BACKGROUND
Small songbirds respond and adapt to various geographical barriers during their annual migration. Global flyways reveal the diverse migration strategies in response to different geographical barriers, among which are high-elevation plateaus. However, few studies have been focused on the largest and highest plateau in the world, the Qinghai-Tibet Plateau (QTP) which poses a significant barrier to migratory passerines. The present study explored the annual migration routes and strategies of a population of Siberian Rubythroats (Calliope calliope) that breed on the north-eastern edge of the QTP.
METHODS METHODS
Over the period from 2021 to 2023, we applied light-level geolocators (13 deployed, seven recollected), archival GPS tags (45 deployed, 17 recollected), and CAnMove multi-sensor loggers (with barometer, accelerometer, thermometer, and light sensor, 20 deployed, six recollected) to adult males from the breeding population of Siberian Rubythroat on the QTP. Here we describe the migratory routes and phenology extracted or inferred from the GPS and multi-sensor logger data, and used a combination of accelerometric and barometric data to describe the elevational migration pattern, flight altitude, and flight duration. All light-level geolocators failed to collect suitable data.
RESULTS RESULTS
Both GPS locations and positions derived from pressure-based inference revealed that during autumn, the migration route detoured from the bee-line between breeding and wintering grounds, leading to a gradual elevational decrease. The spring route was more direct, with more flights over mountainous areas in western China. This different migration route during spring probably reflects a strategy for faster migration, which corresponds with more frequent long nocturnal migration flights and shorter stopovers during spring migration than in autumn. The average flight altitude (1856 ± 781 m above sea level) was correlated with ground elevation but did not differ between the seasons.
CONCLUSIONS CONCLUSIONS
Our finding indicates strong, season-dependent impact of the Qinghai-Tibet Plateau on shaping passerine migration strategies. We hereby call for more attention to the unexplored central-China flyway to extend our knowledge on the environment-migration interaction among small passerines.

Identifiants

pubmed: 39090724
doi: 10.1186/s40462-024-00495-5
pii: 10.1186/s40462-024-00495-5
doi:

Types de publication

Journal Article

Langues

eng

Pagination

54

Informations de copyright

© 2024. The Author(s).

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Auteurs

Tianhao Zhao (T)

Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, 9747 AG, Groningen, The Netherlands. tianhao.zhao@rug.nl.

Wieland Heim (W)

Institute of Biology and Environmental Sciences (IBU), Carl von Ossietzky University of Oldenburg, Ammerländer Heerstraße 114-118, 26129, Oldenburg, Germany.
Department of Bird Migration, Swiss Ornithological Institute, 6204, Sempach, Switzerland.
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.

Raphaël Nussbaumer (R)

Department of Bird Migration, Swiss Ornithological Institute, 6204, Sempach, Switzerland.
Cornell Lab of Ornithology, Ithaca, NY, USA.

Mariëlle van Toor (M)

Center for Ecology and Evolution in Microbial Model Systems (EEMiS), Linnaeus University, 391 82, Kalmar, Sweden.

Guoming Zhang (G)

Qinghai University, Xining, China.

Arne Andersson (A)

Department of Biology, Lund University, 223 62, Lund, Sweden.

Johan Bäckman (J)

Department of Biology, Lund University, 223 62, Lund, Sweden.

Zongzhuang Liu (Z)

Department of Ecology and Genetics, Uppsala University, 752 36, Uppsala, Sweden.

Gang Song (G)

Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management, Institute of Zoology, Chinese Academy of Science, Beijing, China.

Magnus Hellström (M)

Ottenby Bird Observatory, BirdLife Sweden, 386 64, Ottenby, Sweden.

Jacob Roved (J)

Department of Biology, Lund University, 223 62, Lund, Sweden.
GLOBE Institute, University of Copenhagen, 1356, Copenhagen, Denmark.

Yang Liu (Y)

School of Ecology, Sun Yat-sen University, Shenzhen, China.

Staffan Bensch (S)

Department of Biology, Lund University, 223 62, Lund, Sweden.

Bregje Wertheim (B)

Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, 9747 AG, Groningen, The Netherlands.

Fumin Lei (F)

Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management, Institute of Zoology, Chinese Academy of Science, Beijing, China. leifm@ioz.ac.cn.

Barbara Helm (B)

Department of Bird Migration, Swiss Ornithological Institute, 6204, Sempach, Switzerland. barbara.helm@vogelwarte.ch.

Classifications MeSH