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Fusion of wildlife tracking and satellite geomagnetic data for the study of animal migration

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Date
11/06/2021
Author
Benitez Paez, Manuel Fernando
Brum-Bastos, Vanessa
Beggan , Ciarán
Long, Jed
Demsar, Urska
Funder
The Leverhulme Trust
Grant ID
RPG-2018-258
Keywords
Animal migration
Data fusion
Earth's magnetic field
GPS tracking
Swarm satellite constellation
QH301 Biology
DAS
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Abstract
Background: Migratory animals use information from the Earth’s magnetic field on their journeys. Geomagnetic navigation has been observed across many taxa, but how animals use geomagnetic information to find their way is still relatively unknown. Most migration studies use a static representation of geomagnetic field and do not consider its temporal variation. However, short-term temporal perturbations may affect how animals respond - to understand this phenomenon, we need to obtain fine resolution accurate geomagnetic measurements at the location and time of the animal. Satellite geomagnetic measurements provide a potential to create such accurate measurements, yet have not been used yet for exploration of animal migration. Methods: We develop a new tool for data fusion of satellite geomagnetic data (from the European Space Agency’s Swarm constellation) with animal tracking data using a spatio-temporal interpolation approach. We assess accuracy of the fusion through a comparison with calibrated terrestrial measurements from the International Real-time Magnetic Observatory Network (INTERMAGNET). We fit a generalized linear model (GLM) to assess how the absolute error of annotated geomagnetic intensity varies with interpolation parameters and with the local geomagnetic disturbance. Results: We find that the average absolute error of intensity is − 21.6 nT (95% CI [− 22.26555, − 20.96664]), which is at the lower range of the intensity that animals can sense. The main predictor of error is the level of geomagnetic disturbance, given by the Kp index (indicating the presence of a geomagnetic storm). Since storm level disturbances are rare, this means that our tool is suitable for studies of animal geomagnetic navigation. Caution should be taken with data obtained during geomagnetically disturbed days due to rapid and localised changes of the field which may not be adequately captured. Conclusions: By using our new tool, ecologists will be able to, for the first time, access accurate real-time satellite geomagnetic data at the location and time of each tracked animal, without having to start new tracking studies with specialised magnetic sensors. This opens a new and exciting possibility for large multi-species studies that will search for general migratory responses to geomagnetic cues. The tool therefore has a potential to uncover new knowledge about geomagnetic navigation and help resolve long-standing debates.
Citation
Benitez Paez , M F , Brum-Bastos , V , Beggan , C , Long , J & Demsar , U 2021 , ' Fusion of wildlife tracking and satellite geomagnetic data for the study of animal migration ' , Movement Ecology , vol. 9 , 31 . https://doi.org/10.1186/s40462-021-00268-4
Publication
Movement Ecology
Status
Peer reviewed
DOI
https://doi.org/10.1186/s40462-021-00268-4
ISSN
2051-3933
Type
Journal article
Rights
Copyright © The Author(s). 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Description
This work was supported by the Leverhulme Trust [Research Project Grant RPG-2018-258].
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/23359

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