0 Datasets
0 Files
$0 Value
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free Access
King Abdullah University of Science and Technology
<title>Abstract</title> Animal movement paths display substantial complexity and variability, leading researchers to seek underlying rules that govern these patterns and mathematical models that best describe them. Using high-resolution (≥ 10 Hz) movement from 43 vertebrate species across diverse taxa, mass, and lifestyles, we show that movement paths are universally composed of straight-line steps interspersed with sharp turns, echoing a pattern documented for lower taxa such as bacteria. We report how these vertebrate ‘fundamental step lengths’ and ‘fundamental turn angles’, which are intrinsically different from the straight-line paths detailed in studies using low resolution position data, vary with species’ mass, lifestyle, behaviour, and environmental context. To explain these, we posit that animals inherently move in a straight line until sensory information signals a perceived better heading, which instigates a turn. The constellation of fundamental step lengths and turn angles over varying time intervals affects how well different models of animal movement (such as random walk or Lévy flight) fit lower resolution data. By examining turns as decision points, we can seek drivers of animal movement patterns and thereby work to predict future paths under varying conditions.
Richard Gunner, Rory P. Wilson, Miguel Lurgi, Luca Börger, James Redcliffe, Emily L. C. Shepard, Mark D. Holton, Margaret C. Crofoot, Abdulaziz N. Alagaili, Samantha Andrzejaczek, Daniel Ariano‐Sánchez, Thomas Barbedette-Gerard, Nigel C. Bennett, Alice Bernard, M. Rowan Brown, Nik C. Cole, Scott Creel, Ariovaldo P. Cruz‐Neto, Agustina di Virgilio, Carlos M. Duarte, Christophe Eizaguirre, Kyle H. Elliott, Monika Faltusová, Mathieu Garel, Natasha Gillies, Adrian C. Gleiss, Aoife Göppert, David Grémillet, Sophie de Grissac, Tim Guilford, Maxime Hoareau, Mark Jessopp, Agustina Gómez‐Laich, Miloš Ježek, Sergio A. Lambertucci, Pascal Marchand, Nikki J. Marks, Andréia Martins, Mark G. Meekan, Yuichi Mizutani, Rasmus Mohr Mortensen, Bradley M. Norman, Josué Ortega, Oliver Padget, Michael S. Painter, Aurore Ponchon, Pascal Provost, Aurore Ponchon, Flavio Quintana, Stefanie Reinhardt, Samantha Reynolds, Frank Rosell, Carlos R. Ruiz‐Miranda, Peter G. Ryan, Michael Scantlebury, Stefan Schoombie, Rebecca Scott, Václav Silovský, Rabindra Vikash Tatayah, Carole Toïgo, Lucía Tórrez, Fred Tremblay, Joshua P. Twining, Ken Yoda, Henri Weimerskirch, Shannon Whelan, Juan Morales, Jonathan R. Potts (2024). High resolution data reveal fundamental steps and turning points in animal movements. , DOI: https://doi.org/10.21203/rs.3.rs-5559169/v1.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Preprint
Year
2024
Authors
68
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.21203/rs.3.rs-5559169/v1
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access
