Revell, Christopher and Somveille, Marius ORCID: https://orcid.org/0000-0002-6868-5080
(2017)
A physics-inspired mechanistic model of migratory movement patterns in birds.
Scientific Reports, 7 (1).
ISSN 2045-2322
Preview |
PDF (Revell_Somveille_2017_SciRep)
- Published Version
Available under License Creative Commons Attribution. Download (3MB) | Preview |
Abstract
In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.
Item Type: | Article |
---|---|
Faculty \ School: | Faculty of Science > School of Environmental Sciences |
Related URLs: | |
Depositing User: | LivePure Connector |
Date Deposited: | 22 Jul 2024 10:33 |
Last Modified: | 22 Jul 2024 15:32 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/95987 |
DOI: | 10.1038/s41598-017-09270-6 |
Downloads
Downloads per month over past year
Actions (login required)
![]() |
View Item |