Modelling geomagnetic bird navigation

Abstract

Geomagnetic navigation is a complex process which has been studied in experimental behaviour and observation studies. However, to date there have been relatively few modelling studies, and all have used geomagnetic data that don’t account for fine-scale dynamics of the geomagnetic field. The objective of this thesis is to study avian migratory navigation using novel data-driven approaches based on high-resolution contemporaneous and co-located geomagnetic and bird tracking data.

Two different methods (random walk models, RWM and step selection analysis, SSA) were applied to evaluate the use of geomagnetic navigational strategies by migratory birds alongside geomagnetic cues (intensity, inclination), and to study the effect of abiotic factors on navigation. Both methods incorporated navigational strategies, which were derived from literature and associated with geomagnetic values. For RWM, these were translated into novel probability surfaces (represented as spatial grids) and for SSA into strategy-based covariates. I further investigated the effect of using higher resolution satellite geomagnetic data and found that models significantly improved with their use. Future studies of geomagnetic navigation should therefore use fine-scale geomagnetic data.

My studies suggest that the most simplistic navigational compass mechanism (i.e. taxis) based on geomagnetic intensity is a preferred strategy. This is likely the most energy efficient mechanism which is the least prone to changes of the geomagnetic field. Additionally, I studied two different abiotic factors which have been proposed to influence bird navigation: the time of the day and local structure of the geomagnetic field. For both, I found the first empirical evidence for their effects on geomagnetic navigation.

My methodologies can be used for direct comparisons of different species migrating in different geographical areas and to study interaction effects with other navigational strategies and environmental factors (e.g. wind). The thesis therefore has a potential for a high impact on the study of migratory navigation.

Date of Award	14 Jun 2023
Original language	English
Awarding Institution	University of St Andrews
Supervisor	Urska Demsar (Supervisor), Jed Andrew Long (Supervisor) & Kamran Safi (Supervisor)