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.
Highlights
In recent years, there has been significant interest in inter-disciplinary research, between the physical and biological sciences
Our method improves upon physical transport models, which focus on the dynamics of the physical environment but neglect the organism’s movement abilities[18]
After describing our new method and its applications, we demonstrate its promise by exploring its ability to predict non-breeding migration patterns from breeding colonies of black-browed albatrosses (Thalassarche melanophris)
Summary
We introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Our model aims to explore the underlying forces driving migration from first principles, and in this paperit is adapted to study the long-distance migration of birds This method integrates the influence of the physical environment into movement decisions made by the birds to track. The species has a circumpolar distribution, breeding colonially on many geographically separated subantarctic islands and archipelagos, and exhibiting a mix of short and long distance migratory movements during the non-breeding season[30] This species feeds on a wide variety of prey and mostly targets neritic, productive upwellings and shelf areas[31, 32]. We produced exploratory results for populations from the five major breeding colonies discussed above, and made predictions for untracked populations from Campbell Island, the Crozet Islands, and Islas Diego de Almagro
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