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A periodic Markov model to formalize animal migration on a network
Andrea Kölzsch1,2,3, Erik Kleyheeg1, Helmut Kruckenberg3
1Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology, Am Obstberg 1, 78315 Radolfzell, Germany.
Royal Society Open Science
|August 16, 2018
Summary
This study introduces a periodic Markov model to simulate animal migration patterns, revealing seasonal population densities and network dynamics. This tool aids in understanding climate change and pathogen spread impacts on migratory species.
Area of Science:
- Ecology
- Mathematical Biology
- Zoology
Background:
- Animal migrations impact ecosystems through trophic interactions and organism transport.
- The spatial dynamics of migration flyways are crucial but understudied.
- Understanding migration patterns is vital for conservation and disease ecology.
Purpose of the Study:
- To develop a formal model for describing animal migration at the population level.
- To analyze the spatial structure and dynamic properties of migration networks.
- To investigate the effects of climate and habitat change on migratory animals.
Main Methods:
- Proposed a periodic Markov model on a spatial migration network.
- Derived seasonal animal densities from time-varying transition rates.
- Parametrized the model using GPS and satellite telemetry data from white storks and geese.
Main Results:
- The model generated stable, seasonal animal densities at network nodes.
- Derived migration networks exhibited properties like changing connectivity and directed movement.
- Modelled networks accurately reflected population-level migration dynamics.
Conclusions:
- The periodic Markov model realistically describes population migration.
- This model is a valuable tool for studying climate change and pathogen spread effects.
- Further research is needed to understand the dynamic properties of this novel model type.
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