A HITCHHIKER'S GUIDE TO WATERBIRD MIGRATION

van Toor, Marielle

A HITCHHIKER'S GUIDE TO WATERBIRD MIGRATION

Dateien

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Datum

2016

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Biologie

Publikationstyp

Dissertation

Publikationsstatus

Published

Zusammenfassung

The ability to move profits the mobile individual, but also makes it a potential vector for nutrients, pathogens, and propagules. Moving animals thus have the potential to impose effects at an ecological scale that far surpasses the immediate consequences for the single moving individual itself. Long-distance migrants, which are estimated to comprise billions of individuals each year, exert a tremendous potential to link ecosystems, or even continents. In a time that the global phenomenon of long-distance migration is slowly starting to disappear, we are only beginning to understand the drivers and ecological impact of these seasonal mass movements. Technological advances and the miniaturisation of tracking devices allow us to peer ever deeper into the life of individuals, yet these observations remain hard to generalise over large numbers of individuals. Turning to an increasing diversity of movement models, however, offers the possibilities to describe and generalise animal movement by quantitative means. While this provides the opportunity to replicate the underlying movement process, these models often cannot account for the immediate environmental context under which movement occurred. Animals, however, do not move randomly through space, and the incorporation of environmental information into predicting both the causes and effects of massive, long-distance migrations is essential. I develop a framework that integrates movement models with environmental information using movement data collected from several species of Asian waterbirds as a model system. This framework incorporates both the environmental context of simulated trajectories and the habitat use of the species and specifically acknowledges that both environment and habitat use can be subject to seasonal changes. This is mainly achieved by identifying periods of time during which the habitat use of individuals is constant directly from empirical tracking data. Therefore, I introduce a novel segmentation approach for animal movement data in chapter 1. I show that this segmentation approach is able to identify relevant changes in habitat use caused by changes in both the available environment and habitat utilisation using simulations, and apply the method to data collected for the common teal (Anas crecca, Linnaeus 1758). In chapter 2, I explore whether temporally dynamic predictions of habitat suitability that are derived after a segmentation can, in combination with movement simulation, make ecologically sensible predictions of migratory movements. I expand a recently developed movement model to account for the typical migratory strategy of the bar-headed goose (Anser indicus, Latham 1790) and derive a metric to evaluate the ecological likelihood of simulated migratory trajectories. This chapter shows that a combination of predicted habitat suitability at stopover sites and metrics of simulated trajectories can reflect our knowledge of this species’ movements within its native range both in space and time even in areas for which no tracking data were available. Finally, I apply this framework to data from bar-headed geese and the ruddy shelduck (Tadorna ferruginea, Pallas 1764) to estimate their contribution to the dispersal of avian influenza A virus H5N1 under the assumption that both of these species are able to transport the virus between stopover sites. Even though the dispersal patterns of a pathogen with a variety of hosts are likely more complex than assumed in this chapter, I was able to explain a significant portion of the virus diffusion across the Asian continent by incorporating both geographic distance and the environmentally informed movement simulations.
In conclusion, this thesis presents one approach how to derive quantitative predictions of how, when, and where animals might move through heterogeneous landscapes from empirical tracking data. I think that the framework established in this thesis is sufficiently flexible to be adapted for a diversity of applications. While this work is only an initial step to understand the complexity of global migration, the results show how movement models can profit from the integration of the environmental context of animal movement.

Fachgebiet (DDC)

570 Biowissenschaften, Biologie

Zitieren

ISO 690

VAN TOOR, Marielle, 2016. A HITCHHIKER'S GUIDE TO WATERBIRD MIGRATION [Dissertation]. Konstanz: University of Konstanz

BibTex

@phdthesis{vanToor2016HITCH-43649,
  year={2016},
  title={A HITCHHIKER'S GUIDE TO WATERBIRD MIGRATION},
  author={van Toor, Marielle},
  address={Konstanz},
  school={Universität Konstanz}
}

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    <dcterms:abstract xml:lang="eng">The ability to move profits the mobile individual, but also makes it a potential vector for nutrients, pathogens, and propagules. Moving animals thus have the potential to impose effects at an ecological scale that far surpasses the immediate consequences for the single moving individual itself. Long-distance migrants, which are estimated to comprise billions of individuals each year, exert a tremendous potential to link ecosystems, or even continents. In a time that the global phenomenon of long-distance migration is slowly starting to disappear, we are only beginning to understand the drivers and ecological impact of these seasonal mass movements. Technological advances and the miniaturisation of tracking devices allow us to peer ever deeper into the life of individuals, yet these observations remain hard to generalise over large numbers of individuals. Turning to an increasing diversity of movement models, however, offers the possibilities to describe and generalise animal movement by quantitative means. While this provides the opportunity to replicate the underlying movement process, these models often cannot account for the immediate environmental context under which movement occurred. Animals, however, do not move randomly through space, and the incorporation of environmental information into predicting both the causes and effects of massive, long-distance migrations is essential. I develop a framework that integrates movement models with environmental information using movement data collected from several species of Asian waterbirds as a model system. This framework incorporates both the environmental context of simulated trajectories and the habitat use of the species and specifically acknowledges that both environment and habitat use can be subject to seasonal changes. This is mainly achieved by identifying periods of time during which the habitat use of individuals is constant directly from empirical tracking data. Therefore, I introduce a novel segmentation approach for animal movement data in chapter 1. I show that this segmentation approach is able to identify relevant changes in habitat use caused by changes in both the available environment and habitat utilisation using simulations, and apply the method to data collected for the common teal (Anas crecca, Linnaeus 1758). In chapter 2, I explore whether temporally dynamic predictions of habitat suitability that are derived after a segmentation can, in combination with movement simulation, make ecologically sensible predictions of migratory movements. I expand a recently developed movement model to account for the typical migratory strategy of the bar-headed goose (Anser indicus, Latham 1790) and derive a metric to evaluate the ecological likelihood of simulated migratory trajectories. This chapter shows that a combination of predicted habitat suitability at stopover sites and metrics of simulated trajectories can reflect our knowledge of this species’ movements within its native range both in space and time even in areas for which no tracking data were available. Finally, I apply this framework to data from bar-headed geese and the ruddy shelduck (Tadorna ferruginea, Pallas 1764) to estimate their contribution to the dispersal of avian influenza A virus H5N1 under the assumption that both of these species are able to transport the virus between stopover sites. Even though the dispersal patterns of a pathogen with a variety of hosts are likely more complex than assumed in this chapter, I was able to explain a significant portion of the virus diffusion across the Asian continent by incorporating both geographic distance and the environmentally informed movement simulations.&lt;br /&gt;In conclusion, this thesis presents one approach how to derive quantitative predictions of how, when, and where animals might move through heterogeneous landscapes from empirical tracking data. I think that the framework established in this thesis is sufficiently flexible to be adapted for a diversity of applications. While this work is only an initial step to understand the complexity of global migration, the results show how movement models can profit from the integration of the environmental context of animal movement.</dcterms:abstract>
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Prüfungsdatum der Dissertation

November 25, 2016

Hochschulschriftenvermerk

Konstanz, Univ., Diss., 2016