Bivariate Gaussian bridges : directional factorization of diffusion in Brownian bridge models

Lade...
Vorschaubild
Dateien
Kranstauber_2-1lm6746h5egst7.pdf
Kranstauber_2-1lm6746h5egst7.pdfGröße: 2.89 MBDownloads: 166
Datum
2014
Autor:innen
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Gold
Sammlungen
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Movement Ecology. BioMed Central. 2014, 2, 5. eISSN 2051-3933. Available under: doi: 10.1186/2051-3933-2-5
Zusammenfassung

Background
In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion.

Results
Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk.

Conclusion
We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the “move” package for R.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
570 Biowissenschaften, Biologie
Schlagwörter
Dynamic Bivariate Gaussian bridge, Dynamic Brownian bridge movement model, Utilisation distribution, Animal tracking, GPS, Home range and space use modelling
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690KRANSTAUBER, Bart, Kamran SAFI, Frederic BARTUMEUS, 2014. Bivariate Gaussian bridges : directional factorization of diffusion in Brownian bridge models. In: Movement Ecology. BioMed Central. 2014, 2, 5. eISSN 2051-3933. Available under: doi: 10.1186/2051-3933-2-5
BibTex
@article{Kranstauber2014Bivar-52040,
  year={2014},
  doi={10.1186/2051-3933-2-5},
  title={Bivariate Gaussian bridges : directional factorization of diffusion in Brownian bridge models},
  volume={2},
  journal={Movement Ecology},
  author={Kranstauber, Bart and Safi, Kamran and Bartumeus, Frederic},
  note={Article Number: 5}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/52040">
    <dc:language>eng</dc:language>
    <dc:creator>Kranstauber, Bart</dc:creator>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/52040/3/Kranstauber_2-1lm6746h5egst7.pdf"/>
    <dcterms:title>Bivariate Gaussian bridges : directional factorization of diffusion in Brownian bridge models</dcterms:title>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:contributor>Safi, Kamran</dc:contributor>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/52040"/>
    <dcterms:abstract xml:lang="eng">Background&lt;br /&gt;In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion.&lt;br /&gt;&lt;br /&gt;Results&lt;br /&gt;Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk.&lt;br /&gt;&lt;br /&gt;Conclusion&lt;br /&gt;We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the “move” package for R.</dcterms:abstract>
    <dc:rights>Attribution 2.0 Generic</dc:rights>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-12-08T09:47:34Z</dcterms:available>
    <dcterms:issued>2014</dcterms:issued>
    <dc:creator>Safi, Kamran</dc:creator>
    <dc:contributor>Bartumeus, Frederic</dc:contributor>
    <dc:creator>Bartumeus, Frederic</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-12-08T09:47:34Z</dc:date>
    <dc:contributor>Kranstauber, Bart</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/52040/3/Kranstauber_2-1lm6746h5egst7.pdf"/>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Begutachtet
Ja
Diese Publikation teilen