Publikation:

Integrating animal tracking and trait data to facilitate global ecological discoveries

Lade...
Vorschaubild

Dateien

Beltran_2-1iiwovhjw7u8a8.pdf
Beltran_2-1iiwovhjw7u8a8.pdfGröße: 1.81 MBDownloads: 3

Datum

2025

Autor:innen

Beltran, Roxanne S.
Kilpatrick, A. Marm
Adamczak, Stephanie K.
Beumer, Larissa T.
Czapanskiy, Max F.
McLean, Bryan S.
Mueller, Thomas
Payne, Allison R.
Soria, Carmen D.
et al.

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

DOI (zitierfähiger Link)
ArXiv-ID

Internationale Patentnummer

Link zur Lizenz

Angaben zur Forschungsförderung

U.S. National Science Foundation (NSF): IOS 2052497
U.S. National Science Foundation (NSF): DBI 2228385
U.S. National Science Foundation (NSF): DEB-1717498
U.S. National Science Foundation (NSF): DEB-1911853

Projekt

Open Access-Veröffentlichung
Open Access Hybrid
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published

Erschienen in

Journal of Experimental Biology. The Company of Biologists. 2025, 228(Suppl_1), jeb247981. ISSN 0022-0949. eISSN 1477-9145. Verfügbar unter: doi: 10.1242/jeb.247981

Zusammenfassung

Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
570 Biowissenschaften, Biologie

Schlagwörter

Biologging, Integration, Macroecology, Repository, Tracking data, Trait data

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690BELTRAN, Roxanne S., A. Marm KILPATRICK, Stephanie K. ADAMCZAK, Larissa T. BEUMER, Max F. CZAPANSKIY, Sarah C. DAVIDSON, Bryan S. MCLEAN, Thomas MUELLER, Allison R. PAYNE, Carmen D. SORIA, 2025. Integrating animal tracking and trait data to facilitate global ecological discoveries. In: Journal of Experimental Biology. The Company of Biologists. 2025, 228(Suppl_1), jeb247981. ISSN 0022-0949. eISSN 1477-9145. Verfügbar unter: doi: 10.1242/jeb.247981
BibTex
@article{Beltran2025-02-15Integ-72863,
  title={Integrating animal tracking and trait data to facilitate global ecological discoveries},
  year={2025},
  doi={10.1242/jeb.247981},
  number={Suppl_1},
  volume={228},
  issn={0022-0949},
  journal={Journal of Experimental Biology},
  author={Beltran, Roxanne S. and Kilpatrick, A. Marm and Adamczak, Stephanie K. and Beumer, Larissa T. and Czapanskiy, Max F. and Davidson, Sarah C. and McLean, Bryan S. and Mueller, Thomas and Payne, Allison R. and Soria, Carmen D.},
  note={Article Number: jeb247981}
}
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/123456789/72863">
    <dc:creator>Mueller, Thomas</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2025-04-02T07:42:54Z</dc:date>
    <dc:contributor>Beltran, Roxanne S.</dc:contributor>
    <dc:creator>Beumer, Larissa T.</dc:creator>
    <dc:contributor>Kilpatrick, A. Marm</dc:contributor>
    <dc:contributor>Soria, Carmen D.</dc:contributor>
    <dc:creator>Soria, Carmen D.</dc:creator>
    <dc:contributor>Adamczak, Stephanie K.</dc:contributor>
    <dc:creator>Czapanskiy, Max F.</dc:creator>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:creator>Kilpatrick, A. Marm</dc:creator>
    <dc:creator>Adamczak, Stephanie K.</dc:creator>
    <dc:contributor>Davidson, Sarah C.</dc:contributor>
    <dc:language>eng</dc:language>
    <dcterms:title>Integrating animal tracking and trait data to facilitate global ecological discoveries</dcterms:title>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/72863"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/72863/1/Beltran_2-1iiwovhjw7u8a8.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dc:creator>Davidson, Sarah C.</dc:creator>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2025-04-02T07:42:54Z</dcterms:available>
    <dc:contributor>Czapanskiy, Max F.</dc:contributor>
    <dc:contributor>Mueller, Thomas</dc:contributor>
    <dcterms:issued>2025-02-15</dcterms:issued>
    <dcterms:abstract>Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.</dcterms:abstract>
    <dc:creator>McLean, Bryan S.</dc:creator>
    <dc:contributor>Beumer, Larissa T.</dc:contributor>
    <dc:contributor>Payne, Allison R.</dc:contributor>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/72863/1/Beltran_2-1iiwovhjw7u8a8.pdf"/>
    <dc:rights>Attribution 4.0 International</dc:rights>
    <dc:contributor>McLean, Bryan S.</dc:contributor>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
    <dc:creator>Beltran, Roxanne S.</dc:creator>
    <dc:creator>Payne, Allison R.</dc:creator>
  </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
Nein
Begutachtet
Ja
Diese Publikation teilen