Publikation: Observing the unwatchable through acceleration logging of animal behavior
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
Behavior is an important mechanism of evolution and it is paid for through energy expenditure. Nevertheless, field biologists can rarely observe animals for more than a fraction of their daily activities and attempts to quantify behavior for modeling ecological processes often exclude cryptic yet important behavioral events. Over the past few years, an explosion of research on remote monitoring of animal behavior using acceleration sensors has smashed the decades-old limits of observational studies. Animal-attached accelerometers measure the change in velocity of the body over time and can quantify fine-scale movements and body postures unlimited by visibility, observer bias, or the scale of space use. Pioneered more than a decade ago, application of accelerometers as a remote monitoring tool has recently surged thanks to the development of more accessible hardware and software. It has been applied to more than 120 species of animals to date. Accelerometer measurements are typically collected in three dimensions of movement at very high resolution (>10 Hz), and have so far been applied towards two main objectives. First, the patterns of accelerometer waveforms can be used to deduce specific behaviors through animal movement and body posture. Second, the variation in accelerometer waveform measurements has been shown to correlate with energy expenditure, opening up a suite of scientific questions in species notoriously difficult to observe in the wild. To date, studies of wild aquatic species outnumber wild terrestrial species and analyses of social behaviors are particularly few in number. Researchers of domestic and captive species also tend to report methodology more thoroughly than those studying species in the wild. There are substantial challenges to getting the most out of accelerometers, including validation, calibration, and the management and analysis of large quantities of data. In this review, we illustrate how accelerometers work, provide an overview of the ecological questions that have employed accelerometry, and highlight the emerging best practices for data acquisition and analysis. This tool offers a level of detail in behavioral studies of free-ranging wild animals that has previously been impossible to achieve and, across scientific disciplines, it improves understanding of the role of behavioral mechanisms in ecological and evolutionary processes.
Zusammenfassung in einer weiteren Sprache
El comportamiento es un mecanismo importante de la evolución y que se paga a través del gasto de energía. Sin embargo, los biólogos de campo raramente observan los animales durante más de una fracción de sus actividades y los intentos de cuantificar el comportamiento para el modelado de los procesos ecológicos a menudo excluyen eventos crípticos pero importantes. En los últimos años se produjeron avances importantes en el monitoreo remoto del comportamiento de los animales, utilizando sensores de telemétro de aceleración (acelerómetros) que empujan los límites tradicionales de los estudios observacionales. Acelerómetros unidos a los animales miden el cambio de la velocidad del cuerpo en el tiempo y pueden cuantificar los movimientos a escala fina y posturas corporales ilimitadas por la visibilidad, el sesgo del observador, o la escala de la utilización del espacio. Como pionero hace más de una década, la aplicación de los acelerómetros como una herramienta de monitoreo remoto ha aumentado recientemente debido al desarrollo de hardware y software más accesibles. Se ha aplicado a más de 120 especies de animales hasta hoy. Medidas de los acelerómetros se recogen típicamente en tres dimensiones de movimiento a muy alta resolución (>10 Hz), y hasta ahora se han aplicado hacia dos objetivos principales. Primero, los patrones de las formas de los acelerómetros de onda se pueden utilizar para deducir comportamientos específicos a través de movimiento de los animales y la postura corporal. Segundo, se ha demonstrado que la variación en las medidas de forma de los acelerómetros de onda se ha demostrado que se correlaciona con el gasto de energía, abriendo una serie de preguntas de carácter científico sobre especies muy difíciles de observar en la naturaleza. Hasta la fecha, los estudios de las especies acuáticas silvestres superan a las especies terrestres silvestres, y los análisis de los comportamientos sociales son muy pocos en número. Los investigadores de las especies domésticas y en cautiverio tienden a reportar metodología más completa que los que estudian las especies silvestres. Hay retos importantes para conseguir el máximo rendimiento de los acelerómetros, incluyendo la validación, calibración y gestión y análisis de grandes cantidades de datos. En esta revisión se ilustra cómo funciona el acelerómetro, se proporciona una visión general de las investigaciones ecológicas que han empleado los acelerómetros y se destacan las mejores prácticas emergentes para la adquisición y análisis de datos. Esta herramienta ofrece un nivel de detalle en los estudios de comportamiento de los animales salvajes que han sido hasta ahora imposibles de alcanzar y, en todas las disciplinas científicas, que mejora la comprensión del papel de los mecanismos de comportamiento de los procesos ecológicos y evolutivos.
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
BROWN, Danielle D., Roland KAYS, Martin WIKELSKI, Rory WILSON, A. Peter KLIMLEY, 2013. Observing the unwatchable through acceleration logging of animal behavior. In: Animal Biotelemetry. 2013, 1(1), 20. ISSN 2050-3385. eISSN 2050-3385. Available under: doi: 10.1186/2050-3385-1-20BibTex
@article{Brown2013Obser-28087, year={2013}, doi={10.1186/2050-3385-1-20}, title={Observing the unwatchable through acceleration logging of animal behavior}, number={1}, volume={1}, issn={2050-3385}, journal={Animal Biotelemetry}, author={Brown, Danielle D. and Kays, Roland and Wikelski, Martin and Wilson, Rory and Klimley, A. Peter}, note={Article Number: 20} }
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/123456789/28087"> <dc:contributor>Klimley, A. Peter</dc:contributor> <dc:creator>Brown, Danielle D.</dc:creator> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/28087"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-06-11T08:59:14Z</dcterms:available> <dc:creator>Wikelski, Martin</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-06-11T08:59:14Z</dc:date> <dcterms:title>Observing the unwatchable through acceleration logging of animal behavior</dcterms:title> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:contributor>Wikelski, Martin</dc:contributor> <dcterms:issued>2013</dcterms:issued> <dc:creator>Wilson, Rory</dc:creator> <dc:contributor>Wilson, Rory</dc:contributor> <dc:contributor>Brown, Danielle D.</dc:contributor> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/28087/1/Brown_280876.pdf"/> <dc:creator>Klimley, A. Peter</dc:creator> <dc:contributor>Kays, Roland</dc:contributor> <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/2.0/"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/28087/1/Brown_280876.pdf"/> <dc:language>eng</dc:language> <dcterms:abstract xml:lang="eng">Behavior is an important mechanism of evolution and it is paid for through energy expenditure. Nevertheless, field biologists can rarely observe animals for more than a fraction of their daily activities and attempts to quantify behavior for modeling ecological processes often exclude cryptic yet important behavioral events. Over the past few years, an explosion of research on remote monitoring of animal behavior using acceleration sensors has smashed the decades-old limits of observational studies. Animal-attached accelerometers measure the change in velocity of the body over time and can quantify fine-scale movements and body postures unlimited by visibility, observer bias, or the scale of space use. Pioneered more than a decade ago, application of accelerometers as a remote monitoring tool has recently surged thanks to the development of more accessible hardware and software. It has been applied to more than 120 species of animals to date. Accelerometer measurements are typically collected in three dimensions of movement at very high resolution (>10 Hz), and have so far been applied towards two main objectives. First, the patterns of accelerometer waveforms can be used to deduce specific behaviors through animal movement and body posture. Second, the variation in accelerometer waveform measurements has been shown to correlate with energy expenditure, opening up a suite of scientific questions in species notoriously difficult to observe in the wild. To date, studies of wild aquatic species outnumber wild terrestrial species and analyses of social behaviors are particularly few in number. Researchers of domestic and captive species also tend to report methodology more thoroughly than those studying species in the wild. There are substantial challenges to getting the most out of accelerometers, including validation, calibration, and the management and analysis of large quantities of data. In this review, we illustrate how accelerometers work, provide an overview of the ecological questions that have employed accelerometry, and highlight the emerging best practices for data acquisition and analysis. This tool offers a level of detail in behavioral studies of free-ranging wild animals that has previously been impossible to achieve and, across scientific disciplines, it improves understanding of the role of behavioral mechanisms in ecological and evolutionary processes.</dcterms:abstract> <dcterms:bibliographicCitation>Animal Biotelemetry ; 1 (2013). - 20</dcterms:bibliographicCitation> <dc:rights>Attribution 2.0 Generic</dc:rights> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Kays, Roland</dc:creator> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/> </rdf:Description> </rdf:RDF>