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dc.contributor.author
Pennekamp, Frank
dc.contributor.author
Schtickzelle, Nicolas
dc.contributor.author
Petchey, Owen L.
dc.date.accessioned
2019-06-18T11:49:05Z
dc.date.available
2017-06-11T23:22:16Z
dc.date.available
2019-06-18T11:49:05Z
dc.date.issued
2015-07
dc.identifier.other
10.1002/ece3.1529
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/110930
dc.identifier.doi
10.3929/ethz-b-000110930
dc.description.abstract
Microbes are critical components of ecosystems and provide vital services (e.g., photosynthesis, decomposition, nutrient recycling). From the diverse roles microbes play in natural ecosystems, high levels of functional diversity result. Quantifying this diversity is challenging, because it is weakly associated with morphological differentiation. In addition, the small size of microbes hinders morphological and behavioral measurements at the individual level, as well as interactions between individuals. Advances in microbial community genetics and genomics, flow cytometry and digital analysis of still images are promising approaches. They miss out, however, on a very important aspect of populations and communities: the behavior of individuals. Video analysis complements these methods by providing in addition to abundance and trait measurements, detailed behavioral information, capturing dynamic processes such as movement, and hence has the potential to describe the interactions between individuals. We introduce BEMOVI, a package using the R and ImageJ software, to extract abundance, morphology, and movement data for tens to thousands of individuals in a video. Through a set of functions BEMOVI identifies individuals present in a video, reconstructs their movement trajectories through space and time, and merges this information into a single database. BEMOVI is a modular set of functions, which can be customized to allow for peculiarities of the videos to be analyzed, in terms of organisms features (e.g., morphology or movement) and how they can be distinguished from the background. We illustrate the validity and accuracy of the method with an example on experimental multispecies communities of aquatic protists. We show high correspondence between manual and automatic counts and illustrate how simultaneous time series of abundance, morphology, and behavior are obtained from BEMOVI. We further demonstrate how the trait data can be used with machine learning to automatically classify individuals into species and that information on movement behavior improves the predictive ability.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Wiley
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Microbial ecology
en_US
dc.subject
Microcosm
en_US
dc.subject
Trait-based ecology
en_US
dc.subject
Video analysis
en_US
dc.title
BEMOVI, software for extracting behavior and morphology from videos, illustrated with analyses of microbes
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Ecology and Evolution
ethz.journal.volume
5
en_US
ethz.journal.issue
13
en_US
ethz.pages.start
2584
en_US
ethz.pages.end
2595
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.nebis
007041168
ethz.publication.place
S.l.
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02720 - Institut für Integrative Biologie / Institute of Integrative Biology::03705 - Jokela, Jukka / Jokela, Jukka
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02720 - Institut für Integrative Biologie / Institute of Integrative Biology::03705 - Jokela, Jukka / Jokela, Jukka
ethz.date.deposited
2017-06-11T23:22:47Z
ethz.source
ECIT
ethz.identifier.importid
imp593653fd2699112031
ethz.ecitpid
pub:172228
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-13T07:20:14Z
ethz.rosetta.lastUpdated
2019-06-18T11:49:16Z
ethz.rosetta.versionExported
true
ethz.COinS
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