Correlated velocity models as a fundamental unit of animal movement : synthesis and applications

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dc.contributor.author Gurarie, Eliezer
dc.contributor.author Fleming, Christen H.
dc.contributor.author Fagan, William F.
dc.contributor.author Laidre, Kristin L.
dc.contributor.author Hernandez-Pliego, Jesus
dc.contributor.author Ovaskainen, Otso
dc.date.accessioned 2018-02-23T13:10:01Z
dc.date.available 2018-02-23T13:10:01Z
dc.date.issued 2017-05-10
dc.identifier.citation Gurarie , E , Fleming , C H , Fagan , W F , Laidre , K L , Hernandez-Pliego , J & Ovaskainen , O 2017 , ' Correlated velocity models as a fundamental unit of animal movement : synthesis and applications ' , Movement Ecology , vol. 5 , 13 . https://doi.org/10.1186/s40462-017-0103-3
dc.identifier.other PURE: 99362934
dc.identifier.other PURE UUID: 7f88cd43-1866-42b1-a335-986046ca4357
dc.identifier.other WOS: 000401116900001
dc.identifier.other Scopus: 85018383009
dc.identifier.uri http://hdl.handle.net/10138/232829
dc.description.abstract Background: Continuous time movement models resolve many of the problems with scaling, sampling, and interpretation that affect discrete movement models. They can, however, be challenging to estimate, have been presented in inconsistent ways, and are not widely used. Methods: We review the literature on integrated Ornstein-Uhlenbeck velocity models and propose four fundamental correlated velocity movement models (CVM's): random, advective, rotational, and rotational-advective. The models are defined in terms of biologically meaningful speeds and time scales of autocorrelation. We summarize several approaches to estimating the models, and apply these tools for the higher order task of behavioral partitioning via change point analysis. Results: An array of simulation illustrate the precision and accuracy of the estimation tools. An analysis of a swimming track of a bowhead whale (Balaena mysticetus) illustrates their robustness to irregular and sparse sampling and identifies switches between slower and faster, and directed vs. random movements. An analysis of a short flight of a lesser kestrel (Falco naumanni) identifies exact moments when switches occur between loopy, thermal soaring and directed flapping or gliding flights. Conclusions: We provide tools to estimate parameters and perform change point analyses in continuous time movement models as an R package (smoove). These resources, together with the synthesis, should facilitate the wider application and development of correlated velocity models among movement ecologists. en
dc.format.extent 18
dc.language.iso eng
dc.relation.ispartof Movement Ecology
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject Correlated velocity movement
dc.subject Velocity autocovariance function
dc.subject Correlated random walk
dc.subject Integrated Ornstein-Uhlenbeck process
dc.subject Balaena mysticetus
dc.subject Thermal soaring
dc.subject Falco naumanni
dc.subject BROWNIAN-MOTION
dc.subject RANDOM-WALKS
dc.subject TIME
dc.subject MIGRATION
dc.subject SPACE
dc.subject CHALLENGES
dc.subject SELECTION
dc.subject ECOLOGY
dc.subject PATH
dc.subject 1181 Ecology, evolutionary biology
dc.title Correlated velocity models as a fundamental unit of animal movement : synthesis and applications en
dc.type Article
dc.contributor.organization Otso Ovaskainen / Principal Investigator
dc.contributor.organization Biosciences
dc.contributor.organization Centre of Excellence in Metapopulation Research
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1186/s40462-017-0103-3
dc.relation.issn 2051-3933
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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