Correlated velocity models as a fundamental unit of animal movement: synthesis and applications
[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 literat...
Published in: | Movement Ecology |
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BioMed Central
2017
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Online Access: | http://hdl.handle.net/10261/149525 https://doi.org/10.1186/s40462-017-0103-3 https://doi.org/10.13039/100000001 https://doi.org/10.13039/501100000781 https://doi.org/10.13039/100000006 https://doi.org/10.13039/501100000780 https://doi.org/10.13039/501100003339 https://doi.org/10.13039/501100002341 https://doi.org/10.13039/501100011011 |
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ftcsic:oai:digital.csic.es:10261/149525 2024-02-11T10:02:18+01:00 Correlated velocity models as a fundamental unit of animal movement: synthesis and applications Gurarie, Eliezer Fleming, Christen H. Fagan, William F. Laidre, Kristin L. Hernández-Pliego, Jesús Ovaskainen, O. National Science Foundation (US) Academy of Finland European Research Council Research Council of Norway Office of Naval Research (US) Junta de Andalucía European Commission Consejo Superior de Investigaciones Científicas (España) 2017-05-10 http://hdl.handle.net/10261/149525 https://doi.org/10.1186/s40462-017-0103-3 https://doi.org/10.13039/100000001 https://doi.org/10.13039/501100000781 https://doi.org/10.13039/100000006 https://doi.org/10.13039/501100000780 https://doi.org/10.13039/501100003339 https://doi.org/10.13039/501100002341 https://doi.org/10.13039/501100011011 unknown BioMed Central Publisher's version http://dx.doi.org/10.1186/s40462-017-0103-3 Sí Movement Ecology 5(1): 13 (2017) 2051-3933 http://hdl.handle.net/10261/149525 doi:10.1186/s40462-017-0103-3 http://dx.doi.org/10.13039/100000001 http://dx.doi.org/10.13039/501100000781 http://dx.doi.org/10.13039/100000006 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100003339 http://dx.doi.org/10.13039/501100002341 http://dx.doi.org/10.13039/501100011011 28496983 open Correlated velocity movement Velocity autocovariance function Correlated random walks Integrated Ornstein-Uhlenbeck process Balaena mysticetus Thermal soaring Falco naumanni artículo http://purl.org/coar/resource_type/c_6501 2017 ftcsic https://doi.org/10.1186/s40462-017-0103-310.13039/10000000110.13039/50110000078110.13039/10000000610.13039/50110000078010.13039/50110000333910.13039/50110000234110.13039/501100011011 2024-01-16T10:23:03Z [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. EG, CF, and WF were supported by the US National Science Foundation under grants ABI-1062411 and ABI-1458748; OO and EG were funded in part by Academy of Finland (grants 129636 and 250444) and European Research Council (ERC Starting Grant 205905). EG was additionally funded by the ‘Animals on the Move’ NASA Grant Number NNX15AV92. OO was additionally funded by the Research Council of Norway (Centres of Excellence funding scheme, project number 223257). The bowhead whale data ... Article in Journal/Newspaper Balaena mysticetus bowhead whale Digital.CSIC (Spanish National Research Council) Norway Movement Ecology 5 1 |
institution |
Open Polar |
collection |
Digital.CSIC (Spanish National Research Council) |
op_collection_id |
ftcsic |
language |
unknown |
topic |
Correlated velocity movement Velocity autocovariance function Correlated random walks Integrated Ornstein-Uhlenbeck process Balaena mysticetus Thermal soaring Falco naumanni |
spellingShingle |
Correlated velocity movement Velocity autocovariance function Correlated random walks Integrated Ornstein-Uhlenbeck process Balaena mysticetus Thermal soaring Falco naumanni Gurarie, Eliezer Fleming, Christen H. Fagan, William F. Laidre, Kristin L. Hernández-Pliego, Jesús Ovaskainen, O. Correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
topic_facet |
Correlated velocity movement Velocity autocovariance function Correlated random walks Integrated Ornstein-Uhlenbeck process Balaena mysticetus Thermal soaring Falco naumanni |
description |
[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. EG, CF, and WF were supported by the US National Science Foundation under grants ABI-1062411 and ABI-1458748; OO and EG were funded in part by Academy of Finland (grants 129636 and 250444) and European Research Council (ERC Starting Grant 205905). EG was additionally funded by the ‘Animals on the Move’ NASA Grant Number NNX15AV92. OO was additionally funded by the Research Council of Norway (Centres of Excellence funding scheme, project number 223257). The bowhead whale data ... |
author2 |
National Science Foundation (US) Academy of Finland European Research Council Research Council of Norway Office of Naval Research (US) Junta de Andalucía European Commission Consejo Superior de Investigaciones Científicas (España) |
format |
Article in Journal/Newspaper |
author |
Gurarie, Eliezer Fleming, Christen H. Fagan, William F. Laidre, Kristin L. Hernández-Pliego, Jesús Ovaskainen, O. |
author_facet |
Gurarie, Eliezer Fleming, Christen H. Fagan, William F. Laidre, Kristin L. Hernández-Pliego, Jesús Ovaskainen, O. |
author_sort |
Gurarie, Eliezer |
title |
Correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
title_short |
Correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
title_full |
Correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
title_fullStr |
Correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
title_full_unstemmed |
Correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
title_sort |
correlated velocity models as a fundamental unit of animal movement: synthesis and applications |
publisher |
BioMed Central |
publishDate |
2017 |
url |
http://hdl.handle.net/10261/149525 https://doi.org/10.1186/s40462-017-0103-3 https://doi.org/10.13039/100000001 https://doi.org/10.13039/501100000781 https://doi.org/10.13039/100000006 https://doi.org/10.13039/501100000780 https://doi.org/10.13039/501100003339 https://doi.org/10.13039/501100002341 https://doi.org/10.13039/501100011011 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Balaena mysticetus bowhead whale |
genre_facet |
Balaena mysticetus bowhead whale |
op_relation |
Publisher's version http://dx.doi.org/10.1186/s40462-017-0103-3 Sí Movement Ecology 5(1): 13 (2017) 2051-3933 http://hdl.handle.net/10261/149525 doi:10.1186/s40462-017-0103-3 http://dx.doi.org/10.13039/100000001 http://dx.doi.org/10.13039/501100000781 http://dx.doi.org/10.13039/100000006 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100003339 http://dx.doi.org/10.13039/501100002341 http://dx.doi.org/10.13039/501100011011 28496983 |
op_rights |
open |
op_doi |
https://doi.org/10.1186/s40462-017-0103-310.13039/10000000110.13039/50110000078110.13039/10000000610.13039/50110000078010.13039/50110000333910.13039/50110000234110.13039/501100011011 |
container_title |
Movement Ecology |
container_volume |
5 |
container_issue |
1 |
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1790598234010288128 |