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

• Published in: Movement Ecology
• Main Authors: Gurarie, Eliezer, Fleming, Christen H., Fagan, William F., Laidre, Kristin L., Hernández-Pliego, Jesús, Ovaskainen, O.
• Other Authors: 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
• Language: unknown
• Published: BioMed Central 2017
• Subjects: Correlated velocity movement; Velocity autocovariance function; Correlated random walks; Integrated; Ornstein-Uhlenbeck process; Balaena mysticetus; Thermal soaring; Falco naumanni; Norway; bowhead whale
• 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

[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 ...