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Imputation Approaches for Animal Movement Modeling

  • Henry Scharf
  • Mevin B. Hooten
  • Devin S. Johnson
Article

Abstract

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals (Callorhinus ursinus) in the Bering Sea. Supplementary materials accompanying this paper appear online.

Keywords

Animal movement models Hierarchical models Telemetry data Multiple imputation 

Notes

Acknowledgements

The authors thank Ephraim Hanks for early insights and discussions about the research. Funding for this research was provided by NOAA (RWO 103), CPW (TO 1304), and NSF (DMS 1614392). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Supplementary material

13253_2017_294_MOESM1_ESM.pdf (3.9 mb)
Supplement A: Implementation details This document contains implementation details and additional results for both simulation studies and the appllication to the movement of a Northern fur seal. (PDF 3.91MB)
13253_2017_294_MOESM2_ESM.zip (3.4 mb)
Supplement B: Application vignette This vignette shows how the two-stage process imputation procedure was implemented for the application to the movement of a Norther fur seal. (ZIP 3.38MB)

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Copyright information

© International Biometric Society 2017

Authors and Affiliations

  1. 1. Department of StatisticsColorado State UniversityFort CollinsUSA
  2. 2.U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife, and Conservation Biology, Department of Statistics, Colorado State UniversityFort CollinsUSA
  3. 3.Alaska Fisheries Science Center, NOAA FisheriesSeattleUSA

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