DOI: 10.5061/dryad.qz612jmjw
title: Data from: aniMotum, an R package for animal movement data: rapid quality control, behavioural estimation and simulation

description: 1.  Animal tracking data are indispensable for understanding the
 ecology, behaviour and physiology of mobile or cryptic species. Meaningful
 signals in these data can be obscured by noise due to imperfect
 measurement technologies, requiring rigorous quality control as part of
 any comprehensive analysis.   2.  State-space models are
 powerful tools that separate signal from noise. These tools are ideal for
 quality control of error-prone location data and for inferring where
 animals are and what they are doing when they record or transmit other
 information. However, these statistical models can be challenging and
 time-consuming to fit to diverse animal tracking data sets.   3.
  The R package aniMotum eases the tasks of conducting quality
 control on and inference of changes in movement from animal tracking data.
 This is achieved via: 1) a simple but extensible workflow that
 accommodates both novice and experienced users; 2) automated processes
 that alleviate complexity from data processing and model
 specification/fitting steps; 3) simple movement models coupled with a
 powerful numerical optimization approach for rapid and reliable model
 fitting.   4.  We highlight
 aniMotum's capabilities through three applications to real
 animal tracking data. Full R code for these and additional applications
 are included as Supporting Information so users can gain a deeper
 understanding of how to use aniMotum for their own analyses. 
description: This datafile contains the data used by Jonsen et al. (in
 Applications 3.2 & 3.3) to highlight the capabilities of the
 aniMotum R package for analysis of animal tracking data. 
 The lipe_gps_ex32.csv file contains GPS-derived
 locations for 4 little penguins, recorded by AxyTrek data
 loggers. The lipe_pc_ex32.csv file contains processed
 prey capture events inferred from 3-D accelerometry data, recorded by
 AxyTrek data loggers. The sese_extra.csv file
 contains Argos-derived locations for 4 southern elephant seals (Jonsen et
 al. Appendix 3), transmitted by SMRU CTD satellite relay data
 loggers. The hase_ex33.csv file contains
 Argos-derived locations for 1 juvenile harp seal, recorded by SMRU
 satellite relay data loggers. See Jonsen
 et al. (main text and Supporting Information) for details on data
 pre-processing and all analysis code. For details on
 little penguin GPS and prey capture data see: Phillips, L., Carroll, G.,
 Jonsen, I., et al. Variability in prey field structure drives inter-annual
 differences in prey encounter by a marine predator, the little penguin.
 Royal Society Open Science, 9, 220028 (2022). For
 details on southern elephant seal Argos location data see: Jonsen, I.D.,
 McMahon, C.R., Patterson, T.A. et al. Movement responses to environment:
 fast inference of variation among southern elephant seals with a mixed
 effects model. Ecology, 100, e02566 (2019). For details
 on harp seal Argos location data see: Grecian, W.J., Stenson, G.B., Biuw,
 M. et al. Environmental drivers of population-level variation in the
 migratory and diving ontogeny of an arctic top predator. Royal Society
 Open Science, 9 (2022).