aniMotum, an R package for animal movement data: Rapid quality control, behavioural estimation and simulation

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. 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. 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. We highlight aniMotum's capabilities through three applications to real animal tracking data. Full R code for these and additional applications is included as Supporting Information, so users can gain a deeper understanding of how to use aniMotum for their own analyses.

Automated summary

Animal tracking data is vital for understanding the behavior, ecology, and physiology of mobile or cryptic species. Noise in the data due to imperfect measurement technologies can hinder meaningful signals, necessitating rigorous quality control in comprehensive analysis. State-space models are powerful tools to separate signal from noise, particularly for error-prone location data, enabling inference of animal movements. However, fitting these statistical models to diverse animal tracking data sets can be challenging and time-consuming. The R package aniMotum simplifies quality control and movement inference tasks for animal tracking data.