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Area of Science:

  • Ecology
  • Computational Biology
  • Data Science

Background:

  • Miniaturized biologging devices generate vast animal tracking datasets.
  • Numerous R packages exist for processing, visualizing, and analyzing this data.
  • Fragmentation and isolation of these tools challenge user selection.

Purpose of the Study:

  • To review and describe R packages for animal tracking data analysis.
  • To assess package documentation quality and user-friendliness.
  • To identify package interdependencies and community fragmentation.

Main Methods:

  • Categorization of 58 R packages based on a tracking data workflow (pre-processing, post-processing, analysis).
  • User survey to evaluate package documentation quality.
  • Network graph analysis to assess package connectivity.

Main Results:

  • 11 packages identified with good or excellent documentation.
  • One-third of packages operate in isolation, indicating community fragmentation.
  • Recommendations provided for users and developers.

Conclusions:

  • A structured workflow approach aids in understanding the R package landscape for movement ecology.
  • Improving documentation and inter-package links can enhance the utility of tracking analysis tools.
  • Addressing fragmentation is crucial for advancing the R movement-ecology programming community.