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A cross-validation-based approach for delimiting reliable home range estimates.

Eric R Dougherty1, Colin J Carlson1, Jason K Blackburn2,3

  • 1Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA USA.

Movement Ecology
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Summary
This summary is machine-generated.

This study introduces an objective cross-validation method to optimize Time Local Convex Hull (T-LoCoH) parameters for animal movement analysis. This approach provides more reliable home range comparisons than subjective guidelines.

Keywords:
DurationEpidemiologyHome rangeT-LoCoHTime Local Convex HullsVisitationcross-validation

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Area of Science:

  • Ecology
  • Quantitative Biology
  • Spatial Ecology

Background:

  • Exponential growth in animal movement data from GPS telemetry.
  • Development of complex statistical tools for movement path analysis.
  • Limitations in existing methods, including subjectivity in Time Local Convex Hull (T-LoCoH) parameter selection.

Purpose of the Study:

  • To present a cross-validation approach for optimizing T-LoCoH parameters.
  • To address the subjectivity in T-LoCoH parameter selection.
  • To enable more objective analysis of animal home ranges.

Main Methods:

  • Developed a cross-validation-based algorithm for parameter selection.
  • Applied and demonstrated the method using a case study in Etosha National Park.
  • Optimized the Time Local Convex Hull (T-LoCoH) algorithm.

Main Results:

  • The proposed algorithm yielded significantly different site fidelity metrics compared to T-LoCoH documentation guidelines.
  • Demonstrated a more objective parameter selection process.
  • Highlighted the impact of parameter choice on derived movement metrics.

Conclusions:

  • Cross-validation offers an objective alternative to subjective T-LoCoH guidelines.
  • Enables more accurate comparisons of home ranges across individuals, species, and studies.
  • Enhances the utility of T-LoCoH for ecological research.