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Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
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Recursive filtering for zero offset correction of diving depth time series with GNU R package diveMove.

Sebastián P Luque1, Roland Fried

  • 1Department of Biological Sciences, University of Manitoba, Winnipeg, Canada. spluque@gmail.com

Plos One
|February 8, 2011
PubMed
Summary
This summary is machine-generated.

A new Free Software method using GNU R package diveMove corrects diving depth data from time-depth recorders. This reliable technique accurately removes artifacts, ensuring better analysis of marine animal diving behavior.

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Area of Science:

  • Marine Biology
  • Animal Behavior
  • Data Science

Background:

  • Diving depth data from time-depth recorders require zero offset correction due to pressure transducer inaccuracies.
  • Current correction methods are proprietary, limiting researcher control and transparency.

Purpose of the Study:

  • To introduce and evaluate a novel, transparent method for zero offset correction of diving depth data.
  • To provide a Free Software alternative for accurate data processing in diving behavior studies.

Main Methods:

  • Implementation of a recursive smoothing and filtering procedure using moving quantiles within the GNU R package diveMove.
  • Evaluation using a "perfect" dataset corrupted with noise and comparison with original data from an Antarctic fur seal.

Main Results:

  • The developed method demonstrated high accuracy, with Root Mean Square Error comparable to introduced noise levels.
  • The procedure proved flexible and efficient across diverse species and sampling protocols.

Conclusions:

  • The diveMove package offers a reliable and transparent solution for zero offset correction in diving behavior research.
  • This Free Software approach enhances data integrity and researcher control over time-depth recorder data analysis.