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Dynamic time warping analysis of accelerometry data: a tool for interpreting fine-scale movement patterns during fish
Jacey C Van Wert1, Stephen D Johnston2, Quin V Johnston2
1Institute for Food and Agricultural Sciences, School of Forest, Fisheries, and Geomatic Sciences, Fisheries and Aquatic Sciences Program, University of Florida, PO Box 110410, 1745 McCarty Drive, Gainesville, FL 32611-0410, USA.
Conservation Physiology
|June 5, 2026
Summary
New dynamic time warping (DTW) methods analyze fish capture data from accelerometers, linking fight dynamics to physiological stress and improving catch-and-release conservation strategies.
Area of Science:
- Fisheries Science
- Animal Physiology
- Conservation Biology
Background:
- Post-release survival in fisheries is unpredictable, often due to a lack of understanding of capture-induced physiological stress.
- Current management relies on uniform survival estimates, which do not account for variable capture event dynamics.
- Accelerometers on fishing lines offer a way to quantify fish fight dynamics but traditional analysis methods obscure fine-scale temporal patterns.
Purpose of the Study:
- To introduce a dynamic time warping (DTW) toolbox for analyzing accelerometer data from fish capture events.
- To link fine-scale fight behavior patterns to physiological disturbance in captured fish.
- To evaluate the effectiveness of DTW-based approaches compared to traditional summary statistics for predicting physiological outcomes.
Main Methods:
- Tri-axial jerk accelerometers ('jerk' tags) were attached to fishing lines to record capture events of Chinook and coho salmon.
- Physiological disturbance was quantified by measuring blood pH and plasma lactate levels one hour post-capture.
- Thirteen analytical pipelines, including summary metrics and DTW approaches on raw and processed jerk data, were systematically evaluated.
Main Results:
- Both summary metrics and DTW approaches captured different dimensions of the fish-fight relationship.
- Summary metrics broadly described fight patterns and grouped fish with similar fight signatures.
- DTW analysis identified specific Y-axis movement patterns that correlated with individual fish recovery, indicated by plasma lactate levels.
Conclusions:
- The DTW toolbox preserves temporal data structure, offering a more nuanced understanding of capture dynamics and physiological stress.
- This approach is transferable across species and accelerometer types, requiring only attachment to angling gear.
- Systematic evaluation of analytical pipelines, including DTW, enables optimized inference and the development of evidence-based conservation practices for improved catch-and-release outcomes.
