Analyzing telemetry data and translating it into meaningful indicators of fish welfare remains a challenge , as it is necessary to distinguish between typical and atypical behavior .
Entropy approaches can be used to analyze telemetry data and detect changes in fish behavior , providing valuable insights into fish welfare . Telemetry is an important tool for studying fish behavior and allows for the real-time monitoring of fish movements . However , analyzing telemetry data and translating it into meaningful indicators of fish welfare is a challenge . Entropy-based methods , which use information theory to quantify the complexity and unpredictability of animal behavior , provide a more comprehensive understanding of the animal state .
By analyzing data probability density function with entropy approaches , it is possible to identify atypical behavior that may indicate compromised welfare . These methods can detect irregularities in fish behavior and provide insight into the animal’s state.
Results and Discusion
Typical behavior is not a single type of distribution , but rather a set of distributions . Entropy analysis is an effective method for identifying atypical behavior in fish welfare assessment , as it provides a more robust evaluation of telemetry datasets than classical statistical analysis . Entropy analysis allows for continuous monitoring of behavior and can identify when fish start behaving atypically . It can also determine which fish and which values are atypical or typical . By analyzing the variability of feeding behavior , social interactions , and behavior in response to different environmental conditions or stressors , entropy analysis can provide insights into the complexity and variability of fish behavior and promote more effective management practices . Entropy approaches can help to improve telemetry data analysis and provide objective indicators of fish welfare for management and regulatory purposes.
The study received funding from the European Union’ s Horizon 2020 research and innovation programme under grant agreement N° 871108 (AQUAEXCEL3.0). This output reflects only the author’s view and the European Union cannot be held responsible for any use that may be made of the information contained therein.
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