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Swimming performance assessment in fishes.

Journal of visualized experiments : JoVE | 2011

Swimming performance tests of fish have been integral to studies of muscle energetics, swimming mechanics, gas exchange, cardiac physiology, disease, pollution, hypoxia and temperature. This paper describes a flexible protocol to assess fish swimming performance using equipment in which water velocity can be controlled. The protocol involves one to several stepped increases in flow speed that are intended to cause fish to fatigue. Step speeds and their duration can be set to capture swimming abilities of different physiological and ecological relevance. Most frequently step size is set to determine critical swimming velocity (U(crit;)), which is intended to capture maximum sustained swimming ability. Traditionally this test has consisted of approximately ten steps each of 20 min duration. However, steps of shorter duration (e.g. 1 min) are increasingly being utilized to capture acceleration ability or burst swimming performance. Regardless of step size, swimming tests can be repeated over time to gauge individual variation and recovery ability. Endpoints related to swimming such as measures of metabolic rate, fin use, ventilation rate, and of behavior, such as the distance between schooling fish, are often included before, during and after swimming tests. Given the diversity of fish species, the number of unexplored research questions, and the importance of many species to global ecology and economic health, studies of fish swimming performance will remain popular and invaluable for the foreseeable future.

Pubmed ID: 21633333 RIS Download

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Noldus (tool)

RRID:SCR_004074

Commercial organization that develops tools and systems for measurement and analysis of animal and human behavior. They develop instrumented home cage systems, in which rodent behavior and ultrasonic vocalizations can be measured in a non-intrusive manner. Furthermore, they develop computer vision and pattern recognition technology for automated behavior detection. They believe that this approach has significant potential in research on animal models for Autism Spectrum Disorder.

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