Experimental Predictions of The Functional Response of A Freshwater Fish

Authors

  • Gregory P. D. Murray,

    Corresponding author
    1. Centre for Conservation Ecology and Environmental Change, School of Applied Sciences, Bournemouth University, Bournemouth, Dorset, UK
    • Correspondence

      Gregory P. D. Murray, Christchurch House, Bournemouth University, Talbot Campus, Fern Barrow, Poole, Bournemouth, Dorset BH12 5BB, UK.

      E-mail: gmurray@bournemouth.ac.uk

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  • Richard A. Stillman,

    1. Centre for Conservation Ecology and Environmental Change, School of Applied Sciences, Bournemouth University, Bournemouth, Dorset, UK
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  • Rodolphe E. Gozlan,

    1. Centre for Conservation Ecology and Environmental Change, School of Applied Sciences, Bournemouth University, Bournemouth, Dorset, UK
    2. Unité Mixte de Recherche Biologie des Organismes et Écosystèmes Aquatiques (Institut de Recherche pour le Développement 207, Centre National de la Recherche Scientifique 7208, Muséum National d'Histoire Naturelle, Université Pierre et Marie Curie), Muséum National d'Histoire Naturelle, Paris Cedex, France
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  • J. Robert Britton

    1. Centre for Conservation Ecology and Environmental Change, School of Applied Sciences, Bournemouth University, Bournemouth, Dorset, UK
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Abstract

The functional response is the relationship between the feeding rate of an animal and its food density. It is reliant on two basic parameters; the volume searched for prey per unit time (searching rate) and the time taken to consume each prey item (handling time). As fish functional responses can be difficult to determine directly, it may be more feasible to measure their underlying behavioural parameters in controlled conditions and use these to predict the functional response. Here, we tested how accurately a Type II functional response model predicted the observed functional response of roach Rutilus rutilus, a visually foraging fish, and compared it with Type I functional response. Foraging experiments were performed by exposing fish in tank aquaria to a range of food densities, with their response captured using a two-camera videography system. This system was validated and was able to accurately measure fish behaviour in the aquaria, and enabled estimates of fish reaction distance, swimming speed (from which searching rate was calculated) and handling time to be measured. The parameterised Type II functional response model accurately predicted the observed functional response and was superior to the Type I model. These outputs suggest it will be possible to accurately measure behavioural parameters in other animal species and use these to predict the functional response in situations where it cannot be observed directly.

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