Document: JAS-3-56-22

A general model of selectivity for fish feeding: A rank proportion algorithm.

LINK, J.S.* and S.J.WHIPPLE

National Marine Fisheries Service, Woods Hole, MA 02543, USA ¹

Abstract:
Predator-prey interactions can ultimately determine the fate and flux of every population in an ecosystem, particularly upper level consumers of fiscal importance. Thus, the impacts and dynamics of fish feeding have implications for nearly every aquatic ecosystem. Given that varying prey are available to fish in a particular ecosystem, by default fish feed selectively. Studies of fish feeding ecology have provided key insights into the dynamics of aquatic ecosystems, yet diet selectivity is the least addressed component of these studies. This may be due to the higher level of effort associated with examining both the stomach contents and ambient prey abundance, the assumption that a determined diet composition is static, or the lack of a predictive protocol for a priori estimates of selectivity/composition. We present a rank proportion algorithm (RPA) that predicts diet composition from ambient prey concentrations and first principles of predation. We applied our model for benthivore, planktivore, and piscivore examples from lentic, lotic, estuartine, and marine ecosystems. Validating RPA model predictions of diet composition with observed stomach contents exhibits >90% model accuracy. Bayesian resampling statistics showed the model results were significantly different than random assignment of ranks. Our results suggest that the RPA may be a useful tool to apply when stomach composition data is limited but required for other applications, and a general knowledge of the predation process may be useful to obtain quantitative information of fish diet.

Keywords: Prey Selectivity, Predation Algorithm, Model

This abstract is being presented at: 11:00 AM in session:
Oral Session #70: Aquatic Ecology.