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Toward a Sustainable Fishery Management Policy: An Artificial Neural Network Model for Predicting Bull Shark (Carcharhinus Leucas) Presence

Toward a Sustainable Fishery Management Policy: An Artificial Neural Network Model for Predicting Bull Shark (Carcharhinus Leucas) Presence
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Author(s): Steven P. Coy (University of Houston-Downtown, USA), Margaret F. Shipley (University of Houston-Downtown, USA) and J. Brooke Shipley-Lozano (Coastal Fisheries - Artificial Reef Program, USA)
Copyright: 2017
Pages: 22
Source title: Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0788-8.ch067

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Abstract

This article proposes an Artificial Neural Network (ANN) model to predict neonatal and juvenile bull shark habitat usage in the Sabine Pass, located within the Gulf of Mexico between Louisiana and Texas. Given continuing discussion regarding overfishing of all shark species, including bull sharks, in the northwestern Atlantic and Gulf of Mexico, the research objective was to analyze environmental data proven to be conducive to bull shark early life stages and to use these data in an ANN to predict bull shark presence during late spring and throughout summer months at designated sampling sites. The results of this analysis can both aid decision making in a fisheries context and inform the discussion on bull shark habitat usage in general, thereby contributing to the discussion of whether or not the need exists for conservation efforts to ensure sustainability of the species as part of an effective bull shark management plan.

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