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  Citation Number 3
 Views 22
Predicting the Size Selectivity Based on the Striped Red Mullet Morphology (Mullus surmuletus) in Bottom Trawl Fisheries
2018
Journal:  
Aquatic Sciences and Engineering
Author:  
Abstract:

DOI: 10.26650/ASE201817 The striped red mullet (Mullus surmuletus) is a commercially important demersal species caught by mixed trawl fishing in the Mediterranean Sea. Although it is not among the target species of bottom trawl operations, the striped red mullet is an important species due to its high commercial value in trawl catch composition. The primary target is to catch adult individuals while allowing the immature and juvenile fish to escape for sustainable fisheries using selective fishing gears. Various selectivity studies regarding trawl codends aimed at improving selectivity have been carried out in the past two decades. However, the selectivity sea trials generally require a great deal of work, time, and labor on the deck and are also expensive. Therefore, instead of experimental-based selectivity studies, simulation-based studies (i.e., the FISHSELECT methodology) were recently started to predict the size selectivity of species in bottom trawl fisheries. In this study, sampled individuals of the striped red mullet were used in morphological measurements, fall-through experiments, and simulation phases. Diamond mesh sizes of 40, 44, and 50 mm and a square mesh size of 40 mm of bottom trawl codends were simulated, and the L50 values were calculated as 9.87, 10.75, 12.19, and 12.3 cm for the aforementioned mesh sizes, respectively. Design guides were then created for various mesh sizes and opening angles. The study results were compared with those of previous studies on the red mullet (M. barbatus) that were conducted using the FISHSELECT methodology, and the selectivity results of these two species were found to be similar.

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Aquatic Sciences and Engineering

Field :   Fen Bilimleri ve Matematik; Mühendislik

Journal Type :   Uluslararası

Metrics
Article : 234
Cite : 343
2023 Impact : 0.094
Aquatic Sciences and Engineering