Yingqi Zhou

Length-frequency compositions and weight-length relations for bigeye tuna, yellowfin tuna, and albacore (Perciformes: Scombrinae) in the Atlantic, Indian, and eastern Pacific oceans

The weight–length relation (WLR) is an important tool in fish biology, physiology, ecology, and fisheries assessment and has been originally used to provide information on the condition of fish and determine whether somatic growth is isometric or allometric (Ricker 1975, Oscoz et al. 2005). WLRs are useful in determining weight and biomass when only length measurements are available, as indications of condition and to allow for comparisons of species growth between different regions (Koutrakis and Tsikliras 2003). Bigeye tuna, Thunnus obesus (Lowe, 1839); yellowfin tuna, Thunnus albacares (Bonnaterre, 1788); and albacore, Thunnus alalunga (Bonnaterre, 1788), are the important commercial species in the tropical and subtropical waters of the Atlantic, Indian, and Pacific oceans (Driggers et al. 1999, Sun et al. 2001, Miao and Huang 2003, Farley et al. 2006). It constitutes an extremely valuable fishery resource intensively exploited by Asian longliners, and US and European purse seiners, at various stages of its life cycle (Stequert and Conand 2000). However, the stocks of the above tuna species, especially bigeye tuna, are almost on the verge of over-exploitation and may soon be regarded as overfished (Joseph 2003). It is crucial to the future existence of this economically important species that the best possible biological data on the species is provided to fisheries managers (Manooch and Hinkley 1991). This study contributes to the knowledge of the WLRs of bigeye tuna, yellowfin tuna and albacore of the Atlantic, Indian, and Pacific Oceans. ACTA ICHTHYOLOGICA ET PISCATORIA (2008) 38 (2): 157–161 DOI: 10.3750/AIP2008.38.2.12

Application of whole-implicit algorithm and virtual neural lattice in pelagic longline modeling

This study developed a whole-implicit algorithm and virtual neural lattice to model and simulate the dynamics of pelagic longline gear. The programming, model calculation and behavior simulation of longline dynamics were implemented in R language. Equilibrium state and stable solution of the models were reached. The hooks were more stable in the deepest water layer than that in the midwater layer. It indicated that the whole-implicit method and virtual neural lattice were high efficient and accurate in solving the complicated engineering equations of longline gear, also in the presentation of the motion of longline in sea water.

Modeling of Three-Dimensional Dynamical Behavior of Ropes Used in Fishery Based on R Language

Ropes are widely used in various kinds of fishing gear. In this paper, a numerical method is presented which is competent in predicting the three-dimensional dynamic behavior of cables. The dynamic behavior of cables were simulated using dynamical equations and R language. The method was based on the lump-mass and spring model and the implicit algorithm was applied to solve the stiff differential equations. The mathematics-mechanical analysis was provided on the basic characteristics of the model. The R platform was used in programming, simulation, and visualization of the results. The three-dimensional dynamic behavior of cables in different examples were presented successfully and verify the effectiveness of this method, and the motion process was consistent with the observed data in the ocean.