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Modelling escapement during the fishing process as a dual sequence – Introducing SELNET We compare modelling of selectivity data by two different models.

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Presentation on theme: "Modelling escapement during the fishing process as a dual sequence – Introducing SELNET We compare modelling of selectivity data by two different models."— Presentation transcript:

1 Modelling escapement during the fishing process as a dual sequence – Introducing SELNET We compare modelling of selectivity data by two different models. The data modelled were collected in experimental fishing trials using a multiSampler or a dualsampler. The purpose was to separate the fish escaping during towing at the seabed from the fish escaping at a later stage of the fishing process (haul-back and at surface). The first model lead to a description which is similar to what has previously been used to model and analyze this type of selectivity data (Madsen et al., 2008; Grimaldo et al., 2009). The second model is more flexible and contains the first at a special case. It adds another parameter that could actually be linked to fish behaviour, which is of special interest in this kind of selectivity experiments. We show results for a number of different species and demonstrate that the new model is better at describing the data in some of the cases. In addition, the values obtained for the behavioural linked parameter make sense when comparing the different species. For simplicity, we only show preliminary results for pooled hauls. The second model has a similar structure to the one applied by Zuur et al. (2001) to model escapement through an escapement panel and a codend separately. A new flexible software tool named SELNET has been developed to analyse these and other selectivity data for towed fishing gears. SELNET can handle collection and analysis of data for a number of different experimental designs such as covered codend, paired gear, catch comparison and catch data. Besides the standard curves Logit, Probit, log-log and Richard, SELNET contains a number of other curves (including the models we use in this study), which are derived from combining these. Experimental data Data from project survival for haddock and whiting were used. These have previously been published in Madsen et al. (2008). Data for Cod and Haddock published in Grimaldo et al. (2009) were also reanalyzed in this study. Yet unpublished, data on Plaice from a national Danish project SELTRA were also included in this study. Modeling the escapement process as dual sequence In this study, we are interested in modelling separately the escapement during towing at the seabed and the escapement which occurs during haul-back or at the surface. In the datasets where haul-back and surface escapement were collected separately, these two compartments were treated united. Therefore, the data to be modelled have the following structure: COVER1 (number of fish that escaped during towing), COVER2 (number of fish that escaped during haul-back or at surface), TEST (number of fish retained). The analysis is based on the number of fish of each length class present in each of these three compartments. Assuming that the fate of each fish is independent, the number of individuals of a specific length class l present in the three compartments (COVER1,COVER2, TEST) could be modelled by a Multinomial distribution with probabilities e 1 (l), e 2 (l), r(l). For fish attempting to escape through the codend during the two phases, we assume the success probability to be well represented by a logistic curve. For the escapement during the haul- back/surface phase, we assume that all fish get into contact with the netting. For the towing phase, we investigate two different models: one where we describe the escapement likelihood by a logit function and another one where we assume that only a length independent fraction C tow (number between 0.0 and 1.0) do attempt to escape. For the fraction attempting to escape we assume the probability to follow a logit function. Thus, all fish that do not escape during towing are susceptible of making attempts in the succeeding phase. Below, we show the two models: Model one contains 4 parameters (L50 tow, SR tow, L50 back, SR back ), which are estimated simultaneously by minimizing the function above. Model two contains an additional parameter C tow, which can be interpreted as a behavioural parameter describing how active the species is on attempting to contact the codend meshes during towing (contact factor towing). nt l is the number of fish of length l being retained in the test codend. nc1 l is the number that escaped to COVER1 and nc2 l the number that escaped to COVER2. Below results. Black curves stand for model one while grey curves represent model two. References Grimaldo, E., Larsen, R.B., Sistiaga, M., Madsen, N., Breen, M., Selectivity and escape percentages during three phases of the towing process for codends fitted with different selection systems. Fish. Res. 95, (**) Madsen, N., Skeide, R., Breen, M., Krag, L.,A., Huse, I., Soldal, A.V., Selectivity in trawl codend during haul-back operation – an overlooked phenomenon. Fish. Res. 91, (*) Zuur, G., Fryer, R.J., Ferro, R.S.T., Tokai, T., Modelling the size selectivity of a trawl codend and an associated square mesh panel. ICES J. Mar. Sci. 58: Bent Herrmann 1, Niels Madsen 1, Manu Sistiaga 2, Eduardo Grimaldo 3 Model 1 Model 2 Function to minimize 1 Denmark Technical University (DTU), North Sea Centre, DK-9850 Hirtshals, Denmark 2 Norwegian College of Fishery Science, Breivika, N-9037 Tromsø, Norway 3 SINTEF Fiskeri og Havbruk AS, Brattørkaia 17B, 7010 TRONDHEIM, Norway PlaiceWhiting Haddock * Haddock ** Cod Escape during haul- back/ surface: e 2 (l) Escape during tow: e 1 (l) Retention: r(l) Contact factor during towing: c tow 67%100% 86% 87%80% Results ICES FTFB 2009


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