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Mesh sticking probability in fishing gear selectivity: Methodology and case study on Norway lobster (Nephrops norvegicus) and mantis shrimp (Squilla mantis) in the Mediterranean Sea creel fishery

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Fish or crustaceans stuck in the fishing gear meshes can lead to operational problems in some fisheries and thereby affect the
economic gain. However, mesh sticking probability has never been formally quantified as a part of the estimation of fishing gear
size selectivity. Therefore, this study developed a size selection model and estimation procedure that, besides the size dependent
retention and escape probabilities, includes the size dependent mesh sticking probability. The new method was applied to quantify the size dependent retention, sticking and escape probabilities for mantis shrimp (Squilla mantis) and Norway lobster (Nephrops norvegicus) in creels with 41 mm square mesh netting. The mesh sticking probability was found to display a bell-shaped curvature with a maximum value for a specific carapace length and decreasing probabilities for both smaller and bigger individuals. For mantis shrimp the maximum sticking probability was found for 32.5 mm carapace length with a value at 13.5%, while 63.1% and 23.4% of that size were respectively retained inside the creels and escaped. For Norway lobster the maximum sticking probability
was 2% and occurred for 34.0 mm carapace length. The method and estimation procedure presented in this study might be applicable for quantifying mesh sticking probability as an integral part of future fishing gear size selectivity studies on other species
and fisheries.


Sticking probability; selectivity; Norway lobster; mantis shrimp; creels

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Anonymus, 2011. Atlas of Demersal Discarding, Scientific Observations and Potential Solutions. Marine Institute, Bord Iascaigh Mhara. 82 pp.

Anonymus, 2015. Pravilnik o obavljanju gospodarskog ribolova na moru mrežama

stajaćicama, klopkastim, udičarskim i probodnim ribolovnim alatima te posebnim

načinima ribolova. Narodne novine br.: 84.

Arkley, 2001. Improving Selectivity in Towed Fishing Gears - Guidelines on the Rigging of Square Mesh Panels. SEAFISH, 24 pp.

Brčić, J., Herrmann, B., Mašanović, M., Baranović, M., Šifner, S.K., et al., 2018a. Size selection of Nephrops norvegicus (L.) in commercial creel fishery in the Mediterranean Sea. Fisheries Research, 200, 25-32.

Brčić, J., Herrmann, B., Mašanović, M., Krstulović Šifner, S.K., et al., 2018b. CREELSELECT—A method for determining the optimal creel mesh: Case study on Norway lobster (Nephrops norvegicus) fishery in the Mediterranean Sea. Fisheries Research, 204, 433-440.

Chernick, M.R., 2007. Bootstrap methods: a guide for practitioners and researchers. Wiley, New York. 400 pp.

Efron, B., 1982. The jackknife, the bootstrap and other resampling plans. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 100 pp.

Eriksson, S.P., 2006. Differences in the condition of Norway lobsters (Nephrops norvegicus (L.)) from trawled and creeled fishing areas. Marine Biology Research, 2, 52–58.

Fryer, R., 1991. A model of the between-haul variation in selectivity. ICES Journal of Marine Science, 48 (3), 281-290.

Hamer, D.J., Goldsworthy, S.D., 2006. Seal–fishery operational interactions: Identifying the environmental and operational aspects of a trawl fishery that contribute to by-catch and mortality of Australian fur seals (Arctocephalus pusillus doriferus). Biological Conservation, 130 (4), 517-529.

Herrmann, B., Sistiaga, M., Nielsen, K.N., Larsen, R.B., 2012. Understanding the size selectivity of redfish (Sebastes spp.) in North Atlantic trawl codends. Journal of Northwest Atlantic fishery science, 44, 1–13.

Hovgård, H., Lassen, H. 2000. Manual on estimation of selectivity for gillnet and longline gears in abundance surveys. FAO, FAO Fisheries Technical Paper No. 397, 84pp.

ICES. 2012. Report of the ICES-FAO Working Group on Fishing Technology and Fish Behaviour (WGFTFB). ICES CM 2012/SSGESST:07, 206 pp.

Krag, L.A., Herrmann, B., Karlsen, J.D., 2014. Inferring Fish Escape Behaviour in Trawls Based on Catch Comparison Data: Model Development and Evaluation Based on Data from Skagerrak, Denmark. PLoS ONE, 9 (2), e88819. https://doi.org/10.1371/journal.pone.0088819.

Larsen, R.B., Herrmann, B., Sistiaga, M., Brinkhof, J., Tatone, I., et al., 2018. New approach for modelling size selectivity in shrimp trawl fisheries. ICES Journal of Marine Science, 75 (1), 351-360.

Løkkeborg, S., 2011. Best practices to mitigate seabird bycatch in longline, trawl and gillnet fisheries—efficiency and practical applicability. Marine Ecology Progress Series, 435, 285-303.

Pol, M.V., Herrmann, B., Rillahan, C., He, P., 2016. Impact of codend mesh sizes on selectivity and retention of Acadian redfish Sebastes fasciatus in the Gulf of Maine trawl fishery. Fisheries Research 184, 54-63.

Rahikainen, M., Peltonen, H., Pönni, J., 2004. Unaccounted mortality in northern Baltic Sea herring fishery—magnitude and effects on estimates of stock dynamics. Fisheries Research, 67, 111-127.

Ridgway, I.D., Taylor, A.C., Atkinson, R.J.A., Chang, E.S., Neil, D.M., 2006. Impact of

capture method and trawl duration on the health status of the Norway lobster,

Nephrops norvegicus. Journal of Experimental Marine Biology and Ecology 339 (2), 135–147.

Sistiaga, M., Herrmann, B., Grimaldo, E., O’Neill, F., 2016. Estimating the selectivity of unpaired trawl data: a case study with a pelagic gear. Scientia Marina, 80 (3), 321-327.

Weimerskirch, H., Capdeville, D., Duhamel, G., 2000. Factors affecting the number and mortality of seabirds attending trawlers and long-liners in the Kerguelen area. Polar Biology, 23 (4), 236-249.

Wileman, D., Ferro, R.S.T., Fonteyne, R., Millar, R.B., 1996. Manual of methods of measuring the selectivity of towed fishing gears. ICES Cooperative Research Report No. 215., 132 pp.


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