A morphological and geometric method for estimating the selectivity of gill nets
We propose a new method for estimating gill net selectivity which estimates the probabilities leading to retention by analyzing both the fish morphology and the mesh geometry. This method estimates the number of fish approaching and contacting gill nets of different mesh sizes as an intermediate step towards computing the selectivity. Instead of assuming an underlying probability distribution as in indirect methods, we split the entire interaction between a fish and the gill net into several stages, each with its own probability. All the necessary parameters to compute these probabilities can be obtained from measurements of the fish, knowledge of the mesh geometry, and catch data from different mesh sizes. The framework offers three pathways for computing the total number of fish contacting the gill nets and has the capability to use both wedged and entangled fish in the analysis. As a proof of concept, the method is applied to catch data for cod (G. morhua) and Dolly Varden (S. malma) to estimate the number of fish contacting the gill nets in both cases. By estimating the number of fish contacting the gill net in addition to the selectivity, this method provides an important step towards deriving estimates of fish density in a particular fishery from gill net measurement.
KeywordsGill nets Mathematical modeling Selectivity
The authors would like to acknowledge Gregory Markevich for organizing the expedition to Kamchatka for data collection, A. Boosh, E. Saltykova, G. Sedash for their assistance in fishing and processing the fish, professor Kriksunov E.A., Burmensky V.A. and Charles Anderson, Adjunct Assistant Professor (Minnesota Department of Natural Resources). Partial funding to make this collaboration possible was provided by Anthony Vodacek through the Paul and Francena Miller Chair in International Education at RIT.
- Aleev IG (1963) Function and gross morphology in fish ([Available From the U. S. Dept. of Commerce, Clearinghouse for Federal Scientific and Technical Information, Springfield, Va.]). Israel Program for Scientific TranslationsGoogle Scholar
- Baranov FI (1914) The capture of fish by gillnets. Mater Poznaniyu Russ Rybolov 3(6):56–99 (Partially transl. from Russian by W. E. Ricker)Google Scholar
- Baranov FI (1948) Theory and assessment of fishing gear. Ch. 7, Theory of fishing with gillnets. Pishchepromizdat, Moscow. (Translation from Russian by Ontario Dept of Lands For., Maple, Ont., 45 pp.)Google Scholar
- Clark JR (1960) Report on selectivity of fishing gear. Can J Fish Aquat Sci 2:21–36Google Scholar
- Hansen MJ, Schorfhaar RG, Selgeby JH (1998) Gill-net saturation by lake trout in michigan waters of lake superior. North Am J Fish Manag 18(4):847–853. https://doi.org/10.1577/1548-8675(1998)018%3c0847:GNSBLT%3e2.0.CO;2 CrossRefGoogle Scholar
- Kendall MG, Moran PA (1963) Geometric probability. Charles Griffin and Company, LondonGoogle Scholar
- Lucas CE, Schaefer MB, Holt SJ, Beverton RJ (1960) Report on fishing effort and the effect of fishing on resources. J Fish Res Board Can 2:5–26Google Scholar
- Olsen S, Tjemsland J (1963) A method of finding an empirical total selection curve for gill nets, describing all means of attachment. S. 88–94. https://brage.bibsys.no/xmlui/handle/11250/114584
- Parrish BB (1963) Some remarks on selection processes in fishing operations. J Fish Res Board Can 5:166–170Google Scholar
- Treshev AI (1974) Scientific basis of fishery selectivity. Food Industry, MoscowGoogle Scholar