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This study investigated the selectivity parameters of bottom longlines for the Whiting (Merlangius merlangus euxinus) in the small-scale fisheries of the Southeastern Black Sea. Experimental fishing operations were conducted using longlines with hook of 11, 12, 13, and 14mm gaps. A total of 552 fish specimens from four species were captured, with Whiting, the target species, accounting for 90.94% (502 specimens) of the total catch by numbers. The sizes of the Whiting ranged from 10.6 to 20.0 cm Total Length (TL), with a mean size of 15.79 ± 0.087 cm TL. The longline selectivity parameters and curves were fitted using the SELECT method, with the bi-modal model offering the best-fit, based on the lowest deviance value. The modal sizes of specimens caught using the hook of 11, 12, 13, and 14-mm gaps were 12.40, 13.53, 14.66, and 15.78 cm TL, respectively. The modal sizes and spread values increased proportionally with hook size. All the individuals caught by the 14-mm gap hooks exceeded the minimum landing size (MLS) of 13 cm. However, the proportions of individuals below the MLS for the 11, 12, and 13-mm gap hooks were 32.09%, 6.98%, and 0.68%, respectively. Based on the MLS, hooks with gaps larger than 11 mm were found to be highly selective and are recommended for sustainability of the fisheries while ensuring the conservation of immature individuals in the Whiting stocks of the Black Sea. These findings contribute to the much-needed data and information for the design of sound management plans for the small-scale fisheries in the region. • Longlines are an extremely suitable and convenient fishing gear for the rational use and management of fish stocks. • Selective and suitable hook size can be a simple and low-cost way to reduce immature fish and by-catch in longline fishery. • Hooks with gaps larger than 11 mm are suggested for sustainable fishery and conservation of whiting stocks in the Black Sea. • Longline fishing targeting whiting will be an important gain for the protection of stocks and their sustainable use. • Longline fishing targeting whiting will be an important gain for the protection of stocks and their sustainable use. [ABSTRACT FROM AUTHOR]

This study was conducted to determine the selectivity of the hooks used for bluefish (Pomatomus saltatrix Linneaus, 1766) in the Gallipoli Peninsula and the Dardanelles between 2006 and 2009 fishing seasons (November to September). Bluefish were fished with hooks sized 1, 1/0, 2/0, 3/0, 4/0 and in sum; 1210 bluefish were caught. The hook no 2/0 caught the highest number of fish (344 fish, 20.43%) and the hook no 1 caught the least (35 fish, 2.89%). Length frequency distribution of bluefish, which were caught with different hook sizes, was used in SELECT method and according to the results; the normal scale model gave the best fit for selectivity. The normal scale model was used to calculate model length (ML) and spread value (SV) of each hook size. Model length and spread value were found as follows; 19.18 cm ML and 4.44 SV for hook no. 1; 21.88 cm ML, 5.07 SV for hook no 1/0; 24.14 cm ML, 5.59 SV for hook no. 2/0; 27.02 cm ML, 6.26 SV for hook no. 3/0; 28.19 cm ML, 6.53 SV for hook no. 4/0, respectively. Because the minimum landing size (MLS) for bluefish has been stipulated as 20.0 cm (TL) in the Turkish Fishery Regulations, the use of hook no. 2/0 or bigger hook sizes can be recommended for fishing of bluefish.

In this study, it was aimed to determine the selectivity properties of the gillnets used for Shabbout (Arabibarbus grypus Heckel, 1843) in Keban Dam Lake, Turkey. Experiments were carried out at 3 different stations of the dam lake using 5 monofilament gillnets with 40, 50, 60, 70, 80 mm nominal mesh size (bar length). A total of 510 target species between 38 and 79.2 cm in total length were caught in 47 catching trials. The select method was used to estimate the selectivity parameters. When the model deviations were compared, the lowest deviation (183.6104) was observed to be given by the lognormal model. According to this model, optimum catch lengths of nets which have 40, 50, 60, 70, 80 mm mesh size determined as 40.12, 50.15, 60.18, 70.21, 80.24 cm and their spread values 3.03, 3.79, 4.55, 5.30, 6.06 cm, respectively. The differences between the length frequencies of the fish caught by all nets were found to be significant according to the Kolmogorav- Smirnov test. Minimum catch size of Shabbout is notified as 45 cm in Turkey. According to results of this study, gillnets with 50 mm and above mesh size do not cause an overfishing on Shabbout stocks. [ABSTRACT FROM AUTHOR]

The size selectivity of crayfish traps (fyke-nets) with 34, 38 or 42 mm mesh size and with diamond-shaped (D) or hexagonal-shaped (Hex) mesh was compared for narrow-clawed crayfish Astacus leptodactylus Eschscholtz, 1823 in the Eğirdir Lake, Turkey. The SELECT model was used to fit the logistic selection curves and to calculate selectivity parameters. The selectivity curves and parameters were calculated by comparing the size frequencies of the crayfish retained in the traps, including the 34 mm diamond (D) trap control. The 50%-selectivity length (l50) and selection range (SR) of fyke-net traps with diamond mesh were 8.70 cm and 3.16 cm for 38 mm (38 D) and 8.69 cm and 1.99 cm for 42 mm (42 D) bar length. The l50 and SR values of hexagonal mesh traps were 8.06 cm and 3.42 cm for 34 mm (34 Hex), 10.23 cm and 2.80 cm for 38 mm (38 Hex) and 11.00 cm and 2.62 cm for 42 mm (42 Hex) bar length, respectively. [ABSTRACT FROM AUTHOR]

The present study estimated the size-selectivity of Hipposcarus harid and Lethrinus harak caught in monofilament trammel nets of 50, 56, and 62 mm inner-panel mesh sizes. Fishing was carried out in the coral reef fisheries of Jeddah during the period from June 2013 to March 2014. The selectivity parameters were calculated using the SELECT method implemented in Pasgear 2 software. The normal location, normal scale, log-normal, gamma and bi-modal selectivity models were fitted to the data to estimate the selectivity curves. Results indicated that the log-normal model provided the best fit based on the lowest deviance value. Modal lengths estimated from the log-normal selectivity curves are: 19.73, 22.10, and 24.46 cm for H. harid, 18.41, 20.62, and 22.83 cm for L. harak caught with 50, 56 and 62 mm inner-panel mesh sizes, respectively. The length–girth relationship was estimated and described by the linear equation: G = 0.480 + 0.70 L (r2 = 0.95) for H. harid, and G = 0.73 L − 0.65 (r2 = 0.96) for L. harak. For proper management of H. harid and L. harak, the minimum inner-panel mesh size should be 62 mm to catch fish sizes larger than the length at maturity for both species.

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Fishing trials were carried out with gill nets and trammel nets in the northern Aegean Sea from March 2004 to February 2005. Four different mesh sizes for the gill nets and the inner panel of trammel nets (16, 18, 20 and 22 mm bar length) were used. Selectivity parameters for the five most economically important species, bogue (Boops boops), annular sea bream (Diplodus annularis), striped red mullet (Mullus surmuletus), axillary sea bream (Pagellus acarne) and blotched picarel (Spicara maena), caught by the two gears were estimated. The SELECT method was used to estimate the selectivity parameters of a variety of models. Catch composition and catch proportion of several species were different in gill and trammel nets. The length frequency distributions of the species caught by the two gears were significantly different. The bi-modal model selectivity curve gave the best fit for gill net and trammel net data, and there was little difference between the modal lengths of these nets. However, a clear difference was found in catching efficiency. The highest catch rates were obtained with the trammel net. Given that many discard species and small fish are caught by gill nets and trammel nets with a mesh size of 16 mm, it is clear that these nets are not appropriate for fisheries. Consequently, the best mesh size for multispecies fisheries is 18 mm. This mesh size will considerably reduce the numbers of small sized individuals and discard species in the catch.

The impact of the gillnet fishery on Merluccius merluccius (European hake) was investigated in the northern Tyrrhenian Sea, western Mediterranean. Four mesh sizes were tested: 53, 62.5, 70 and 82 mm. Horse mackerel (Trachurus trachurus), hake and tub gurnard (Chelidonichthys lucerna) dominated the catches, from a minimum of 89% (82 mm mesh) to a maximum of 97.8% (70 mm) of the biomass caught. Efficiency of the four meshes was not significantly different with respect to the total hake catches. Selectivity on M. merluccius was assessed by Sechin and SELECT methods. Tangling was an important catch modality for hake, as evidenced by the results of the Sechin model which described only the first mode of the size distributions corresponding to the entangled specimens. SELECT showed that the bi-modal function gave the best adjustment to the length-frequency distributions; the modal catch sizes were 33, 39.2, 43.6 and 51 cm total length respectively for the 53, 62.5, 70 and 82 mm mesh sizes. Taking into account the size of first maturity for females (35.1 cm TL), 62.5 mm is the most adequate mesh for exploiting hake as it gives some protection to both immature specimens and large females.

The present study estimated the size-selectivity of Hipposcarus harid and Lethrinus harak caught in monofilament trammel nets of 50, 56, and 62 mm inner-panel mesh sizes. Fishing was carried out in the coral reef fisheries of Jeddah during the period from June 2013 to March 2014. The selectivity parameters were calculated using the SELECT method implemented in Pasgear 2 software. The normal location, normal scale, log-normal, gamma and bi-modal selectivity models were fitted to the data to estimate the selectivity curves. Results indicated that the log-normal model provided the best fit based on the lowest deviance value. Modal lengths estimated from the log-normal selectivity curves are: 19.73, 22.10, and 24.46 cm for H. harid , 18.41, 20.62, and 22.83 cm for L. harak caught with 50, 56 and 62 mm inner-panel mesh sizes, respectively. The length–girth relationship was estimated and described by the linear equation: G = 0.480 + 0.70 L ( r 2 = 0.95) for H. harid , and G = 0.73 L − 0.65 ( r 2 = 0.96) for L. harak . For proper management of H. harid and L. harak , the minimum inner-panel mesh size should be 62 mm to catch fish sizes larger than the length at maturity for both species. [ABSTRACT FROM AUTHOR]

We evaluated the statistical models that best describe the selectivity of common fishing gears used in Lake Koka for four freshwater species widely distributed in Ethiopia and elsewhere: tilapia Oreochromis niloticus (L.), catfish Clarias gariepinus (B.), common carp Cyprinus carpio (L.), and barb Labeobarbus intermedius (R.). Sampling was conducted from October 2012 to March 2013 using gillnets (60, 80, 100, and 120 mm stretched mesh), longlines (4/0, 6/0, and 8/0 hooks size), and a beach seine with covered codend. Size at maturity ( L) was determined for each species. The SELECT method was used to explore unimodal selectivity models for gillnet and longline gears, while the logistic function was used for beach seine. Results show that a log-normal model best described gillnet selectivity for all species, while a normal scale model best described longline selectivity for C. gariepinus. Gillnets with ≥100 mm mesh and longlines with >4/0 hooks could be safely used, as they allow target resources to attain L before becoming vulnerable to fishing. The mesh size of the beach seine needs to be enlarged, as the estimated length of capture was much smaller than all L values. The results have important management implications for protecting juveniles and mega-spawners of the studied species in Lake Koka and beyond. [ABSTRACT FROM AUTHOR]

Abstract: Multimesh nylon gillnets were set in three Ebro Delta (North-East of Spain) lagoons to determine mesh selectivity for the inhabiting fish community. Each gillnet consisted on a series of twelve panels of different mesh size (ranging from 5.0 to 55.0 mm bar length) randomly distributed. The SELECT method (Share Each Length’s Catch Total) was used to estimate retention curves through five models: normal location, normal scale, gamma, lognormal and inverse Gaussian. Each model was fitted twice, under the assumptions of equal and proportional to mesh size fishing effort, but no differences were found between approaches. A possible situation of overfishing in the lagoons, where artisanal fisheries are carried out with a low surveillance effort, was assessed using a vulnerable species inhabiting these brackish waters as case study: the sand smelt, Atherina boyeri. The minimum size for its fishery has not been established, thus remaining under an uncontrolled exploitation situation. Therefore, a Minimum Landing Size (MLS) is proposed based on sexual maturity data. The importance of establishing an adequate MLS and regulate mesh sizes in order to respect natural maturation length is discussed, as well as, the proposal of other measures to improve A. boyeri fishery management. [Copyright &y& Elsevier]

The catch of red tilefish by the Japanese longline fishery in the East China Sea has steeply declined during the last two decades, and resource management is clearly required. This study presents the size selectivity of hooks for red tilefish as a method to control first capture size, based on the results of longline fishing experiments using “Tainawa-bari” hooks of several sizes: Japanese nominal sizes J#10, J#11, J#12, J#13, J#14 and J#16. On the assumption of geometrical similarity in the combination of upper jaw length u and hook width g at a given retention probability, a single master curve s( R) = exp (−14.42 + 8.85 R)/(1 + exp [−14.42 + 8.85 R]) was estimated in terms of relative upper jaw length to hook width, R = u/ g, using the SELECT method based on a multinomial distribution. The relative upper jaw length for 50% retention is 1.63, and the selection range is 0.25. Almost all fish over 300 mm in total length were retained by a hook of size J#12, but smaller fish with less commercial value were also caught. Moreover, J#10 hooks catch fish with total lengths of >250 mm efficiently. This indicates that J#10 and J#12 hooks that are currently used are too small to optimize yield per recruit and also for resource conservation. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the paired-gear and covered cod-end methods for estimating the selectivity of trawl cod-ends are compared. A modified version of the cod-end selectivity simulator PRESEMO is used to simulate the data that would be collected from a paired-gear experiment where the test cod-end also had a small mesh cover. Thus, estimates of the selectivity parameters of the test cod-end can be made using both the paired-gear method and the covered cod-end method. These estimates are compared and, as it is assumed that the covered cod-end method is objective, we conclude that the paired-gear method is biased. We demonstrate that extreme parameter estimates as well as discrepancies between the paired-gear and covered cod-end experiments do not necessarily reflect physical or biological mechanisms. We believe that this phenomenon may help explain cases in the literature where the covered cod-end and paired-gear methods produce different estimates of cod-end selectivity. [Copyright &y& Elsevier]

The selectivity of fishing gear can vary considerably from set to set even when deployment is replicated under controlled conditions. Analysis of data from size-selectivity experiments will be misleading if this between-deployment variability is not taken into consideration. Here, two approaches are presented for including the effect of between-haul variability when performing size-selectivity experiments for trawls. The first is a simple ad hoc approach that provides a “catch-all” estimate of variability that also takes into account the effect of subsampling the catches. The second is a formal model of random between-haul variability that is fitted via maximum likelihood. The two approaches are applied to both covered-codend and twin-trawl selectivity experiments. The first method is seen to be more intuitive and interpretable, especially when selectivity may depend on catch size, but is limited in its ability to cope with complex experimental designs. [Copyright &y& Elsevier]

The log-linear modelling capabilities of existing statistical software permit a generalization of Holt's indirect estimation method by allowing several different selection curve models to be fitted to catch data from an arbitrary number of mesh sizes. This also facilitates the use of formal inferential procedures such as model selection, assessment of relative fishing powers, estimation of standard errors, and permits inclusion of knowledge regarding the shape of the population length distribution. This methodology is equally applicable to estimation of hook selectivity. [ABSTRACT FROM PUBLISHER]

When the catches in the components (cod-end and cover, say) of experimental trawl selectivity gear are sampled then the length-class frequencies of the catches can be estimated by multiplying the frequencies in the samples by the inverse of the sampling fractions. The statistical properties of selection curves fitted to these estimated catch frequencies are unknown, and consequently goodness of fit cannot be checked and trawl selectivity studies cannot be designed. It is shown that a statistically well-behaved procedure is obtained by working directly with the raw data whereby the estimated selection curve is obtained from the fitting of a related curve to these raw data. For covered cod-end trials in which a logistic selection curve is assumed the related curve is also logistic and no modifications to existing software are required. this facilitated an investigation of the efficiency of three different sampling strategies: to sample from the cod-end and cover either (1) the same weight of fish; (2) the same number of fish; or (3) the same fraction of fish. Strategy (1) was found to be the least efficient. Strategies (2) and (3) had similar performance, with strategy (2) slightly better overall. [ABSTRACT FROM PUBLISHER]