scholarly journals Discard Avoidance by Improving Fishing Gear Selectivity: Helping the Fishing Industry Help Itself

2018 ◽  
pp. 279-296 ◽  
Author(s):  
Finbarr G. O’Neill ◽  
Jordan Feekings ◽  
Robert J. Fryer ◽  
Laurence Fauconnet ◽  
Pedro Afonso
Keyword(s):  
Fishing Gear ◽  
Fishing Industry ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity

scholarly journals Assessment of a small-scale fishery: Lane Snapper (Lutjanus synagris) using a length metric method

2020 ◽  
Author(s):  
Liliana Sierra Castillo ◽  
Masami Fujiwara
Keyword(s):  
Small Scale ◽  
Fishing Gear ◽  
Optimal Length ◽  
Limited Availability ◽  
Small Scale Fisheries ◽  
Catch Data ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity ◽  
High Level

ABSTRACTSmall-scale fisheries are hard to assess because of the limited availability of data. Therefore, a method requiring easy-to-obtain catch-data is important for the assessment and management of small-scale fisheries. The objectives of this study were to assess the effect of fishing gear selectivity on a length-based metric method proposed by Froese by estimating three indicators using catch-data from Lane Snapper (Lutjanus synagris) collected in Honduras. These indicators are (1) the percentage of mature individuals in the catch, (2) the percentage of fish within the range of estimated optimal lengths to be captured and (3) the percentage of fish larger than the optimal length. These indicators determine the level of overfishing. The indicators were estimated separately for catchdata corresponding to gillnets, and each indicator was estimated with and without selectivity correction. Selectivity and mesh sizes of the fishing gear had a major impact in the estimation of indicators 1 and 2. As for indicator 3, it consistently showed a high level of exploitation. The three estimated indicators suggested that the Lane Snapper fishery in Honduras, is experiencing overfishing. Overall, the method proposed by Froese appears to be promising for the assessment of small-scale fisheries, but it should be used cautiously.

scholarly journals Inferring genetic connectivity in real populations, exemplified by coastal and oceanic Atlantic cod

2018 ◽  
Vol 115 (19) ◽  
pp. 4945-4950 ◽  
Author(s):  
Ingrid Spies ◽  
Lorenz Hauser ◽  
Per Erik Jorde ◽  
Halvor Knutsen ◽  
André E. Punt ◽  
...  
Keyword(s):  
Genetic Differentiation ◽  
Population Size ◽  
Extreme Values ◽  
Atlantic Cod ◽  
Genetic Connectivity ◽  
Fishing Gear ◽  
The North ◽  
Empirical Estimates ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity

Genetic data are commonly used to estimate connectivity between putative populations, but translating them to demographic dispersal rates is complicated. Theoretical equations that infer a migration rate based on the genetic estimator FST, such as Wright’s equation, FST ≈ 1/(4Nem + 1), make assumptions that do not apply to most real populations. How complexities inherent to real populations affect migration was exemplified by Atlantic cod in the North Sea and Skagerrak and was examined within an age-structured model that incorporated genetic markers. Migration was determined under various scenarios by varying the number of simulated migrants until the mean simulated level of genetic differentiation matched a fixed level of genetic differentiation equal to empirical estimates. Parameters that decreased the Ne/Nt ratio (where Ne is the effective and Nt is the total population size), such as high fishing mortality and high fishing gear selectivity, increased the number of migrants required to achieve empirical levels of genetic differentiation. Higher maturity-at-age and lower selectivity increased Ne/Nt and decreased migration when genetic differentiation was fixed. Changes in natural mortality, fishing gear selectivity, and maturity-at-age within expected limits had a moderate effect on migration when genetic differentiation was held constant. Changes in population size had the greatest effect on the number of migrants to achieve fixed levels of FST, particularly when genetic differentiation was low, FST ≈ 10−3. Highly variable migration patterns, compared with constant migration, resulted in higher variance in genetic differentiation and higher extreme values. Results are compared with and provide insight into the use of theoretical equations to estimate migration among real populations.

scholarly journals When is enough, enough? Quantifying trade-offs between information quality and sampling effort for fishing gear selectivity data

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0199655 ◽  
Author(s):  
Tiago Veiga-Malta ◽  
Jordan Feekings ◽  
Bent Herrmann ◽  
Ludvig Ahm Krag
Keyword(s):  
Information Quality ◽  
Sampling Effort ◽  
Fishing Gear ◽  
Trade Offs ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity

Fishing gear selectivity: an overview

1992 ◽  
Vol 13 (3) ◽  
pp. 201-204 ◽  
Author(s):  
David N. MacLennan
Keyword(s):  
Fishing Gear ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity

Fishing gear selectivity on sub-adults and spawning stock of the Tarpon Megalops atlanticus (Actinopterygii: Megalopidae) in Northeast Brazil

2021 ◽  
Vol 44 ◽  
pp. 101727
Author(s):  
Carlos Eduardo Lira dos Santos Silva ◽  
Caroline Vieira Feitosa ◽  
Cezar Augusto Freire Fernandes
Keyword(s):  
Fishing Gear ◽  
Northeast Brazil ◽  
Megalops Atlanticus ◽  
Gear Selectivity ◽  
Spawning Stock ◽  
Fishing Gear Selectivity

scholarly journals Estimation of gillnet selectivity for Tor tambra captured in Lirik River, Merangin Regency, Jambi Province

2020 ◽  
Vol 1 (1) ◽  
pp. 29-35
Author(s):  
Muhammad Natsir Kholis ◽  
Sulaeman Martasuganda ◽  
Mohd. Yusuf Amrullah ◽  
Jaliadi Jaliadi
Keyword(s):  
Essential Role ◽  
Mesh Size ◽  
Fishing Gear ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity ◽  
Pass Through

Fishing gear selectivity is the condition of a fishing gear that can catch fish the target of catching and escaped other fish so that selectivity has an essential role for fisheries managers who make regulations regarding the mesh size. The purpose of this study is to estimate the selectivity of gillnet fishing gear on Semah fish (Tor tambra). The method used in this research is the experimental fishing method. The results showed that the gillnet in the Lirik river has an estimated value of selectivity to Semah fish (Tor tambra) mesh size of 1.5 inches at a length of 48.59 cm and a mesh size of 2 inches at a length of 64.78 cm. Semah fish (Tor tambra) which have a length far below the estimated value of selectivity will be able to pass through the net without getting caught (escaped), and fish that have a length far above the estimated value of selectivity will be entangled.

scholarly journals Introducing selfisher: open source software for statistical analyses of fishing gear selectivity

2020 ◽  
Author(s):  
Mollie E Brooks ◽  
Valentina Melli ◽  
Esther Savina ◽  
Juan Santos ◽  
Russell Millar ◽  
...  
Keyword(s):  
Open Source ◽  
Statistical Methods ◽  
Open Source Software ◽  
Fixed Effects ◽  
Mesh Size ◽  
R Package ◽  
Fishing Gear ◽  
Comparison Study ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity

Fishing gear is constantly being improved to select certain sizes and species while excluding others. Experiments are conducted to quantify the selectivity and the resulting data needs to be analyzed using specialized statistical methods in many cases. Here, we present a new estimation tool for analyzing this type of data: an R package named selfisher. It can be used for both active and passive gears, and can handle different trial designs. It allows fitting models containing multiple fixed effects (e.g. length, total catch weight, mesh size, water turbidity) and random effects (e.g. haul). A bootstrapping procedure is provided to account for between and within haul variability and overdispersion. We demonstrate its use via four case studies including (1) covered codend analyses of four gears, (2) a paired gear study with numerous potential covariates, (3) a catch comparison study of unpaired hauls of gillnets and (4) a catch comparison study of paired hauls using polynomials and splines. This free and open source software will make it easier to model fishing gear selectivity, teach the statistical methods, and make analyses more repeatable.

scholarly journals Assessment of a small-scale fishery: Lane Snapper (Lutjanus synagris) using a length metric method

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0233479
Author(s):  
Liliana Sierra Castillo ◽  
Masami Fujiwara
Keyword(s):  
Small Scale ◽  
Fishing Gear ◽  
Optimal Length ◽  
Gill Nets ◽  
Limited Availability ◽  
Small Scale Fisheries ◽  
Catch Data ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity ◽  
High Level

Small-scale fisheries are hard to assess because of the limited availability of data. Therefore, a method requiring easy-to-obtain catch-data is important for the assessment and management of small-scale fisheries. The objective of this study was to assess the effect of fishing gear selectivity on a length-based metric method proposed by Froese by estimating three indicators using catch-data from Lane Snapper (Lutjanus synagris) collected in Honduras. These indicators are (1) the percentage of mature individuals in the catch, (2) the percentage of fish within the range of estimated optimal lengths to be captured, and (3) the percentage of fish larger than the optimal length. These indicators determine the level of overfishing. The indicators were estimated separately for catch-data corresponding to gill nets, and each indicator was estimated with and without selectivity correction. Selectivity and mesh sizes of the fishing gear had a major impact on the estimation of indicators 1 and 2. As for indicator 3, it consistently showed a high level of exploitation. The three estimated indicators suggested that the Lane Snapper fishery in Honduras is experiencing overfishing. Overall, the method appears to be promising for the assessment of small-scale fisheries, but it should be used cautiously.

Significant effects of fishing gear selectivity on fish life history

2013 ◽  
Vol 13 (3) ◽  
pp. 467-471 ◽  
Author(s):  
Zhenlin Liang ◽  
Peng Sun ◽  
Wei Yan ◽  
Liuyi Huang ◽  
Yanli Tang
Keyword(s):  
Life History ◽  
Fishing Gear ◽  
Gear Selectivity ◽  
Fishing Gear Selectivity
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