Introducing selfisher: open source software for statistical analyses of 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.

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

Tomini Journal of Aquatic Science ◽

10.37905/tjas.v1i1.5830 ◽

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.

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The Effects of Communication Patterns on the Success of Open Source Software Projects

Journal of Global Information Management ◽

10.4018/jgim.2016100102 ◽

2016 ◽

Vol 24 (4) ◽

pp. 22-44 ◽

Cited By ~ 3

Author(s):

Jing Wu ◽

Khim-Yong Goh ◽

He Li ◽

Chuan Luo ◽

Haichao Zheng

Keyword(s):

Open Source ◽

Open Source Software ◽

Fixed Effects ◽

Communication Patterns ◽

Estimation Model ◽

Software Projects ◽

Team Members ◽

Analysis Methodology ◽

Model Following ◽

Time Period

Drawing on the theoretical lens of communication patterns in organizational theory, this research analyzed the longitudinal success of open source software (OSS) projects by employing social network analysis method, based on extensive analyses of empirical data. This study is expected to provide an understanding on how communication patterns established in different roles and different levels. The authors not only measured OSS success from both developers and users' perspectives, but also extended the existing research by including the potential relationships among these success measures in the estimation model. Following the panel data econometric analysis methodology, they evaluated their research hypotheses using the Three-Stage Least Squares model, accounting for both time-period and project fixed effects. The authors' results indicated that according to the objectives of projects, a proper and planned control for the communication among team members is crucial for the success of OSS projects.

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

The European Landing Obligation ◽

10.1007/978-3-030-03308-8_14 ◽

2018 ◽

pp. 279-296 ◽

Cited By ~ 4

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

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Analysing global economic costs of invasive alien species with the invacost R package

10.1101/2020.12.10.419432 ◽

2020 ◽

Author(s):

Boris Leroy ◽

Andrew M Kramer ◽

Anne-Charlotte Vaissière ◽

Franck Courchamp ◽

Christophe Diagne

Keyword(s):

Invasive Species ◽

Alien Species ◽

Open Source ◽

Open Source Software ◽

Large Scale ◽

Invasive Alien Species ◽

Standard Procedure ◽

R Package ◽

Economic Costs ◽

Global Database

Aim: Large-scale datasets are becoming increasingly available for macroecological research from different disciplines. However, learning their specific extraction and analytical requirements can become prohibitively time-consuming for researchers. We argue that this issue can be tackled with the provision of methodological frameworks published in open-source software. We illustrate this solution with the invacost R package, an open-source software designed to query and analyse the global database on reported economic costs of invasive alien species, InvaCost. Innovations: First, the invacost package provides updates of this dynamic database directly in the analytical environment R. Second, it helps understand the nature of economic cost data for invasive species, their harmonisation process, and the inherent biases associated with such data. Third, it readily provides complementary methods to query and analyse the costs of invasive species at the global scale, all the while accounting for econometric statistical issues. Main conclusions: This tool will be useful for scientists working on invasive alien species, by (i) facilitating access and use to this multi-disciplinary data resource and (ii) providing a standard procedure which will facilitate reproducibility and comparability of studies, one of the major critics of this topic until now. We discuss how the development of this R package was designed as an enforcement of general recommendations for transparency, reproducibility and comparability of science in the era of big data in ecology.

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

10.1101/2020.05.13.093856 ◽

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.

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ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

Frontiers in Genetics ◽

10.3389/fgene.2021.706907 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chun-Hui Gao ◽

Guangchuang Yu ◽

Peng Cai

Keyword(s):

Open Source ◽

Open Source Software ◽

Source Code ◽

R Package ◽

Venn Diagram ◽

Free Access ◽

High Quality ◽

Venn Diagrams ◽

Label Edge ◽

The Cost

Venn diagrams are widely used diagrams to show the set relationships in biomedical studies. In this study, we developed ggVennDiagram, an R package that could automatically generate high-quality Venn diagrams with two to seven sets. The ggVennDiagram is built based on ggplot2, and it integrates the advantages of existing packages, such as venn, RVenn, VennDiagram, and sf. Satisfactory results can be obtained with minimal configurations. Furthermore, we designed comprehensive objects to store the entire data of the Venn diagram, which allowed free access to both intersection values and Venn plot sub-elements, such as set label/edge and region label/filling. Therefore, high customization of every Venn plot sub-element can be fulfilled without increasing the cost of learning when the user is familiar with ggplot2 methods. To date, ggVennDiagram has been cited in more than 10 publications, and its source code repository has been starred by more than 140 GitHub users, suggesting a great potential in applications. The package is an open-source software released under the GPL-3 license, and it is freely available through CRAN (https://cran.r-project.org/package=ggVennDiagram).

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Fishing Gear Selectivity in the Rationalized Aleutian Islands Golden King Crab Fishery

10.4027/fbgics.2015.14 ◽

2015 ◽

Author(s):

D Pengilly ◽

V Vanek ◽

MSM Siddeek

Keyword(s):

Aleutian Islands ◽

Fishing Gear ◽

King Crab ◽

Gear Selectivity ◽

Fishing Gear Selectivity

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

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1800096115 ◽

2018 ◽

Vol 115 (19) ◽

pp. 4945-4950 ◽

Cited By ~ 1

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.

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