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Fishes
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Fisheries Stock Assessment and Modeling
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Fisheries Stock Assessment and Modeling

A special issue of Fishes (ISSN 2410-3888).

Deadline for manuscript submissions: closed (11 November 2024) | Viewed by 2521

Special Issue Editors

Prof. Dr. Yan Jiao

E-Mail Website
Guest Editor
Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
Interests: population dynamics; demographic modeling; spatial–temporal dynamics; stock assessment; fisheries management; bayesian hierarchical modeling
Dr. Jie Cao

E-Mail Website
Co-Guest Editor
Department of Applied Ecology, North Carolina State University, Morehead City, NC 28557, USA
Interests: quantitative fisheries management; fish population dynamics; stock assessment; ecosystem modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Rujia Bi

E-Mail Website
Co-Guest Editor
Center for Limnology, University of Wisconsin-Madison, Madison, WI 53706, USA
Interests: fisheries management; spatiotemporal analysis; population dynamics; stock assessment; marine ecology; climate change
Dr. Qiuyun Ma

E-Mail Website
Co-Guest Editor
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
Interests: stock assessment; population dynamics; fisheries management

Special Issue Information

Dear Colleagues,

Fisheries stock assessment and modeling involves research of an interdisciplinary nature, fostering a holistic understanding of math, statistics, fish stocks, biology, ecology, and socio-economic dimensions. This article collection aims to showcase cutting-edge research and methodologies dedicated to understanding and managing fish populations. By integrating advanced modeling techniques with fisheries and survey data, the contributors explore the intricate interplay between environmental factors, fishing pressure, and biological processes that shape fish stocks. From population dynamics, spatial distribution, spatial–temporal dynamics, and state-space models to Bayesian hierarchical modeling and nonstationary models, we welcome articles offering valuable insights that will be crucial to bettering fish stock assessments and sustainable fisheries management. Additionally, this Special Issue welcomes studies addressing the pressing challenges of climate change and data limitations, highlighting the need for modeling and adaptive strategy evaluation in the face of shifting oceanic conditions and/or situations of limited information.

Prof. Dr. Yan Jiao
Dr. Jie Cao
Dr. Rujia Bi
Dr. Qiuyun Ma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fishes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • population dynamics
  • population ecology
  • stock assessment
  • climate change
  • nonstationarity
  • spatial–temporal dynamics
  • ecosystem modeling

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Published Papers (2 papers)

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Research

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15 pages, 1806 KiB  
Article
Spawning Potential Ratio Can Provide Reference Points for Fishery Management That Are Robust to Environmental Variability
by Kyle W. Shertzer, Matthew D. Damiano and Erik H. Williams
Fishes 2024, 9(12), 497; https://doi.org/10.3390/fishes9120497 - 3 Dec 2024
Viewed by 562
Abstract
Biological reference points are key quantities provided by stock assessments and used in fishery management for evaluating fishery status and setting future catch levels. For many fisheries worldwide, biological reference points are based on the spawning potential ratio (SPR), which measures per-recruit reproductive [...] Read more.
Biological reference points are key quantities provided by stock assessments and used in fishery management for evaluating fishery status and setting future catch levels. For many fisheries worldwide, biological reference points are based on the spawning potential ratio (SPR), which measures per-recruit reproductive output as a function of the fishing rate relative to that when fishing is absent. SPR depends on the biological characteristics of the stock, which in turn can be influenced by the environment. A fishing rate based on SPR is often used as a proxy for the fishing rate that provides maximum sustainable yield. Here, we evaluate variability in the fishing rate (F40) that provides an SPR of 40%, a commonly used limit reference point, given plausible variability in biological characteristics. Using eight case-study species from marine waters off the southeast United States, we consider both simple random variability and directional variability, both of which might result from climate change. We test the sensitivity of F40 to various life-history traits and compute distributions of F40, given the expected variability in those traits. Based on those distributions, we evaluate the probabilities of overfishing given a target fishing rate (here, 75%F40) that is based on prevailing conditions without considering future variability in F40, consistent with common, current practice. Analyses also considered an SPR of 30% and 50% to evaluate the generality of conclusions. Results support that SPR-reference points are generally robust to plausible levels of variability in life-history traits that might be induced by environmental nonstationarity and that associated target fishing rates can provide meaningful buffers to prevent overfishing. Full article
(This article belongs to the Special Issue Fisheries Stock Assessment and Modeling)
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Review

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25 pages, 1111 KiB  
Review
Systematic Review of Multi-Species Models in Fisheries: Key Features and Current Trends
by Pablo Couve, Nixon Bahamon, Cristian M. Canales and Joan B. Company
Fishes 2024, 9(10), 372; https://doi.org/10.3390/fishes9100372 - 24 Sep 2024
Viewed by 1214
Abstract
In the context of ecosystem-based fisheries management (EBFM), multi-species models offer a potential alternative to traditional single-species models for managing key species, particularly in mixed-fishery settings. These models account for interactions between different species, providing a more holistic approach to fisheries compared to [...] Read more.
In the context of ecosystem-based fisheries management (EBFM), multi-species models offer a potential alternative to traditional single-species models for managing key species, particularly in mixed-fishery settings. These models account for interactions between different species, providing a more holistic approach to fisheries compared to traditional single-species management. There is currently no comprehensive list or recent analysis of the diverse methods used to account for species interactions in fisheries worldwide. We conducted a systematic review to objectively present the current multi-species models used in fisheries. The systematic search identified 86 multi-species models, which were then evaluated to assess their similarities. Employing a clustering analysis, three distinct groups were identified: extensions of single-species/dynamic multi-species models, aggregated ecosystem models, and end-to-end/coupled and hybrid models. The first group was among the most diverse, owing to their ability to integrate biological components, while maintaining an intermediate level of complexity. The second group, primarily defined by the EwE method, features an aggregated biomass pool structure incorporating biological components and environmental effects. The third cluster featured the most complex models, which included a comprehensive representation of size and age structure, the ability to incorporate biological components and environmental effects, as well as spatial representation. The application of these methods is primarily concentrated on small pelagic and demersal species from North America and Europe. This analysis provides a comprehensive guide for stakeholders on the development and use of multi-species models, considering data constraints and regional contexts. Full article
(This article belongs to the Special Issue Fisheries Stock Assessment and Modeling)
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