Fisheries Stock Assessment and Modeling

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

Deadline for manuscript submissions: closed (11 November 2024) | Viewed by 1804

Special Issue Editors


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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
Department of Applied Ecology, North Carolina State University, Morehead City, NC 28557, USA
Interests: quantitative fisheries management; fish population dynamics; stock assessment; ecosystem modeling
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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
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

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Keywords

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

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Published Papers (1 paper)

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Review

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 1109
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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