Special Issue "Stock Assessment and Management for Sustainable Fisheries"

A special issue of Fishes (ISSN 2410-3888). This special issue belongs to the section "Sustainable Aquaculture".

Deadline for manuscript submissions: 31 July 2023 | Viewed by 2775

Special Issue Editors

Dr. Siquan Tian
E-Mail Website
Guest Editor
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
Interests: fisheries stock assessment and management; fisheries oceanography
Department of Applied Ecology, North Carolina State University, Morehead City, NC 28557, USA
Interests: quantitative fisheries ecology; fish population dynamics; ecosystem modeling

Special Issue Information

Dear Colleagues,

Defining and implementing measures for the sustainable management of fisheries has become imperative owing to the management status of fish stocks and given the current changes in environmental features and their influence on fish populations worldwide. The stock status of a variety of selected fish species is to be evaluated by regional researchers and/or expert working groups based on the regional/country-specific needs, mostly in connection with the socio-economic and ecological importance of the respective stock. Typically, the assessment is based on available data, best available methods assessment techniques and/or knowledge of the life history of the species being assessed. After stock status has been assessed, fisheries managers are responsible for determining, evaluating and adopting management measures. As these measures will define the health situation of different ecosystems and assure the sustainable harvest of different fish stocks in the future. In this regard, it is considered particularly vital that this Special Issue includes a Section devoted to single-and-multi-species fisheries management models, management strategy evaluation, stock assessment modeling, data-limited methods for exploited and non-targeted species, habitat changes relate to fishing pressures, and identification of key environmental factors affecting the spatial distribution of species.

Dr. Siquan Tian
Dr. Jie Cao
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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

  • fisheries sustainable use
  • fisheries stock assessment
  • fisheries management
  • fish population dynamics

Published Papers (3 papers)

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Research

Article
Effects of Aging Uncertainty on the Estimation of Growth Functions of Major Tuna Species
Fishes 2023, 8(3), 131; https://doi.org/10.3390/fishes8030131 - 24 Feb 2023
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Abstract
Fishery stock assessment requires accurate specification of the growth function of target species, and aging uncertainty is an important factor that affects the estimation of growth parameters. In this study, we used simulations to study the effects of two types of aging uncertainty, [...] Read more.
Fishery stock assessment requires accurate specification of the growth function of target species, and aging uncertainty is an important factor that affects the estimation of growth parameters. In this study, we used simulations to study the effects of two types of aging uncertainty, aging error and sampled age range, on the parameter estimation of the Von Bertalanffy growth function, including asymptotic length (L), growth coefficient (k), and theoretical age in the year at zero length (t0) of five important tuna species. We found that the uncertainty of the estimated growth curves increased with increasing aging errors. When aging errors were fixed among ages, the effects of age range on estimation error of growth parameters were different among species and growth parameters. When the aging error increased with age, the estimation uncertainty of L and k was the greatest when only young age groups were sampled, while the estimation uncertainty of t0 was the greatest when only old age groups were sampled. Therefore, reducing the aging error and sampling individuals with a wider age range are important for increasing the accuracy and decreasing the uncertainty of the estimated growth function, which will further reduce the uncertainty in fishery stock assessment. Full article
(This article belongs to the Special Issue Stock Assessment and Management for Sustainable Fisheries)
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Article
Exploring the Response of the Japanese Sardine (Sardinops melanostictus) Stock-Recruitment Relationship to Environmental Changes under Different Structural Models
by , and
Fishes 2022, 7(5), 276; https://doi.org/10.3390/fishes7050276 - 06 Oct 2022
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Abstract
Japanese sardines (Sardinops melanostictus) are environmentally sensitive pelagic fish. We investigated the effects of environmental factors on the stock-recruitment (S-R) relationship of S. melanostictus in the Pacific Ocean from 1984 to 2018. We modeled and analyzed the recruitment of S. melanostictus [...] Read more.
Japanese sardines (Sardinops melanostictus) are environmentally sensitive pelagic fish. We investigated the effects of environmental factors on the stock-recruitment (S-R) relationship of S. melanostictus in the Pacific Ocean from 1984 to 2018. We modeled and analyzed the recruitment of S. melanostictus using the Ricker model, the Ricker environment extension model (Ricker-E), and the generalized additive model (GAM). Different numbers of environmental factors were added to the models for fitting, and the Akaike information criterion (AIC) was used to select the optimal model. The results showed that the nonlinear GAM provided the best fit. The results of the GAM single factor and multifactor analysis showed that environmental factors were significantly correlated with recruitment in S. melanostictus (p < 0.05). The best fitting model was the GAM, with an AIC of 57.9 and a cumulative explanation rate of 95.7%. Sea surface temperature was the most dominant environmental factor and had a negative impact on R/S. Considering both spawning stock biomass (S) and the environmental factors in the S-R relationship is important for studying the mechanisms of complementary changes and population changes in S. melanostictus under the influence of the marine environment. Full article
(This article belongs to the Special Issue Stock Assessment and Management for Sustainable Fisheries)
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Article
Do Two Different Approaches to the Season in Modeling Affect the Predicted Distribution of Fish? A Case Study for Decapterus maruadsi in the Offshore Waters of Southern Zhejiang, China
Fishes 2022, 7(4), 153; https://doi.org/10.3390/fishes7040153 - 27 Jun 2022
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Abstract
The relationships between environmental factors and fish density are closely related, and species distribution models (SDMs) have been widely used in exploring these relationships and predicting the spatial distribution of fishery resources. When exploring the prediction of the spatial distribution of species in [...] Read more.
The relationships between environmental factors and fish density are closely related, and species distribution models (SDMs) have been widely used in exploring these relationships and predicting the spatial distribution of fishery resources. When exploring the prediction of the spatial distribution of species in different seasons, the method of choosing the appropriate approach to the season will help to improve the predictive performance of the model. Based on data collected from 2015 to 2020 during a survey off southern Zhejiang, the Tweedie-GAM was used to establish the relationship between the density of Decapterus maruadsi and environmental factors at different modeling approaches. The results showed that water temperature, salinity and depth were the main factors influencing D. maruadsi, and they operated through different mechanisms and even resulted in opposite trends of density in different seasons. Spatially, the two modeling approaches also differed in predicting the spatial distribution of D. maruadsi, with the seasonal model showing a higher density trend in inshore waters than in offshore waters in spring but showing the opposite trend in summer and autumn, which was more consistent with the actual spatial distribution of the resource. By analyzing the effects of two different approaches on the prediction of fishery resources, this study aims to provide research ideas and references for improving the predictive performance of SDMs. Full article
(This article belongs to the Special Issue Stock Assessment and Management for Sustainable Fisheries)
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