Marine Fisheries and Ecosystem Modeling

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Biodiversity and Functionality of Aquatic Ecosystems".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 12439

Special Issue Editor


E-Mail Website
Guest Editor
CNR-IAS, National Research Council of Italy, Institute for the Anthropic Impacts and Sustainability in Marine Environment, 90149 Palermo, Italy
Interests: fisheries oceanography; fisheries ecology; ecology of fishes and other aquatic organisms in relation to their sustainable exploitation; scientific advice to fisheries management

Special Issue Information

Dear Colleagues,

The sustainable exploitation of marine fish populations is an important issue worldwide, due to the globally increasing impacts of fishing efforts and climate change. It is essential to evaluate how both these factors affect the dynamics of natural resources in order to develop adaptation policies that aim to reduce their impacts. There is a general lack of information on the mechanisms governing marine ecosystems, which needs to be addressed. This Special Issue will focus on recent trends in this topic, assessing the role of the different modelling methodologies available, and exploring innovative approaches in support of marine fisheries management, suggesting alternative pathways to be adopted in order to limit the vulnerability of marine species to environmental changes and fishing activities. 

Prof. Dr. Bernardo Patti
Guest Editor

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. Water is an international peer-reviewed open access semimonthly 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

  • marine fish populations
  • fisheries
  • marine ecosystems
  • environmental factors
  • climate change
  • mechanistic models
  • statistical models

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

16 pages, 2028 KiB  
Article
Environmental Conditions along Tuna Larval Dispersion: Insights on the Spawning Habitat and Impact on Their Development Stages
by Stefania Russo, Marco Torri, Bernardo Patti, Marianna Musco, Tiziana Masullo, Marilena Vita Di Natale, Gianluca Sarà and Angela Cuttitta
Water 2022, 14(10), 1568; https://doi.org/10.3390/w14101568 - 13 May 2022
Cited by 5 | Viewed by 2084
Abstract
Estimated larval backward trajectories of three Tuna species, namely, Atlantic Bluefin Tuna (Thunnus thynnus, Linnaeus, 1758), Bullet Tuna (Auxis Rochei, Risso, 1801) and Albacore Tuna (Thunnus alalunga, Bonnaterre, 1788) in the central Mediterranean Sea, were used to [...] Read more.
Estimated larval backward trajectories of three Tuna species, namely, Atlantic Bluefin Tuna (Thunnus thynnus, Linnaeus, 1758), Bullet Tuna (Auxis Rochei, Risso, 1801) and Albacore Tuna (Thunnus alalunga, Bonnaterre, 1788) in the central Mediterranean Sea, were used to characterize their spawning habitats, and to assess the impact of changes due to the major environmental parameters (i.e., sea surface temperature and chlorophyll-a concentration) on larval development during their advection by surface currents. We assumed that the environmental variability experienced by larvae along their paths may have influenced their development, also affecting their survival. Our results showed that the Tuna larvae underwent an accelerated growth in favorable environmental conditions, impacting on the notochord development. In addition, further updated information on spawning and larval retention habitats of Atlantic Bluefin Tuna, Bullet and Albacore Tunas in the central Mediterranean Sea were delivered. Full article
(This article belongs to the Special Issue Marine Fisheries and Ecosystem Modeling)
Show Figures

Figure 1

19 pages, 4105 KiB  
Article
Inferring Population Structure from Early Life Stage: The Case of the European Anchovy in the Sicilian and Maltese Shelves
by Angela Cuttitta, Bernardo Patti, Marianna Musco, Tiziana Masullo, Francesco Placenti, Enza Maria Quinci, Francesca Falco, Carmelo Daniele Bennici, Marilena Di Natale, Vito Pipitone, Matteo Cammarata, Isabel Maneiro, Stefania Russo and Marco Torri
Water 2022, 14(9), 1427; https://doi.org/10.3390/w14091427 - 29 Apr 2022
Cited by 2 | Viewed by 1782
Abstract
The European anchovy is an important fishing resource in the Sicilian Channel that supports a high recruitment success variability. The presence of two spawning areas, the drifting of the larvae along the currents and the different oceanographic conditions within the region suggest the [...] Read more.
The European anchovy is an important fishing resource in the Sicilian Channel that supports a high recruitment success variability. The presence of two spawning areas, the drifting of the larvae along the currents and the different oceanographic conditions within the region suggest the presence of different larvae subpopulations. Morphometric and biochemical approaches have been used to analyze the differences among larvae collected. The amino acid composition discriminates two larval groups closely related to the spawning regions: Adventure Bank and the shelf between the South of Sicily and Malta. In addition, there are morphometric and growth differences between recently hatched larvae in these two regions, reinforcing the hypothesis of two larval subpopulations and suggesting differences in the parental reproduction effort. Between the South of Sicily and Malta there are growth and biochemical composition differences since larvae from the Maltese coast present a higher protein content and a bigger growth rate than those from Sicily, pointing out that Malta is an area with a better nutritional condition environment. No differences in the growth rate have been observed between the Adventure Bank area and the Maltese shelf, therefore, a diverse nutritional condition cannot be suggested between these two areas despite the Maltese larvae having a higher protein content present. Full article
(This article belongs to the Special Issue Marine Fisheries and Ecosystem Modeling)
Show Figures

Figure 1

16 pages, 3220 KiB  
Article
Predicting Potential Spawning Habitat by Ensemble Species Distribution Models: The Case Study of European Anchovy (Engraulis encrasicolus) in the Strait of Sicily
by Enza Maria Quinci, Marco Torri, Angela Cuttitta and Bernardo Patti
Water 2022, 14(9), 1400; https://doi.org/10.3390/w14091400 - 27 Apr 2022
Cited by 4 | Viewed by 1840
Abstract
Species distribution models (SDMs) are important tools for exploring the complex association between species and habitats. Here, we applied six SDMs combining 1946 pieces of presence/absence data regarding European anchovy eggs with environmental parameters from surveys conducted in the Strait of Sicily from [...] Read more.
Species distribution models (SDMs) are important tools for exploring the complex association between species and habitats. Here, we applied six SDMs combining 1946 pieces of presence/absence data regarding European anchovy eggs with environmental parameters from surveys conducted in the Strait of Sicily from 1998 to 2016. We aimed to investigate the mechanisms influencing spawning habitat suitability for anchovy (Engraulis encrasicolus). The dataset was split into a training subset (75%) and a test subset (25%) for evaluating the predictive performance of the models. The results suggested the role of environmental parameters in explaining egg occurrence, model accuracy and spatial predictions. Bottom depth consistently had the highest importance, followed by absolute dynamic topography, which gives insights about local mesoscale oceanographic features. Each modelling method, except the linear model, produced successful performance for both the training and the test datasets. The spatial predictions were estimated as weighted averages of single-model predictions, with weights based on discriminatory power measured by the area under the receiver operating characteristic curve (AUC). This ensemble approach often provided more robust predictions than a single model. The coastal waters were identified as the most favorable for anchovy spawning, especially the south-central sector and the area around the southern-most tip of Sicily. Full article
(This article belongs to the Special Issue Marine Fisheries and Ecosystem Modeling)
Show Figures

Graphical abstract

16 pages, 7002 KiB  
Article
Development and Evaluation of a Chinook Salmon Smolt Swimming Behavior Model
by Edward S. Gross, Rusty C. Holleman, Michael J. Thomas, Nann A. Fangue and Andrew L. Rypel
Water 2021, 13(20), 2904; https://doi.org/10.3390/w13202904 - 16 Oct 2021
Cited by 3 | Viewed by 2486
Abstract
Hydrologic currents and swimming behavior influence routing and survival of emigrating Chinook salmon in branched migratory corridors. Behavioral particle-tracking models (PTM) of Chinook salmon can estimate migration paths of salmon using the combination of hydrodynamic velocity and swimming behavior. To test our hypotheses [...] Read more.
Hydrologic currents and swimming behavior influence routing and survival of emigrating Chinook salmon in branched migratory corridors. Behavioral particle-tracking models (PTM) of Chinook salmon can estimate migration paths of salmon using the combination of hydrodynamic velocity and swimming behavior. To test our hypotheses of the importance of management, models can simulate historical conditions and alternative management scenarios such as flow manipulation and modification of channel geometry. Swimming behaviors in these models are often specified to match aggregated observed properties such as transit time estimated from acoustic telemetry data. In our study, we estimate swimming behaviors at 5 s intervals directly from acoustic telemetry data and concurrent high-resolution three-dimensional hydrodynamic model results at the junction of the San Joaquin River and Old River in the Sacramento-San Joaquin Delta, California. We use the swimming speed dataset to specify a stochastic swimming behavior consistent with observations of instantaneous swimming. We then evaluate the effect of individual components of the swimming formulation on predicted route selection and the consistency with observed route selection. The PTM predicted route selection fractions are similar among passive and active swimming behaviors for most tags, but the observed route selection for some tags would be unlikely under passive behavior leading to the conclusion that active swimming behavior influenced the route selection of several tagged smolts. Full article
(This article belongs to the Special Issue Marine Fisheries and Ecosystem Modeling)
Show Figures

Figure 1

18 pages, 21759 KiB  
Article
Study on the Coexistence of Offshore Wind Farms and Cage Culture
by Hsing-Yu Wang, Hui-Ming Fang and Yun-Chih Chiang
Water 2021, 13(14), 1960; https://doi.org/10.3390/w13141960 - 17 Jul 2021
Viewed by 2379
Abstract
In this study, a hydrodynamic model was used that includes the effects of wave–current interactions to simulate the wave and current patterns before and after offshore wind turbine installation in western Taiwan. By simulating the waves and currents after the offshore wind turbine [...] Read more.
In this study, a hydrodynamic model was used that includes the effects of wave–current interactions to simulate the wave and current patterns before and after offshore wind turbine installation in western Taiwan. By simulating the waves and currents after the offshore wind turbine was established, the waves and currents caused by the wind turbine were seen to have a limited range of influence, which is probably within an area about four to five times the size of the diameter (12–15 m) of the foundation structure. Overall, the analysis of the simulation results of the wave and current patterns after the offshore wind turbines were established shows that the underwater foundation only affected the local area near the pile structure. The wind farm (code E) of the research case can be equipped with about 720 cage cultures; if this is extended to other wind farms in the western sea area, it should be possible to produce economic-scale farming operations such as offshore wind power and fisheries. However, this study did not consider the future operation of the entire offshore wind farm. If the operation and maintenance of offshore wind farms are not affected, and if the consent of the developer is obtained, it should be possible to use this method to provide economically large-scale farming areas as a mutually beneficial method for offshore wind power generation and fisheries. Full article
(This article belongs to the Special Issue Marine Fisheries and Ecosystem Modeling)
Show Figures

Figure 1

17 pages, 6553 KiB  
Article
Purpleback Flying Squid Sthenoteuthis oualaniensis in the South China Sea: Growth, Resources and Association with the Environment
by Chunxu Zhao, Chunyan Shen, Andrew Bakun, Yunrong Yan and Bin Kang
Water 2021, 13(1), 65; https://doi.org/10.3390/w13010065 - 31 Dec 2020
Cited by 8 | Viewed by 3440
Abstract
The purpleback flying squid (Ommastrephidae: Sthenoteuthis oualaniensis) is an important species at higher trophic levels of the regional marine ecosystem in the South China Sea (SCS), where it is considered to show the potential for fishery development. Accordingly, under increasing climatic and [...] Read more.
The purpleback flying squid (Ommastrephidae: Sthenoteuthis oualaniensis) is an important species at higher trophic levels of the regional marine ecosystem in the South China Sea (SCS), where it is considered to show the potential for fishery development. Accordingly, under increasing climatic and environmental changes, understanding the nature and importance of various factors that determine the spatial and temporal distribution and abundance of S. oualaniensis in the SCS is of great scientific and socio-economic interest. Using generalized additive model (GAM) methods, we analyzed the relationship between available environmental factors and catch per unit effort (CPUE) data of S. oualaniensis. The body size of S. oualaniensis in the SCS was relatively small (<19.4 cm), with a shorter lifespan than individuals in other seas. The biological characteristics indicate that S. oualaniensis in the SCS showed a positive allometric growth, and could be suitably described by the logistic growth equation. In our study, the sea areas with higher CPUE were mainly distributed at 10°–11° N, with a 27–28 °C sea surface temperature (SST) range, a sea surface height anomaly (SSHA) of −0.05–0.05 m, and chlorophyll-a concentration (Chl-a) higher than 0.18 μg/L. The SST was the most important factor in the GAM analysis and the best fitting GAM model explained 67.9% of the variance. Understanding the biological characteristics and habitat status of S. oualaniensis in the SCS will benefit the management of this resource. Full article
(This article belongs to the Special Issue Marine Fisheries and Ecosystem Modeling)
Show Figures

Figure 1

Back to TopTop