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17 pages, 4493 KiB  
Article
The Effects of Climate Change on Sthenoteuthis oualaniensis Habitats in the Northern Indian Ocean
by Lihong Wen, Heng Zhang, Zhou Fang and Xinjun Chen
Animals 2025, 15(4), 573; https://doi.org/10.3390/ani15040573 - 17 Feb 2025
Abstract
The northern Indian Ocean is located in a typical monsoon region that is also influenced by climate events such as the Indian Ocean Dipole (IOD), which makes Sthenoteuthis oualaniensis habitat highly susceptible to changes in climate and marine environmental conditions. This study established [...] Read more.
The northern Indian Ocean is located in a typical monsoon region that is also influenced by climate events such as the Indian Ocean Dipole (IOD), which makes Sthenoteuthis oualaniensis habitat highly susceptible to changes in climate and marine environmental conditions. This study established a suitability index (SI) model and used the arithmetic average method to construct a comprehensive habitat suitability index (HSI) model based on S. oualaniensis production statistics in the northern Indian Ocean from 2017 to 2019. Variations in the suitability of S. oualaniensis habitat during different IOD events were then analyzed. The results indicate that the model performed best when year, month, latitude, longitude, sea surface temperature (SST), wind speed (WS), and photosynthetically active radiation (PAR) variables were included in the generalized additive model (GAM). SST, WS, and PAR were identified as the most important key environmental factors. The HSI model showed that the most suitable habitat during a positive IOD event was smaller than during a negative IOD event and that the suitable habitat’s center was located west of the positive IOD event and east of the negative IOD event. There was a significant inverse relationship between the area, suitable for habitation, and the north–south shift in the latitudinal gravity center and the Dipole modal index (DMI). The results indicate significant differences in the habitat of S. oualaniensis in the northern Indian Ocean during different IOD events, as well as differences in suitable habitat ranges and the spatial distribution of the species. Full article
(This article belongs to the Section Aquatic Animals)
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<p>The ln (CPUE + 1) frequency distribution and distribution tests for <span class="html-italic">Sthenoteuthis oualaniensis</span> in the northern Indian Ocean. (<b>A</b>) Normal Q-Q plot of ln (CPUE + 1). (<b>B</b>) Frequency distribution of ln (CPUE + 1).</p>
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<p>The distribution of HSI climatic area for <span class="html-italic">Sthenoteuthis oualaniensis</span> in the northern Indian Ocean from January to March and October to December.</p>
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<p>The distribution of <span class="html-italic">Sthenoteuthis oualaniensis</span> habitats in the northern Indian Ocean from January to March and October to December during different climatic events. nIOD stands for the negative Indian Ocean Dipole. pIOD stands for the positive Indian Ocean Dipole.</p>
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<p>Suitable HSI frequency statistics and monthly DMIs for <span class="html-italic">S. oualaniensis</span> in the northern Indian Ocean from January to March and October to December of 2000 to 2010 (<b>A</b>). Suitable HSI frequency statistics and monthly DMI variation trends for <span class="html-italic">S. oualaniensis</span> from January to March and October to December in the northern Indian Ocean from 2011 to 2020 (<b>B</b>).</p>
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<p>The relationship between HSI longitude center of gravity and annual DMI for <span class="html-italic">S. oualaniensis</span> from January to March and October to December in the northern Indian Ocean from 2000 to 2020.</p>
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<p>The relationship between HSI latitude center of gravity and annual DMI for <span class="html-italic">S. oualaniensis</span> from January to March and October to December in the northern Indian Ocean from 2000 to 2020.</p>
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19 pages, 2352 KiB  
Article
Characterization of the Complete Mitochondrial Genome of Dwarf Form of Purpleback Flying Squid (Sthenoteuthis oualaniensis) and Phylogenetic Analysis of the Family Ommastrephidae
by Wenjuan Duo, Lei Xu, Mohd Johari Mohd Yusof, Yingmin Wang, Seng Beng Ng and Feiyan Du
Genes 2025, 16(2), 226; https://doi.org/10.3390/genes16020226 - 15 Feb 2025
Abstract
Background: The Ommastrephidae family of cephalopods is important in marine ecosystems as both predators and prey. Species such as Todarodes pacificus, Illex argentinus, and Dosidicus gigas are economically valuable but are threatened by overfishing and environmental changes. The genus Sthenoteuthis, [...] Read more.
Background: The Ommastrephidae family of cephalopods is important in marine ecosystems as both predators and prey. Species such as Todarodes pacificus, Illex argentinus, and Dosidicus gigas are economically valuable but are threatened by overfishing and environmental changes. The genus Sthenoteuthis, especially S. oualaniensis, shows significant morphological and genetic variation, including medium-sized and dwarf forms found in the South China Sea. Methods: Specimens of S. oualaniensis were collected from the South China Sea, their genomic DNA sequenced, and phylogenetic relationships analyzed using mitochondrial genomes from various Ommastrephidae species. Results: The study presents the complete mitochondrial genome of the dwarf form of S. oualaniensis (20,320 bp) and compares it with the medium-sized form, revealing a typical vertebrate structure with 13 protein-coding genes, 21 tRNA genes, and 2 rRNA genes, along with a strong AT bias. Nucleotide composition analysis shows a 12% genetic divergence between the two forms, suggesting a recent common ancestor and potential cryptic speciation, with all protein-coding genes exhibiting purifying selection based on Ka/Ks ratios below 1. Conclusions: The mitochondrial genome of the dwarf form of S. oualaniensis shows a close evolutionary relationship with the medium-sized form and a 12% genetic divergence, suggesting potential cryptic speciation. These findings underscore the importance of mitochondrial analysis in understanding speciation and guiding future conservation efforts. Full article
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<p>Annotated mitochondrial genome of dwarf form of <span class="html-italic">S. oualaniensis</span>. Blue bars denote protein-coding genes, virescent bars represent rRNA genes, and lavender bars indicate tRNA genes. The direction of transcription is shown by the orientation of gene arrows: arrows pointing to the right indicate the heavy strand, while those pointing to the left denote the light strand. The black circle represents GC content, with outward projections indicating GC content above the average level and inward projections indicating below-average content. The GC skew is depicted using purple and green circles, where green represents negative GC skew and deep purple indicates positive GC skew.</p>
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<p>Relative synonymous codon usage (RSCU) patterns in the medium-sized and dwarf forms of <span class="html-italic">S. oualaniensis</span>.</p>
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<p>The ratio of nonsynonymous to synonymous substitutions (Ka/Ks) across 13 protein coding genes in two forms of <span class="html-italic">S. oualaniensis</span>.</p>
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<p>Bayesian inference (BI) (<b>A</b>) and maximum likelihood (ML) (<b>B</b>) phylogenetic trees illustrating the evolutionary relationships among cephalopod species based on mitochondrial genome sequences. The tree is rooted with <span class="html-italic">A. dux</span> as the outgroup. Posterior probabilities and support value are displayed at the nodes. Notable clades include multiple mitochondrial haplotypes of <span class="html-italic">S. oualaniensis</span> forming a well-supported cluster, and a close relationship between <span class="html-italic">D. gigas</span> and <span class="html-italic">Eucleoteuthis luminosa</span>. The longer branch lengths of <span class="html-italic">T. pacificus</span> and <span class="html-italic">I. argentinus</span> indicate greater genetic divergence compared to other taxa. The scale bar represents genetic distance.</p>
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17 pages, 8502 KiB  
Article
A Lightweight Deep Learning Model for Forecasting the Fishing Ground of Purpleback Flying Squid (Sthenoteuthis oualaniensis) in the Northwest Indian Ocean
by Shengmao Zhang, Junlin Chen, Haibin Han, Fenghua Tang, Xuesen Cui and Yongchuang Shi
Appl. Sci. 2025, 15(3), 1219; https://doi.org/10.3390/app15031219 - 24 Jan 2025
Viewed by 368
Abstract
The purpleback flying squid (Sthenoteuthis oualaniensis) is an economically significant cephalopod species in the Northwest Indian Ocean. Predicting its fishing grounds can provide a crucial foundation for fishery management and production. In this research, we collected data from China’s light-purse seine [...] Read more.
The purpleback flying squid (Sthenoteuthis oualaniensis) is an economically significant cephalopod species in the Northwest Indian Ocean. Predicting its fishing grounds can provide a crucial foundation for fishery management and production. In this research, we collected data from China’s light-purse seine fishery in the Northwest Indian Ocean from 2016 to 2020 to train and validate the AlexNet and VGG11 models. We designed a data partitioning method (DPM) to divide the training set into three scenarios, namely DPM-S1, DPM-S2, and DPM-S3. Firstly, DPM-S1 was employed to select the base model (BM). Subsequently, the optimal BM was lightweighted to obtain the optimal model (OM). The OM, known as the AlexNetMini model, has a model size that is one-third of that of the BM-AlexNet model. Our results also showed the following: (1) the F1-scores for AlexNet and AlexNetMini across the datasets DPM-S1, -S2, and -S3 were 0.6957, 0.7505, and 0.7430 for AlexNet and 0.6992, 0.7495, and 0.7486 for AlexNetMini, suggesting that both models exhibited comparable predictive performance; (2) the optimal dropout values for the AlexNetMini model were 0 and 0.2, and the optimal training set proportion was 0.8; (3) AlexNetMini utilized both DPM-S2 and DPM-S3, yielding comparable outcomes. However, given that the training duration for DPM-S3 was relatively shorter, DPM-S3 was selected as the preferred method for data partitioning. The findings of our study indicated that the lightweight model for the purpleback flying squid fishing ground prediction, specifically AlexNetMini, demonstrated superior performance compared to the original AlexNet model, particularly in terms of efficiency. Our study on the lightweight method for deep learning models provided a reference for enhancing the usability of deep learning in fisheries. Full article
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<p>Distribution of average CPUE of purpleback flying squid in the Northwest Indian Ocean from 2016 to 2021.</p>
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<p>Schematic of a 2D matrix of 4 channels, including SST, longitude, latitude, and time.</p>
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<p>The network architecture diagram of the AlexNet model (<b>a</b>) and VGG11 model (<b>b</b>).</p>
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<p>Test set accuracy of the VGG11 (<b>A</b>) and AlexNet (<b>B</b>) models.</p>
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<p>Loss curves of the VGG11 (<b>A</b>) and AlexNet (<b>B</b>) models.</p>
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<p>Comparison of validation set accuracy results for AM3 (<b>A</b>) and AM6 (<b>B</b>).</p>
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<p>Comparison of F1-score results between AlexNet (<b>left</b>) and AlexNetMini (<b>right</b>).</p>
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16 pages, 6965 KiB  
Article
Spatiotemporal Variation and Predictors of the Purpleback Flying Squid (Sthenoteuthis oualaniensis) Distribution Surrounding the Xisha and Zhongsha Islands during a Fishing Moratorium
by Liangming Wang, Changping Yang, Binbin Shan, Yan Liu, Jianwei Zou, Dianrong Sun and Tao Guo
Fishes 2024, 9(7), 253; https://doi.org/10.3390/fishes9070253 - 1 Jul 2024
Viewed by 818
Abstract
As an economic species widely distributed in the South China Sea (SCS), the purpleback flying squid (Sthenoteuthis oualaniensis) still has a large potential for exploitation, and the variations in its use as a resource are highly correlated with environmental and other [...] Read more.
As an economic species widely distributed in the South China Sea (SCS), the purpleback flying squid (Sthenoteuthis oualaniensis) still has a large potential for exploitation, and the variations in its use as a resource are highly correlated with environmental and other factors. In this study, using a generalized additive model (GAM) and gradient forest analysis (GFA), in conjunction with environmental factors, the distribution of purpleback flying squid surrounding the Xisha and Zhongsha islands during the fishing moratorium period was investigated. The results indicated that catch per unit effort (CPUE) had a gradual increase from May to July 2023 in the primary fishing area surrounded the Xisha Islands during May to June, then moved southward towards 13–15° N after July. CPUE is used as an important indicator to reflect the abundance of the fishery, while the GFA results show that CPUE has a better fit than catch in this study. Therefore, the subsequent analysis focused on CPUE. Longitude and sea surface temperature (SST) were of relative higher importance, followed by sea surface salinity (SSS), latitude, chlorophyll a concentration (Chla), sea surface height (SSH), and mixed layer depth (MLD). Longitude and CPUE had a significant, positive correlation. The CPUE gradually increased with latitude within 14–16° N. The CPUE increased slowly as SST increased from 29.5 to 30.5 °C in the primary fishing area. The Chla in this fishing zone was 0–0.2 mg/m3 and displayed a significant positive association with CPUE. Conversely, SSS, SSH, and MLD had negative correlations with CPUE. These findings will promote the sustainable utilization of purpleback flying squid in the SCS. Full article
(This article belongs to the Special Issue Assessment and Management of Fishery Resources)
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<p>Schematic diagram of masked net boat (<b>a</b>) and net gear (<b>b</b>) [<a href="#B19-fishes-09-00253" class="html-bibr">19</a>].</p>
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<p>The fishing area of purpleback flying squid.</p>
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<p>Seasonal variations in the catch and CPUE of purpleback flying squid.</p>
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<p>Spatiotemporal distribution of the purpleback flying squid catch.</p>
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<p>Spatiotemporal distribution of the purpleback flying squid CPUE.</p>
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<p>The variation in the barycenter of purpleback flying squid catch (<b>a</b>) and CPUE (<b>b</b>). The colors represent different periods.</p>
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<p>Distribution of environmental factors in each season.</p>
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<p>Weighted importance (<b>a</b>) and cumulative importance (<b>b</b>) of environmental factors in explaining the distribution of the purpleback flying squid catch and CPUE based on a GFA.</p>
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<p>Effects of various factors on the CPUE of purpleback flying squid during the period from late May to early July in 2023 are depicted, with shaded areas representing the 95% confidence intervals.</p>
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15 pages, 3118 KiB  
Article
Morphological Differences and Contour Visualization of Statoliths in Different Geographic Populations of Purpleback Flying Squid (Sthenoteuthis oualaniensis)
by Moxian Chu, Bilin Liu, Liguo Ou, Ziyue Chen and Qingying Li
J. Mar. Sci. Eng. 2024, 12(4), 597; https://doi.org/10.3390/jmse12040597 - 30 Mar 2024
Viewed by 989
Abstract
Statoliths are important hard tissues in cephalopods. Significant differences are found in the external morphology of statoliths in different groups or species. In this study, stepwise discriminant analysis was used to investigate the external morphological differences in purpleback flying squid statoliths in three [...] Read more.
Statoliths are important hard tissues in cephalopods. Significant differences are found in the external morphology of statoliths in different groups or species. In this study, stepwise discriminant analysis was used to investigate the external morphological differences in purpleback flying squid statoliths in three different marine regions, comprising the East Indian Ocean (5° S–2° N, 82°–92° E), Central East Pacific Ocean (02°37′ S–0°59′ N, 99°44′ W–114°19′ W), and Northwest Indian Ocean (17°04′ N–17°18′ N, 61°05′ E–61°32′ E). The contours of statoliths were reconstructed visually by using Fourier analysis and the landmark method. The results obtained by stepwise discriminant analysis showed that the accuracy of identification was 84.4% for the traditional measurement method, 82.9% for the Fourier analysis method, and 87.3% for the landmark method. The contour visualization results showed that the purpleback flying squid statoliths were small in the Central East Pacific Ocean, and the curvature of the side region was the most obvious. The radian differentiation of statoliths was most gentle in the East Indian Ocean. In the Northwest Indian Ocean, the rostral region of statoliths was shorter and the dorsal region was smoother. The reconstruction results detected significant differences in the outer morphology of statoliths in different marine regions. The results obtained in this study show that all three methods are effective for identifying populations, but the landmark method is better than the traditional measurement method. The reconstruction of statolith contours using the Fourier transform and landmark methods provides an important scientific basis for conducting taxonomy, according to statolith morphology. Full article
(This article belongs to the Section Marine Biology)
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<p>Distribution of sampling regions.</p>
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<p>Scheme of morphological parameters of statolith. NOTE: A—TSL; B—RL; C—RW; D—DLL; E—RLL; F—LDL; G—WL; H—WW; I—MW.</p>
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<p>Mean shape. The numbers represent the landmarks’ identifiers.</p>
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<p>Scatterplot of typical discriminant functions for overall morphology of purpleback flying squid statoliths in three marine regions. The three methods, from left to right, are the traditional measurement method, Fourier analysis method, and landmark method. (CEPO = Central East Pacific Ocean, EIO = East Indian Ocean, NIO = Northwest Indian Ocean).</p>
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<p>Reconstruction of entire statolith shape and sulcus shape from the number of Fourier harmonics. Note: The number (1–20) represents the number of harmonics used for the shape. (<b>a</b>) Statolith morphology in East Indian Ocean. (<b>b</b>) Statolith morphology in Central East Pacific Ocean. (<b>c</b>) Statolith morphology in Northwest Indian Ocean.</p>
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<p>Reconstruction of entire statolith shape and sulcus shape from the number of Fourier harmonics. Note: The number (1–20) represents the number of harmonics used for the shape. (<b>a</b>) Statolith morphology in East Indian Ocean. (<b>b</b>) Statolith morphology in Central East Pacific Ocean. (<b>c</b>) Statolith morphology in Northwest Indian Ocean.</p>
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<p>Variations enlarged three times in the vector diagram for landmarks. Note: In the following order: East Indian Ocean, Central East Pacific Ocean, and Northwest Indian Ocean.</p>
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<p>Variations enlarged three times in the diagram for landmarks. Note: In the following order: East Indian Ocean, Central East Pacific Ocean, and Northwest Indian Ocean.</p>
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11 pages, 2223 KiB  
Article
Habitat Suitability of the Squid Sthenoteuthis oualaniensis in Northern Indian Ocean Based on Different Weights
by Jun Yu, Lihong Wen, Siyuan Liu, Heng Zhang and Zhou Fang
Fishes 2024, 9(3), 107; https://doi.org/10.3390/fishes9030107 - 15 Mar 2024
Viewed by 1602
Abstract
Data from the fishery of S. oualaniensis in the northern Indian Ocean from January to March and October to December 2017 to 2019 were modeled with sea surface temperature (SST), wind speed (WS), and photosynthetically active radiation (PAR). In this study, the fishing [...] Read more.
Data from the fishery of S. oualaniensis in the northern Indian Ocean from January to March and October to December 2017 to 2019 were modeled with sea surface temperature (SST), wind speed (WS), and photosynthetically active radiation (PAR). In this study, the fishing effort was used to evaluate the suitability index (SI) at SST, WS, and PAR. An integrated habitat suitability model (HSI) was developed with different weighting scenarios and weighting schemes. The optimal case was selected by calculation and comparison with the proportion of catch, effort, and catch per unit effort (CPUE) in the HSI interval (0~0.2, 0.2~0.6, 0.6~1); validation was performed using data from 2019. The weight of the optimal HSI model was 0.25 for sea surface temperature and photosynthetically active radiation, and 0.5 for wind speed. This model yielded the best performance and could accurately predict the fishing ground of S. oualaniensis in the northern Indian Ocean. The findings suggest that the integrated HSI model can predict the distribution of S. oualaniensis commendably, with wind speed as the most important factor affecting the spatial distribution of S. oualaniensis’ habitat in the northern Indian Ocean. By analyzing habitat selection by S. oualaniensis, this study verified and predicted the distribution of squid in the northern Indian Ocean, which allows the distribution of squid resources and fishing grounds to be modeled, and for the sustainable use of squid fishery resources. Full article
(This article belongs to the Section Biology and Ecology)
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<p>Research scope of the squid <span class="html-italic">Sthenoteuthis oualaniensis</span> in the Indian Ocean. The red box represents the fishing operation area for data used by the research institute.</p>
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<p>The spatial distribution of CPUE overlapped with the HSI values in 2017–2018. The larger the CPUE coverage, the higher the overlap with the HSI values.</p>
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<p>The spatial distribution of CPUE overlapped with the HSI values from 2019, calculated by the optimal model. The larger the CPUE coverage, the more it overlaps with the predicted habitat.</p>
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19 pages, 4859 KiB  
Article
Relationship between Resource Distribution and Vertical Structure of Water Temperature of Purpleback Flying Squid (Sthenoteuthis oualaniensis) in the Northwest Indian Ocean Based on GAM and GBT Models
by Chen Shang, Haibin Han, Junlin Chen, Fenghua Tang, Wei Fan, Heng Zhang and Xuesen Cui
J. Mar. Sci. Eng. 2023, 11(9), 1800; https://doi.org/10.3390/jmse11091800 - 15 Sep 2023
Cited by 4 | Viewed by 1486
Abstract
The Northwest Indian Ocean is a key fishing ground for China’s pelagic fisheries, with the purpleback flying squid being a significant target. This study uses commercial fishing logs of the Indian Ocean between 2015 and 2021, alongside pelagic seawater temperature and its vertical [...] Read more.
The Northwest Indian Ocean is a key fishing ground for China’s pelagic fisheries, with the purpleback flying squid being a significant target. This study uses commercial fishing logs of the Indian Ocean between 2015 and 2021, alongside pelagic seawater temperature and its vertical temperature difference within the 0–200 m depth range, to construct generalized additive models (GAMs) and gradient boosting tree models (GBTs). These two models are evaluated using cross-validation to assess their ability to predict the distribution of purpleback flying squid. The findings show that factors like year, latitude, longitude, and month significantly influence the distribution of purpleback flying squid, while surface water temperature, 200 m water temperature, and the 150–200 m water layer temperature difference also play a role in the GBT model. Similar factors also take effects in the GAM. Comparing the two models, both GAM and GBT align with reality in predicting purpleback flying squid resource distribution, but the precision indices of GBT model outperform those of the GAM. The predicted distribution for 2021 by GBT also has a higher overlap with the actual fishing ground than that by GAM, indicating GBT’s superior forecasting ability for the purpleback flying squid fishing ground in the Northwest Indian Ocean. Full article
(This article belongs to the Section Marine Biology)
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<p>Distribution of fish catches of purpleback flying squid in the Northwest Indian Ocean during 2015–2021.</p>
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<p>Analysis of the GAM results of the influence of spatiotemporal factors on CPUE: (<b>A</b>) year; (<b>B</b>) month; (<b>C</b>) longitude; (<b>D</b>) latitude. The solid line is the influence curve, and the 95% confidence interval is between the two dashed lines.</p>
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<p>Analysis of the GAM results of the influence of environmental factors on CPUE: (<b>A</b>) T<sub>0</sub>; (<b>B</b>) T<sub>50</sub>; (<b>C</b>) T<sub>100</sub>; (<b>D</b>) T<sub>150</sub>; (<b>E</b>) T<sub>200</sub>; (<b>F</b>) ΔT<sub>0–50</sub>; (<b>G</b>) ΔT<sub>50–100</sub>; (<b>H</b>) ΔT<sub>100–150</sub>; (<b>I</b>) ΔT<sub>150–200</sub>. The solid line is the influence curve, and the 95% confidence interval is between the two dashed lines.</p>
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<p>Analysis of the GBT model results of the influence of spatiotemporal factors on CPUE: (<b>A</b>) year; (<b>B</b>) month; (<b>C</b>) longitude; (<b>D</b>) latitude. The black curve is the influence curve of factor on CPUE, and the grey area is the 95% confidence interval.</p>
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<p>Analysis of the GBT model results of the influence of environmental factors on CPUE: (<b>A</b>) T<sub>0</sub>; (<b>B</b>) T<sub>50</sub>; (<b>C</b>) T<sub>100</sub>; (<b>D</b>) T<sub>150;</sub> (<b>E</b>) T<sub>200</sub>; (<b>F</b>) ΔT<sub>0–50</sub>; (<b>G</b>) ΔT<sub>50–100</sub>; (<b>H</b>) ΔT<sub>100–150</sub>; (<b>I</b>) ΔT<sub>150–200</sub>. The black curve is the influence curve of factor on CPUE, and the grey area is the 95% confidence interval.</p>
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<p>The monthly observed CPUE and forecast results distribution of purpleback flying squid based on GBT model in the Northwest Indian Ocean in 2021: (<b>A</b>) January; (<b>B</b>) February; (<b>C</b>) March; (<b>D</b>) April; (<b>E</b>) May; (<b>F</b>) September; (<b>G</b>) October; (<b>H</b>) November.</p>
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<p>The monthly observed CPUE and forecast results distribution of purpleback flying squid based on GAM in the Northwest Indian Ocean in 2021: (<b>A</b>) January; (<b>B</b>) February; (<b>C</b>) March; (<b>D</b>) April; (<b>E</b>) May; (<b>F</b>) September; (<b>G</b>) October; (<b>H</b>) November.</p>
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20 pages, 4184 KiB  
Article
Migration Route of Sthenoteuthis oualaniensis in the South China Sea Based on Statolith Trace Element Information
by Jiangtao Fan, Zhou Fang, Shengwei Ma, Peng Zhang, Xue Feng and Zuozhi Chen
Animals 2023, 13(18), 2811; https://doi.org/10.3390/ani13182811 - 5 Sep 2023
Viewed by 1132
Abstract
Sthenoteuthis oualaniensis (Lesson, 1830) is a pelagic species with a complex population structure and wide migration range. The trace elements in statoliths are effective indicators for reconstructing the life history of an individual. In this study, the trace elements in statoliths were determined [...] Read more.
Sthenoteuthis oualaniensis (Lesson, 1830) is a pelagic species with a complex population structure and wide migration range. The trace elements in statoliths are effective indicators for reconstructing the life history of an individual. In this study, the trace elements in statoliths were determined via laser ablation inductively coupled plasma mass spectrometry, and a multiple regression tree (MRT) model was used to trace the migration of S. oualaniensis and identify its potential habitats in the South China Sea. Na, Mg, Fe, Sr, and Ba were the effective trace elements, with significant differences found among stocks (p < 0.05). The MRT was divided into five clusters representing five life history stages. The Mg:Ca and Sr:Ca ratios decreased initially and increased thereafter, and the Mg:Ca, Sr:Ca, and Ba:Ca ratios differed significantly among the stages of the life history in each stock (p < 0.05). The hatching water temperatures for the winter and summer–autumn spawning populations were 28.05–28.88 °C (temperature at 25 m) and 27.15–27.92 °C (temperature at 25 m). The winter stock hatched in the southern South China Sea, and the larvae then migrated northwest during the summer monsoon. The summer–autumn stocks hatched in the northern South China Sea, and the larvae migrated southward under the mesoscale closed anticyclonic circulation in the northern South China Sea. These results provide insight into the migration of S. oualaniensis in the South China Sea. Full article
(This article belongs to the Section Aquatic Animals)
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<p><span class="html-italic">Sthenoteuthis oualaniensis</span> sampling site in the South China Sea. Squares, circles, triangles, and diamonds represent the spring, summer, autumn, and winter sampling sites, respectively.</p>
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<p>Analytic spots (·) in a statolith from <span class="html-italic">S. oualaniensis</span>.</p>
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<p>Change in effective elements ratio in statoliths from <span class="html-italic">S. oualaniensis</span> in a time series.</p>
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<p>Change in effective elements ratio in statoliths from <span class="html-italic">S. oualaniensis</span> in a time series.</p>
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<p>Trace element clustering of statoliths from <span class="html-italic">S. oualaniensis</span> based on a multiple regression tree model.</p>
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<p>The ratios of key trace elements to calcium in the statoliths in different clusters. (<b>a</b>–<b>c</b>) Show the summer, autumn, and winter stocks, respectively.</p>
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<p>The ratios of key trace elements to calcium in the statoliths in different clusters. (<b>a</b>–<b>c</b>) Show the summer, autumn, and winter stocks, respectively.</p>
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<p>Potential distribution areas of winter stock at different growth stages. S1, S2, S3, S4, and S5 represent individual embryonic, larval, juvenile, sub-adult, and adult stages, respectively. Heat bars represent the probability that the stock is in the predicted sea area.</p>
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<p>Potential distribution areas of summer–autumn stock at different growth stages. S1, S2, S3, S4, and S5 represent individual embryonic, larval, juvenile, sub-adult, and adult stages, respectively. Heat bars represent the probability that the stock is in the predicted sea area.</p>
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<p>Spatial distribution of migration centers at different growth stages of winter and summer–autumn stocks.</p>
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23 pages, 8037 KiB  
Article
Ontogenetic Variation and Sexual Dimorphism of Beaks among Four Cephalopod Species Based on Geometric Morphometrics
by Chao Wang and Zhou Fang
Animals 2023, 13(4), 752; https://doi.org/10.3390/ani13040752 - 19 Feb 2023
Cited by 2 | Viewed by 2228
Abstract
Investigating the ontogenetic variation of biological individuals helps us to fully understand the characteristics of evolution. In order to explore the ontogenetic variation and sexual dimorphism of the beak shape in Octopus minor, Uroteuthis edulis, Sepia esculenta and Sthenoteuthis oualaniensis of [...] Read more.
Investigating the ontogenetic variation of biological individuals helps us to fully understand the characteristics of evolution. In order to explore the ontogenetic variation and sexual dimorphism of the beak shape in Octopus minor, Uroteuthis edulis, Sepia esculenta and Sthenoteuthis oualaniensis of the China’s coastal waters, the differences between immature and mature stages and the sex-linked differences in the beak shape and size were analyzed with geometric morphometrics methods in this study. The results of Procrustes analysis of variance, principal component analysis and multivariate regression showed that the shapes of the upper beaks of O. minor, U. edulis and S. esculenta differed significantly among various ontogenetic stages (p < 0.05). The shapes of the lower beaks of U. edulis, S. esculenta and Sthenoteuthis oualaniensis were also significantly different among various ontogenetic stages (p < 0.05). The results of thin-plate spline deformation grids showed that the beaks of the four cephalopod species presented different variation patterns. This study gives us basic beak geometry morphology information for Octopus minor, Uroteuthis edulis, Sepia esculenta and Sthenoteuthis oualaniensis present in China’s coastal waters. The ontogenetic differences in beak shape might be related to extrinsic factors (diet difference and intra and interspecific competition) in habitat. Full article
(This article belongs to the Special Issue Assessment and Management of Cephalopod Fisheries and Ecosystems)
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<p>Shape and digitized landmarks (hollow dots) and semi-landmarks (solid dots) of the Cephalopods beak. (<b>a</b>): Landmark positions. (<b>b</b>): Shape description—A: Rostral tip, B: Jaw angle, C: Wing, D: Lateral wall, E: Crest, F: Hood, G: Rostrum.</p>
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<p>Beak centroid size variation of four cephalopods in different ontogenetic stages. (<b>a</b>): Upper beak; (<b>b</b>): Lower beak. I: Immature stages; M: Mature stages; A: <span class="html-italic">Octopus minor</span>; B: <span class="html-italic">Uroteuthis edulis</span>; C: <span class="html-italic">Sepia esculenta</span>; D: <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Results of principal component analysis (PCA) of upper beak of the four cephalopods, showing the first principal component (PC1) versus (PC2) and (PC3) versus (PC4) shape variation with 95% ellipse confidence intervals of immature (solid line) and mature (dashed line) beaks. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Results of principal component analysis (PCA) of upper beak of the four cephalopods, showing the first principal component (PC1) versus (PC2) and (PC3) versus (PC4) shape variation with 95% ellipse confidence intervals of immature (solid line) and mature (dashed line) beaks. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Thin-plate spline deformation grids of upper beak of the four cephalopods considered in different ontogenetic stages. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Thin-plate spline deformation grids of upper beak of the four cephalopods considered in different ontogenetic stages. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Correlativity of the regression scores of upper beak shape and predicted values versus log(Centroid Size). F–A: Immature, female; F–B: Mature, female; M–A: Immature, male; M–B: Mature, male. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Correlativity of the regression scores of upper beak shape and predicted values versus log(Centroid Size). F–A: Immature, female; F–B: Mature, female; M–A: Immature, male; M–B: Mature, male. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Results of principal component analysis (PCA) of lower beak of the four cephalopods, showing the first principal component (PC1) versus (PC2) and (PC3) versus (PC4) shape variation with 95% ellipse confidence intervals of immature (solid line) and mature (dashed line). (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
Full article ">Figure 6 Cont.
<p>Results of principal component analysis (PCA) of lower beak of the four cephalopods, showing the first principal component (PC1) versus (PC2) and (PC3) versus (PC4) shape variation with 95% ellipse confidence intervals of immature (solid line) and mature (dashed line). (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Results of principal component analysis (PCA) of lower beak of the four cephalopods, showing the first principal component (PC1) versus (PC2) and (PC3) versus (PC4) shape variation with 95% ellipse confidence intervals of immature (solid line) and mature (dashed line). (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Thin-plate spline deformation grids of lower beak of the four cephalopods considered in different ontogenetic stages. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
Full article ">Figure 7 Cont.
<p>Thin-plate spline deformation grids of lower beak of the four cephalopods considered in different ontogenetic stages. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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<p>Correlativity of the regression scores of lower beak shape and predicted values versus log(Centroid Size). F–A: Immature, female; F–B: Mature, female; M–A: Immature, male; M–B: Mature, male. (<b>a</b>) <span class="html-italic">Octopus minor</span>. (<b>b</b>) <span class="html-italic">Uroteuthis edulis</span>. (<b>c</b>) <span class="html-italic">Sepia esculenta</span>. (<b>d</b>) <span class="html-italic">Sthenoteuthis oualaniensis</span>.</p>
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19 pages, 8201 KiB  
Article
The Influence of Spatial and Temporal Scales on Fisheries Modeling—An Example of Sthenoteuthis oualaniensis in the Nansha Islands, South China Sea
by Xingxing Zhou, Shengwei Ma, Yancong Cai, Jie Yu, Zuozhi Chen and Jiangtao Fan
J. Mar. Sci. Eng. 2022, 10(12), 1840; https://doi.org/10.3390/jmse10121840 - 1 Dec 2022
Cited by 5 | Viewed by 2375
Abstract
The choice of spatial and temporal scales affects the performance of fisheries models and is particularly important in exploring the relationship between resource abundance and the marine environment. Traditional fishery models are constructed at a particular scale, and the results of the study [...] Read more.
The choice of spatial and temporal scales affects the performance of fisheries models and is particularly important in exploring the relationship between resource abundance and the marine environment. Traditional fishery models are constructed at a particular scale, and the results of the study hold only at that scale. Sthenoteuthis oualaniensis is one of the main target species of large-scale light falling-net fishing in the Nansha Islands in the South China Sea. We used the S. oualaniensis fishery in the Nansha Islands as an example to compare the performance of fisheries models for 12 spatial and temporal settings and to explore the relationship between the abundance of S. oualaniensis and the marine environment in the Nansha Islands under the optimal spatial and temporal settings. The results show that the spatial and temporal scale chosen in the construction of the fishery model is not as fine as possible in generalized additive models (GAMs) for abundance index-catch per unit effort (AI-CPUE)-based scenarios, and 0.5° with the season was the best spatial and temporal setting; meanwhile, in GAMs for AI-effort-based scenarios, 0.1° with the month was the best spatial and temporal setting. The distribution of S. oualaniensis resources in the Nansha Islands was characterized by significant seasonal variation, and the monthly center of gravity had a significant negative correlation with the Niño 3.4 index and the PDO index, with correlation coefficients of 100 and 1000, respectively. It is hypothesized that Pacific Decadal Oscillation and ENSO events affect the marine environment in the South China Sea by influencing the strength of the Kuroshio force and the degree of Kuroshio curvature, which in turn affects the distribution of S. oualaniensis in the Nansha Islands. The results help us to understand the influence of spatial and temporal scales on fisheries models and the environmental factors affecting the distribution of S. oualaniensis resources in the Nansha Islands. Thus, they provide a scientific basis for the sustainable development of S. oualaniensis fisheries in this region. Full article
(This article belongs to the Section Marine Biology)
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<p>Study area.</p>
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<p>Distribution of AI-CPUE and AI-Effort at different spatial scales.</p>
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<p>Distribution of adj-R<sup>2</sup>, AIC, and ten-fold cross-validated RMSE on 3D scatterplots based on GAMs for 12 spatial and temporal settings.</p>
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<p>Monthly center of gravity distribution for 2014–2017 (Figure <b>a</b> plotted using AI-Effort projections, Figure <b>b</b> plotted using AI-Effort).</p>
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<p>Correlation analysis of anomalous climatic events with the latitude and longitude of the monthly center of gravity (LON refers to the longitude of the center of gravity, LAT refers to the latitude of the center of gravity, Pre-LON refers to the longitude of the predicted center of gravity, and Pre-LAT refers to the latitude of the predicted center of gravity). * <span class="html-italic">p</span> &lt; 0.01, a statistically significant correlation. ** <span class="html-italic">p</span> &lt; 0.001, a highly statistically significant correlation.</p>
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<p>(<b>a</b>) Cross-correlation coefficients between the center of gravity latitude of AI-Effort and the Niño 3.4 index. (<b>b</b>) Cross-correlation coefficients between the predicted center of gravity latitude and the Niño 3.4 index and the PDO.</p>
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<p>Seasonal distribution of fishing grounds of <span class="html-italic">S. oualaniensis</span> in the Nansha Islands.</p>
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<p>(<b>a</b>) Monthly Niño 3.4 index and PDO index for 2014–2017. (<b>b</b>) Latitudinal distribution range of monthly centers of gravity for 2014–2017.</p>
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<p>Extent to which each explanatory variable explains the response variable in each of the 12 spatial and temporal settings.</p>
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17 pages, 4274 KiB  
Article
Age, Growth and Population Structure Analyses of the Purpleback Flying Squid Sthenoteuthis oualaniensis in the Northwest Indian Ocean by the Statolith Microstructure
by Yu-Zhe Ou, Hua-Jie Lu, Hong-Hao Wang, Zi-Yue Chen and Mao-Lin Zhao
Fishes 2022, 7(6), 324; https://doi.org/10.3390/fishes7060324 - 9 Nov 2022
Cited by 3 | Viewed by 1840
Abstract
A total of 1177 Sthenoteuthis oualaniensis were randomly collected from the northwest Indian Ocean from February between May 2019 and 2020 by lighting falling-net vessels. The age, growth, and population structure of S. oualaniensis were studied based on the statolith microstructure. The results [...] Read more.
A total of 1177 Sthenoteuthis oualaniensis were randomly collected from the northwest Indian Ocean from February between May 2019 and 2020 by lighting falling-net vessels. The age, growth, and population structure of S. oualaniensis were studied based on the statolith microstructure. The results showed that the range of mantle length (ML) was 123–562 mm for females and 88–273 mm for males, and the range of body weight (BW) was 78–6268 g for females and 82–518 g for males in 2019 and 2020, respectively. The hatching date extended from May to December, with the 2019 samples mainly composed of the autumn population, while the 2020 samples were mostly composed of the summer population. The analysis of covariance (ANCOVA) showed that there were significant differences in the growth of ML–age and BW–age between sexes. In the growth model of the ML–age relationship, both females and males in 2019 were best described by s linear model, and 2020 was best described by a logarithmic model. The growth model of the BW–age relationship of females and males in 2019 was best described as linear and the growth model of the BW–age relationship of females and males in 2020 was described logarithmically and exponentially, respectively. The average absolute daily growth rate (AGR) and instantaneous growth rate (IGR) for ML of the 2019 samples were 0.85 mm/d and 0.40%/d, and the average AGR and IGR for ML of the 2020 samples were 0.65 mm/d and 0.18%, respectively. The growth of S. oualaniensis samples in 2019 was faster than that in 2020. This study provided basic information on the age, growth, and population of S. oualaniensis, which will supply a scientific basis for stock assessment and sustainable development. Full article
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<p>Sample localities of <span class="html-italic">S. oualaniensis</span> in the northwest Indian Ocean.</p>
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<p>Appearance of <span class="html-italic">S. oualaniensis</span>.</p>
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<p>Composition of ML for <span class="html-italic">S. oualaniensis</span> in different years: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>Composition of BW for <span class="html-italic">S. oualaniensis</span> in different years: (<b>a</b>,<b>c</b>) female; (<b>b</b>) male.</p>
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<p>Statolith microstructure of <span class="html-italic">S. oualaniensis</span>: (<b>a</b>) showing three distinct growth zones with different incremental width; (<b>b</b>) showing the postnuclear zone (P) and dark zone (DZ); (<b>c</b>) showing the dark zone (DZ) and peripheral zone (PZ).</p>
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<p>Composition of age for <span class="html-italic">S. oualaniensis</span> in different years: (<b>a</b>) female (<b>b</b>) male.</p>
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<p>Maturity stage compositions of the two <span class="html-italic">S. oualaniensis</span> sexes in the northwest Indian Ocean in the two years of study: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>Hatching date frequency distribution of <span class="html-italic">S. oualaniensis</span> of different sexes in different years: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>The relationship between ML–age for <span class="html-italic">S. oualaniensis</span> in the northwest Indian Ocean in different years: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>The relationship between BW–age for <span class="html-italic">S. oualaniensis</span> in the northwest Indian Ocean in different years: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>Relationship between ML growth rate and age of <span class="html-italic">S. oualaniensis</span>: (<b>a</b>) AGR; (<b>b</b>) IGR.</p>
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13 pages, 3846 KiB  
Article
Statolith Microstructure Estimates of the Age, Growth, and Population Structure of Purpleback Flying Squid (Sthenoteuthis oualaniensis) in the Waters of the Xisha Islands of the South China Sea
by Huajie Lu, Ziyue Chen, Kai Liu, Yuzhe Ou, Maolin Zhao and Tianzi Sun
Fishes 2022, 7(5), 234; https://doi.org/10.3390/fishes7050234 - 2 Sep 2022
Cited by 5 | Viewed by 1769
Abstract
In this study, we aimed to estimate the age, growth, and population structure to explore the life history of purpleback flying squid (Sthenoteuthis oualaniensis) by statolith microstructure in the waters of the Xisha Islands of the South China Sea. The purpleback [...] Read more.
In this study, we aimed to estimate the age, growth, and population structure to explore the life history of purpleback flying squid (Sthenoteuthis oualaniensis) by statolith microstructure in the waters of the Xisha Islands of the South China Sea. The purpleback squid, S. oualaniensis, has been the most important economic cephalopod resource of the South China Sea; however, little is known about its life history, especially its age and population structure. The age and growth pattern have been explored via the statolith microstructure of this species of squid, specimens of which were caught randomly between January and March and between May and August of 2018, 2019, and 2020 in the waters surrounding the Xisha Islands of the South China Sea. The results indicated that the range of the mantle length (ML) was 63–229 mm for females and 59–184 for males, and the body weight (BW) ranged from 13 to 435 g for females and from 7 to 152 g for males; the ages were estimated as being between 81 and 298 days for females and between 67 and 286 days for males, respectively. The hatching date extended from January to December, with a peak between November and March of the following year, suggesting the presence of one spawning group (winter–spring group). Significant differences existed between the ML growth and the BW growth. The relationships between ML and age were best described by the linear function for females and the power function for males; the relationship between BW and age were best described by the exponential function for females and the power function for males, based on our AIC models, respectively. S. oualaniensis is a fast-growing squid; the growth rate is the fastest during the young life stage, and it decreases after the subadult stage (120–150 days). After the first spawning behavior, the inflection point of the growth was recognized at the age of 180–210 days (6–7 months). This study provided basic, favorable information for the fishery biology, ecology, and resource management of purpleback flying squid (S. oualaniensis) of the South China Sea. Full article
(This article belongs to the Section Biology and Ecology)
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<p>Site of investigations and sample collection for <span class="html-italic">S</span>. <span class="html-italic">oualaniensis</span>.</p>
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<p>Frequency distribution of mantle length for <span class="html-italic">S. oualaniensis</span> in the waters of the Xisha Islands of the South China Sea.</p>
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<p>Frequency distribution of body weight for <span class="html-italic">S. oualaniensis</span> in the waters of the Xisha Islands of the South China Sea.</p>
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<p>Statolith microstructure of <span class="html-italic">S. oualaniensis</span> from the waters of the Xisha Islands of the South China Sea (female with mantle length 138 mm, body weight 173 g, age 169 d). (<b>A</b>) The nuclear zone (N); (<b>B</b>) the post-nuclear zone (PN); (<b>C</b>,<b>D</b>) the dark zone (DZ); (<b>E</b>,<b>F</b>) the peripheral zone (PZ); (<b>G</b>) growth increments in microstructure.</p>
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<p>Frequency distribution of age structure for <span class="html-italic">S. oualaniensis</span> in the waters of the Xisha Islands of the South China Sea.</p>
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<p>Frequency distribution of back-calculated hatching dates for <span class="html-italic">S. oualaniensis</span> in the waters of the Xisha Islands of the South China Sea.</p>
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<p>Relationships between mantle length (ML) and age for <span class="html-italic">S. oualaniensis</span> in the waters of the Xisha Islands of the South China Sea.</p>
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<p>Relationships between body weight (BW) and age for <span class="html-italic">S. oualaniensis</span> in the waters of the Xisha Islands of the South China Sea.</p>
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<p>Absolute growth rates (AGRs) of mantle length and body weight for <span class="html-italic">S. oualaniensis:</span> (<b>A</b>) males, and (<b>B</b>) females.</p>
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<p>Instantaneous growth rates (IGRs) of mantle length and body weight for <span class="html-italic">S. oualaniensis:</span> (<b>A</b>) males, and (<b>B</b>) females.</p>
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15 pages, 3794 KiB  
Article
Age, Growth and Population Structure Analyses of the Purpleback Flying Squid Sthenoteuthis oualaniensis in the Northwest Indian Ocean by Beak Microstructure
by Hua-Jie Lu, Yu-Zhe Ou, Jing-Ru He, Mao-Lin Zhao, Zi-Yue Chen and Xin-Jun Chen
J. Mar. Sci. Eng. 2022, 10(8), 1094; https://doi.org/10.3390/jmse10081094 - 10 Aug 2022
Cited by 9 | Viewed by 2221
Abstract
To explore the feasibility of using beak microstructure information to estimate the age of Sthenoteuthis oualaniensis, the microstructures of the upper beaks of individual squid were applied in this work to analyze the ages and growth patterns of squid caught from February–May [...] Read more.
To explore the feasibility of using beak microstructure information to estimate the age of Sthenoteuthis oualaniensis, the microstructures of the upper beaks of individual squid were applied in this work to analyze the ages and growth patterns of squid caught from February–May 2019 and from October–December 2020 in the northwest Indian Ocean. The results indicated that the squid samples in the two years were no older than 9 months, and the samples in 2019 were autumn population and 2020 were spring population. The linear growth model of the autumn population (2019) was the best model for describing the relationship between age and ML, while the power model of the spring population (2020) was the best for describing the relationship between age and ML. The maximum instantaneous growth rate (IGR) and absolute daily growth rate (AGR) values of the spring population were 0.24%/d and 1.09 mm/d, respectively, occurring in squid between 200 and 220 days of age. The maximum IGR and AGR values of the autumn population were 0.69%/d and 1.73 mm/d, respectively, occurring in squid between 200 and 240 days of age. The period from 141–260 days (5–8 months) was considered to correspond to the subadult stage in the whole life history of S. oualaniensis in the Northwest Indian Ocean. The beak microstructure information can be effectively applied to estimate the age of S. oualaniensis individuals. Full article
(This article belongs to the Section Marine Biology)
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<p>Sample localities of <span class="html-italic">S. oualaniensis</span> in the northwest Indian Ocean.</p>
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<p>ML compositions of <span class="html-italic">S. oualaniensis</span> samples in different years: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>BW compositions of <span class="html-italic">S. oualaniensis</span> samples in different years: (<b>a</b>,<b>b</b>) female; (<b>c</b>) male.</p>
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<p>Upper beak microstructure of <span class="html-italic">S. oualaniensis</span>: (<b>a</b>) upper beak rostrum; (<b>b</b>) growth stripe and marker stripe on the hood; (<b>c</b>) upper beak RSS microstructure in 2019; (<b>d</b>) upper beak RSS microstructure in 2020; (<b>e</b>) light and dark bands and growth stripe in 2019; and (<b>f</b>) light and dark bands and growth whorl stripe in 2020.</p>
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<p>Age compositions of <span class="html-italic">S. oualaniensis</span> samples in different years: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>Maturity stage compositions of the two <span class="html-italic">S. oualaniensis</span> sexes in the northwest Indian Ocean in the two years of study: (<b>a</b>) female; (<b>b</b>) male.</p>
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<p>Hatching date frequency distributions of <span class="html-italic">S. oualaniensis</span> samples in the two years of the study.</p>
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<p>ML-age relationships of <span class="html-italic">S. oualaniensis</span> samples.</p>
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<p>Relationships between the ML growth rate and age of <span class="html-italic">S.</span> <span class="html-italic">oualaniensis</span> samples: (<b>a</b>) IGR; (<b>b</b>) AGR.</p>
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17 pages, 7242 KiB  
Article
Microbial Community Structure and Metabolic Characteristics of Intestine and Gills of Dwarf-Form Populations of Sthenoteuthis oualaniensis in South China Sea
by Xiaojuan Hu, Haochang Su, Peng Zhang, Zuozhi Chen, Yu Xu, Wujie Xu, Jie Li, Guoliang Wen and Yucheng Cao
Fishes 2022, 7(4), 191; https://doi.org/10.3390/fishes7040191 - 4 Aug 2022
Cited by 3 | Viewed by 2263
Abstract
Sthenoteuthis oualaniensis is an important biological resource in the South China Sea. However, the microbiological characteristics of this squid, especially those of the dwarf-form, are poorly understood. This study was conducted to analyze the microbial community structure and metabolic characteristics of the intestinal [...] Read more.
Sthenoteuthis oualaniensis is an important biological resource in the South China Sea. However, the microbiological characteristics of this squid, especially those of the dwarf-form, are poorly understood. This study was conducted to analyze the microbial community structure and metabolic characteristics of the intestinal and gill tissues of dwarf-form populations of S. oualaniensis. The dwarf-form squids of different sexes and gonadal maturities were collected from South China Sea in spring 2020. Results showed that Mycoplasma was the most dominant group of bacteria in the intestinal samples of the females with immature gonads (FN), females at sexual maturity (FY), and males at sexual maturity (MY) and the second-highest relative abundance group in males with immature gonads (MN). The microbial community structure in squid gills differed from that of intestinal flora. The BD1-7 clade was the dominant genus in gill samples of all groups. Furthermore, the microbial community activities in gills were higher than in intestinal groups, especially FYG. The larger dwarf-form populations had microbial communities with more robust utilization of carbon sources, assessed via average well color development (AWCD). Correlation and redundancy analysis determined that AWCD significantly positively correlated with the relative abundance of BD1-7 clade (p < 0.05). The results indicated that the dominant group of bacteria and microbial community structure were different between the intestinal and gill microbial communities in the dwarf-form S. oualaniensis populations of different sexes and maturities. Moreover, the metabolic potential of the gill microbial community was higher than that of the intestinal microbial community in the dwarf-form populations. Full article
(This article belongs to the Special Issue Gut Microbiota in Fish and Shellfish)
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Figure 1
<p>Mantle lengths of dwarf-form populations of <italic>Sthenoteuthis oualaniensis.</italic> Significant differences are indicated by different letters (<italic>p</italic> &lt; 0.05).</p>
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<p>Body masses of dwarf-form populations of <italic>Sthenoteuthis oualaniensis.</italic> Significant differences are indicated by different letters (<italic>p</italic> &lt; 0.05).</p>
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<p>Microbial diversity indices in the intestine and gill microbial samples of dwarf-form populations of <italic>Sthenoteuthis oualaniensis</italic>. (<bold>a</bold>) Observed, (<bold>b</bold>) Chao1 indices, (<bold>c</bold>) Simpson indices, and (<bold>d</bold>) Shannon indices. FNI: intestine samples of females with immature gonads, MNI: intestine samples of males with immature gonads, FYI: intestine samples of females at sexual maturity, MYI: intestine samples of males at sexual maturity; FNG: gill samples of females with immature gonads, MNG: gill samples of males with immature gonads, FYG: gill samples of females at sexual maturity, and MYG: gill samples of males at sexual maturity. * Indicates the significant difference between two samples (<italic>p</italic> &lt; 0.05) and ** indicates the extremely significant difference between two samples (<italic>p</italic> &lt; 0.01).</p>
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<p>Venn diagram of the intestine and gill microbial samples of dwarf-form populations of <italic>Sthenoteuthis oualaniensis.</italic> n represents the total OTU number of each sample.</p>
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<p>Dominant bacterial community composition in intestinal and gill tissues of dwarf-form squid. (<bold>a</bold>) Phylum level, (<bold>b</bold>) genus level.</p>
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<p>Inter-group variation of intestinal and gill tissues of dwarf-form squid. (<bold>a</bold>) LDA score; (<bold>b</bold>) LEfSe cladogram.</p>
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<p>Inter-group variation of intestinal and gill tissues of dwarf-form squid. (<bold>a</bold>) LDA score; (<bold>b</bold>) LEfSe cladogram.</p>
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<p>Correlation network analyses of the microbial communities of dwarf-form squid at the bacterial phyla level. The node size represents the abundance of each phylum. The green lines between phyla indicate a positive relationship, while the red lines indicate a negative relationship.</p>
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<p>Average well color development (AWCD) variation in EcoPlates.</p>
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<p>Variations in carbon source utilization by microbial communities of intestinal and gill tissues of dwarf-form squid. (<bold>a</bold>) Polymers, (<bold>b</bold>) Carboxylic acids, (<bold>c</bold>) Amino acids, (<bold>d</bold>) Carbohydrate, (<bold>e</bold>) Amines and (<bold>f</bold>) Others.</p>
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<p>Variations in carbon source utilization by microbial communities of intestinal and gill tissues of dwarf-form squid. (<bold>a</bold>) Polymers, (<bold>b</bold>) Carboxylic acids, (<bold>c</bold>) Amino acids, (<bold>d</bold>) Carbohydrate, (<bold>e</bold>) Amines and (<bold>f</bold>) Others.</p>
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<p>Redundancy analysis ordination of data.</p>
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16 pages, 2421 KiB  
Article
Beak Microstructure Estimates of the Age, Growth, and Population Structure of Purpleback Flying Squid (Sthenoteuthis oualaniensis) in the Xisha Islands Waters of the South China Sea
by Ziyue Chen, Huajie Lu, Wei Liu, Kai Liu and Xinjun Chen
Fishes 2022, 7(4), 187; https://doi.org/10.3390/fishes7040187 - 26 Jul 2022
Cited by 8 | Viewed by 2885
Abstract
This study aimed to explore the feasibility of using an upper beak microstructure to estimate the age of purpleback flying squid (Sthenoteuthis oualaniensis). From these microstructures, the age and growth of squid caught from January to March and May to August [...] Read more.
This study aimed to explore the feasibility of using an upper beak microstructure to estimate the age of purpleback flying squid (Sthenoteuthis oualaniensis). From these microstructures, the age and growth of squid caught from January to March and May to August in 2018, 2019, and 2020 in the waters surrounding the Xisha Islands in the South China Sea were determined. We found three typical growth zones (the hood region, crest region, and axis), abnormal increments (checks), and erosion in the beak examination. The average dorsal mantle length (ML) of males and females was 112.13 (±15.23 mm) and 119.67 mm (±24.50 mm), respectively, and no squid were older than 10 months. The peak hatching dates, according to back calculations, were from October to January of the next year. All sampled squid belonged to the autumn/winter cohort. Significant sex differences were found in the relationship between ML and age in squid with similar growth patterns. Exponential models best described the relationships of ML with age and body weight (BW) for both sexes. However, a linear model best described the relationship between age and upper rostrum length (URL). The maximum absolute daily growth rates (AGR) of BW were reached during days 240–270 for both sexes. The maximum AGRs in ML were reached during days 180–210 and 240–270 for males and females, respectively. The period of 120–150 days (4–5 months) was considered the sub-adult stage of S. oualaniensis in the Xisha Islands waters of the South China Sea. This study confirmed that the beak microstructure provides good age estimates for purpleback flying squid (S. oualaniensis). Full article
(This article belongs to the Section Biology and Ecology)
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<p>Site of investigations and samples for <span class="html-italic">S. oualaniensis</span>.</p>
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<p>The microstructure of the <span class="html-italic">S. oualaniensis</span> rostrum sagittal section (RSS). (<b>a</b>) The RSS of the upper beak; (<b>b</b>) microstructure of the RSS; (<b>c</b>) characteristic increments in the hood region and crest region; (<b>d</b>) daily and sub-daily increments; and (<b>e</b>) checks and erosion of the rostrum tip.</p>
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<p>Distribution of mantle lengths according to maturity stage for <span class="html-italic">S. oualaniensis</span> (<b>a</b>) males and (<b>b</b>) females.</p>
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<p>Distribution of body weights in both sexes of <span class="html-italic">S. oualaniensis</span>.</p>
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<p>Age distribution of <span class="html-italic">S. oualaniensis</span> individuals of different sexes.</p>
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<p>Age distribution by maturity stage for <span class="html-italic">S. oualaniensis</span> (<b>a</b>) males and (<b>b</b>) females.</p>
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<p>Hatching date distribution of <span class="html-italic">S. oualaniensis</span> individuals of different sexes.</p>
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<p>The mantle length–age, body weight–age, and upper rostrum length–age relationships in <span class="html-italic">S. oualaniensis</span>.</p>
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<p>Absolute growth rates (AGRs) of mantle length and body weight for <span class="html-italic">S. oualaniensis</span> (<b>a</b>) males and (<b>b</b>) females.</p>
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<p>Instantaneous growth rates (IGRs) of mantle length and body weight for <span class="html-italic">S. oualaniensis</span> (<b>a</b>) males and (<b>b</b>) females.</p>
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<p>Age at first maturity for <span class="html-italic">S. oualaniensis</span> males (128 d) and females (152 d).</p>
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