Stock Structure Analysis of the Japanese Spanish Mackerel Scomberomorus niphonius (Cuvier, 1832) Along the China Coast Based on Truss Network

JIANG Yiqian, ZHANG Chi, YE Zhenjiang, XU Binduo, TIAN Yongjun, ,and WATANABE Yoshiro,

1) College of Fisheries, Ocean University of China, Qingdao 266003, China

2) Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China

3) Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8564, Japan

Abstract The Japanese Spanish mackerel Scomberomorus niphonius (Cuvier, 1832) is widely distributed in the subtropical and temperate waters of the northwestern Pacific Ocean, supporting one of the most important commercial fisheries in China. However,ignoring the potential population structure changes induced by fishing pressure and climate change may undermine the population stability under the current management strategy. In this study, the population structure of the Japanese Spanish mackerel was investigated based on a morphometric truss network system. A total of 534 individuals were randomly collected from commercial gill nets spanning eight major spawning grounds in the Bohai, Yellow, and East China Seas during the peak spawning seasons respectively. A total of 17 measurements (including eye diameter) were conducted in each specimen and subjected to principal component analysis(PCA) and discriminant function analysis (DFA). The results of PCA indicated that the first two factors cumulatively caused 78.38%of the total morphometric variation and observable differences, primarily fin the caudal and trunk areas. The results of DFA revealed that the eight spawning groups can be divided into three stocks, i.e., southern, middle, and northern stocks, with 68.7% of total accuracy. In contrast to previous studies, the spawning groups of the Japanese Spanish mackerel demonstrated a tendency to disperse to northern regions. In conclusion, this study found that to maintain the stability of the population structure and the total production of Japanese Spanish mackerel S. niphonius (Cuvier, 1832), a newly revised management method should be developed and implemented.

Key words Japanese Spanish mackerel; population structure; truss morphometry; management framework

1 Introduction

Fish stocks or populations are the fundamental biological unit considered in the assessment and management of fisheries, but the choice of spatial management alone does not necessarily incorporate the entire available suite of potentially meaningful biological information (Carvalho and Hauser, 1994; Gaggiotti, 2006; Reiss et al.,2009). In fact, a fish population can be composed of several subpopulations, each having its own demographic properties and capabilities for recovery after overexploitation. Such subpopulations can be relatively discrete and self-replenishing while still maintain sufficient exchange to preserve genetic homogeneity through the dispersal of individuals (Hanski and Simberloff, 1997; Hanski, 1999).Therefore, population identity and the underlying metapopulation structure should be incorporated together within resource assessments made in support of fishery management (Reiss et al., 2009). Otherwise, it could lead to the local depletion and the associated loss of genetic diversity (Stephenson, 1999; Hutchinson, 2008; Ying et al.,2011).

The Japanese Spanish mackerel Scomberomorus niphonius is an epipelagic, neritic species that is widely distributed in the subtropical and temperate waters of the northwestern Pacific Ocean and supports one of the most important commercial fisheries in China (Wei and Zhou, 1988).Previous studies with tagging, genetic techniques, and otolith shape analysis have detected the metapopulation structure of Japanese Spanish mackerel, identifying several distinct subpopulations (Liu et al., 1982; Shui et al., 2009;Zhang et al., 2016). Long-term fishing pressure and environmental changes may cause the fluctuations in annual landings and the life history trait shifts within subpopulations (such as earlier maturation and faster growth)(Qiu and Ye, 1996). To protect the fish resources, a series of management measures had been enacted in China over the past 5 decades, such as the conservation of juveniles and spawning stocks, fishing closure in summer, and protection of spawning grounds (Qiu et al., 2007). Although these management measures have made positive results,several problems still need to be solved (Qiu et al., 2007).

Regime shift has been observed in the Japanese Spanish mackerel (Tian et al., 2006), which is the hypothesized first response of a population to climate change. Such population change induced by climate, known as local adaptation, has also been observed in the small yellow croaker (Larimichthys polyactis), a species subjected to similar pressures in the China Seas. Therefore, it is important to study the effects of exploitation and climate changes on the population structure of the Japanese Spanish mackerel to provide a basis for effective fishery management.

Each identification method (such as traditional morphologics, otolith morphologics, and genetic methods) offers a unique perspective on a population structure from one point. Thus, multidisciplinary techniques are preferred to give the whole picture of the fish resources from different points. Phenotypic characterisics can be particularly important indicator of population identification, especially where differences are caused by environmental influences(Pinheiro et al., 2005; Francoy et al., 2012; Pazhayamadom et al., 2015). The ‘Truss network analysis’ (Strauss and Bookstein, 1982) has been increasingly applied in stock identification of species. It has more advantages over the traditional morphometric methods in discriminating‘phenotypic stocks’, which are groups of individuals with similar growth, mortality, and reproductive rates (Booke,1981).

In the present study, we used the morphometric truss network system analysis to study the current population structure of the Japanese Spanish Mackerel, which will be important for the conservation and sustainable utilization of the Japanese Spanish mackerel resources.

2 Materials and Methods

2.1 Sampling

A total of 534 Japanese Spanish mackerel specimens(Table 1) were randomly captured from eight spawning grounds in the coastal areas of China during mid- and late May (peak spawning season) in 2014 and used for morphometric analysis (Fig.1). They were captured with commercial gill net in the depth of 10 m. Only sexually mature specimens were used in this study (376 < FL < 603 mm),which were primarily 1-year-old individuals (FL, fork length).Undamaged fish were placed in isolated boxes with ice and transported to laboratory for analysis. In the laboratory, the FL (±1 mm) and eye diameter (mm) were measured and sex was determined for each individual.

Table 1 Japanese Spanish mackerel samples in the 2014 spawning season in the coastal areas in China

Fig.1 Sampling locations of the Japanese Spanish mackerel in 2014.

All animal experiments were conducted in accordance with the guidelines and approval of the respective Animal Research and Ethics Committees of Ocean University of China (Permit Number: 20141201. http://www.gov.cn/gong bao/content/2011/content_1860757.htm). Endangered or protected species were not involved in the field studies.

2.2 Morphometric Data

In the laboratory, high-resolution digital photographs of the samples were taken using a Nikon D80 camera on the left side of each fish after thawing the fish under running tap water. A total of eight landmarks were defined and recorded as X-Y coordinates. Connecting these landmarks,we set a truss box of 16 lines as described by Strauss and Bookstein (1982) (Fig.2). Measurements of the 16 distances were obtained using the following three software programs: tpsUtil v1.58, tipsDig2 v2.17 (Rohlf, 2006), and Paleontological Statistics (Hammer et al., 2001). Including eye diameter, 17 morphometrics were used in the subsequent multivariate data analysis.

Fig.2 Digital image of the Japanese Spanish mackerel showing 8 landmarks and the 16 distances used in the morphometbric analysis extracted from 8 points truss. The 8 points in the truss network represent: 1, Tip of snout; 2, frontal insertion of the first dorsal fin; 3, frontal insertion of the second dorsal fin; 4, dorsal side of caudal peduncle, at the nadir; 5, ventral side of caudal peduncle, at the nadir; 6, origin of anal fin; 7, origin of pelvic fin; 8, termination of maxilla.

2.3 Multivariate Analysis

In general, morphometric measurements are closely correlated with fish size (Bookstein et al., 1985). To remove the effect of fish size on morphometric characteristics, an allometric method (Elliott et al., 1995) was adapted before conducting multivariate data analysis. Standardized morphometric measurements (Ms) were calculated for each individual fish as follows:

where M is the original measurement; L0is the fork length of the fish; Lsis the overall mean of fork length for all fish from all samples in each analysis; and b is estimated for each character from the observed data as the slope of the regression of logM on logL0using all fish from each group. The results derived from the allometric method were confirmed by assessing the significance of the correlation between the transformed variables and fork length (Turan, 1999). We found no external sexual dimorphism in the Japanese Spanish mackerel (one-way analysis of variance (ANOVA)); therefore, the sexes were pooled together in the subsequent analysis. To test whether the data transformation was effective in eliminating the size effect on data, bivariate correlation analysis was performed between the transformed variables and the fork length of the fish. ANOVA was performed to identify whether there were any significant differences among the eight spawning grounds for each characteristic. Principal component analysis (PCA) was used to determine which morphometric measurement(s) among the specimens most effectively differentiated the populations (Mohaddasi et al.,2013; Purushothaman et al., 2017). Next, discriminant function analysis (DFA) was used to determine the similarity among the spawning grounds and to explore the effectiveness of variables in predicting different group locations(Jolliffe et al., 1988; Loy et al., 2008). Each individual was assigned to the group with the nearest centroid with 95%confidence intervals derived from the DFA, and the population centroids were used to visualize the relationships between the groups. The success rate of classification was evaluated based on the percentage of individuals correctly assigned into the original sample (jackknife cross-validation). All the above mentioned statistical analyses were performed using SPSS v20.

3 Results

None of the standardized morphometric characteristics exhibited a significant correlation with the fork length of the fish, indicating that the effects of fish size had been successfully removed by the allometric transformation.Among the eight spawning groups, all 17 morphometric characteristics were found to be significantly different (P< 0.001).

The results of PCA indicated that the first two components cumulatively explained 78.38% of the total morphometric variation, with eigenvalues of 12.17 and 1.15,respectively (Table 2). The first principal component (PC1)accounted for 71.02% of the total variance. All the variable loadings (except eye diameter) were significantly and approximately equal, indicating the presence of size effect on the truss morphometric characteristics. The highest component loadings were mostly in the caudal peduncle region (94.3%) of the fish body and the trunk (94.8%).The cephalic region occupied the lowest overall component loadings. The second principal component (PC2) accounted for 7.36% of the total variation and was mostly correlated to eye diameter.

Table 2 Component loadings of two principal components for morphometric measurements in the Japanese Spanish mackerel

Wilks’ lambda tests of DFA revealed significant morphometric differences between all spawning components.The first six functions demonstrated highly significant differences (P < 0.001), while only for the seventh function no significant difference was observed. Forward DFA of the 17 variables resulted in seven discriminant functions(DFs). The seven DFs separately described 50.0%, 19.5%,13.5%, 7.8%, 5.7%, 2.4% and 1.0% of the total morphological variation in the sample (Table 3). The morphometric measurements with meaningful loadings on discriminant function 1 (DF1) were L3to4, L4to6, L3to5, L5to6,L2to6, L2to3, L6to7, L3to7 and L1to7, explaining 50.0%of the total variance. The horizontal and crossed direction characteristics along the entire body of the fish were the most effective in predicting different group locations. The second discriminating function (DF2) explained 19.5% of the total variance, and no distance variable showed significant loading. The DF1 vs. DF2 plot explained 69.5% of the total variance among the samples, which represented intermingling among some Japanese Spanish mackerel spawning groups from the coastal area of China (Fig.3).DFA generated a 60.3% correct classification rate, andthe cross-validation test results were similar (56.4%). The percentage of correctly classified fishes was the highest in the Fuzhou sample (80.4%), whereas the Lvsi component’s discriminant success was the lowest (22.0%) and overlapped with other groups heavily (Table 4).

Table 3 Morphometric measurement contributions to discriminant functions of the Japanese Spanish mackerel

Fig.3 DFA plot of 17 morphometric variables used for the Japanese Spanish mackerel from eight spawning grounds of the coastal area of China.

Table 4 Percentage of specimens classified in each spawning ground and after validation for morphometric measurements for the Japanese Spanish mackerel along China coast†

4 Discussion

In recent years, some endangered and overexploited species have gained recovery to some degree through effective fishery management measures (Hutchings et al.,2010). However, traditional fishery management measures sometimes fail when analyzing complex and dynamic population structures. A major reason of such failure is the metapopulation structures of a species is ignored (Murawski, 2010). Therefore, an essential premise for effective fishery management and assessment is to identify the potential metapopulation structure changes induced by climate change.

The truss-based analysis of morphometric characteristics indicated significant phenotypic heterogeneity among the Japanese Spanish mackerel samples collected from different locations in the coastal areas of China. PC1 of the factor analysis was most substantially related to major caudal area of the fish, which could be a consequence of phenotypic plasticity in response to local hydrological conditions and environmental characteristics during migration.The morphological variation in the caudal area may differ based on water velocity. For example, Brook charr (Salvelinus fontinalis) reared in high-velocity treatments developed larger caudal fin heights and deeper caudal peduncles than fish reared in low-velocity treatments (Imre et al., 2002). Several different regions in China with diverse oceanographic conditions probably have similar effects.

The combined influence of the Yellow Sea Warm Current and the Bohai Sea Coastal Waters (Zhang et al., 2013)results in relatively static water conditions for the Bohai Sea. Effectively, spawning fishes in the Bohai Sea experience lower temperatures during spawning migration.In this condition, the body of individuals from the Bohai Sea spawning groups (LDB and LZB) is stockier, especially the caudal portion. Conversely, the other regions are influenced by the colder and more variable Kuroshio Current, the Tsushima Warm Current, and the Yellow Sea Warm Current, resulting in more dynamic water conditions. Our results support the hypothesis that the fish from other spawning grounds is characteristically more slender to withstand the faster water motions. The second factor was mostly correlated with eye diameter, which may reflect regional differences in turbidity (Matthews, 1998). According to Ostrand and Wilde (2002), the abundance of small-eyed species increased along a turbidity gradient in the upper Brazos River, Texas. A previous research has also demonstrated that the turbidity of Bohai and Yellow Seas is higher than that of the East China Sea (Zhu and Zhao,1991).

Discriminant function analysis (DFA) is a useful method to distinguish different stocks of the same species (Karakousis et al., 1991). In this study, the results of DFA exhibited a cross-validated deviation that explained 14.6%–77.3% of the total variance, with an average rate of 56.4%.Fish collected from the eight spawning grounds were divided into southern (FZ), middle (QD, HZB, LS, ZS), and northern (HY, LZB, LDB) stocks (Fig.4), which was consistent with the otolith analysis (Zhang et al., 2016). In contrast to previous research (Shui et al., 2009), the Zhoushan spawning group was more similar to the middle stock, whereas the Fuzhou group showed the highest isolation. The spawning groups of the Japanese Spanish mackerel exhibited a tendency to disperse to northern regions. Climate change is one of the primary causes for the variations in the population structure (Lu and Lee, 2014).An earlier study indicated that fishing might contribute to a shift in distribution of the South African sardine (Coetzee et al., 2008). Fishing might result in variations in the population structure as well. The cross-validation test rates of the three stocks ranged from 60.8% to 71.7% in this study (Table 5). In general, the south East China Sea spawning group (FZ) can be considered as a distinct subpopulation, and the middle and northern stocks is the other subpopulation, which appears to amalgamate the metapopulation structure of Japanese Spanish mackerel along the coast of China with that of the southern East China Sea subpopulation.

Fig.4 DFA plot of 17 morphometric variables used for the Japanese Spanish mackerel between three subpopulations.

Table 5 Cross-validation matrix for morphometric measurements between identified subpopulations†

According to the results of this study, morphometric analysis is an effective tool to discriminate the Japanese Spanish mackerel stocks in the coastal areas of China.Our results demonstrated division of the Japanese Spanish mackerel population segments into three stocks along the Chinese coast, providing additional evidence for the existence of metapopulation structure in the Japanese Spanish mackerel. A precise discrimination of the metapopulation structure is a prerequisite for an accurate assessment of fish resources and an effective management of fisheries.Therefore, understanding and managing the metapopulation structure are important to ensure population stability.However, due to the increasing human activities and climate changes, there have been changes in the population structure of this fish. These changes have large impacts on subpopulations, some of which may disappear as a result of continued overfishing and environmental changes (Hsieh et al., 2010). Therefore, a series of new and accurate measures (such as the protection of spawning stock and young fishes and the limitation of the total yield of fishing)should be drawn up to optimize the current management policy to maintain the stability of the population and the sustainability of resources. Management measures should be adaptive to specific subpopulations and consider the complex dynamics of each subpopulation. Furthermore, the application of a genetic analysis would be another effective method for discriminating the stock structure, which is worthy to be conducted in the future.

5 Conclusions

The findings of this study reveal the power of the truss network system for the identification of the Japanese Spanish mackerel stocks, which can help in decision support functions for the management of this fish population in this region. The increasing human activities and climate changes have resulted in the changes of the population structure of Japanese Spanish mackerel through changes in the spawning grounds. Particular changes in the population structure have been detected in the Fuzhou spawning group.Therefore, effective fishery management and assessment of this resource should consider the metapopulation structure rather than a single unit.

Acknowledgements

This work was supported by the Fundamental Research Funds for the Central Universities of Ocean University of China (Nos. 201762015 and 201822027). We are grateful to Prof. Andrew Bakun (University of Miami) and Dr.Robert Boenish (Environmental Defense Fund) for their valuable comments and language polishing.