Introduction

Crustaceans are important marine organisms, and include both pelagic and benthic groups. Some species have importantly commercial value, including Decapoda and Stomatopoda. Decapoda and Stomatopoda play important roles in marine ecosystems, and provide a large amount of high-quality proteins for human consumption. With the decline of fish stocks, the commercial importance of crustaceans has increased in the world fisheries (Tully et al. 2003). However, the biomass of crustaceans has decreased in the offshore waters of China for half a century because of multiple stressors, including overfishing, environmental pollution and climate change (Jin 2003; Jin et al. 2013). The biomass ratio of crustaceans has increased due to the slower rate of decline than fish (Wu et al. 2016, 2018). In 2017, the total catch of crustaceans in the offshore waters of China was 2.08 million tons, which accounted for 18.66% of the total fisheries catch (China fisheries statistics yearbook 2018).

The Yellow Sea is an important fishery in China, where there are many fishing grounds, such as Yanwei, Shidao, Haizhou Bay and Lvsi. A variety of species of commercially important crustaceans inhabit the Yellow Sea, and include Fenneropenaeus chinensis, Trachypenaeus curvirostris, Metapenaeus joyneri, Crangon affinis and Portunus trituberculatus. Due to the influence of the Kuroshio Current, the Yellow Sea Cold Water Mass and the coastal low-salt water system, NECS is a good habitat for marine organisms, such as shrimps and crabs, to breed, feed and grow (Huang et al. 2009). The crustacean resources in NECS are rich in species diversity and large in quantity. Specifically, more than ten species of these species occur with high economic value (Lu et al. 2013). This study aimed at contributing to a better understanding of community dynamics of crustaceans in the Yellow Sea and NECS through evaluating the seasonal and regional changes in species composition, biomass structure, biodiversity and distribution of crustaceans. In addition, the results of this study should provide scientific support for the sustainable utilization of crustaceans in the Yellow Sea and NECS.

Results

Changes in species composition

A total of 78 species of crustaceans belonging to 2 orders, 31 families and 55 genera were captured in the Yellow Sea and NECS during 2014–2015. The number of species, genera, families and orders of crustaceans caught in each season were listed (Table 1). Overall, the number of species, genera, and families of crustaceans in the Yellow Sea and NECS was highest in Oct-2014 (autumn), followed by August 2014 (summer) and May-2015 (spring), and lowest in Jan-2015 (winter).

Table 1 Species composition of crustaceans in the Yellow Sea and the northern East China Sea
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According to the species composition of commercially important crustaceans captured during 2014–2015, the species diversity of crustaceans changed significantly in different subareas. The number of species, genera, families and orders of crustaceans caught in each subarea were listed (Table 2). Overall, the species diversity of crustaceans decreased with the increasing latitude. The species diversity index of crustaceans was highest in NECS, followed by the southern Yellow Sea (SYS) and the central Yellow Sea (CYS), and lowest in the northern Yellow Sea (NYS).

Table 2 Species composition of crustaceans by subarea during 2014–2015
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The results illustrated the seasonal and regional changes of the relative biomass density of commercially important crustaceans in the Yellow Sea and NECS (Fig. 1). Overall, the relative biomass density of crustaceans was highest in Oct-2014, followed by Aug-2014 and Jan-2015, and lowest in May-2015. According to the average biomass density in four seasons, shrimp was the most biomass-dominant (6.42 kg/h), followed by crab (5.11 kg/h) and squillid (0.18 kg/h). In the northern and central Yellow Sea, the average biomass density of crustaceans in four seasons was 10.00 kg/h and 9.41 kg/h, respectively. Shrimps were the most biomass-dominant accounting for 94.55% and 95.52% of the total biomass of crustaceans, respectively. In SYS, the average biomass density of crustaceans in four seasons was 14.01 kg/h. Crab and shrimp accounted for 51.61% and 45.99% of the total biomass of crustaceans, respectively. The comparative analysis of the biomass density of different subareas showed that the difference between any two subareas was not significant (P > 0.05). The biomass density of crustaceans was highest in Oct-2014 followed by Aug-2014 and Jan-2015, and lowest in May-2015. In NECS, the average biomass density of crustaceans in four seasons was 12.61 kg/h. Crab was the most biomass-dominant accounting for 73.20% of the total biomass of crustaceans. The biomass density of crustaceans was highest in Aug-2014, followed by Oct-2014 and Jan-2015, and lowest in May-2015. The comparative analysis of the biomass density in different seasons showed that the difference between any two seasons was not significant (P > 0.05), except for that between Oct-2014 and May-2015 (P < 0.05).

Fig. 1
figure 1

Seasonal and regional changes of the relative biomass density of crustaceans during 2014–2015 (a North Yellow Sea; b Central Yellow Sea; c Southern Yellow Sea; d Northern East China Sea; e Total)

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Figure 2 displays the seasonal and regional changes of the biomass-dominant species of commercially important crustaceans in the Yellow Sea and NECS. Overall, the most biomass-dominant species was C. affinis in Oct-2014, Jan and May-2015, and P. trituberculatus in Aug-2014 in the Yellow Sea and NECS. The most biomass-dominant species changed in different subareas. In NYS, C. affinis was the most biomass-dominant species in four seasons accounting for more than 59% of the total biomass of crustaceans. In CYS, C. affinis was also the most biomass-dominant species in four seasons accounting for more than 72% of the total biomass of crustaceans. In SYS, the most biomass-dominant species was P. trituberculatus in August and Oct-2014, accounting for 66% and 41% of the total biomass of crustaceans, respectively. C. affinis was the most biomass-dominant species in January and May accounting for 35% and 25%, respectively. In NECS, P. trituberculatus was the most biomass-dominant species in August and October accounting for 53% and 61%, respectively. Ovalipes punctatus was the most biomass-dominant species in January and May accounting for 62% and 43%, respectively.

Fig. 2
figure 2

Seasonal and regional changes of the biomass-dominant species of crustaceans during 2014–2015

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Seasonal and regional changes in biodiversity

We compared the seasonal variations of the biodiversity of commercially important crustaceans in different subareas. Overall, the seasonal trend of the two diversity indices (J′ & H′) was similar, which was highest in Oct-2014, followed successively by May-2015, Jan-2015 and Aug-2014. Unlike J′ and H′, Margalef’s richness index (D) was highest in Jan-2015 followed successively by May-2015, Oct and Aug-2014. The regional trend of the three diversity indices (D, J′ & H′) was similar, which was highest in NECS, followed by SYS (Fig. 3).

Fig. 3
figure 3

Seasonal and regional changes of the biodiversity of crustaceans during 2014–2015

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The significance of the difference in the diversity indices (D, J′, H′) was tested between different areas and different seasons (Table 3). H′ and D in NYS was significantly lower than that in SYS (P < 0.01). D in NYS was significantly lower than that in NECS (P < 0.01). J′ in CYS was significantly lower than that in NECS (P < 0.01). In Aug-2014, H′ was significantly lower than that in Jan-2015 and May-2015 (P < 0.05). In Oct-2014, D was significantly lower than that in Jan-2015 (P < 0.05). In Aug-2014, J′ was significantly lower than that in Oct-2014 and Jan-2015 (P < 0.05).

Table 3 The significance level of the difference in the diversity indices between different areas and seasons
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Seasonal changes in biomass distribution

Figure 4 displays the seasonal changes of the biomass distribution of commercially important crustaceans in the Yellow Sea and NECS. Due to the absolute dominance of C. affinis, shrimps accounted for 94.55% and 95.52% of the total biomass of crustaceans in NYS and CYS during 2014–2015, respectively. As the decline of the biomass proportion of shrimp, crab became the most dominant in SYS and NECS. Overall, shrimp was the most biomass-dominant in high latitude waters, and crab was biomass-dominant in the Yangtze River Estuary and its adjacent waters.

Fig. 4
figure 4

Seasonal changes in the biomass distribution of crustaceans in the Yellow Sea and the northern East China Sea during 2014–2015

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Correlation between crustacean density and environmental factors

Table 4 shows that the correlation was not significant in each season (P > 0.05) between the density of commercially important crustaceans and the environmental factors including water depth, sea bottom temperature, salinity and zooplankton density.

Table 4 Correlation between the individual density of crustaceans and environmental factors
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The correlation between Shannon–Wiener diversity index (H′) of commercially important crustaceans and water depth was not significant (P > 0.05). The correlation between H′ of crustaceans and salinity was significant (P < 0.05) in October 2014, and extremely significant (P < 0.01) in January 2015. In addition, the correlation between H′ of crustaceans and zooplankton density was significant (P < 0.05) in May 2015 (Table 5). Overall, salinity has the highest correlation with H′ of crustaceans, followed by zooplankton density, sea bottom temperature and water depth. Both water depth and sea bed temperature have no significant correlation (P > 0.05) with H′ of crustaceans in any season.

Table 5 Correlation between Shannon–Wiener diversity index (H′) of crustaceans and the environmental factors
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Discussion

In this study, a total of 42 species of commercially important crustaceans were captured in January 2015, which was 10–15 species less than that in other seasons. This phenomenon may be explained by 10 unexecuted survey sites due to bad weather in winter. The unexecuted survey sites reflect a reduction in survey area. Some studies have proved that there are more species in a larger area (Darlington 1959; Dony 1963; Williams 1943), which may be explained by the following facts: (1) there are more individuals in a larger area (Williams 1964); (2) there are more habitats in a larger area (Coleman 1982); and (3) there are more biogeographical components in a larger area (Hart and Horwitz 1991). The results of this study verify the classical theory above, and expand its scope to marine crustaceans.

In each subarea of the Yellow Sea, the seasonal variation trend of the biomass of commercially important crustaceans was similar, which was highest in Oct-2014 and lowest in May or Jan-2015. In NECS, the biomass density of crustaceans was highest in Aug-2014, followed by Oct-2014, and lowest in May-2015. This phenomenon may be explained by the following reasons: (1) The fishing moratorium was from 1st June to 1st September in most of the Yellow Sea, and from 1st June to 1st August in NECS during 2014–2015. Crustaceans grew quickly during the closed fishing season. Thereafter, the biomass density of crustaceans declined gradually due to fishing. So the biomass density of crustaceans was highest in Oct-2014 in the Yellow Sea, and Aug-2014 in NECS. (2) Most crustaceans breed during the period from April to June, and die after breeding. Meanwhile, the larva has not yet grown up. So the biomass density of crustaceans is low in May in the Yellow Sea and NECS.

Biologists have been fascinated by the latitudinal gradient of increasing biodiversity from the polar regions to the equator since the time of Darwin (Andrew and James 2006; Darlington 1959; Fischer and Alfred 1960; Jiang and Ma 2009; Pianka 1966). Previous research data indicated that this gradient holds for nearly all major groups of terrestrial mammals, birds, and aquatic and marine taxa (Allen et al. 2002; Blackburn and Gaston 1997; Rohde 1992; Rosenzweig 1992; Simpson 1964; Willig et al. 2003). The results of this study verify the classical theory of latitudinal gradient and expand its scope of application to marine crustaceans. In this study, the number of crustacean species increased with the decreasing latitude. A total of 72 species of crustaceans were captured in NECS, which decreased to 45 species in SYS, 35 species in the Central Yellow Sea, and 26 species in NYS, respectively. In general, when the sampling sites shifted south by one latitudinal degree, Margalef’s richness index (D) of crustaceans increased by 0.10 in those waters. Although there are some studies concerning the decline of marine biodiversity with increasing latitude (Allen et al. 2002; Willig et al. 2003), the reports do not quantify the extent to which the diversity index decreases with the increasing latitude.

Usually, the variational trend of Pielou’s evenness index (J′) is opposite to Margalef’s richness index (D), but the variational trend of the above two indices is consistent in this study. When the sampling sites shifted south by one latitudinal degree, J′ of commercially important crustaceans increased by 0.03 in the study sites. The explanation for this phenomenon is that the dominance of C. affinis’ decreases as the sampling sites shift south, resulting in the increase of J′. Shannon–Wiener index (H′) is a comprehensive indicator, which reflects species richness and species evenness. In this study, the variational trend of H′ was the same as D when the sampling sites shifted south by one latitudinal degree; H′ of crustaceans increased by 0.09 in those sites.

The water temperature gradually rises in the Yellow Sea and the East China Sea with decreasing latitude(Ju and Xiong 2013) resulting in the decreasing biomass proportion of cold-temperate species, and the increasing biomass proportion of warm-temperate species. As a cold-temperate species, C. affinis was the biomass-dominant species in NYS and CYS accounting for 72.75% and 82.75% of the total biomass of crustaceans during 2014–2015, respectively. The biomass proportion of C. affinis decreased to 28.75% in SYS and 6.01% in NECS with decreasing latitude during 2014–2015. Meanwhile, the biomass proportion of warm-temperate species gradually increased. P. trituberculatus became the first biomass-dominant species in SYS accounting for 30.50% of the total biomass of crustaceans. O. punctatus became the first biomass-dominant species in NECS, accounting for 35.25% of the total biomass of crustaceans. Overall, the biomass-dominant species of commercially important crustaceans changed with the latitudinal gradient. As the latitude decreases, the biomass proportion of cold-temperate species (e.g. C. affinis) decreases and the biomass proportion of warm-temperate species (e.g. P. trituberculatus and O. punctatus) increases.

Conclusion

This study shows that the latitudinal gradient is obvious in species richness, dominant species and biodiversity of commercially important crustaceans in the Yellow Sea and NECS. The indices of biodiversity increase with decreasing latitude. On the whole, when the sampling sites shift south by one latitudinal degree, the diversity indices of D, J′ and H′ of crustaceans increase by 0.10, 0.03 and 0.09, respectively. The biomass proportion of the cold-temperate species (e.g. C. affinis) declines with the decreasing latitude, and the warm-temperate species (e.g. O. punctatus and P. trituberculatus) increases. Because of the growth regulation of crustaceans and the fishing moratorium, the biomass of crustaceans in the Yellow Sea and NECS is highest in October and August, respectively. Salinity has a more significant influence on the H′ of crustaceans than other environmental factors (including zooplankton density, sea bed temperature and water depth). Overall, the results of this study contribute to a better understanding of community dynamics of crustaceans in the Yellow Sea and northern East China Sea, and provide evidence to verify the latitudinal gradient theory in biodiversity.

Materials and methods

Sampling

Data used in this study were obtained from seasonal surveys in the Yellow Sea and NECS during 2014–2015. To evaluate the spatio-temporal variations in the community structure of commercially important crustaceans, the waters surveyed were divided into four subareas, including NYS, the central Yellow Sea (CYS), SYS and northern East China Sea (NECS) (Fig. 5). The number of survey sites is listed by season and subarea (Table 6).

Fig. 5
figure 5

Survey sites in the Yellow Sea and the northern East China Sea. Ten sites in the dashed box were not surveyed in January 2015 due to bad weather

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Table 6 Number of survey sites by season and subarea
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The R/V “Beidou” was used to conduct bottom trawl scientific surveys during 2014–2015. The trawl net has a cod-end mesh size of 2.4 cm, a headline height of 6.1–8.3 m, and a distance of 25 m between wings. The trawl speed was 3.0 knots and all catch rates by species were standardized for 1 h for each site to get the relative biomass/individual density. The water depth, sea bed temperature, and salinity were recorded by a conductivity-temperature-depth system (CTD). Zooplankton was collected vertically with plankton nets from a depth near the bottom to the surface.

Data analysis

The biodiversity indices of the crustacean community were calculated for each sampling site using Shannon–Wiener diversity index (H′) (Shannon and Weaver 1963), Pielou’s evenness index (J′) (Pielou 1966) and Margalef’s richness index (D) (Margalef 1958) as indicators. The average of the biodiversity indices for all survey sites was subsequently calculated by season. We evaluated the seasonal changes in the biodiversity indices of crustacean community.

It is noted that the economically important crustaceans usually inhabit the bottom of the sea, and mostly feed on zooplankton (Zhu and Li 1998). We calculated the correlation between the density of crustaceans and environmental factors, including water depth, salinity, sea bed temperature and zooplankton density using the spearman correlation coefficient. The correlation between Shannon–Wiener diversity index (H′) of crustaceans and the environmental factors was calculated also.