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Article

Cold Dome Affects Mesozooplankton Communities during the Southwest Monsoon Period in the Southeast East China Sea

by
Yan-Guo Wang
1,†,
Li-Chun Tseng
2,†,
Xiao-Yin Chen
1,
Rou-Xin Sun
1,
Peng Xiang
1,
Bing-Peng Xing
1,
Chun-Guang Wang
1 and
Jiang-Shiou Hwang
2,3,4,*
1
Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
2
Institute of Marine Biology, National Taiwan Ocean University, Keelung 202301, Taiwan
3
Center of Excellence for Ocean Engineering, National Taiwan Ocean University, Keelung 202301, Taiwan
4
Center of Excellence for the Oceans, National Taiwan Ocean University, Keelung 202301, Taiwan
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
J. Mar. Sci. Eng. 2023, 11(3), 508; https://doi.org/10.3390/jmse11030508
Submission received: 17 January 2023 / Revised: 16 February 2023 / Accepted: 21 February 2023 / Published: 26 February 2023
(This article belongs to the Special Issue Ecology of Marine Zooplankton)
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Abstract

:
In order to better understand the cold dome influence on zooplankton community structure, zooplankton samples were collected during the southwest monsoon prevailing period from the southeast waters of the East China Sea. To reduce the bias caused by different sampling months, the samples were collected in June 2018 and in June 2019. An obvious cold dome activity was proven by images of remote sensing satellites during the June 2018 cruise. In contrast, the research area was much affected by open sea high temperature and water masses during the June 2019 cruise. Significant differences in water conditions were demonstrated by surface seawater temperature, salinity, and dissolved oxygen concentrations between the two cruises. Nevertheless, no significant differences were observed concerning mesozooplankton in general, copepods, large crustaceans, other crustaceans, and pelagic molluscs between the June 2018 and June 2019 cruises. However, the mean abundance of gelatinous plankton was significantly different with 1213.08 ± 850.46 (ind./m3) and 2955.93 ± 1904.42 (ind./m3) in June 2018 and June 2019, respectively. Noteworthy, a significantly lower mean abundance of meroplankton, with 60.78 ± 47.32 (ind./m3), was identified in June 2018 compared to 464.45 ± 292.80 (ind./m3) in June 2019. Pearson’s correlation analysis also showed a highly positive correlation of gelatinous plankton and meroplankton with sea surface temperature (p < 0.01). The variation of salinity showed a significant negative correlation with gelatinous plankton abundance (p < 0.05), and a highly significant negative correlation with the abundance of meroplankton (p < 0.01). Only the abundance of meroplankton showed a positive correlation with dissolved oxygen concentrations (p < 0.05). The copepod communities were separated in two groups which were consistent with sampling cruises in 2018 and 2019. Based on the specificity and occupancy of copepods, Macrosetella gracilis, Oithona rigida, Cosmocalanus darwinii, Paracalanus parvus, and Calocalanus pavo were selected as indicator species for the cold dome effect in the study area during June 2018, whereas the indicator species of warm water impact in the open sea were Calanopia elliptica, Subeucalanus pileatus, Paracalanus aculeatus, and Acrocalanus gibber during the June 2019 cruise.

1. Introduction

Zooplankton, which is considered as a dominant link between primary production and upper trophic levels, plays a pivotal role in shaping marine ecosystems [1,2]. Zooplankton can also be used as bio-indicators of environmental quality and water masses due to their high dependence on environmental conditions and fast responses to environmental variations [3,4,5]. The abundance and distribution of zooplankton can be affected among other factors by temperature, salinity, and primary production [5,6,7,8]. Several studies reported that water masses influenced the zooplankton communities at different spatial and temporal scales in waters of northeast Taiwan [5,9,10,11,12,13,14,15]. The distribution, abundance, and species composition of copepods are associated with different water masses in the upwelling waters off northeastern Taiwan [16]. Conversely, increased zooplankton concentration was observed around the upwelling [17]. Tseng et al. [13,18] reported that distribution patterns of mesozooplankton and copepod communities in northern Taiwan varied spatially with distance to land but did not discuss the possibility of the influence of an upwelling cold dome. However, both diatom and larval fish assemblages were strongly affected by monsoon derived water mass succession and topographic upwelling in the offshore of northeast Taiwan [19,20].
The northern shelf of Taiwan is an extremely dynamic oceanic region. The Kuroshio Current (KC), which is the western boundary current of the North Pacific Subtropical Gyre, flows northeastwards along the eastern coast of Taiwan island with occasionally intrusion on the shelf [21,22,23]. Cold domes, which are formed by the KC intrusion at the edge of the shelf, are observed in the south of the East China Sea [22,23,24,25,26]. Takahashi et al. [27] described a current that flows in the opposite direction to the KC in northeastern Taiwan by high-frequency radar measurements. This current was recently confirmed and named the northeastern Taiwan counter current (NETCC) [28]. In situ observations proved that the main sources and dynamic mechanisms of the NETCC are the counterclockwise flow in the cold dome off northeastern Taiwan and the southward intrusion of the coastal current in northern Taiwan [29,30].
The research area is located in Yilan Bay in northeastern Taiwan, where the water masses are mainly influenced by the interactions of the NETCC, KC, China costal current, and tidal currents [31]. In the present study, a hypothesis was pursued that mesozooplankton communities and the copepod assemblage were influenced by an upwelling cold dome during the southwest monsoon prevailing period in the southeastern East China Sea. The particular aim of the present study was to understand: (1) whether and how the cold dome affected the mesozooplankton communities in the research area; (2) which functional groups of the mesozooplankton were particularly affected from the cold dome phenomenon; and (3) which species could serve as indicator species for the cold dome.

2. Materials and Methods

2.1. Sampling Area and Sampling Strategy

In an attempt to reduce the bias caused by different sampling months, both the zooplankton samples were selected in June in the years 2018 and 2019. The satellite image revealed an upwelling cold dome appearing in the southeast of the East China Sea during the 1 June 2018 cruise (Figure 1A). In order to understand the cold dome effects on the mesozooplankton community in the research area, the samples were recollected from the same stations during the weak phase of the cold dome around the 21 June 2019 (Figure 1B). In total, 9 sampling stations were arranged around Kueishan Island at the edge of the cold dome, Southeast East China Sea (Figure 1C). Samples were collected during the Southwest monsoon prevailing period during the 2018 and 2019 cruises. All samples were collected by horizontal tows from surface waters by a standard north pacific plankton net with a mouth diameter of 45 cm and a mesh size of 200 μm. The tow was kept trawling for 10 min at the 5 m depth layer from near the sea surface with a speed of about 1.0 m/s. The filtered water volume was calculated based on a Hydro-Bios flow-meter, which was mounted in the center of the net mouth. Zooplankton samples gathered at the end of the sampling net were immediately preserved in 5% seawater buffered formaldehyde solution on board for identification and counting in the laboratory. Water temperature, salinity, and dissolved oxygen (DO) were measured prior to the collection of zooplankton samples with a SeaBird CTD sensor (Canada) instrument which was mounted on a rosette sampler.

2.2. Sample Handling and Identification

In the laboratory, mesozooplankton samples were divided by a Folsom splitter until about 300–500 individuals remained in the subsample. Subsamples were counted and identified by a dissecting microscope (SMZ1500, Nikon, Japan). Adult copepods were counted and identified at species level. Immature copepods were counted at genus level. Other mesozooplankton groups were counted at class or phylum level. Several taxonomic literature and illustrations were used to identify the mesozooplankton species [32,33,34,35].

2.3. Data Processing and Statistical Analysis

The mesozooplankton was classified into 6 groups: gelatinous plankton, meroplankton, pelagic Mollusca, Copepoda, large Crustacea, and other Crustacea based on their ecological functioning. Gelatinous plankton included Cnidaria, Urochordata, and Chaetognatha. Mysidacea, Euphausiacea, and Decapoda that were included into the group of large crustaceans. Pteropoda and Heteropoda were considered as taxa of pelagic Mollusca. Taxa of other crustaceans comprised of Amphipoda and Cladocera. The density of individuals belonging to the different groups was calculated by the individuals divided by the filtered water volume and given the unit individuals/m3 (ind./m3). Dry weight was estimated referring to the fitted mixed contribution model which was suggested by Tseng [13].
The difference of environmental and biological parameters between different cruises was compared by an independent sample t-test. The correlation of mesozooplankton and environmental parameters was calculated by Pearson’s correlation analysis. The specificity and occupancy referred to the definition of Dufrene and Legendre [36] and was calculated by the following formula:
Specificity = N i n d i v i d u a l s i , j N i n d i v i d u a l s i ;   Occupancy = N s i t e s i , j N s i t e s j
Specificity equaled the ratio of the average abundance of the i th species in j th community ( N i n d i v i d u a l s i , j ) and the sum of the average abundance of the i th species in different communities ( N i n d i v i d u a l s i ). The occupancy was defined as the relative frequency of occurrence of the i th in j th community. The specificity–occupancy plot was achieved in R language, applying ggplot 2 package.
Group average linkage was used in the cluster analysis with Bray–Curtis similarity. Before cluster analysis, the abundance of copepods species was log (x+1) transformed. Assemblage analysis was performed with Primer 6.

3. Results

3.1. Environmental Characters in the Research Area

The variations in surface sea temperature (Figure 2A), salinity (Figure 2B), and dissolved oxygen (Figure 2C) of each sampling station during two cruises showed a marked difference. The occurrence of the cold dome influenced the hydrological environment of the surrounding waters as revealed by the above three parameters. Furthermore, the results of an independent sample t-test showed that the average surface water temperature was significantly different (t = 6.90, p < 0.001) during the summer cruises of 2018 and 2019 with an average surface water temperature of 26.16 ± 0.29 °C and 27.20 ± 0.34 °C, respectively (Figure 2A-1). A relatively higher average salinity 34.46 ± 0.02 was recorded during the 2018 cruise. The average salinity was 33.84 ± 0.01 during the 2019 cruise which was significantly lower than during the 2018 cruise (t = 77.67, p < 0.001) (Figure 2B-1). Similar to the seawater temperature, the surface water DO was also significantly different (t = 35.94, p < 0.001) in 2018 and 2019 with an average of 5.58 ± 0.07 (mg/L) and 6.71 ± 0.06 mg/L), respectively (Figure 2C-1).

3.2. Composition of Mesozooplankton

The mean abundance of mesozooplankton of two sampling cruises (n = 18) was 9786.15 ± 5052.66 (ind./m3) during the Southwest monsoon prevailing period in the research area. The statistical results showed that there was no significant difference (p > 0.05, t-test) of the mesozooplankton mean abundance between 2018 and 2019 with mean values of 9792.60 ± 5634.76 (ind./m3) and 9779.70 ± 4743.34 (ind./m3), respectively. Copepods were the most dominant taxon in the research area. The mean abundance of copepods was 8278.71 ± 5392.97 (ind./m3) in 2018 with a percentage 84.25% of the total mesozooplankton (Figure 3A). During 2019, the copepods accounted for 65.20% of the total mesozooplankton mean abundance with 6168.46 ± 3075.17 (ind./m3) (Figure 3B). The copepod mean abundance between 2018 and 2019 was not significantly different (p > 0.05, t-test). Both the large Crustacea, other Crustacea, and pelagic Mollusca were not significantly different between these two cruises. However, the mean abundance of gelatinous plankton, which was the second most abundant in the research area, was significantly lower in 2018 (1213.08 ± 850.46 ind./m3) than in 2019 (2955.93 ± 1904.42 ind./m3) (p < 0.05). The mean abundance of Cnidaria was 75.95 ± 42.64 (ind./m3) during the 2018 cruise, which was obviously lower than during the 2019 cruise with a mean abundance 133.24 ± 110.78 (ind./m3). Mean abundance of urochordata was significantly lower during the 2018 cruise than during the 2019 cruise with values of 931.76 ± 788.86 (ind./m3) and 2652.60 ± 1682.22 (ind./m3), respectively. There was no obvious difference in the mean abundance of Chaetognatha in the 2018 and 2019 cruise. Due to the obviously higher mean abundance of Bivalvia larva, Brachyura zoea, and Macrura larva during 2019 cruise, the mean abundance of meroplankton was significantly higher in 2019 than in the 2018 cruise with the mean value 464.45 ± 292.80 (ind./m3) and 60.78 ± 47.32 (ind./m3), respectively (p < 0.05) (Supplementary Materials Table S1).
In the present study, we could not find a significant correlation between the total mesozooplankton abundance and environment parameters during the research period (Table 1). The variations of Copepoda, large Crustacea, and pelagic Mollusca also showed no correlation with environmental parameters in the research area. In contrast, the variation of gelatinous plankton correlated significantly positively with surface temperature (p < 0.01) and negatively with salinity (p = 0.02). In contrast, the meroplankton showed a significant negative correlation with salinity (p < 0.01), but a positive correlation with surface temperature (p < 0.01) and with surface DO (p = 0.02) in the research area. The variation of other Crustacea showed only a positive correlation with surface temperature (p = 0.04) in the research area.
The dry weight of mesozooplankton ranged from 244.70 mg/m3 to 1063.21 mg/m3 with mean 555.56 ± 255.69 (mg/m3) in research area during the 2018 cruise. The dry weight was significantly higher during the 2019 cruise with a mean value of 987.78 ± 521.58 (mg/m3). The dry weight ranged from 458.67 mg/m3 to 2016.21 mg/m3 during the 2019 cruise.

3.3. Copepod Assemblages

Totally, 76 copepod species were identified belonging to the Calanoida, Cyclopoida, Harpacticoida, and Poecilostomatoida during the cruises of the present study. In total, 58 and 53 copepod species were found in 2018 and 2019, respectively (Supplementary Materials Table S1). The percentage of Calanoida copepods was dominant and occupying 56.90% and 64.15% of all copepod species in 2018 and 2019, respectively. These were followed by Poecilostomatoida copepods with a percentage of 34.48% in 2018 and 24.53% in 2019.
The results of the cluster analysis indicated that all samples were divided into three groups at a 37.61% similarity level (Figure 4). Samples collected from S1 station in 2019 had a relative lower similarity to other stations, being arranged into a group with the presence of only 19 copepod species. The dominant species was Temora turbinata with a relative abundance of 59.04% in this sample. This was followed by Canthocalanus pauper and Paracalanus aculeatus with a relative abundance of 14.76% and 7.38%, respectively. The remaining eight samples collected in 2019 were gathered into group b with a similarity of 52.68%. Totally, 50 copepods species were identified, and the dominant species was T. turbinanta with a relative abundance of 39.86% in this group. The relative abundance of P. aculeatus was 12.29%, representing the second most dominant species in this group. The relative abundance was 6.33% and 5.74% for Acrocalanus gibber and C. pauper, respectively, in group b. In group c, which included all nine samples collected from the 2018 cruise, 58 copepods species were recorded. There were seven species with relative abundances higher than 5% in this group. The mean abundance of T. turbinata accounted for 30.88% of the total mean abundance in this group. The following relative abundance was 11.01% for Oncaea venusta in group c. The relative abundance of Macrosetella gracilis, Acrocalanus gracilis, Paracalanus parvus, Farranula gibbula, and Oithona rigida was 8.37%, 7.86%, 7.78%, 6.73%, and 6.30%, respectively. The results of the cluster analysis clearly indicated a significant difference in the composition of the copepod assemblage between the cruises in June of these two years.

3.4. Specificity and Occupancy of Copepods

The specificity and occupancy of copepods being counted at species level, were calculated and projected to a plot of these two cruises (Figure 5). The results showed that most copepods species were characterized by a relative lower specificity and occupancy during these two cruises. Indicator species are shown in dotted boxes of Figure 5 with specificity and occupancy both higher than 0.8. Indicator species were specific to certain conditions and widely distributed in that environment. There were five species selected as indicator species in 2018. In contrast, four species were selected as indicator species with both specificity and occupancy greater than 0.8 in 2019 (Table 2).
The specificity of Macrosetella gracilis was 96.37% with a mean abundance of 384.04 ± 284.22 (ind./m3) in 2018 (Figure 5). This was followed by Oithona rigida and Cosmocalanus darwinii with the specificity 95.26% and 93.89%, and mean abundances of 289.12 ± 624.92 (ind./m3) and 45.28 ± 54.78 (ind./m3). In 2019, the mean abundance of M. gracilis, O. rigida, and C. darwinii was only 14.45 ± 43.35 (ind./m3), 14.38 ± 30.39 (ind./m3), and 2.95 ± 8.85 (ind./m3), respectively (Table 2). The results of Pearson’s correlation analysis showed that there was no significant correlation between the variation of O. rigida and environmental parameters in the research area. The variation of M. gracilis, however, was significantly positive correlated with salinity, surface temperature (p = 0.01) and DO (p = 0.05), respectively. The results of the analysis implied that M. gracilis should come from high temperature and high salinity Kuroshio water, and its abundance variation could be influenced by the interplay of Kuroshio and East China Sea waters in research area. A positive correlation of the variation of C. darwinii and salinity was detected in the study area. The specificity of Paracalanus parvus and Calocalanus pavo was 91.72% and 86.10% with a mean abundance of 356.88 ± 297.73 (ind./m3) and 108.24 ± 78.30 (ind./m3) in 2018. During the 2019 cruise, the mean abundance of Paracalanus parvus and Calocalanus pavo was only 32.22 ± 50.52 (ind./m3) and 17.47 ± 34.73 (ind./m3). Pearson’s correlation analysis results showed that both P. parvus and C. pavo were significantly positively (p < 0.01) correlated with surface salinity in the study area.
During the 2019 cruise, the specificity of both Calanopia elliptica and Subeucalanus pileatus were 100% with a mean abundance of 21.10 ± 28.36 (ind./m3) and 36.12 ± 64.73 (ind./m3), respectively (Figure 5). Paracalanus aculeatus and Acrocalanus gibber were indicator species with specificities of 91.13% and 89.01% and mean abundance of 495.24 ± 401.77 (ind./m3) and 254.70 ± 231.24 (ind./m3), respectively. The variation of S. pileatus showed no significant correlation with environmental parameters. Whereas the variation of C. elliptica showed a significant negative correlation with salinity. A. gibber also showed a significantly negative correlation with salinity and a positive correlation with sea surface temperature (p = 0.01) and DO (p = 0.05). The variation of P. aculeatus correlated significantly negatively with salinity and positively with sea surface temperature (p = 0.01) and DO (p = 0.05).

4. Discussion

Intermittent but common upwelling in the southern East China Sea was associated with local cyclonic circulation and inshore intrusion of Kuroshio waters interacting with ocean topography [22,37,38]. Remote sensing satellite images and in situ measured hydrographic parameters indicated that the study area was obviously affected by cold dome upwelling water in June 2018. Conversely, the study area was mainly dominated by oceanic oligotrophic and warm waters in June 2019. Relatively lower surface water temperature and higher salinity in the present study were observed during the June 2018 cruise. This is mainly explained by the upwelling bringing cold and saline Kuroshio waters to the surface and developing a cold dome region in the area. The cold dome waters were transported to the study area by NETCC during June 2018 [31]. Withal, several studies reported that the cold dome provided a major fishing ground due to the higher concentration of nutrients [16,39,40]. Previous studies noted that physical factors (monsoon, stratification, and upwelling) could reduce the availability of dissolved oxygen [41]. An obviously lower DO concentration was observed in the surface water at the edge of the cold dome during the June 2018 cruise of the present study. DO concentrations were thought to diminish in the upwelling area due to a strong remineralization of sinking organic matter [42]. From a biological perspective, changes in the relative dominance of functional groups in the community could also affect the DO concentrations in the upwelling area [43,44,45,46,47].
Several studies reported that the abundance and distribution of zooplankton were influenced severely by environmental factors such as temperature, salinity, and primary production [5,6,7,8,15]. The composition of mesozooplankton was also influenced by environmental parameters in the research area [4,5,11,12,13,14]. In the present study, despite no obvious difference of mesozooplankton mean abundance between the cruises in June 2018 and June 2019, the community structure was significantly influenced by the cold dome during June 2018. The relative abundance of copepods was higher in 2018 than in 2019 but without significant differences by statistical comparison between these two study cruises. Madhupratap et al. [48] reported that a higher abundance of copepods was found due to a relatively higher primary production in the upwelling area. In this research, surface water was obviously affected by the cold dome with relative lower temperature and higher salinity during 2018 cruise. Gelatinous plankton and meroplankton showed a significantly correlation with surface water temperature and salinity. The abundance and relative abundance of gelatinous plankton and meroplankton were significantly higher during the June 2019 than during the June 2018 cruise. Thus, we inferred that gelatinous plankton and meroplankton probably had a negative correlation with the cold dome. This phenomenon is explained by the energy contribution from high phytoplankton production followed by a peak production of secondary producers with abundant copepods, as well as many fish species in the upwelling area [49]. In convergent ecosystems, however, food chains are characterized by small flagellate phytoplankton, an abundance of small copepods, and large numbers of gelatinous plankton [50].
Temora turbinata, C. pauper, and O. venusta were the most common species both during the June 2018 and June 2019 cruise. Due to the effect of cold upwelling waters, the mean abundance of T. turbinata and C. pauper was slightly lower in June 2018. Several studies proved that T. turbinata was commonly found around coastal waters of Taiwan [9,14,51,52,53,54,55,56]. Previous reports pointed out that T. turbinata preferred to occur in waters with seawater temperatures higher than 28 °C, being considered a warm-water indicator species in the northwest of Taiwan [54,57,58]. Consistent with previous research, T. turbinata was the most abundant species and also showed an increased tendency to be accompanied with a relative higher water temperature in the present study. This was followed by Oncaea venusta, which was one of the easiest oncaeid species to be recognized in mesozooplankton samples, with a mean abundance of 505.35 ind./m3 in June 2018. Tseng et al. [13] found O. venusta as a dominant species in the boundary waters of the East China Sea and Kuroshio Current during the southwest-northeast monsoon transition period. This species commonly provides a substantial fraction of copepod assemblages in coastal and oceanic regions in middle to low latitude epi- and mesopelagic waters worldwide [59,60,61,62,63]. Júnior et al. [64] reported that the abundance and biomass of O. venusta positively correlated with seawater temperature in the south Atlantic, ranging from 21 to 27 °C. However, the abundance of O. venusta was correlated with relatively lower surface water temperatures of 22–24 °C rather than 26 °C in the northeast of Taiwan [4]. In the present study, the mean abundance of O. venusta was significantly higher in June 2018 than during the June 2019 cruise with a relative abundance of 11.01% and 4.07%, respectively, which also showed an inclination to a relatively lower seawater temperature.
The harpacticoid copepod Macrosetella gracilis, which was surmised as a most suitable indicator species for upwelling influence in the study area during the June 2018 cruise, is a species that occurs globally in tropical and subtropical oceans and is typically found in association with blooms of Trichodesmium spp. [65,66]. In coincidence with the present study results, M. gracilis is an indicator species for monsoon derived cold water masses during the northeast monsoon prevailing period in the study area [5]. Species in Oithona are described as the most ubiquitous and abundant oceanic copepod species worldwide [67]. The cyclopoid copepod Oithona rigida, which makes use of a variety of food items, was less sensitive and more tolerant to extreme environmental conditions, such as high temperature, low nutrients, and low pH [68], and had a higher productivity than Calanoida copepods [69]. In this study, O. rigida was also surmised as an indicator species with an occupancy of 88.89% during the June 2018 cruise, showing cold dome upwelling. Our results were supported by the findings of Keister and Tuttle [70], who suggested that species in the genus Oithona might migrate to the surface layer due to subsurface hypoxia during upwelling events. The Calanoida copepod Paracalanus parvus, playing an important role in ocean fisheries with relatively higher abundance in the western subtropical Pacific, is widely distributed in temperate and tropical regions [71,72,73,74]. In addition, P. parvus was reported as a coldwater mass indicator species in northeast Taiwan during the northeast monsoon season [5]. The temperate species Calocalanus pavo was suggested as an indicator species of the upwelling cold dome influence in June 2018. It was reported as being related to cold-water masses in the northeast of Taiwan with a relative abundance of 0.56% during the monsoonal transition period in 1998 [18]. The omnivorous Calanoida copepod Calanopia elliptica, belonging to the Pontellidae family, was recorded in June 2019 with 100% occurrence in the present study. It has been reported as a Lessepsian migration species, indicating the connection between the Red Sea and the southeastern Mediterranean Sea via the Suez Canal [75]. Subeucalanus pileatus, a warm coastal and shelf water species, was only recorded during the June 2019 cruise with an occurrence rate of 88.89%. Previous studies emphasized that P. aculeatus was widely distributed around Taiwan [5,9,76,77,78]. In the present study, the abundant P. aculeatus was recorded in June 2019, and its abundance was significantly negative correlated with salinity but positively with the change of sea surface temperature. Previous reports found that A. gibber was abundant during summer and decreasing during winter and was considered as an indicator species of the Kuroshio Branch Current in the waters of northeast Taiwan [58,78,79]. Abundant A. gibber was recorded during June 2019 with the warmest oceanic water affection in the present study. The variations of indicator species in the research area proved that mesozooplankton communities were significantly changing during the southwest monsoon prevailing period from the June 2018 to the June 2019 cruise.

5. Conclusions

Based on two years of zooplankton sampling in the same months, significant differences in the community structure of mesozooplankton and copepod assemblages were revealed in the East China Sea northeast of Taiwan. The hypothesis that the presence of a cold dome was affecting the composition and overall density of mesozooplankton communities could be strengthened. The information obtained from the present study on functional groups and indicator species of copepods could contribute to future studies on the effects of cold domes on secondary producers. Studies on the dynamic composition and functional groups of mesozooplankton and dominant copepod species are needed to better understand the impact of cold domes in the future.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jmse11030508/s1, Table S1: Species list with mean abundance and standard error.

Author Contributions

Conceptualization and methodology, Y.-G.W. and J.-S.H.; software, Y.-G.W., C.-G.W., P.X., and L.-C.T.; validation, R.-X.S. and X.-Y.C.; formal analysis, Y.-G.W. and L.-C.T.; investigation, Y.-G.W.; resources, Y.-G.W. and J.-S.H.; data curation, Y.-G.W.; writing—original draft preparation, Y.-G.W.; writing—review and editing, L.-C.T.; visualization, L.-C.T. and B.-P.X.; supervision, B.-P.X.; project administration, J.-S.H.; funding acquisition, J.-S.H. All authors have read and agreed to the published version of the manuscript.

Funding

Financial support from the National Science and Technology Council (NSTC) of Taiwan through grant no. MOST 106-2621-M-019-001, MOST 107-2621-M-019-001, MOST 108-2621-M-019-003, MOST 109-2621-M-019-002, MOST 110-2621-M-019-001 and MOST 111-2621-M-019-001, and Center of Excellence for Ocean Engineering (Grant No. 109J 13801-51 110J13801-51, 111J13801-51) to J.-S.H. This work was financially supported by the Scientific Research Foundation of the Third Institute of Oceanography, MNR, No. 2017010 and No. 2017009, and the Bilateral Cooperation of Maritime Affairs and the Marine Biological Sample Museum (GASI-02-YPK-SW) to C.-G.W. and grant no. MOST 109-2811-M-019-504, MOST 110-2811-M-019-504, and MOST 111-2811-M-019-003 to L.-C.T. The funders had no role on study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors are grateful to members of Jiang-Shiou Hwang’s laboratory for their assistance during the field works during cruises to the waters off northeastern Taiwan. The authors acknowledge the support from the Ocean Data Bank of the Ministry of Science and Technology, Republic of China for providing temperature and salinity data.

Conflicts of Interest

The authors declare no conflict of interest.

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Jmse 11 00508 g001 550
Figure 1. Satellite images of the sea surface temperature on 1 June 2018 (A) and 21 June 2019 (B), and the maps of the research area and sampling stations (C).
Figure 1. Satellite images of the sea surface temperature on 1 June 2018 (A) and 21 June 2019 (B), and the maps of the research area and sampling stations (C).
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Figure 2. Variation of seawater temperature (A); salinity (B); and dissolved oxygen (C); as well as comparisons of the seawater temperature (A-1); salinity (B-1); and dissolved oxygen (C-1) in average values (mean ± standard deviation) from the cruises in June 2018 and June 2019.
Figure 2. Variation of seawater temperature (A); salinity (B); and dissolved oxygen (C); as well as comparisons of the seawater temperature (A-1); salinity (B-1); and dissolved oxygen (C-1) in average values (mean ± standard deviation) from the cruises in June 2018 and June 2019.
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Figure 3. The proportion of functional taxa among mesozooplankton communities collected during the cruises in June 2018 (A), and June 2019 (B).
Figure 3. The proportion of functional taxa among mesozooplankton communities collected during the cruises in June 2018 (A), and June 2019 (B).
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Figure 4. The results of the cluster analysis of the copepod community in each sample, measured by Bray-Curtis similarity distances.
Figure 4. The results of the cluster analysis of the copepod community in each sample, measured by Bray-Curtis similarity distances.
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Figure 5. Specificity-occupancy plots of copepods collected from cruises in June 2018 and June 2019.
Figure 5. Specificity-occupancy plots of copepods collected from cruises in June 2018 and June 2019.
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Table
Table 1. Pearson’s correlation of functional groups mean abundance and environmental parameters. The numbers in parentheses are p-values.
Table 1. Pearson’s correlation of functional groups mean abundance and environmental parameters. The numbers in parentheses are p-values.
Functional GroupsTemperatureSalinityDO
Copepoda0.02 (0.94)0.23 (0.36)−0.14 (0.58)
Gelatinous plankton0.63 ** (<0.01)−0.54 * (0.02)0.43 (0.08)
Large Crustacea−0.08 (0.77)0.32 (0.20)−0.09 (0.73)
Meroplankton0.75 ** (<0.01)−0.72 ** (<0.01)0.53 * (0.02)
Other Crustacea0.49 * (0.04)−0.29 (0.25)0.21 (0.41)
Pelagic Mollusca−0.06 (0.83)0.10 (0.69)0.00 (1.00)
Total abundance0.27 (0.27)−0.02 (0.95)0.05 (0.83)
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
Table
Table 2. Mean abundance, occupancy, and comparative results of mean abundances using t-test for indicator species recorded during the sampling cruises in 2018 and 2019. The numbers in parentheses represent the occupancy (%). * Indicates the indicator species during that cruise. N.A. means not available.
Table 2. Mean abundance, occupancy, and comparative results of mean abundances using t-test for indicator species recorded during the sampling cruises in 2018 and 2019. The numbers in parentheses represent the occupancy (%). * Indicates the indicator species during that cruise. N.A. means not available.
Species Name20182019t-Test
Macrosetella gracilis384.04 ± 284.23 * (100)14.45 ± 3.35 (44.44)p < 0.01
Oithona rigida289.12 ± 624.92 * (88.89)14.38 ± 30.39 (22.22)p < 0.05
Cosmocalanus darwinii45.28 ± 54.78 * (100)2.95 ± 8.85 (44.44)p < 0.01
Paracalanus parvus356.88 ± 297.73 * (88.89)32.22 ± 5.52 (33.33)p < 0.01
Calocalanus pavo108.24 ± 78.30 * (100)17.47 ± 34.73 (44.44)p = 0.085
Calanopia ellipticaN.A.21.10 ± 28.36 * (100)p < 0.01
Subeucalanus pileatusN.A.36.12 ± 64.73 * (88.89)p < 0.01
Paracalanus aculeatus48.21 ± 48.62 (66.67)495.24 ± 401.77 * (100)p < 0.01
Acrocalanus gibber31.46 ± 55.93 (44.44)254.70 ± 231.24 * (88.89)p < 0.01
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Wang, Y.-G.; Tseng, L.-C.; Chen, X.-Y.; Sun, R.-X.; Xiang, P.; Xing, B.-P.; Wang, C.-G.; Hwang, J.-S. Cold Dome Affects Mesozooplankton Communities during the Southwest Monsoon Period in the Southeast East China Sea. J. Mar. Sci. Eng. 2023, 11, 508. https://doi.org/10.3390/jmse11030508

AMA Style

Wang Y-G, Tseng L-C, Chen X-Y, Sun R-X, Xiang P, Xing B-P, Wang C-G, Hwang J-S. Cold Dome Affects Mesozooplankton Communities during the Southwest Monsoon Period in the Southeast East China Sea. Journal of Marine Science and Engineering. 2023; 11(3):508. https://doi.org/10.3390/jmse11030508

Chicago/Turabian Style

Wang, Yan-Guo, Li-Chun Tseng, Xiao-Yin Chen, Rou-Xin Sun, Peng Xiang, Bing-Peng Xing, Chun-Guang Wang, and Jiang-Shiou Hwang. 2023. "Cold Dome Affects Mesozooplankton Communities during the Southwest Monsoon Period in the Southeast East China Sea" Journal of Marine Science and Engineering 11, no. 3: 508. https://doi.org/10.3390/jmse11030508

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