Kuroshio intrusion drives the Trichodesmium assemblage and shapes the phytoplankton community during spring in the East China Sea

Yue, Jiaqi; Noman, Md. Abu; Sun, Jun

doi:10.1007/s00343-020-9344-x

Cited by 5 publications

(4 citation statements)

References 52 publications

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“…dumerili spawn along the continental shelf's edge in the northern waters of Taiwan in the southern ECS mainly from February to April, according to an investigation of the early larvae distribution [13] and the seasonal gonadal development of adults [44]. Our findings noted that in the spring, the spatiotemporal distribution pattern of S. dumerili is higher in the southern part of the ECS, which has favorable oceanographic characteristics because of the Kuroshio Branch Current and Kuroshio Current [45]. Tone et al [46] reported that the S. dumerili spawning ground in February and March was located in the ECS.…”

Section: Predicted Spatial Distribution Pattern Of the Greater Amberjackmentioning

confidence: 75%

Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data

et al. 2022

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The environmental characteristics of the Taiwan Strait (TS) have been linked to variations in the abundance and distribution of greater amberjack (Seriola dumerili) populations. Greater amberjack is a commercially and ecologically valuable species in ecosystems, and its spatial distribution patterns are pivotal to fisheries management and conservation. However, the relationship between the catch rates of S. dumerili and the environmental changes and their impact on fish communities remains undetermined in the TS. The goal of this study was to determine the spatiotemporal distribution pattern of S. dumerili with environmental characteristics in the TS from south to north (20°N–29°N and 115°E–127°E), applying generalized additive models (GAMs) and spatiotemporal fisheries data from logbooks and voyage data recorders from Taiwanese fishing vessels (2014–2017) as well as satellite-derived remote sensing environmental data. We used the generalized linear model (GLM) and GAM to analyze the effect of environmental factors and catch rates. The predictive performance of the two statistical models was quantitatively assessed by using the root mean square difference. Results reveal that the GAM outperforms the GLM model in terms of the functional relationship of the GAM for generating a reliable predictive tool. The model selection process was based on the significance of model terms, increase in deviance explained, decrease in residual factor, and reduction in Akaike’s information criterion. We then developed a species distribution model based on the best GAMs. The deviance explained indicated that sea surface temperature, linked to high catch rates, was the key factor influencing S. dumerili distributions, whereas mixed layer depth was the least relevant factor. The model predicted a relatively high S. dumerili catch rate in the northwestern region of the TS in summer, with the area extending to the East China Sea. The target species is strongly influenced by biophysical environmental conditions, and potential fishing areas are located throughout the waters of the TS. The findings of this study showed how S. dumerili populations respond to environmental variables and predict species distributions. Data on the habitat preferences and distribution patterns of S. dumerili are essential for understanding the environmental conditions of the TS, which can inform future priorities for conservation planning and management.

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Section: Predicted Spatial Distribution Pattern Of the Greater Amberjackmentioning

confidence: 75%

Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data

et al. 2022

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“…In this region, the SCM is often unclear, and the chlorophyll fluorescence is relatively constant over its cline. In areas affected by riverine input, such as the ECS, the chlorophyll maximum is sometimes formed near the surface by dinoflagellates or buoyant cyanobacteria (Yue et al 2021), which are not in the detection range of a flow cytometer ( see “Materials and Methods” section). This likely accounts for the deeper subsurface peaks of the three phytoplankton groups compared with the SCM in this area (Fig.…”

Section: Discussionmentioning

confidence: 99%

Relative depths of the subsurface peaks of phytoplankton abundance conserved over ocean provinces

Sato

Shiozaki

Hashihama

et al. 2022

Limnology & Oceanography

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Flow cytometric data collected from more than 250 stations in the Pacific and Indian Oceans were analyzed to determine the factors affecting the depth and magnitude of the subsurface abundance maximum of Synechococcus, Prochlorococcus, and small eukaryotes (< 6 μm). The peak depth of each phytoplankton population estimated by curve fitting was strongly correlated with the depth of the subsurface chlorophyll maximum (SCM). The slope of the regression line demonstrated that the peak depths of Synechococcus, Prochlorococcus, and small eukaryotes were 74% AE 1%, 88% AE 1%, and 104% AE 1% of the SCM depth (with confidence interval of 95%), respectively. This trend was largely conserved across the different ocean provinces of the Pacific and Indian Oceans. The peaks of Synechococcus frequently appeared in the nitrate-depleted layer of subtropical waters, suggesting their high affinity for regenerated and/or organic nutrients. The estimated daily irradiance received at the peak depths of Synechococcus and Prochlorococcus did not show a distinct latitudinal trend and fluctuated among neighboring stations, whereas that of small eukaryotes slightly increased toward the subarctic region. The present results show that the peak depths of Synechococcus, Prochlorococcus, and small eukaryotes relative to SCM were globally conserved on average, which is largely in line with the difference in their ability to acquire light and nutrients. However, the absolute light level and nutrient concentrations at the peak depths varied dramatically among neighboring stations, likely affected by physical movements.

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“…The East China Sea (ECS) is the largest marginal sea of the northwest Pacific Ocean, bordered by the coast of China to the west and the Korean Peninsula and Japan to the east ( Wong et al, 2000 ; Yue et al, 2021 ). The coastal area of the ECS is subject to intricate hydrodynamic processes, including the Changjiang (Yangtze) River discharge and Kuroshio water intrusion ( Zhou et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Microbial community diversity from nearshore to offshore in the East China Sea

Jin,

Liu,

Zhao

et al. 2024

Front. Microbiol.

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The Pollution Nagasaki (PN) section of the East China Sea (ECS) is a typical area for studying the complex hydrographic dynamics between Changjiang River discharge and Kuroshio, displaying intense variations of environmental gradients from nearshore to offshore. However, the temporal and spatial changes of microbial communities along the PN section have long been overlooked. In this study, we performed a comprehensive investigation into the abundance, diversity and ecology of free-living (FL) and particle-associated (PA) microbial communities in seawater samples along the PN section during both summer and winter. Distinct hydrological conditions and resulting environmental gradients were observed between summer and winter, with clear features of intrusive Kuroshio subsurface water in summer and strong vertical mixing of seawater in winter. Bacterial abundance along the PN section was higher in summer (1.11 × 108 copies·L−1 – 7.37 × 108 copies·L−1) than in winter (1.83 × 106 copies·L−1 – 1.34 × 108 copies·L−1). Microbial diversity, as indicated by α-diversity indices, remained at relatively stable levels in summer, while a clear decreasing trend was observed in winter along the PN section. Additionally, the winter communities exhibited a more evident spatial shift along the PN section compared to the summer communities. 16S rRNA gene amplicon sequencing showed that microbial community composition varied considerably between different seasons (summer and winter) and lifestyles (FL and PA), with a notable dominance of Ralstonia species. in winter. Regarding the assembly of microbial communities, the stochastic process represented by dispersal limitation was the dominant process in summer, while the deterministic homogeneous selection was the most important process in winter. Correspondingly, distinct topological properties of the microbial co-occurrence networks were shown between different seasons and along the PN section. These results enhance our understanding of how hydrological conditions influence dynamic changes of microbial communities along the PN section, providing new insights for the microbial community assembly and interactions in such a complex environment.

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Kuroshio intrusion drives the Trichodesmium assemblage and shapes the phytoplankton community during spring in the East China Sea

Cited by 5 publications

References 52 publications

Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data

Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data

Relative depths of the subsurface peaks of phytoplankton abundance conserved over ocean provinces

Microbial community diversity from nearshore to offshore in the East China Sea

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