Marine Ecological Systems Research Articles

Long term of sea surface temperature prediction for Indonesia seas using multi time-series satellite data for upwelling dynamics projection

Global warming, which impacts global temperatures, has led to an increase in sea surface temperature (SST). This rise significantly affects marine ecological systems, especially in Indonesia. As a result, long-term forecasting of SST dynamics is essential for shaping various policies. However, most studies on SST forecasting have focused on short-term predictions in local or medium-sized areas and often overlook the dynamic upwelling that influences SST. In this paper, we propose a five-year SST prediction for the Indonesian seas, incorporating multi-time-series satellite data to project upwelling dynamics. We utilized two deep learning time series models to construct a predictive model that estimates monthly SST values. This model employs extensive multiple satellite data, encompassing 14,934 points (including SST with a resolution of 0.090, wind, ENSO, heat flux, and solar radiation) from 2003 to 2021. To enrich the training data and mitigate overfitting, we applied data augmentation for time series. Experimental results reveal that all satellite datasets correlate with SST over five years. The 1D-Convolution Neural Network outperformed the Long-Short Term Memory model, exhibiting the lowest mean absolute error of 0.39 °C compared to 0.45 °C. Our model detected a consistent upwelling dynamic over a five-year pattern in the Indonesian seas. These findings suggest that our proposed model offers accurate and efficient long-term monthly SST predictions, crucial for upwelling projections.

Prediction of Sea Surface Chlorophyll-a Concentrations Based on Deep Learning and Time-Series Remote Sensing Data

Accurate prediction of future chlorophyll-a (Chl-a) concentrations is of great importance for effective management and early warning of marine ecological systems. However, previous studies primarily focused on chlorophyll-a inversion and reconstruction, while methods for predicting Chl-a concentrations remain limited. To address this issue, we adopted four deep learning approaches, including Convolutional LSTM Network (ConvLSTM), Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Eidetic 3D LSTM (E3D-LSTM), and Self-Attention ConvLSTM (SA-ConvLSTM) models, to predict Chl-a over the Yellow Sea and Bohai Sea (YBS) in China. Furthermore, 14 environmental variables obtained from the remote sensing data of Moderate-resolution Imaging Spectroradiometer (MODIS) and ECMWF Reanalysis v5 (ERA5) were utilized to predict the Chl-a concentrations in the study area. The results showed that all four models performed satisfactorily in predicting Chl-a concentrations in the YBS, with SA-ConvLSTM exhibiting a closer approximation to true values. Furthermore, we analyzed the impact of the Self-Attention Memory Module (SAM) on the prediction results. Compared to the ConvLSTM model, the SA-ConvLSTM model integrated with the SAM module better captured subtle large-scale variations within the study area. The SA-ConvLSTM model exhibited the highest prediction accuracy, and the one-month Pearson correlation coefficient reached 0.887. Our study provides an available approach for anticipating Chl-a concentrations over a large area of sea.

Analysis of the spatio-temporal changes and driving factors of the marine economic–ecological–social coupling coordination: A case study of 11 coastal regions in China

For the sustainable development of the ocean, examining the coupled and coordinated relationships of the marine economic-ecological-social system (MEESS) is crucial. In this study, data from 11 coastal regions of China from 2006 to 2020 are utilized to quantify and analyze the MEESS coupling coordination relationships and driving factors using the entropy method, mean squared deviation weighting method, coefficient of variation method, improved coupling coordination degree (CCD), GM (1,1) (grey model), and generalized method of moments (GMM) models. The findings show that (1) the comprehensive level of the MEESS in the study area indicates a steady upward trend. The marine economic system maintains a steady rise, the marine ecological system starts at a high level and grows at a low rate, and the marine social system starts at a low level and grows at a high rate. (2) The coupling degree is higher in areas with a higher comprehensive level of marine ecological systems. (3) As of 2020, six study regions were in the moderate coordination stage. Except for Shanghai, the coupling coordination degree (CCD) in other regions shows a fluctuating upward trend. (4) From 2021 to 2026, the coastal area overall will enter the intermediate coordination stage. Shandong will take the lead in the good coordination stage. (5) In terms of drivers, port activity, financial industry development, and government support significantly affect the CCD. The findings of this study demonstrate the applicability and effectiveness of the improved CCD model in evaluating the interactions of multiple ocean subsystems. This demonstration can help policymakers tailor marine development planning and provide a new perspective on sustainable marine development.

The spring–neap variability and mechanisms of long-term variations in the upwelling at the tip of Liaodong Peninsula, China

Upwelling is one of the important phenomena in oceans which plays a significant role in marine hydrology and marine ecological systems. During the summer stratified season, there are usually cold patches around the tip of Peninsula. Using the satellite sea surface temperature (SST) data from 1999 to 2018, this study showed that there was a pod-like cold water patch with two cold centers around the tip of Liaodong Peninsula, China. The range and the intensity of upwelling indicated an increasing trend during 1999–2018. We used a two-dimensional hydrodynamic model Mike21 to study the impact of the tidal current to the intra-month variations of upwelling (DHI 2009). The variability of tidal currents brought the significant spring–neap variations of the upwelling, showing that the SST of upwelling during the spring tide was lower about 1°C and the range of the cold water extended farther than that during the neap tide. The variations of upwelling area lagged behind the tide range about 4 days. The mechanisms of long-term variations of the upwelling were analyzed using the remote sensing wind data and the reanalysis ocean current data. Summer surface wind in the Bohai Sea suppressed the upwelling through the inshore Ekman transports and the effect of the wind curls could be ignored. The dispersion of geostrophic current around the Laotieshan Channel due to the bottom friction could drive the upward vertical velocities. Both of wind and current contributed to the multi-year variations of the upwelling around the tip of Liaodong Peninsula, China.

Suggestions for marine protected area management in Australia: a review of temperature trends and management plans

Climate change and related ocean warming have affected marine ecological and socioeconomic systems worldwide. Therefore, it is critically important to assess the performance of conservation mechanisms, particularly marine protected areas (MPAs) to moderate the risks of climate-related impacts. In this study, sea surface temperature trends of Australian Commonwealth MPAs are assessed against climate change management criteria, as defined in Adapting to Climate Change: Guidance for Protected Area Managers and Planners. Monthly sea surface temperature trends between 1993 and 2017 were statistically assessed using the Mann–Kendall trend test and management plans were subject to a thematic analysis. Temperature trends showed variable SST changes among the regions, with the northern reserves all showing statistically significant increases in temperature, and the Southwest Network having the least number of reserves with statistically significant increases in temperature. The thematic analysis shows that management plans address approximately half of the climate change adaptation criteria. Several management strategies, such as dynamic MPAs, replication, and translocations, are currently absent and have been suggested as necessary tools in supporting the climate readiness of Australian MPAs. This study is significant because it helps to identify and synthesize regions most vulnerable to the impacts of ocean warming and provides management suggestions make MPAs “climate ready.”

Probabilistic Analysis of a Marine Ecological System with Intense Variability

This work seeks to simulate and examine the complex character of marine predation. By taking into account the interaction between phytoplankton and zooplankton, we present a sophisticated mathematical system with a general functional response describing the ecological competition. This system is disturbed by a novel category of perturbations in the hybrid form which simulates certain unstable climatic and environmental variations. We merge between the higher-order white noise and quadratic jumps to offer an excellent overview of the complexity induced in the ecosystem. Analytically, we offer a surrogate framework to get the sharp sill between stationarity and zooplankton eradication. Our analysis enriches and improves many works by proposing an unfamiliar form of perturbation and unifying the criteria of said asymptotic characteristics. Numerically, we probe the rigor of our sill in a non-standard case: cubic white noise and quadratic leaps. We demonstrate that the increased order of perturbation has a significant effect on the zooplankton living time. This result shows that the sources of intricate fluctuations carry out an active role in the transient dynamics of marine ecological systems.

Temporal variability of plutonium in surface waters of the Sea of Japan

Long-term temporal variations of plutonium in Sea of Japan (SOJ) surface waters have been examined with the aim to better understand its behavior during several decades. The first observation is that 239,240Pu activity concentrations in surface waters of the SOJ during 1977–2019 were 6.5 ± 4.7 mBq m−3 in average, and 5.1 mBq m−3 as the median, whereas 137Cs and 90Sr activity concentrations decreased with time, except of the perturbation due to the 2011 Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident. Another observation is that sporadic high 239,240Pu activity concentrations occurred in the east Japan Basin, ranging from 1 to 39 mBq m−3. The spatial distribution of 239,240Pu activity concentrations in surface waters revealed that high 239,240Pu levels (>20 mBq m−3) occurred in 1994 in the northern SOJ, which was considered to be due to winter convection. To elucidate factors controlling the temporal variability of surface 239,240Pu levels in the SOJ, a relationship between surface 239,240Pu activity concentrations and vertical diffusion coefficients was examined. The results revealed that this relationship could be classified into two groups: one group did not show a change with increasing diffusion coefficient, while the other group showed a positive correlation. The vertical 239,240Pu distribution in SOJ waters suggests that the high surface 239,240Pu levels occurred due to the upwelling of cyclonic eddy. The rapid recycling of deeper plutonium occurred in the SOJ due to deep winter convection and upwelling associated with cyclonic eddy. The plutonium levels in the SOJ have been found to be sensitive to climate changes. Warming of the SOJ may cause a reduction of winter convection and eddy activity as a result of increasing sea surface temperature. This leads to a decline of recirculation of plutonium and other bioavailable elements from Japan Sea Proper Water (JSPW) to surface water layers. Plutonium would be, therefore, an important indicator of biogeochemical processes in the marine environment, helping to assess climate change impacts on marine ecological systems.

Monitoring Alaskan Arctic Shelf Ecosystems Through Collaborative Observation Networks

Ongoing scientific programs that monitor marine environmental and ecological systems and changes comprise an informal but collaborative, information-rich, and spatially extensive network for the Alaskan Arctic continental shelves. Such programs reflect contributions and priorities of regional, national, and international funding agencies, as well as private donors and communities. These science programs are operated by a variety of local, regional, state, and national agencies, and academic, Tribal, for-profit, and nongovernmental nonprofit entities. Efforts include research ship and autonomous vehicle surveys, year-long mooring deployments, and observations from coastal communities. Inter-program coordination allows cost-effective leveraging of field logistics and collected data into value-added information that fosters new insights unattainable by any single program operating alone. Coordination occurs at many levels, from discussions at marine mammal co-management meetings and interagency meetings to scientific symposia and data workshops. Together, the efforts represented by this collection of loosely linked long-term monitoring programs enable a biologically focused scientific foundation for understanding ecosystem responses to warming water temperatures and declining Arctic sea ice. Here, we introduce a variety of currently active monitoring efforts in the Alaskan Arctic marine realm that exemplify the above attributes.

Multiple Stakeholders’ Perspectives of Marine Ecological Systems, a Case Study on the Barents Sea

Multiple Stakeholders’ Perspectives of Marine Ecological Systems, a Case Study on the Barents Sea

Tipping points and multiple drivers in changing aquatic ecosystems: A review of experimental studies

AbstractNatural ecosystems are experiencing unprecedented rates of change due to anthropogenic activities and global change, leading to either gradual changes in a given response or tipping points. While the tipping point concept has been tested in an array of habitats since the 1960s, the spatiotemporal superposition of multiple drivers in different ecosystems needs to be considered when investigating the response of species, communities, populations, and ecosystems along environmental gradients. Here, we (1) develop a historical and current perspective of tipping point studies in terrestrial, freshwater, and marine ecological systems; (2) portray the research effort in different freshwater and marine habitats; and (3) explore the results of experimental studies focusing on tipping points measured at the individual, communities, ecosystem level, as well as ecosystem functions and services in a context of single and multiple stressors. The number of studies mentioning the concept of tipping points increases every year, but very few studies have specific objective to identify them. Even fewer studies consider how the addition of another stressor into an ecosystem may alter a tipping point. In addition, many studies investigated multiple responses, but only one‐fourth (7 out of 28) of them concentrate their effort on multiple biological or ecological levels of complexity. This review allowed us to identify shortcomings in this research field and propose ways to make this ecological concept anew.

Collembola (Hexapoda) as Biological Drivers between Land and Sea

Simple SummaryCollembola also represent one of the most abundant and important taxa of soil invertebrates inhabiting tundra soils. We focused on the structure and distribution patterns of the collembolan communities along the environmental gradient from costal tundra to live macroalgae and aged macroalgae debris deposited across the sub-Arctic coastline. Our results imply that environmental filtering influences collembolan species distributions across the gradient studied and the sorting of species according to their respective functional traits, including dispersal ability. We also suggest that the competition—colonisation trade-off mechanism, which affected the relative importance of competition and environmental filtering, probably determined Collembola community composition over the examined gradient. We believe that our results may become the basis for further study explaining the importance of Collembola as biological drivers of connectivity between land and sea.Macroalgae debris accumulated onshore function as points of interaction between marine and terrestrial ecological systems, but knowledge of the importance of detritivores facilitating the introduction of organic matter via the detritus pathway into neighbouring ecosystems, is still poorly understood. In particular, not much is known about biodiversity patterns and the colonisation of macroalgal debris by terrestrial, detritivorous soil microarthropods in the harsh environmental conditions in the subpolar Arctic region. We hypothesised that (i) soil microarthropods of the coastal tundra, including Collembola, can cross the ecosystem boundary and colonise decaying and freshly exposed macroalgae; and (ii) various inundation regimes by sea water, microhabitat stability and decaying of macroalgae drive distribution patterns of collembolan species. Our results suggest that environmental filtering influences collembolan species’ distributions across the examined gradient and induces sorting of species according to their functional traits, including dispersal ability, resistance to disturbance and environmental tolerance.

Prediction of Sea Surface Temperature in the China Seas Based on Long Short-Term Memory Neural Networks

Sea surface temperature (SST) in the China Seas has shown an enhanced response in the accelerated global warming period and the hiatus period, causing local climate changes and affecting the health of coastal marine ecological systems. Therefore, SST distribution prediction in this area, especially seasonal and yearly predictions, could provide information to help understand and assess the future consequences of SST changes. The past few years have witnessed the applications and achievements of neural network technology in SST prediction. Due to the diversity of SST features in the China Seas, long-term and high-spatial-resolution prediction remains a crucial challenge. In this study, we adopted long short-term memory (LSTM)-based deep neural networks for 12-month lead time SST prediction from 2015 to 2018 at a 0.05° spatial resolution. Considering the sub-regional differences in the SST features of the study area, we applied self-organizing feature maps (SOM) to classify the SST data first, and then used the classification results as additional inputs for model training and validation. We selected nine models differing in structure and initial parameters for ensemble to overcome the high variance in the output. The statistics of four years’ SST difference between the predicted SST and Operational SST and Ice Analysis (OSTIA) data shows the average root mean square error (RMSE) is 0.5 °C for a one-month lead time and is 0.66 °C for a 12-month lead time. The southeast of the study area shows the highest predictable accuracy, with an RMSE less than 0.4 °C for a 12-month prediction lead time. The results indicate that our model is feasible and provides accurate long-term and high-spatial-resolution SST prediction. The experiments prove that introducing appropriate class labels as auxiliary information can improve the prediction accuracy, and integrating models with different structures and parameters can increase the stability of the prediction results.

Coastal Belt Linked Classification (CBLC): A System for Characterizing the Interface between Land and Sea Based on Large Marine Ecosystems, Coastal Ecological Sequences, and Terrestrial Ecoregions

Finkl, C.W. and Makowski, C., 2020. Coastal Belt Linked Classification (CBLC): A system for characterizing the interface between land and sea based on large marine ecosystems, coastal ecological sequences, and terrestrial ecoregions. Journal of Coastal Research, 36(4), 677–693. Coconut Creek (Florida), ISSN 0749-0208.The Coastal Belt Linked Classification (CBLC) is a novel approach based on interpretation of satellite images and assimilation of collateral data to characterize coastal belt segments that function as discrete interfaces between land and sea. This method is based on the formulation of concepts derived from the Biophysical Cross-shore Classification System (BCCS), the worldwide and regional-scale Large Marine Ecosystems (LME) classification, and the global distribution of terrestrial Ecoregions (ER). The coastal belt, a zone that extends across the shore from marine environments to inland terrestrial habitats, has recently been described in terms of cross-shore catenary sequences based on biophysical attributes of geomorphology and ecology. The CBLC formulates a cross-shore coastal classification by conjoining the Dominant Catenary Sequences (DCS) and Coastal Ecological Sequences (CES) with marine (LME) and terrestrial (ER) ecological systems; thus, a linkage is now provided between marine and terrestrial areas across coastal belts that function as transitional succession zones. This study proposes to combine the traditionally separated tripartite marine, coastal, and terrestrial delineations by melding them into a single descriptive code sequence that can be ascertained from interpretation of Google Earth satellite imagery and accessing collateral data via interactive LME and ER online platforms. Development of the CBLC is facilitated by the fact that LME and ER units are codified by numerals that are easily added to the formulated CES as prefixes and suffixes. The resulting combined alphanumeric code brings together a trove of information at different levels of investigation (Levels I – IV) that was heretofore not easily assimilated. This linkage of DCS and CES catenas with marine LME and terrestrial ER units brings added advantage to the interpretation of satellite imagery of the world's coasts, as it allows coastal belts to be viewed within the context of transitional interfaces between connected marine and terrestrial parameters. Recognition of coastal belts as interfacial bridges linking terrestrial and marine ecosystems into one codified descriptor sequence allows for cross-shore transects to be defined in the form of the Coastal Belt Linked Classification (CBLC) and provides an opportunity to fully comprehend the dynamic nature of coastal zones around the world.

Synthesis of dynamic and eco-screening approaches in modeling for ecological risk assessment

The paper proposes a method of mathematical modeling and assessment of ecological risk for marine ecological systems under the combined action of natural, anthropogenic and climatic factors. The method is based on the use of observational data, dynamic models of ecosystem state and probabilistic ecoscreening risk assessments. The main idea and novelty of the method is to take into account the annual variations of ecological risk and substantiates the primacy of determining the magnitude of the allowable risk of ecological systems, and then the allowable intensity of anthropogenic impact. Calculations using the proposed method makes it possible to get answers to questions about the principle of the admissibility of accidents of certain scales. The use of the proposed method for specific ecosystems will help to harmonize ecological and economic requirements to ensure the ecological safety of the development of shelf resources.

Application advances and prospects of CRISPR/Cas9 genome editing in nematodes

Nematodes that belong to the Phylum Nematoda are the most abundant multicellular animals on earth. They are widespread in almost all ecosystems and habitats throughout the planet, including the land and the sea (both shallow sea and deep sea). In the Phylum Nematoda, Caenorhabditis elegans is a popular model organism used in biomedical research, although other organisms such as free-living marine nematodes and parasitic nematodes are also the research focus because of their important roles in marine ecological systems or their roles as pathogens of parasitic diseases in humans, livestock, and crops. In recent years, the rapid development and the widespread application of genome editing techniques based on the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system have revolutionized research in biological sciences. Because of the advantages of simple design, low cost, wide range of targets, and high efficiency, the CRISPR/Cas9 system is rapidly becoming an indispensable experimental tool for the entire biological and medical fields. The application of CRISPR/Cas9 technology for studying the nematode worms can help researchers further investigate the function of genes and the associated biological processes, which is essential for our health, society, and environment. In this review, we summarize the recent progress made in the application of the CRISPR/Cas9 genome editing technique in C. elegans and other nematodes. We also discuss the prospects and future application hotspots of this technology in nematodes.

Rapid emergence of climate change in environmental drivers of marine ecosystems

Climate change is expected to modify ecological responses in the ocean, with the potential for important effects on the ecosystem services provided to humankind. Here we address the question of how rapidly multiple drivers of marine ecosystem change develop in the future ocean. By analysing an ensemble of models we find that, within the next 15 years, the climate change-driven trends in multiple ecosystem drivers emerge from the background of natural variability in 55% of the ocean and propagate rapidly to encompass 86% of the ocean by 2050 under a ‘business-as-usual’ scenario. However, we also demonstrate that the exposure of marine ecosystems to climate change-induced stress can be drastically reduced via climate mitigation measures; with mitigation, the proportion of ocean susceptible to multiple drivers within the next 15 years is reduced to 34%. Mitigation slows the pace at which multiple drivers emerge, allowing an additional 20 years for adaptation in marine ecological and socio-economic systems alike.

Nitrate assimilation by marine heterotrophic bacteria

Nitrate assimilation is a process where bacteria utilize nitrate as a nitrogen source and synthesize it into organic nitrogen. We found that nitrate-assimilating bacteria (NAB) are widely distributed in various marine environments, from surface to the deep ocean and sediment, which indicates that NAB are significant to the oceanic nitrogen cycle. Comparative genomic analysis revealed nitrate-assimilating genes (nasA) in these marine heterotrophic NAB showed different gene arrangements and diverse regulation systems. Summary on recent findings will contribute to understanding the process of nitrate assimilation in NAB and their ecological significance in the nitrogen cycle. A systematic analysis of a number of studies on bacterial nitrate assimilation in marine ecological systems was conducted to clarify directions for future research.

Towards understanding the organisation of metacommunities in highly dynamic ecological systems

Community ecology recognises today that local biological communities are not only affected by local biotic interactions and abiotic environmental conditions, but also by regional processes (e.g. dispersal). While much is known about how metacommunities are organised in space in terrestrial, marine and freshwater ecological systems, their temporal variations remain poorly studied. Here, we address the question of the dynamics of metacommunities in highly variable systems, using intermittent rivers (IRs), those rivers which temporarily stop flowing or dry up, as a model system. We first review how habitat heterogeneity in space and time influences metacommunity organisation. Second, we compare the metacommunities in IRs to those in perennial rivers (PRs) and develop the idea that IRs could undergo highly dynamic shifts due to the temporal variability in local and regional community processes. Third, we develop the idea that in IRs, metacommunities of the wet and dry phases of IRs are closely intertwined, thereby increasing even more their respective temporal dynamics. Last, we provide a roadmap to stimulate further conceptual and empirical developments of metacommunity research and identify possible applications for improving the management of IRs and other highly dynamic ecological systems.SynthesisExtensive research has examined the importance of local biotic interactions, environmental filtering, and regional processes on community assembly. Movement of organisms between sites, i.e. dispersal, is a major set of processes within this framework. However, subsequent metacommunity organisation also varies over time in ecosystems because habitat characteristics such as configuration and composition continuously shift. Intermittent rivers are an ideal set of systems to examine these ideas because these freshwater systems temporarily cease flowing thereby limiting dispersal events. We proposed the hypothesis that metacommunities in dynamic ecosystems will undergo frequent shifts in structure and composition in response to the temporal variability in environmental filtering and dispersal. In addition to providing a roadmap for developing a more dynamic perspective for community ecology, these framework provides direct insights for the management of intermittent rivers.

Marine Ecological State-Shifts Following the Triassic–Jurassic Mass Extinction

One of the most severe extinction events in Earth history, the Triassic–Jurassic extinction, struck against a backdrop of radical increases in atmospheric CO2and supercontinent breakup. This juxtaposition of first-order geophysical and biotic changes produced excellent case studies in Earth-Life Transitions. Recent recognition of a worldwide “carbonate gap” following the extinction has focused attention on causes, often invoked as eustacy or ocean acidification, but the ecology of the extinction aftermath remains poorly understood. Results from paleoecological studies on three separate Triassic–Jurassic records are presented and incorporated into regional depositional models. Examination of the Penarth Group of Great Britain reveals a widespread, laterally homogenous, level-bottom microbial stromatolite regime across the innermost ramp. The Sunrise Formation in Nevada, USA, was deposited during a biosiliceous (“glass”) regime dominated by demosponges across the inner ramp that lasted at least two million years. Investigations of the Pucará group in the central Andes of Peru revealed a demosponge-dominated level-bottom glass ramp with many similarities to the Nevada deposits, but offering broader regional extent and variation in recorded depositional settings. This suite of studies demonstrates state-shifts in marine ecological systems that also profoundly altered regional sedimentation regimes. The sponge-dominated systems produced glass ramp conditions instead of carbonate ramps, and indicate the importance of marine silica concentrations. The post-extinction changes in regional marine ecology demonstrate connectivity to changes in global climate and terrigenous weathering driven by global-scale geophysical processes.

Illumina sequencing-based analysis of free-living bacterial community dynamics during an Akashiwo sanguine bloom in Xiamen sea, China.

Although phytoplankton are the major source of marine dissolved organic matter (DOM), their blooms are a global problem that can greatly affect marine ecological systems, especially free-living bacteria, which are the primary DOM degraders. In this study, we analyzed free-living bacterial communities from Xiamen sea during an Akashiwo sanguine bloom using Illumina MiSeq sequencing of 16S rRNA gene amplicons. The bloom was probably stimulated by low salinity and ended after abatement of eutrophication pollution. A total of 658,446 sequence reads and 11,807 OTUs were obtained in both bloom and control samples with Alpha-proteobacteria and Gamma-proteobacteria being the predominant classes detected. The bloom decreased bacterial diversity, increased species evenness, and significantly changed the bacterial community structure. Bacterial communities within the bloom were more homogeneous than those within the control area. The bacteria stimulated by this bloom included the SAR86 and SAR116 clades and the AEGEAN-169 marine group, but a few were suppressed. In addition, many bacteria known to be associated with phytoplankton were detected only in the bloom samples. This study revealed the great influence of an A. sanguinea bloom on free-living bacterial communities, and provided new insights into the relationship between bacteria and A. sanguinea in marine ecosystems.