Phytoplankton Cell Abundance Research Articles

Exploring the response and prediction of phytoplankton to environmental factors in eutrophic marine areas using interpretable machine learning methods

Coastal marine areas are frequently affected by human activities and face ecological and environmental threats, such as algal blooms and climate change. The community structure of phytoplankton—primary producers in marine ecosystems—is highly sensitive to environmental factors, such as temperature, salinity, and nutrients. However, traditional methods for exploring the relationship between phytoplankton communities and environmental factors in eutrophic marine areas are limited by various factors. Therefore, this study employed interpretable machine learning models, integrating high-dimensional data analysis and complex system modeling, to quantitatively and thoroughly analyze the dynamic relationship between phytoplankton communities and environmental variables in high-frequency samples collected over 53 weeks from eutrophic marine areas. The cell abundance of phytoplankton exhibited a distinct “two-peak pattern” variation. Interpretable machine learning model analysis revealed the dynamic contributions of different environmental factors during changes in the phytoplankton community structure. The results showed that temperature was a key environmental factor that affected phytoplankton growth during peak periods. In addition, the contribution of salinity increased during the second peak in phytoplankton abundance, highlighting its central role in the ecological dynamics of this phase. During green tide outbreaks, particularly in Area 01, the contributions of factors such as temperature and salinity increased, whereas those of phosphates and silicates decreased, indicating that green tide outbreaks substantially altered the nutritional dynamics of the ecosystem. Furthermore, different phytoplankton species, such as Skeletonema costatum, Thalassiosira spp., and Nitzschia spp., exhibit varying responses to environmental factors. Hence, the predictions made using random forest and generalized additive models for phytoplankton cell abundance in two marine areas revealed complex nonlinear relationships between environmental factors, such as temperature, salinity, and phytoplankton abundance.

Characteristics of phytoplankton assemblages and their relationship with environmental factors in the Qiongzhou Strait, China

The characteristics and influencing factors of phytoplankton assemblages were analyzed in July (rainy season) and November (dry season) 2022 in the Qiongzhou Strait, China. A total of 68 species of phytoplankton belonging to 33 genera and 3 phyla were recorded. Diatom was the most dominant group. The broad-temperature widespread species were the most abundant. The dominant species in the rainy season were Skeletonema costatum, S. tropicum, Chaetoceros preseudocurvisetus and Thalassionema nitzschioides while those in the dry season were T. frauenfeldii, T. nitzschioides and Coscinodiscus granii. Phytoplankton cell abundance was significantly positively correlated with nitrite and total nitrogen concentrations, and negatively correlated with temperature and pH. Red tide algae occurred with high frequency. All sites were at eutrophic level except for 3 sites in the rainy season, which were at mesotrophic level. Therefore, there is a potential risk of red tides in the Qiongzhou Strait, which requires long-term monitoring and precautions.

The relationship between salmon (Salmo salar) farming and cell abundance of harmful algal taxa

The effects of nutrient effluents from fish cage aquaculture are an important eutrophication concern. It has been proposed that marine fish farm derived nutrients have the potential to increase phytoplankton abundance and lead to intensification of Harmful Algal Blooms (HABs), and that these blooms may negatively impact both the finfish and the shellfish industry. This study addressed this hypothesis using farmed salmon biomass in Scottish marine waters (as a proxy for nutrient load added to the water column as a consequence of fish farming) cell abundance of HAB taxa that most frequently impact shellfish farms and human health in the region (Dinophysis spp., Alexandrium spp. and Pseudo-nitzschia spp.), and cell abundance of one phytoplankton species of particular concern to the salmon farming industry (Karenia mikimotoi). Data from a 15-year weekly HAB monitoring programme and parallel national monitoring data relating to salmon farm stocking biomass were summarised in 5 km per 5 km aggregation boxes. Linear regression models were used to assess (i) inter-annual variation in cell abundance and total annual farmed salmon biomass; (ii) intra-annual (monthly) variation in harmful phytoplankton cell abundance and salmon biomass; (iii) a further analysis included seasonal effects within the intra-annual analysis. Farmed salmon biomass alone had a non-significant effect on cell abundance of any of the studied phytoplankton taxa. In contrast, a significant effect on cell abundance was found when using location, month or season as the predictive variable. Despite the non-significant impact of fish biomass on phytoplankton counts, the relationship varied seasonally, with a different response of Dinophysis spp. indicating a taxa specific interaction. A possible explanation for the lack of a significant relationship between farmed salmon and harmful phytoplankton cell abundance is that aquaculture farms are generally located in hydrodynamically energetic locations where recurrent flushing likely allows efficient dilution of nutrients. Overall, the analyses suggest that current levels of salmon farming activities do not markedly impact the abundance of routinely monitored biotoxin producing or fish killing phytoplankton taxa in Scottish waters.

Response of River Ecosystem Health Status to Water Environmental Factors in the Middle Reaches of Yarlung Zangbo River

River ecological health assessments are the premise for protecting river biodiversity and curbing river water environment deterioration. To explore the river ecosystem health status and its response mechanism to water environmental factors in the middle reaches of the Yarlung Zangbo River, phytoplankton samples were collected during July and October 2021, and water environmental factors were measured. The phytoplankton species were identified, and their cell abundance and biomass were calculated. The phytoplankton integrity index was constructed to evaluate the ecological health status of the river. The temporal and spatial distribution characteristics of water environmental factors and phytoplankton community, as well as the correlation between P-IBI value and community parameters and water environmental factors were analyzed. The results showed that the difference in water environmental factors was not evident in time but was significant in space. The average cell abundance and biomass of phytoplankton were in the order of wet season>dry season and main stream>tributaries. Diatoms dominated the community, and pH and WT were the major water environmental factors driving the spatial and temporal distributions of phytoplankton. The ecological health status of the middle reaches of the Yarlung Zangbo River was "healthy to sub-healthy." The river health status was better than that of the dry season, and that of the tributaries was better than that of the main stream. EC, TUR, WT, NO3--N, and NH4+-N were the major water environmental factors affecting the ecological health status of the river reach, which could be affected by the direction and rate of phytoplankton community succession. It is involved in and affects the process of material circulation and energy flow of the river ecosystem, thereby driving the ecological health of the middle reaches of the Yarlung Zangbo River.

Phytoplankton dynamics in the Mar Menor, a Mediterranean coastal lagoon strongly impacted by eutrophication

The Mar Menor hypersaline coastal lagoon has suffered serious degradation in the last three decades attributable to nutrient pollution. In 2015, the lagoon experienced an intensive bloom of cyanobacteria that triggered a drastic change of its ecosystem. Our analyses indicate that phytoplankton in 2016–2021 did not present a seasonal variability pattern; the community was mainly dominated by diatoms and punctually reached abundance peaks above 107 cell L−1 along with chlorophyll a concentrations exceeding 20 μg L−1. The predominant diatom genera during these blooms were different as well as the nutrient conditions under which they were produced. These high diatom abundances are unprecedented in the lagoon; in fact, our data indicate that the taxonomic composition, time variation patterns and cell abundance of phytoplankton in 2016–2021 differ notably in comparison to the data published before 2015. Consequently, our results support the finding that the trophic status of the lagoon has changed profoundly.

Phytoplankton Community Diversity and Its Environmental Driving Factors in the Northern South China Sea

The South China Sea (SCS) plays an important role in global marine ecology. Studies of phytoplankton diversity promote the sustainable utilization of resources in the SCS. From July to August 2020, the phytoplankton community structure at 47 stations in the northern SCS was investigated. Species composition and distribution of phytoplankton, water quality, diversity index, main influencing factors, and succession characteristics of the community structure were analyzed in combination with the survey results from previous years. A total of 332 separate taxa from 83 genera and three phyla were identified, including 142 species and 45 genera of Bacillariophyta, 188 species and 36 genera of Dinophyta, and two species and two genera of Chrysophyta. Average phytoplankton cell abundance was 649.97 cells/L. Nitzschia spp., Thalassionema nitzschioides, and Scrippsiella spp. were the dominant species. Scrippsiella spp. was found for the first time as a dominant species in the northern SCS. Meanwhile, Nitzschia spp. was associated with organic-polluted water. The high-value areas of Nitzschia spp. also indicated eutrophication, and water was slightly polluted. The Shannon–Weiner diversity index of the surface layer was 0.99–4.56 (with a mean of 3.57), and the evenness index was 0.23–0.96 (with a mean of 0.83). The phytoplankton community structure in the northern SCS was deemed to be stable. Pearson correlation analysis showed that the sum of nitrate and nitrite was significantly negatively correlated with the abundance of dinoflagellate, which indicated restrictions as a result of the sum of nitrate and nitrite, with no significant correlation between ammonium salt and various groups. Small- and medium-sized phytoplankton are usually dominant in the SCS, where nitrogen is limited.

Sequencing our way to more accurate community abundance.

Over the last two decades, there has been a huge increase in our understanding of microbial diversity, structure and composition enabled by high-throughput sequencing technologies. Yet, it is unclear how the number of sequences translates to the number of cells or species within the community. In some cases, additional observational data may be required to ensure relative abundance patterns from sequence reads are biologically meaningful. The goal of DNA-based methods for biodiversity assessments is to obtain robust community abundance data, simultaneously, from environmental samples. In this issue of Molecular Ecology Resources, Pierella Karlusich et al.(2022) describe a new method for quantifying phytoplankton cell abundance. Using Tara Oceans data sets, the authors propose the photosynthetic gene psbO for reporting accurate relative abundance of the entire phytoplankton community from metagenomic data. The authors demonstrate higher correlations with traditional optical methods (including microscopy and flow cytometry), using their new method, improving upon molecular abundance assessments using multicopy marker genes. Furthermore, to facilitate application of their approach, the authors curated a psbO gene database for accessible taxonomic queries. This is an important step towards improving species abundance estimates from molecular data and eventually reporting of absolute species abundance, enhancing our understanding of community dynamics.

Phytoplankton community structure and driving mechanism of its construction process in autumn in Zhelin Reservoir, Lake Poyang Basin

研究环境过滤过程和空间扩散限制过程在构建水生浮游植物群落结构中的作用是了解这些因素如何驱动物种分布和影响群落结构的关键步骤.为了揭示鄱阳湖流域柘林水库浮游植物群落结构特征与环境因子的关系，以及明确环境因子和空间扩散限制性因子在浮游植物群落构建过程中的影响机制，于2020年10月，对柘林水库33个采样点的浮游植物和水质理化进行调查分析.共鉴定浮游植物7门122种，其中，以绿藻门种类最多，为34属62种，占总物种数的50.81%，硅藻门次之，为11属27种.柘林水库浮游植物优势种类主要是蓝藻门中的伪鱼腥藻属（Pseudoanabaena）、浮鞘丝藻属（Planktolyngbya）、小尖头藻属（Raphidiopsis）以及硅藻门中的针杆藻属（Synedra）.柘林水库浮游植物细胞丰度的变化范围为0.93×10⁶~172.12×10⁶ cells/L，平均值为95.42×10⁶ cells/L，生物量的变化范围为0.95~22.35 mg/L，平均值为9.35 mg/L.上游修河水域浮游植物生物多样性指数显著高于库心和库湾水域，库心与库湾水域之间浮游植物生物多样性指数差异性不明显.柘林水库上游修河水域浮游植物群落结构与库心和库湾水域存在明显分离，群落结构的差异性主要受水体透明度、电导率、氨氮和硝态氮的影响.变差分解结果显示，空间扩散限制性作用在驱动柘林水库浮游植物群落构建过程中占据主导地位.;Evaluation of the relative influences of environmental and spatial processes in structuring aquatic phytoplankton metacommunities is an essential step for understanding the species spatio-temporal distributions. To reveal the relationships between community structures of phytoplankton and the environment as well as clarify the driving mechanism of environmental factors and spatial diffusion limiting factors on phytoplankton community structure in Zhelin Reservoir, Lake Poyang Basin, the phytoplankton and water quality physicochemical characteristics of 33 sampling sites were investigated and analyzed in October 2020. A total of 122 species belong to 7 genera were identified, with 62 species in 34 genera were Chlorophyta, accounting for 50.81% of the total species, followed by Bacillariophyta with 27 species in 11 genera. The dominant species of phytoplankton in Zhelin Reservoir are Pseudoanabaena, Planktolyngbya and Raphidiopsis of Cyanophyta and Synedra of Bacillariophyta. The cell abundance of phytoplankton in the Zhelin Reservoir varied from 0.93×10⁶ to 172.12×10⁶ cells/L with an average of 95.42×10⁶ cells/L, and the biomass varied from 0.95 to 22.35 mg/L with an average of 9.35 mg/L. The phytoplankton biodiversity index in the upstream Xiuhe tributary area was significantly higher than that in the center of the reservoir area and the reservoir bay area, while no significant difference in the phytoplankton biodiversity index between the center of the reservoir area and the reservoir bay area was found. The phytoplankton community structure in the Xiuhe tributaries of Zhelin Reservoir was separated from that in the center reservoir and reservoir bay, and the differences were mainly affected by water transparency, electrical conductivity, ammonia nitrogen and nitrate nitrogen. The results of variation partitioning showed that the spatial diffusion limiting effect was dominant in driving the phytoplankton community structure in Zhelin Reservoir.

Mediterranean nascent sea spray organic aerosol and relationships with seawater biogeochemistry

Abstract. The organic mass fraction from sea spray aerosol (SSA) is currently a subject of intense research. The majority of this research is dedicated to measurements in ambient air. However a number of studies have recently started to focus on nascent sea spray aerosol. This work presents measurements collected during a 5-week cruise in May and June 2017 in the central and western Mediterranean Sea, an oligotrophic marine region with low phytoplankton biomass. Surface seawater was continuously pumped into a bubble-bursting apparatus to generate nascent sea spray aerosol. Size distributions were measured with a differential mobility particle sizer (DMPS). Chemical characterization of the submicron aerosol was performed with a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) operating with 10 min time resolution and with filter-based chemical analysis on a daily basis. Using positive matrix factorization analysis, the ToF-ACSM non-refractory organic matter (OMNR) was separated into four different organic aerosol types, identified as primary OA (POANR), oxidized OA (OOANR), methanesulfonic acid type OA (MSA-OANR), and mixed OA (MOANR). In parallel, surface seawater biogeochemical properties were monitored providing information on phytoplankton cell abundance and seawater particulate organic carbon (1 h time resolution) and seawater surface microlayer (SML) dissolved organic carbon (DOC) (on a daily basis). Statistically robust correlations (for n>500) were found between MOANR and nanophytoplankton cell abundance, as well as between POANR, OOANR, and particulate organic carbon (POC). Parameterizations of the contributions of different types of organics to the submicron nascent sea spray aerosol are proposed as a function of the seawater biogeochemical properties for use in models.

Microbial Communities in Water during Red Tides along the Coast of China-A Case Study of Prorocentrum Donghaiense Red Tide in the East China Sea

Red tides are a major public hazard in the global oceans. The coast of the East China Sea is the sea area where red tide disasters are the most frequent and serious in China. In order to accurately grasp the occurrence of red tides in the coastal waters of the East China Sea, and to understand the microbial communities in the waters during the occurrence of red tides in the East China Sea, a special survey of red tides in the coastal waters of Zhejiang, China was carried out in June 2018. The results showed that nutrient concentrations of N and P were generally high in this area, DIN concentrations in most areas exceeded the permitted limit of Chinese seawater quality grade I. There were significant differences in dissolved oxygen, pH, COD, chlorophyll and phytoplankton abundance of red tides. During the investigation, red tides were found in the waters near the Yushan Islands. The content of chlorophyll a was 42.12mg/m3, the cell abundance of phytoplankton was 8.16×108/L, and the abundance of Prorocentrum edulis accounted for 98.5%. The Illumina MiSeq sequencing platform was used for 16s high-throughput sequencing of water microorganisms, and a total of 16 bacteria were identified. Proteobacteria is the first dominant phylum, followed by Cyanobacteria and Bacteroides. Some differences in bacterial community compositions between HAB and the nearby seawater were observed. The predominant bacteria in the red tide occurrence area were Proteobacteria, comprising 46.1% of the relative abundance; while the predominant bacteria in the nearby sea area, comprising 42.0% of the relative abundance.

Modelling the impact of phytoplankton cell size and abundance on inherent optical properties (IOPs) and a remotely sensed chlorophyll-a product

Abstract Ocean colour data are commonly used to quantify primary production, study phytoplankton dynamics and calibrate marine models, thus understanding the origin of errors in the retrieved chlorophyll-a (Chl-a) product is critical. One source of uncertainty in retrieved Chl-a products can be related to large photosynthetic cells, characterised by lower mass-specific absorption coefficients due to increased packaging effect. Here, we explore the relationship between phytoplankton size structure and an ocean colour product using optical simulations and in situ observations. Specifically, we use an optical model to explore how phytoplankton cell size and abundance influence phytoplankton absorption and backscattering coefficients and the implication this has for water leaving radiance and the estimated Chl-a derived from satellite ocean colour. The optical model simulations show phytoplankton cell size has a significant impact on the remote-sensing reflectance, with Chl-a packaged in 5 to 10 μm cells resulting in about 54 to 76% the simulated ocean colour Chl-a compared to 1 μm cells, as determined by an algorithm that converts reflectances to Chl-a. To support optical simulations, size-fractionated Chl-a samples were collected from several water masses to investigate the phytoplankton size contribution (i.e., 10 μm) to the total Chl-a. We focused on the offshore eastern Australian ocean region, largely characterised by oligotrophic waters in which phytoplankton dominate the optical properties of the water column. Of the 22 stations sampled, a total of ten in situ size fractionated Chl-a measurements were matched-up with the corresponding clear-sky satellite Chl-a product. The matched-up points revealed a systematic underestimation of in situ Chl-a. With the low amount of data, it was not possible to statistically relate the satellite underestimation to a specific phytoplankton size class, but the observations showed that the largest satellite Chl-a underestimates were found when phytoplankton larger than 10 μm represented more than 50% of the phytoplankton community. Additional measurements that combine in situ optical measurements with phytoplankton size distribution and carbon/Chl-a ratio would help to clarify the relationship between phytoplankton size structures and remotely sensed Chl-a product.

Patterns of phytoplankton structure in response to environmental gradients in a macrotidal estuary of the Equatorial Margin (Atlantic coast, Brazil)

The structure of phytoplankton community was studied in a tropical macrotidal estuary (Paciência river estuary), which is socially and ecologically important because is surrounded by one of the most extensive mangrove forests of the world and plays a key role in the local economy, through artisanal fishing and bivalve extraction activities in natural environments. To understand the regulation mechanisms driving the phytoplankton dynamics and the key indicator species for monitoring ecological change, the study considered seasonal and spatial analysis of environmental and biological variables in thirteen sampling points during the three seasonal periods in 2017. The ecological patterns of phytoplankton were explored by Cluster Analysis and key species were selected by the indicator value method (IndVal). From 171 identified taxa, Bacillariophyta was the most representative division (128 taxa). The phytoplankton structure was well-defined by a salinity gradient governed by rainfall and river discharge. Thus, three scenarios related to seasonality and salinity gradient were identified: tidal river zone, mixing zone and coastal zone. During the rainy and transitional seasons, it was observed a spatial gradient of salinity, characterized by the gradual increase in phytoplankton abundance and biomass from the freshwater zone towards the coastal zone, following an opposite nutrient gradient. The highest salinity and light availability (low turbidity and total particulate matter) in the dry season favored a significant growth of phytoplankton (cell abundance and biomass). Thus, the key species selected by IndVal method was Discostella stelligera, Coscinodiscus oculus-iridis and Trieres sinensis in the rainy period, Nitzschia reversa, Thalassiosira sp. and Bellerochea horologicalis in the transitional period, and Protoperidinium sp., Thalassiosira subtilis, Cyclotella striata and Thalassiosira rotula in the dry period. Hence, this work contributes to the understanding of the macrotidal estuaries functioning, reinforcing the importance of phytoplankton monitoring for the identification of ecological changes.

Metabolic Functional Community Diversity of Associated Bacteria during the Degradation of Phytoplankton from a Drinking Water Reservoir.

In the drinking water reservoir ecosystem, phytoplankton and bacteria play important roles in shaping freshwater health and function. In this work, the associated bacterial community functional diversity during degradation of phytoplankton was determined using the substrate utilization profiling (BIOLOG) technique, meanwhile, the composition and concentration of phytoplankton were examined using a microscope. The results indicated that Euglena decreased 58.33% from 0 to 38 d, while the smallest degradation of Bacillariophyta was 20.19%. Average well color development (AWCD590nm) increased during the static periods from 0 to 38 d; however, the AWCD590nm of 18 and 38 d had no significant difference (p < 0.05). The Simpson’s index (D) was in accordance with Shannon’s diversity (H) and species richness(S); it was measured to be18 > 38 > 5 > 0 d. There were significant differences in the pattern and level of carbon sources used by the phytoplankton-associated bacteria. In addition, the principle component analyses (PCA) suggested that the first principle component (PC1) and the second principle component (PC2) explained 46.76% and 21.49% of the total variation for bacterial community, respectively. Redundancy analysis (RDA) revealed that cell abundance of phytoplankton was negatively correlated with the AWCD590nm, amino acids and other functional indexes. Therefore, the data suggest that there are differences in the phytoplankton-associated bacterial community functional diversity during different static stages of water samples collected from the drinking water reservoir.

Multivariate analysis of phytoplankton community structure in Changli Gold Coast National Nature Reserve of Hebei Province in Spring, 2019

In order to research the characteristics of phytoplankton community structure in Changli Gold Coast National Nature Reserve, China, 14 survey stations were set up in this area in May 2019. The basic characteristics of phytoplankton community composition, cell abundance and community diversity were analyzed, and the Multi-Dimensional Scaling (MDS) was used to divide the structure of phytoplankton community. The results showed that a total of 30 species of phytoplankton were identified in this area, mainly diatoms, and the main ecological types were temperate inshore wide temperature and wide salt species. The average cell abundance of phytoplankton in May was 54.38×104 cells/m3, and the main dominant species were Nitzschia sp., Skeletonema costatum and Noctiluca scientillans. The average value of Shannon-Wiener index was 2.26, The average value of evenness index was 0.75. The average of richness index was 0.73. The phytoplankton divided into 6 zones with significant differences by CLUSTER Analysis (P<0.001).

Microscopic view of phytoplankton along the Yangtze River

Phytoplankton play an important role in nutrient cycling and energy conversion. However, phytoplankton community is poorly understood in large river ecosystems. Based on the large-scale samplings conducted in spring and autumn of 2017, a systematic study has been made on seasonal and spatial distributions of phytoplankton community along the mainstream of the Yangtze River. As results, 6 phyla were identified and 59 phytoplankton species were detected using microscopy, including Bacillariophyta (29 species), Chlorophyta (13 species) and Cyanophyta (8 species) as the dominant group. Moreover, the density of phytoplankton was ranged 0.05 × 106−1.90 × 106 cells/L and the biomass was 0.01–1.01 mg/L, both reaching their maximum in the middle reach from Yichang to Wuhan. Significant seasonal difference of phytoplankton community was observed and spatial dissimilarity in spring was revealed. The cell abundance and biomass of phytoplankton could be fairly estimated by chlorophyll-a, and redundancy analysis indicated that water temperature, dissolved oxygen, biochemical oxygen demand, nitrite, and ammonia nitrogen were the most important explanatory environmental factors for phytoplankton compositions in the Yangtze River.

Small pigmented eukaryotes play a major role in carbon cycling in the P‐depleted western subtropical North Atlantic, which may be supported by mixotrophy

AbstractWe found that in the phosphate (PO4)‐depleted western subtropical North Atlantic Ocean, small‐sized pigmented eukaryotes (P‐Euk; &lt; 5 μm) play a central role in the carbon (C) cycling. Although P‐Euk were only ~ 5% of the microbial phytoplankton cell abundance, they represented at least two thirds of the microbial phytoplankton C biomass and fixed more CO2 than picocyanobacteria, accounting for roughly half of the volumetric CO2 fixation by the microbial phytoplankton, or a third of the total primary production. Cell‐specific PO4 assimilation rates of P‐Euk and nonpigmented eukaryotes (NP‐Euk; &lt; 5 μm) were generally higher than of picocyanobacteria. However, when normalized to biovolumes, picocyanobacteria assimilated roughly four times more PO4 than small eukaryotes, indicating different strategies to cope with PO4 limitation. Our results underline an imbalance in the CO2 : PO4 uptake rate ratios, which may be explained by phagotrophic predation providing mixotrophic protists with their largest source of PO4. 18S rDNA amplicon sequence analyses suggested that P‐Euk was dominated by members of green algae and dinoflagellates, the latter group commonly mixotrophic, whereas marine alveolates were the dominant NP‐Euk. Bacterivory by P‐Euk (0.9 ± 0.3 bacteria P‐Euk−1 h−1) was comparable to values previously measured in the central North Atlantic, indicating that small mixotrophic eukaryotes likely exhibit similar predatory pressure on bacteria. Interestingly, bacterivory rates were reduced when PO4 was added during experimental incubations, indicating that feeding rate by P‐Euk is regulated by PO4 availability. This may be in response to the higher cost associated with assimilating PO4 by phagocytosis compared to osmotrophy.

Spatio-temporal variability of phytoplankton assemblages and its controlling factors in spring and summer in the Subei Shoal of Yellow Sea, China

The Subei Shoal is a special coastal area with complex physical oceanographic properties in the Yellow Sea. In the present study, the distribution of phytoplankton and its correlation with environmental factors were studied during spring and summer of 2012 in the Subei Shoal of the Yellow Sea. Phytoplankton species composition and abundance data were accomplished by Utermohl method. Diatoms represented the greatest cellular abundance during the study period. In spring, the phytoplankton cell abundance ranged from 1.59×103 to 269.78×103 cell/L with an average of 41.80×103 cell/L, and Skeletonema sp. and Paralia sulcata was the most dominant species. In summer, the average phytoplankton cell abundance was 72.59×103 cell/L with the range of 1.78×103 to 574.96×103 cell/L, and the main dominant species was Pseudo-nitzschia pungens, Skeletonema sp., Dactyliosolen fragilissima and Chaetoceros curvisetus. The results of a redundancy analysis (RDA) showed that turbidity, temperature, salinity, pH, dissolved oxygen (DO), the ratio of dissolved inorganic nitrogen to silicate and SiO4-Si (DIN/SiO4-Si) were the most important environmental factors controlling phytoplankton assemblages in spring or summer in the Subei Shoal of the Yellow Sea.

Spatial-temporal variation of phytoplankton community structure in Jiaozhou Bay, China

To better understand the spatial-temporal variation in phytoplankton community structure and its controlling factors in Jiaozhou Bay, Qingdao, North China, four seasonal sampling were carried out in 2017. The phytoplankton community structure and various environmental parameters were examined. The phytoplankton community in the bay was composed of mainly diatoms and dinoflagellates, and several other species of Chrysophyta were also observed. Diatoms were the most dominant phytoplankton group throughout the year, except in spring and winter, when Noctiluca scintillans was co-dominant. High Si/N ratios in summer and fall reflect the high dominance of diatoms in the two seasons. Temporally, the phytoplankton cell abundance peaked in summer, due mainly to the high temperatures and nutrient concentrations in summer. Spatially, the phytoplankton cell abundance was higher in the northern part of the bay than in the other parts of the bay in four seasons. The diatom cell abundances show significant positive correlations with the nutrient concentrations, while the dinoflagellate cell abundances show no correlation or a negative correlation with the nutrient concentrations but a significant positive correlation with the stratification index. This discrepancy was mainly due to the different survival strategies between diatoms and dinoflagellates. The Shannon-Wiener diversity index (H′) values in the bay ranged from 0.08 to 4.18, which fell in the range reported in historical studies. The distribution pattern of H′ values was quite different from that of chlorophyll a, indicating that the phytoplankton community structure might have high biomass with a low diversity index. Compared with historical studies, we believe that the dominant phytoplankton species have been changed in recent years due mainly to the changing environment in the Jiaozhou Bay in recent 30 years.

Seasonal species diversity and abundance of phytoplankton from the southwestern Caspian Sea

In the present investigation, we aimed to study diversity and cell abundance of phytoplankton in the southwest of the Caspian Sea. This survey included 4 transects and 12 stations. A total of 48 samples were collected during spring 2012 and spring 2013. Finally, 72 species of phytoplankton were identified including phyla Diatoms (29 species), Chlorophyta (17 species), Pyrrophyta (16 species), Cyanophyta (6 species), and Euglenophyta (4 species). The total average of cell abundance was approximately 43.55 ± 5.10 × 104 cells/m3. The number of recorded species in spring, summer, autumn, and winter was 46, 50, 41 and 39, respectively. Diatoms had the highest species diversity and cell abundance in winter related to Thalassionema nitzschiodes at a depth of 10 m. Seasonal changes in diversity of phytoplankton significantly differed, showing maximum in autumn with high diversity index (2.532) and minimum in spring (2.201) on Shannon Diversity Index. Finally, the quality of water is classified according to this index in the middle level.

Characteristics of phytoplankton assemblages in the southern Yellow Sea, China

The characteristics of phytoplankton assemblages were analyzed by the Utermöhl method in the southern Yellow Sea in summer, 2008. A total of 113 species (including varieties and forms), belonging to 51 genera and 3 phyla, were identified. Diatom was the most dominant group. The dominant species included Eucampia zoodiacus, Leptocylindrus danicus, Chaetoceros affinis, Thalassionema nitzschioides, Skeletonema costatum, Paralia sulcata and Chaetoceros tortissimus, which were eurytopic and temperate species. The cell abundance of phytoplankton ranged from 0.04 to 620.08 cells·mL−1 with an average of 27.52 cells·mL−1. Horizontally, the cell abundance showed a decreasing trend from the south to the north. In terms of vertical distribution, the values in surface and subsurface water layers were higher than those in bottom water layers. Results of correlation analysis showed that phytoplankton cell abundance was positively correlated with water temperature, ammonia and nitrite concentrations, and negatively correlated with salinity and silicate concentration.