Phytoplankton Dynamics Research Articles

How to learn more about hydrological conditions and phytoplankton dynamics and diversity in the eastern English Channel and the Southern Bight of the North Sea: the Suivi Régional des Nutriments data set (1992–2021)

Abstract. This article describes a 30-year data series produced by the SRN (“Suivi Régional des Nutriments” in French; Regional Nutrients Monitoring Programme) network managed by Ifremer. Since 1992, the SRN network has been analysing phytoplankton species and measuring physicochemical (temperature, salinity, oxygen, suspended matter, nutrients) and biological (chlorophyll a, phytoplankton abundance) parameters at 10 different stations distributed along three different transects located in the eastern English Channel and the Southern Bight of the North Sea. This geographic coverage allows for the study of three distinct ecosystems, i.e. three transects (estuary, coastal region under freshwater influence, and coastal region), as well as the investigation of coastal to offshore water gradients. The SRN collects a maximum of 184 samples per year (3687 samples spread over 10 stations during the studied period) and detects up to 291 taxa, including harmful algal bloom species (HABs), with a bi-weekly to monthly sampling frequency (depending on the location and the season). The objectives of this monitoring programme are to assess the influence of continental inputs on the marine environment and their implications for possible eutrophication processes. It also aims to estimate the effectiveness of development and management policies in the marine coastal zone by providing information on trends and/or shifts in pressure, state, and impact variables. The regular acquisition of data allows the establishment of long-term monitoring of the evolution of coastal water quality as well as the observation of the consequences of large-scale alterations mainly driven by climate change and modifications that are more related to local/regional anthropogenic activities. This paper provides an overview of the main characteristics of SRN data (descriptive statistics and data series main patterns) as well as an analysis of temporal trends and shifts. We also propose to the data user a specific numerical tool available as an R package to optimize the data pre-processing and processing steps. Users will then have easy access to statistics, trends, and anomalies as proposed in this paper. The main results of several research projects based on SRN data and dealing with hydrology, phytoplankton blooms, HABs, phenology, and niches are also highlighted, providing the readers with examples of what can be done with such a data set. We hope that this synthesis will also save data users time by allowing them to jump right into a deeper analysis based on previous conclusions and perspectives or to investigate new scientific key challenges. These data should also be used at a wider geographical scale, combined with other data sources, to define more global patterns of environmental changes in a moving world subject to strong anthropogenic pressures. Data can also be used by the remote sensing (ocean colour observation) and modelling communities to calibrate or validate products in this complex and vital coastal region. The SRN data set is publicly available: https://doi.org/10.17882/50832 (SRN – Regional Observation and Monitoring program for Phytoplankton and Hydrology in the eastern English Channel, 2022).

Algal cell viability assessment: The role of environmental factors in phytoplankton population dynamics

The viability of algal cells is one of the most fundamental issues in marine ecological research. In this work, a method was designed to identify algal cell viability based on digital holography and deep learning, which divided algal cells into three categories: active, weak, and dead cells. This method was applied to measure algal cells in surface waters of the East China Sea in spring, revealing about 4.34 %–23.29 % weak cells and 3.98 %–19.47 % dead cells. Levels of nitrate and chlorophyll a were the main factors affecting the viability of algal cells. Furthermore, algal viability changes during the heating and cooling were observed in laboratory experiments: high temperatures led to an increase in weak algal cells. This may provide an explanation for why most harmful algal blooms occur in warming months. This study provided a novel insight into how to identify the viability of algal cells and understand their significance in the ocean.

Phytoplankton Seasonal Dynamics under Conditions of Climate Change and Anthropogenic Pollution in the Western Coastal Waters of the Black Sea (Sevastopol Region)

The studies of seasonal phytoplankton dynamics, its growth rate, and microzooplankton grazing were conducted on two stations in the western Black Sea coastal waters near Sevastopol from January 2021 to December 2022. The phytoplankton species composition has remained relatively the same during recent years compared to the end of the last century and the beginning of the 2000s. However, significant changes have occurred in the ratio between different species of diatoms, and the proportion of dinoflagellates was increased, especially in the autumn. Large diatoms and dinoflagellates play a crucial role in forming the phytoplankton biomass seasonal peaks. The first central maximum was observed in July, and the second smaller one was in September–November. Whereas two decades ago, the small diatoms generated three peaks annually: in February, May, and September–October. The maximum values of the phytoplankton growth rate and the rate of its consumption by microzooplankton decreased 2–3 times compared to the beginning of the 2000s. The relative share of primary production consumed by microzooplankton annually averages 35%, two times lower than before.

MODELING CELL POPULATIONS MEASURED BY FLOW CYTOMETRY WITH COVARIATES USING SPARSE MIXTURE OF REGRESSIONS.

The ocean is filled with microscopic microalgae, called phytoplankton, which together are responsible for as much photosynthesis as all plants on land combined. Our ability to predict their response to the warming ocean relies on understanding how the dynamics of phytoplankton populations is influenced by changes in environmental conditions. One powerful technique to study the dynamics of phytoplankton is flow cytometry which measures the optical properties of thousands of individual cells per second. Today, oceanographers are able to collect flow cytometry data in real time onboard a moving ship, providing them with fine-scale resolution of the distribution of phytoplankton across thousands of kilometers. One of the current challenges is to understand how these small- and large-scale variations relate to environmental conditions, such as nutrient availability, temperature, light and ocean currents. In this paper we propose a novel sparse mixture of multivariate regressions model to estimate the time-varying phytoplankton subpopulations while simultaneously identifying the specific environmental covariates that are predictive of the observed changes to these subpopulations. We demonstrate the usefulness and interpretability of the approach using both synthetic data and real observations collected on an oceanographic cruise conducted in the northeast Pacific in the spring of 2017.

MODIS-derived green Noctiluca blooms in the upper Gulf of Thailand: Algorithm development and seasonal variation mapping

In recent decades, red tides of non-toxic harmful algal blooms have frequently occurred in monsoon-influenced tropical areas, particularly the green form of Noctiluca scintillans (hereafter green Noctiluca). However, our understanding of the mechanism of red tide formation is hindered by spatial and temporal constraints of field data. In this study, we used moderate resolution imaging spectroradiometer (MODIS) ocean color data along with a locally developed algal-bloom classification algorithm to investigate the seasonal variability of dominant red tides across the upper Gulf of Thailand (uGoT). During our July 2018 observation, a super green Noctiluca bloom with extraordinarily high chl-a (>1,469 mg m-3) displayed a distinct spectral reflectance characteristic among red tides in blue-to-green and red-to-near infrared wavelengths. According to the distinctive in situ hyperspectral characteristics of uGoT algal blooms, we developed a classification algorithm for MODIS normalized at 488, 531, and 667 nm, which successfully discriminated green Noctiluca in three levels of blooms, namely, super (100%), strong (>80%), and weak (>40%), from other algal blooms (i.e., dinoflagellates, diatoms, cyanobacteria, and mixed red tide species) as well as non-bloom oceanic and coastal waters using MODIS data, as confirmed by uGoT red tide reports. Monthly MODIS-based discrimination composites from 2003 to 2021 revealed seasonal variability in the surface distribution and bloom frequency of green Noctiluca and other red tides according to the Asian monsoon seasons: the southwest monsoon (May–September) and the northeast monsoon (October–January of the following year). Green Noctiluca blooms occurred farther from the shore and estuaries than other red tides (dinoflagellates and cyanobacteria), and were much more frequent than other red tides between the Tha Chin and Chao Phraya River mouths during the non-monsoon period (February to April). The frequency and distribution of green Noctiluca blooms, as well as other algal blooms, varied with the monsoon season. By comparing MODIS-derived algal blooms to monsoon-induced factors (i.e., sea surface winds, precipitation, and river discharge), we present an unprecedented overview of the spatial and temporal dynamics of red tides throughout the uGoT under Asian monsoon conditions. This research contributes to our understanding of the impact of climate change on phytoplankton dynamics.

Revised chlorophyll-a algorithms for satellite ocean color sensors in the East/Japan Sea

The East/Japan Sea (hereafter, East Sea (ES)) is a semi-enclosed marginal sea and considered as a miniature ocean with oceanic features (e.g., currents, eddies, fronts, upwelling) and dynamic marine environments. The ES is significantly influenced by the global ocean warming with fast increases in sea surface temperature during the last several decades. The climate-induced environmental changes can affect marine ecosystem and food webs in the ES. Therefore, more accurate estimates in phytoplankton biomass in the ES with high spatial and temporal resolutions are necessary to investigate phytoplankton production, fisheries, and carbon budget as well as biological responses to the environmental and climate changes. The NASA ocean chlorophyll-type (OCx) chlorophyll-a (Chl-a) algorithms based on blue to green band ratio for the satellite ocean color data in the global ocean have been evaluated using the in situ radiometric and Chl-a measurements in the ES. The model-derived Chl-a data using the OC Chl-a algorithms present systematic overestimation in the lower Chl-a concentrations between about 0.1 and 1.0 mg/m3 in the ES (with ∼40% uncertainties). New Chl-a algorithms for the ES has been derived from the 3rd polynomial regression fits of in situ Chl-a and maximum band ratios of remote sensing reflectance (Rrs). The revised Chl-a algorithms considerably improve the Chl-a data in the ES from the satellite ocean color data in the lower Chl-a concentrations. Thus, the new Chl-a algorithms can provide more accurate assessments in biological and biogeochemical processes such as primary productivity, phytoplankton phenology, phytoplankton dynamics, and carbon cycles.

Phytoplankton dynamics, growth and microzooplankton grazing across the subtropical frontal zone, east of New Zealand

Elevated but variable phytoplankton biomass and productivity is often associated with the subtropical front (STF) where nitrogen-limited subtropical and iron-limited subantarctic waters mix. To understand variability within the STF east of New Zealand, we assessed phytoplankton community structure, growth, and grazing dynamics in relation to physico-chemical conditions across 23 stations distributed along the Chatham Rise region during late autumn-early winter. Serial dilution experiments were coupled with size-fractionated chlorophyll a (Chla) analysis (Total and <20 μm) and flow-cytometry (Synechococcus and picoeukaryote numbers, <2 μm) to estimate phytoplankton growth and microzooplankton grazing rates. Within the broad STF zone, subantarctic influenced waters (SAIW), frontal zone (FZ), and subtropical influenced waters (STIW) were delimited based on salinity, temperature and nutrient gradients. The chlorophyll a biomass (TChla) of phytoplankton and the abundance of larger sized cells (>20 μm chlorophyll a) peaked in FZ waters but declined steadily southwards into the colder SAIW, and rapidly reduced north into the STIW. Chlorophyll a <2 μm peaked in the northern STIW. Phytoplankton growth (TChla) was higher in warmer STIW (μ = 0.49 ± 0.07 day−1) than in iron limited SAIW (μ = 0.29 ± 0.06 day−1) but was on average moderate (μ = 0.42 ± 0.05 day−1) when compared to previous studies in the region. Microzooplankton grazing on TChla was lower (m = 0.17 ± 0.04 day−1) than growth and accounted for half of daily primary production (m:μ, 0.47 ± 0.06). Growth in the <20 μm Chla size fraction was higher (μ = 0.52 ± 0.06 day−1) but a larger proportion was consumed by microzooplankton (m:μ = 0.64 ± 0.06). Picoeukaryotes showed the fastest growth (1.49 ± 0.13 day−1) and grazing (1.43 ± 0.11 day−1) rates on average, which peaked in the FZ but remained closely balanced across different waters (m:μ = 1.00 ± 0.02). Conversely, Synechococcus rates peaked in STIW and decreased southwards, with growth (μ = 0.42 ± 0.08 day−1) generally exceeding grazing (m = 0.28 ± 0.06 day−1) across all regions. Our results indicate differences in grazing together with nutrient (likely iron) availability were the primary factors controlling phytoplankton dynamics in the STF zone. These factors also affected the accumulation of larger phytoplankton biomass in the FZ, including the potential for export or transfer to higher trophic levels.

Evolution of multi-annual and large-scale phytoplankton patterns in the Scheldt estuary: The disappearance of phytoplankton accumulation in the brackish region

Estuaries often show regions in which Chlorophyll-a (Chl-a) accumulates. The location and magnitude corresponding to such accumulation result from a complex interplay between processes such as river flushing, salinity, nutrients, grazing on phytoplankton, and the light climate in the water column. An example is the multi-annual evolution of the estuary-scale Chl-a distribution in the Scheldt estuary (Belgium/Netherlands) in spring. From 2004–2007, we observed a limited spring bloom in the brackish region (km 60–90 from the mouth, salinity ∼ 1–10 ppt). This bloom intensified in 2008–2014 and disappeared after 2015. This multi-annual evolution of Chl-a has been hypothesized to be linked to simultaneous multi-annual trends in the suspended particulate matter (SPM) distribution in summer and winter between 1995–2015 and the improvement of the water quality (e.g., reduction of ammonium), which affects grazing on phytoplankton by zooplankton. However, this hypothesis has not been systematically investigated. In this contribution, we apply a modeling approach in which observations are the core. We first analyze multi-annual in situ observations covering the full estuary. These observations include the SPM concentration, zooplankton abundance, and other variables affecting the Chl-a concentration. They show a multi-annual estuary-scale evolution not only in the SPM distribution but also in zooplankton abundance, freshwater discharge, and phytoplankon photosynthetic characteristics. Next, we apply a model approach that consists of an extensive sensitivity study and four model scenarios that are supported by these observations to constrain the processes and corresponding parameter variability that may have caused the observed change in Chl-a. Our results suggest that a change in SPM alone cannot explain the Chl-a observations. Instead, a multi-annual change in mortality rate, which we can attribute to both grazing by zooplankton and phytoplankton community (i.e., mortality dependence on salinity), may explain the multi-annual estuary-scale evolution of Chl-a in spring. Different model parameter choices may thus lead to similar model results (equifinality). Our results highlight that insight into the zooplankton dynamics and phytoplankton community characteristics is essential to understand the phytoplankton (cf. Chl-a) dynamics in the Scheldt estuary and that additional data regarding mortality and grazing rates is required to further constrain the model parameters.

Trait-based approach revealed the seasonal variation of mesozooplankton functional groups in the South Yellow Sea

Functional traits determine the fitness of organisms and mirror their ecological functions. Although trait-based approaches provide ecological insights, it is underexploited for marine zooplankton, particularly with respect to seasonal variation. Here, based on four major functional traits, including body length, feeding type, trophic group, and reproduction mode, we quantified the seasonal variations of mesozooplankton functional groups in the South Yellow Sea (SYS) in the spring, summer, and autumn of 2018. Strong seasonal dynamics were identified for all traits but patterns varied among traits. Small zooplankton (47.7–88.6%), omnivores–herbivores (81.3–97.6%), and free spawners (54.8–92.5%) dominated in three seasons, while ambush feeders and current feeders dominated in spring (45.7%), and autumn (73.4%), respectively. Cluster analysis of the functional traits showed that the mesozooplankton in the SYS can be classified into eight functional groups. The biogeographic and seasonal variations of functional groups can be partially explained by environmental drivers. Group 1, represented by omnivores–herbivores, was the most dominant functional group, the abundance of which peaked in spring and was positively correlated with chlorophyll a concentration, indicating its close association with phytoplankton dynamics. The contribution of giant, active ambush carnivores, passive ambush carnivore jellyfish, current omnivores–detritivores, and parthenogenetic cladocerans increased with sea surface temperature. The proportion of giant, active ambush carnivores and active ambush omnivore–carnivore copepods decreased with salinity in autumn. This study presents a new perspective for understanding the dynamics of zooplankton and paves the way for further research on the functional diversity of zooplankton in the SYS.

Dynamical Behaviour Changes in Response to Various Functional Responses: Temporal and Spatial Plankton System

In this paper, we focus on the comparison between ratio-dependent and Holling type-II functional response in the phytoplankton dynamics with the susceptible and infected populations with or without diffusion. The dynamics are investigated in terms of local stability using both the response function for the systems and the definition of the Hopf-bifurcation, which has been demonstrated to occur in the Holling type-II functional response using the half-saturation time (i.e. $$\alpha$$ ) as the bifurcation parameter. We observed that the system’s dynamical behaviour is affected by the response functions and the system is more stable in the case of the ratio-dependent functional response. Furthermore, the study of higher-order perturbation terms reveals the heterogeneity of in-homogeneous spatiotemporal perturbation around temporal steady state outside the linear regime. The system behaviours to both types of response functions are studied numerically in the temporal and spatiotemporal domain (i.e. pattern formation in the diffusive population). Numerical simulation is used to examine the results.

Role of environmental variables and seasonal mixing in dynamics of the phytoplankton community in a Tropical Highland Lake Ardibo, Ethiopia

This study aimed to assess the spatial and seasonal variations of the phytoplankton community in response to environmental variables in Lake Ardibo. The study was done from October 2020 to September 2021 and physicochemical parameters such as water temperature, pH, dissolved oxygen, electrical conductivity, turbidity, alkalinity, Secchi-depth, nitrate, ammonium, silicon dioxide, soluble reactive phosphorus, and total phosphorus were measured using standard methods. ANOVA results indicated that all physicochemical parameters except turbidity had significant variation (p < 0.05) in all seasons. A total of 66 phytoplankton species grouped into seven phyla, including Bacillariophyta (23 taxa), Chlorophyta (21 taxa), Cyanophyta (14 taxa), Euglenophyta (3 taxa), Charophyta (2 taxa), Dinophyta (2 taxa) and Cryptophyta (1 taxon) were identified. Phytoplankton biomass showed significant spatial and seasonal variation with maximum cell density during the pre-rainy season, and low density in the main rainy season. Redundancy analysis (RDA) revealed that nutrients had a positive affinity with the phytoplankton community, whereas electrical conductivity, water temperature, and pH showed a negative relationship with phytoplankton abundance. Temporal rather that abiotic factors far influenced phytoplankton dynamics in this deep tropical lake. The analysis postulates that partial atelomixis during the pre-rainy months favors higher phytoplankton biomass with functional groups such as desmids and heavy diatoms contributing most during this mixing period, while wet season mixing depressed algal biomass due to increased turbidity with nutrients not being limiting during these times.

Coexistence of Synechococcus and Microcystis Blooms in a Tropical Urban Reservoir and Their Links with Microbiomes.

Bacteria play a crucial role in driving ecological processes in aquatic ecosystems. Studies have shown that bacteria-cyanobacteria interactions contributed significantly to phytoplankton dynamics. However, information on the contribution of bacterial communities to blooms remains scarce. Here, we tracked changes in the bacterial community during the development of a cyanobacterial bloom in an equatorial estuarine reservoir. Two forms of blooms were observed simultaneously corresponding to the lotic and lentic characteristics of the sampling sites where significant spatial variabilities in physicochemical water quality, cyanobacterial biomass, secondary metabolites, and cyanobacterial/bacterial compositions were detected. Microcystis dominated the upstream sites during peak periods and were succeeded by Synechococcus when the bloom subsided. For the main body of the reservoir, a mixed bloom featuring coccoid and filamentous cyanobacteria (Microcystis, Synechococcus, Planktothricoides, Nodosilinea, Raphidiopsis, and Prochlorothrix) was observed. Concentrations of the picocyanobacteria Synechococcus remained high throughout the study, and their positive correlations with cylindrospermopsin and anatoxin-a suggested that they could produce cyanotoxins, which pose more damaging impacts than previously supposed. Succession of different cyanobacteria (Synechococcus and Microcystis) following changes in nutrient composition and ionic strength was demonstrated. The microbiomes associated with blooms were unique to the dominant cyanobacteria. Generic and specialized bloom biomarkers for the Microcystis and downstream mixed blooms were also identified. Microscillaceae, Chthoniobacteraceae, and Roseomonas were the major heterotrophic bacteria associated with Microcystis bloom, whereas Phycisphaeraceae and Methylacidiphilaceae were the most prominent groups for the Synechococcus bloom. Collectively, bacterial community can be greatly deviated by the geological condition, monsoon season, cyanobacterial density, and dominant cyanobacteria.

Role of nutrients and temperature in shaping distinct summer phytoplankton and microzooplankton population dynamics in the western North Pacific and Bering Sea

AbstractPhytoplankton growth and microzooplankton grazing are two critical processes in marine food webs, but they remain understudied in the vast area of the subarctic western Pacific and the Bering Sea. In this study, we measured phytoplankton growth and microzooplankton grazing rates in these less‐explored regions to demonstrate their spatial patterns and investigate underlying mechanisms driving the planktonic food web dynamics. Our results showed that the phytoplankton growth in these regions was determined by nutrient availability and temperature. In the high‐nutrient, low‐chlorophyll regions (HNLC), iron availability was the primary factor limiting phytoplankton growth. In contrast, phytoplankton growth in the Gulf of Anadyr and Kamchatka Strait was mainly limited by inorganic nitrogen exhausted by the summer blooms. We found that microzooplankton grazing rate was affected by temperature and prey availability, highlighting the positive effect of temperature. Strong top‐down control on phytoplankton by microzooplankton in the Gulf of Anadyr and Kamchatka Strait indicated an active microbial food web with high turnover rates. In contrast, the decoupling of phytoplankton growth and microzooplankton grazing in the HNLC regions illustrates a weak role of microzooplankton in the marine food web. These results indicated different food web structures in the areas with and without riverine iron input. By revealing the roles of temperature and nutrient or prey availability in regulating the spatial variability of plankton rates, we expect that the plankton will respond differently to ocean warming between the HNLC and coastal regions of the subarctic Pacific due to different nutrient conditions. Our study helps understand how marine plankton will respond to environmental changes at high latitudes.

Consistency of six in situ, in vitro and satellite-based methods to derive chlorophyll a in two optically different lakes

Phytoplankton and its most common pigment chlorophyll a (Chl-a) are important parameters in characterizing lake ecosystems. We compared six methods to measure the concentration of Chl a (CChl-a) in two optically different lakes: stratified clear-water Lake Saadjärv and non-stratified turbid Lake Võrtsjärv. CChl-a was estimated from: in vitro (spectrophotometric, high-performance liquid chromatography); fluorescence (in situ automated high-frequency measurement (AHFM) buoys) and spectral (in situ high-frequency hyperspectral above-water radiometer (WISPStation), satellites Sentinel-3 OLCI and Sentinel-2 MSI) measurements. The agreement between methods ranged from weak (R2 = 0.26) to strong (R2 = 0.93). The consistency was better in turbid lake compared to the clear-water lake where the vertical and short-term temporal variability of the CChl-a was larger. The agreement between the methods depends on multiple factors, e.g., the environmental and in-water conditions, placement of sensors, sensitivity of algorithms. Also in case of some methods, seasonal bias can be detected in both lakes due to signal strength and background turbidity. The inherent differences of the methods should be studied before the synergistic use of data which will clearly increase the spatial (via satellites), temporal (AHFM buoy, WISPStation and satellites) and vertical (profiling AHFM buoy) coverage of data necessary to advance the research on phytoplankton dynamics in lakes.

Exploring the Dynamics of Phytoplankton in Khadakwasla Reservoir through Qualitative and Quantitative Analysis

Exploring the Dynamics of Phytoplankton in Khadakwasla Reservoir through Qualitative and Quantitative Analysis

Novel insights in seasonal dynamics and co-existence patterns of phytoplankton and micro-eukaryotes in drinking water reservoir, Northwest China: DNA data and ecological model.

Although associations between phytoplankton and micro-eukaryotes have been studied in aquatic ecosystems, there are still knowledge gaps in comprehending their dynamics and interactions in drinking water reservoirs. Here, the seasonal dynamics of phytoplankton and micro-eukaryotic diversities and their co-existence patterns were studied in a drinking water reservoir, Northwest China. The highest phytoplankton diversity was observed in summer, and Chlorella sp. that belongs to Chlorophyta was the most abundant genus. The highest eukaryotic diversity was also detected in summer, and Rimostrombidium sp. that belongs to Ciliophora was the most dominant genus. Mantel test showed that the phytoplankton diversity was significantly correlated with ammonia nitrogen (r = 0.561, p = 0.001) and dissolved organic carbon (r = 0.267, p = 0.017), while the eukaryotic diversity was significantly associated with ammonia nitrogen (r = 0.265, p = 0.034) and temperature (r = 0.208, p = 0.046). PLS-PM (Partial Least Squares Path Modeling) further revealed that nutrients (P < 0.01) significantly affected the phytoplankton diversity, while nutrients (P < 0.01) and temperature (P < 0.01) significantly influenced the eukaryotic diversity. Co-occurrence network displayed the primarily positive interactions (77.66% positive and 22.34% negative) between phytoplankton and micro-eukaryotes. These findings could deepen our understanding of interactions between phytoplankton and micro-eukaryotes and their driving factors under changing aquatic environments of drinking water reservoirs.

Determinantes locais e regionais da comunidade fitoplanctônica em barragens de água do bioma Cerrado

Abstract Aim Based on a study comprising water reservoirs within the Brazilian Cerrado biome, we seek to answer the following question: how does phytoplankton communities respond to environmental, landscape, and spatial predictors? We expected local predictors to be the main factors structuring the communities. Since phytoplankton has high dispersal capacity, the geographical distance would be of minor importance. Methods: We collected phytoplankton samples from 40 water reservoirs in the rainy season and 37 reservoirs in the dry season. We performed a partial Redundancy Analysis (pRDA) to evaluate the factors influencing the variation in the composition of phytoplankton communities. Results We found that spatially structured environmental factors were controlling phytoplankton communities at the rainy season, whereas landscape was the main predictor in the dry season. On the other hand, phytoplankton morphofunctional groups were influenced only by local predictors. Conclusions We demonstrated that phytoplankton dynamics differs between rainy and dry seasons, and that distinct predictors affect phytoplankton communities over seasons.

Coupled effects of environmental conditions on the spatio-temporal variability of phytoplankton in canyon-shaped reservoirs

Algal blooms are increasingly frequently reported in reservoirs, posing a serious threat to the water environment and operation status. The phytoplankton that causes blooms is affected by environmental conditions including light-heat, water quality and hydrodynamics. Exploring the environmental coupling effects (including hydrodynamic effects) of phytoplankton is critical for reservoir management, but such studies are still scarce. This study monitored the phytoplankton and environmental factor data of Zipingpu Reservoir for 29 months and constructed a novel partial least squares structural equation modeling to quantify the impacts of environmental conditions on the phytoplankton in the canyon-shaped reservoir. There were significant spatial differences in the biomass of phytoplankton in the reservoir, and the biomass reached its peak in May to July every year. The model explained 51.4% of the spatiotemporal variation in phytoplankton and revealed that the coupling effect of flow and nutrition affected the transparency (with a coefficient of −0.427, p < 0.01) and then influence the biomass of phytoplankton. The coupling effect of flow and meteorology indirectly modified phytoplankton biomass by changing physicochemical properties (with a coefficient of 0.261, p < 0.01). Meteorology indirectly affected stratification by changing the physicochemical properties of the water and promoted temporal variation in phytoplankton biomass. The contribution rates of hydrodynamic conditions, including operation, flow and stratification variables, to phytoplankton dynamics were extremely high, reaching 34.9%. The flow change caused by reservoir operation will significantly affect phytoplankton (with a coefficient of 0.352, p < 0.01), especially when the temperature is appropriate, and a hydrodynamic operation strategy aiming to avoid rapid increases in the water level (more than 0.8 m d−1) in the reservoir may be effective in restraining blooms. This study not only further clarifies the coupling effects of environmental conditions on phytoplankton, but also provided important information to support sustainable blooms prevention and control decisions by reservoir managers.

Dynamics of phytoplankton in the coastal waters at Vladivostok in 2019–2021

Structure and abundance of phytoplankton community in the Sportivnaya Harbour and Paris Bay in Vladivostok (western coast of the Japan Sea) was monitored from October 2019 to December 2021. In total, 130 and 144 phytoplankton taxa were identified in these two areas, respectively. The overall cell abundance ranged from 1.3 · 103 to 19 · 106 cells/L (on average 21 · 104 and 84.5 · 104 cells/L); the total phytoplankton biomass — from 3.0 mg/m 3 to 38.5 g/m 3 (on average 0.8 and 2.6 g/m 3 , respectively, by areas). The long-term observations were made for the first time in the Sportivnaya Harbour. The community composition was typical of eutrophic waters, with usual seasonal succession in the Paris Bay but frequent blooms in the Sportivnaya Harbour, when diatoms were replaced by flagellates and filamentous cyanobacteria. Such dynamics is presumably caused by anthropogenic eutrophication due to uncontrolled wastewater discharge.

Phytoplankton and seston fatty acid dynamics in the northern Bering-Chukchi Sea region

Arctic and subarctic ecosystems are transitioning due to ocean warming, resulting in conditions that will lead to shifts in phytoplankton communities, their nutritional compositions, and production of fatty acids (FAs). FA biomarkers are useful indicators of changing phytoplankton community composition and provide insight into basal resource quality for higher trophic level consumers such as zooplankton, fish, birds and marine mammals, yet phytoplankton FA information is largely lacking from the Bering and Chukchi Sea regions. Therefore, we analyzed suspended particulate matter (seston) FAs, chlorophyll-a (Chl-a) and environmental data collected from four surveys in the northern Bering and Chukchi Seas, two during June of 2017 and 2018 and two during August and September 2017 and 2019. Our objectives were to determine 1) whether seston FA composition was correlated with phytoplankton taxonomic composition analyzed using imaging microscope (FlowCAM) techniques, 2) if there were seasonal differences in seston FA concentrations, and 3) how FA concentrations varied with environmental variables. We found significant seasonal differences in seston FA compositions, with diatom biomarkers more prevalent in spring, followed by a community shift to dinoflagellate and small flagellate FA biomarkers in late summer. These results were confirmed by FlowCAM analyses. FA biomarkers were correlated with total and large size-fractioned Chl-a concentrations, nitrogen concentration and temperature. Lastly, we used a model framework to predict availability of the diatom-associated essential FA, eicosapentaenoic acid (EPA, 20:5n-3). Our analysis provides new information on phytoplankton FA dynamics and the important nutritional role of phytoplankton for higher trophic level consumers in the northern Bering and Chukchi Sea regions.