Phytoplankton Population Dynamics Research Articles

Seasonal dynamics and diversity of Antarctic marine viruses reveal a novel viral seascape

The Southern Ocean microbial ecosystem, with its pronounced seasonal shifts, is vulnerable to the impacts of climate change. Since viruses are key modulators of microbial abundance, diversity, and evolution, we need a better understanding of the effects of seasonality on the viruses in this region. Our comprehensive exploration of DNA viral diversity in the Southern Ocean reveals a unique and largely uncharted viral landscape, of which 75% was previously unidentified in other oceanic areas. We uncover novel viral taxa at high taxonomic ranks, expanding our understanding of crassphage, polinton-like virus, and virophage diversity. Nucleocytoviricota viruses represent an abundant and diverse group of Antarctic viruses, highlighting their potential as important regulators of phytoplankton population dynamics. Our temporal analysis reveals complex seasonal patterns in marine viral communities (bacteriophages, eukaryotic viruses) which underscores the apparent interactions with their microbial hosts, whilst deepening our understanding of their roles in the world’s most sensitive and rapidly changing ecosystem.

Structure and Dynamics of Phytoplankton Populations in the Black Sea from 2014 to 2017

This study investigated the seasonal variations in phytoplankton communities along the Turkish Black Sea coast (2014-2017). Analyzing data from 20 stations revealed high biodiversity (175 species across 14 classes). Phytoplankton abundance showed distinct seasonality, with a peak in summer (2017, 96.6%) and lows in winter, characterized by dinoflagellate dominance. In terms of biomass, diatoms dominated in half of the sampling seasons, while dinoflagellates dominated in the other half at the surface during the study period. The dominance of dinoflagellates corresponded to the winters and summers of 2015 and 2016. The winter conditions of 2015 were harsh. The surface water community composition sometimes varied from that of the water column. Importantly, 44 potentially toxic species were identified, comprising 25% of the community and significantly contributing to both abundance (73.2-98.6%) and biomass (64-90.2%) throughout the year. These results highlight the unique structure of the Black Sea phytoplankton community, characterized by seasonal dominance of diatoms and a significant presence of potentially toxic species. Season, year, and water depth significantly influenced the phytoplankton assemblages. Water temperature was negatively correlated with dissolved oxygen and nitrogen-based nutrients.

QPCR-based phytoplankton abundance and chlorophyll a: A multi-year study in twelve large freshwater rivers across the United States

Phytoplankton overgrowth, which characterizes the eutrophication or trophic status of surface water bodies, threatens ecosystems and public health. Quantitative polymerase chain reaction (qPCR) is promising for assessing the abundance and community composition of phytoplankton. However, applications of qPCR to indicate eutrophication and trophic status, especially in lotic systems, have yet to be comprehensively evaluated. For the first time, this study correlates qPCR-based phytoplankton abundance with chlorophyll a (the most widely used indicator of eutrophication and trophic status) in multiple freshwater rivers. From early summer to late fall in 2017, 2018, and 2019, we evaluated phytoplankton, chlorophyll a, pheophytin a, and the Trophic Level Index (TLI) in twelve large freshwater rivers in three regions (western, midcontinent, and eastern) in the United States. qPCR-based phytoplankton abundance had positive allometric correlations with chlorophyll a concentration (adjusted R2 = 0.5437, p-value < 0.001), pheophytin a concentration (adjusted R2 = 0.3378, p-value <0.001), and TLI (adjusted R2 = 0.4789, p-value < 0.001). Thus, a greater phytoplankton abundance suggests a higher trophic status. This work also presents the numerical values of qPCR-based phytoplankton abundance defining the boundaries among trophic statuses (e.g., oligotrophic, mesotrophic, and eutrophic) of freshwater rivers. The sampling sites in the midcontinent rivers were more eutrophic because they had significantly higher chlorophyll a concentrations, pheophytin a concentrations, and TLI values than the sites in the western and eastern rivers. The higher phytoplankton abundance at the midcontinent sites confirmed their higher trophic status. By linking qPCR-based phytoplankton abundance to chlorophyll a, this study demonstrates that qPCR is a promising avenue to investigate the population dynamics of phytoplankton and the trophic status (or eutrophication) of freshwater rivers.

Aquaculture Ponds Identification Based on Multi-Feature Combination Strategy and Machine Learning from Landsat-5/8 in a Typical Inland Lake of China

Inland aquaculture ponds, as an important land use type, have brought great economic benefits to local people but at the same time have caused many environmental problems threatening regional ecology security. Therefore, understanding the spatiotemporal pattern of aquaculture ponds and its potential influence on water quality is vital for the sustainable development of inland lakes. In this study, based on Landsat5/8 images, three types of land features, namely spectral features, index features, and texture features, and five machine learning algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), artificial neural network (ANN), k-nearest neighbor (KNN), and Gaussian naive Bayes (GNB), were combined to identify aquaculture ponds and some other primary land use types around a typical inland lake of China. The results demonstrated that the XGBoost algorithm that integrated the three features performed the best among all groups of the five machine learning algorithms and the three features, with an overall accuracy of up to 96.15%. In particular, the texture features provided additional useful information besides the spectral features to allow more accurately separation of aquaculture ponds from other land use types and thus improve the land use mapping ability in complex inland lakes. Next, this study examined the tendency of aquaculture ponds and found a segmented increase mode, namely sharp increase during 1984–2003 and then slow elevation since 2003. Further positive correlation detected between the area of aquaculture ponds and the phytoplankton population dynamics suggest a likely influence of aquaculture activity on the lake water quality. This study provides an important scientific basis for the sustainable management and ecological protection of inland lakes.

Local intraspecific aggregation in phytoplankton model communities: spatial scales of occurrence and implications for coexistence.

The coexistence of multiple phytoplankton species despite their reliance on similar resources is often explained with mean-field models assuming mixed populations. In reality, observations of phytoplankton indicate spatial aggregation at all scales, including at the scale of a few individuals. Local spatial aggregation can hinder competitive exclusion since individuals then interact mostly with other individuals of their own species, rather than competitors from different species. To evaluate how microscale spatial aggregation might explain phytoplankton diversity maintenance, an individual-based, multispecies representation of cells in a hydrodynamic environment is required. We formulate a three-dimensional and multispecies individual-based model of phytoplankton population dynamics at the Kolmogorov scale. The model is studied through both simulations and the derivation of spatial moment equations, in connection with point process theory. The spatial moment equations show a good match between theory and simulations. We parameterized the model based on phytoplankters' ecological and physical characteristics, for both large and small phytoplankton. Defining a zone of potential interactions as the overlap between nutrient depletion volumes, we show that local species composition-within the range of possible interactions-depends on the size class of phytoplankton. In small phytoplankton, individuals remain in mostly monospecific clusters. Spatial structure therefore favours intra- over inter-specific interactions for small phytoplankton, contributing to coexistence. Large phytoplankton cell neighbourhoods appear more mixed. Although some small-scale self-organizing spatial structure remains and could influence coexistence mechanisms, other factors may need to be explored to explain diversity maintenance in large phytoplankton.

Use of mesocosm and field studies to assess the effects of nutrient levels on phytoplankton population dynamics in Korean coastal waters

We integrated data from field observations during April and March with data from a 2-week mesocosm experiment to investigate changes in phytoplankton populations in southern Korean coastal waters (KCWs) following nutrient enrichment during early spring of 2021. The mesocosm experiments used 1000 L cylindrical plastic containers that had natural seawater (control), a low nutrient (LN) treatment, or a high nutrient (HN) treatment. The field observations showed that increased freshwater runoff following spring rainfall led to elevated levels of dissolved inorganic nitrogen and silicate and a significant increase in total phytoplankton abundance. In March, nutrient enrichment from water mixing and terrestrial runoff led to dominance of cryptophyte Cryptomonas spp. In April, higher nutrient levels than March (p&amp;lt; 0.05) resulting from increased terrestrial runoff after rainfall and dominant species were Skeletonema spp., and Cryptomonas spp. In the mesocosm experiment, a succession from E. zodiacus initially to Chaetoceros spp. in the middle stage, and then to Cylindrotheca closterium and Pseudo-nitzschia spp. finally was observed, depending on the species-specific nutrient availability after nutrient addition. In principal component analysis, the negative correlation between C. closterium and nutrient levels supports their nutrient availability, which is an adaptation to low-nutrient conditions. The combined data from the field observations and mesocosm experiments indicated that nutrient supplementation from terrestrial runoff and tidal mixing played a crucial role in determining the dynamics of phytoplankton populations during early spring in the KCWs.

Stability and Hopf Bifurcation Analysis of a Phytoplankton-Zooplankton Model Under Temperature Factor and Stage-Structure Population of Phytoplankton

In the paper, we built a predator-prey model to simulate and study the dynamics of zooplankton and phytoplankton populations under the temperature impact, in which the stage structure is considered in the zooplankton population. Our model is an ordinary differential system of three nonlinear equations with some parameters as temperature-dependent functions and uses the generalized Holling response function. The non-negative and boundedness of the model solutions have been proven. The behaviors of our system are shown by the local stability conditions of the equilibria, especially the co-existence case. The stage transformation of zooplankton was studied through the Hopf bifurcation results of varying the temperature. The analysis and simulation results indicate that the ideal temperature for the co-existence is about 12-21 degrees Celsius. The zooplankton's transformation decreases when the temperature increases, leading to an imbalance in the system. Besides that, we also provided simulation figures to illustrate the found theoretical results.

Seasonal Dynamics of Phytoplankton Population of Ramadugu Lake in Nizamabad District Telangana, India

Phytoplanktons are one of the smallest and the most plentiful organisms ranging from unicellular to multicellular forms. These organisms play a vital role in aquatic ecosystems. Algae being photoautotrophs take part in photosynthesis process, they form the food base for other organisms living in lakes, reservoirs, ponds, streams and oceans. Lakes are very important water resources which are used in daily life for several purposes. Majority of fresh water lakes showed distinct seasonal variation in phytoplankton abundance. The primary objective of this paper is to highlight the current status and to provide a quantitative record of the seasonal changes of phytoplankton and to examine their distribution and diversity in relation to environmental gradients of the Ramadugu lake which is located in Ramadugu village of Nizamabad district, Telangana. The present work was carried out to identify the fresh water algal flora and its diversity for a period of one year from January 2018 to December 2019 in different seasons. Water samples were collected seasonally over three seasons – March to June(summer), July to october(Monsoon) and November to February(winter) from selected four sampling stations of lake. The algal forms were identified by using various keys. Mainly four major algal groups were identified in Ramadugu lake throughout the study period. They are Chlorophyceae, Bacillariophyceae, Cyanophyceae and Euglenophyceae. Seasonal variations were observed in the presence and density of various algae. The density of diatoms are high in winter season indicates that lake water is unpolluted and good to support life. The lake water is used for irrigation and pisciculture but not suitable for drinking purpose.

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.

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.

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.

Phytoplankton Population Dynamics in Relation to Environmental Variables at Paradip Port, East Coast of India

Phytoplankton Population Dynamics in Relation to Environmental Variables at Paradip Port, East Coast of India

Impacts of a changing environment on a stoichiometric producer-grazer system: a stochastic modelling approach

Internal and external factors on a producer-grazer system are important because these systems underpin many food chains and changes in them are therefore significant for many animal species. In particular, alterations between phytoplankton and zooplankton are important because they represent a vast source of nutriments for aquatic species. However, the impacts of different intrinsic and extrinsic noise on phytoplankton and zooplankton population dynamics are still missing. By applying stochastic methods to a popular stoichiometric model, the influence of internal and external factors on the system are explored, culminating with a proposition of how noise in the system can be used to examine the latitudinal spatial distribution of phytoplankton. This is achieved by expanding the stoichiometric model to account for macro environmental factors that induce noise in the system. First, the population dynamics under the influence of factors, such as predation, wind gusts and temperature, are individually documented in the paper. Thereafter, using the macro environmental factors such as climate change, stochastic simulations generate a spatial distribution in a latitudinal sense of phytoplankton where it is observed that the phytoplankton clusters are blooming at a higher than expected latitude. Therefore, the latitudinal distribution of phytoplankton of these clusters gives further evidence of the influence of arctic amplification.

Energy Transformation Through Primary Productivity and Nutrient Dynamics of Lentic Water

Some societies can cope, at least temporarily, with pollution and availability constraints. In most of the world, however, population increases continue without significant reduction rates. Growth will continue to impose increasing demands upon freshwater supplies. Control and reversal of degradation requires a proper economic and social valuation of fresh water. Human impact on freshwater ecosystems will increase until industrial growth is stabilized.&#x0D; Emotionalism and alarmist reactions to the momentum of exploitation by the technological system accomplish little. Understanding the metabolic responses of aquatic ecosystems is essential in order to confront and offset the effects of human alterations. Many small ponds in different parts of the world have been drained or reclaimed to extend arable land. This has caused unusual fluctuations in water land, the impact of which is tremendous. The biodiversity and dynamics of different phytoplankton population are one of the least explored areas in aquatic biology.&#x0D; Ecological studies give humans a deep insight into principles of life, its forms and levels of existence. F.A forel may be considered as the founder of modern limnology for his original work on Swiss Lakes. The primary social need of every sustainable society is to protect and utilize all their natural resources wisely.&#x0D; In India, such studies on the pattern of energy flow in aquatic ecosystem by various organisms at different trophic levels are very few. Odum suggested to bring out a comparative picture by investigating the physical, chemical and biological characteristic of lentic water bodies. It is clear that no detailed bioecological investigations have been done so far in this area.

A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series.

The rates of cell growth, division, and carbon loss of microbial populations are key parameters for understanding how organisms interact with their environment and how they contribute to the carbon cycle. However, the invasive nature of current analytical methods has hindered efforts to reliably quantify these parameters. In recent years, size-structured matrix population models (MPMs) have gained popularity for estimating division rates of microbial populations by mechanistically describing changes in microbial cell size distributions over time. Motivated by the mechanistic structure of these models, we employ a Bayesian approach to extend size-structured MPMs to capture additional biological processes describing the dynamics of a marine phytoplankton population over the day-night cycle. Our Bayesian framework is able to take prior scientific knowledge into account and generate biologically interpretable results. Using data from an exponentially growing laboratory culture of the cyanobacterium Prochlorococcus, we isolate respiratory and exudative carbon losses as critical parameters for the modeling of their population dynamics. The results suggest that this modeling framework can provide deeper insights into microbial population dynamics provided by size distribution time-series data.

Mathematical modeling and analysis of Phytoplankton–Zooplankton–Nanoparticle dynamics

In this paper, we investigate the population dynamics of phytoplankton–zooplankton–nanoparticle model with diffusion and density dependent death rate of predator. The functional response of predator in this model is considered as Beddington–DeAngelis type. The stability analysis of the equilibrium points is observed by applying the Routh–Hurwitz criterion. Numerical simulations are given to illustrate the theoretical results.

Relationship of Spatial Phytoplankton Variability during Spring with Eutrophic Inshore and Oligotrophic Offshore Waters in the East Sea, Including Dokdo, Korea

The area near the subpolar front of the East Sea has high primary productivity during the spring season. We conducted two surveys, one in early spring and another in late spring, to assess environmental factors that influence phytoplankton community structure during these times. During early spring, vertical mixing supplied abundant nutrients to the surface. Due to the well-mixed water column, there were high nutrient levels, but total phytoplankton abundances and diversity were relatively low and were dominated by the diatom Chaetoceros spp. During late spring, the water column gradually stratified, with relatively high levels of nutrients in the surface layers near the coastal areas. Phytoplankton abundance and diversity at that time were higher, and there were diatoms (Pseudo-nitzschia spp. and Chaetoceros spp.), cryptophytes, and small flagellates. Pseudo-nitzschia spp. were especially abundant in re-sampled areas. The presence of a stratified and stable water mass and sufficient nitrate led to high phytoplankton growth, even in the open sea during late spring. These findings provide a better understanding of how phytoplankton population dynamics in the East Sea depend on water column stability during both early and late spring seasons.

Biophysical controls on seasonal changes in the structure, growth, and grazing of the size-fractionated phytoplankton community in the northern South China Sea

Abstract. The size-fractionated phytoplankton growth and microzooplankton grazing are crucial for the temporal change of community size structure, regulating not only trophic transfer but also the carbon cycle of the ocean. However, the size-dependent growth and grazing dynamics on a monthly or an annual basis are less addressed in the coastal ocean. In this paper, the seasonal responses of the size-fractionated phytoplankton growth and grazing to environmental change were examined over 1 year at a coastal site of the northern South China Sea. We found a nanophytoplankton-dominated community with strong seasonal variations in all size classes. Phytoplankton community growth rate was positively correlated to nutrients, with community grazing rate correlating to the total chlorophyll a at the station, reflecting a combined bottom-up and top-down effect on phytoplankton population dynamics. Further analyses suggested that the specific growth rate of microphytoplankton was significantly influenced by phosphate, and that of nanophytoplankton was influenced by light, although picophytoplankton growth was controlled by both nitrate and temperature. In addition, the specific grazing rate of nanophytoplankton was well correlated to phytoplankton standing stock, while that of micro- and pico-compartments was negatively influenced by ciliate abundance and salinity. Finally, a lower grazing impact for micro-cells (38 %) than nano- and pico-cells (72 % and 60 %, respectively) may support size-selective grazing of microzooplankton on small cells at this eutrophic system.

Mathematical Modeling of the Phytoplankton Populations Geographic Dynamics for Possible Scenarios of Changes in the Azov Sea Hydrological Regime

Increased influence of abiotic and anthropogenic factors on the ecological state of coastal systems leads to uncontrollable changes in the overall ecosystem. This paper considers the crucial problem of studying the effect of an increase in the water’s salinity in the Azov Sea and the Taganrog Bay on hydrobiological processes. The main aim of the research is the diagnostic and predictive modeling of the geographic dynamics of the general phytoplankton populations. A mathematical model that describes the dynamics of three types of phytoplankton is proposed, considering the influence of salinity and nutrients on algae development. Discretization is carried out based on a linear combination of Upwind Leapfrog difference schemes and a central difference scheme, which makes it possible to increase the accuracy of solving the biological kinetics problem at large values of the grid Péclet number (Peh &gt; 2). A software package has been developed that implements interrelated models of hydrodynamics and biogeochemical cycles. A modified alternating-triangular method was used to solve large-dimensional systems of linear algebraic equations (SLAE). Based on the scenario approach, several numerical experiments were carried out to simulate the dynamics of the main species of phytoplankton populations at different levels of water salinity in coastal systems. It is shown that with an increase in the salinity of waters, the habitats of phytoplankton populations shift, and marine species invasively replace freshwater species of algae.

Linking population dynamics models with empirically derived models through phytoplankton primary production.

There are alternative methods for estimation of phytoplankton primary production (PP) that are fundamentally different in the calculation approach. The process‐oriented PP model is a mechanistic, empirically derived method based on the photosynthesis–light relationships. The population dynamics‐based PP calculation, which is a synthetic method, provides a production estimate based on population dynamics of phytoplankton. These alternative methods were here compared with regard to production estimates and linked to enhance the performance of the existing models of population dynamics applied to a wide variety of lakes worldwide in terms of morphometry, nutrient status, and light environments. Estimates of PP were shown to be sensitive to changes in phytoplankton sinking and zooplankton grazing rates in both methods. Production estimates in the process‐oriented PP model were also sensitive to light‐associated parameters such as day length. Although the production estimated from the population dynamics‐based PP calculation tended to be lower than that from the process‐oriented PP model irrespective of lake morphometry, production estimates calculated from both methods with standard parameterization were comparable when production was estimated on an annual timescale. However, it was also shown that the alternative methods could produce different production estimates when estimated on shorter timescales such as cyanobacterial blooms in summer. Cyanobacteria with low mortality due to grazing and sinking losses have been considered as trophic bottlenecks, but there is increasing evidence that their mortality is, to a considerable extent, due to parasitic pathogens. In the case of cyanobacterial blooms, an addition of parasite‐related loss term (19%–33% of standing stock) resulted in a resolution of the difference in production estimates between the methods. These analyses theoretically support the critical role of parasitism and resolve the bottleneck problem in aquatic ecosystem metabolism.