Planktonic Populations Research Articles

Colloidal Structure Dictates Antimicrobial Efficacy in LL-37 Self-Assemblies With Glycerol Monooleate.

The antimicrobial peptide LL-37 is a promising alternative to conventional antibiotics to combat bacteria in suspension and biofilms. Its self-assembly with polar lipids is suggested to improve its potential for therapeutic applications with higher stability against degradation and bioavailability. This study investigates the self-assembly of LL-37 with glyceryl monooleate (GMO), establishing the link between colloidal structure and antimicrobial activity. Small-angle X-ray scattering, dynamic light scattering and cryogenic transmission electron microscopy show structural transformation from dispersions of inverse bicontinuous structure (cubosomes) to multilamellar vesicles and direct rod-like mixed-micelles upon increasing the content of LL-37 in GMO. In vitro assays against planktonic and biofilm cells demonstrate that 128 µg mL-1 of GMO cubosomes have no impact on Pseudomonas aeruginosa. Still, the cubosomes reduce the Staphylococcus aureus planktonic population by ≈ 1-log after 24 h. Cylindrical micelles formed at LL-37/GMO 9/1 and 8/2 with 128 µg mL-1 LL-37 decrease the Pseudomonas aeruginosa population by 6-log. This activity is gradually abolished when LL-37 is encapsulated in vesicles or cubosomes. They also demonstrate low antibiofilm efficacy and promote the biomass of Staphylococcus aureus biofilms. These results highlight the importance of colloidal structure for therapeutic outcomes, providing insights for advanced lipid nanocarrier designs.

Early warning indicators of decadal shifts in the planktonic assemblage of the Cabo Frio upwelling ecosystem

Long-term monitoring of coupled environmental and biological components in upwelling ecosystems is critical for early warning under the global warming context. Temperature, salinity, nutrients, and plankton populations are promising indicators of the ecosystem state that help us to address the current status of the oceans and construct better predictions for the future. The Cabo Frio Upwelling System (CFUS) is a regionally productive wind-driven coastal upwelling ecosystem on the northern boundary of the South Brazilian Shelf sustaining diverse marine life including large stocks of fish and squid. Like other cold marine ecosystems, most of its functioning is likely threatened by ocean warming which emphasizes the need for ecological indicators. This study aimed to analyze the causal relationships between the temporal changes in the physical and chemical properties and the dominant planktonic communities leveraging long-term observations (20 years). The results suggested a link between the temporal changes in the ecosystem conditions and the composition of the plankton assemblage, notably an increasing proportion of dinoflagellates relative to diatoms and cladocerans relative to copepods. This increase in the proportional abundance of dinoflagellates and cladocerans over time suggests a regime shift in the plankton assemblages during the 2000s, highlighting some large phytoplankton and zooplankton groups as early indicators of productivity shifts in upwelling ecosystems.

Analytical and Numerical Study of the Problem of the Plankton Population Dynamics in the Presence of Microplastics

Analytical and Numerical Study of the Problem of the Plankton Population Dynamics in the Presence of Microplastics

Antibacterial and Antibiofilm Effects of L-Carnitine-Fumarate on Oral Streptococcal Strains Streptococcus mutans and Streptococcus sobrinus.

Streptococcus mutans is a major pathogenic habitant of oral caries. Owing to its physiological and biochemical features, it prevails in the form of plaque biofilm together with another important mutans streptococci species, Streptococcus sobrinus. Both species are considered as initiators of cavity lesions, and biofilm is essential to the dental caries process. Compared with the planktonic populations, the biofilm form has higher resistance to environmental conditions and antibiotics. Dental plaques also secure the long-term survival of microorganisms and protection from any stress conditions. To address the need for new antibiofilm agents, we have focused on L-carnitine-fumarate, a fumarate-conjugated quaternary ammonium compound. Using the macro-broth susceptibility testing method, we established its MIC value as 6.0 mg/mL. The MBC value, determined from the broth dilution minimum inhibitory concentration test by sub-culturing it to BHI agar plates, was established as 7.0 mg/mL. Antibiofilm efficacy was tested in 96-well plates coated with saliva using BHI broth supplemented with 1% sucrose as a standard approach. The obtained results allowed us to assess the MIBC as 7.5 mg/mL and the MBBC value as 10.0 mg/mL. The latter concentration also caused approximately 20% eradication of pre-existing biofilm. EPS-rich matrix, forming the core of the biofilm and enabling a confined acidic microenvironment, was also examined and confirmed the effectiveness of 10.0 mg/mL L-carnitine-fumarate concentration in inhibiting EPS formation. Furthermore, the anti-adherent and anti-aciduric impacts of L-carnitine-fumarate were investigated and revealed significant inhibitory effects at sub-MIC concentrations. The influence of L-carnitine-fumarate on the phosphotransferase system was investigated as well. Our results provide a new insight into the antibacterial potential of L-carnitine-fumarate as a valuable compound to be considered for alternative or adjunct anti-caries and antibiofilm preventive approaches.

The combined effect of pH and NaCl on the susceptibility of Listeria monocytogenes to rhamnolipids

The use of natural and sustainable additives, that are less aggressive to the environment, is a trend in the food industry. Rhamnolipids (RL) biosurfactants have shown potential for controlling food pathogens however, due to the presence of free carboxyl groups, the pH and ionic strength may influence the properties of such surfactants. In this study, we describe the antimicrobial activity of RL under different pH values and NaCl concentrations, towards both planktonic and biofilms of Listeria monocytogenes. RL were effective at pH 5.0 and the addition of 5 % NaCl improved the bactericidal efficacy for planktonic and sessile cells. The effect of NaCl was more pronounced at pH above 6 showing a significant increase in RL antimicrobial activity. At pH 7.0 planktonic population was eradicated by RL only when salt was present whereas biofilm viability was decreased by 5 log with MBIC varying from > 2500.0 mg/L (RL) to 39.0 mg/L (RL + 5 % NaCl). Larger vesicular and lamellar RL self-assembly structures were predominant when NaCl was present, suggesting their association with the antimicrobial activity observed. The pH and ionic strength of the medium are important parameters to be considered for the development of RL-based strategies to control L. monocytogenes.

Effect of pellet-size on fish growth, feeding behaviour and natural food web in pond polyculture

In carp-tilapia pond polyculture, carps are stocked once and usually harvested each 12 to 24 months, while, tilapia is stocked and harvested each 4 to 6 months. Therefore, per carp cycle there are 3 to 6 tilapia cycles. With time, carps grow bigger while tilapia reach only 10 to 50% the mass of carps. Pellet size can offer a feeding management tool in the ponds with large carp and small tilapia. This experiment investigated whether pellet-size can steer the growth of large carps (∼ 500 g) and small tilapias (∼30 g) in polyculture ponds. Four pellet-size treatments were applied in this study, each with a different combination of small (2 mm) and large (6 mm) pellets (on weight basis): S100L0 (100% small, 0% large), S50L50 (50% small, 50% large), S25L75 (25% small, 75% large) and S0L100 (0% small, 100% large). Each treatment was applied to six replicate ponds. The experiment lasted for 8 weeks. The treatments did not alter carp production, but tilapia production was highest in S100L0 treatment ponds (P < 0.001). The fish always needed more time to consume large pellets than the small pellets. Small pellets were consumed much quicker when the portion fed was small, indicating strong competition. A similar trend was observed with large pellets but the difference in feed intake time across the treatments was smaller than with small pellets. This is because tilapia ate the majority of both small and large pellets while carps ate less pellets. Tilapia at treatment S0L100 had a lower protein and fat content and a higher ash content than at the other pellet-size treatments. Carp's body composition remain unaffected by pellet-size treatment except the ash content of rohu which was highest at S100L0 and lowest at S0L100. By volume, tilapia had a higher amount of food in the stomach in treatments S100 L0 and S50L50 than in the other treatments. In contrast, more food was found in the gut of rohu in treatments S0L100 and S25L75 than in the other treatments. Pellet-size treatments did not affect water quality and the pond food web (P > 0.05) except phytoplankton diversity which was positively influenced when feeding more large pellets. The plankton population increased with the progression of the experiment, suggesting the food web was not fully exploited. In conclusion, pellet-size proves to be a feeding management tool to steer the production of tilapia as well as of total fish biomass, but not of carp's biomass in carp-tilapia pond polyculture.

Computing the Plankton-Oxygen Dynamics Model Using Deep Neural Networks in the Context of Climate Change

This study proposes a novel approach to computing the plankton-oxygen dynamics model using deep neural networks (DNNs) within the context of climate change. By leveraging advanced computational methods, particularly deep learning algorithms, we aim to enhance our understanding of how plankton populations and oxygen concentrations interact in response to changing environmental conditions. The integration of DNNs offers several advantages, including the ability to capture complex nonlinear relationships and patterns from large datasets, making them well-suited for modeling dynamic systems such as aquatic ecosystems. By training DNNs on observational data and environmental variables, we can develop predictive models that simulate the behavior of plankton-oxygen dynamics under different climate scenarios. This research builds upon existing studies in ecological modeling and deep learning techniques to advance our knowledge of plankton-oxygen dynamics and their implications for ecosystem resilience in the face of climate change. By computationally modeling these dynamics, we can gain valuable insights into the mechanisms driving ecosystem responses to environmental stressors and inform conservation efforts and policy decisions.

Environmental health risk of brine disposal for reverse osmosis water desalination plants: A case study in Bandar Abbas city, Iran

Reverse osmosis desalination brine (RODB) is a concentrated by-product containing higher salinity and turbidity and chemicals added to the raw water. As the RODB discharge has caused many environmental concerns, this case-control study investigated the (RODB) impact on the coastal environment. Five RODB Receiving beaches and one control point were selected, 84 samples of RODB, seawater, and coastal sediments were taken then chemical, physical, and biological parameters were measured. As well as environmental risk was assessed. The seawater salinity and turbidity on the RODB-receiving beaches were higher than the control point, and the population and diversity of plankton were lower. The content of some heavy metals was higher in the sediments affected by RODB. Low to moderate degrees of heavy metal-related environmental threat was calculated. The discharge of RODB leads to changes in the coastal ecosystem quality and can be an environmental hazard, therefore, it requires serious monitoring and control programs.

Influence of Water Quality and Phytoplankton Community on the Growth of Litopenaeus vannamei in Low-Salinity Semi-Mass Circular Ponds

This study examines the dynamics of vannamei shrimp (Litopenaeus vannamei) cultivation in low salinity aquaculture systems, focusing on water quality parameters, plankton diversity, and shrimp growth rates. Vannamei shrimp are favored in aquaculture due to their disease resistance, rapid growth, and high survival rates. Key water quality parameters, including dissolved oxygen (DO), temperature, light intensity, pH, and salinity, were monitored over a 30-day period in low salinity ponds. The results showed significant fluctuations in these parameters, influencing shrimp health and growth. DO levels varied from 5.8 to 8.39 ppm in the morning and from 5.14 to 7.8 ppm in the afternoon. Water temperature ranged from 27.3°C to 32.3°C, light intensity from 3,170 to 66,300 lux, pH from 7.72 to 8.73, and salinity from 5 to 6 ppt. Plankton diversity and density, including species like Microcystis, Cyclotella, and Rhizosolenia, were also assessed, highlighting their role in the aquatic ecosystem. The specific growth rate (SGR) of the shrimp was calculated, showing a favorable growth rate of 2.32% per day. These findings indicate that maintaining stable water quality and diverse plankton populations is crucial for optimizing shrimp growth in low salinity aquaculture systems. This research provides valuable insights into the environmental conditions necessary for successful vannamei shrimp cultivation, emphasizing the importance of regular monitoring and management to ensure sustainable aquaculture

Stability analysis for the phytoplankton-zooplankton model with depletion of dissolved oxygen and strong Allee effects

The photosynthetic activity of phytoplankton in the seas is responsible for an estimated 50–80 % of the world's oxygen generation. Both phytoplankton and zooplankton require some of this synthesized oxygen for cellular respiration. This study aims to better understand how the oxygen-phytoplankton dynamics are altered due to the Allee effect in phytoplankton development, particularly when considering the time-dependent oxygen generation rate. The dynamic analysis of the model is dedicated to finding the possible equilibrium points. The analysis reveals that three equilibrium points can be obtained. The stability study demonstrates that one of the equilibrium points is always stable. The remaining equilibrium points are stable under specific conditions. We also identify bifurcations originating from these equilibrium points, including transcritical, pitchfork, and Hopf bifurcation. We derive conditions for stable limit cycles (supercritical Hopf bifurcation) and, in some cases, establish the non-existence of solutions. Numerical simulations are performed to validate our theoretical findings. Furthermore, it is noted that the Allee threshold for the phytoplankton population (k0) significantly influences the overall dynamics of the system. When k0≤0.001, the population of plankton is at risk of extinction. On the other hand, when 0.001<k0≤0.01, the population of zooplankton is at risk of extinction. When 0.01<k0≤2, the solution reaches a stable condition of coexistence. Conversely, when k0≥2.1, the solution exhibits periodic attractor behaviour.

Responses of plankton community to threshold metal concentrations of cadmium and lead in a mesocosm experiment at Bay of Bengal

Metals are essential at trace levels to aquatic organisms for the function of many physiological and biological processes. But their elevated levels are toxic to the ecosystem and even brings about shifts in the plankton population. Threshold limits such as Predicted No Effect Concentration (PNEC - 0.6 μg/l of Cd; 2.7 μg/l of Pb), Criterion Continuous Concentration (CCC - 3.0 μg/l of Cd; 4.5 μg/l of Pb) and Criterion Maximum Concentration (CMC - 23 μg/l of Cd; 130 μg/l of Pb) prescribed for Indian coastal waters were used for the study. Short-term mesocosm experiments (96 h) were conducted in coastal waters of Visakhapatnam to evaluate responses of the planktonic community on exposure to threshold concentrations of cadmium and lead for the first time. Four individual experimental bags of 2500 L capacity (Control, PNEC, CCC & CMC) were used for the deployment and ambient water samples were analysed simultaneously to evaluate the impacts of the threshold levels in the natural waters. Chaetoceros sp. were dominant group in the control system whereas, Prorocentrum sp. Ceratium sp. Tintinopsis sp. Chaetoceros sp. and Skeletonema sp. were major groups in the test bags. Throughout the experiment the phytoplankton community did not show any significant differences with increased nutrients and plankton biomass (Chl-a <8.64 mg/m3). Positive response of plankton community was observed in the experimental bags. High abundance of diatoms were observed in PNEC, CCC & CMC bags at 48 h and the abundance decreased with shift in the species at 72–96 h. The catalase activity in phytoplankton (5.99 nmol/min/ml) and the zooplankton (4.77 nmol/min/ml) showed induction after exposure to PNEC. The present mesocosm study is confirmed that short-term exposure to threshold metal concentration did not affects the phytoplankton community structure in PNEC, but CCC and CMC affects the community structure beyond 24 h. The insights from this study will serve as a baseline information and help develop environmental management tools. We believe that long-term mesocosm experiments would unravel metal detoxification mechanisms at the cellular level and metal transfer rate at higher trophic levels in real-world environment.

Temporal and Spatial Dynamics of Plankton Communities in the Lower Haora River, Tripura, India

Planktons are significant bioindicator of ecosystem functioning, knowledge of the seasonal fluctuation in the plankton population in riverine waters of Indian subcontinent is rather limited. In the present study, analysis regarding spatio-temporal variations based on different multivariate statistics and indicator value analysis is done along with analysis of community structure of plankton assemblages. A total of 46 plankton taxa out of which 38 phytoplankton and 8 zooplankton taxa have been identified based on examination of samples taken from four locations over three sampling seasons. The primary phytoplankton families that involve Chlorophyceae, Bacillariophyceae, Cyanophyceae, Euglenophyceae and Composopogonophyceae. Chlorophyceae dominated the phytoplankton population, followed by Bacillariophyceae and Cyanophyceae. The plankton abundance was recorded highest in spring, followed by winter, and the least reported in monsoon season. The high average percent contribution of Aulacoseira, Oscillatoria, and Spirogyra species is well represented through SIMPER analysis. In addition, the Shannon–Wiener index (H) was calculated to determine plankton diversity, and Pielous' Evenness index (E) was calculated to determine individual distribution within a community whereas Margalef’s Richness index showed species richness of the study area. This qualitative and quantitative study will aid future research on the occurrence of plankton as well as the more trustworthy information generation on fish diet and feeding behaviors. The condition of planktons as bioindicators would indirectly provide an estimation of the ecosystem's natural state or amount of pollution.

Survey of automatic plankton image recognition: challenges, existing solutions and future perspectives

Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of aquatic ecosystems and respond quickly to changes in the environment, therefore their monitoring is vital to follow and understand these changes. Advances in imaging technology have enabled novel possibilities to study plankton populations, but the manual classification of images is time consuming and expert-based, making such an approach unsuitable for large-scale application and urging for automatic solutions for the analysis, especially recognizing the plankton species from images. Despite the extensive research done on automatic plankton recognition, the latest cutting-edge methods have not been widely adopted for operational use. In this paper, a comprehensive survey on existing solutions for automatic plankton recognition is presented. First, we identify the most notable challenges that make the development of plankton recognition systems difficult and restrict the deployment of these systems for operational use. Then, we provide a detailed description of solutions found in plankton recognition literature. Finally, we propose a workflow to identify the specific challenges in new datasets and the recommended approaches to address them. Many important challenges remain unsolved including the following: (1) the domain shift between the datasets hindering the development of an imaging instrument independent plankton recognition system, (2) the difficulty to identify and process the images of previously unseen classes and non-plankton particles, and (3) the uncertainty in expert annotations that affects the training of the machine learning models. To build harmonized instrument and location agnostic methods for operational purposes these challenges should be addressed in future research.

Adhesion of Klebsiella oxytoca to bladder or lung epithelial cells is promoted by the presence of other opportunistic pathogens

The intestinal and respiratory tracts of healthy individuals serve as habitats for a diverse array of microorganisms, among which Klebsiella oxytoca holds significance as a causative agent in numerous community- and hospital-acquired infections, often manifesting in polymicrobial contexts. In specific circumstances, K. oxytoca, alongside other constituents of the gut microbiota, undergoes translocation to distinct physiological niches. In these new environments, it engages in close interactions with other microbial community members. As this interaction may progress to co-infection where the virulence of involved pathogens may be promoted and enhance disease severity, we investigated how K. oxytoca affects the adhesion of commonly co-isolated bacteria and vice versa during co-incubation of different biotic and abiotic surfaces. Co-incubation was beneficial for the adhesion of at least one of the two co-cultured strains. K. oxytoca enhanced the adhesion of other enterobacteria strains to polystyrene and adhered more efficiently to bladder or lung epithelial cell lines in the presence of most enterobacteria strains and S. aureus. This effect was accompanied by bacterial coaggregation mediated by carbohydrate-protein interactions occurring between bacteria. These interactions occur only in sessile, but not planktonic populations, and depend on the features of the surface. The data are of particular importance for the risk assessment of the urinary and respiratory tract infections caused by K. oxytoca, including those device-associated. In this paper, we present the first report on K. oxytoca ability to acquire increased adhesive capacities on epithelial cells through interactions with common causal agents of urinary and respiratory tract infections.

Common food preservatives impose distinct selective pressures on Salmonella Typhimurium planktonic and biofilm populations

Food preservatives are crucial in controlling microbial growth in processed foods to maintain food safety. Bacterial biofilms pose a threat in the food chain by facilitating persistence on a range of surfaces and food products. Cells in a biofilm are often highly tolerant of antimicrobials and can evolve in response to antimicrobial exposure. Little is known about the efficacy of preservatives against biofilms and their potential impact on the evolution of antimicrobial resistance. In this study we investigated how Salmonella enterica serovar Typhimurium responded to subinhibitory concentrations of four food preservatives (sodium chloride, potassium chloride, sodium nitrite or sodium lactate) when grown planktonically and in biofilms. We found that each preservative exerted a unique selective pressure on S. Typhimurium populations. There was a trade-off between biofilm formation and growth in the presence of three of the four preservatives, where prolonged preservative exposure resulted in reduced biofilm biomass and matrix production over time. All three preservatives selected for mutations in global stress response regulators rpoS and crp. There was no evidence for any selection of cross-resistance to antibiotics after preservative exposure. In conclusion, we showed that preservatives affect biofilm formation and bacterial growth in a compound specific manner. We showed trade-offs between biofilm formation and preservative tolerance, but no antibiotic cross-tolerance. This indicates that bacterial adaptation to continuous preservative exposure, is unlikely to affect food safety or contribute to antibiotic resistance.

Impact of Nuclear Pollution on the Population and Diversity of Plankton

Plankton, as a crucial component of aquatic ecosystems, plays a key role in maintaining ecological balance with its population and diversity. However, with the increase in human activities, the emission of nuclear waste, and the frequency of nuclear accidents, the issue of nuclear pollution has become increasingly severe, posing a significant threat to the living environment of plankton. The primary sources of nuclear pollution are the discharge of nuclear waste and leaks from nuclear power plant accidents. These radioactive substances dissolve in water and emit radiation, causing severe damage to the aquatic ecosystem. Plankton, such as algae and protozoa, due to their characteristics, are more susceptible to radiation. The impact of nuclear pollution on the population and diversity of plankton is evident. To protect the balance of aquatic ecosystems, it's necessary to strengthen the management and regulation of nuclear pollution, reduce the discharge of nuclear waste, and lower the risk of nuclear accidents. Also, for water bodies already affected by nuclear pollution, effective purification measures should be taken to restore the health of the aquatic ecosystem.

Optimization of an in vitro Pseudomonas aeruginosa Biofilm Model to Examine Antibiotic Pharmacodynamics at the Air-Liquid Interface

Pseudomonas aeruginosa is an important cause of lower respiratory tract infections, such as ventilator-associated bacterial pneumonia (VABP). Using inhaled antibiotics to treat VABP can achieve high drug concentrations at the infection site while minimizing systemic toxicities. Despite the theoretical advantages, clinical trials have failed to show a benefit for inhaled antibiotic therapy in treating VABP. A potential reason for this discordance is the presence of biofilm-embedded bacteria in lower respiratory tract infections. Drug selection and dosing are often based on data from bacteria grown planktonically. In the present study, an in vitro air-liquid interface pharmacokinetic/pharmacodynamic biofilm model was optimized to evaluate the activity of simulated epithelial lining fluid exposures of inhaled and intravenous doses of polymyxin B and tobramycin against two P. aeruginosa strains. Antibiotic activity was also determined against the P. aeruginosa strains grown planktonically. Our study revealed that inhaled antibiotic exposures were more active than their intravenous counterparts across biofilm and planktonic populations. Inhaled exposures of polymyxin B and tobramycin exhibited comparable activity against planktonic P. aeruginosa. Although inhaled polymyxin B exposures were initially more active against P. aeruginosa biofilms (through 6 h), tobramycin was more active by the end of the experiment (48 h). Together, these data slightly favor the use of inhaled tobramycin for VABP caused by biofilm-forming P. aeruginosa that are not resistant to either antibiotic. The optimized in vitro air-liquid interface pharmacokinetic/pharmacodynamic biofilm model may be beneficial for the development of novel anti-biofilm agents or to optimize antibiotic dosing for infections such as VABP.

Initial cyclic-di-GMP upregulation triggers sporadic cellular expansion leading to improved cellular survival.

Bacterial second messenger c-di-GMP upregulation is associated with the transition from planktonic to sessile microbial lifestyle, inhibiting cellular motility, and virulence. However, in-depth elucidation of the cellular processes resulting from c-di-GMP upregulation has not been fully explored. Here, we report the role of upregulated cellular c-di-GMP in promoting planktonic cell growth of Escherichia coli K12 and Pseudomonas aeruginosa PAO1. We found a rapid expansion of cellular growth during initial cellular c-di-GMP upregulation, resulting in a larger planktonic bacterial population. The initial increase in c-di-GMP levels promotes bacterial swarming motility during the growth phase, which is subsequently inhibited by the continuous increase of c-di-GMP, and ultimately facilitates the formation of biofilms. We demonstrated that c-di-GMP upregulation triggers key bacterial genes linked to bacterial growth, swarming motility, and biofilm formation. These genes are mainly controlled by the master regulatory genes csgD and csrA. This study provides us a glimpse of the bacterial behavior of evading potential threats through adapting lifestyle changes via c-di-GMP regulation.

Forecasting the Coastal Systems State using Mathematical Modelling Based on Satellite Images

Introduction. Coastal systems of Southern Russia are constantly exposed to biotic, abiotic and anthropogenic factors. In this regard, there is a need to develop non-stationary spatially inhomogeneous interconnected mathematical models that make it possible to reproduce various scenarios for the dynamics of biological and geochemical processes in coastal systems. There is also the problem of the practical use of mathematical modelling, namely its equipping with real input data (boundary, initial conditions, information about source functions). An operational source of field information can be data received from artificial Earth satellites. Therefore, the problem arises of identifying phytoplankton populations in images of reservoirs, which, as a rule, have a spotty structure, with low image contrast relative to the background, as well as determining the boundaries of their location.Materials and Methods. This work is based on the correct application of modern mathematical analysis methods, mathematical physics and functional analysis, the theory of difference schemes, as well as methods for solving grid equations. Biogeochemical processes are described based on convection-diffusion-reaction equations. Linearization of the constructed model is carried out on a time grid with step τ. A method for recognizing the boundaries of spotted structures is being developed based on Earth remote sensing data. A combination of methods is considered as image processing algorithms: local binary patterns (LBP) and a two-layer neural network.Results. The developed software-algorithmic tools for space image recognition are presented, based on a combination of methods — local binary patterns (LBP) and neural network technologies, focused on the subsequent input of the obtained initial conditions for the problem of phytoplankton dynamics into a mathematical model. Regarding the necessary mathematical model, a continuous linearized model has been proposed and studied, and on its basis a linearized discrete model of biogeochemical cycles in coastal systems, for which practically acceptable time step values have been established for numerical (predictive) modelling of problems of the dynamics of planktonic populations and biogeochemical cycles, including in the event of death phenomena, which makes it possible to reduce the time of operational forecasting. At the same time, for the constructed discrete model, properties that are practically significant for discrete models are guaranteed to be satisfied: stability, monotonicity and convergence of the difference scheme, which is important for reliable forecasts of adverse and dangerous phenomena.In the process of work, referring to satellite images, which make it possible to obtain the state of coastal systems with high accuracy, initial conditions are entered into the mathematical (computer) model. The model analyzes satellite image data and determines levels of “pollution”, the formation of extinction zones and other factors that may threaten nature.Discussion and Conclusion. Discussion and conclusions. Using this model, it is possible to predict possible changes in coastal ecosystems and develop strategies to protect them. The results obtained make it possible to significantly reduce the time of forecast calculations (by 20−30 %) and increase the likelihood of early detection of unfavorable and dangerous phenomena, such as intense “blooming” of the aquatic environment and the formation of extinction zones in coastal systems.

Theoretical exploration and controller design of bifurcation in a plankton population dynamical system accompanying delay

Theoretical exploration and controller design of bifurcation in a plankton population dynamical system accompanying delay