Oscillations of algal cell quota: Considering two-stage phosphate uptake kinetics.

Elucidating the mechanism of effect of phosphate (PO43-) uptake on the growth of algal cells helps understand the frequent outbreaks of algal blooms caused by eutrophication. In this study, we develop a comprehensive mathematical model that incorporates two stages of PO43- uptake and accounts for transport time delay. The model parameter values are determined by fitting experimental data of Prorocentrum donghaiense and the model is validated using experimental data of Karenia mikimotoi. The numerical results demonstrate that the model successfully captures the general characteristics of algal growth and PO43- uptake under PO43- sufficient conditions. Significantly, the experimental and mathematical findings suggest that the time delay associated with the transfer of PO43- from the surface-adsorbed PO43- (Ps) pool to the intracellular PO43- (Pi) pool may serve as a physiologically plausible mechanism leading to oscillations of algal cell quota. These results have important implications for resource managers, enabling them to predict and deepen their understanding of harmful algal blooms.

Theory of Stoichiometric Intraguild Predation: Algae, Ciliate, and Daphnia.

Consumers respond differently to external nutrient changes than producers, resulting in a mismatch in elemental composition between them and potentially having a significant impact on their interactions. To explore the responses of herbivores and omnivores to changes in elemental composition in producers, we develop a novel stoichiometric model with an intraguild predation structure. The model is validated using experimental data, and the results show that our model can well capture the growth dynamics of these three species. Theoretical and numerical analyses reveal that the model exhibits complex dynamics, including chaotic-like oscillations and multiple types of bifurcations, and undergoes long transients and regime shifts. Under moderate light intensity and phosphate concentration, these three species can coexist. However, when the light intensity is high or the phosphate concentration is low, the energy enrichment paradox occurs, leading to the extinction of ciliate and Daphnia. Furthermore, if phosphate is sufficient, the competitive effect of ciliate and Daphnia on algae will be dominant, leading to competitive exclusion. Notably, when the phosphorus-to-carbon ratio of ciliate is in a suitable range, the energy enrichment paradox can be avoided, thus promoting the coexistence of species. These findings contribute to a deeper understanding of species coexistence and biodiversity.

Threshold behavior and exponential ergodicity of an sir epidemic model: the impact of random jamming and hospital capacity.

This article uses hospital capacity to determine the treatment rate for an infectious disease. To examine the impact of random jamming and hospital capacity on the spread of the disease, we propose a stochastic SIR model with nonlinear treatment rate and degenerate diffusion. Our findings demonstrate that the disease's persistence or eradication depends on the basic reproduction number [Formula: see text]. If [Formula: see text], the disease is eradicated with a probability of 1, while [Formula: see text] results in the disease being almost surely strongly stochastically permanent. We also demonstrate that if [Formula: see text], the Markov process has a unique stationary distribution and is exponentially ergodic. Additionally, we identify a critical capacity which determines the minimum hospital capacity required.

Precipitation governing vegetation patterns in an arid or semi-arid environment.

In an arid or semi-arid environment, precipitation plays a vital role in vegetation growth. Recent researches reveal that the response of vegetation growth to precipitation has a lag effect. To explore the mechanism behind the lag phenomenon, we propose and investigate a water-vegetation model with spatiotemporal nonlocal effects. It is shown that the temporal kernel function does not affect Turing bifurcation. For better understanding the influences of lag effect and nonlocal competition on the vegetation pattern formation, we choose some special kernel functions and obtain some insightful results: (i) Time delay does not trigger the vegetation pattern formation, but can postpone the evolution of vegetation. In addition, in the absence of diffusion, time delay can induce the occurrence of stability switches, while in the presence of diffusion, spatially nonhomogeneous time-periodic solutions may emerge, but there are no stability switches; (ii) The spatial nonlocal interaction may trigger the pattern onset for small diffusion ratio of water and vegetation, and can change the number and size of isolated vegetation patches for large diffusion ratio. (iii) The interaction between time delay and spatial nonlocal competition may induce the emergence of traveling wave patterns, so that the vegetation remains periodic in space, but is oscillating in time. These results demonstrate that precipitation can significantly affect the growth and spatial distribution of vegetation.

Controlling Biological Invasions: A Stochastic Host-Generalist Parasitoid Model.

On a global scale, biological invasions are seriously destroying the stability of ecosystem, sharply decreasing biodiversity and even endangering human health and causing huge economic losses. However, there exist few effective measures controlling biological invasions. To more accurately examine the prevention and control effects of biological control on biological invasions in real environments of random fluctuations, we construct a stochastic host-generalist parasitoid model. We first establish, respectively, the sufficient conditions for the persistence and extinction of invasive hosts and generalist parasitoids, including (1) only the intrusive hosts go extinct; (2) only the generalist parasitoids are extinct, and (3) the intrusive hosts and generalist parasitoids are both extinct or persistent. Then, we perform a series of numerical simulations to verify the validity of the theoretical results obtained, based on which we further discuss the impacts of stochastic environmental fluctuations on the control of intrusive hosts, especially the possible changes of qualitative behavior caused by environmental noises in the bistable scenario. Our theoretical and numerical results indicate that compared with the invasive hosts, the generalist parasitoids are more vulnerable to environmental noises, and the prevention and control effects of biological control on invasive hosts are closely dependent to the initial population sizes. Thus, improving the ability of early detection of ecosystems, including the initial densities of biological populations and their dynamic characteristics, will provide effective predictive guidance for the prevention and control of alien host invasions.

Spatiotemporal patterns of a diffusive prey-predator model with spatial memory and pregnancy period in an intimidatory environment.

Spatial memory and predator-induced fear have recently been considered in modeling population dynamics of animals independently. This paper is the first to integrate both aspects in a prey-predator model with pregnancy cycle to investigate the direct and indirect effects of predation on the spatial distribution of prey. We extensively study Turing instability and Hopf bifurcation. When the prey population has slow memory-based diffusion, the model is easier to generate Turing patterns. While when the prey population has fast memory-based diffusion, the model can exhibit rich dynamics. Specifically, (1) for the model with spatial memory delay only, the prey population with long term memory shows a spatially nonhomogeneous periodic distribution; (2) for the model with pregnancy delay only, the prey population with long pregnancy cycles shows a spatially homogeneous (or nonhomogeneous) periodic distribution, and (3) for the model with both the two time delays, more interesting spatiotemporal dynamics can be observed for long memory delay and (or) long pregnancy cycles. Our findings indicate that both spatial memory and pregnancy cycle play significant roles in the pattern formation of prey-predator interactions.

Stochastic switches of eutrophication and oligotrophication: Modeling extreme weather via non-Gaussian Lévy noise.

Disturbances related to extreme weather events, such as hurricanes, heavy precipitation events, and droughts, are important drivers of evolution processes of a shallow lake ecosystem. A non-Gaussian α-stable Lévy process is esteemed to be the most suitable model to describe such extreme events. This paper incorporates extreme weather via α-stable Lévy noise into a parameterized lake model for phosphorus dynamics. We obtain the stationary probability density function of phosphorus concentration and examine the pivotal roles of α-stable Lévy noise on phosphorus dynamics. The switches between the oligotrophic state and the eutrophic state can be induced by the noise intensity σ, skewness parameter ß, or stability index α. We calculate the mean first passage time, also referred to as the mean switching time, from the oligotrophic state to the eutrophic state. We observe that the increased noise intensity, skewness parameter, or stability index makes the mean switching time shorter and thus accelerates the switching process and facilitates lake eutrophication. When the frequency of extreme weather events exceeds a critical value, the intensity of extreme events becomes the most key factor for promoting lake eutrophication. As an application, we analyze the available data of Lake Taihu (2014-2018) for monthly precipitation, phosphorus, and chlorophyll-a concentrations and quantify the linkage among them using the Lévy-stable distribution. This study provides a fundamental framework to uncover the impact of any extreme climate event on aquatic nutrient status.

Dynamics of a ratio-dependent population model for Green Sea Turtle with age structure.

The reproduction of the green sea turtles is characterized by the temperature dependent sex determination (TSD). Green sea turtle eggs are laid asexually. Temperature during hatching determines the sex of baby green sea turtles. In order to study the population dynamics of the green sea turtles and understand the dynamics of the sex ratio, in this paper we establish a stage-structured model by incorporating TSD and the ratio dependent Holling III functional response in the reproduction process of the green sea turtle population. The effects of incubation temperature and sex ratio deviation on persistence of the population are captured by the sole basic reproduction number. The persistent mode can be either a stable equilibrium or periodic oscillations. Numerical simulations and sensitive analysis help us to identify vital parameters in our model. Our research in the paper is in favor of elevating sexual encounter rates, reducing the searching time for males and increasing survival odds from baby state into adult in order to maintain sustainability of the green sea turtles.

Competitive Exclusion in a General Multi-species Chemostat Model with Stochastic Perturbations.

Based on the fact that the continuous culture of microorganisms in a chemostat is subject to environmental noises, we present and analyze a stochastic competition chemostat model with general monotonic response functions and differential removal rates. The existence and boundedness of the unique positive solution are first obtained. By defining a stochastic break-even concentration for every species, we prove that at most one competitor survives in the chemostat and the winner has the smallest stochastic break-even concentration, provided its response function satisfies a technical assumption. That is to say, the competitive exclusion principle holds for the stochastic competition chemostat model. Furthermore, we find that the noise experienced by one species is adverse to its growth while may be favorable for the growth of other one species. Namely, the destinies can be exchanged between two microorganism species in the chemostat due to the environmental noise.

Microrisk Lab: An Online Freeware for Predictive Microbiology.

Microrisk Lab is an R-based online modeling freeware designed to realize parameter estimation and model simulation in predictive microbiology. A total of 36 peer-reviewed models were integrated for parameter estimation (including primary models of bacterial growth/inactivation under static and nonisothermal conditions, secondary models of specific growth rate, and competition models of two-flora growth) and model simulation (including integrated models of deterministic or stochastic bacterial growth/inactivation under static and nonisothermal conditions) in Microrisk Lab. Each modeling section was designed to provide numerical and graphical results with comprehensive statistical indicators depending on the appropriate data set and/or parameter setting. In this study, six case studies were reproduced in Microrisk Lab and compared in parallel with DMFit, GInaFiT, IPMP 2013/GraphPad Prism, Bioinactivation FE, and @Risk, respectively. The estimated and simulated results demonstrated that the performance of Microrisk Lab was statistically equivalent to that of other existing modeling systems. Microrisk Lab allows for a friendly user experience when modeling microbial behaviors owing to its interactive interfaces, high integration, and interconnectivity. Users can freely access this application at https://microrisklab.shinyapps.io/english/ or https://microrisklab.shinyapps.io/chinese/.

Noise-Induced Transitions in a Nonsmooth Producer-Grazer Model with Stoichiometric Constraints.

Stoichiometric producer-grazer models are nonsmooth due to the Liebig's Law of Minimum and can generate new dynamics such as bistability for producer-grazer interactions. Environmental noises can be extremely important and change dynamical behaviors of a stoichiometric producer-grazer model. In this paper, we consider a stochastically forced producer-grazer model and study the phenomena of noise-induced state switching between two stochastic attractors in the bistable zone. Namely, there is a frequent random hopping of phase trajectories between attracting basins of the attractors. In addition, by applying the stochastic sensitivity function technique, we construct the confidence ellipse and confidence band to find the configurational arrangement of equilibria and a limit cycle, respectively.

Regulation of phosphate uptake kinetics in the bloom-forming dinoflagellates prorocentrum donghaiense with emphasis on two-stage dynamic process.

Phosphorus is an essential element for the growth and reproduction of algae. In recent years, the frequent outbreaks of algal blooms caused by eutrophication have drawn much attention to the influence of phosphate (P) uptake on the growth of algal cells. The previous study only considered the effect of total P pools on the P uptake process of algal cells and considered the process as one stage, which is insufficient. P uptake by algae is actually a two-stage kinetic process because in many algae species, surface-adsorbed P pools account for a large proportion of total P pools. In this paper, we fit one-stage and two-stage models of P uptake by algae to our experimental data on short-term uptake kinetics of algae Prorocentrum donghaiense under P-deplete and P-replete conditions at 24°C. According to the experimental results, P. donghaiense possesses different P uptake characteristics under different P concentrations. P. donghaiense grows faster and exponentially for longer periods of time under P-replete condition. Ranges of change of Qc (cell quota of intracellular P) and Sp (cell quota of surface-adsorbed P) during the culture time are obviously larger under P-replete condition than those under P-deplete condition. The value of Kp (represents the impact of P-starvation on P uptake rate) in one-stage model under P-deplete condition is smaller than that under P-replete condition, which is opposite to results of two-stage model and does not meet the actual biological significance of Kp. The two-stage model gives more reasonable and realistic explanations to the process of P uptake by algae no matter from the perspective of intuitive fitting effect, biological significance of parameters, statistical test results or essential dynamic process. These results, combined with long-term lab and field data in ocean, could be used to effectively predict algal blooms.

An edge-based SIR model for sexually transmitted diseases on the contact network.

Sexually transmitted diseases, which are infections through sexual contact, pose severe public health threat nowadays. In this paper, we develop a novel model for such diseases on a bipartite random contact network. Our model is precise with arbitrary initial conditions, which makes it suitable to study preventative vaccination strategies. We derive the reproduction number and show that R0=1 is the disease threshold. An implicit formula for the final epidemic size is also derived, and we show that the formula gives a unique positive final epidemic size when the reproduction number is larger than unity. We find that the final size in either sex is heavily influenced by the degree distribution of the opposite sex.

Host contact structure is important for the recurrence of Influenza A.

An important characteristic of influenza A is its ability to escape host immunity through antigenic drift. A novel influenza A strain that causes a pandemic confers full immunity to infected individuals. Yet when the pandemic strain drifts, these individuals will have decreased immunity to drifted strains in the following seasonal epidemics. We compute the required decrease in immunity so that a recurrence is possible. Models for influenza A must make assumptions on the contact structure on which the disease spreads. By considering local stability of the disease free equilibrium via computation of the reproduction number, we show that the classical random mixing assumption predicts an unrealistically large decrease of immunity before a recurrence is possible. We improve over the classical random mixing assumption by incorporating a contact network structure. A complication of contact networks is correlations induced by the initial pandemic. We provide a novel analytic derivation of such correlations and show that contact networks may require a dramatically smaller loss of immunity before recurrence. Hence, the key new insight in our paper is that on contact networks the establishment of a new strain is possible for much higher immunity levels of previously infected individuals than predicted by the commonly used random mixing assumption. This suggests that stable contacts like classmates, coworkers and family members are a crucial path for the spread of influenza in human populations.

The effect of media coverage on threshold dynamics for a stochastic SIS epidemic model.

Media coverage is one of the important measures for controlling infectious diseases, but the effect of media coverage on diseases spreading in a stochastic environment still needs to be further investigated. Here, we present a stochastic susceptible-infected-susceptible (SIS) epidemic model incorporating media coverage and environmental fluctuations. By using Feller's test and stochastic comparison principle, we establish the stochastic basic reproduction number R 0 s , which completely determines whether the disease is persistent or not in the population. If R 0 s ≤ 1 , the disease will go to extinction; if R 0 s = 1 , the disease will also go to extinction in probability, which has not been reported in the known literatures; and if R 0 s > 1 , the disease will be stochastically persistent. In addition, the existence of the stationary distribution of the model and its ergodicity are obtained. Numerical simulations based on real examples support the theoretical results. The interesting findings are that (i) the environmental fluctuation may significantly affect the threshold dynamical behavior of the disease and the fluctuations in different size scale population, and (ii) the media coverage plays an important role in affecting the stationary distribution of disease under a low intensity noise environment.

Disease invasion risk in a growing population.

The spread of an infectious disease may depend on the population size. For simplicity, classic epidemic models assume homogeneous mixing, usually standard incidence or mass action. For standard incidence, the contact rate between any pair of individuals is inversely proportional to the population size, and so the basic reproduction number (and thus the initial exponential growth rate of the disease) is independent of the population size. For mass action, this contact rate remains constant, predicting that the basic reproduction number increases linearly with the population size, meaning that disease invasion is easiest when the population is largest. In this paper, we show that neither of these may be true on a slowly evolving contact network: the basic reproduction number of a short epidemic can reach its maximum while the population is still growing. The basic reproduction number is proportional to the spectral radius of a contact matrix, which is shown numerically to be well approximated by the average excess degree of the contact network. We base our analysis on modeling the dynamics of the average excess degree of a random contact network with constant population input, proportional deaths, and preferential attachment for contacts brought in by incoming individuals (i.e., individuals with more contacts attract more incoming contacts). In addition, we show that our result also holds for uniform attachment of incoming contacts (i.e., every individual has the same chance of attracting incoming contacts), and much more general population dynamics. Our results show that a disease spreading in a growing population may evade control if disease control planning is based on the basic reproduction number at maximum population size.

Survival and Stationary Distribution Analysis of a Stochastic Competitive Model of Three Species in a Polluted Environment.

In this paper, we develop and study a stochastic model for the competition of three species with a generalized dose-response function in a polluted environment. We first carry out the survival analysis and obtain sufficient conditions for the extinction, non-persistence, weak persistence in the mean, strong persistence in the mean and stochastic permanence. The threshold between weak persistence in the mean and extinction is established for each species. Then, using Hasminskii's methods and a Lyapunov function, we derive sufficient conditions for the existence of stationary distribution for each population. Numerical simulations are carried out to support our theoretical results, and some biological significance is presented.

Threshold dynamics of a switching diffusion SIR model with logistic growth and healthcare resources.

In this article, we have constructed a stochastic SIR model with healthcare resources and logistic growth, aiming to explore the effect of random environment and healthcare resources on disease transmission dynamics. We have showed that under mild extra conditions, there exists a critical parameter, i.e., the basic reproduction number $ R_0/ $, which completely determines the dynamics of disease: when $ R_0/ < 1 $, the disease is eradicated; while when $ R_0/ > 1 $, the disease is persistent. To validate our theoretical findings, we conducted some numerical simulations using actual parameter values of COVID-19. Both our theoretical and simulation results indicated that (1) the white noise can significantly affect the dynamics of a disease, and importantly, it can shift the stability of the disease-free equilibrium; (2) infectious disease resurgence may be caused by random switching of the environment; and (3) it is vital to maintain adequate healthcare resources to control the spread of disease.

Bifurcation analysis in a modified Leslie-Gower predator-prey model with fear effect and multiple delays.

In this paper, we explored a modified Leslie-Gower predator-prey model incorporating a fear effect and multiple delays. We analyzed the existence and local stability of each potential equilibrium. Furthermore, we investigated the presence of periodic solutions via Hopf bifurcation bifurcated from the positive equilibrium with respect to both delays. By utilizing the normal form theory and the center manifold theorem, we investigated the direction and stability of these periodic solutions. Our theoretical findings were validated through numerical simulations, which demonstrated that the fear delay could trigger a stability shift at the positive equilibrium. Additionally, we observed that an increase in fear intensity or the presence of substitute prey reinforces the stability of the positive equilibrium.

Stability and Hopf bifurcation of an intraguild prey-predator fishery model with two delays and Michaelis-Menten type predator harvest.

In this paper, we have proposed and investigated an intraguild predator-prey system incorporating two delays and a harvesting mechanism based on the Michaelis-Menten principle, and it was assumed that the two species compete for a shared resource. Firstly, we examined the properties of the relevant characteristic equations to derive sufficient conditions for the asymptotical stability of equilibria in the delayed model and the existence of Hopf bifurcation. Using the normal form method and the central manifold theorem, we analyzed the stability and direction of periodic solutions arising from Hopf bifurcations. Our theoretical findings were subsequently validated through numerical simulations. Furthermore, we explored the impact of harvesting on the quantity of biological resources and examined the critical values associated with the two delays.