Spatial Predator-prey Models Research Articles

Double Hopf bifurcation induced by spatial memory in a diffusive predator–prey model with Allee effect and maturation delay of predator

In this paper, we delve into double Hopf bifurcation induced by memory-driven directed movement in a spatial predator–prey model with Allee effect and maturation delay of predators. We first adopt a novel technique to handle the associated characteristic equation and thus obtain the crossing curves as well as the double Hopf points. We then calculate explicit formulae of normal form regarding non-resonant double Hopf bifurcation. We thus divide the dynamics of the developed model into several categories near the double Hopf bifurcation points. Our numerical and theoretical results both demonstrate that the model can exhibit various complex phenomena when the parameters are near the double Hopf bifurcation points. For example, the transition from one stable spatially inhomogeneous periodic orbit with mode-5 to another with mode-4 and the coexistence of them can be observed.

Detection of Hopf bifurcations induced by pregnancy and maturation delays in a spatial predator–prey model via crossing curves method

We investigate the stability switches behaviors due to Hopf bifurcations triggered by maturation and pregnancy delays for a diffusive predator–prey model under the joint impacts of fear and Allee effect of predators. We firstly carry out the linear analysis of the proposed model by applying the recently developed crossing curves method to cope with the corresponding characteristic equation incorporating wave number as well as delay-dependent parameters. We then procure the Hopf bifurcation curves through which delays pass, the stability of the associated constant equilibrium can change accordingly. Thereupon, we deduce the normal form regarding Hopf bifurcation and thus clarify its properties. Finally, we present a numerical example and perform some simulations to verify the accuracy of the obtained results. It is shown that both the maturation and pregnancy periods can respectively induce stability switches.

Incorporating neurological and behavioral mechanisms of sociality into predator-prey models.

Consumer-resource population models drive progress in predicting and understanding predation. However, they are often built by averaging the foraging outcomes of individuals to estimate per capita functional responses (functions that describe predation rate). Reliance on per-capita functional responses rests on the assumption that that individuals forage independently without affecting each other. Undermining this assumption, extensive behavioral neuroscience research has made clear that facilitative and antagonistic interactions among conspecifics frequently alter foraging through interference competition and persistent neurophysiological changes. For example, repeated social defeats dysregulates rodent hypothalamic signaling, modulating appetite. In behavioral ecology, similar mechanisms are studied under the concept of dominance hierarchies. Neurological and behavioral changes in response to conspecifics undoubtedly play some sort of role in the foraging of populations, but modern predator-prey theory does not explicitly include them. Here we describe how some modern approaches to population modeling might account for this. Further, we propose that spatial predator-prey models can be modified to describe plastic changes in foraging behavior driven by intraspecific interaction, namely individuals switching between patches or plastic strategies to avoid competition. Extensive neurological and behavioral ecology research suggests that interactions among conspecifics help shape populations' functional responses. Modeling interdependent functional responses woven together by behavioral and neurological mechanisms may thus be indispensable in predicting the outcome of consumer-resource interactions across systems.

Spatiotemporal dynamics of a diffusive predator-prey system incorporating social behavior

<abstract><p>This research concerned with a new formulation of a spatial predator-prey model with Leslie-Gower and Holling type II schemes in the presence of prey social behavior. The aim interest here is to distinguish the influence of Leslie-Gower term on the spatiotemporal behavior of the model. Interesting results are obtained as Hopf bifurcation, Turing bifurcation and Turing-Hopf bifurcation. A rigorous mathematical analysis shows that the presence of Leslie-Gower can induce Turing pattern, which shows that this kind of interaction is very important in modeling different natural phenomena. The direction of Turing-Hopf bifurcation is studied with the help of the normal form. The obtained results are tested numerically.</p></abstract>

Data assimilation with agent-based models using Markov chain sampling

Every day, weather forecasting centres around the world make use of noisy, incomplete observations of the atmosphere to update their weather forecasts. This process is known as data assimilation, data fusion or state estimation and is best expressed as Bayesian inference: given a set of observations, some prior beliefs and a model of the target system, what is the probability distribution of some set of unobserved quantities or latent variables at some time, possibly in the future? While data assimilation has developed rapidly in some areas, relatively little progress has been made in performing data assimilation with agent-based models. This has hampered the use of agent-based models to make quantitative claims about real-world systems. Here we present an algorithm that uses Markov-Chain-Monte-Carlo (MCMC) methods to generate samples of the parameters and trajectories of an agent-based model over a window of time given a set of possibly noisy, aggregated and incomplete observations of the system. This can be used as-is, or as part of a data assimilation cycle or sequential-MCMC algorithm. Our algorithm is applicable to time-stepping, agent-based models whose agents have a finite set of states and a finite number of ways of acting on the world. As presented, the algorithm is only practical for agents with a few bytes of internal state although we discuss ways of removing this restriction. We demonstrate the algorithm by performing data assimilation with an agent-based, spatial predator-prey model.

Complex Dynamical Behavior of Holling–Tanner Predator-Prey Model with Cross-Diffusion

Spatial predator-prey models have been studied by researchers for many years, because the exact distributions of the population can be well illustrated via pattern formation. In this paper, amplitude equations of a spatial Holling–Tanner predator-prey model are studied via multiple scale analysis. First, by amplitude equations, we obtain the corresponding intervals in which different kinds of patterns will be onset. Additionally, we get the conclusion that pattern transitions of the predator are induced by the increasing rate of conversion into predator biomass. Specifically, pattern transitions of the predator between distinct Turing pattern structures vary in an orderly manner: from spotted patterns to stripe patterns, and finally to black-eye patterns. Moreover, it is discovered that pattern transitions of prey can be induced by cross-diffusion; that is, patterns of prey transmit from spotted patterns to stripe patterns and finally to a mixture of spot and stripe patterns. Meanwhile, it is found that both effects of cross-diffusion and interaction between the prey and predator can lead to the complicated phenomenon of dynamics in the system of biology.

SPATIAL PATTERNS DYNAMICS OF A DIFFUSIVE PREDATOR–PREY SYSTEM WITH COOPERATIVE BEHAVIOR IN PREDATORS

Cooperative behavior is an extensive mechanism in nature, and seen in several organisms, from bacterial cells to primates. In this paper, we have investigated a spatial predator–prey model with hunting cooperation in predators. Using linear stability analysis, we obtain the condition for diffusive instability and identify the corresponding domain in the space of control parameters. Using extensive numerical simulations, we obtain complex patterns, namely, spotted pattern, stripe pattern and mixed pattern in the Turing domain, by varying the hunting cooperation rate in predators and ratio of diffusion coefficient. The results focus on the effect of hunting cooperation rate in pattern dynamics of a diffusive predator–prey model and help us in better understanding of the dynamics of the predator–prey interaction in real environment.

Characterizing the existence of hydra effect in spatial predator-prey models and the influence of functional response types and species dispersal

The hydra effect in ecology corresponds to the increase in the equilibrium or time-averaged density of a population when its mortality rate is augmented. The literature presents examples of the hydra effect in continuous as well as in discrete time population models described by nonlinear systems of ordinary differential and difference equations, respectively. The novelty of this work is that we show by means of numerical simulation the occurrence of the hydra effect in some stationary dynamics of one dimensional reaction-diffusion predator-prey models described by nonlinear systems of partial differential equations with distinct nonlinear functional responses. Reaction-diffusion models are a set of mathematical models that take into account population dynamics and dispersal (diffusivity) within a predefined spatial domain. We show that for a type 2 functional response an increasing diffusivity shortens the range of the hydra effect. Another interesting result concerns the fact that, together with the hydra effect, the prey density also increases with the increase of the per capita density-independent mortality rate of the predator. This result indicates that this top-down disturbance does not necessarily create a trophic cascade in a spatial predator-prey interaction at the steady-state regime.

What are the benefits of delisting endangered species and who receives them?: Lessons from the gray wolf recovery in Greater Yellowstone

This paper uses a spatial predator-prey model to provide insights into the complex and politically charged management of species recently removed from the federal endangered species list. The model is motivated by the recently delisted gray wolf with spatiotemporal dynamics between elk, wolves, hunters, cattle ranchers, and the tourism industry in the Greater Yellowstone Ecosystem. State wildlife managers set hunting rates for elk and wolves to maximize the discounted net benefits from tourism, hunting, cattle grazing, and non-use values that accrue to the area while ensuring a minimum viable wolf population meant to prevent extinction. We show that the cost of wolf conservation paid by residents and visitors to the area falls substantially after delisting. These costs savings arise by taking advantage of differences in habitats and economies across the region resulting in an unequal spatial distribution of wolves and of wolf hunting opportunities. The cost savings from delisting are reduced when a more even distribution of wolves and hunting opportunity is achieved, highlighting a bioeconomic equity-efficiency tradeoff. Finally, we show that current livestock compensation programs cannot decrease the discrepancy between state and federal management following delisting but propose a federally-funded alternative that can.

Bifurcations in periodic integrodifference equations in <inline-formula><tex-math id="M1">\begin{document}$ C(\Omega) $\end{document}</tex-math></inline-formula> Ⅱ: Discrete torus bifurcations

We provide a convenient Neimark-Sacker bifurcation result for time-periodic difference equations in arbitrary Banach spaces. It ensures the bifurcation of invariant tori caused by a pair of complex-conjugated Floquet multipliers crossing the complex unit circle. This criterion is made explicit for integrodifference equations, which are infinite-dimensional discrete dynamical systems popular in theoretical ecology, and are used to describe the temporal evolution and spatial dispersal of populations with nonoverlapping generations. As an application, we combine analytical and numerical tools for a detailed bifurcation analysis of a spatial predator-prey model. Since such realistic models can frequently only be studied numerically, we formulate our assumptions in such a fashion as to allow for numerically stable verification.

SPATIAL ASPECT OF HUNTING COOPERATION IN PREDATORS WITH HOLLING TYPE II FUNCTIONAL RESPONSE

In this paper, we have investigated a spatial predator–prey model with hunting cooperation in predators. Using linear stability analysis, we obtain the condition for diffusive instability and identify the corresponding domain in the space of controlling parameters. Using extensive numerical simulations, we obtain complex patterns, namely, spotted pattern, stripe pattern and mixed pattern in the Turing domain, by varying the hunting cooperation parameter in predators and carrying capacity of preys. The results focus on the effect of hunting cooperation in pattern dynamics of a diffusive predator–prey model and help us in better understanding of the dynamics of the predator–prey interaction in real environments.

Pattern Dynamics in a Spatial Predator–Prey Model with Nonmonotonic Response Function

In this paper, we study a diffusive predator–prey system with the nonmonotonic response function. The conditions on Hopf bifurcation and Turing instability of spatial systems are obtained. Near the Turing bifurcation point we apply the weakly nonlinear analysis to derive the amplitude equations of stationary pattern, to investigate the selection of spatiotemporal pattern. It shows that different types of patterns will occur in the model under various conditions. Numerical simulations agree well with our theoretical analysis when control parameters are in the Turing space. This study may provide some deep insights into the formation and selection of patterns for diffusive predator–prey systems.

Spatio-temporal pattern formation in predator-prey systems with fitness taxis

We pose a spatial predator–prey model in which the movement of animals is not purely diffusive, but also contains a drift term in the direction of higher specific growth rates. We refer to this as fitness taxis. We conduct a linear stability analysis of the resulting coupled reaction–advection–diffusion equations and derive conditions under which spatial patterns form. We find that for some parameters the problem is ill posed and short waves grow with unbounded speeds. To eliminate this, we introduce spatial kernels in the model, yielding coupled integro-differential equations, and conduct a similar stability analysis for this system. Through numerical simulation, we find that a variety of patterns can emerge, including stationary spatial patterns, standing and travelling waves, and seemingly chaotic spatio-temporal patterns. We argue that fitness taxis represents a simple and generic extension of diffusive motion, is ecologically plausible, and provides an alternative mechanism for formation of patterns in spatially explicit ecosystem models, with emphasis on non-stationary spatio-temporal dynamics.

Spatial patterns and biodiversity in off-lattice simulations of a cyclic three-species Lotka-Volterra model

Stochastic simulations of cyclic three-species spatial predator-prey models are usually performed in square lattices with nearest-neighbour interactions starting from random initial conditions. In this letter we describe the results of off-lattice Lotka-Volterra stochastic simulations, showing that the emergence of spiral patterns does occur for sufficiently high values of the (conserved) total density of individuals. We also investigate the dynamics in our simulations, finding an empirical relation characterizing the dependence of the characteristic peak frequency and amplitude on the total density. Finally, we study the impact of the total density on the extinction probability, showing how a low population density may jeopardize biodiversity.

Spatial dynamics of a predator-prey system with cross diffusion

In this paper, a spatial predator-prey model with self-defense mechanism that the prey species keep themselves away from the attack of the predator, which leads the existence of the cross diffusion in biological communities, is investigated. Conditions for cross diffusion induced Turing instability are obtained by mathematical analysis. By the numerical simulations, five types of patterns such as hot/cold spots, hot/cold spots-stripes and stripes patterns emerge. Our study suggests that the interactions of self and cross diffusion have great effects on the mechanism for the emergence of complex dynamics in biological systems.

Pattern dynamics of a diffusive predator–prey model with delay effect

We study the spatiotemporal dynamics in a diffusive predator–prey system with time delay. By investigating the dynamical behavior of the system in the presence of Turing–Hopf bifurcations, we present a classification of the pattern dynamics based on the dispersion relation for the two unstable modes. More specifically, we researched the existence of the Turing pattern when control parameters lie in the Turing space. Particularly, when parameter values are taken in Turing–Hopf domain, we numerically investigate the formation of all the possible patterns, including time-dependent wave pattern, persistent short-term competing dynamics and stationary Turing pattern. Furthermore, the effect of time delay on the formation of spatial pattern has also been analyzed from the aspects of theory and numerical simulation. We speculate that the interaction of spatial and temporal instabilities in the reaction–diffusion system might bring some insight to the finding of patterns in spatial predator–prey models.

Diffusion driven instability and Hopf bifurcation in spatial predator-prey model on a circular domain

In this paper, we investigate theoretically and numerically a 2-D spatio-temporal dynamics of a predator-prey mathematical model which incorporates the Holling type II and a modified Leslie–Gower functional response and logistic growth of the prey. This system is modeled by a reaction diffusion equations defined on a disc domain {(x,y)∈R2/x2+y2<R2} with Dirichlet initial conditions and Neumann boundary conditions. We study the local and global stability of the positive equilibrium point. We show that the diffusion can induce instability of the uniform equilibrium point which is stable with respect to a constant perturbation as shown by Turing in 1950s and derive the conditions for Hopf and Turing bifurcation in the spatial domain. Numerical results are given in order to illustrate how biological processes affect spatiotemporal pattern formation in a spatial domain. We perform the computations and generalize, on a circular domain, the results presented in Camara and Aziz-Alaoui [6].

Rich dynamics in a spatial predator–prey model with delay

In this paper, we study the spatiotemporal dynamics of a diffusive Holling–Tanner predator–prey model with discrete time delay. Via analytically and numerically analysis, we unveil six types of patterns with and without time delay. Among them, of particular novel is the observation of linear pattern (consisting of a series of parallel lines), whose formation is closely related with the temporal Hopf bifurcation threshold. Moreover, we also find that larger time delay or diffusion of predator may induce the extinction of both prey and predator. Theoretical analysis and numerical simulations validate the well-known conclusion: diffusion is usually beneficial for stabilizing pattern formation, yet discrete time delay plays a destabilizing role in the generation of pattern.

Spatial dynamics in a predator-prey model with herd behavior

In this paper, a spatial predator-prey model with herd behavior in prey population and quadratic mortality in predator population is investigated. By the linear stability analysis, we obtain the condition for stationary pattern. Moreover, using standard multiple-scale analysis, we establish the amplitude equations for the excited modes, which determine the stability of amplitudes towards uniform and inhomogeneous perturbations. By numerical simulations, we find that the model exhibits complex pattern replication: spotted pattern, stripe pattern, and coexistence of the two. The results may enrich the pattern dynamics in predator-prey models and help us to better understand the dynamics of predator-prey interactions in a real environment.

Scaling up the predator functional response in heterogeneous environment: When Holling type III can emerge?

Accurate parametrization of functional terms in model equations is of great importance for reproducing the dynamics of real food webs. Constructing models over large spatial and temporal scales using mathematical expressions obtained based on microcosm experiments can be erroneous. Here, using a generic spatial predator–prey model, we show that scaling up the microscale functional response of a predator can result in qualitative alterations of functional response on macroscales. In particular, a global functional response of sigmoid type (Holling type III) can emerge as a result of non-linear averaging of non-sigmoid local responses (Holling type I or II). We demonstrate that alteration between the local and the global response in the model is a result of the interplay between density-dependent dispersal of the predator across the habitat and heterogeneity of the environment. Using the method of aggregation of variables, we analytically derive the mathematical formulation of the global functional response as a function of the total amount of prey in the system, and reveal the key parameters which control the emergence of a Holling type III global response. We argue that this mechanism by which a global Holling type III emerges from a local Holling type II response has not been reported in the literature yet: in particular, Holling type III can emerge in the case of a fixed gradient of resource distribution across the habitat, which would be impossible in priorly suggested mechanisms. As a case study, we consider the interaction between phytoplankton and zooplankton grazers in the water column; and we show that the emergence of a Holling type III global response can allow for the efficient top-down regulation of primary producers and stabilization of planktonic ecosystems under eutrophic conditions.