Vikas Rai

Why chaos is rarely observed in natural populations

Abstract An attempt has been made to understand why chaotic dynamics have received poor evidential support from field studies. Our study opens up the possibility that the cause of failure might not be poor quality of data, as pointed out by earlier authors, but an ecological reality. We have designed two model food chains to examine whether there is a biological basis for the crisis. This investigation is effected with the help of a new method which we introduce at an appropriate place in the text. The fact that chaos exists in a narrow range of parametric values in both the model systems suggests that the crisis indeed has a biological origin.

Chaos: An Ecological Reality?

Deterministic chaos has been studied extensively in various fields. Some of the ideas emerging out of these studies have been put to novel applications. However, it is unknown whether natural ecological systems support chaotic dynamics. There is no concrete evidence which suggests that ecosystem evolution is chaotic in certain situations. This is very intriguing because ecosystems do possess all the necessary qualifications to be able to support such a dynamical behavior. The present paper attempts to answer the above question with the help of a few systems modeling different but very common ecological situations. A new methodology for the analysis of a class of model ecological systems is presented. Simulation experiments suggest that natural terrestrial systems are not suitable candidates where one should look for chaos. Additionally, our study also points out that the failure of attempts to observe chaos in natural populations might have resulted because biological interactions are not conducive for such a behavior to be supported. The cause of these failures may not be the poor data quality or demerits in the analysis techniques.

Crisis-limited chaotic dynamics in ecological systems

Abstract We review our recent efforts to understand why chaotic dynamics is rarely observed in natural populations. The study of two-model ecosystems considered in this paper suggests that chaos exists in narrow parameter ranges. This dynamical behaviour is caused by the crisis-induced sudden death of chaotic attractors. The computed bifurcation diagrams and basin boundary calculations reinforce our earlier conclusion [Chaos, Solitons & Fractals 8 (12) (1997) 1933; Int J Bifurc Chaos 8 (6) (1998) 1325] that the reason why chaos is rarely observed in natural populations is hidden within the mathematical structure of the ecological interactions and not with the problem associated with the data (insufficient length, precision, noise, etc.) and its analysis. We also argue that crisis-limited chaotic dynamics can be commonly found in model terrestrial ecosystems.

Stability and complexity in ecological systems

Abstract The paper attempts to answer an outstanding question in theoretical ecology whether structural complexity is essential for dynamical complexity to exist. Advances in dynamical systems theory and their application to ecosystem analysis has enabled us to have a better grasp of the concept of dynamical complexity. Our basin boundary calculations indicate that structural complexity is not necessary for dynamical complexity to exist. Very simple ecosystems can display dynamical behaviour which is unpredictable in certain situations. In certain cases, when riddled basins are found, even qualitative predictability is denied.

How do ecosystems respond to external perturbations

Abstract This paper attempts to study the influence of environmental perturbations on evolutionary modes (dynamical regimes) of model ecosystems. Three model systems are analysed and the relative importance of these modes is depicted in basin boundary structures. It is found that sudden perturbations usually influence these modes significantly. The coexistence of two or more distinct attractors on the same set of parametric values in nonlinear dynamical systems suggests that the environmental forces may alter the dynamical regimes of these systems. Two-dimensional parameter scans suggest that even smooth (periodic or seasonal) perturbations, which bring changes in system parameters and thus decide dynamical modes to be displayed in a particular situation, are able to induce variations in these modes. It should be noted that the nature of changes induced by the two types of perturbations is different. While the former causes predictable changes in the dynamical modes, the latter forces the system to meander among different dynamical regimes aimlessly. The present study indicates that the influences of sudden (unforeseen) perturbations (e.g., forest fire, drought, flood, invasion by exotic species, etc.) on the ecosystem dynamics can be controlled provided the systems dynamic complexity is understood properly. The knowledge of these influences may help us in gaining insight into how ecological disasters can be managed.

Complex Population Dynamics in Heterogeneous Environments: Effects of Random and Directed Animal Movements

Abstract In this paper, we have investigated the complex dynamics of a one-dimensional spatial nonlinear coupled reaction-diffusion system with a Holling type IV functional response, akin to standard Michaelis-Menten inhibitory kinetics. Prey-taxis is included in a general reaction-diffusion equation to incorporate the active movement of predator species towards regions with high prey concentrations or if the predator is following some sort of cue (such as odor) to find the prey. We have carried out stability analysis of both the non-spatial model without diffusive spreading and of the spatial model. We performed extensive computer simulations to identify various parameter ranges for stable homogeneous solution. Our findings specifically elucidate the role of predator diffusion and prey-taxis in controlling emergent structures, and transitions towards spatio-temporal chaos. We observe that the increasing predator random movement and moderate value of prey-taxis stabilize the system.

DIFFUSION-DRIVEN INSTABILITIES AND SPATIO-TEMPORAL PATTERNS IN AN AQUATIC PREDATOR–PREY SYSTEM WITH BEDDINGTON–DEANGELIS TYPE FUNCTIONAL RESPONSE

Predator–prey communities are building blocks of an ecosystem. Feeding rates reflect interference between predators in several situations, e.g. when predators form a dense colony or perform collective motion in a school, encounter prey in a region of limited size, etc. We perform spatio-temporal dynamics and pattern formation in a model aquatic system in both homogeneous and heterogeneous environments. Zooplanktons are predated by fishes and interfere with individuals of their own community. Numerical simulations are carried out to explore Turing and non-Turing spatial patterns. We also examine the effect of spatial heterogeneity on the spatio-temporal dynamics of the phytoplankton–zooplankton system. The phytoplankton specific growth rate is assumed to be a linear function of the depth of the water body. It is found that the spatio-temporal dynamics of an aquatic system is governed by three important factors: (i) intensity of interference between the zooplankton, (ii) rate of fish predation and (iii) the spatial heterogeneity. In an homogeneous environment, the temporal dynamics of prey and predator species are drastically different. While prey species density evolves chaotically, predator densities execute a regular motion irrespective of the intensity of fish predation. When the spatial heterogeneity is included, the two species oscillate in unison. It has been found that the instability observed in the model aquatic system is diffusion driven and fish predation acts as a regularizing factor. We also observed that spatial heterogeneity stabilizes the system. The idea contained in the paper provides a better understanding of the pattern formation in aquatic systems.

Modeling spatiotemporal dynamics of vole populations in Europe and America

The mathematical models proposed and studied in the present paper provide a unified framework to understand complex dynamical patterns in vole populations in Europe and North America. We have extended the well-known model provided by Hanski and Turchin by incorporating the diffusion term and spatial heterogeneity and performed several mathematical and numerical analyses to explore the dynamics in space and time of the model. These models successfully predicted the observed rodent dynamics in these regions. An attempt has been made to bridge the gap between the field and theoretical studies carried out by Turchin and Hanski (1997) and Turchin and Ellner (2000). Simulation experiments, mainly two-dimensional parameter scans, show the importance of spatial heterogeneity in order to understand the poorly understood fluctuations in population densities of voles in Fennoscandia and Northern America. This study shed new light upon the dynamics of voles in these regions. The nonlinear analysis of vole data suggests that the dynamical shift is from stability to chaos. Diffusion driven model systems predict a new type of dynamics not yet observed in the field studies of vole populations carried out so far. This has been termed as chaotic in time and regular in space (CTRS). We observed CTRS dynamics in several simulation experiments. This directs us to expect that dynamics of this animal would be de-correlated in time and simultaneously mass extinctions might be possible at many spatial locations.

Species extinction problem: genetic vs ecological factors

Abstract Conservation biologists have been facing an intriguing question: whether it is genetic or ecological factors which govern the ecological systems. In this paper, we have constructed a few model systems describing real ecological situations and analysed them using a methodology designed for the purpose. Simulation experiments suggest that both these factors should be given equal weightage in working out strategies for any conservation effort. We conclude that the complex ecosystems are safe places for species belonging to the higher life forms, especially, generalist predators. On the contrary, simple (small) ecosystems cannot harbour these species for long. Another useful observation is that the vertebrate predators should be preferred to their invertebrate counterparts while aiming at conserving endangered prey species.

Deciphering Dynamics of Epidemic Spread: The Case of Influenza Virus

In this paper, we have proposed and analyzed a simple model of Influenza spread with an asymptotic transmission rate. Existence and uniqueness of solutions are established and shown to be uniformly bounded for all non-negative initial values. We have also found a sufficient condition which ensures the persistence of the model system. This implies that both susceptible and infected will always coexist at any location of the inhabited domain. This coexistence is independent of values of the diffusivity constants for two subpopulations. The global stability of the endemic equilibrium is established by constructing a Lyapunov function. By linearizing the system at the positive constant steady-state solution and analyzing the associated characteristic equation, conditions for Hopf and Turing bifurcations are obtained. We have also studied the criteria for diffusion-driven instability caused by local random movements of both susceptible and infective subpopulations. Turing patterns selected by the reaction–diffusion system under zero flux boundary conditions have been explored. Numerical simulations show that contact rate, β which is related to the reproduction number , plays an important role in spatial pattern formation. It was found that diffusion has appreciable influence on spatial spread of epidemics. The wave of chaos appears to be a dominant mode of disease dispersal. This suggests a bidirectional spread for influenza epidemics. The epidemic propagates in the form of nonchaotic and chaotic waves as observed in H1N1 incidence data of positive tests in 2009 in the United States. We have conducted numerical simulations to confirm the analytic work and observed interesting behaviors. This suggests that influenza has a complex dynamics of spatial spread which evolves with time.