The earth’s climate is increasing in temperature and as a result many species’ habitat ranges are shifting. The shift in habitat ranges threatens the local persistence of many species. Mathematical models that capture this phenomena of range shift do so by considering a bounded domain that has a time dependant location on the real line. The analysis on persistence conditions has been considered in both continuous-time and -space, and discrete-time, continuous-space settings. In both model types density was considered to be continuous across the boundaries. However it has been shown that many species exhibit particular behaviour at habitat edges, such as biased movement towards the more suitable habitat. This behaviour should be incorporated into the analysis to obtain more accurate persistence conditions. In this thesis persistence conditions are obtained for generalized boundary conditions with a continuous-time and -space model for a range-shifting habitat. It is shown that a high preference for the suitable habitat at the trailing edge can greatly reduce the size of suitable habitat required for species persistence. As well, for fast shifting ranges, a high preference at the trailing edge is crucial for persistence.

A fibrilação, atrial ou ventricular, é caracterizada por uma desorganização da atividade elétrica do músculo. O coração, que normalmente contrai-se globalmente, em uníssono e uniforme, durante a fibrilação contrai-se localmente em várias regiões, de modo descoordenado. Para estudar qualitativamente este fenômeno, é aqui proposto um novo modelo matemático, mais simples do que os demais existentes e que, principalmente, admite uma representação singela na forma de circuito elétrico equivalente. O modelo foi desenvolvido empiricamente, após estudo crítico dos modelos conhecidos, e após uma série de sucessivas tentativas, ajustes e correções. O modelo mostra-se eficaz na simulação dos fenômenos, que se traduzem em padrões espaciais e temporais das ondas de excitação normais e patológicas, propagando-se em uma grade de pontos que representa o tecido muscular. O trabalho aqui desenvolvido é a parte básica e essencial de um projeto em andamento no Departamento de Engenharia Elétrica da EESC-USP, que é a elaboração de uma rede elétrica ativa, tal que possa ser estudada utilizando recursos computacionais de simuladores usualmente aplicados em projetos de circuitos integrados / Atrial and ventricular fibrillation are characterized by a disorganized electrical activity of the cardiac muscle. While normal heart contracts uniformly as a whole, during fibrillation several small regions of the muscle contracts locally and uncoordinatedly. The present work introduces a new mathematical model for the qualitative study of fibrillation. The proposed model is simpler than other known models and, more importantly, it leads to a very simple electrical equivalent circuit of the excitable cell membrane. The final form of the model equations was established after a long process of trial runs and modifications. Simulation results using the new model are in accordance with those obtained using other (more complex) models found in the related literature. As usual, simulations are performed on a two-dimensional grid of points (representing a piece of heart tissue) where normal or pathological spatial and temporal wave patterns are produced. As a future work, the proposed model will be used as the building block of a large active electrical network representing the muscle tissue, in an integrated circuit simulator

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Understanding eco-evolutionary dynamics in cancer tumors, species invasions, and the human microbiome is vital for numerous health and economic applications. However, spatial structure and population heterogeneity make this challenging. This dissertation tackles these challenges using a population dynamics approach, wherein systems evolve through individual growth and dispersal. The bulk of this dissertation studies expanding populations, such as growing microbial colonies, species range expansions, and cancer tumors. In this context, I first study the effect of a directional bias in dispersal: I develop a model for the stochastic growth of left-right or chirally asymmetric cells that quantitatively reproduces experimental patterns in microbial colonies. Using the model, I demonstrate that chiral dispersal provides an evolutionary advantage and affects spatial population structure in expanding populations. Second, I investigate the impact of environmental structure affecting both dispersal and growth on expanding populations. I show that cooperative population expansions in a periodic environment can be pinned to a particular location or locked to specific velocities determined by the environmental periodicity. Third, I study the problem of a phenotypically heterogeneous population, with each phenotype differing in growth and dispersal abilities. I determine the exact velocity of an expanding population where phenotypes move ballistically and explain the connection to the explosive growth transition in experimental microtubule asters. The final chapter of the dissertation examines the challenge of assembling microbial communities for performing functions such as biofuel production, nitrogen fixation, or health remediation. Due to the exponential number of possible species combinations, bioengineers resort to heuristic search strategies to find the optimal community. I identify biological properties and develop statistical measures to help bioengineers estimate their chance of success in assembling an optimal community. / 2023-02-06T00:00:00Z

In this thesis, we study two stochastic reaction diffusion models - the diffusion limited reaction model of Smoluchowski, and a second approach popularized by Doi. Both models treat molecules as points undergoing Brownian motion. The former represents chemical reactions between two reactants through the use of reactive boundary conditions, with two molecules reacting instantly upon reaching the boundary of a properly embedded open set, termed the reaction region (or more generally some fixed lower dimensional sub-manifold). The Doi model uses reaction potentials, supported in the reaction region, whereby two molecules react with a fixed probability per unit time, λ, upon entering the reaction region. The problem considered is that of obtaining estimates for convergence rates, in λ, of the Doi model to the Smoluchowski model. This problem fits into the theory of singular perturbation or optimization, depending on which reactive boundary conditions one considers, and we solve it - at least for the bimolecular reaction with one stationary target.

The biodegradation process of some types of polymers occurs due to many different factors including their morphology, structure and chemical composition. Although this is a complicated process, most of its important stages like the diffusion of monomers and the hydrolysis reactions have been modeled phenomenologically through reaction-diffusion equations, where the properties of the polymers were encompassed. Using a simplified reaction-diffusion model for the biodegradation of polymers, in this contribution we study the possible effects of the curvature of the system’s geometry in the degradation process, which is characterized by the interaction of the corresponding reaction rate and the diffusion coefficient. To illustrate the problem of diffusion on a curved surface we consider the surface of a cylinder and of the so-called Gaussian bump. We show how the degradation process is affected by the curvature of the system for the simplified model.

This thesis focuses on the impact of spatially heterogeneous environments on the spatio-temporal behavior of planktonic systems. Specific emphasis placed is on the influence of spatial variations in the strength of random or chaotic movements (diffusion) of the organisms. Interaction between different species is described by ordinary differential equations. In order to describe movements in space, reaction–diffusion or advection–reaction–diffusion systems are studied. Examples are given for different approaches of diffusive motion as well as for the possible effects on the localized biological system. The results are discussed based on their biological and physical meanings. In doing so, different mechanisms are shown which are able to explain events of fast plankton growth near turbulent flows. In general, it is shown that local variation in the strength of vertical mixing can have global effects on the biological system, such as changing the stability of dynamical solutions and generating new spatiotemporal behavior. The thesis consists of five chapters. Three of them have been published in international peer-reviewed scientific journals. Chapter 1. Introduction: This chapter gives a general introduction to the history of plankton modeling and introduces basic ideas and concepts which are used in the following chapters. Chapter 2. Fokker-Planck law of diffusion: The influence of spatially in- homogeneous diffusion on several common ecological problems is analyzed. Dif- fusion is modeled with Fick’s law and the Fokker–Planck law of diffusion. A discussion is given about the differences between the two formalisms and when to use the one or the other. To do this, the discussion starts with a pure diffusion equation, then it turns to a reaction–diffusion system with one logistically growing component which invades the spatial domain. This chapter also provides a look at systems of two reacting components, namely a trimolecular oscillating chemical model system and an excitable predator–prey model. Contrary to Fickian diffusion, spatial inhomogeneities promote spatial and spatiotemporal pattern formation in the case of Fokker–Planck diffusion. A slightly modified version of this chapter has been published in the Journal of Mathematical Biology (Bengfort et al., 2016). Chapter 3. Plankton blooms and patchiness: Microscopic turbulent motions of water have been shown to influence the dynamics of microscopic species. Therefore, the number, stability, and excitability of stationary states in a predator– prey model of plankton species can change when the strength of turbulent motions varies. In a spatial system these microscopic turbulent motions are naturally of different strength and form a heterogeneous physical environment. Spatially neighboring plankton communities with different physical conditions can impact each other due to diffusive coupling. It is shown that local variations in the physical conditions can influence the global system in the form of propagating pulses of high population densities. For this, three local predator–prey models with different local responses to variation in the physical environment are considered. The degree of spatial heterogeneity can, depending on the model, promote or reduce the number of propagating pulses, which can be interpreted as patchy plankton distributions and recurrent blooms. This chapter has been published in the Journal Ecological Complexity (Bengfort et al., 2014). Chapter 4. Advection–reaction–diffusion model: Here, some of the models introduced in chapter 1 and 2 are modified to perform two dimensional spatial simulations including advection, reaction and diffusion. These models include assumptions about turbulent flows introduced in chapter 1. Chapter 5. Competition: Some plankton species, such as cyanobacteria, have an advantage in competition for light compared to other species because of their buoyancy. This advantage can be diminished by vertical mixing in the surround- ing water column. A non–spatial model, based on ordinary differential equations, which accounts for this effect is introduced. The main aim is to show that vertical mixing influences the outcome of competition between different species. Hystersis is possible for a certain range of parameters. Introducing a grazing predator, the system exhibits different dynamics depending on the strength of mixing. In a diffusively coupled horizontal spatial model, local vertical mixing can also have a global effect on the biological system, for instance, destabilization of a locally stable solution, or the generation of new spatiotemporal behavior. This chapter has been published in the Journal Ecological Modelling (Bengfort and Malchow, 2016).

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Elliptic obstacle problems are formulated to find either superharmonic solutions or minimal surfaces that lie on or over the obstacles, by incorporating inequality constraints. This dissertation investigates simple iterative algorithms based on the successive over-relaxation (SOR) method. It introduces subgrid methods to reduce accuracy deterioration occurring near the free boundary when the mesh grid does not match with the free boundary. For nonlinear obstacle problems, a method of gradient-weighting is introduced to solve the problem more conveniently and efficiently. The iterative algorithm is analyzed for convergence for both linear and nonlinear obstacle problems. Parabolic initial-boundary value problems with nonsmooth data show either rapid transitions or reduced smoothness in its solution. For those problems, specific numerical methods are required to avoid spurious oscillations as well as unrealistic smoothing of steep changes in the numerical solution. This dissertation investigates characteristics of the θ-method and introduces a variable-θ method as a synergistic combination of the Crank-Nicolson (CN) method and the implicit method. It suppresses spurious oscillations, by evolving the solution implicitly at points where the solution shows a certain portent of oscillations or reduced smoothness, and maintains as a similar accuracy as the CN method with smooth data. An effective strategy is suggested for the detection of points where the solution may introduce spurious oscillations (the wobble set); the resulting variable-θ method is analyzed for its accuracy and stability. After a theory of morphogenesis in chemical cells was introduced in 1950s, much attention had been devoted to the numerical solution of reaction-diffusion (RD) equations. This dissertation studies a nonoscillatory second-order time-stepping procedure for RD equations incorporating with variable-θ method, as a perturbation of the CN method. We also perform a sensitivity analysis for the numerical solution of RD systems to conclude that it is much more sensitive to the spatial mesh resolution than the temporal one. Moreover, to enhance the spatial approximation of RD equations, this dissertation investigates the averaging scheme, that is, an interpolation of the standard and skewed discrete Laplacian operator and introduce the simple optimizing strategy to minimize the leading truncation error of the scheme.