Deterministic Mathematical Models in Population Ecology


Book Description

Single-species growth; Pedration and parasitism; Predador-prey systems; Lotka-volterra systems for predator-prey interactions; Intermediate predator-prey models; Continous models; Discrete models; The kolmogorov model; Related topics and applications; Related topics; Aplications; competition and cooperation (symbiosis); Lotka-volterra competition models; Higher-oder competition models; cooperation (symbiosis); Pertubation theory; The implicit function theorem; Existence and Uniqueness of solutions of ordinary differential equations; Stability and periodicity; The poincare-bendixon theorem; The hopf bifurcation theorem.




Methods and Models in Mathematical Biology


Book Description

This book developed from classes in mathematical biology taught by the authors over several years at the Technische Universität München. The main themes are modeling principles, mathematical principles for the analysis of these models and model-based analysis of data. The key topics of modern biomathematics are covered: ecology, epidemiology, biochemistry, regulatory networks, neuronal networks and population genetics. A variety of mathematical methods are introduced, ranging from ordinary and partial differential equations to stochastic graph theory and branching processes. A special emphasis is placed on the interplay between stochastic and deterministic models.







Mathematical Biology


Book Description

Mathematics has always benefited from its involvement with developing sciences. Each successive interaction revitalises and enhances the field. Biomedical science is clearly the premier science of the foreseeable future. For the continuing health of their subject mathematicians must become involved with biology. With the example of how mathematics has benefited from and influenced physics, it is clear that if mathematicians do not become involved in the biosciences they will simply not be a part of what are likely to be the most important and exciting scientific discoveries of all time. Mathematical biology is a fast growing, well recognised, albeit not clearly defined, subject and is, to my mind, the most exciting modern application of mathematics. The increasing use of mathematics in biology is inevitable as biol ogy becomes more quantitative. The complexity of the biological sciences makes interdisciplinary involvement essential. For the mathematician, biology opens up new and exciting branches while for the biologist mathematical modelling offers another research tool commmensurate with a new powerful laboratory technique but only if used appropriately and its limitations recognised. However, the use of esoteric mathematics arrogantly applied to biological problems by mathemati cians who know little about the real biology, together with unsubstantiated claims as to how important such theories are, does little to promote the interdisciplinary involvement which is so essential. Mathematical biology research, to be useful and interesting, must be relevant biologically.




Modelling Biological Populations in Space and Time


Book Description

This volume develops a unifying approach to population studies, emphasising the interplay between modelling and experimentation. Throughout, mathematicians and biologists are provided with a framework within which population dynamics can be fully explored and understood. Aspects of population dynamics covered include birth-death and logistic processes, competition and predator-prey relationships, chaos, reaction time-delays, fluctuating environments, spatial systems, velocities of spread, epidemics, and spatial branching structures. Both deterministic and stochastic models are considered. Whilst the more theoretically orientated sections will appeal to mathematical biologists, the material is presented so that readers with little mathematical expertise can bypass these without losing the main flow of the text.




Biomathematics


Book Description

This book on modelling and simulation in biomathematics will be invaluable to researchers who are interested in the emerging areas of the field. Graduate students in related areas as well as lecturers will also find it beneficial. Some of the chapters have been written by distinguished experts in the field. Sample Chapter(s). Chapter 1: Detecting Mosaic Structures in DNA Sequence Alignments (1,349 KB). Contents: Detecting Mosaic Structures in DNA Sequence Alignments (D Husmeier); Application of Statistical Methodology and Model Design to Socio-Behaviour of HIV Transmission (J Oluwoye); A Stochastic Model Incorporating HIV Treatments for a Heterosexual Population: Impact on Threshold Conditions (R J Gallop et al.); Modeling and Identification of the Dynamics of the MF-Influenced Free-Radical Transformations in Lipid-Modeling Substances and Lipids (J Bentsman et al.); Computer Simulation of Self-Reorganization in Biological Cells (D Greenspan); Modelling Biological Gel Contraction by Cells: Consequences of Cell Traction Forces Distribution and Initial Stress (S Ramtani); Peristaltic Transport of Physiological Fluids (J C Misra & S K Pandey); Mathematical Modelling of DNA Knots and Links (J C Misra & S Mukherjee); Using Monodomain Computer Models for the Simulation of Electric Fields During Excitation Spread in Cardiac Tissue (G Plank); Flow in Tubes with Complicated Geometries with Special Application to Blood Flow in Large Arteries (G Jayaraman); Mathematical Modeling in Reproductive Biomedicine (S Sharma & S K Guha); Image Theory and Applications in Bioelectromagnetics (P D Einziger et al.); Dynamics of Humanoid Robots: Geometrical and Topological Duality (V G Ivancevic); The Effects of Body Composition on Energy Expenditure and Weight Dynamics During Hypophagia: A Setpoint Analysis (F P Kozusko); Mathematical Models in Population Dynamics and Ecology (R Diluo); Modelling in Bone Biomechanics (J C Misra & S Samanta). Readership: Graduate students, academic and researchers in biomathematics, mathematical biology, mathematical modeling, biotechnology, biocomputing, biophysics, bioengineering and mechanics."




Complex Population Dynamics


Book Description

Why do organisms become extremely abundant one year and then seem to disappear a few years later? Why do population outbreaks in particular species happen more or less regularly in certain locations, but only irregularly (or never at all) in other locations? Complex population dynamics have fascinated biologists for decades. By bringing together mathematical models, statistical analyses, and field experiments, this book offers a comprehensive new synthesis of the theory of population oscillations. Peter Turchin first reviews the conceptual tools that ecologists use to investigate population oscillations, introducing population modeling and the statistical analysis of time series data. He then provides an in-depth discussion of several case studies--including the larch budmoth, southern pine beetle, red grouse, voles and lemmings, snowshoe hare, and ungulates--to develop a new analysis of the mechanisms that drive population oscillations in nature. Through such work, the author argues, ecologists can develop general laws of population dynamics that will help turn ecology into a truly quantitative and predictive science. Complex Population Dynamics integrates theoretical and empirical studies into a major new synthesis of current knowledge about population dynamics. It is also a pioneering work that sets the course for ecology's future as a predictive science.




A Short History of Mathematical Population Dynamics


Book Description

As Eugene Wigner stressed, mathematics has proven unreasonably effective in the physical sciences and their technological applications. The role of mathematics in the biological, medical and social sciences has been much more modest but has recently grown thanks to the simulation capacity offered by modern computers. This book traces the history of population dynamics---a theoretical subject closely connected to genetics, ecology, epidemiology and demography---where mathematics has brought significant insights. It presents an overview of the genesis of several important themes: exponential growth, from Euler and Malthus to the Chinese one-child policy; the development of stochastic models, from Mendel's laws and the question of extinction of family names to percolation theory for the spread of epidemics, and chaotic populations, where determinism and randomness intertwine. The reader of this book will see, from a different perspective, the problems that scientists face when governments ask for reliable predictions to help control epidemics (AIDS, SARS, swine flu), manage renewable resources (fishing quotas, spread of genetically modified organisms) or anticipate demographic evolutions such as aging.




Spatiotemporal Patterns in Ecology and Epidemiology


Book Description

Although the spatial dimension of ecosystem dynamics is now widely recognized, the specific mechanisms behind species patterning in space are still poorly understood and the corresponding theoretical framework is underdeveloped. Going beyond the classical Turing scenario of pattern formation, Spatiotemporal Patterns in Ecology and Epidemiology:




Mathematical Models


Book Description

The author uses mathematical techniques to give an in-depth look at models for mechanical vibrations, population dynamics, and traffic flow.