A population is a summation of all the organisms of the same group or species, which live in a particular geographical area, and have the capability of interbreeding. The main mathematical problem for a given population is to carefully examine the evolution (time dependent dynamics) of the population. The mathematical methods used in the study of this problem are based on probability theory, stochastic processes, dynamical systems, nonlinear differential and difference equations, and (non-)associative algebras.A state of a population is a distribution of probabilities of the different types of organisms in every generation. Type partition is called differentiation (for example, sex differentiation which defines a bisexual population). This book systematically describes the recently developed theory of (bisexual) population, and mainly contains results obtained since 2010.The book presents algebraic and probabilistic approaches in the theory of population dynamics. It also includes several dynamical systems of biological models such as dynamics generated by Markov processes of cubic stochastic matrices; dynamics of sex-linked population; dynamical systems generated by a gonosomal evolution operator; dynamical system and an evolution algebra of mosquito population; and ocean ecosystems.The main aim of this book is to facilitate the reader's in-depth understanding by giving a systematic review of the theory of population dynamics which has wide applications in biology, mathematics, medicine, and physics.

Population Dynamics fills the gap between the classical supply-side population theory of Malthus and the modern demand-side theory of economic demography. In doing so, author Cyrus Chu investigates specifically the dynamic macro implications of various static micro family economic decisions. Holding the characteristic composition of the macro population to always be an aggregate result of some corresponding individual micro decision, Chu extends his research on the fertility-related decisions of families to an analysis of other economic determinations. Within this framework, Chu studies the income distribution, attitude composition, job structure, and aggregate savings and pensions of the population. While in some cases a micro-macro connection is easily established under regular behavioral assumptions, in several chapters Chu enlists the mathematical tool of branching processes to determine the connection. Offering a wealth of detail, this book provides a balanced discussion of background motivation, theoretical characterization, and empirical evidence in an effort to bring about a renewal in the economic approach to population dynamics. This welcome addition to the research and theory of economic demography will interest professional economists as well as professors and graduate students of economics.

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.

This monograph introduces the theory of structured population dynamics and its applications, focusing on the asymptotic dynamics of deterministic models.

This book provides an introduction to population dynamics, exploring rules that govern change in any dynamic system and applying these general principles to populations of living organisms. Principles of Population Dynamics and their Application is aimed at applied ecologists, resource managers. and pest managers. It is also aimed at undergraduate students taking courses in forestry, fisheries, widlife and pest management.

The vast majority of random processes in the real world have no memory - the next step in their development depends purely on their current state. Stochastic realizations are therefore defined purely in terms of successive event-time pairs, and such systems are easy to simulate irrespective of their degree of complexity. However, whilst the associated probability equations are straightforward to write down, their solution usually requires the use of approximation and perturbation