The field of stochastic growth encompasses various different processes which are ubiquitously seen across the physical world. In many systems, stochasticity appears quite naturally, where inherent randomness provides the right setting for the tone of motion and interaction, whose symphony leads to the surprising emergence of interesting patterns and structure. Although on the microscopic scale one can be overwhelmed by the randomness arising from the fluctuating interactions between components, on the macroscopic scale, however, one is mesmerized by the emergence of mathematical beauty and symmetry, leading to complex structures with fractal architecture. Competition between components adds an extra degree of complexity and leads to the possibility of critical behaviour and phase transitions. It is an important aspect of many systems, and in order to provide a full explanation of many natural phenomena, we have to understand the role it plays on modifying behaviour. The combination of stochastic growth and competition leads to the emergence of interesting complex patterns. They occur in various systems and in many forms, and thus we treat competition in growth models driven by different laws for the stochastic noise. As a consequence our results are widely applicable and we encourage the reader to find good use for them in their respective field. In this thesis we study stochastic systems containing interacting particles whose motion and interplay lead to directed growth structures on a particular geometry. We show how the effect of the overall geometry in many growth processes can be captured elegantly in terms of a time dependent metric. A natural example we treat is isoradial growth in two dimensions, with domain boundaries of competing microbial species as an example of a system with a homogeneously changing metric. In general, we view domain boundaries as space-time trajectories of particles moving on a dynamic surface and map those into more easily tractable systems with constant metric. This leads to establishing a generic relation between locally interacting, scale invariant stochastic space-time trajectories under constant and time dependent metric. Indeed "the book of nature is written in the language of mathematics" (Galileo Galilei) and we provide a mathematical framework for various systems with various interactions and our results are backed with numerical confirmation.

The groundbreaking Encyclopedia of Ecology provides an authoritative and comprehensive coverage of the complete field of ecology, from general to applied. It includes over 500 detailed entries, structured to provide the user with complete coverage of the core knowledge, accessed as intuitively as possible, and heavily cross-referenced. Written by an international team of leading experts, this revolutionary encyclopedia will serve as a one-stop-shop to concise, stand-alone articles to be used as a point of entry for undergraduate students, or as a tool for active researchers looking for the latest information in the field. Entries cover a range of topics, including: Behavioral Ecology Ecological Processes Ecological Modeling Ecological Engineering Ecological Indicators Ecological Informatics Ecosystems Ecotoxicology Evolutionary Ecology General Ecology Global Ecology Human Ecology System Ecology The first reference work to cover all aspects of ecology, from basic to applied Over 500 concise, stand-alone articles are written by prominent leaders in the field Article text is supported by full-color photos, drawings, tables, and other visual material Fully indexed and cross referenced with detailed references for further study Writing level is suited to both the expert and non-expert Available electronically on ScienceDirect shortly upon publication

This is a collection of topical survey articles by researchers in the fields of applied analysis and probability theory, working on the mathematical description of growth phenomena. Particular emphasis is given to the interplay of the usually separate fields of applied analysis and probability theory.

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.