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Describing a theoretical view of ecosystems based on how they self-organise to produce complex patterns, this book focuses on very simple models that despite their simplicity encapsulate fundamental properties of how ecosystems work.
Air Pollution Calculations: Quantifying Pollutant Formation, Transport, Transformation, Fate and Risks, Second Edition enhances the systems science aspects of air pollution, including transformation reactions in soil, water, sediment and biota that contribute to air pollution. This second edition will be an update based on research and actions taken since 2019 that affect air pollution calculations, including new control technologies, emissions measurement, and air quality modeling. Recent court cases, regulatory decisions, and advances in technology are discussed and, where necessary, calculations have been revised to reflect these updates. Sections discuss pollutant characterization, pollutant transformation, and environmental partitioning. Air partitioning, physical transport of air pollutants, air pollution biogeochemistry, and thermal reactions are also thoroughly explored. The author then carefully examines air pollution risk calculations, control technologies and dispersion models. The text wraps with discussions of economics and project management, reliability and failure, and air pollution decision-making. - Provides real-life current cases as examples of quantitation of emerging air pollution problems - Includes straightforward derivation of equations, giving practitioners and instructors a direct link between first principles of science and applications of technologies - Presents example calculations that make scientific theory real for the student and practitioner
Advances in molecular biology, remote sensing, systems biology, bioinformatics, non-linear science, the physics of complex systems and other fields have rendered a great amount of data that remain to be integrated into models and theories that are capable of accounting for the complexity of ecological systems and the evolutionary dynamics of life. It is thus necessary to provide a solid basis to discuss and reflect on these and other challenges both at the local and global scales. This volume aims to delineate an integrative and interdisciplinary view that suggests new avenues in research and teaching, critically discusses the scope of the diverse methods in the study of complex systems, and points at key open questions. Finally, this book will provide students and specialists with a collection of high quality open access essays that will contribute to integrate Ecology, Evolution and Complexity in the context of basic research and in the field of Sustainability Sciences.
This book provides a conceptual clarification of the interconnections between agent-based modeling and business process management (BPM) and presents practical examples of agent-based models dealing with BPM and simulation in NetLogo. The book is structured in three parts. Part I starts with the motivation for the work and introduces the general structure of the book. Next, chapter 2 provides a brief introduction to main BPM concepts including the business process lifecycle, which describes the analysis of an organization by means of modeling and simulation, business process performance indicators, and the automatic extraction of information from event data. Chapter 3 then offers a summary of the concept of agent and the studies concerning agent-based approaches that involve business process analysis and management studies. Part II of the book introduces in chapter 4 the NetLogo tool adopted throughout the remaining book. After that, chapter 5 focuses on agent-oriented modeling as a problem domain analysis and design approach for creating decision-support systems based on agent-based simulations. Chapter 6 further describes the topic of agent-based modeling and simulation for business process analysis. The final part III starts with chapter 7 that reviews some BPM applications by introducing programs enabling to manage models represented in standard formats, such as BPMN, Petri nets, and the eXtensible Event Stream standard language. Subsequently, chapter 8 describes a number of case studies from different areas, and eventually, chapter 9 introduces some examples of advanced topics of process mining and agent-based simulation with process discovery, conformance checking, and agent-based applications utilizing Petri nets. The book is primarily written for researchers and advanced graduate and PhD students who look for an introduction to the fruitful exploitation of agent-based modeling to business process management. The book is also useful for industry practitioners who are interested in supporting their business decisions with computational simulations. The book is complemented by a dedicated web site with lots of additional details and models in NetLogo for further evaluation by the reader.
Scholars consider the origins and consequences of the evolution of multicellularity, addressing a range of organisms, experimental protocols, theoretical concepts, and philosophical issues. The evolution of multicellularity raises questions regarding genomic and developmental commonalities and discordances, selective advantages and disadvantages, physical determinants of development, and the origins of morphological novelties. It also represents a change in the definition of individuality, because a new organism emerges from interactions among single cells. This volume considers these and other questions, with contributions that explore the origins and consequences of the evolution of multicellularity, addressing a range of topics, organisms, and experimental protocols. Each section focuses on selected topics or particular lineages that present a significant insight or challenge. The contributors consider the fossil record of the paleontological circumstances in which animal multicellularity evolved; cooptation, recurrent patterns, modularity, and plausible pathways for multicellular evolution in plants; theoretical approaches to the amoebozoa and fungi (cellular slime molds having long provided a robust model system for exploring the evolution of multicellularity), plants, and animals; genomic toolkits of metazoan multicellularity; and philosophical aspects of the meaning of individuality in light of multicellular evolution. Contributors Maja Adamska, Argyris Arnellos, Juan A. Arias, Eugenio Azpeitia, Mariana Benítez, Adriano Bonforti, John Tyler Bonner, Peter L. Conlin, A. Keith Dunker, Salva Duran-Nebreda, Ana E. Escalante, Valeria Hernández-Hernández, Kunihiko Kaneko, Andrew H. Knoll, Stephan G. König, Daniel J. G. Lahr, Ottoline Leyser, Alan C. Love, Raul Montañez, Emilio Mora van Cauwelaert, Alvaro Moreno, Vidyanand Nanjundiah, Aurora M. Nedelcu, Stuart A. Newman, Karl J. Niklas, William C. Ratcliff, Iñaki Ruiz-Trillo, Ricard Solé
Terminology, conceptual overview, biogeography, modeling.
Can physics be an appropriate framework for the understanding of ecological science? Most ecologists would probably agree that there is little relation between the complexity of natural ecosystems and the simplicity of any example derived from Newtonian physics. Though ecologists have long been interested in concepts originally developed by statistical physicists and later applied to explain everything from why stock markets crash to why rivers develop particular branching patterns, applying such concepts to ecosystems has remained a challenge. Self-Organization in Complex Ecosystems is the first book to clearly synthesize what we have learned about the usefulness of tools from statistical physics in ecology. Ricard Solé and Jordi Bascompte provide a comprehensive introduction to complex systems theory, and ask: do universal laws shape the structure of ecosystems, at least at some scales? They offer the most compelling array of theoretical evidence to date of the potential of nonlinear ecological interactions to generate nonrandom, self-organized patterns at all levels. Tackling classic ecological questions--from population dynamics to biodiversity to macroevolution--the book's novel presentation of theories and data shows the power of statistical physics and complexity in ecology. Self-Organization in Complex Ecosystems will be a staple resource for years to come for ecologists interested in complex systems theory as well as mathematicians and physicists interested in ecology.
A New Ecology: Systems Perspective, Second Edition, gives an overview of the commonalities of all ecosystems from a variety of properties, including physical openness, ontic openness, directionality, connectivity, a complex dynamic for growth and development, and a complex dynamic response to disturbances. Each chapter details basic and characteristic properties that help the reader understand how they can be applied to explain a wide spectrum of current ecological research and environmental management applications. - Contains revised, updated or redeveloped chapters that include the most current research and technology - Reviews universal traits of ecosystems from multiple perspectives, giving the reader a complete overview of the systems perspective of ecology - Offers broad examples of ecology as a systems science, from the history of science, to philosophy and the arts - Brings together the systems perspective in a framework of four columns for greater understanding, including thermodynamics, network theory, hierarchy theory and biochemistry - Contains new chapter on the application of the theory to environmental management
Lattice-gas cellular automata (LGCA) and lattice Boltzmann models (LBM) are relatively new and promising methods for the numerical solution of nonlinear partial differential equations. The book provides an introduction for graduate students and researchers. Working knowledge of calculus is required and experience in PDEs and fluid dynamics is recommended. Some peculiarities of cellular automata are outlined in Chapter 2. The properties of various LGCA and special coding techniques are discussed in Chapter 3. Concepts from statistical mechanics (Chapter 4) provide the necessary theoretical background for LGCA and LBM. The properties of lattice Boltzmann models and a method for their construction are presented in Chapter 5.
This book synthesizes and reconciles modern and classical perspectives into a general unified theory.