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This book is an outgrowth of one phase of an upper-division course on quantitative ecology, given each year for the past eight at Berkeley. I am most grateful to the students in that course and to many graduate students in the Berkeley Department of Zoology and Colleges of Engineering and Natural Resources whose spirited discussions inspired much of the book's content. I also am deeply grateful to those faculty colleagues with whom, at one time or another, I have shared courses or seminars in ecology or population biology, D.M. Auslander, L. Demetrius, G. Oster, O.H. Paris, F.A. Pitelka, A.M. Schultz, Y. Takahashi, D.B. Tyler, and P. Vogelhut, all of whom contributed substantially to the development of my thinking in those fields, to my Depart mental colleagues E. Polak and A.J. Thomasian, who guided me into the litera ture on numerical methods and stochastic processes, and to the graduate students who at one time or another have worked with me on population-biology projects, L.M. Brodnax, S-P. Chan, A. Elterman, G.C. Ferrell, D. Green, C. Hayashi, K-L. Lee, W.F. Martin Jr., D. May, J. Stamnes, G.E. Swanson, and I. Weeks, who, together, undoubtedly provided me with the greatest inspiration. I am indebted to the copy-editing and production staff of Springer-Verlag, especially to Ms. M. Muzeniek, for their diligence and skill, and to Mrs. Alice Peters, biomathematics editor, for her patience.
In this new century mankind faces ever more challenging environmental and publichealthproblems,suchaspollution,invasionbyexoticspecies,theem- gence of new diseases or the emergence of diseases into new regions (West Nile virus,SARS,Anthrax,etc.),andtheresurgenceofexistingdiseases(in?uenza, malaria, TB, HIV/AIDS, etc.). Mathematical models have been successfully used to study many biological, epidemiological and medical problems, and nonlinear and complex dynamics have been observed in all of those contexts. Mathematical studies have helped us not only to better understand these problems but also to ?nd solutions in some cases, such as the prediction and control of SARS outbreaks, understanding HIV infection, and the investi- tion of antibiotic-resistant infections in hospitals. Structuredpopulationmodelsdistinguishindividualsfromoneanother- cording to characteristics such as age, size, location, status, and movement, to determine the birth, growth and death rates, interaction with each other and with environment, infectivity, etc. The goal of structured population models is to understand how these characteristics a?ect the dynamics of these models and thus the outcomes and consequences of the biological and epidemiolo- cal processes. There is a very large and growing body of literature on these topics. This book deals with the recent and important advances in the study of structured population models in biology and epidemiology. There are six chapters in this book, written by leading researchers in these areas.
Integrated Population Biology and Modeling: Part A offers very complex and precise realities of quantifying modern and traditional methods of understanding populations and population dynamics. Chapters cover emerging topics of note, including Longevity dynamics, Modeling human-environment interactions, Survival Probabilities from 5-Year Cumulative Life Table Survival Ratios (Tx+5/Tx): Some Innovative Methodological Investigations, Cell migration Models, Evolutionary Dynamics of Cancer Cells, an Integrated approach for modeling of coastal lagoons: A case for Chilka Lake, India, Population and metapopulation dynamics, Mortality analysis: measures and models, Stationary Population Models, Are there biological and social limits to human longevity?, Probability models in biology, Stochastic Models in Population Biology, and more. Covers emerging topics of note in the subject matter Presents chapters on Longevity dynamics, Modeling human-environment interactions, Survival Probabilities from 5-Year Cumulative Life Table Survival Ratios (Tx+5/Tx), and more
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.
Reviewing the general theory of population stability, this text critically analyzes techniques for inferring whether a given population is in balance or not. It goes on to show how rigorous empirical research can reveal both the proximal causes of stability and its most evolutionary cases.
Integrated Population Biology and Modeling: Part B, Volume 40, offers very delicately complex and precise realities of quantifying modern and traditional methods of understanding populations and population dynamics, with this updated release focusing on Prey-predator animal models, Back projections, Evolutionary Biology computations, Population biology of collective behavior and bio patchiness, Collective behavior, Population biology through data science, Mathematical modeling of multi-species mutualism: new insights, remaining challenges and applications to ecology, Population Dynamics of Manipur, Stochastic Processes and Population Dynamics Models: The Mechanisms for Extinction, Persistence and Resonance, Theories of Stationary Populations and association with life lived and life left, and more. Studies human and animal models that are studied both separately and throughout chapters Presents a comprehensive and timely update on integrated population biology
This volume presents a timely and comprehensive overview of biological networks at all organization levels in the spirit of the complex systems approach. It discusses the transversal issues and fundamental principles as well as the overall structure, dynamics, and modeling of a wide array of biological networks at the molecular, cellular, and population levels. Anchored in both empirical data and a strong theoretical background, the book therefore lends valuable credence to the complex systems approach. Sample Chapter(s). Chapter 1: Scale-Free Networks in Biology (821 KB). Contents: Scale-Free Networks in Biology (E Almaas et al.); Modularity in Biological Networks (R V Sol(r) et al.); Inference of Biological Regulatory Networks: Machine Learning Approaches (F d''Alch(r)-Buc); Transcriptional Networks (F K(r)p s); Protein Interaction Networks (K Tan & T Ideker); Metabolic Networks (D A Fell); Heterogeneous Molecular Networks (V Schnchter); Evolution of Regulatory Networks (A Veron et al.); Complexity in Neuronal Networks (Y Fr(r)gnac et al.); Networks of the Immune System (R E Callard & J Stark); A History of the Study of Ecological Networks (L-F Bersier); Dynamic Network Models of Ecological Diversity, Complexity, and Nonlinear Persistence (R J Williams & N D Martinez); Infection Transmission through Networks (J S Koopman). Readership: Graduate students and industry experts in systems biology and complex systems; biologists; chemists; physicists; mathematicians; computer scientists
As the first comprehensive title on network biology, this book covers a wide range of subjects including scientific fundamentals (graphs, networks, etc) of network biology, construction and analysis of biological networks, methods for identifying crucial nodes in biological networks, link prediction, flow analysis, network dynamics, evolution, simulation and control, ecological networks, social networks, molecular and cellular networks, network pharmacology and network toxicology, big data analytics, and more.Across 12 parts and 26 chapters, with Matlab codes provided for most models and algorithms, this self-contained title provides an in-depth and complete insight on network biology. It is a valuable read for high-level undergraduates and postgraduates in the areas of biology, ecology, environmental sciences, medical science, computational science, applied mathematics, and social science.