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An increasing variety of biological problems involving resource management, conservation and environmental quality have been dealt with using the principles of population biology (defined to include population dynamics, genetics and certain aspects of community ecology). There appears to be a mixed record of successes and failures and almost no critical synthesis or reviews that have attempted to discuss the reasons and ways in which population biology, with its remarkable theoretical as well as experimental advances, could find more useful application in agriculture, forestry, fishery, medicine and resource and environmental management. This book provides examples of state-of-the-art applications by a distinguished group of researchers in several fields. The diversity of topics richly illustrates the scientific and economic breadth of their discussions as well as epistemological and comparative analyses by the authors and editors. Several principles and common themes are emphasized and both strengths and potential sources of uncertainty in applications are discussed. This volume will hopefully stimulate new interdisciplinary avenues of problem-solving research

Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1. Some General Remarks on Mathematical Modeling -- Bibliographic Remarks -- PART 1. BASIC POPULATION GROWTH MODELS -- Chapter 2. Birth, Death, and Migration -- 2.1 The Fundamental Balance Equation of Population Dynamics -- 2.2 Birth Date Dependent Life Expectancies -- 2.3 The Probability of Lifetime Emigration -- Chapter 3. Unconstrained Population Growth for Single Species -- 3.1 Closed Populations -- 3.1.1 The Average Intrinsic Growth Rate for Periodic Environments -- 3.1.2 The Average Intrinsic Growth Rate for Nonperiodic Environments -- 3.2 Open Populations -- 3.2.1 Nonzero Average Intrinsic Growth Rate -- 3.2.2 Zero Average Intrinsic Growth Rate -- Chapter 4. Von Bertalanffy Growth of Body Size -- Chapter 5. Classic Models of Density-Dependent Population Growth for 37 Single Species -- 5.1 The Bernoulli and the Verhulst Equations -- 5.2 The Beverton-Holt and Smith Differential Equation -- 5.2.1 Derivation from a Resource-Consumer Model -- 5.2.2 Derivation from Cannibalism of Juveniles by Adults -- 5.3 The Ricker Differential Equation -- 5.4 The Gompertz Equation -- 5.5 A First Comparison of the Various Equations -- Chapter 6. Sigmoid Growth -- 6.1 General Conditions for Sigmoid Growth -- 6.2 Fitting Sigmoid Population Data -- Chapter 7. The Allee Effect -- 7.1 First Model Derivation: Search for a Mate -- 7.2 Second Model Derivation: Impact of a Satiating Generalist Predator -- 7.3 Model Analysis -- Chapter 8. Nonautonomous Population Growth:Asymptotic Equality of 75 Population Sizes -- Chapter 9. Discrete-Time Single-Species Models -- 9.1 The Discrete Analog of the Verhulst (Logistic) and the Bernoulli Equation: the Beverton-Holt Difference Equation and Its Generalization -- 9.2 The Ricker Difference Equation -- 9.3 Some Analytic Results for Scalar Difference Equations

This research monograph provides an introduction to the theory of nonautonomous semiflows with applications to population dynamics. It develops dynamical system approaches to various evolutionary equations such as difference, ordinary, functional, and partial differential equations, and pays more attention to periodic and almost periodic phenomena. The presentation includes persistence theory, monotone dynamics, periodic and almost periodic semiflows, basic reproduction ratios, traveling waves, and global analysis of prototypical population models in ecology and epidemiology.Research mathematicians working with nonlinear dynamics, particularly those interested in applications to biology, will find this book useful. It may also be used as a textbook or as supplementary reading for a graduate special topics course on the theory and applications of dynamical systems. Dr. Xiao-Qiang Zhao is a University Research Professor at Memorial University of Newfoundland, Canada. His main research interests involve applied dynamical systems, nonlinear differential equations, and mathematical biology. He is the author of more than 100 papers, and his research has played an important role in the development of the theory and applications of monotone dynamical systems, periodic and almost periodic semiflows, uniform persistence, and basic reproduction ratios. Dr. Xiao-Qiang Zhao is a professor in applied mathematics at Memorial University of Newfoundland, Canada. His main research interests involve applied dynamical systems, nonlinear differential equations, and mathematical biology. He is the author of more than 40 papers and his research has played an important role in the development of the theory of periodic and almost periodic semiflows and their applications.

▪ Abstract  In this professional memoir I trace my career and the changes that occurred after World War II in the biological anthropology studies of human populations. I describe my academic training at the University of New Mexico and Harvard University and my research training at the US Climatic Research Laboratory. During my academic career at The Pennsylvania State University, I directed two multidisciplinary research efforts as part of the International Biological Programme and Man in the Biosphere Program. These were the high-altitude studies in Nunoa, Peru, and the migration and modernization studies of Samoan communities. I describe my participation in the development of these international science programs as well as the effects on the discipline of biological anthropology. In conclusion, I reflect on the growth and development of biological anthropology, particularly in human population biology.

This unique collection of essays deals with the foundation and historical development of population biology and its relationship to population genetics and population ecology on the one hand and to the rapidly growing fields of molecular quantitative genetics, genomics and bioinformatics on the other. Published in honor of Richard Lewontin

Part I. Historical Foundations and Perspectives -- 1. Building a science of population biology / Richard Lewontin -- 2. Toward a population biology, still / Richard Levins -- Part II. Genotypes to Phenotypes : New Genetic and Bioinformatic Advances -- 3. Genetic dissection of quantitative traits / Trudy Mackay -- 4. Gene expression profiling in evolutionary genetics / Daniel Hartl, Colin Meiklejohn, Cristian Castillo-Davis, Duccio Cavelieri, Jose Ranz and Jeffrey Townsend -- 5. Population biology and bioinformatics / Brian Golding -- 6. Beyond beanbag genetics : Wright's adaptive landscape, gene interaction networks and the evolution of new genetic systems / Rama Singh and Richard Morton -- Part III. Phenotypes to Fitness : Genetics and Ecology of Populations -- 7. Density dependant selection / Freddy Christiansen -- 8. Non-synonymous polymorphisms and frequency-dependent selection / Bryan Clarke -- 9. Why k=4Næs is silly / John Gillespie -- 10. Inferences about the structure and history of populations : Coalescents and intraspecific phylogeography / John Wakely -- 11. The population genetics of life-history evolution / Brian Charlesworth -- 12. Gene-environment complexities : what is so interesting to measure and to model? / Peter Taylor -- 13. Genus-specific diversification of mating types / Marcy Uyenoyama and Naoki Takebayashi -- Part III. Genes, Organisms and Environment : Evolutionary Case Studies -- 14. Adaptation, constraint, and neutrality : mechanistic case studies with butterflies and their general implications / Ward Watt -- 15. Evolution in hybrid zones / Daniel Howard, Seth Britch, W. Evan Braswell and Jeremy Marshall -- 16. Nine relatives from one African ancestor : Population biology and evolution of the Drosophila melanogaster subgroup species / Daniel Lachaise, Pierre Capy, Marie-Louise Cariou, Dominique Joly, Francoise Lemeunier and Jean R. David -- Part IV. Applied Population Biology : Biodiversity and Food, Disease and Health -- 17. Conservation biology : where are we? / Philip Hedrick -- 18. The emergence of modern human mortality patterns / Shripad Tuljapurkar -- 19. Units of selection and the evolution of virulence / Paul Ewald and Gregory Cochran -- 20. Evolutionary genetics and emergence of RNA virus diseases / Edward Holmes -- 21. A scientific adventure : a fifty years study of human evolution / Luigi Cavalli-Sforza -- 22. Geneticists and the biology of race, 1900-1924 / Will Provine.

Population biology has been investigated quantitatively for many decades, resulting in a rich body of scientific literature. Ecologists often avoid this literature, put off by its apparently formidable mathematics. This textbook provides an introduction to the biology and ecology of populations by emphasizing the roles of simple mathematical models in explaining the growth and behavior of populations. The author only assumes acquaintance with elementary calculus, and provides tutorial explanations where needed to develop mathematical concepts. Examples, problems, extensive marginal notes and numerous graphs enhance the book's value to students in classes ranging from population biology and population ecology to mathematical biology and mathematical ecology. The book will also be useful as a supplement to introductory courses in ecology

The biology of transient, unstable populations form the evolutionary stage used to describe events leading to the origin of new species, which is the theme of the present analysis. This problem is approached from different perspectives, ranging from population genetics, population ecology and developmental biology to the molecular level of evolution. Covering these main disciplines involved in the elucidation of evolutionary mechanisms, the present volume bridges the gap between molecularly orientated evolutionists and population biologists. Readers will find a high quality, well balanced set of theoretical and experimental articles authored by leading researchers in the field of evolutionary biology

This book provides the mathematical foundations for the analysis of a class of degenerate elliptic operators defined on manifolds with corners, which arise in a variety of applications such as population genetics, mathematical finance, and economics. The results discussed in this book prove the uniqueness of the solution to the Martingale problem and therefore the existence of the associated Markov process. Charles Epstein and Rafe Mazzeo use an ""integral kernel method"" to develop mathematical foundations for the study of such degenerate elliptic operators and the stochastic proces

Front Cover -- Integrated Population Biology and Modeling, Part B -- Copyright -- Contents -- Contributors -- Preface -- Section VI: Agent Based Models, Capture-Recapture Methods and Multi-Species Mutualism -- Chapter 1: An Agent-Based Model of the Spatial Distribution and Density of the Santa Cruz Island Fox -- 1. Introduction -- 2. Incorporating GIS Data into an ABM -- 2.1. GIS Data Types -- 2.2. Projections and Coordinate Systems for GIS Data -- 3. Model Description -- 3.1. Overview -- 3.1.1. Purpose -- 3.1.2. Entities, State Variables, and Scales -- 3.1.3. Process Overview -- 3.2. Design Concepts -- 3.2.1. Basic Principles -- 3.2.2. Emergence -- 3.2.3. Adaptation -- 3.2.4. Objectives -- 3.2.5. Learning -- 3.2.6. Prediction -- 3.2.7. Sensing -- 3.2.8. Interaction -- 3.2.9. Stochasticity -- 3.2.9.1. Decisions Using Random Number Generation -- 3.2.9.2. Decisions Using Random Selection of Entities -- 3.2.10. Collectives -- 3.2.11. Observation -- 3.3. Details -- 3.3.1. Initialization -- 3.3.2. Submodels -- Forage -- Disperse -- Make-Fox-Territory -- Set-Eagle-Breeding-Territories -- Breed-Foxes -- Birth -- Death -- Distribute-Food -- 4. Results -- 4.1. Results of Model Analysis Without Golden Eagle Predation -- 4.1.1. SCI Fox Carrying Capacity -- 4.1.2. SCI Fox Population Viability -- 4.1.3. SCI Fox Spatial Distribution -- 4.2. Model Results with Golden Eagle Predation -- 5. Conclusions and Discussion -- Acknowledgments -- Appendix -- Supplemental Resources -- References -- Chapter 2: Capture-Recapture Methods and Models: Estimating Population Size -- 1. Introduction -- 2. Closed Population Capture-Recapture Studies -- 2.1. Simple Beginnings: Lincoln-Petersen Estimator -- 2.1.1. Example: Mice Data -- 2.2. Multiple Capture Occasions -- 2.2.1. Schnabel Census -- 2.2.2. Capture Histories -- 2.2.3. Model Formulations -- Poisson Model

Front Cover -- Integrated Population Biology and Modeling, Part A -- Copyright -- Contents -- Contributors -- Preface -- Section I: Cellular Population Dynamics -- Chapter 1: Population Dynamics and Evolution of Cancer Cells -- 1. Introduction -- 2. Evolutionary Dynamics of Escape From Tissue Homeostasis -- 2.1. Mathematical Models of Tissue Homeostasis -- 2.2. Evolutionary Dynamics of Feedback Escape -- 2.3. Feedback, Stem Cell Enrichment, and Drug Resistance -- 3. Telomeres and the Evolutionary Potential of Cells -- 3.1. Replicative Limits and Cellular Hierarchy -- 3.2. Replicative Limits and Precancerous Mutations -- 3.3. Replicative Limits in a Growing Cell Population -- 4. Dynamics of Therapy Responses and Resistance Evolution -- 4.1. Dynamics Underlying Chemoprevention With Aspirin -- 5. Conclusions -- References -- Chapter 2: Stochastic and Deterministic Modeling of Cell Migration -- 1. Introduction -- 2. Cell Motility -- 2.1. Connecting Stochastic and Deterministic Models of Cell Movement -- 2.1.1. On-Lattice Models -- 2.1.1.1. Noninteracting Cells Undergoing Unbiased Movement -- 2.1.1.2. Excluding Cells -- 2.1.2. Off-Lattice Models -- 2.1.2.1. Noninteracting Cells Undergoing Unbiased Movement -- 2.1.2.2. Volume-Excluding Cells -- 2.2. Higher Dimensions -- 2.3. Higher Order Closure Approximations -- 3. Model Extensions -- 3.1. Cell Proliferation -- 3.2. Cell Interactions -- 3.2.1. Chemotaxis -- 3.2.2. Adhesion-Repulsion -- 3.2.3. Pushing and Pulling -- 3.3. Growing Domains -- 3.4. Persistence of Motion -- 4. Conclusion -- References -- Chapter 3: Data-Driven Mathematical Modeling of Microbial Community Dynamics -- 1. Introduction -- 2. Microbial Community Profiling -- 3. Mechanistic Modeling Approach -- 3.1. Derivation of Specific LV Systems -- 3.1.1. Derivation of Logistic Equation -- 3.1.2. Derivation of Competition Model