A Biologist s Guide to Mathematical Modeling in Ecology and Evolution

Author: Sarah P. Otto
Publisher: Princeton University Press
ISBN: 9781400840915
Release Date: 2011-09-19
Genre: Science

Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available

A Biologist s Guide to Mathematical Modeling in Ecology and Evolution

Author: Sarah P. Otto
Publisher: Princeton University Press
ISBN: 9780691123448
Release Date: 2007-03-12
Genre: Mathematics

Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available

Elements of Mathematical Ecology

Author: Mark Kot
Publisher: Cambridge University Press
ISBN: 9781316584057
Release Date: 2001-07-19
Genre: Nature

Elements of Mathematical Ecology provides an introduction to classical and modern mathematical models, methods, and issues in population ecology. The first part of the book is devoted to simple, unstructured population models that ignore much of the variability found in natural populations for the sake of tractability. Topics covered include density dependence, bifurcations, demographic stochasticity, time delays, population interactions (predation, competition, and mutualism), and the application of optimal control theory to the management of renewable resources. The second part of this book is devoted to structured population models, covering spatially-structured population models (with a focus on reaction-diffusion models), age-structured models, and two-sex models. Suitable for upper level students and beginning researchers in ecology, mathematical biology and applied mathematics, the volume includes numerous clear line diagrams that clarify the mathematics, relevant problems thoughout the text that aid understanding, and supplementary mathematical and historical material that enrich the main text.

Modelling for Field Biologists and Other Interesting People

Author: Hanna Kokko
Publisher: Cambridge University Press
ISBN: 9781139463652
Release Date: 2007-06-28
Genre: Medical

Students of evolutionary and behavioural ecology are often unfamiliar with mathematical techniques, though much of biology relies on mathematics. Evolutionary ideas are often complex, meaning that the logic of hypotheses proposed should not only be tested empirically but also mathematically. There are numerous different modelling tools used by ecologists, ranging from population genetic 'bookkeeping', to game theory and individual-based computer simulations. Due to the many different modelling options available, it is often difficult to know where to start. Hanna Kokko has designed this 2007 book to help with these decisions. Each method described is illustrated with one or two biologically interesting examples that have been chosen to help overcome fears of many biologists when faced with mathematical work, whilst also providing the programming code (Matlab) for each problem. Aimed primarily at students of evolutionary and behavioural ecology, this book will be of interest to any biologist interested in mathematical modelling.

Essential Mathematical Biology

Author: Nicholas F. Britton
Publisher: Springer Science & Business Media
ISBN: 9781447100492
Release Date: 2012-12-06
Genre: Mathematics

This self-contained introduction to the fast-growing field of Mathematical Biology is written for students with a mathematical background. It sets the subject in a historical context and guides the reader towards questions of current research interest. A broad range of topics is covered including: Population dynamics, Infectious diseases, Population genetics and evolution, Dispersal, Molecular and cellular biology, Pattern formation, and Cancer modelling. Particular attention is paid to situations where the simple assumptions of homogenity made in early models break down and the process of mathematical modelling is seen in action.

Mathematical Models of Social Evolution

Author: Richard McElreath
Publisher: University of Chicago Press
ISBN: 9780226558288
Release Date: 2008-09-15
Genre: Social Science

Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field. Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own.

How to be a Quantitative Ecologist

Author: Jason Matthiopoulos
Publisher: John Wiley & Sons
ISBN: 1119991722
Release Date: 2011-04-12
Genre: Mathematics

Ecological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This textbook provides a practical introduction to quantitative ecology for students and practitioners who have realised that they need this opportunity. The text is addressed to readers who haven't used mathematics since school, who were perhaps more confused than enlightened by their undergraduate lectures in statistics and who have never used a computer for much more than word processing and data entry. From this starting point, it slowly but surely instils an understanding of mathematics, statistics and programming, sufficient for initiating research in ecology. The book’s practical value is enhanced by extensive use of biological examples and the computer language R for graphics, programming and data analysis. Key Features: Provides a complete introduction to mathematics statistics and computing for ecologists. Presents a wealth of ecological examples demonstrating the applied relevance of abstract mathematical concepts, showing how a little technique can go a long way in answering interesting ecological questions. Covers elementary topics, including the rules of algebra, logarithms, geometry, calculus, descriptive statistics, probability, hypothesis testing and linear regression. Explores more advanced topics including fractals, non-linear dynamical systems, likelihood and Bayesian estimation, generalised linear, mixed and additive models, and multivariate statistics. R boxes provide step-by-step recipes for implementing the graphical and numerical techniques outlined in each section. How to be a Quantitative Ecologist provides a comprehensive introduction to mathematics, statistics and computing and is the ideal textbook for late undergraduate and postgraduate courses in environmental biology. "With a book like this, there is no excuse for people to be afraid of maths, and to be ignorant of what it can do." —Professor Tim Benton, Faculty of Biological Sciences, University of Leeds, UK

Data driven Modelling of Structured Populations

Author: Stephen P. Ellner
Publisher: Springer
ISBN: 9783319288932
Release Date: 2016-05-13
Genre: Mathematics

This book is a “How To” guide for modeling population dynamics using Integral Projection Models (IPM) starting from observational data. It is written by a leading research team in this area and includes code in the R language (in the text and online) to carry out all computations. The intended audience are ecologists, evolutionary biologists, and mathematical biologists interested in developing data-driven models for animal and plant populations. IPMs may seem hard as they involve integrals. The aim of this book is to demystify IPMs, so they become the model of choice for populations structured by size or other continuously varying traits. The book uses real examples of increasing complexity to show how the life-cycle of the study organism naturally leads to the appropriate statistical analysis, which leads directly to the IPM itself. A wide range of model types and analyses are presented, including model construction, computational methods, and the underlying theory, with the more technical material in Boxes and Appendices. Self-contained R code which replicates all of the figures and calculations within the text is available to readers on GitHub. Stephen P. Ellner is Horace White Professor of Ecology and Evolutionary Biology at Cornell University, USA; Dylan Z. Childs is Lecturer and NERC Postdoctoral Fellow in the Department of Animal and Plant Sciences at The University of Sheffield, UK; Mark Rees is Professor in the Department of Animal and Plant Sciences at The University of Sheffield, UK.

Handbook of Meta analysis in Ecology and Evolution

Author: Julia Koricheva
Publisher: Princeton University Press
ISBN: 9780691137292
Release Date: 2013
Genre: Mathematics

Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets

Structural Equation Modeling

Author: Bruce H. Pugesek
Publisher: Cambridge University Press
ISBN: 1139435396
Release Date: 2003-01-23
Genre: Nature

Structural equation modelling (SEM) is a technique that is used to estimate, analyse and test models that specify relationships among variables. The ability to conduct such analyses is essential for many problems in ecology and evolutionary biology. This book begins by explaining the theory behind the statistical methodology, including chapters on conceptual issues, the implementation of an SEM study and the history of the development of SEM. The second section provides examples of analyses on biological data including multi-group models, means models, P-technique and time-series. The final section of the book deals with computer applications and contrasts three popular SEM software packages. Aimed specifically at biological researchers and graduate students, this book will serve as valuable resource for both learning and teaching the SEM methodology. Moreover, data sets and programs that are presented in the book can also be downloaded from a website to assist the learning process.

The Theoretical Biologist s Toolbox

Author: Marc Mangel
Publisher: Cambridge University Press
ISBN: 9781139455862
Release Date: 2006-07-27
Genre: Science

Mathematical modelling is widely used in ecology and evolutionary biology and it is a topic that many biologists find difficult to grasp. In this new textbook Marc Mangel provides a no-nonsense introduction to the skills needed to understand the principles of theoretical and mathematical biology. Fundamental theories and applications are introduced using numerous examples from current biological research, complete with illustrations to highlight key points. Exercises are also included throughout the text to show how theory can be applied and to test knowledge gained so far. Suitable for advanced undergraduate courses in theoretical and mathematical biology, this book forms an essential resource for anyone wanting to gain an understanding of theoretical ecology and evolution.

Foundations of Social Evolution

Author: Steven A. Frank
Publisher: Princeton University Press
ISBN: 0691059349
Release Date: 1998
Genre: Science

This is a masterly theoretical treatment of one of the central problems in evolutionary biology, the evolution of social cooperation and conflict. Steven Frank tackles the problem with a highly original combination of approaches: game theory, classical models of natural selection, quantitative genetics, and kin selection. He unites these with the best of economic thought: a clear theory of model formation and comparative statics, the development of simple methods for analyzing complex problems, and notions of information and rationality. Using this unique, multidisciplinary approach, Frank makes major advances in understanding the foundations of social evolution. Frank begins by developing the three measures of value used in biology--marginal value, reproductive value, and kin selection. He then combines these measures into a coherent framework, providing the first unified analysis of social evolution in its full ecological and demographic context. Frank also extends the theory of kin selection by showing that relatedness has two distinct meanings. The first is a measure of information about social partners, with close affinity to theories of correlated equilibrium and Bayesian rationality in economic game theory. The second is a measure of the fidelity by which characters are transmitted to future generations--an extended notion of heritability. Throughout, Frank illustrates his methods with many examples, including a complete reformulation of the theory of sex allocation. The book also provides a unique "how-to" guide for constructing models of social behavior. It is essential reading for evolutionary biologists and for economists, mathematicians, and others interested in natural selection.

The Comparative Approach in Evolutionary Anthropology and Biology

Author: Charles L. Nunn
Publisher: University of Chicago Press
ISBN: 9780226608983
Release Date: 2011-11-30
Genre: Science

Comparison is fundamental to evolutionary anthropology. When scientists study chimpanzee cognition, for example, they compare chimp performance on cognitive tasks to the performance of human children on the same tasks. And when new fossils are found, such as those of the tiny humans of Flores, scientists compare these remains to other fossils and contemporary humans. Comparison provides a way to draw general inferences about the evolution of traits and therefore has long been the cornerstone of efforts to understand biological and cultural diversity. Individual studies of fossilized remains, living species, or human populations are the essential units of analysis in a comparative study; bringing these elements into a broader comparative framework allows the puzzle pieces to fall into place, creating a means of testing adaptive hypotheses and generating new ones. With this book, Charles L. Nunn intends to ensure that evolutionary anthropologists and organismal biologists have the tools to realize the potential of comparative research. Nunn provides a wide-ranging investigation of the comparative foundations of evolutionary anthropology in past and present research, including studies of animal behavior, biodiversity, linguistic evolution, allometry, and cross-cultural variation. He also points the way to the future, exploring the new phylogeny-based comparative approaches and offering a how-to manual for scientists who wish to incorporate these new methods into their research.

The Causes of Molecular Evolution

Author: John H. Gillespie
Publisher: Oxford University Press
ISBN: 0195357744
Release Date: 1994-05-26
Genre: Science

This work provides a unified theory that addresses the important problem of the origin and maintenance of genetic variation in natural populations. With modern molecular techniques, variation is found in all species, sometimes at astonishingly high levels. Yet, despite these observations, the forces that maintain variation within and between species have been difficult subjects of study. Because they act very weakly and operate over vast time scales, scientists must rely on indirect inferences and speculative mathematical models. However, despite these obstacles, many advances have been made. The author's research in molecular genetics, evolution, and bio-mathematics has enabled him to draw on this work, and present a coherent and valuable view of the field. The book is divided into three parts. The first consists of three chapters on protein evolution, DNA evolution, and molecular mechanisms. This section reviews the experimental observations on genetic variation. The second part gives a unified treatment of the mathematical theory of selection in a fluctuating environment. The final two chapters combine the earlier assessments in a treatment of the scientific status of two competing theories for the maintenance of genetic variation. Steeped in the enormous advances population genetics has made over the past 25 years, this book has proven highly popular among human geneticists, biologists, evolutionary theorists, and bio-mathematicians.