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A Biologist's Guide to Mathematical Modeling in Ecology and Evolution Hardcover – Illustrated, 22 May 2007
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- Publisher : Princeton University Press; 1st edition (22 May 2007)
- Language : English
- Hardcover : 744 pages
- ISBN-10 : 0691123446
- ISBN-13 : 978-0691123448
- Dimensions : 20.32 x 4.45 x 25.4 cm
- Best Sellers Rank: 145,774 in Books (See Top 100 in Books)
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From the Back Cover
"A wonderfully pedagogical introduction to mathematical modeling in population biology: an ideal first course for biologists."--Simon A. Levin, Princeton University
"This book is an amazing teaching resource for developing a comprehensive understanding of the methods and importance of biological modeling. But more than that, this book should be read by every student of evolutionary biology and ecology so that they can come to a deeper appreciation of the fundamental ideas and models that underlie these fields."--Patrick C. Phillips, University of Oregon
"There is an increasing use of mathematics throughout the biological sciences, yet the training of most biologists still woefully lacks crucial mathematical tools. Sally Otto and Troy Day are themselves two masters at the deft use of theoretical models to crystallize conceptual insights about ecological and evolutionary problems, and in this wonderful book they make accessible to a broad audience the essential mathematical tool kit biologists need, both to read the literature and to craft and analyze models themselves."--Robert D. Holt, University of Florida
"I am often asked by biologists to recommend a book on mathematical modeling, but I must tell them that there is no single good book that will guide them through the difficult first stages of learning to make models. Otto and Day's book fills the gap. The quality is high throughout, the scholarship is sound, the book is comprehensive. The authors are both first-rate scientists. I think this will be a classic."--Steven A. Frank, author of Immunology and Evolution of Infectious Disease
"This book provides a general introduction to mathematical modeling--in particular, to population modeling--in the biological sciences. This past year I taught a 400-level course in mathematical modeling of biological systems, and I had to do so without a textbook because no adequate text existed. Otto and Day's book would have met my needs beautifully. This book is an important addition to the field."--Carl Bergstrom, University of Washington
"This book has the ambitious and worthy goal of teaching biologists enough about modeling and about mathematical methods to be both intelligent consumers of models and competent creators of their own models. Its concentration on the process of building rather than analyzing models is its strongest point."--Frederick R. Adler, author of Modeling the Dynamics of Life: Calculus and Probability for Life Scientists
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I am very happy about buying this book.
The book starts with an intro into HIV dynamics, quite unlike the equation mouthing, yet great book by Dr. Nowak- Evolutionary Dynamics: Exploring the Equations of Life . The book then goes onto explain model building from scratch, explaining classical models in biology, and introducing various graphical techniques, different mathematical models used in biology and ending with a huge section devoted to probablistic models. All of these chapters contain small primers teaching the reader the basic maths used in the book. Also, the appendix consists of a detailed intro on various mathematical techniques used in the book, even calculus :)
The only down side of the book, is a lack of online resources. Though the book references a website for more resources, but it falls short of anything substantial.
Other than this shortcoming, the book is a big thumbs-up!!! Kudos to the authors
The first chapters of this book are very gentle and easy to read. I found particularly useful the 2nd chapter, on How to Construct a Model, when writing my graduate research project on ecological modeling. I also thought the appendixes were very useful, because they make this book self contained. This makes it an advisable book for anyone starting in the modeling field and studying by himself. In the last chapters of the book, the authors address more advance models that are quite interesting but also more complex. I found that this part is the hardest to follow, specially the two chapters dedicated to stochastic modeling, it feels like there is a missing appendix here. This couple of chapters should be compared to Marc Mangel's The Theoretical Biologist's Toolbox, who also offers a fine introduction into stochastic modeling.
The biggest lack I found in this text is in the computational implementation of the analysis, the authors offer some supplementary material at their website and the scripts to generate the figures in Mathematica. Nevertheless, I found the scripts uneasy to follow and reproduce, not to mention that Mathematica is a expensive software.