Sign in to turn on 1-Click ordering.
More Buying Choices
Have one to sell? Sell yours here
Sorry, this item is not available in
Image not available for
Image not available

Tell the Publisher!
I’d like to read this book on Kindle

Don't have a Kindle? Get your Kindle here, or download a FREE Kindle Reading App.

A Practical Guide to Ecological Modelling: Using R as a Simulation Platform [Paperback]

Karline Soetaert , Peter M.J. Herman
5.0 out of 5 stars  See all reviews (1 customer review)
RRP: £62.99
Price: £61.03 & FREE Delivery in the UK. Details
You Save: £1.96 (3%)
o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o
In stock.
Dispatched from and sold by Amazon. Gift-wrap available.
Want it tomorrow, 17 Sep.? Choose Express delivery at checkout. Details


Amazon Price New from Used from
Hardcover £62.99  
Paperback £61.03  

Book Description

19 Oct 2010 904817936X 978-9048179367 Softcover reprint of hardcover 1st ed. 2009

Mathematical modelling is an essential tool in present-day ecological research. Yet for many ecologists it is still problematic to apply modelling in their research. In our experience, the major problem is at the conceptual level: proper understanding of what a model is, how ecological relations can be translated consistently into mathematical equations, how models are solved, steady states calculated and interpreted. Many textbooks jump over these conceptual hurdles to dive into detailed formulations or the mathematics of solution. This book attempts to fill that gap. It introduces essential concepts for mathematical modelling, explains the mathematics behind the methods, and helps readers to implement models and obtain hands-on experience. Throughout the book, emphasis is laid on how to translate ecological questions into interpretable models in a practical way.

The book aims to be an introductory textbook at the undergraduate-graduate level, but will also be useful to seduce experienced ecologists into the world of modelling. The range of ecological models treated is wide, from Lotka-Volterra type of principle-seeking models to environmental or ecosystem models, and including matrix models, lattice models and sequential decision models. All chapters contain a concise introduction into the theory, worked-out examples and exercises. All examples are implemented in the open-source package R, thus taking away problems of software availability for use of the book. All code used in the book is available on a dedicated website.

Product details

  • Paperback: 390 pages
  • Publisher: Springer; Softcover reprint of hardcover 1st ed. 2009 edition (19 Oct 2010)
  • Language: English
  • ISBN-10: 904817936X
  • ISBN-13: 978-9048179367
  • Product Dimensions: 2 x 15.4 x 23 cm
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Bestsellers Rank: 1,599,990 in Books (See Top 100 in Books)
  • See Complete Table of Contents

More About the Author

Discover books, learn about writers, and more.

Product Description


"This is the book many of us were waiting for, maybe for longer than the time since R entered our computational toolbox." ... "To return to my first sentence, yes, this is the book I was waiting for. It exceeds my expectations and it is very practical with an optimal mix of theoretical and numerical topics. It is of particular use for aquatic ecologists, and definitely worth to be considered by ecologists from other fields." ...  "One point I very much enjoyed is the link between ecological, chemical and hydrophysical topics. I am not aware of any other book that brings these together in such a concise and understandable way. I completely agree with the authors that "this book is written for young researchers who want to get more out of their data than just description" and I warmly recommend it for all, who are young in mind. It helps to democratise modelling knowledge and provides a highly efficient method to supply ecologists with this urgently needed competence."
© 2009 Thomas Petzoldt


"This outstanding book provides a comprehensive and extremely clear treatment on the development, implementation, use and testing of ecological models. It embraces and covers the diverse approaches used by ecologists and biogeochemists; e.g. from simple food-web models to time-dependent transport-reaction models. Numerous, instructive examples are provided and implemented in R, a public domain programming language. I have successfully used a draft version for master courses on biogeochemical modeling and strongly recommend it to ecologists and biogeochemists interested to elucidate the functioning of natural ecosystems."
Jack J. Middelburg, Professor in Biogeochemistry and Senior Scientist at the Netherlands Institute of Ecology.

"Soetaert and Herman have provided an unexpected, back-door solution to producing cross-platform, ecological models.  Robust, cross-platform statistical packages have been difficult to find.  Moreover, many statisticians are not satisfied with black-box programs whose algorithms they have not checked.  To solve both problems simultaneously, many have moved to doing their statistics on the R platform.  R is a high-level, open-source programming language strong on both statistical computing and graphic output."
"Commercial providers of modeling software have been far better in providing cross-platform support than have statistical package providers.  Mathematica and Stella have focused on user friendliness of basic functions and graphing, making it easy to learn as you go.  Matlab has a somewhat steeper learning curve, but is blazingly fast with matrix operations on large data sets and sets of simulated data.  All are fairly expensive to license and upgrade.  I find R less intuitive than any of these other programs."
"Nevertheless, Soetaert and Herman make a good case for giving R a serious look as a modeling tool for reasons beyond the fact that it is available at no cost.  If you have already come in through the back door to R for its statistical uses, then the steep learning-curve argument is behind you.  Philosophically and functionally, there is good reason to want to model and analyze statistically in the same environment:  Modeling and hypothesis testing both progress fastest when they alternate iteratively.  Soetaert and Herman develop a very deliberate set of switchbacks up the learning curve by emphasizing model diversity and relatively easy examples.  The examples are the ones that have survived the sometimes brutally Darwinian process of teaching a class based on the draft book.  Examples are diverse enough that others can teach from the book and still develop an emphasis of their own choosing."
P. Jumars, Director, School of Marine Sciences, University of Maine

From the reviews:

“An ‘introductory text for ecological modelling for graduate and post-graduate students or others interested in making more out of their data’ … . This book is an excellent introductory text for mathematical biology … . It is a good resource for R-code with code for all the examples, figures and analyses being available in the book … . useful as a reference text introducing new topics and approaches for modelling. The book is well written, as are the mathematical descriptions, the concepts and the R-code.” (Louise Emmerson, Austral Ecology, Vol. 36 (e14), 2011)

From the Back Cover

Many texts on ecological models jump to describing either particular relations or computational results, without treating in detail the conceptual and mathematical basis of many steps in modelling: why set up models, what are basic conceptual models, how do conservation laws come in, how are models solved, what are steady states. This book is intended to bridge this gap. It is intended as an introductory text for graduate and post-graduate students, but also as a help for experienced ecologists who want to make more of their data by modelling. It contains many examples, all worked out in the open-source package R, providing the reader the opportunity to practice all methods and get hands-on experience.

This book will be of interest to advanced undergraduate and graduate students in ecology, biology, geology, bio-engineering, and to some extent students from physics and chemistry.

Inside This Book (Learn More)
Browse and search another edition of this book.
Browse Sample Pages
Front Cover | Copyright | Table of Contents | Excerpt | Index
Search inside this book:

Sell a Digital Version of This Book in the Kindle Store

If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store. Learn more

Customer Reviews

4 star
3 star
2 star
1 star
5.0 out of 5 stars
5.0 out of 5 stars
Most Helpful Customer Reviews
5.0 out of 5 stars R is good for simulation, as well as statistics 29 Jun 2014
Format:Paperback|Verified Purchase
This book is excellent and a fine introduction to using R for computer simulation. Its examples all come from ecology, but if you are not an ecologist, don't let that put you off.

The popular image of R is as a language for statistics and visualization, but under the hood, it is a universal engine for computing. So R is just like matlab, except that it is free and open source. It can perfectly well replace matlab in engineering and the physical sciences. This book is the best (only?) demonstration of the power, ease of use and versatility of R in this area.

The book combines teaching the basics of simulation with many worked examples. The appropriate code, is available on the author's web site. This approach makes it easy to get up and running. The aim is to get beginners producing interesting results as soon as possible.

Advanced material is indicated, so that beginners can avoid information overload.
Comment | 
Was this review helpful to you?
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com: 3.0 out of 5 stars  2 reviews
5.0 out of 5 stars Awesome book 18 July 2011
By Jan Galkowski - Published on Amazon.com
Format:Paperback|Verified Purchase
This is an awesome book, primarily about modeling, less about R. There are many "introduction to R" books available, perhaps too many.

This book and its accompanying software in the several R packages are an excellent way to both learn the material, and to explore other related problems.

Naturally, the course is primarily what you bring to it. Soetaert and Hermann provide a comprehensive introduction, heavily illustrated by examples. The mathematics is excellent, and essential.
1 of 6 people found the following review helpful
1.0 out of 5 stars A missed chance 2 Jun 2011
By eb - Published on Amazon.com
Format:Paperback|Verified Purchase
I bought this book to learn both about ecological modelling and about R. The latter was impossible for 2 reasons:
- the R code was printed in a font that made it impossible to distinguish the letter "l" from the figure "1".
- Beyond this, there are errors in the printed R code which I could not identify because there is no systematic introduction to R, which however would be required to understand the error messages produced by R.

As to the introduction to ecological modelling, I got to page 104 before giving up. The writing style is just too entrancing.
Were these reviews helpful?   Let us know
Search Customer Reviews
Only search this product's reviews

Customer Discussions

This product's forum
Discussion Replies Latest Post
No discussions yet

Ask questions, Share opinions, Gain insight
Start a new discussion
First post:
Prompts for sign-in

Search Customer Discussions
Search all Amazon discussions

Look for similar items by category