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A Primer Of Ecology With R (Use R!)
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Provides simple explanations of the important concepts in population and community ecology. Provides R code throughout, to illustrate model development and analysis, as well as appendix introducing the R language. Interweaves ecological content and code so that either stands alone. Supplemental web site for additional code.

Series: Use R!

Paperback: 388 pages

Publisher: Springer; 1st ed. 2009 edition (June 11, 2009)

Language: English

ISBN-10: 0387898816

ISBN-13: 978-0387898810

Product Dimensions: 6.1 x 1 x 9.2 inches

Shipping Weight: 1.6 pounds (View shipping rates and policies)

Average Customer Review: 4.0 out of 5 stars  See all reviews (3 customer reviews)

Best Sellers Rank: #759,687 in Books (See Top 100 in Books) #173 in Books > Computers & Technology > Computer Science > Computer Simulation #176 in Books > Textbooks > Medicine & Health Sciences > Research > Biostatistics #316 in Books > Medical Books > Basic Sciences > Biostatistics

This is an excellent introduction to ecological modeling and to programming in R. Unlike most text books, even those that focus on modeling, Stevens provides both the equations and the code necessary to implement the models and graph the output. He also provides occasional asides on how models can be derived through numeric estimation or simulation. He has an expansive works cited and covers a broad range of ecology, from classic Lotka-Voltera to modern models in community ecology. I've gone through much of this book on my own and will probably read it from beginning to end before my comprehensive exams.The text is direct and the code often no-nonsense and sparsely annotated - this is not an introductory text for either ecology or programming. The goal appears to be to provide you with the essential code for creating graphs that you can examine closely yourself, fuss with the parameters to see what happens, and be able to explore graphically the logic and output of the models He doesn't always walk you through every step of the derivation of the models or the logic behind the code, but does provides an intro to programming in R in the back and he employs several approaches to programming and templates for coding. In the end this book does make an excellent guide to programming because it provides numerous examples of different ways to solve programming and modeling problems. He also employs lots of code for adding text, arrows, and other tidbits to plot to make model output more readable - code that I am personally pilfering almost daily in my own work. This book does not focus on ecological statistics or using R as a statistics platform. Much of the code, however, is useful for manipulating data and creating functions that can extract information from data.

First of all, there is a free version of this available for download via .pdf. The .pdf has some minor clerical errors but is identical to the book. If you need this for a class and don't want to pay for something you might not use again, just search for it online. You could also download the .pdf and see what you are buying before you make the leap. I got the pdf and decided I wanted it in print so I could read the material prior to attempting the code. If you aren't familiar with R, then you may want to consider supplementing this book with some walk-troughs, available online was well. Good luck and have fun in R.

This primer provides an excellent, upper-level, introduction to theoretical and simulation ecology. Working through the presented R code and exercises provides a deeper understanding of the thinking of many of the most famous theoretical ecologists, while also introducing the methods by which students can examine ecological questions through simulation.

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