From the reviews: "...I found the text to be an excellent foray into ecological models using R. I plan to use this book in my upcoming modeling course for upper-level undergraduates, a course cross-listed in the math and biology departments. The models will present some challenges for my students but I think the pace of the text will work for them. In addition, many of my students will be new to R, and to programming, but the text does a great job of integrating an introduction to R with the models. I can see this book being valuable to graduate students and research ecologists wishing to work with these foundational models in R. It is now time to jump into R!" (Ecology, 91(4), 2010) "Ecology is a complex discipline that can best be understood by making suitable abstractions, or models. The simplest mathematical models are composed of general rules and rarely require more than two equations. These models have the advantage that they apply to a variety of systems. The book...primarily focuses on population dynamics, a field where such simple models are commonly used. ...the novelty lies in the tools that are used to make the theory work and that will undoubtedly bring this type of analysis closer to the individual researcher and the students. ...Undoubtedly, this book will contribute to the further democratization of mathematical modeling and the use of R in this field. Given the variety of the topics covered, the highly readable text, and the ready-to-use code excerpts, I consider the book an absolute must for those who are active or intend to work in the field of population modeling." (Journal of Statistical Software, January 2010, Vol. 32, Book Review 3) "This volume fills an important niche in the ecology textbook community. Like other primers, this book covers many of the core concepts of ecology, particularly population ecology, but Stevens goes into greater depth, presenting many of the complexities of core ecological processes. ... an excellent volume for graduate-level courses in ecology and will be useful to ecologists who desire to refamiliarize themselves with core ecological concepts while learning computational analysis and modeling techniques." (Matthew Aiello-Lammens, The Quarterly Review of Biology, Vol. 85 (3), 2010)

• Single Species Populations.- Simple Density-independent Growth.- Density-independent Demography.- Density-dependent Growth.- Populations in Space.- Two-species Interactions.- Lotka–Volterra Interspecific Competition.- Enemy–Victim Interactions.- Special Topics.- An Introduction to Food Webs, and Lessons from Lotka–Volterra Models.- Multiple Basins of Attraction.- Competition, Colonization, and Temporal Niche Partitioning.- Community Composition and Diversity.

From the reviews: "...I found the text to be an excellent foray into ecological models using R. I plan to use this book in my upcoming modeling course for upper-level undergraduates, a course cross-listed in the math and biology departments. The models will present some challenges for my students but I think the pace of the text will work for them. In addition, many of my students will be new to R, and to programming, but the text does a great job of integrating an introduction to R with the models. I can see this book being valuable to graduate students and research ecologists wishing to work with these foundational models in R. It is now time to jump into R!" (Ecology, 91(4), 2010) "Ecology is a complex discipline that can best be understood by making suitable abstractions, or models. The simplest mathematical models are composed of general rules and rarely require more than two equations. These models have the advantage that they apply to a variety of systems. The book...primarily focuses on population dynamics, a field where such simple models are commonly used. ...the novelty lies in the tools that are used to make the theory work and that will undoubtedly bring this type of analysis closer to the individual researcher and the students. ...Undoubtedly, this book will contribute to the further democratization of mathematical modeling and the use of R in this field. Given the variety of the topics covered, the highly readable text, and the ready-to-use code excerpts, I consider the book an absolute must for those who are active or intend to work in the field of population modeling." (Journal of Statistical Software, January 2010, Vol. 32, Book Review 3) "This volume fills an important niche in the ecology textbook community. Like other primers, this book covers many of the core concepts of ecology, particularly population ecology, but Stevens goes into greater depth, presenting many of the complexities of core ecological processes. ... an excellent volume for graduate-level courses in ecology and will be useful to ecologists who desire to refamiliarize themselves with core ecological concepts while learning computational analysis and modeling techniques." (Matthew Aiello-Lammens, The Quarterly Review of Biology, Vol. 85 (3), 2010)

• Single Species Populations.- Simple Density-independent Growth.- Density-independent Demography.- Density-dependent Growth.- Populations in Space.- Two-species Interactions.- Lotka–Volterra Interspecific Competition.- Enemy–Victim Interactions.- Special Topics.- An Introduction to Food Webs, and Lessons from Lotka–Volterra Models.- Multiple Basins of Attraction.- Competition, Colonization, and Temporal Niche Partitioning.- Community Composition and Diversity.

From the reviews: "...I found the text to be an excellent foray into ecological models using R. I plan to use this book in my upcoming modeling course for upper-level undergraduates, a course cross-listed in the math and biology departments. The models will present some challenges for my students but I think the pace of the text will work for them. In addition, many of my students will be new to R, and to programming, but the text does a great job of integrating an introduction to R with the models. I can see this book being valuable to graduate students and research ecologists wishing to work with these foundational models in R. It is now time to jump into R!" (Ecology, 91(4), 2010) "Ecology is a complex discipline that can best be understood by making suitable abstractions, or models. The simplest mathematical models are composed of general rules and rarely require more than two equations. These models have the advantage that they apply to a variety of systems. The book...primarily focuses on population dynamics, a field where such simple models are commonly used. ...the novelty lies in the tools that are used to make the theory work and that will undoubtedly bring this type of analysis closer to the individual researcher and the students. ...Undoubtedly, this book will contribute to the further democratization of mathematical modeling and the use of R in this field. Given the variety of the topics covered, the highly readable text, and the ready-to-use code excerpts, I consider the book an absolute must for those who are active or intend to work in the field of population modeling." (Journal of Statistical Software, January 2010, Vol. 32, Book Review 3) "This volume fills an important niche in the ecology textbook community. Like other primers, this book covers many of the core concepts of ecology, particularly population ecology, but Stevens goes into greater depth, presenting many of the complexities of core ecological processes. ... an excellent volume for graduate-level courses in ecology and will be useful to ecologists who desire to refamiliarize themselves with core ecological concepts while learning computational analysis and modeling techniques." (Matthew Aiello-Lammens, The Quarterly Review of Biology, Vol. 85 (3), 2010)

• Single Species Populations.- Simple Density-independent Growth.- Density-independent Demography.- Density-dependent Growth.- Populations in Space.- Two-species Interactions.- Lotka–Volterra Interspecific Competition.- Enemy–Victim Interactions.- Special Topics.- An Introduction to Food Webs, and Lessons from Lotka–Volterra Models.- Multiple Basins of Attraction.- Competition, Colonization, and Temporal Niche Partitioning.- Community Composition and Diversity.