lefko3: a gentle introduction
Creating and analyzing matrix projection models in R
This book is dedicated to the people of Ukraine, who are teaching the world every day that all people have the inherent human right to self-determination.
Matrix projection models (MPMs) have been used by ecologists for nearly a century now. Particularly since the 1990s, software packages have occasionally come onto the market offering students of population ecology a means of building or, more often, analyzing specific types of MPMs. However, as far as I am aware, no one has ever attempted to put together all the different forms of MPMs into one main package that would both build and analyze them. Package
lefko3 is an attempt to fill that void. In filling that void,
lefko3 provides a one-step programming environment for MPM analysis.
lefko3 not only builds all kinds of MPMs, including discretized IPMs, but also provides a variety of functions that standardize the process and make it easier. One perennial issue that crops up when population ecologists collaborate, for example, is that everyone has their own way of entering data, and translating that into the proper format can be truly time consuming.
lefko3 offers functions that standardize demographic data regardless of what format that they are organized in, and also provides standardized programming objects for the matrix models and further analytical objects. Graduate students and natural areas managers should find
lefko3 particularly useful for its simplicity in developing common analyses. Advanced population ecologists should find it useful for its flexibility in creating custom projections, including simulations of density dependent and stochastic runs involving patch dynamics.
lefko3 is a free, open-source package made for the R programming language. R is a free, open-source programming language based on the S+ programming language, and is now the most commonly used programming language for statistical analysis. Packages are available from a variety of sources, but the most stable and well-supported packages are available natively through CRAN, which also maintains R itself. Package
lefko3 is available through R’s native
install.packages() context and through CRAN’s lefko3 page, with developmental versions also available on R Forge’s lefko3 page.
This book was written as intro to MPM analysis using
lefko3. It i based roughly on Evan Cooch and Gary White’s classic (and continually evolving) Program Mark: A Gentle Introduction (http://www.phidot.org/software/mark/docs/book/). As such, this book can be thought of as a short course on using
lefko3, and just as in the program MARK case, this book will keep growing and evolving as we develop more content both for package
lefko3 and for this book. Ultimately, this is because although vignettes are provided within
lefko3, space limitations on CRAN-based vignettes prevent the incorporation of key details and lengthy explanations, and it is just these details and lengthy explanations that can often help students understand how to use new analytical software. This book attempts to deal with these weaknesses of the vignettes by taking users step by step through the building and analysis of MPMs, even offering some of the theory behind population ecology along the way. Note, however, that this book is not a substitute for a good ecology textbook, but should be used in conjunction with one for the best possible understanding.
As with all such projects, this book is a work in progress. The author encourages readers who find mistakes or issues, or who simply have questions along the way, to contact him.
This book is organized into four main parts. Chapters 1, 2, and 3 deal with theory and data preparation required prior to the development of matrices. Chapters 4 through 7 introduce the different matrix projection models and illustrate how they are created. Chapters 8 through 10 are focused on analysis, currently including deterministic, stochastic, cyclical, and density dependent analyses, and custom projections. Finally, chapter 11 deals with issues and extensions in developing and analyzing MPMs.
We are planning to expand this book with several more chapters. Currently, these include planned chapters on LTRE and sLTRE analysis, transient dynamics, demographic stochasticity and individual-based simulation, and adaptive dynamics. These chapters and others will be developed as we introduce new functions and procedures to
I wish to thank all of the people who have contributed to this work. E. Holton provided discussion and feedback throughout the writing of this book, and also tested code and procedures. J. Nagata provided a sounding board for ideas. The University of Tokyo provided a place to sit and think. And the Japan Society for the Promotion of Science provided grant-in-aid 19H03298, which funded the development of this work and of