The majority of evolutionary processes, such as major phenotypic changes and
the origin of new species, take place over time periods too long to study
experimentally. Consequently, comparative biology has long been an important
resource in the study of *macroevolution*: evolution over thousands of
generations to millions of years. *Phylogenetic comparative methods* is the
discipline in which a phylogeny is used - often jointly with phenotypic
observations for species - to study the process and pattern of evolutionary
change through time and among taxa. This workshop focuses on teaching the
theory, implementation, and use of phylogenetic comparative methods, with
particular attention to methods implemented for the *R statistical computing
environment*.

__Location__: Sala de Usos Múltiples, Laboratorio Nacional de Ciencias de la Sostenibilidad (LANCIS), Instituto de Ecología, UNAM. Circuito Exterior S/N, Ciudad Universitaria, UNAM.

__Times__: 10 am to 6 pm, lunch 1:30 - 3:00 pm. Lunches will be served at the venue for all students.

__Contact in case of emergency__: Dr. Alejandro Gonzalez Voyer, cell phone (044) 55 6791 1458.

We recommend installing the most recent available version of R (https://www.r-project.org). For Mac users, we also encourage the installation of Rstudio (https://www.rstudio.com/). If you have any prior experience working with R, we also recommend you pre-install the most recent version of a number of R phylogenetics packages and their dependencies. More information can be found here.

More advanced users of R may also want to review this very basic tutorial on the use of *rmarkdown* (an R extension of the popular language known as markdown) that is very useful in building reproducible data analysis pipelines, including for the exercises of this course: example R markdown, example markdown built with *knitr*, *knitr* R package.

- Introduction of instructors & students.
- Introduction to the phylogenetic comparative method. [PDF]
- Exercise 1: Introduction the basics of the R statistical computing environment. [URL]
- Exercise 2: Introduction to reading, writing, manipulating, and visualizing phylogenies and comparative data in R. [URL]
- Brownian motion and phylogenetically independent contrasts. [PDF]
- Exercise 3: Phylogenetically independent contrasts in R. [URL]
- Challenge problem 1: Challenge problem on contrasts regression. [problem, solution]

- Phylogenetic generalized least squares. [PDF]
- Excerise 4: Phylogenetic generalized least squares regression. [URL]
- Challenge problem 2: PGLS. [problem, solution]
- Other models of continuous character evolution on trees. [PDF]
- Exercise 5: Fitting models of continuous character evolution. [URL]
- Discrete character evolution on phylogenies. [PDF]

- Exercise 6: Fitting discrete character evolution models to phylogenetic data in R. [URL]
- Challenge problem 3: Discrete character evolution. [problem, solution]
- Ancestral state reconstruction for discrete & continuous characters. [PDF]
- Exercise 7: Ancestral state reconstruction. [URL]
- Challenge problem 4: Stochastic mapping discrete characters on a phylogeny. [problem, solution]
- Pagel’s model for correlated binary trait evolution. [PDF]
- Exercise 8: Pagel’s model for studysing the evolutionary correlation of discrete characters. [URL]
- Challenge problem 5: Examining the limitations of Pagel’s (1994) method. [problem, solution]

- Introduction to multi-rate and multi-regime models of continuous character evolution. [PDF]
- Exercise 9: Multi-rate, multi-regime, and multivariate models for continuous trait evolution. [URL]
- Using reconstructed phylogenies to study the dynamics of species diversification. [PDF]
- Exercies 10: Introduction to studying diversification on phylogenies. [URL]
- Exercise 11: Fitting state-dependent diversification models in R using diversitree. [URL]
- Course evaluation survey. [URL]
- Exercise 12: Visualizing phylogenies and comparative data in R. [URL]
- Discussion & wrap-up.

*Course co-taught by Michael Alfaro, Ricardo Betancur, Alejandro Gonzalez-Voyer, Luke Harmon, & Liam Revell. 26-29 June 2018.*

Co-organized by Alejandro Gonzalez-Voyer (Universidad Nacional Autónoma de México) and Liam Revell (University of Massachusetts Boston), and funded by the National Science Foundation.