Syllabus
1. Intro to evolutionary data (evolution in molecular, geographic and functional data, public databases, overview of concepts and methods on phylogeny construction, compiling, manipulating and editing trees for further analysis in R, constructing supertrees and consensus trees, time-calibrating trees in R) (MRBAYES, BEAST, FigTree, R) READING: Felsenstein 2003, Donoghue and Benton 2007. 2.
Evolution of phenotypes, life histories and trade-offs (models of trait evolution, ancestral reconstructions, coevolution of traits and species, rate of trait evolution, phylogenetic signal, niche conservatism, reconstruction of the niche, evolution in the niche space) (APE, GEIGER) READING: Wiens and Donoghue 2004, Felsenstein 1985. 3. Evolution of communities (species and phylogenetic diversity, community phylogenetics, overdispersion and clustering at the phylogenetic and phenotypic level, delimitation of species pools, dispersal, null models, inferring competition from community structure) (PHYLOCOM, PICANTE) READING: Webb et al. 2000, Cavender-Barres et al. 2004. 4.
Evolution of geographic patterns (biogeography & macroecology) (historical biogeography, reconstruction of past dispersal, models colonization and dispersal, evolution in island biogeography) (BIOGEOBEARS, LAGRANGE, DIVA) READING: Mittelbach et al. 2007, Schluter and Pennell 2017. 5. Evolution of higher taxa (speciation formation, diversification) (genetic and ecological formation of species, speciation and extinction, diversification, background extinction, causes of mass extinctions, inferring diversification dynamics from phylogenies, ecology of the diversification process, state-dependent diversification models) (BAMM, REVBAYES, LASER) READING: Benton and Emerson 2007, Rabosky and Glor 2010.
Annotation
The course intends to develop and sharpen evolutionary thinking, based on solving conceptual problems using concrete methods and examples. The methods and examples take advantage of statistical approaches (phylogenetic comparative methods, diversification analyses, ancestral reconstructions, GIS) broadly used to address key questions in ecology and evolution (community structure, evolution of life histories, biogeography, macroevolution). Students will consequently learn how to define an evolutionary question, design the methodology for solving such question, and practically implement the solution using proper statistical tools, especially in R. The course covers five related areas: (1) Intro to evolutionary data, (2) Evolution of life-history, (3) Evolution of ecological communities, (4) Evolution of geographic patterns, (5) Evolution of higher taxa. No pre-requisite courses are required. But undergraduate-level understanding of evolution and ecology is expected. Preliminary knowledge of R will increase the benefits of taking the course, but is not needed to for its successful completion. The course is built to provide the most practical tools to address relevant biological problems, such as those commonly addressed in master’s theses and dissertations. The course runs in English, Czech, or some combination of both, depending on the language and the preferences of the students.