“Methods in Ecology and Evolution” will introduce you to fundamental concepts in ecology and evolution and show how the two disciplines intersect in terms of research questions and methodologies. Selected topics (e.g. speciation, molecular evolution and biological invasions) each drawn from current research in the department of GEE are discussed in more detail, and each is accompanied by a dataset to be analysed in practicals. You will use statistical methods introduced in BIOL0001 “Quantitative Biology” to explore and analyse ecological and evolutionary datasets related to each topic. A substantial part of the practicals is devoted to introducing the fundamentals of computer programming, using the R language. You will learn how to write simple programs in R to analyse data and be introduced to bioinformatics. After completing all the practicals you will be asked to analyse a dataset and report on your findings in the form of a scientific paper.


By the end of the module you will have gained practical experience in R programming, and in using a variety of quantitative approaches to explore and analyse different kinds of data. You will have learned, first-hand, about research being carried out in the department and have been introduced to scientific paper writing.


Learning objectives
●    Learn basic concepts of evolution and ecology.
●    Consolidate understanding of statistical methods covered in BIOL0001 “Quantitative Biology” by exploring and analysing ecological and evolutionary datasets related to each topic.
●    Learn basics of R programming, including variable and list assignments, for-loops, if-statements, function definitions, and basic data plotting.
●    Gain practical experience in data analysis using a variety of quantitative approaches to explore and analyse different kinds of data.
●    Learn the fundamentals of a scientific paper writing, and practice by writing one.


By the end of the module, students should be able to:
●    Understand basic concepts in evolution (natural selection, sequence evolution, population genetics) and ecology (population growth, competition)
●    Write small programs in R to perform basic data analysis and/or simulation
●    Write a research paper containing all the expected parts (introduction, methods, results, discussion, conclusion)


Indicative lecture topics – based on module content in 2021/22


Variation and natural selection
●    What is evolution?
●    Sources of genetic variation, variation in fitness and selection coefficients
●    Laboratory, agricultural, man-made examples of selection
●    Types of natural selection
●    Genetic drift


Evolution of biological sequences
●    Biological sequences
●    How to model sequence evolution?
●    Discrete markov chains and maximum likelihood
●    Basic tree reconstruction


Interactions between genetic drift, selection and demography
●    Evolution of quantitative traits
●    Effects of selection in the distribution of trait values
●    Interactions between genetic drift and demography
●    Interactions between genetic drift and selection


Population ecology
●    Patterns of population growth – logarithmic growth, exponential growth
●    Predator-prey interaction; Lotka-Volterra
●    Competition
●    The future: Extinction rates, pollution, global warming; future of human evolution.