新香港六合彩开奖结果

鈥淢ethods in Ecology and Evolution鈥� 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. natural selection, 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 鈥淨uantitative Biology鈥� 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 鈥淨uantitative Biology鈥� 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 simulations
• 听Write a research paper containing all the expected parts (introduction, methods, results, discussion, conclusion)

Indicative lecture topics 鈥� based on module content in 2022/23

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

Evolution of biological sequences
听听 听Biological sequences
听听 听How to model sequence evolution?
听听 听Discrete Markov chains and Maximum Likelihood
听听 听Basic tree reconstruction

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

Population ecology
听听 听Patterns of population growth 鈥� logarithmic growth, exponential growth
听听 听Predator-prey interaction; Lotka-Volterra
听听 听Competition
听听 听Selected topics on biology and society.