Module Database

Information for module BIOL1008

This module is available for 2017/18

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Module code:BIOL1008 (Add to my personalised list)
Title:Methods in Ecology and Evolution
Credit value:.5
Division:Division of Biosciences
Module organiser (provisional):Dr Christophe Dessimoz
Organiser's location:Darwin Building
Available for students in Year(s):1
Module prerequisites:None 
Module outline:This module introduces students to the scope, basic concepts and methods of ecology/evolution. It shows them 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. Students use statistical methods covered in BIOL1002 “Quantitative Biology” to explore and analyse ecological and evolutionary datasets related to each topic. They learn how to write simple programs in R for performing their analyses and are introduced to bioinformatics.  
Module aims:This module introduces students to fundamental concepts in ecology and evolution. It will provide insights into contemporary quantitative and bioinformatic approaches used in biological sciences. Students will learn to extract and analyse evidence from a variety of sources and apply the skills that they have acquired to specific case studies. 
Module objectives:Through a combination of lectures and weekly practicals, students are introduced to issues driving current research in ecology and evolution, encouraged to direct their own data analysis and gain experience in peer reviewing and writing scientific papers. Each section of the course introduces students to a specific topic in ecology/evolution and the quantitative methods used to study it. Topics will be based on current research and will vary from year to year as new staff are recruited and research focuses change. In each case students acquire knowledge of the major questions and systems that are of interest to researchers; a more detailed understanding of specific case studies and experience using an appropriate analytical approach in the associated practical element. The module will be assessed via practical reports/problem solving exercises at the end of each block of lectures/practicals. At the end of the course students will select one topic to write up in the form of a scientific paper.  
Key skills provided by module:Students will gain practical experience in R programming, and in using a variety of quantitative approaches to explore and analyse different kinds of data. They will learn first-hand about research being carried out in the department and be introduced to scientific paper writing. 
Module timetable: 
Module assessment:Coursework one (4 x 500 words) 60.00%
Coursework two (2,500 words) 40.00% 
Taking this module as an option?: 
Link to virtual learning environment (registered students only) 
Last updated:2017-03-09 20:48:48 by ucbtcde