- UCAS course code
- C100
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Biology
- Typical A-level offer: AAA-AAB including specific subjects
- Typical contextual A-level offer: AAB-ABC including specific subjects
- Refugee/care-experienced offer: ABB-ABC including specific subjects
- Typical International Baccalaureate offer: 36-35 points overall with 6,6,6 to 6,6,5 at HL, including specific requirements
Course unit details:
Advanced Behavioural and Evolutionary Ecology
Unit code | BIOL31471 |
---|---|
Credit rating | 10 |
Unit level | Level 3 |
Teaching period(s) | Semester 1 |
Available as a free choice unit? | No |
Overview
You will study in depth the principles of evolutionary biology and ecology, trace historical origins and discuss emerging concepts. In addition, we will explore advanced topics such as: evolution of sociality, indirect genetic effects, and morality and fairness, phenotypic plasticity and evolvability. You will also take part in seminars on identifying current hot topics, updated every year.
Pre/co-requisites
Unit title | Unit code | Requirement type | Description |
---|---|---|---|
Genes, Evolution and Development | BIOL10521 | Pre-Requisite | Recommended |
Fundamentals of Evolutionary Biology | BIOL21232 | Pre-Requisite | Recommended |
Animal Behaviour | BIOL21432 | Pre-Requisite | Recommended |
Aims
This course provides a detailed perspective on the major concepts in behavioural ecology and evolutionary biology illustrated by in-depth current research examples. We will discuss fundamental questions, how and why they originated, in fields such as epigenetics, phenotypic plasticity, conservation biology, genomics and bioinformatics and what the links between these areas are. A particular focus is to understand the structure of evolutionary theory tracing its development from pre-Darwinian forms to the Extended Synthesis that incorporates aspects of epigenetics, plasticity, niche construction and indirect genetic effects. This is complemented by discussions on the most recent major advances in the field.
Learning outcomes
Intended Learning Outcomes
- A basic understanding of key concepts such as optimality, game theory, and comparative approaches.
- In depth understanding of theoretical and empirical approaches with critiques, e.g., sexual selection, indirect genetic effects, phenotypic plasticity, New Synthesis.
- Application of behavioural ecology and animal behaviour studies (e.g. conservation biology) and the use of genomics, statistics and quantitative genetic tools in evolutionary biology.
- Being able to conceptualize current research areas both in the broader context and their links. To identify quantitative, empirical and theoretical approaches suitable to tackle current fundamental questions in behavioural and evolutionary ecology.
Syllabus
Lecture content
We begin by outlining key concepts in behavioural and evolutionary ecology with an in-depth discussion of fitness and adaptation. How does sociality arise and what are the selective forces underlying the various forms found in nature and humans is the focus of a set of lectures. We then discuss broader concepts such as plasticity, levels of selection, The New Synthesis and evo-devo to show how these form part of an extended definition of evolutionary biology. This is complemented by a case study where we look in detail at how a fundamental question has been addressed using quantitative genetics. We will then explore the genetic and epigenetic basis of variation in behaviour and look at modern tools in genomics and quantitative analysis used in current research. This is complemented by a discussion of how behavioural ecology is applied to conservation biology and by identifying current hot topics. We finally take a broader look at human evolution, and trace the ecological and social transitions to modern humans, identify signatures of recent selection at the genetic level and explore current and future selective changes.
eLearning Activity
a) Online discussion
b) Practice exam paper & peer review
c) Big Question abstract using AI tools
Employability skills
- Analytical skills
- Needed for practice exam and peer review.
- Group/team working
- Study groups are possible for the essay but students need to submit their very own work.
- Project management
- Required for practice exam.
- Oral communication
- Active lectures and seminars with student participation.
- Problem solving
- Needed for practice exam and peer review.
- Research
- Literature research is required for exam and online seminar contribution.
- Written communication
- Essay during course and written examination. Further, online contribution to seminar.
Assessment methods
Method | Weight |
---|---|
Other | 15% |
Written exam | 79% |
Written assignment (inc essay) | 6% |
2 hour written examination (79%)
January 2026, date TBC
Practice exam paper and peer review (6%)
Practice Paper released on Blackboard (“Assessments” section) on Mon 11 Oct at 13:00h.
Please ensure that you use the paper named “Practice Paper” and NOT the 2021 past paper on the main Course Content page!
Select two questions from this “Practice Paper” and write an essay plan for each - maximum of 200 words per essay plan. Both plans should be submitted as a single Word file – and together on a single side of A4. Your ID number should be clearly visible at the top of the page. The file should then be uploaded according to Blackboard instructions. (2% will be awarded for the satisfactory completion of each plan, 4% in total).
The DEADLINE is Mon 25 Oct at 16:00h.
At 18:00h on Mon 25 Oct, Blackboard will release the ‘Indicative Answers’ for the paper as well as two different sets of essay plans for peer-review (assigned randomly by Blackboard). Using the Indicative Answers, students should review & peer mark each plan (can be found in: Assessments > Essay – Past Paper – PeerMark Assignment 1). You will be asked to comment on the essay plans (2 plans, i.e. 4 question plans in total) with a 50 word minimum response for each, including both positive/negative comments & suggestions where appropriate.
(2% awarded for satisfactory completion of Peer Review).
The DEADLINE is Mon 1 Nov at 16:00h.
The Big Question abstract (15%)
The aim of this assignment is to write a 200 word abstract on a big question based on the summary of five papers on a given lecture topic.
Select a lecture topic of interest
Using google scholar or a different search engine, search for primary research papers on this topic and select those 5 you find most relevant and interesting.
Using generative AI tools, such as ChatGPT, have those 5 papers summarised
Based on the summaries, you need to define one unanswered question that emerges from these primary studies. This question should be broad and identify a significant gap in knowledge within the topic of the lecture.
Then, write a max 200-word contribution on why this is a big question, and why closing this gap would present a significant advance in the field. Do NOT have AI write this for you.
The word limit is 200, use no more than five references, which do not count toward the word limit. You need to list those references at the end
Feedback methods
Feedback on student performance and participation is central to achieving the learning outcomes. Feedback on the exam will be given through a 1h feedback session during which each student can have the grade explained. Each script is annotated, giving individual feedback.
Recommended reading
- Gini B, Hager R. 2012. Behavioural ecology. Encyclopaedia of Life Sciences. Chichester:Wiley.
http://onlinelibrary.wiley.com/doi/10.1002/9780470015902.a0003217.pub2/full
- Westneat DF & Fox CW. 2010. Evolutionary behavioral ecology. Oxford UP.
- Piglucci M & Mueller GB. 2010. Evolution – The extended synthesis. MIT Press (sections I, II, IV, VI, rest is optional)
- Other textbook used: Krebs JR, Davies NB, West SA. 2012. An Introduction to Behavioural Ecology. 4th ed; Oxford UP
Study hours
Scheduled activity hours | |
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Assessment written exam | 2 |
Lectures | 18 |
Independent study hours | |
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Independent study | 80 |
Teaching staff
Staff member | Role |
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Reinmar Hager | Unit coordinator |