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Ecology and Evolutionary Biology Tropical Field Course (BIOL0057)

Key information

Faculty
Faculty of Life Sciences
Teaching department
Division of Biosciences
Credit value
15
Restrictions
For 2024 places will be limited to 10 students. Only students on the degree routes of the MSci Biological Sciences degree programme (Biodiversity and Conservation, and Zoology) will be considered. Prerequisite modules include Introduction to Field Ecology (BIOL0007) and Fundamentals of Ecology (BIOL0014). Computational Biology (BIOL0029) is desirable. ALL students wishing to take this module should register for it as early as possible on Portico. Priority will be given based on the date of registration and to students with the most suitable academic backgrounds. If necessary, selection will be by lottery.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module will provide advanced ecological fieldwork training focusing on tropical ecosystems. Students will develop and refine skills including identifying, estimating, and monitoring biodiversity using traditional methods and new technology for nature, including application of molecular ecology in real-time, and experimental field-based approaches. Analysis of these data will be carried out using R. Students will learn about and appreciate the complexity of tropical ecosystems, current impacts on their biodiversity, and conservation measures. The module also aims to develop skills in hypothesis testing and research, through conducting mini research field projects. The module will run at the beginning of June (after the third-year project presentations and the start of the summer vacation) for 14 days, with 10 full days in the field and will be based at Mpala Research Station, central Kenya, East Africa.

Lecture/topic list:

As this is a field-based course, the majority of the learning will be in the field, but this will be backed up by ‘lab’ style classes focusing on analyses of field/molecular data. There will also be evening seminars and a student led debate on colonial legacies in conservation.

The module will be taught in the field and during

Learning Aims and Objectives:

On completing this module students will be able to:

  • Describe the complexity of tropical ecosystems focusing on key East African montane forest and savanna sites and understand impacts of land-use change on biodiversity and conservation measures in these systems.
  • Use a range of field techniques and molecular/computational tools for estimating and quantifying diversity, applying phylogenetic inference for data analysis including species delimitation.
  • Use tools for species identification across animals and plants from African tropical forests and savanna.
  • Use of statistical tests to analyse field data
  • Generate and test hypothesis and apply them in a field setting.
  • Co-ordination of group work
  • Keep a detailed field notebook, communicate research findings, and produce a brief communication style research paper.

Students will:

1) Produce a short communications style paper (2000 words max) based on their mini research project (40%)

2) Deliver a presentation/vlog - 5 minutes max on a field method(s) from the course (25%)

3) Produce a fieldnote based on observations from the field and lab (35%)

Please note: Students will be asked to pay for the return flight to Kenya, and will also need to pay for their travel to London Heathrow, and any additional food/drink (beyond the meals provided at the research station). Bursaries are available to students for whom these costs would be prohibitive.

Module deliveries for 2024/25 academic year

Intended teaching term: Terms 3 and Summer period ÌýÌýÌý Undergraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
70% Coursework
30% Viva or oral presentation
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
6
Module leader
Professor Julia Day
Who to contact for more information
j.day@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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