THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : School of Geosciences : Ecological Science

Undergraduate Course: Ecological and Environmental Analysis (ECSC08008)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course provides 2nd-year students with a foundation course in the collection and analysis of data relevant to biological, ecological and environmental problems. Topics dealt with in the course involve:
- Recognising variability and uncertainty in environmental and ecological systems and their importance;
- Gathering data suited to explain environmental and ecological systems through surveys and sampling;
- Establishing and describing relationships between different environmental and/or ecological variables;
- Design, analysis and interpretation of controlled experiments;
- Use of dynamic simulation models.
Course description To understand the way that ecological and environmental systems function, we often look for associations and seek evidence of causality, or the pattern of interaction between components. We may ultimately seek to establish the nature of these relationships that we can make predictions for other systems or of future change.
Reaching robust conclusions requires collection of sound data and proper statistical interpretation. The EEA course equips students with an integrated knowledge of data collection and data analysis, for use in dissertation projects and careers beyond.

This course considers the formulation of research questions and four broad themes:
- Survey and sampling
- Relationships between variables
- Design, analysis and interpretation of controlled experiments
- Dynamic data and the principles of simulation modelling.

Teaching will be in three-week blocks with half-day sessions each Monday morning (10:00 - 13:00). Six tutorials on Mondays, Wednesdays or Fridays will support your progress towards the in-course assessments.
The Monday sessions begin with a presentation of background and concepts and move into interactive sessions of up to two hours. The practical sessions may involve working in pairs and groups and will include computing activities using 'R'.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
Pre-requisitesNone
High Demand Course? Yes
Course Delivery Information
Academic year 2020/21, Available to all students (SV1) Quota:  60
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 44, Seminar/Tutorial Hours 6, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 146 )
Assessment (Further Info) Written Exam 60 %, Coursework 40 %, Practical Exam 0 %
Additional Information (Assessment) Coursework (40%):
- Designing a survey (25%)
- Experimental design (15%)

Examination (60%):
Two-hour examination at the end of Semester 2 based on short and long answer questions

Students are required to pass 40% of coursework and 40% of the exam in order to attain an overall pass for the course.
Feedback - The extended interactive sessions that follow each lecture are guided by teaching staff and supported by demonstrators, providing opportunity for 1:1 verbal interaction and feedback;
- Many of the tutorial sessions and oriented around assignments for in-course assessment, structured to encourage peer feedback and tutor interaction;
- Detailed and general written feedback on assessed work will be provided electronically via Learn
- Exam marking includes comments to students that can be reviewed in Year 3.

Feedback on the course can be provided to the CO directly or via one of two student representatives, who will also participate in the staff-student liaison committee. Course survey data from previous years' students has been considered and feedback will be sought for the current course in Week 10.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)2:00
Resit Exam Diet (August)2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Define appropriate strategies for quality and sampling survey
  2. Explore data in ways that enable relationships to be established between different environmental and/or ecological variables
  3. Design, analyse and interpret controlled experiments
  4. Understand time series data and their use in simulation modelling
  5. Use current computing tools to undertake analysis
Reading List
Week 1
Dunbar, R. (1995) The Trouble with Science. Faber and Faber, London
Chalmers, A. F. (1999) What is this thing called Science? Open University Press, Maidenhead.
Ford E.D. (2000) Scientific Method for Ecological Research. Cambridge University Press;

Weeks 1-3
Barnard C, Gilbert F & McGregor P (2001) Asking Questions in Biology. 2nd Edition. Pearson;
Feinsinger P (2001). Designing Field Studies for Biodiversity Conservation. Nature Conservancy, Washington;
Hughes IG & Hase TPA (2010) Measurements and their Uncertainty, Oxford University Press, Oxford;

Week 4-5
Fowler J, Cohen L & Jarvis P (1998) Practical Statistics for Field Biology, 2nd Edition. John Wiley;
Grafen A & Hails R (2002) Modern statistics for the Life Sciences. Oxford University Press, Oxford;

Week 6-8
Ennos R (2007) Statistical and Data Handling Skills in Biology. Pearson;
Grafen, A & Hails, R (2002) Modern statistics for the life sciences. oxford University Press (£22.99)
Sokal, R. R & Rohlf, F. J. (1969) Biometry. Freeman, San Fransisco
Ruxton GD & Colegrave N (2006) Experimental Design for the Life Sciences. 2nd Edition. Oxford University Press, Oxford;

Week 10-11
Haefner JW (1996) Modelling biological systems, Chapman & Hall, New York;
Smith J & Smith P (2007) Environmental Modelling: An Introduction, Oxford University Press.
Additional Information
Graduate Attributes and Skills Goal definition in experimental design.
Strategies for data collection.
Fluency with a range of statistical software tools .
KeywordsEEA year 2,experimental design,ecological survey,data analysis,environmental modelling
Contacts
Course organiserDr Saran Sohi
Tel: (0131 6)51 4471
Email: saran.sohi@ed.ac.uk
Course secretaryMrs Nicola Clark
Tel: (0131 6)50 4842
Email: nicola.clark@ed.ac.uk
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