Module overview
This course focuses on understanding the causes and ecological consequences of seascape patterns and processes in space and time. A central theme will be the movements of marine organisms and their interaction with dynamic environments at different scales. Emphasis will be placed on learning skills to conduct spatiotemporal analyses in pelagic ecosystems. This understanding and these skills will then be applied to questions including quantifying scale and dynamics for conservation and management applications.
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Discuss spatiotemporal scale of patterns and processes in pelagic ecosystems.
- Compute and map statistical analyses of spatiotemporal marine data.
- Summarise the main technologies for studying spatiotemporal patterns in marine ecosystems.
- Create an integrated workflow for the analysis, presentation, and interpretation of spatiotemporal marine data.
- Compare movement patterns and processes among various marine organisms.
- Appraise the application of seascape ecology concepts to marine conservation and management issues.
Syllabus
The syllabus initially introduces the relatively new discipline of ‘seascape ecology, whereafter it deals with spatial and temporal patterns in pelagic ecosystems, and the analysis of these patterns. Next, the material focusses on movements of marine organisms, and the analysis of movement data, as a top-down lens for considering pelagic spatiotemporal patterns and processes. Finally, the module looks at the application of seascape ecology to marine conservation and management.
Learning and Teaching
Teaching and learning methods
The goal is to provide the students with an interactive, hands-on learning environment. An important element is practical sessions where students develop skills for analysing spatiotemporal marine data in the R environment.
Teaching formats include:
Traditional lectures
A series of core lectures will introduce the core knowledge content. These lectures are supplemented by short videos of key definitions and concepts via Blackboard and Panopto lecture capture.
Special topics lectures and seminars
Lectures and seminars, often research-centred, by guest speakers cover specific topics. Case studies are accompanied by in-class discussion sessions.
Practicals
Practical sessions giving hands-on experience of the R environment.
| Type | Hours |
|---|---|
| Independent Study | 120 |
| Teaching | 30 |
| Total study time | 150 |
Resources & Reading list
General Resources
Software. Software for this module: - R (https://www.r-project.org/); - RStudio (https://www.rstudio.com/) Both free and open-source.
PDFs and/or links to key papers and book chapters will be provided on the module’s Blackboard site..
Textbooks
Wickham H, Grolemund G (2017). R for Data Science. O'Reilly.
Lovelace R, Nowosad J, Muenchow J (2019). Geocomputation with R. CRC Press..
Pitman SJ (2017). Seascape Ecology. John Wiley & Sons, Hoboken, NJ.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Multiple choice questionSummative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Case study report | 40% |
| Assignment | 60% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Essay | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Essay | 100% |
Repeat Information
Repeat type: Internal & External