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Curricular information is subject to change
On completion of this module, students will be able to:
i) significantly improve their R and GIS skills;
ii) run a resource selection function using presence-only data and be able to build habitat suitability models;
iii) predict species habitat selection under different scenarios (climate change, habitat change);
iv) become confident with wildlife habitat modelling (different techniques) and acquire the proper skills required to study species ecology and improve their management and conservation.
Indicative topics:
- Habitat use, habitat selection, habitat choice by animals: theory and practical examples.
- Type of data gathered when monitoring animals in the wild: presence/absence spatial data, used/unused spatial data data, presence/available spatial data. Theory and practical examples including analytical approaches.
- Resource selection by animals: sampling protocols and study design.
- Spatial analysis in R (loading, manipulating, and visualising spatial data).
- Revision of the basic statistical concepts needed to analyse animal spatial data: regression models.
- How to build a resource selection function used to explain habitat selection by animals.
- How to produce HTML interactive reports using RMarkdown by RStudio which can be used to display the results of wildlife habitat modelling (used in academic research, conservation, wildlife management, and ecological consultancies).
Student Effort Type | Hours |
---|---|
Lectures | 12 |
Computer Aided Lab | 12 |
Autonomous Student Learning | 101 |
Total | 125 |
Students should have some familiarity (at least the basics) with R and GIS (ArcMap or similar software). Please contact the lecturer if you need further details about your eligibility.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Continuous Assessment: Multiple Choice Questions, exercises, and/or short questions on the different topics taught in class to make sure students are on track with the skills needed to develop their final project. | Throughout the Trimester | n/a | Alternative linear conversion grade scale 40% | No | 40 |
Project: Data analysis of spatial data provided in class (e.g. satellite radiotracking data of deer, wolf, cougar, orangutan) describing habitat selection of the selected species. |
Coursework (End of Trimester) | n/a | Graded | Yes | 60 |
Resit In | Terminal Exam |
---|---|
Summer | No |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
The students will continuously receive in-class support and feedback during their projects' development (with special regard to the practical sessions). The students will also receive individual feedback (post-assessment).
Name | Role |
---|---|
Dr Virginia Morera-Pujol | Lecturer / Co-Lecturer |
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23 | Fri 09:00 - 11:50 |
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23 | Thurs 11:00 - 11:50 |
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23 | Tues 12:00 - 12:50 |
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23 | Wed 13:00 - 13:50 |