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ZOOL40490

Academic Year 2024/2025

Wildlife Habitat Modelling for Ecology and Conservation (ZOOL40490)

Subject:
Zoology
College:
Science
School:
Biology & Environment Science
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Dr Simone Ciuti
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This module provides a unique opportunity for students to acquire skills in habitat modelling and learn how to analyse species presence data. Such spatial data can be gathered for different species across taxa (from trees to large mammals through invertebrates) and with different techniques and sampling designs (plots and surveys, visual observations, satellite telemetry data, museum records, preference trials, satellite imagery and drone technology). Using recent advances with habitat modelling – namely, resource selection functions and step selection functions – students will learn how to build a habitat suitability model, describe species habitat selection, and forecast hotspots of connectivity or species core areas that need special conservation attention. The techniques taught in this module have clear applications in species ecology, conservation and management. Special focus will be given to mammal movement data, but the skills acquired in this course can be used to model any presence data (including plants).
Landscape connectivity describes how the movement of animals relates to landscape structure. The way in which movement among populations is affected by environmental conditions is important for predicting the effects of habitat fragmentation, and for defining conservation corridors, and this class will provide students with the skills needed to solve these challenging tasks. Finally, predictive models taught in this class can be used to predict future scenarios of species occupancy based on forecasted climate change. Students should have some familiarity with R and GIS (ArcMap or similar software such as QGIS).

About this Module

Learning Outcomes:

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 Module Content:

1-h lectures will be delivered 3 times a week for 4 weeks (Tuesdays, Wednesdays, Thursdays), each week ending with a long computer lab session (Fridays, 9am – 12 pm) when students will be equipped with new computational skills as well as they will be working on their final assignments while being assisted by the lecturers and skilled demonstrators.

[SC: Simone Ciuti; VMP: Virginia Morera-Pujol]

week 1
L1 Habitat use, habitat selection, habitat choice by animals: theory and practical examples [SC]
L2 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. [SC]
L3 Resource selection by animals: sampling protocols and study design [SC]
Computer lab 1 – HTML documents in Rmarkdown - 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). [SC]

week 2
L4 Spatial analysis in R part I (loading, manipulating, and visualising spatial data) [VMP]
L5 Spatial analysis in R part II (loading, manipulating, and visualising spatial data) [VMP]
L6 Spatial analysis in R part III (loading, manipulating, and visualising spatial data) [VMP]
Computer lab 2 – GIS in R [VMP]

week3
L7 Revision of the basic statistical concepts needed to analyse animal spatial data: regression models [SC]
L8 How to build a resource selection function used to explain habitat selection by animals part I [SC]
L9 How to build a resource selection function used to explain habitat selection by animals part II [SC]
Computer lab 3 – Running a habitat selection model [SC]

week 4
L10 In-class revision of key habitat wildlife modelling concepts and discussion about student projects (part I) [SC]
L11 In-class revision of key habitat wildlife modelling concepts and discussion about student projects (part II) [SC]
L12 In-class revision of key habitat wildlife modelling concepts and discussion about student projects (part III) [SC]
Computer lab 4 – Finalising a habitat selection model [SC]


Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

101
Lectures

12
Computer Aided Lab

12
Total

125

Approaches to Teaching and Learning:
This is a truly hands-on experience for the students! The lecturer will introduce and explain key topics and tools used in Wildlife Habitat Modelling and explain their importance in ecology and conservation. Weekly computer-based lab sessions will guide students step-by-step through habitat modelling techniques, receiving continuous support on the projects they are expected to develop. The class is a perfect balance between theory - when students will have the chance to understand the key concepts - and practice - with several hours in the computer lab to put in practice the wildlife habitat modelling tools.

Requirements, Exclusions and Recommendations
Learning Recommendations:

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.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Quizzes/Short Exercises: Short quizzes or exercises made available at the end of some of the lectures in weeks 1, 2, and 3. Students will have between 12-24 hrs to complete them after the end of the lecture. Week 1, Week 2, Week 3 Alternative linear conversion grade scale 40% No
40
 No
Individual Project: Students will work on their projects in class, and will have a few weeks after the completion of the course to submit their wildlife project (HTML format) Week 8 Graded No
60
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Summer No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

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).

Lectures and labs will be interactive and based on hands-on activities which will allow students to learn by doing. There is no official textbook and students will be provided with the necessary reading material during the course.

Name Role
Dr Virginia Morera-Pujol Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23 Fri 09:00 - 11:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23 Thurs 11:00 - 11:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23 Tues 12:00 - 12:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23 Wed 13:00 - 13:50
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