FSC-30029 - Environmental and Wildlife Forensics
Coordinator: Adam Jeffery Tel: +44 1782 7 33170
Lecture Time: See Timetable...
Level: Level 6
Credits: 15
Study Hours: 150
School Office: 01782 734921

Programme/Approved Electives for 2025/26

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2025/26

This module will provide teaching and learning resources for you to become aware, understand and apply key theoretical and practical aspects of Environmental and Wildlife Forensics.
You will gain knowledge on how environmental and wildlife crime investigators use forensic science to assist them in legal investigations.

Aims
This module aims to teach students key theoretical and practical procedures of environmental and wildlife forensics which helps to enforce regulation to protect the environment and wildlife in the UK and internationally.

Talis Aspire Reading List
Any reading lists will be provided by the start of the course.
http://lists.lib.keele.ac.uk/modules/fsc-30029/lists

Intended Learning Outcomes

evaluate and present the realised and potential value of natural and artificial materials, animals, plants, and fungi in forensic investigations.: 1,2
evaluate and apply the methods and procedures used in environmental and forensic wildlife crime scene investigation.: 1,2
appraise the scale and nature of national and international environment and wildlife crime and its links to other types of serious crime.: 1,2

Study hours

Active learning hours:
Interactive Seminar Sessions - 24 Hours
Practical classes - 15 hours

Independent study hours:
Guided independent study - 111 hours

School Rules

None

Description of Module Assessment

1: Group Assessment weighted 50%
Group project
Group report. Students will, in groups, produce a 2500 word written report using data that they collect during an outdoor practical class.

2: Report weighted 50%
Trace evidence Report
Independent report. Students will produce a 2500 word written report using data derived from a choice of pre-collected datasets.