701-1411-00L  Environmental DNA - Concepts and Applications for Biodiversity Monitoring at the Landscape Scale

SemesterHerbstsemester 2023
DozierendeL. Pellissier, K. Deiner, A. Frossard
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch


KurzbeschreibungEnvironmental DNA (eDNA) allows the detection of organisms from traces of their DNA sampled from water, air or soil. Sampling eDNA instead of organisms makes monitoring fast, non-invasive, scalable and inexpensive. In this lecture, students will learn about eDNA and how it can be sampled, sequenced and analysed for biodiversity discovery and monitoring.
LernzielAt the end of this course, participants should be able to:
- describe what eDNA is and how to harness the information in eDNA to turn it into a survey method for biodiversity
- describe the eDNA analytical steps, from the sampling, laboratory, data analysis and interpretation.
- summarise the common software and analytical tools for analysing eDNA data and be able to interpret the results.
- apply eDNA methods to design programs for monitoring in conservation and restoration through case studies.
Additionally, participants should be able to:
- provide constructive feedback to peers and learn from feedback,
- integrate concepts within and among disciplines of science.
InhaltThe course is consisting of two pillars:
Pillar 1: Theoretical background. The first pillar offers generals theoretical knowledge about the nature of eDNA and its use in biodiversity science. It is structured into theoretical blocks with video content about sampling design, laboratory and data processing, which offer fundamental knowledge to solve the practical case studies of pillar 2.
Pillar 2: Data application on applied Case Studies. Each theory block will be associated with an exercise in which students are challenged to apply their knowledge from the theory. Students will collaborate on planning eDNA sampling design, visit the laboratory, run eDNA analysis (in R) following the best guidelines and interpret the results of analyses. These exercises will happen in person in the classroom.
Voraussetzungen / Besonderes- Basic understanding of genetics and molecular analyses.
- Basic knowledge of R and Geographic Information Systems (GIS).
- The analytic part of the lecture will rely on skills from “Environmental Systems Data Science”