Stable isotopes: analysis and application in trophic ecology

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General information

The growing demand for a sustainable use of aquatic resources has stimulated research interest in untangling the functional relationships between aquatic organisms, including interactions at the basis of food webs. Knowledge of these (trophic) interactions is a prerequisite to understand and to protect the carrying capacity of aquatic ecosystems. Stable isotope analysis (SIA) has proven to be a useful tool in reconstructing diets, characterizing trophic relationships, elucidating patterns of resource allocation, and constructing food webs. Consequently, the number of studies using SIA in trophic ecology has increased exponentially over the past decade. Several subdisciplines have developed, including isotope mixing models, incorporation dynamics models, lipid-extraction and correction methods, isotopic routing models, and compound-specific isotopic analysis. This course aims to provide advanced knowledge on the use of stable isotopes as tracers in ecological research. More specifically, next to theory on the up-to-date techniques, analysing and implementing biomarker and tracer data in food web modelling will be included in the training. A short introduction to the use of the statistical software package R is foreseen as well.

Target audience: PhD students with research interest in ecology, physiology, biochemistry, aquaculture, microbiology.

The course will be organised by the Marine Biology Section (UGent) with lectures and lab sessions at Campus Sterre (S8). A one-day trip to the University of Liège (lectures and lab demonstrations) is included .

Contact Person: Marleen De Troch (


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Venue: Ghent University
Ghent, Belgium

Marine Biology Section

Krijgslaan 281
Campus Sterre - S8
B-9000 Ghent Belgium

A one-day trip to the University of Liège (lectures and lab demonstrations) is included .


Open from
1 Nov 2013 to 15 Jan 2016



The participation costs will include the course material, trip to Liège and coffee breaks.


Applicants need at least a master diploma. An introduction to R is foreseen in the frame of the course.

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