Unravelling the impact of environmental changes on freshwater phytoplankton

What:

We are excited to offer a Master’s internship in ecology, centered on the study of phytoplankton traits, with a special focus on the impacts of global environmental change on harmful cyanobacteria. This internship is a fantastic opportunity to apply trait-based ecological approaches, delve into the dynamic world of phytoplankton, and explore their functional responses to contrasting environments.

Context:

Cyanobacteria significantly impact human and ecosystem health. They alter food webs, reduce biodiversity, and change nutrient cycles. Through the variation of their abundance, biomass and toxins concentration, it has been demonstrated that cyanobacteria particularly benefit from environmental changes including warming, nutrient changes and light climate. Trait-based ecology bridges the gap between these changes in environmental drivers and the responses of cyanobacteria. Specifically, it can help reveal the underlying mechanisms that drive cyanobacterial blooms. For example, an approach at the individual level (i.e. at the single cell level) reveals phenotypic plasticity of a species which in turn informs on the success of this species. However, trait-based ecology of phytoplankton is currently limited in approaches to rapidly measure traits at the individual-level.

To address this, we developed an innovative framework using in combination a flow cytometer and a graphical user interface to obtain the functional traits of each individual. Using this approach, we would like to increase our knowledge on the functional response of different phytoplankton species to various environmental changes (e.g. nitrogen, phosphorus or light limitation).

For this project we seek a highly motivated student who is interested in learning more about phytoplankton. With the close support of the supervision team, the candidate will investigate his own research question by designing and conducting their own experiment that involves culturing different phytoplankton species under a range of conditions, measuring and analyzing the various traits, and then interpreting the results.

Requirement:

Basic knowledge of R: data manipulation and graphical representation.

Where:

This project will be performed at the Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen.

Duration:

5 months or more. Flexible start from September onwards