PhD studentship

Picophytoplankton make up 34% of the oceanic chlorophyll (Uitz et al. 2006,
see also figure 1). Based on the high turnover rates in the microbial loop one
would expect their contribution to primary production to be even higher. The
high grazing rates of microzooplankton suppress picophytoplankton from
forming blooms, and thus their biomass is relatively more constant in space
and time than of the larger phytoplankton. However, from their small size and
lack of ballast one would expect their contribution to export to be smaller.
Because of their small size (big surface to volume ratio) they grow well at low
nutrient and light conditions. This specialisation in poor conditions probably
also contributes to their relatively constant biomass. The physiology of
cyanobacteria is relatively well studied, but much less is known about
picoeukaryotes.

The aim of this project is to improve the representation of picophytoplankton
in a global ocean biogeochemical model. In combination with an ongoing
project on the representation of microzooplankton (Buitenhuis et al.
submitted) and the recent inclusion of bacteria in the PlankTOM10 model (Le
Quere et al. in prep.), the overall aim is to better represent the microbial loop.
In this project the PhD student would combine data synthesis of published
physiological information (maximum growth rate, nutrient and light physiology,
nutrient stoichiometries and DOC production) with laboratory experiments to
fill in the gaps. With these data, the following questions will be addressed:

Are picophytoplankton typical K-strategists with low maximum growth rates
and high afffinities for light and nutrients?
Do they achieve this by having low minimum nutrient and high maximum
chlorophyll quota relative to carbon, or by having superior nutrient uptake
kinetics?
Depending on the interest of the candidate, this project would include either a
limited effort in using the model for sensitivity analysis, or a more extensive
additional effort in programming the model with newly identified mechanisms
from the physiological work. Similar ongoing projects on diatoms and
coccolithophores spend roughly 65% of their time on lab work, 25% on data
synthesis and 10% on modelling. This kind of time planning would suit a
candidate with a strong background in microbiology, but a more model and
data synthesis oriented project would be possible.