Climate effects on planktonic food quality and trophic transfer in the Arctic marginal ice zone
Obtain a better knowledge of Arctic zooplankton physiology and life history strategies to predict the degree of match/mismatch of key biological processes at the base of the Arctic marine food web in a changing Arctic.
1) Through field investigations document the full annual cycle of Calanus glacialis. Obtain data that will allow testing of predictions on diapause duration, critical size of lipid storage, and reproductive success and population abundance of this key Arctic grazer.
2) In laboratory studies, obtain fundamental measurements of metabolism and diapause-flexibility of C. glacialis, including testing of predictions on the temperature- and food-dependence of these traits.
3) Model the life history of C. glacialis in order to predict optimal strategies for specified environments and thereby predict how C. glacialis and similar species may respond to climate change in the Arctic.
A warmer climate with less extensive ice cover will lead to higher total primary production in the Arctic, which has the potential to increase the overall secondary production. However, altered climate conditions will affect timing, quantity and quality of ice algal and phytoplankton food sources with extensive implications for grazers. Depending on the grazers ability to adapt to these new conditions, some organisms will be favored more than others, resulting in ecological winners and losers. We therefore propose a project that will study Arctic zooplankton and their capability to adapt their current life history strategies and physiology to a changing Arctic. We will focus in our study on Calanus glacialis, the key herbivore in Arctic shelf seas, and combine field and laboratory investigations with model development to ultimately arrive at an improved understanding of the physiological and life
history adaptations of Arctic zooplankton. A central element of our approach is to move towards individual-based zooplankton ecology where states, such as lipid reserves, are measured at the level of individuals. We aim at a tight linkage between data collection through field and experimental studies and the modeling work where models deliver predictions for field and laboratory work, securing target-aimed field investigations and well-defined hypotheses. In turn, findings from field and experimental work do not only test model predictions, but also deliver a better basis for improved parameterization and design of models. Long-term data-series acquired through previous projects will be continued and will
allow us to include inter-annual variability and different ice-cover scenarios in our investigations. This project will include several national institutions and international
collaborators, with strong participation by early career scientists.