Worpackage V

Linking biological timing to population dynamics in the polar marine ecosystem

Helmholtz Centre for Environmental Research (UFZ), Carl von Ossietzky University Oldenburg (UO)

This work package will use mathematical modeling to transfer the results from the physiological and field studies to an ecosystem level. The models will be used to investigate the interplay of endogenous rhythms in polar pelagic invertebrates with population and community dynamics and to predict the consequences of shifting biorhythms for both the krill population and the entire Antarctic pelagic food chain. The Blasius lab (UO) will establish population dynamics models of Antarctic krill and calanoid copepods to model biological timing in these organisms and its functional interaction with the polar environment, characterized by extreme temporal forcing. The models will explore the synchronization of endogenous physiological and behavioral timing systems (i.e., daily and seasonal life-cycle functions) to the external cycles in environmental factors (e.g., photoperiod, seasonal sea ice dynamics) and will infer the consequences for population and community dynamics. The models will be used to study the interaction of various rhythms at different time scales (i.e., diurnal, seasonal and multi-annual climate cycles) and will consider: the community perspective (i.e., the timing of krill with respect to the timing of top predators and phytoplankton food source), the species perspective (i.e., species specific differences between krill and copepods), and the spatial perspective (i.e., latitudinal migration of krill from lower to higher latitudes and associated changes of photoperiod and timing of food sources). Finally, the models will be used to understand and predict the effect of climate induced changes in polar environments and associated mismatch of biological timing for the whole polar pelagic ecosystem at the species and community level.

The Grimm lab (UFZ) will contribute its expertise in the mechanistic modeling of population dynamics. The models will take into account the full life cycle of the organisms, individual variability, local interactions, physiology, and adaptive behavior. Sub-models will be tested and parameterized for a wide range of environmental conditions so that the full individual-based modeling (IBM) can be used to predict responses of the population to unprecedented environmental conditions. Due to the high abundances in marine invertebrates like krill, individuals will be grouped into “super-individuals”, i.e. stage-cohorts of identical individuals. The model will include environmental drivers of individual development and performance, internal and external biorhythms and their interaction, and a sub-model that takes into account food intake and use. This sub-model should be based on an established theory, for example Dynamic Energy Budget Theory or Metabolic Scaling Theory. Data for parameterizing the model will be provided by the empirical groups, as well as various patterns observed in the real system which can be used to inversely determine model structure and parameters (“pattern-oriented modeling”).