The heat is on: resilience and tipping points in Arctic phytoplankton populations under climate change induced heatwaves

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Effects of climate change and associated extreme events on primary productivity are of paramount interest for ecosystem functioning and biogeochemical cycling. In a future climate, marine heatwaves are forecasted to increase globally in frequency and intensity, especially in high-latitude regions. Yet, rigorous approaches to investigate underlying ecological mechanisms in the response to such events and their implications for primary producers are still very limited. This project aims at elucidating the adaptive capacity and limits of Arctic phytoplankton towards short warming events within three intertwined work packages focusing on laboratory experiments, field observations and refinement of novel methodology. Adjustments to changed environmental conditions can take place through physiological and evolutionary responses on several fundamental ecological levels (genotype, population and species community), which are especially in protists extremely difficult to disentangle. One of the largest challenges is the analysis of intraspecific diversity and dynamics, which will be the special focus of this project. Using a novel approach to efficiently examine the composition of protist populations (Microsatellite PoolSeq Barcoding), along with targeted experiments and a unique environmental time-series across six consecutive years from an Arctic fjord, I will work towards closing these substantial knowledge gaps on rapid physiological and evolutionary adjustments to heatwaves. The direct combination of experimental and observational data is a novel and necessary approach to making measurements in simplified setups more applicable to the ‘real world’ situation. The experiments are designed to disentangle heatwave responses at several levels of ecological complexity (from laboratory monocultures to natural field communities) in comparable set-ups, and will provide outcomes directly relevant for application in ecological models.