Modelling the biogeography of Antarctic phytoplankton
Marine pelagic diatoms are coined to be strong drivers of the Southern Ocean silicate pump. Their growth and sinking dynamics substantially affect silicate supply in lower latitude surface water masses of the world ocean. We have explored the use of species distribution modeling (SDM) to investigate the potential responses of a few key diatom species to climate change. These models describe the response of a species to its environment by combining occurrence and environmental data using statistical or machine learning approaches. Subsequently, the species’ potential distribution is mapped by projecting the model on gridded environmental layers, also for future scenarios. This methodology became a standard approach in biogeography as well as conservation and climate change science, though with a strong bias towards terrestrial organisms. Marine organisms are clearly underrepresented and there is little experience with the applicability of SDMs for planktonic organisms. Taxon occurrence records were harvested from public resources like the GBIF network, and extended by additional samples from the literature and from the Hustedt Collection, a large diatom herbarium located at the AWI. Environmental parameters included nutrient concentrations and oceanographic variables like sea surface temperature and salinity. Results of this study will be presented focusing on the current availability of taxon observation records and environmental parameters, model evaluation and projection on expected environmental conditions predicted for future climate scenarios. In summary, the resulting current potential distribution maps of the models agree well with species distributions expected based on background knowledge, although the nature of a distribution boundary in the pelagial poses some challenges for interpretation. Projections on IPCC scenarios suggest that the distribution range of the main silica carrier of the Southern Ocean might shift polewards and substantially shrink during the upcoming decades.