Incorporating new knowledge of phytoplankton diversity and nutrient utilisation into an ocean-climate model to improve forecasts of ocean function. Phytoplankton drives ocean biogeochemical cycles and regulate Earth’s climate yet are poorly represented in ocean-climate models. This project will use advanced cell sorting and analysis techniques and innovative selection experiments to gain a deeper understanding of phytoplankton diversity and nutrient utilisation under projected climate change. Th ....Incorporating new knowledge of phytoplankton diversity and nutrient utilisation into an ocean-climate model to improve forecasts of ocean function. Phytoplankton drives ocean biogeochemical cycles and regulate Earth’s climate yet are poorly represented in ocean-climate models. This project will use advanced cell sorting and analysis techniques and innovative selection experiments to gain a deeper understanding of phytoplankton diversity and nutrient utilisation under projected climate change. This new knowledge will be used to improve the biological structure of an existing coupled ocean-climate model and reduce key uncertainties in forecasts of ocean function. This research will provide managers and industry with more accurate insight into the effects of ongoing climate change on the delivery of ecosystem services in eastern Australian waters.Read moreRead less
Global integration of microbial community and climate data. Microbial communities in the environment control the cycling of carbon and nutrients on Earth, but climate models do not directly incorporate microbial inputs. This interdisciplinary project will link planetary-scale climate modelling data with novel large-scale microbial community analysis, using climate information to provide insight into the fantastic diversity of microbial processes on our planet. The interdisciplinary approach will ....Global integration of microbial community and climate data. Microbial communities in the environment control the cycling of carbon and nutrients on Earth, but climate models do not directly incorporate microbial inputs. This interdisciplinary project will link planetary-scale climate modelling data with novel large-scale microbial community analysis, using climate information to provide insight into the fantastic diversity of microbial processes on our planet. The interdisciplinary approach will inform the next generation of climate models and better predict our future climate’s feedbacks. Conversely, it will make progress on the grand challenge of understanding microbial community function by enabling microbial ecology to be treated as a data-intensive machine learning problem.Read moreRead less