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Description
Our work will focus on the development of new regional models to describe connections between phytoplankton and the ecosystem, plankton life cycle, plankton growth and respiration, and also understanding factors are influencing those parameters. We aim to use these new developed models to derive plankton properties from satellite data. This will extend geographical and temporal coverage of the relevant data today and in the future, when larger parts of the Arctic Ocean become ice free. We will make use of existing information and will obtain new data using state-of-the-art in situ measurements and through water sample collection from research vessels in the European sector of the Arctic Ocean. We will particularly focus on the Fram Strait and Svalbard Shelf between Greenland and Svalbard. Fram Strait is the main gateway for the water exchange between North Atlantic and Arctic Ocean, with the West Spitsbergen Current bringing warm Atlantic waters into the Arctic and East Greenland Current transporting cold Polar waters southwards out of the Arctic Ocean. The key measurements will include concentrations of essential biogeochemical variables: net community production, dissolved and particulate organic carbon, chlorophyll a and particles suspended in water. We will also measure inherent and apparent optical properties, as well as conduct standard oceanographic observations of temperature and salinity. Statistical tools will be used to develop regional plankton model, validate satellite data and trace the links between physical properties of the ocean and ecosystem processes. More than 4 million Arctic residents and many millions of people beyond the region directly and indirectly rely on ecosystem services of the Arctic Ocean and its seas – such as fisheries and aquaculture. Up to date knowledge about current state and ecosystem changes across all levels of the Arctic marine food web is the key for responsible ecosystem management of the Arctic Ocean.
Summary of project results
Phytoplankton are microscopic organisms in the ocean that use energy from the sun and carbon dioxide (CO2) to produce marine organic matter, just like plants on land. They constitute just 1% of the photosynthetic Earth biomass, but produce half of the World’s oxygen, which is the same amount of oxygen as all the plants on land. Some studies show that without phytoplankton CO2 concentrations would have increased by 200 ppm, which would have been critical for humans. Today CO2 concentration is 421 ppm and according to projections, at the level 500 ppm extreme weather and sea level rise would endanger global food supplies and other economic sectors. This shows that tiny phytoplankton are doing a very important process for the whole planet by decreasing the levels of CO2. They are also at the base of the marine food web; it was proven that fish stock and recruitment rates depend on the number of phytoplankton. However, the quality of phytoplankton growth monitoring and forecast, which is critical to understand the processes of CO2 cycling and impact on the fish stock, is not yet at an acceptable level yet. An example is the difference in phytoplankton growth modelling estimates, which differ two times globally and fifty times when only the Arctic is considered. In the MOPAR project we’ve set the goal to improve the quality of the phytoplankton modelling from the satellite data in the Greenland Sea. This region was chosen as here the pronounced effects of the changing climate are observed, yet our understanding on its influence on the phytoplankton is far from complete.
The main project output is the algorithm that gives more accurate estimates of phytoplankton growth rate in the Greenland Sea than those previously reported. We’ve achieved this accuracy by using different types of local data collected during the expeditions of the Institute of Oceanology of Polish Academy of Sciences in 2015-2022, and two expeditions of Norwegian Polar Institute and GEOMAR Helmholtz Centre for Ocean Research where our team took part. We then tested this data for the different model types. Using local vertical distribution of phytoplankton biomass, local satellite product for the sunlight distribution developed in the course of the project by our team, and accounting for the way local phytoplankton species absorb the light improved the algorithm performance significantly. With this algorithm we were able to produce maps tracking the phytoplankton seasonal cycle for the years 1998-2022, which showed more prolonged phytoplankton bloom than previously reported. When calculating the total budget of the phytoplankton production, we’ve observed 11%-150% larger estimates depending on the study we compared the results to. This means that we are dealing with larger CO2 uptake in this part of the World Ocean than previously stated. The larger observed estimates are likely caused by accounting for the subsurface phytoplankton maximum, an increase in phytoplankton concentration that is observed at depths larger than 15 m which are barely seen by the satellite data and usually are not accounted for in models. In addition to this, we used self-processed satellite data instead of the standard product, which allowed us to get more data in the northern areas, meaning having estimates for some areas previously reported as zero production.
As a result of our project we have developed the Greenland Sea algorithm that provides more accurate primary production estimates for this area when validated against in-situ data than the similar Arctic algorithms. Our primary production estimates and the algorithm itself can be used for any of the biogeochemical studies in the Greenland Sea in which the carbon dioxide uptake by the phytoplankton is taken into account. We developed the primary production algorithm primarily for the use by the scientific community, particularly as an input to biogeochemical models such as those used in IPCC reports. In addition to that, the researchers working with surface and deep sea biogeochemical field data are also potential users of the algorithm, as most studies dealing with the marine carbon dioxide uptake assessment require estimates of primary production. The fact that we provided Greenland Sea primary production estimates with higher accuracy than before gives opportunity to the researchers focusing on the Greenland Sea to obtain more accurate assessments of the carbon flux for this area.
The conclusions we’ve obtained in the course of developing the algorithm, listing the components that improved the performance of our algorithm, are important information for the model developers. This community could use our conclusions to improve the performance of other regional primary production models. The conclusions on the calculations of annual primary production for the area suggest a higher carbon dioxide uptake in the area than previously stated. This may not be substantial for the global carbon budget, but rather important for the understanding of the biogeochemical processes in the area. As an alternative to the scientific community, our algorithm could be used for the local fisheries industry needs, and to regionally improve the global satellite Earth Observation products, such as the Copernicus Earth observation component of the European Union''s Space programme products. To our current knowledge we’ve developed the first satellite primary production algorithm specialising on the Greenland Sea.