Microbes in the Arctic Ocean: How the ice edge becomes a model for future Arctic summers

The majority of life in the Arctic is comprised of microscopic organisms, including bacteria and algae, which inhabit the water and ice of the Arctic Ocean. These organisms play a pivotal role in marine food chains, as they are responsible for producing biomass from sunlight, water, and nutrients through photosynthesis. This biomass serves as the primary food source for zooplankton, small fish, and crustaceans, thereby forming the foundation of the Arctic food chain, which extends to apex predators such as sharks and orcas.

However, climate change is endangering their habitat, as rising temperatures and melting sea ice are radically changing the conditions in the Arctic Ocean. Projections indicate that the Arctic Ocean will be ice-free on a regular basis in summer by 2050. This will not only have an impact on Arctic inhabitants such as polar bears, but also on the microscopic organisms that form the foundation of the ecosystem.

To find out how these microbial communities are adapting to the new conditions, I traveled to the Arctic last year aboard the research vessel Polarstern. Next month, I will make this trip again to collect water and ice samples. Particular focus will be placed on microbial communities at the ice edge, which marks the transition between the ice-covered zone and the open water. At this point, conditions are subject to rapid change, which is similarly induced by climate change throughout the Arctic. The ice edge thus serves as a model for the future summers of the Arctic.

Mathematical modeling and statistics are essential for the analysis of marine microbial communities, as they facilitate the quantifiable description and prediction of complex ecological processes. Models enable the more accurate description and prediction of the interactions between different microorganisms and their environment. They facilitate the simulation of environmental changes, such as temperature and nutrient fluctuations, and their effects on microbial populations. Finally, they provide a deeper understanding of the underlying mechanisms that control natural microbial communities.

During our investigations, we collect samples and analyze the composition and adaptability of the microbes. We also employ remote access samplers (RAS), which automatically collect water samples over a period of one year. These samples allow us to monitor long-term changes and model the effects of climate change on microbial communities.

A phenomenon that is worthy of further investigation is Atlantification, which refers to the penetration of warm Atlantic water into the Arctic and the continued melting of sea ice. This process results in changes to nutrient conditions and a weaker stratification of the water column. The introduction of Atlantic microbes into Arctic habitats could displace native species, which could have a significant impact on the entire ecosystem.

Our preliminary findings suggest that microbes in the Arctic are highly influenced by changing conditions. In areas where there is a high influx of Atlantic water and little sea ice, bacteria from temperate zones colonize. Their composition varies depending on the season and food availability, particularly due to phytoplankton blooms. In pure Arctic water, on the other hand, typical polar bacterial communities that are specially adapted to life under or in the ice remain dominant.

Some glacial algae species appear to be better adapted to the new conditions than expected. These species also do well in Atlantic water, while typical algae from temperate latitudes have difficulties surviving in cold Arctic water. The temperature gradient between Arctic and Atlantic water thus forms a barrier that prevents mass immigration of Atlantic plankton.

Although the findings allow certain conclusions to be drawn about the long-term consequences of these changes for the Arctic Ocean ecosystem, the exact nature and effects on the marine food web remain unclear. The smallest changes in the composition of microbes could have catastrophic effects, as they form the basis of the entire marine food web. To make precise predictions, more extensive data and modeling are needed. Further data will be collected and analyzed on another expedition in early July to gain a better understanding of future changes and their effects.

If you would like to follow Ellen's expedition to the Arctic, you can find pictures and information on @ceplas_1  from July!

Planter’s Punch

Under the heading Planter’s Punch we present each month one special aspect of the CEPLAS research programme. All contributions are prepared by our early career researchers.

About the author

Ellen Oldenburg successfully completed her bachelor's and master's degrees in quantitative biology. She then started her PhD thesis with the MOSAiC project as her main topic. Through her work on this project, Ellen was able to establish valuable contacts with the Alfred Wegener Institute (AWI). This enabled her to participate in the 2022 and 2024 expeditions.

In addition to her scientific work, Ellen also has personal interests. In her spare time she likes to read and dance. This is a good creative balance to her research work.

The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) project is one of the largest international Arctic expeditions ever undertaken. The goal of the project is to gain a comprehensive understanding of the Arctic and its climate processes by drifting the research vessel Polarstern in the Arctic ice for one year, accompanied by numerous research teams from all over the world.

Further Reading

Ellen Oldenburg et al. (2024b). “Sea-ice melt determines seasonal phytoplankton dynamics
and delimits the habitat of temperate Atlantic taxa as the Arctic Ocean atlantifies”. In: ISME
communications 4.1, ycae027 doi: https://doi.org/10.1093/ismeco/ycae027

Taylor Priest et al. (2023). “Atlantic water influx and sea-ice cover drive taxonomic and func-
tional shifts in Arctic marine bacterial communities”. In: The ISME Journal 17.10, pp. 1612–
1625 doi: https://doi.org/10.1038/s41396-023-01461-6

Ellen Oldenburg et al. (2023b). “DeepLOKI-a deep learning based approach to identify zoo-
plankton taxa on high-resolution images from the optical plankton recorder LOKI”. in: Fron-
tiers in Marine Science 10, p. 1280510 doi: https://doi.org/10.3389/fmars.2023.1280510

Thomas Mock et al. (Oct. 2022). “Multiomics in the central Arctic Ocean for benchmarking
biodiversity change”. In: PLOS Biology 20.10, pp. 1–6. doi: 10 . 1371 / journal . pbio .
3001835. url: https://doi.org/10.1371/journal.pbio.3001835 doi: https://doi.org/10.1371/journal.pbio.3001835