The Natural Cycle

The Arctic glaciers and ice caps experience seasonal cycles of melting and freezing. The polar night is a period of complete darkness when the sea and land are covered by snow and ice (Figure 1A). When the first rays of polar day reach the area, the ice on both land and sea melts and shrinks, and rivers start to deliver glacial meltwater to the coastal zones. It is spring—the most productive time of the year. Tiny marine plants, called phytoplankton, grow and multiply quickly, using sunlight and nutrients in the water to produce food via photosynthesis. Zooplankton, which are small animals carried along by water currents, feed primarily on phytoplankton. In the Arctic, zooplankton are most numerous during summer, which is also the main melting season (Figure 1B). During the summer, zooplankton must accumulate fat to survive hibernation over the winter. When polar night comes, there is less sunlight and temperatures decrease quickly. Ice and snow accumulate on land and water. Rivers become frozen and their run-off into the ocean ceases.

The natural seasonal cycle of the Arctic is being altered by global warming. Ice and snow are starting to melt more quickly and earlier in the season, and less ice is formed in winter. But warming does not only affect physical structures such as glaciers; it is also responsible for many changes in the Arctic’s marine ecosystem.

What Does A Warming Arctic Mean For Coastal Waters?

In polar regions, coastal waters are undergoing remarkable changes. To study them, every summer we go to the Svalbard archipelago in the Arctic. It is a perfect place to study the effects of global warming due to the observed increased flow of warm oceanic water from the Atlantic (Figure 1C, red arrow) and accelerated glacial melting. Freshwater from melting glaciers flows to the sea and brings mud from the land. The muddy water causes seawater darkening, since the mud particles prevent light from penetrating the water. In satellite images, we can see that the dark waters spread further and further every year. Light influences the life cycles and growth of all marine organisms. If changes in underwater light during the Arctic summer become severe, phytoplankton will not be able to photosynthesize, so they will become less abundant. A decrease in phytoplankton creates unfavorable food conditions for zooplankton and decreases their growth, which can then negatively affect fish, polar bears, seals, and seabirds [1].

Challenge Accepted

Although seawater darkening caused by glacial meltwater can have serious effects on the marine ecosystem, it has received less attention than sea ice loss [2, 3]. Since we believe seawater darkening is just as important as other effects of global warming, we took up the challenge of studying it! We geared up with a lot of equipment and went to the Arctic to catch the muddiest water coming from land (Figure 2A). We used a digital camera to snoop on marine organisms in their natural environment (Figure 2, edges). We also used special devices to measure underwater light distribution, counted particles, and examined plankton. We studied areas with clear, open waters outside the “brown zones,” as a comparison (Figure 2B). We determined the levels of turbidity in each of the areas we studied. Turbidity is a measure of how dirty the water is.

Underwater Snow

In the glacial bays, turbidity was high, which means that the water was dirty. It had a milky brownish color due to the presence of small particles delivered from the land (Figure 3A, Table 1). These particles tended to stick together creating “flakes,” which gave us the impression of an intensive underwater snowstorm. In contrast, turbidity was extremely low in clear waters, which had a green color due to the presence of pigments in the phytoplankton (Figure 3B). Marine snow was less abundant in clear waters and it was composed of flocks of dead phytoplankton, zooplankton, and feces—signs that organisms are living there.

Inside the “brown zones,” phytoplankton was only present close to the surface, where it could catch every ray of light. Zooplankton was also less abundant and was the least abundant in shallow, enclosed areas where water exchange was limited. However, some zooplankton species were affected less than others, because they can feed on marine snow. One type of zooplankton, called gelatinous zooplankton (or jellies), turned out to be a good indicator of darkening conditions. Although they are predators that use their sense of touch and do not need light to catch their prey, jellies were scarce in the murky waters, probably because there was less food available close to glaciers—they feed on small zooplankton, or that the marine snow particles could clog their sticky tentacles.

From Observations to Predictions

We obtained a lot of information from our measurements, but our data could not tell us everything we wanted to know about how plankton and particles interact in such worsen conditions during Arctic summer. To learn more, we created computer models, which are programs that use mathematical equations to help scientists better understand their observations and make predictions about the future. To represent the physical conditions (temperature, salinity, currents, etc.) in our study region, we used a model called GOTM. To represent the living matter (phytoplankton, zooplankton, etc.), we used a model called ECOSMO. These two models were linked together, which allowed us to create a virtual world representing our study site. Our model contained general knowledge of who-eats-whom in the Arctic marine ecosystem.

How does the model work? For every day of the year, we input the data that are measured or modeled, including water temperature, salinity (saltiness), and the amount of mud delivered from land. The model uses this input to calculate how the organisms eat and grow. The output from the model is the weight of each group of organisms, which tells us how abundant each group is. The model is structured to give us the weight of phytoplankton, zooplankton, and the larvae of organisms living on the ocean bottom. So far, the model results and our field data show similar trends for all these plankton groups, which is good news! It means that the first step of our model development is working well.

The next step is to use our simple model to predict how gradual warming will affect various plankton groups. To do that, we need to run simulations with possible future environmental data, to predict what might happen to each group of organisms. We can test many things that have not yet happened in the real world; for e.g., we can use our model to predict what will happen to our marine ecosystem if the air and ocean temperatures continue to rise as predicted by climate models. Our model predicts that higher temperatures will result in more mud and marine snow in our future coastal waters. We can continue to improve and modify our model all the time, based on the real-world data we collect. At some point, we hope that this model will become an even more complex and powerful tool to help researchers make predictions upon which we can base actions to protect Arctic ecosystems.

Summary

The Arctic experiences effects of climate change that are more pronounced than anywhere else on Earth. Its future is unclear. There may be a moment called a tipping point, when warming will become irreversible and begin to spread like a wildfire. We certainly will not be able to stop all the changes that will happen in the Arctic ecosystem, but we can observe them, to prepare us for the future. By studying what is happening in darkening waters, we noticed that dark water has a negative effect on plankton, especially on jellies. Changes in the populations of small planktonic organisms can travel up the food chain and possibly have negative effects even on top predators, altering the entire Arctic ecosystem. We are continuing to design virtual experiments that incorporate the essential components of the Arctic coastal waters. Using these computer models, we hope to better understand the aftermath of seawater darkening caused by glacial melting. More research is needed because, at this point, we still do not know how strong the impact of seawater darkening on plankton—and possibly the whole Arctic food web—will be in the future.

Funding

This study was funded by Polish National Science Centre project (NCN, CoastDark2018/29/B/NZ8/02463), Polish Ministry of Science and Education grant (AREX Project 3547/Norway/2016/2), DAAD short-term research grant 2020 (57507441), Changing Arctic Ocean project MiMeMo (NE/R012679/1) jointly funded by the UKRI Natural Environment Research Council (NERC), and the German Federal Ministry of Education and Research (BMBF/03F0801A). This survey was additionally supported by the statutory activity of the Institute of Oceanology Polish Academy of Sciences (IO PAN).

Glossary

Phytoplankton: ↑ Marine organisms that live in the surface waters and use photosynthesis to grow. They are food for zooplankton.

Photosynthesis: ↑ The process of creating energy (in the form of sugar) from sunlight and carbon dioxide. Photosynthesis is used by plants, algae, and certain bacteria.

Zooplankton: ↑ Small organisms that drift with water currents. They are food for fish, seabirds, and whales.

Marine Ecosystem: ↑ Communities of bacteria, plants, and animals living and interacting with each other in an aquatic environment such as sea or the ocean.

Seawater Darkening: ↑ Worsening underwater light conditions due to the presence of many particles, which prevent light from penetrating the water.

Turbidity: ↑ The measure of relative clarity of a water.

Marine Snow: ↑ Macroscopic aggregates of detritus, living organisms, and inorganic particles falling from the upper layers of the water column to the seafloor.

Computer Model: ↑ Set of mathematical equations that describe the behavior of natural systems and that are used to simulate what might or what did happen.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.