Investigating ecosystem tipping points and cascades in the Arctic Seas

Floating iceberg in Eriksfjord, Greenland
Floating iceberg in Eriksfjord, Greenland ©istockphoto/HRAUN
Melting ice in the Arctic is a tipping element

The reduction of Arctic sea ice and melting of the Greenland Ice sheet are examples of tipping elements which have global effects within the earth system. Between 1994 and 2017, about 28 trillion tons of ice entered the seas globally, of which about 60% was from the Northern hemisphere. The Greenland ice sheet alone lost more than 530 billion tonnes in 2019. All of this additional freshwater input into the seas has several effects. First, it contributes to sea level rise, which is perhaps the most well-known effect. The additional input of freshwater also affects the chemistry and physics of the ocean, as freshwater has different a composition and density than sea water.

More freshwater = more layering in the ocean

As more freshwater enters into the seas within the Arctic, it creates a layer of less-dense water on top of the more saline water, thus strengthening the stratification (layering) of the Arctic seas. This disrupts the vertical mixing of water, which is typical of polar seas. It can potentially disrupt the upward mixing of nutrients that support a high primary production and eventually productive fisheries, while also preventing or slowing the sinking of cold, salty water that drives the circulation patterns and deep-sea currents. It is for this reason that scientists worry that the Atlantic Meridional Overturn Circulation (AMOC) which Gulf Stream in the Atlantic Ocean is part of, may weaken, with knock on implications for the global climate.

At the same time, the Arctic is changing in other, similarly profound ways. Water temperatures are increasing at a rate that is twice the global average, species from temperate regions are appearing and polar species are moving northward, and the timing of annually recurring events is changing. It is clear that biodiversity and the ecosystem functions in Arctic waters are being assaulted and irrevocably altered. However, the impact that these changes will have on two key ecosystem services, fisheries and carbon sequestration, is still largely unknown.

Physical changes can trigger biological changes, creating a cascade
Herrings in a fishing net
Herrings in a fishing net ©iStockphoto/Paolo Cipriani

When a threshold is crossed in one part of the system, such as melting of the Greenland Ice Sheet, it can result in changes in another partw of the system, such as the open ocean ecosystem, which can reach its own tipping point – an ecosystem regime shift where one type of marine community changes to another type of community. This is called a tipping cascade with multiple tipping points. A decrease in Arctic Sea Ice and melting of the Greenland Ice sheet, and subsequent increase in freshwater inflow and stratification, can trigger a change in the biological system: an “ecosystem tipping cascade”.

Much of the annual primary production in a seasonally-pulsed pelagic system typically takes place during the spring bloom, when abundant nutrients and sufficient light support a high production of large phytoplankton. The theory is that with warming and / or freshening of the surface waters, the layering - or stratification - would strengthen. This could trigger a change in the phytoplankton production and community composition – an ecosystem tipping cascade with consequences that could cascade all way up to marine mammals, fisheries production, human systems and global climate.

Where does ECOTIP come in?

ECOTIP operates at this important link between the physical and biological systems, where a regional change in the hydrography of the Arctic Ocean might trigger a biological change at the base of the marine food web with cascading effects both on the regional and local socio-economic systems through fisheries, and on the global climate through carbon sequestration. ECOTIP is attempting to anticipate and predict these changes. Yet a few knowledge barriers still exist:

A diatom, which is a type of phytoplankton,under the microscope
A diatom, which is a type of phytoplankton,under the microscope
©iStockphoto / Elif Bayraktar

We still don´t have a good understanding how marine biodiversity in the Arctic is responding to pressure from multiple sources. These include climate-related pressures such as temperature, salinity and pH, as well as land and ocean-based stressors in the form of invasive species, pollution such as heavy metals, marine litter and oil, and fishing. How organisms will respond to combinations of these stressors is largely unknown.

Our current way of describing marine biodiversity and modelling it has its limitations. Despite a century of detailed taxonomic studies, over 90% of the Arctic marine species (macro-organisms) are currently thought to be undiscovered. This makes it difficult to connect species, ecosystem functions and services, and hampers efforts to model the system.

We are unable to predict what are the consequences of the changes in plankton community composition for either carbon sequestration or fisheries.

Our knowledge is still fragmented of how biological changes are interacting with human decisions and behaviour, including how fisheries resources are managed in the Arctic. This limits our ability to develop adaptation options jointly with local communities and Indigenous Peoples in the Arctic.

How will ECOTIP address these issues, and how is it unique?
A Norwegian Polar Institute research vessel undertaking Arctic fieldwork
A Norwegian Polar Institute research vessel undertaking Arctic fieldwork
©fruchtzwerg's world

We will apply new molecular methods on environmental DNA (“eDNA”) to detect invasive species in the Arctic. eDNA refers to DNA molecules that can be collected from the environment (e.g. water samples). The usage of eDNA for species monitoring is revolutionary as it saves time, costs, and workload without impairing neither the target organism nor the ecosystem.

We will also apply the latest developments in paleo-oceanography by examining sediment cores, to peer into the past one thousand years, giving new insights into on the effects of multiple stressors and the speed of the recovery in marine biodiversity.

We will apply the traits-based approach: we will approach changes in Arctic biodiversity and associated ecosystem consequences through a trait-based approach, where species will be replaced by their functional traits. This helps us to overcome the challenge that a large amount of unknown species still exist. A trait-based approach also allows for realistic scenarios of biodiversity change as a response to multiple anthropogenic stressors, since the likelihood of regime shifts, changes in food web interactions or the stability of the ecosystem can be studied as a function of trait composition.

A fishing vessel in Uummannaq, Greenland
A fishing vessel in Uummannaq, Greenland. ©GRID-Arendal

We will fill crucial gaps in understanding the biological pump: we will provide mechanistic understanding of the unknown processes that are ignored in current model representations of the biological pump, such as autotrophic production by archaea in the twilight zone, export flux due to sinking of small phytoplankton and cyanobacteria, and degradation of export flux by particle-colonising zooplankton – all of which have the potential to radically change the Earth System Model predictions that IPCC and other assessments rely on.

We will co-create knowledge with local communities in the Arctic: We will work closely with fisheries communities and other groups in Greenland and elsewhere, drawing on in-depth traditional knowledge of local societies and stakeholders, and bring in research and insights into invasive species and their monitoring, ecosystem service changes, predictions of ecosystem tipping cascades, and socio-economic modelling and forecasting. This two-way process will both increase our knowledge on the future Arctic ecosystem, and help to co-create adaptation scenarios.

We will develop Bayesian networks, which are networks of connected variables that can generate predictions based on assumptions. Bayesian networks can be used to predict the ecosystem vulnerability through different stressor combinations. It can also be used as a knowledge-driven tool to interact with our stakeholders and target groups, for example by exploring various ecosystem scenarios.