Greenfjord project

Study of the Greenland fjord ecosystem in a changing climate: socio-cultural and environmental interactions

The acceleration of climate change in the Arctic is having a profound effect on Greenland’s fjord systems. These systems are fragile because of the delicate link between the cryosphere, ocean, land, atmosphere and biosphere. Moreover, these iconic Greenlandic landscapes are at the heart of the socio-economic and cultural systems that govern local livelihoods. Warming induces the melting of glaciers and the detachment of ice blocks (calving), leading to a sharp increase in surrounding freshwater flows. Changes in these flows have an impact on the dynamics of marine ecosystems and the circulation of nutrients, which in turn affect the marine food web (food webs describe the food interactions between species in an ecosystem) with cascading effects: at lower trophic levels, changes in phytoplankton proliferation have an impact on atmospheric chemistry and cloud formation, and therefore on the surface radiation balance. At higher trophic levels, fish are affected, with major implications for local livelihoods and economies, which depend heavily on marine resources.

With GreenFjord, we want to better understand how climate change is affecting fjord ecosystems and how this is impacting biodiversity and livelihoods. The ultimate goal is to translate this new knowledge into models that can simulate and predict the future evolution of fjord systems, including glacial mass loss, trophic evolution and the carbon cycle. Our fieldwork will be carried out on land and at sea and will involve a high degree of participation by local populations. The main activities are as follows:

Cryosphere

Glacier evolution and impact on fjord water and nutrient circulation

Ocean

Physical and microbial characteristics of fjord systems

Biosphere

Determination of biodiversity using environmental DNA

Atmosphere

Influence of local natural emissions on cloud formation

Earth

Export of terrestrial organic matter to the ocean

Human

Understanding the relationship between local livelihoods and fjordic socio-ecosystems

Energy demonstrator

Swiss energy production from renewable sources is still very dependent on the seasons. In summer, there is a huge overproduction, while in winter we have to import several TWh. A demonstrator has been installed in Sion to convert solar energy into gas and store it for reuse in winter.

GEM, MER Jan Van Herle

A “Power-to-Gas” demonstrator has been installed on the Sedun campus. This is a unique experimental platform in Switzerland. This infrastructure enables the most promising technologies in the energy transition to be tested on a real scale, from the capture of CO₂ to the seasonal storage of energy in the form of hydrogen or methane. The result of collaboration between EPFL, HES-SO and several industrial players, this demonstrator places Valais at the heart of innovation in the production of cleaner, circular energy. While MER Van Herle’s laboratory is responsible for the reversible fuel cell needed for the process to run smoothly, several other EPFL professors are involved in the demonstrator: Prof. Wendy Queen, Prof. Kumar V. Agrawal and Prof. F. Maréchal.

The process can be summarised as follows:

Production of photovoltaic energy using panels installed on the roof of the HES-SO Valais Wallis campus
Decarbonisation and carbon storage for initial injection into methanisation plants
Hydrogen production using a reversible solid oxide fuel cell operating at 750°C
Transformation of the hydrogen produced into methane, in particular by adding_CO2 extracted in phase 2 (for the first cycle, the_CO2 is then reused in a closed circuit)
Methane (CH4) storage in the Sion gas network, in collaboration with Oïken
In winter, gas is extracted from the public grid as required and converted into electricity and heat using a reversible solid oxide fuel cell. The process recovers just under 50% of the initial solar energy.

AI and corals

Based on images taken by cameras, an AI developed at the EPFL can reconstruct coral reefs in 3D in just a few minutes. A minor revolution for seabed study and preservation missions such as those of the Transnational Red Sea Center.

ECEO, Prof. Devis Tuia

Although they may appear in the background in the shots of shimmering fish taken by diving enthusiasts, corals are at the forefront of many scientists’ minds, given their fundamental ecological role. These animals with their limestone skeletons are among the most diverse ecosystems on the planet: although they cover less than 0.1% of the total surface area of the oceans, they are home to almost a third of known marine species. They also have a major impact on the lives of people in many reef-bordered countries: according to a study by the US Oceanic and Atmospheric Administration, up to half a billion people worldwide depend on coral reefs for their food security and tourism-related income. Endangered by rising ocean temperatures and local anthropogenic pollution, which cause coral bleaching and death, corals are the subject of in-depth studies, such as those carried out by the Transnational Red Sea Center (TRSC), which aims to unlock the secrets of Red Sea species that are particularly resistant to the stresses of climate change. DeepReefMap, an artificial intelligence developed by the Laboratory of Computational Science for the Environment and Earth Observation (ECEO) at EPFL, was tested as part of this EPFL-led mission*. It is capable of reconstructing several hundred metres of coral reefs in 3D on the basis of an underwater film taken by a commercial camera in just a few minutes. It can also recognise and quantify certain coral characteristics. “This method democratises the digital reconstruction of reefs and gives a major boost to their monitoring by reducing the work, equipment, logistics and IT costs involved,” points out Samuel Gardaz, TRSC project manager. This research has now been published in Methods in Ecology and Evolution.

Classify corals according to their state of health and shape

In order to further facilitate the work of their biologist colleagues working in the field, the scientists have included semantic segmentation algorithms to classify and quantify corals according to their state of health – from healthy, i.e. very colourful, to dead and covered in algae, via the white of bleaching – and to identify the forms of coral growth that are most common in the shallow reefs of the Red Sea according to an internationally recognised hierarchy – branching, massive, hard, soft, etc. -. “The aim was really to meet the needs of scientists and conservationists working in the field with a tool that can be deployed widely and very quickly: in Djibouti, for example, there are 400 km of coastline”, stresses Jonathan Sauder, who made the development of this AI the subject of his doctoral thesis. “Our method does not require a costly IT infrastructure: on a computer equipped with a simple graphics processing unit, semantic segmentation and 3D reconstruction can be obtained in the same amount of time as the video”.

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