A glimpse into the Arctic future equipping a unique natural experiment for next...
A glimpse into the Arctic future equipping a unique natural experiment for next generation ecosystem research
"Climate change will affect Arctic ecosystems more than any other ecosystem worldwide, with temperature increases expected up to 4-6°C. While this is threatening the integrity and biodiversity of the ecosystems in itself, the larg...
"Climate change will affect Arctic ecosystems more than any other ecosystem worldwide, with temperature increases expected up to 4-6°C. While this is threatening the integrity and biodiversity of the ecosystems in itself, the larger ecosystem feedbacks triggered by this change are even more worrisome. During millions of years, atmospheric carbon has been stored in the Arctic soils. With warming, the carbon can rapidly escape the soils in the form of CO2 and (even worse) the strong greenhouse agent CH4.
Despite decades of research, scientists still struggle to unveil the scale of this carbon exchange, and especially how it will interact with climate change. An overarching question remains: how much carbon will potentially escape the Arctic in the future climate, and how will this affect climate change?
FutureArctic embeds this research challenge directly in an inter-sectoral training initiative for early stage researchers, that aims to form ecosystem-of-things scientists and engineers at the ForHot site. The FORHOT site in Iceland offers a geothermally controlled soil temperature warming gradient, to study how Arctic ecosystem processes are affected by temperature increases as expected through climate change.
FutureArctic aims to pave the way for generalized permanently connected data acquisition systems for key environmental variables and processes. We will initiate a new machine-learning approach to analyse large high-throughput environmental data-streams, through installing a pioneer ""ecosystem-of-things"" at the ForHot site.
FutureArctic will thus channel, building on a timely project in the ForHot area, an important evolution to machine-assisted environmental fundamental research. This is achieved through the dedicated training of researchers with profiles at the inter-sectoral edge of computer science, artificial intelligence, environmental science (both experimental and modelling), scoial sciences and sensor engineering and communication.
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