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2.8. Building a time machine out of a Delorean: Observing, reconstructing, and predicting vegetation change in the Arctic

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27 March 2025 | 10:30 - 12:00 and 16:00 - 18:00 (MDT)

Open Session - HYBRID

Room:  Glen Miller Ballroom in UMC - 208

Organisers:  Donald Walker (Institute of Arctic Biology, University of Alaska Fairbanks, USA); Gabriela Schaepman-Strub (Department of Evolutionary Biology and Environmental Studies, University of Zurich, Switzerland); Amy Breen (University of Alaska Fairbanks, USA)

 

Session Description:

Arctic landscapes are rapidly changing due to factors such as climate alterations, accelerated nutrient cycling, and increased disturbances like wildfires and resource development. These changes drive shifts in vegetation composition and function, serving as key indicators of broader transformations in topography, hydrology, and permafrost.

The Circumpolar Arctic Vegetation Science Initiative (CAVSI) is proposed for ICARP IV to establish a framework for classifying, mapping, and monitoring Arctic vegetation. It aims to create a network of sites with permanent plots representing diverse Arctic conditions, using standardized methods for vegetation surveys and data management. This initiative builds on existing monitoring sites in northern Alaska and could be integrated into U.S. and international Arctic observing networks. Alternatively, the community may identify a need to establish a novel Arctic Vegetation Observatory Network.

The session will highlight recent advances in Arctic vegetation classification and monitoring, particularly as we look ahead to the 5th International Polar Year (2032–2033), with the goal of implementing CAVSI based on lessons learned from other networks and putting forth a framework that aligns with the research priorities identified by ICARP IV. We also invite studies on the impacts of vegetation change on processes such as hydrology, permafrost degradation, and carbon balance. We welcome diverse research approaches to monitor vegetation across temporal and spatial scales, including field surveys, remote sensing, and Earth system models, thereby contributing to a deeper understanding of Arctic ecosystems

 

 

 

 

 

 

 

 

 

 

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