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Paul Miller. Photo.

Paul Miller

Senior lecturer

Paul Miller. Photo.

Tundra shrubification and tree-line advance amplify arctic climate warming : results from an individual-based dynamic vegetation model


  • Wenxin Zhang
  • Paul Miller
  • Benjamin Smith
  • Rita Wania
  • Torben Koenigk
  • Ralf Doscher

Summary, in English

One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model-downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961-1990) agreed well with a composite map of actual arctic vegetation. In the future (2051-2080), a poleward advance of the forest-tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH4, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.


  • Dept of Physical Geography and Ecosystem Science
  • MERGE: ModElling the Regional and Global Earth system
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publishing year





Environmental Research Letters





Document type

Journal article


IOP Publishing


  • Physical Geography


  • arctic climate change
  • individual-based
  • dynamic vegetation model
  • vegetation change
  • land surface feedbacks




  • ISSN: 1748-9326