Dominant vegetation distribution
Figure 1. Dominant vegetation distribution. (a) A composite vegetation map based on a potential natural vegetation (PNV) map (Kaplan et al 2003), the IGBP land cover dataset 2000–2001 (Friedl et al 2010), and the Circumpolar Arctic Vegetation Map (Walker et al 2005). (b) The recent dominant PNV simulated by the CRU-forced run. (c) The recent dominant PNV simulated by the RCAO-forced run. (d) The future dominant PNV simulated by the RCAO-forced run. *: the color of IBS represents temperate needle-leaved evergreen forest in the sub-plot (a).
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.