Climate feedbacks at the tundra-taiga interface.
Feedbacks, or internal interactions, play a crucial role in the climate system. Negative feedback will reduce the impact of an external perturbation, a positive feedback will amplify the effect and could lead to an unstable system. Many of the feedbacks found in the climate system are positive; thus, for example, increasing CO2 levels will increase temperature, reduce the snow cover, increase the absorption of radiation and hence increase temperature further. The most obvious feedbacks, such as the snow example quoted above, are already included within our models of the climate and earth system. Others, such as the impact of increasing forest cover due to global warming, are only just being included. Others, such as, the impact of global warming on the northern peatlands and the impact of freshwater flows on the Arctic Ocean are not yet considered. The contrast in surface characteristics between low tundra vegetation to high taiga forest is considerable. The contrast is greatest in the winter, when the tundra is snow covered but the trees of the taiga protrude through the snow pack, and is probably the greatest contrast found on the land surface anywhere. This variation causes massive changes in the energy fluxes at the surface and hence the temperature conditions on the ground and within the atmosphere. There will be large resultant changes in the vegetation development, the carbon fluxes, the permafrost and the hydrology. The Arctic is already experiencing change and it is essential for us to understand the basic processes, and how these interact, to be confident of our predictions of environmental change in the future.
Harding
Richard
R
Land/Atmosphere Interaction Section, Centre for Ecology and Hydrology at Wallingford, England. rjh@ceh.ac.uk
Kuhry
Peter
P
Christensen
Torben R
TR
Sykes
Martin T
MT
Dankers
Rutger
R
van der Linden
Sandra
S
D000388:Air; D001110:Arctic Regions; D003081:Cold Climate; D004782:Environmental Health; D005246:Feedback; D005544:Forecasting; D005618:Fresh Water; D017752:Greenhouse Effect; D006292:Health Priorities; D006801:Humans; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D012106:Research; D012621:Seasons; D012680:Sensitivity and Specificity; D012914:Snow; D013696:Temperature; D013816:Thermodynamics; D014197:Trees / Q000502:physiology*; D014887:Weather