Over the past several decades, wildfire has become more frequent in Alaskan arctic tundra, an important ecosystem regulating the global carbon budget. As climate warms, discernible changes in vegetation composition and carbon, nutrient and water cycling have been observed in the arctic tundra, Alaska. The major questions of this research are: To what degree do the intensity and pattern of fire influence observed changes in vegetation structure and carbon cycling of tundra ecosystem. And, how do the effects of fire interact with a changing climate? In this study, we use the multiple element limitation (MEL) model to simulate the carbon, nitrogen, phosphorus, and water cycling under various climate and fire disturbance conditions. Parameters for biogeophysical and biogeochemical processes were first calibrated to field measurements from the arctic Long Term Ecological Research (LTER) site. Simulations were then run for the past and current centuries. We compared the patterns of biomass and soil carbon recovery with different burn severities and warming intensities, and assessed the relative significance of fire disturbance and climate variability in terms of their impacts on changes in tundra biogeochemistry and carbon balance.
Results/Conclusions
Fire severity largely determined the postfire trajectory of biomass recovery. Patterns of nutrient limitation and other resource limitation (e.g., light and water) change significantly during the early succession (i.e, the first five years). Over 1000 years, tundra plant growth is most limited by nitrogen availability. Tundra biomass recovers much faster than the boreal forest species, while soil carbon requires decades to centuries to totally recover to the prefire level. Climate variability also plays a role in vegetation recovery and carbon dynamics. As climate warms, the Arctic tundra becomes more woody, but shifts from a carbon sink to a carbon source during the 21st century. Fire induced changes in biomass and the C budget are much larger than those caused by climate variability.