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Wildfire, Ecosystems, and Climate: Examining the Relationships Between Weather, Extreme Fire Events and Fire-Induced Land-Cover Change in the Changing Climate of Siberia

Team Members:

Person Name Person role on project Affiliation
Amber Soja Principal Investigator NASA Langley Research Center, Hampton, United States
Abstract

This research is focused on elucidating the factors that force the dominant driver of Land Cover Change (LCC) in Siberia, fire, which is shaped by human and climate dynamics. It is predicted warming in Northern Eurasia will exceed 40% of the global mean. Our investigation found January temperatures in the south central Siberian Sayani mountain range have already exceeded 2090 Atmosphere Ocean General Circulation Model predictions. Additionally, we concluded that 7 of the last 9 years have resulted in extreme fire seasons, which implies the definition of a “normal” fire year may already be changing. We contend that fire, under the influence of weather, climate and human management, is a mechanism to maintain vegetation stability and diversity in equilibrium with the climate and also a mechanism by which land cover moves more quickly towards a new equilibrium with changing climate. Our research demonstrates the affects of fire and weather are regional and particularly evident in ecotones at upland and lowland treelines of mountainous regions and at the far southern and northern reaches of Siberia. The strong influence of fire weather in Sakha (northern Siberia) is pictured in figure 1, which is information that can be used to predict future vegetation change, driven by fire, weather and climate (figure 2). In Tuva (southern Siberia), we highlight the disappearance of the relic Pinus sylvestris forests, which are first burned and then lack weather conditions conducive for germination and survival. Notably, we found there is already substantial evidence of warming- and fire-induced LCC across Northern Eurasia, which suggests a potential nonlinear rapid response to climate change, as opposed to the predicted slow linear response to climate change.

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