Effects of large fires on boreal forests of China : historical reconstruction and future prediction through landscape modeling

Boreal forests of China store about 350 Tg tree biomass carbon, which is approximately 24â€"31 [percent] of the total forest carbon storage in China, and thus, play an important role in maintain national carbon balance. Long-term fire exclusion and climate warming have foster larger and more severe fires. On 1987 May 6, a catastrophic fire, known as the Black Dragon Fire, occurred in this region, and burned 1.3 million ha. This fire is among the top five of such megafires ever recorded in the world, resulting in high degree of tree mortality and reset forest succession stage for most burned stands. Forests have grown back since, with much more homogeneous age classes and composition, which post new ecological risks and challenges. It is predicted that the warming will continue in the next century, and thus uncertainties exist in future fire regimes and vegetation response under novel climate. Chapter II estimate the burn severity and carbon emissions from the Black Dragon fire. I combined field and remote sensing data to map four burn severity classes and calculated combustion efficiency in terms of the biomass immediately consumed in the fire. Results of this chapter showed that 1.30 million hectares burned and 52 [percent] of that area burned with high severity. The emitted carbon dioxide equivalents (CO2e), accounted for approximately 10 [percent] of total fossil fuel emissions from China in 1987, along with CO (2 [percent] - 3 [percent] of annual anthropogenic CO emissions from China) and non-methane hydrocarbons (NMHC) contributing to the atmospheric pollutants. This study provides an important basis for carbon emission estimation and understanding the impacts of megafires. Chapter III developed a novel framework to spatially reconstruct the post-fire time-series of forest conditions after the 1987 Black Dragon fire of China by integrating a forest landscape model (LANDIS) with remote sensing and inventory data. I derived pre-fire (1985) forest composition and the megafire perimeter and severity using remote sensing and inventory data. I simulated the megafire and the post-megafire forest recovery from 1985-2015 using the LANDIS model. I calibrated the model and validated the simulation results using inventory data. I demonstrated that the framework was effective in reconstructing the post-fire stand dynamics and that it is applicable to other types of disturbances. Chapter IV investigated the effects of future fire regimes on boreal forests of China under a warming climate. I simulated species composition and distribution changes to the year 2100 using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). I focused on two possible fire regimes (frequent small fires and infrequent large fires). Results of this chapter showed that climate warming and fires strongly affected tree species composition and distribution in the boreal forests of China. Climate warming promoted transitions from boreal species to pioneer and temperate species. Fire effects acted in the same direction as climate change effects on species occurrences, thereby catalyzing climate-induced transitions. Frequent small fires exerted stronger effects on the species composition shifts than infrequent large fires. The combined effects of climate warming and fire on the shifts in species composition will accumulate through time and space and can induce a complete transition of forest type, and alter forest dynamics and functions.