Warming-induced drought stress and El Nino-associated summer precipitation failure are responsible for increased forest fire intensities of tropical and temperate forests in Asia and Australia. However, both effects are unclear for boreal forests, the largest biome and carbon stock over land. Here, we combined fire frequency, burned area, and climate data in the Altai boreal forests, the southmost extension of Siberia’s boreal forest into China, and explored their link with El Nino–Southern Oscillation (ENSO). Surprisingly, both summer drought severity and fire occurrence showed significant (p < 0.05) correlation with La Nina events of the previous year and therefore provide an important reference for forest fire prediction and prevention in Altai. Despite a significant warming trend, the increased moisture over Altai has largely offset the effect of warming-induced drought stress and led to an insignificant fire frequency trend in the last decades, resulting in largely reduced burned area since the 1980s. The reduced burned area can also be attributed to fire suppression efforts and greatly increased investment in fire prevention since 1987.

Lightning-ignited fire is sensitive to climatic change and responsible for large fires in boreal forests. In addition to global-warming caused fire increase, large-scale climate oscillations have significantly contributed to fire variability. However, the leading climate oscillation driving lightning-ignited fire and the mechanisms connecting regional and large-scale climate in the boreal forest of Northeast China, the most fire-prone biome of China, are still unclear. By compositing fire, climate, and atmospheric data, we found that the previous Atlantic Multidecadal Oscillation (AMO) was significantly coherent with the May to August temperature–evapotranspiration variability and lightning-ignited fire occurrence. These connections were valid at both the interannual and multidecadal time scales. Different from previous viewpoints, we found no connection of fire occurrence with the El Niño-Southern Oscillation and Pacific Decadal Oscillation. A warm AMO was followed by high sea level pressure and geopotential height over the study region. We assume these atmospheric anomalies are associated with descending atmospheric motion, producing adiabatic warming and less precipitation on the land surface, both of which favour high fuel aridity and lightning ignition. Therefore, we believe that the winter AMO could be a promising predictor for lightning-ignited fire occurrences in the following summer.

The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM_2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km²). In comparison, the PM_2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.

All-season warming is assumed to advance snowmelt and delay snow accumulation; additionally, coupled with warming-induced drought stress, all-season warming could extend both the beginning and the end of the fire season. Using fire data updated for 1968–2018, we found an asymmetrical expansion of the lightning fire season in the boreal forest of Northeast China. Lightning fires have not advanced into the early fire season (May–June) but have largely extended into the snowless late fire season (July–September) since the late 1990s (mean end Julian date delayed by 51.1 days for 1998–2018 compared with 1968–1997, p < 0.001). Despite significant warming, the Julian days of snowmelt have changed only slightly, which has prohibited the fire season from advancing into early spring. The expansion of lightning fires into July–September was associated with a warming-induced significant increase in evapotranspiration and a decrease in soil/fuel moisture.

The Altai Mountains, located in the northwesternmost part of China, have a harsh climate and little human activity, making it an excellent location to study forest ecology undisturbed by human interference. The forest is frequently struck by lightning and experiences long-term natural fire disturbances, leading to the evolution of unique fire adaptation traits in the major conifer species. To explore the role of natural fire disturbances in the Altai Mountain forest ecosystem, we conducted a study on the fire adaptation traits of Larix sibirica, Pinus sibirica, Picea obovata, and Abies sibirica, and reconstructed the fire history of the forest area over the past 100 years. We investigated three representative forest areas with varying fire disturbance conditions and habitats in the Altai Mountains. Data on fire disturbance conditions, relative air humidity, and species composition were collected in these areas. Basal diameter to diameter at breast height, relative bark thickness, and under-crown heights were measured and counted for each of the four species, and litter, bark, and wood layers were sampled and analyzed for physicochemical properties (ash, fat, and higher heating value) for each of the four species in the plots examined. We conducted a count of the four conifer species in the forest for each fire adaptation index and analyzed the differences in fire adaptation traits among the species. Larix sibirica showed fire-tolerant traits, Pinus sibirica displayed fire-embracer traits, and Picea obovata and Abies sibirica exhibited fire-avoider traits. Through the analysis of stand composition and exposure to fire disturbance in the different forest areas, we were able to correlate the fire-adaptive strategies of the four conifers with stand characteristics under varying fire disturbances and habitats. The interaction between forests and fires, and their adaptation to each other, ultimately create the current ecosystems in the Altai Mountains.

Forest fire is one of the dominant disturbances in the forests of Heilongjiang Province, China, and is one of the most rapid response predictors that indicate the impact of climate change on forests. This study calculated the Canadian FWI (Fire Weather Index) and its components from meteorological record over past years, and a linear model was built from the monthly mean FWI and monthly fire numbers. The significance test showed that fire numbers and FWI had a very pronounced correlation, and monthly mean FWI was suitable for predicting the monthly fire numbers in this region. Then FWI and its components were calculated from the SRES (IPCC Special Report on Emission Scenarios) A2 and B2 climatic scenarios, and the linear model was rebuilt to be suitable for the climatic scenarios. The results indicated that fire numbers would increase by 2.98–129.97% and −2.86–103.30% in the A2 and B2 climatic scenarios during 2020–2090, respectively. The monthly variation tendency of the FWI components is similar in the A2 and B2 climatic scenarios. The increasing fire risk is uneven across months in these two climatic scenarios. The monthly analysis showed that the FFMC (Fine Fuel Moisture Code) would increase dramatically in summer, and the decreasing precipitation in summer would contribute greatly to this tendency. The FWI would increase rapidly from the spring fire season to the autumn fire season, and the FWI would have the most rapid increase in speed in the spring fire season. DMC (Duff Moisture Code) and DC (Drought Code) have relatively balanced rates of increasing from spring to autumn. The change in the FWI in this region is uneven in space as well. In early 21st century, the FWI of the north of Heilongjiang Province would increase more rapidly than the south, whereas the FWI of the middle and south of Heilongjiang Province would gradually catch up with the increasing speed of the north from the middle of 21st century. The changes in the FWI across seasons and space would influence the fire management policy in this region, and the increasing fire numbers and variations in the FWI scross season and space suggest that suitable development of the management of fire sources and forest fuel should be conducted.