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Direct effects of climate change (i.e. temperature rise, changes in seasonal precipitation, wind patterns and atmospheric stability) affect fire regimes of boreal forests by altering fire behaviour, fire seasons and fuel moisture. Climate change also alters species composition and fuel characteristics, which subsequently alter fire regimes. However, indirect effects of climate change are often simplified or neglected in the direct climate–fire relationship models and dynamic global vegetation models. This may result in high uncertainties associated with existing projections of fire regimes for climate change scenarios. Moreover, few studies have examined fire regime predictions beyond the 21st century, and consequently, how the fire regimes of boreal forests would respond to climate change at the long term (>100 years) are not clear.We develop a coupled modelling framework integrating direct and indirect effects of climate change to predict fire occurrence probability and burned area for boreal forests in northeastern China. We applied repeated measures ANOVA to quantify direct and indirect effects of climate change on fire regimes in the short (0–50 years), medium (60–100 years) and long term (150–200 years).Results showed that for the 21st century, direct effects of climate change are likely to exert a stronger influence on fire regimes than indirect effects. However, increases in fire occurrence probability and burned area will accelerate the transition of boreal forests to temperate forests in the period 2100–2200, and thereby reduce fire occurrence probability and burned area. This suggests that vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term.Synthesis and applications. Vegetation change will mediate direct effects of climate change on fire regimes of boreal forests at the long term. This finding suggested that policymakers may consider adaptive management by planting deciduous species to reduce fire occurrence probability and resistant management by reducing competition to promote boreal species under changing climate conditions. [ABSTRACT FROM AUTHOR]

Climate change has been observed to significantly influence forest growth, community composition, and species distribution ranges. These influences in turn will impose continuous impacts on forest production and carbon (C) storage potential. Forests in the subtropical China that are experiencing rapid regeneration and recovery may suffer multiple threats in the face of future climate change. Understanding how climate change may affect forest C sequestration and species dynamics over time will help formulate better management strategies for maintaining forest productivity and biodiversity. Here, we used a forest landscape model (LANDIS-II) to evaluate the long-term effects of current business-as-usual (BAU) management and climate projections (current, RCP4.5, and RCP8.5 climate scenarios; IPCC representative concentration pathways [RCPs] scenarios) on above- and belowground forest C storage and tree species dynamics in the Sangzhi County in the subtropical China. Our simulations showed a fast-growing period of forest total C in the first 70 yr, regardless of climate regime. Moderate climate change (RCP4.5 climate scenario) increased soil organic carbon (SOC) (12%) and detrital C (16%) but reduced live C (5%), contributing to a slight augment of 3% in forest C storage compared to the control climate, while severe climate change (RCP8.5 climate scenario) decreased SOC (16%), detrital C (27%), and live C (12%), resulting in a dramatic reduction of 14% in forest C storage, primarily because severe warming-induced water stress restrained species establishment and regeneration in temperature-sensitive areas like the lower elevations. Meanwhile, nature reserves in the higher elevations could act as "safe islands" by providing suitable conditions for most tree species, but the logging ban caused higher canopy closure, which in turn inhibit the growth and establishment of shade-intolerant species. The results also highlighted the positive responses of native "warm species" to climate warming and suggest that using them to replace some conventional coniferous plantation tree species would better mitigate the future climate change. Poor performance of the current BAU management in maintaining forest productivity and diversity suggests that new climate-adapted management strategies should be designed accordingly. [ABSTRACT FROM AUTHOR]

[Display omitted] • The effects of near-natural restoration on post-fire forest in the wildland-urban interface were quantified. • Near-natural restoration increased post-fire forest biomass and biodiversity more than natural succession. • Near-natural restoration shortens the evolution time of fire trails to mature forest. • Near-natural restoration can accelerate post-fire forest recovery in the wildland-urban interface. Forests in the wildland-urban interface (WUI) are of high value but vulnerable to wildland fires due to abundant fire ignitions and flammable forest fuels. Restoring the post-fire Wildland-Urban Interface (WUI) forest landscape is of utmost importance in order to maintain ecosystem service provision. The near-natural restoration strategy is widely employed in vegetation restoration as it enables the formation of healthy, stable, and diverse artificial mixed forests that resemble natural forests. To evaluate the long-term effects of near-natural restoration on the WUI forest landscape, which are largely unclear, we used a wildfire in 2019 near Shenyang City in northeast China as an example and investigated the post-fire forest dynamics under two different scenarios (i.e., natural succession and near-natural restoration) based on the forest landscape model. The results demonstrated that near-natural restoration can significantly accelerate the restoration process in terms of forest biomass, species biodiversity, and age structure. Under the near-natural restoration scenario, the biomass of the burned area can be quickly restored within 20 years after the fire. At the species level, the biomass and proportion of pioneer tree species such as Pinus tabuliformis and Robinia pseudoacacia decreased under the near-natural restoration scenario, while other species started to increase. Then post-fire near-natural planting accelerated the restoration of forest biodiversity, by 2070, the Shannon–Wiener index was predicted to be 1.49 under natural succession and remained at 2.02 under near-natural restoration. In terms of age structure, near-natural restoration shortens the recovery time of fire trails to mature forests. In summary, near-natural restoration accelerates forest recovery in post-fire WUI areas. Our results highlighted the impact of near-natural restoration on forest conservation to inform post-fire forest planning and management practices. [ABSTRACT FROM AUTHOR]

Climate change and forest management practices influence forest productivity and carbon budgets, and understanding their interactions is necessary to develop accurate predictions of carbon dynamics as many countries in the world strive towards carbon neutrality. Here, we developed a model-coupling framework to simulate the carbon dynamics of boreal forests in China. The expected dynamics of forest recovery and change following intense timber harvesting in the recent past and projected carbon dynamics into the future under different climate change scenarios and forest management practices (e.g., restoration, afforestation, tending, and fuel management). We predict that under current management strategies, climate change would lead to increased fire frequency and intensity, eventually shifting these forests from carbon sinks towards being carbon sources. This study suggests that future boreal forest management should be altered to reduce the probability of fire occurrence and carbon losses caused by catastrophic fires through planting deciduous species, mechanical removal, and prescribed fire. [Display omitted] • The effects of forest management on carbon cycle of boreal forests were quantified. • Climate change would lead to increased fire frequency and intensity. • Future fire activity shifting boreal forests from carbon sinks to carbon sources. • Forest management should reduce carbon losses caused by catastrophic fires. [ABSTRACT FROM AUTHOR]

Megafires are large wildfires that occur under extreme weather conditions and produce mixed burn severities across diverse environmental gradients. Assessing megafire effects requires data covering large spatiotemporal extents, which are difficult to collect from field inventories. Remote sensing provides an alternative but is limited in revealing post-fire recovery trajectories and the underlying processes that drive the recovery. We 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. We derived pre-fire (1985) forest composition and the megafire perimeter and severity using remote sensing and inventory data. We simulated the megafire and the post-megafire forest recovery from 1985 to 2015 using the LANDIS model. We demonstrated that the framework was effective in reconstructing the post-fire stand dynamics and that it is applicable to other types of disturbances. • We presents a novel framework for spatially reconstructing the post-fire time-series of forest conditions. • The framework generates detailed stand attributes that can be validated against field inventory data. • The framework is highly scalable and can be applied to filling the gaps where inventory data are not available and to derive recovery trajectories across landscapes. • The framework is applicable to other types of disturbances such as harvest and windstorm. [ABSTRACT FROM AUTHOR]