In the context of global warming, forest fires are expected to occur more frequently and intensively, and impose more significant impacts on human society, terrestrial ecosystems, and atmosphere. Most of the existing methods in monitoring large-scale forest fire are based either on satellite visible and infrared observations or weather-based indices. This work explored the advantages of a new satellite microwave-based vegetation index in monitoring forest fire occurrence and fire intensity in Northeastern Asia and Southern China. Specifically, we used satellite observations during 2002–2011 to investigate the correlation at different temporal scales between forest fire properties (fire count, FC; fire radiative power, FRP) and the vegetation water content proxy of the Microwave Emissivity Difference Vegetation Index (EDVI) derived from the Moderate Resolution Imaging Spectroradiometer and the Advanced Microwave Scanning Radiometer-EOS on Aqua satellite. The correlations were compared to that with three weather-based indices including the Fine Fuel Moisture Code, Initial Spread Index and Fire Weather Index (FWI) to determine whether EDVI provides new independent information of forest fires. Finally, EDVI and the weather-based indices FWI were combined to establish multivariate linear regression models to estimate FC and FRP. Results show that: 1) the temporal variations of FC and total FRP are negatively correlated with EDVI using the daily and monthly observations at 1° grid and regional scales; and overall opposite annual cycles and interannual variations between FC (and total FRP) and EDVI are observed in Northeastern Asia and Southern China; 2) compared to the weather-based indices, EDVI shows higher correlation with the temperate forest fire properties in Southern China while shows weaker correlation with the forest fire properties in Northeastern Asia; and a combination of the two kind of indices is found to improve the explained variance for fire properties in both regions; 3) multivariate linear regression models based on EDVI and FWI provide better estimation of FC and FRP compared to the linear regression models based on FWI alone. To our knowledge, this is the first work that comprehensively investigates the potential application of the microwave-based vegetation water content index in forest fire count and fire intensity.

The boreal forest represents the terrestrial biome most heavily affected by climate change. However, no consensus exists regarding the impacts of these changes on the growth of tree species therein. Moreover, assessments of young tree responses in metrics transposable to forest management remain scarce. Here, we assessed the impacts of climate change on black spruce (Picea mariana [Miller] BSP) and jack pine (Pinus banksiana Lambert) growth, two dominant tree species in boreal forests of North America. Starting with a retrospective analysis including data from 2591 black spruces and 890 jack pines, we forecasted trends in 30-year height growth at the transitions from closed to open boreal coniferous forests in Québec, Canada. We considered three variables: (1) height growth, rarely used, but better-reflecting site potential than other growth proxies, (2) climate normals corresponding to the growth period of each stem, and (3) site type (as a function of texture, stoniness, and drainage), which can modify the effects of climate on tree growth. We found a positive effect of vapor pressure deficit on the growth of both species, although the effect on black spruce leveled off. For black spruce, temperatures had a positive effect on the height at 30 years, which was attenuated when and where climatic conditions became drier. Conversely, drought had a positive effect on height under cold conditions and a negative effect under warm conditions. Spruce growth was also better on mesic than on rocky and sub-hydric sites. For portions of the study areas with projected future climate within the calibration range, median height-change varied from 10 to 31% for black spruce and from 5 to 31% for jack pine, depending on the period and climate scenario. As projected increases are relatively small, they may not be sufficient to compensate for potential increases in future disturbances like forest fires.

We investigated whether stand species mixture can attenuate the vulnerability of eastern Canada’s boreal forests to climate change and insect epidemics. For this, we focused on two dominant boreal species, black spruce [Picea mariana (Mill.) BSP] and trembling aspen (Populus tremuloides Michx.), in stands dominated by black spruce or trembling aspen (“pure stands”), and mixed stands (M) composed of both species within a 36 km2 study area in the Nord-du-Québec region. For each species in each stand composition type, we tested climate-growth relations and assessed the impacts on growth by recorded insect epidemics of a black spruce defoliator, the spruce budworm (SBW) [Choristoneura fumiferana (Clem.)], and a trembling aspen defoliator, the forest tent caterpillar (FTC; Malacosoma disstria Hübn.). We implemented linear models in a Bayesian framework to explain baseline and long-term trends in tree growth for each species according to stand composition type and to differentiate the influences of climate and insect epidemics on tree growth. Overall, we found climate vulnerability was lower for black spruce in mixed stands than in pure stands, while trembling aspen was less sensitive to climate than spruce, and aspen did not present differences in responses based on stand mixture. We did not find any reduction of vulnerability for mixed stands to insect epidemics in the host species, but the non-host species in mixed stands could respond positively to epidemics affecting the host species, thus contributing to stabilize ecosystem-scale growth over time. Our findings partially support boreal forest management strategies including stand species mixture to foster forests that are resilient to climate change and insect epidemics.