Thermogravimetric analysis of the pyrolysis and combustion kinetics of surface dead combustibles in the Daxing’an Mountains

In boreal regions, the frequency of forest fires is increasing. In this study, thermogravimetric analysis was used to analyze the pyrolysis kinetics of dead surface combustibles in different forest types within the Daxing’an Mountains, China. The results show that the combustible material load of forest types, the Larix forest (LG) is relatively high. Base on the E of kinetic parameters, the LG, and Quercus forest (QM) forest types had relatively high combustibility values and comprehensive combustibility values for 1-, 10-, and 100-h time lags. According to the obtained P values, the pyrolysis of dead surface fuels with 1-, 10-, and 100-h time lags is relatively difficult in the Larix / Betula mixed forest (L-B) and QM forest types. Therefore, mixed forests of the LG, L-B, and QM tree species can be established as fire-resistant forests to establish a fire barrier, reduce the combustibility of forest stands, and reduce the possibility of forest fires.

Stand Volume Growth Modeling with Mixed-Effects Models and Quantile Regressions for Major Forest Types in the Eastern Daxing’an Mountains, Northeast China

The relative growth rate (RGRnv) is the standardized measurement of forest growth, whereby excluding the size differences between individuals allows their performance to be compared equally. The RGRnv model was developed using the National Forest Inventory (NFI) data on the Daxing’an Mountains, in Northeast China, which contain Dahurian larch (Larix gmelinii Rupr.), white birch (Betula platyphylla Suk.), and mixed coniferous–broadleaf forests. Four predictor variables—i.e., quadratic mean diameter (Dq), stand basal area (G), average tree height (Ha), and altitude (A)—and four different methods—i.e., the nonlinear mixed-effects models (NLME), three nonlinear quantile regression (NQR3), five nonlinear quantile regression (NQR5), and nine nonlinear quantile regression (NQR9) models—were used in this study. All the models were validated using the leave-one-out method. The results showed that (1) the mixed coniferous–broadleaf forest presented the highest RGRnv; (2) the RGRnv was negatively correlated with the four predictors, and the heteroscedasticity reduced significantly after the weighting function was integrated into the models; and (3) the quantile regression models performed better than NLME, and NQR9 outperformed both NQR3 and NQR5. To make more accurate predictions, parameters of the adjusted mixed-effects and quantile regression models should be recalculated and localized using sampled RGRnv in each region and then applied to predict all the other RGRnv of plots. MAPE% indicates the mean absolute percentage error. The values were stable when the sample numbers were greater than or equal to six across the three forest types, which showed relatively accurate and lowest-cost prediction results.

Seasonal variations in temperature sensitivity of soil respiration in a larch forest in the Northern Daxing’an Mountains in Northeast China

Temperature sensitivity of respiration of forest soils is important for its responses to climate warming and for the accurate assessment of soil carbon budget. The sensitivity of temperature (Ti) to soil respiration rate (Rs), and Q10 defined by e10(lnRs−lna)/Ti has been used extensively for indicating the sensitivity of soil respiration. The soil respiration under a larch (Larix gmelinii) forest in the northern Daxing’an Mountains, Northeast China was observed in situ from April to September, 2019 using the dynamic chamber method. Air temperatures (Tair), soil surface temperatures (T0cm), soil temperatures at depths of 5 and 10 cm (T5cm and T10cm, respectively), and soil-surface water vapor concentrations were monitored at the same time. The results show a significant monthly variability in soil respiration rate in the growing season (April–September). The Q10 at the surface and at depths of 5 and 10 cm was estimated at 5.6, 6.3, and 7.2, respectively. The Q10@10 cm over the period of surface soil thawing (Q10@10 cm, thaw = 36.89) were significantly higher than that of the growing season (Q10@10 cm, growth = 3.82). Furthermore, the Rs in the early stage of near-surface soil thawing and in the middle of the growing season is more sensitive to changes in soil temperatures. Soil temperature is thus the dominant factor for season variations in soil respiration, but rainfall is the main controller for short-term fluctuations in respiration. Thus, the higher sensitivity of soil respiration to temperature (Q10) is found in the middle part of the growing season. The monthly and seasonal Q10 values better reflect the responsiveness of soil respiration to changes in hydrometeorology and ground freeze-thaw processes. This study may help assess the stability of the soil carbon pool and strength of carbon fluxes in the larch forested permafrost regions in the northern Daxing’an Mountains.

Effects of drought stress on soil bacteriall community in the West foot of Daxing’an Mountains

Global warming poses a serious threat to agriculture and natural systems, in part because of the change of soil moisture content, which changes soil microbial communities and ecological processes. Soil water content is the main factor limiting the growth of plants in soil. Microbial communities rely on soil water to complete their activities, and reveal the changes of underground microbial communities under different soil moisture content, which will help us to further understand the potential impact of climate change on soil ecosystem. To investigate the soil bacterial community structure, we established experiment indoor in the West foot of Daxing’an Mountains with manipulative water content treatments consisting of 20%, 15%, 10%, 5%, 0%. Results showed that bacterial community composition varied significantly with altered drought stress , but community richness did not. The relative abundance of Actinobacteria increased with the increase of drought stress, Proteobacteria, Acidobacteria and Gemmatimonadota decreased with the increase of drought stress, actinobacteria was more likely to accumulate or maintain stable under drought stress, bacterial communities can responding directly to changes in soil moisture.

Tree-ring reconstruction of June-July mean temperatures in the northern Daxing’an Mountains, China

In this study, the mean temperature of June to July was reconstructed for the period of 1880 to 2014 by using the Larix gmelinii tree-ring width data for the Mangui region in the northern Daxing’an Mountains, China. The reconstruction accounts for 43.6% of the variance in the temperature observed from AD 1959–2014. During the last 134 years, there were 17 warm years and 17 cold years, which accounted for 12.7% of the total reconstruction years, respectively. Cold episodes occurred throughout 1887–1898 (average value is 14.2°C), while warm episodes occurred during 1994–2014 (15.9°C). Based on this regional study, the warmer events coincided with dry periods and the colder events were consistent with wet conditions. The spatial correlation analyses between the reconstructed series and gridded temperature data revealed that the regional climatic variations were well captured by this study and the reconstruction represented a regional temperature signal for the northern Daxing’an Mountains. In addition, Multi-taper method spectral analysis revealed the existence of significant periodicities in our reconstruction. Significant spectral peaks were found at 29.7, 10.9, 2.5, and 2.2 years. The significant spatial correlations between our temperature reconstruction and the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Solar activity suggested that the temperature in the Daxing’an Mountains area indicated both local-regional climate signals and global-scale climate changes.