• Energy Research

AbstractForests store a large part of the terrestrial vegetation carbon (C) and have high C sequestration potential. Here, we developed a new forest C sequestration (FCS) model based on the secondary succession theory, to estimate vegetation C sequestration capacity in China's forest vegetation. The model used the field measurement data of 3161 forest plots and three future climate scenarios. The results showed that logistic equations provided a good fit for vegetation biomass with forest age in natural and planted forests. The FCS model has been verified with forest biomass data, and model uncertainty is discussed. The increment of vegetation C storage in China's forest vegetation from 2010 to 2050 was estimated as 13.92 Pg C, while the average vegetation C sequestration rate was 0.34 Pg C yr−1 with a 95% confidence interval of 0.28–0.42 Pg C yr−1, which differed significantly between forest types. The largest contributor to the increment was deciduous broadleaf forest (37.8%), while the smallest was deciduous needleleaf forest (2.7%). The vegetation C sequestration rate might reach its maximum around 2020, although vegetation C storage increases continually. It is estimated that vegetation C sequestration might offset 6–8% of China's future emissions. Furthermore, there was a significant negative relationship between vegetation C sequestration rate and C emission rate in different provinces of China, suggesting that developed provinces might need to compensate for undeveloped provinces through C trade. Our findings will provide valuable guidelines to policymakers for designing afforestation strategies and forest C trade in China.

AbstractRewetting after precipitation events plays an important role in regulating soil carbon (C) and nitrogen (N) turnover processes in arid and semiarid ecosystems. Here, we conducted a 48-h rewetting simulation experiment with measurements of soil C and N mineralization rates (RC and RN, respectively) and microbial biomass N (MBN) at high temporal resolution to explore the pulse responses of R C and RN. RC and RN responded strongly and rapidly to rewetting over the short term. The maximum RC value (because of pulse effects) ranged from 16.53 to 19.33 µg C gsoil−1 h−1, observed 10 min after rewetting. The maximum RN varied from 22.86 to 40.87 µg N gsoil−1 h−1, appearing 5–6 h after rewetting. The responses of soil microbial growth to rewetting were rapid, and the maximum MBN was observed 2–3 h after rewetting. Unexpectedly, there was no correlation between RC, RN, and MBN during the process of rewetting, and RC and RN were uncoupled. In sum, the pulse responses of RC, RN, and microbial growth to simulated rewetting were rapid, strong, and asynchronous, which offers insights into the different responses of microbes to rewetting and mechanisms behind microbes.

AbstractHow to assess the temperature sensitivity (Q10) of soil organic matter (SOM) decomposition and its regional variation with high accuracy is one of the largest uncertainties in determining the intensity and direction of the global carbon (C) cycle in response to climate change. In this study, we collected a series of soils from 22 forest sites and 30 grassland sites across China to explore regional variation inQ10and its underlying mechanisms. We conducted a novel incubation experiment with periodically changing temperature (5–30 °C), while continuously measuring soil microbial respiration rates. The results showed thatQ10varied significantly across different ecosystems, ranging from 1.16 to 3.19 (mean 1.63).Q10was ordered as follows: alpine grasslands (2.01) > temperate grasslands (1.81) > tropical forests (1.59) > temperate forests (1.55) > subtropical forests (1.52). TheQ10of grasslands (1.90) was significantly higher than that of forests (1.54). Furthermore,Q10significantly increased with increasing altitude and decreased with increasing longitude. Environmental variables and substrate properties together explained 52% of total variation inQ10across all sites. Overall,pHand soil electrical conductivity primarily explained spatial variation inQ10. The general negative relationships betweenQ10and substrate quality among all ecosystem types supported the C quality temperature (CQT) hypothesis at a large scale, which indicated that soils with low quality should have higher temperature sensitivity. Furthermore, alpine grasslands, which had the highestQ10, were predicted to be more sensitive to climate change under the scenario of global warming.

Increasing atmospheric nitrogen deposition can influence food production, environmental quality and climate change from the regional to global scales. As the largest developing country, China is expected to experience a rapid increase in N deposition. However, the lack of information on dry N deposition limits our understanding of the historical trend of the total N deposition, as well as the main drivers of this trend. Here, we use extensive datasets that include both wet and dry N deposition to evaluate the spatiotemporal variation of N deposition and the changes of its components in China during 1980–2015. Three significant transitions in N deposition in China were observed. First, the total N deposition began to stabilize in 2001–2005, mostly due to a decline in wet NH4+ deposition. Subsequently, a shift to approximately equal wet and dry N deposition occurred in 2011–2015, accompanied by increasing dry deposition. Finally, the contribution of reduced N components in the deposition decreased due to increasing NO3− deposition. These transitions were jointly driven by changes in the socioeconomic structure in China and vigorous controls in N pollution. The three observed important transitions challenge the traditional views about the continuous increase in N deposition in China. Nitrogen deposition in China has been almost constant over the past decade, as decreasing wet deposition has balanced increasing dry deposition, according to analyses of extensive datasets on wet and dry nitrogen depositions in China.