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Forests and the dynamic changes play decisive roles in soil erosion prevention, biodiversity conservation and climate warming mitigation, and are crucial for China to achieve carbon neutrality because of the ability for carbon uptake. China's forests experienced a substantial change over the past century, primarily since the forest conservation and restoration programs were implemented. In this paper, the progress of China's forest change and the similarities and differences of the spatio-temporal patterns from multi-dimension coupling with ground surveys and satellite observations were reviewed comprehensively, and the drivers of forest change were discussed. Our review reported that: 1) China's forests experienced an extensive forest gain/restoration in vegetation greenness, forest cover, and aboveground biomass since the 1970s. 2) Changes in various forest parameters suggested distinctive spatiotemporal patterns in China. Consistent hotspots of forest gain clustered in the Loess Plateau and the southwestern China from most studies, while controversial conclusions about forest loss/degradation were found in the spatial distribution. 3) The geographic discrepancy of forest changes may be related to climate change, human activities, and forest disturbances. Variations in forest dynamics are prerequisites to exploring the effects of natural conditions and forestry policies on forest cover, and strengthening understanding of the carbon cycle. These findings can provide valuable insights for various ecological services in further studies and a scientific basis for forest management and policy-making in China. [ABSTRACT FROM AUTHOR]

To explore the potential effect of industrial transfer on carbon lock-in in China, this paper constructed the measurement formula of industrial transfer based on output and demand, and calculated carbon lock-in according to carbon sink and carbon emissions. By means of a spatial autoregressive model and a panel threshold model, we discussed the spatial spillover of carbon lock-in and the effect of industrial transfer. The findings are as follows: (1) The level of carbon lock-in does have a positive spatial spillover effect between economic neighboring provinces. (2) The effect of industrial transfer on carbon lock-in depends on industry characteristics. (3) Technological progress has direct and indirect carbon unlocking effects, energy structure, trade openness and increased fiscal expenditure exacerbate the carbon lock-in dilemma, while economic growth and carbon lock-in show an inverted "U" relationship. (4) There is a non-linear relationship between industrial transfer and carbon lock-in. Finally, we propose some recommendations to reduce dependence on high-carbon fossil energy and speed up the process of carbon unlocking in China. [ABSTRACT FROM AUTHOR]

With rapid economic growth and urbanization, self-sufficiency in crop production has become central to China's agriculture policy. Accurate crop production statistics are essential for research, monitoring, and planning. Although researchers agree that China's statistical authority has considerably modernized over time, China's economic statistics have still been viewed as unreliable and often overstated to meet growth targets at different administrative levels. Recent increases in crop production reported by national statistics have also come under increasing scrutiny. This paper investigates crop production data quality from a planetary boundary perspective--comparing net primary production (NPP) harvested obtained from national statistics with satellite-driven NPP estimates that are supported by detailed observation of land cover, combined with observations on physical factors that limit plant growth. This approach provides a powerful means to check the plausibility of China's grain production statistics at different administrative levels that can generate insights about their discrepancies and can contribute to improved crop production measurements. We find some evidence of potential misreporting problems from the lower administration level where the risk of manipulation of statistics is higher. We also find problems from provincial-level major grain producers. These values can also affect the national totals. Although the numbers are affected by large uncertainties, we find that improving the spatial resolution of key agricultural parameters can greatly improve the reliability of the indicator that in turn can help improve data quality. More reliable production data will be vital for relevant research and provide better insights into food security problems, the carbon cycle, and sustainable development. [ABSTRACT FROM AUTHOR]

This paper reports change in forest carbon stocks and their relationship to investment in forestry fixed assets in silviculture in China employing the forest stock volume conversion method for carbon stocks and annual sinks. The paper establishes carbon stock estimates, and then analyses recent carbon stock trends of main coniferous species based on the latest inventory of China’s forest resources. The inventory data cover the seven dominant coniferous species from 1989 to 2008. The paper shows that investment in forestry fixed assets in silviculture and forest carbon stocks of some species have a significant effect with a lag of 3–7 years; and there is discussion of various problems regarding forest carbon stocks and sinks. [ABSTRACT FROM PUBLISHER]

• We propose a new forest prediction model and use actual deforestation data for optimization and verification. • Use the XGBoost method to reconstruct deforestation intensity data. • Deforestation hotspots in China are mainly concentrated in the southern and southeastern regions. • Our model provides certain reference information for forest disaster prevention and forest management. Forests are important for the global carbon cycle, hydrothermal balance, and climate change. Human activities can exert a significant impact on forest ecosystems, thereby having the potential to alter their physical and chemical properties and thus affecting carbon, water, and heat budgets, and climate change. The historical reconstruction of the disturbance of global forests can help us understand the processes and patterns of human activities and global change. In this paper, we construct a deforestation prediction model using a Spearman correlation coefficient and implement the XGBoost method, using Python 3.6, for the reconstruction of deforestation intensity data from 2000 to 2019. Secondly, the selection of the driver indicators is done by using extreme difference regularization to unify the magnitude, and the potential deforestation area risk index is calculated in the form of equal weights. Finally, the actual deforestation data were used for optimization and validation. The model shows that the deforestation hotspots are mainly concentrated in the southern and southeastern regions of China and that there are large differences in deforestation in different provinces. In the future, the fine spatial and temporal patterns of deforestation in China during the historical period can be quantitatively reconstructed, which can provide some reference information for forest disaster prevention and forest management in China. [ABSTRACT FROM AUTHOR]

Abstract: Urban land development substantially alters the terrestrial carbon cycle, particularly the net primary productivity (NPP), from local to global scales. However, limited attempts have been undertaken to elucidate the differences in NPP between pre- and post-urban land development in China. In this paper, the terrestrial NPP after urbanization in China was assessed by using the Carnegie-Ames-Stanford approach (CASA), toward which a calibration was conducted for adapting this model on the fine-scale application. In addition, a method of neighborhood proxy was applied to acquire the NPP in the absence of urban land development, assuming that non-urban lands can represent their nearby urban lands before they were transformed. Our analyses indicate that urban land development had overall negative effects on terrestrial NPP. They reduced the NPP at an accelerating rate of 0.31×10−3 PgCyear−1, approximately 5.88% of the annual reduction during the period of 2000–2006 in China. Furthermore, these effects of NPP variations exhibited obvious differences in the amounts and spatial distributions. However, the NPP showed a slight increase around some regions that experienced rapid urbanization, as well as the arid regions in northwest China. These were probably caused by the effects of Urban Heat Island (UHI) and Urban Rain Island (URI), an introduction of faster growing exotics, various resource augmentations and so on. [Copyright &y& Elsevier]

Frequency and severity of droughts were projected to increase in many regions. However, their effects of temporal dynamics on the terrestrial carbon cycle remain uncertain, and hence deserve further investigation. In this paper, the droughts that occurred in China during 2001–2010 were identified by using the standardized precipitation index (SPI). Standardized anomaly index (SAI), which has been widely employed in reflecting precipitation, was extended to evaluate the anomalies of net primary productivity (NPP). In addition, influences of the droughts on vegetation were explored by examining the temporal dynamics of SAI–NPP along with area-weighted drought intensity at different time scales (1, 3, 6, 9 and 12 months). Year-to-year variability of NPP with several factors, including droughts, NDVI, radiation and temperature, was analyzed as well. Consequently, the droughts in the years 2001, 2006 and 2009 were well reconstructed. This indicates that SPI could be applied to the monitoring of the droughts in China during the past decade (2001–2010) effectively. Moreover, strongest correlations between droughts and NPP anomalies were found during or after the drought intensities reached their peak values. In addition, some droughts substantially reduced the countrywide NPP, whereas the others did not. These phenomena can be explained by the regional diversities of drought intensity, drought duration, areal extents of the droughts, as well as the cumulative and lag responses of vegetation to the precipitation deficits. Besides the drought conditions, normalized difference vegetation index (NDVI), radiation and temperature also contribute to the interannual variability of NPP. [Copyright &y& Elsevier]

Abstract: Understanding the sensitivity of soil respiration to temperature change and its impacting factors is an important base for accurately evaluating the response of terrestrial carbon balance to future climatic change, and thus has received much recent attention. In this study, we synthesized 161 field measurement data from 52 published papers to quantify temperature sensitivity of soil respiration in different Chinese ecosystems and its relationship with climate factors, such as temperature and precipitation. The results show that the observed Q 10 value (the factor by which respiration rates increase for a 10°C increase in temperature) is strongly dependent on the soil temperature measurement depth. Generally, Q 10 significantly increased with the depth (0cm, 5cm, and 10cm) of soil temperature measuring point. Different ecosystem types also exhibit different Q 10 values. In response to soil temperature at the depth of 5cm, alpine meadow and tundra has the largest Q 10 value with magnitude of 3.05±1.06, while the Q 10 value of evergreen broadleaf forests is approximately half that amount (Q 10 =1.81±0.43). Spatial correlation analysis also shows that the Q 10 value of forest ecosystems is significantly and negatively correlated with mean annual temperature (R =−0.51, P <0.001) and mean annual precipitation (R =−0.5, P <0.001). This result not only implies that the temperature sensitivity of soil respiration will decline under continued global warming, but also suggests that such acclimation of soil respiration to warming should be taken into account in forecasting future terrestrial carbon cycle and its feedback to climate system. [Copyright &y& Elsevier]

This paper reports the annual carbon (C) balance of China''s forests during 1901–2001 estimated using the Integrated Terrestrial Ecosystem C-budget model (InTEC). Annual carbon source and sink distributions are simulated for the same period using various spatial datasets including land cover and leaf area index (LAI) obtained from remote sensing, soil texture, climate, forest age, and nitrogen deposition. During 1901–1949, China''s forests were a source of 21.0±7.8TgCyr−1 due to disturbances (human activities). Its size increased to 122.3±25.3TgCyr−1 during 1950–1987 due to intensified human activities in the late 1950s, early 1960s, 1970s and early 1980s. The forests became large sinks of 176.7±44.8TgCyr−1 during 1988–2001, owing to large-scale plantation and forest regrowth in previously disturbed areas as well as growth stimulation by nondisturbance factors such as climatic warming, atmospheric CO2 fertilization, and N deposition. From 1901 to 2001, China''s forests were a small carbon source of 3.32PgC, about 32.9±22.3TgCyr−1. The overall C balance in biomass from InTEC generally agrees with previous results derived from forest inventories of China''s forests. InTEC results also include C stock variation in soils and are therefore more comprehensive than previous results. The uncertainty in InTEC results is still large, but it can be reduced if a detailed forest age map becomes available. [Copyright &y& Elsevier]

Coastal wetlands play an increasingly important role in regulating greenhouse gas (GHG) fluxes and thus affecting climate change. However, the overall magnitude, trend, and environmental drivers of GHG fluxes in these wetlands of China remain uncertain. Herein, we synthesized data from 70 publications involving 187 field observations to identify patterns and drivers of GHG fluxes across coastal wetlands in China. Average methane (CH 4), nitrous oxide (N 2 O) fluxes, and carbon dioxide (CO 2) emissions (ecosystem respiration) across coastal wetlands were estimated as 2.20±0.31 mg·m-2·h-1, 16.44±2.96 μg·m-2·h-1, and 388.76±42.28 mg·m-2·h-1, respectively. GHG emissions varied with tidal inundation, where CH 4 and CO 2 emissions during tidal inundation were lower than during ebbing. CH 4 and CO 2 emissions from wetlands decreased linearly with increasing latitude, while N 2 O did not. CH 4 fluxes were positively related to air temperature and aboveground biomass, and CO 2 emissions were positively related to soil organic carbon. N 2 O fluxes were lower with increasing soil pH, and CH 4 and CO 2 emissions were greater with increasing soil moisture. Based on the results of sustained-flux global warming potential and sustained-flux global cooling potential models, our paper indicate that the fluxes of CH 4 and N 2 O in coastal wetlands have a positive feedback to global warming, which is mainly driven by the CH 4 emission. Our synthesis improved understanding of the roles of coastal wetlands in the ecosystem C cycle under global change. We suggest that long-term field observations of GHG fluxes across a wider range of spatiotemporal scales are urgently required to improve the prediction accuracy in GHG fluxes and the assessment of net GHG balance and its contribution to the GWP of coastal wetlands. [ABSTRACT FROM AUTHOR]

Climate change has emerged as one of the most important environmental issues worldwide. As the world's biggest developing country, China is participating in combating climate change by promoting a low carbon economy within the context of global warming. This paper summarizes the pathways of China's low carbon economy including the aspects of energy, industry, low carbon cities, circular economy and low carbon technology, afforestation and carbon sink, the carbon emission trading market and carbon emission reduction targets. There are many achievements in the implementation of low carbon policies. For example, carbon emission intensity has been reduced drastically along with the optimizing of energy and industry structure and a nationwide carbon trading market for electricity industry has been established. However, some problems remain, such as the weakness of public participation, the ineffectiveness of unified policies for certain regions and the absence of long-term planning for low carbon cities development. Therefore, we propose some policy recommendations for the future low carbon economy development in China. Firstly, comprehensive and long-term planning should be involved in all the low carbon economy pathways. Secondly, to coordinate the relationship between central and local governments and narrow the gap between poor and rich regions, different strategies of carbon emission performance assessment should be applied for different regions. Thirdly, enterprises should cooperate with scientific research institutions to explored low carbon technologies. Finally, relevant institutions should be regulated to realize comprehensive low carbon transition through reasonable and feasible low carbon pathways in China. These policy recommendations will provide new perspectives for China's future low carbon economy development and guide practices for combating climate change. [ABSTRACT FROM AUTHOR]