Modeling the carbon dynamics of ecosystem in a typical permafrost area.

Climate change poses mounting threats to fragile alpine ecosystem worldwide. Quantifying changes in carbon stocks in response to the shifting climate was important for developing climate change mitigation and adaptation strategies. This study utilized a process-based land model (Community Land Model 5.0) to analyze spatiotemporal variations in vegetation carbon stock (VCS) and soil organic carbon stock (SOCS) across a typical permafrost area - Qinghai Province, China, from 2000 to 2018. Multiple potential factors influencing carbon stocks dynamics were analyzed, including climate, vegetation, soil hydrothermal status, and soil properties. The results indicated that provincial vegetation carbon storage was 0.22 PgC (0.32 kg/m2) and soil organic carbon pool was 9.12 PgC (13.03 kg/m2). VCS showed a mild increase while SOCS exhibited fluctuating uptrends during this period. Higher carbon stocks were observed in forest (21.74 kg/m2) and alpine meadow (18.08 kg/m2) compared to alpine steppes (9.63 kg/m2). Over 90 % of the carbon was stored in the 0-30 cm topsoil layer. The contribution rates of soil carbon in the 30-60 cm and 60-100 cm soil layers were significantly small, despite increasing stocks across all depths. Solar radiation, temperature, and NDVI emerged as primary influential factors for overall carbon stocks, exhibiting noticeable spatial variability. For SOCS at different depths, the normalized differential vegetation index (NDVI) was the foremost predictor of landscape-level carbon distributions, which explained 52.8 % of SOCS variability in shallow layers (0-30 cm) but dropped to just 12.97 % at the depth of 30-60 cm. However, the dominance of NDVI diminished along the soil depth gradients, superseded by radiation and precipitation. Additionally, with an increase in soil depth, the influence of inherent soil properties also increased. This simulation provided crucial insights for landscape-scale carbon responses to climate change, and offered valuable reference for other climate change-sensitive areas in terms of ecosystem carbon management.

Recent Jishishan earthquake ripple hazard provides a new explanation for the destruction of the prehistoric Lajia Settlement 4000a B.P.

The Jishishan Ms 6.2 earthquake occurred at 23:59 on December 18, 2023 in Gansu Province, China. We conducted a field survey to assess the hazards and damages caused by the earthquake and its associated geo-activities. Subsequently, we organized a seminar to discuss the possible causes of the destruction of a prehistoric site-Lajia Settlement-dated back to four thousand years B.P. and located only several kilometers away from the epicenter of the Jishishan earthquake. The Jishishan earthquake was unique for its hazard and disaster process, which featured ground shaking and a series of complex geological and geomorphological activities: sediment and soil spray piles, liquefaction, collapse, landslide, and mudflow along water channels. We define this phenomenon as the Jishishan earthquake ripple hazard (JERH). The most recent evidence from the JERH suggests that a prehistoric earthquake similar to the JERH, instead of riverine floods or earthquake-induced landslide dam outburst flood, as previously hypothesized, destroyed the Lajia Settlement.

Grid-less wideband direction of arrival estimation based on variational Bayesian inference.

Many recent works have addressed the problem of wideband direction of arrival (DOA) estimation using grid-less sparse techniques, and these methods have been shown to outperform the traditional wideband DOA estimation methods. However, these methods often suffer from the problem of requiring manual parameter tuning or high computational complexity, which reduces their practicality. To alleviate this problem, a grid-less wideband DOA estimation method based on variational Bayesian inference is proposed in this paper. The method approximates the posterior probability density function of DOA with the help of variational Bayesian inference, which does not require manual adjustment of parameters and can obtain accurate DOA estimation results with low computational complexity. Numerical simulations and real measurement data processing show that the proposed method has a higher DOA estimation accuracy than other grid-less wideband methods while providing higher computational speed.

Exploring the impacts of ecosystem services on human well-being in Qinghai Province under the framework of the sustainable development goals.

Ecosystem services (ESs) play vital roles in meeting the needs of human well-being and supporting sustainable development. However, there is limited research on how the types, amounts, interactions, and changes of the ESs collectively impact human well-being under the context of sustainable development goals (SDGs) of the United Nations. This study selected Qinghai Province of China as the study area and intended to make such an attempt to fill this gap in terms of the following aspects: (1) analyzing the spatial patterns and changing trends of ten ESs (food supply, water supply, carbon sink, soil retention, sand fixation, hydrological regulation, flood mitigation，cultural service，net primary productivity, and habitat quality) in Qinghai Province from 2000 to 2018; (2)constructing a multi-level index system of human well-being under the framework of the SDGs, and setting the criteria to assess the level of local human well-being; and (3) building a structural equation model to explore the direct and indirect impacts of the types, amounts, interactions and changes of the ESs on actual human well-being and the gaps between actual and targeted human well-being. The findings revealed that: (1) most of the ecosystem services fluctuated with significant downward or upward trends during 2000-2018, except for four ESs (i.e., carbon sink, soil retention, flood mitigation, and habitat quality); (2) only a few indicators of local residents' well-being such as meat production, milk production, the numbers of medical technical personnel in hospitals and health centers, and the numbers of scientific and technical personnel met the SDG criteria in most time, while other indicators remained at low levels and there were large gaps between them and the SDG criteria; (3) actual human well-being and the gaps between actual and targeted human well-being were affected by the types, amounts, interactions and changes of the ESs with different degrees directly or indirectly. The approaches and results in this study are instructive for other regions of the world to make certain the roles of ESs in promoting human well-being and substantiating the SDGs.

Assessing coupling interactions in a safe and just operating space for regional sustainability.

Human activities affect the Earth System with an unprecedented magnitude, causing undesirable irreversible degradation. The United Nation's Sustainable Development Goals (SDGs) provide an integrated global action plan for sustainable development. However, it remains a great challenge to develop actionable strategies to achieve regional sustainability within social-environmental constraints. Here we proposed a framework, integrating safe and just operating space (SJOS) with SDGs, to assess regional sustainability and interactions between environmental performance and human well-being across scales. Despite China has not fully achieved sustainable development from 2000 to 2018, most provinces have shown significant improvements. Our analyses further delineated four development patterns (i.e., coupled and developed, coupled and underdeveloped, uncoupled and underdeveloped, and coupled and underdeveloped), and developed targeted strategies and pathways for each pattern to transition towards sustainability. Our operationalizable framework is broadly applicable to other regions or nations to actualize sustainable development.

Influential paths of ecosystem services on human well-being in the context of the sustainable development goals.

Ecosystem services (ESs) and their demands from people are closely related to human well-being (HWB). Understanding of the influential paths of ecosystem services on human well-being is significant to sustainable landscape management. This study explored the supply of ecosystem services and the ecosystem service supply-demand relationships (i.e. the ecological supply-demand ratio, ESDR) in the Central and Western Inner Mongolia, as well as HWB by combining the Millennium Ecosystem Assessment (MA) and the sustainable development goals of the United Nations (SDGs). A structural equation model (SEM) was built to quantify the influential paths of the ESs on the HWB. The results indicated that: (1) The HWB was improved during 2000-2018. (2) The supporting services promoted the provisioning services and the regulating services directly. (3) The provisioning services and the regulating services had positive direct influences on the HWB, and also affected the HWB through the ESDR indirectly. The combination of the supporting services and the ESDR presented a panorama of the influential paths of ecosystem services on the HWB and promoted the understanding of the driving mechanisms. Assessments on the ESs, the HWB in the context of SDGs, and their influential paths were instructive for decision-making towards sustainable landscape management.

Factors contributing to spatial-temporal variations of observed oxygen concentration over the Qinghai-Tibetan Plateau.

Oxygen (O2) is the most abundant molecule in the atmosphere after nitrogen. Previous studies have documented that oxygen concentration remains nearly constant (20.946%) at all altitudes. Here we show for the first time that oxygen concentration varies significantly from earlier consensus and shows strong spatial and seasonal differences. Field observations on the Qinghai-Tibetan Plateau (QTP) indicate oxygen concentration of 19.94-20.66% (2018, n = 80), 19.98-20.78% (2019, n = 166) and 19.97-20.73% (2020, n = 176), all statistically different from earlier reports (p < 0.001) and are lower than the nearly constant. The mean oxygen concentration in summer (20.47%) is 0.31% higher than that of winter (20.16%) (n = 53) at identical locations in 2019, sampled in the Qilian Mountains, northwest QTP. We used LMG (The Lindeman, Merenda and Gold) method to estimate the relative contributions of altitude, air temperature and vegetation index (Fractional Vegetation Cover, FVC and Leaf Area Index, LAI) to oxygen concentration, which are 47%, 32% and 3% (FVC, R2 = 82%); 45%, 30% and 7% (LAI, R2 = 82%), respectively. These findings provide a new perspective for in-depth understanding on population risk in high altitude regions in the context of global climate change, to ensure the health and safety of residents and tourists in high altitude regions and promoting the stability, prosperity and sustainable development of high-altitude regions worldwide.

Impacts of meteorological factors and land use pattern on hydrological elements in a semi-arid basin.

The allocation of water resources to meet both human wellbeing and environmental requirements is a critical challenge in a semi-arid landscape. Hydrological models are widely used to understand the influence mechanism of hydrological elements, which is helpful for optimizing water resources management. However, the spatial heterogeneity of hydrological dynamics has been largely omitted in prior studies, partly because it's difficult to correctly simulate the spatial distributions of hydrological elements due to roughly representing the surface biophysical parameters in the hydrological model. In this study, the Distributed Hydrological Soil Vegetation Model (DHSVM) was incorporated with the high-resolution remotely sensed leaf area index (LAI) data in a semiarid basin, located in the upstream of the Xar Moron River Basin, to explore the impacts of meteorological factors (i.e., air temperature, wind speed, relative humidity, shortwave radiation, and precipitation) and LAI on hydrological processes of forests, grasslands, and farmlands. Our results show that the spatial distribution of LAI slightly improves the accuracy of streamflow simulations and significantly promotes the model performance of spatial hydrological element simulations. For the area in study, precipitation, LAI, and relative humidity are the three major influential factors in the forest hydrological dynamics. The hydrological elements of grasslands and farmlands are mainly affected by shortwave radiation, relative humidity, air temperature, and LAI. Compared with grasslands and farmlands, LAI has greater negative influence on forest water availability. To mitigate the negative effects of drying and warming climate and promote ecosystems sustainability, the forest area should be converted into grassland while the native grassland should be maintained for soil water conservation.

China's response to a national land-system sustainability emergency.

China has responded to a national land-system sustainability emergency via an integrated portfolio of large-scale programmes. Here we review 16 sustainability programmes, which invested US$378.5 billion (in 2015 US$), covered 623.9 million hectares of land and involved over 500 million people, mostly since 1998. We find overwhelmingly that the interventions improved the sustainability of China's rural land systems, but the impacts are nuanced and adverse outcomes have occurred. We identify some key characteristics of programme success, potential risks to their durability, and future research needs. We suggest directions for China and other nations as they progress towards the Sustainable Development Goals of the United Nations' Agenda 2030.

Intensive land-use drives regional-scale homogenization of plant communities.

Intensive anthropogenic land-use causes habitat loss and landscape homogenization, which leads to the decrease of biodiversity and ecosystem degradation. Therefore, it is important to study the influence of landscape heterogeneity on biodiversity. In this study, vegetation surveys conducted at 53 sites in the Tabu River basin, located at the agro-pastoral ecotone of Inner Mongolia of China, revealed 146 species. Species diversity was evaluated at three scales: species richness within patches (alpha diversity), between patches (beta diversity) and at the landscape scale (gamma diversity). We analyzed landscape heterogeneity (LHtotal) and its driving factors including environmental variables (LHDFenv-var, such as precipitation and altitude), environmental heterogeneity (LHDFenv-het) and human activities (LHDFhum). We used structural equation modeling (SEM) to evaluate the response of species richness to landscape heterogeneity at three scales and determined the relative contribution of driving factors in explaining species diversity at these scales. The results of the study are summarized as follows: 1) Alpha diversity was the dominant component of gamma diversity in the Tabu River basin in Inner Mongolia. 2) There is no significant correlation (P = 0.512) between alpha diversity and LHtotal; with the increase of LHtotal beta and gamma diversities showed hump-shaped relationships. 3) LHDFenv-het was the primary factor in maintaining alpha diversity, with heterogeneity of mean annual precipitation (MAP), temperature (MAT) and altitude (ALT) acting as three largest contributors. LHDFhum primarily contributed to the maintenance of beta diversity. 4) LHDFhum was the primary contributor to gamma diversity, and human activity exceeded threshold values for positive effects. Based on our findings we suggest liming agricultural use along the river to prevent reductions in species diversity.

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China.

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM2.5 and PM10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM2.5 accumulation; low wind speed and high relative humidity constrained PM10 accumulation; and short sunshine duration and high wind speed constrained O3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

The relationship between urban form and air pollution depends on seasonality and city size.

Understanding how urban form is related to air pollution is important to urban planning and sustainability, but the urban form-air pollution relationship is currently muddled by inconsistent findings. In this study, we investigated how the compositional and configurational attributes of urban form were related to different air pollution measures (PM2.5, API, and exceedance) in 83 Chinese cities, with explicit consideration of city size and seasonality. Ten landscape metrics were selected to quantify urban form attributes, and Spearman's correlation was used to quantify the urban form-air pollution relationship. Our results show that the urban form and air pollution relationship was dominated by city size and moderated by seasonality. Specifically, urban air pollution levels increased consistently and substantially from small to medium, large, and megacities. The urban form-air pollution relationship depended greatly on seasonality and monsoons. That is, the relationship was more pronounced in spring and summer than fall and winter, as well as in cities affected by monsoons. Urban air pollution was correlated more strongly with landscape composition metrics than landscape configuration metrics which seemed to affect only PM2.5 concentrations. Our study suggests that, to understand how air pollution levels are related to urban form, city size and seasonality must be explicitly considered (or controlled). Also, in order to mitigate urban air pollution problems, regional urban planning is needed to curb the spatial extent of built-up areas, reduce the degree of urban fragmentation, and increase urban compactness and contiguity, especially for large and megacities.

Substantial impacts of landscape changes on summer climate with major regional differences: The case of China.

China's rapid socioeconomic development during the past few decades has resulted in large-scale landscape changes across the country. However, the impacts of these land surface modifications on climate are yet to be adequately understood. Using a coupled process-based land-atmospheric model, therefore, we quantified the climatic effects of land cover and land management changes over mainland China from 2001 to 2010, via incorporation of real-time and high-quality satellite-derived landscape representation (i.e., vegetation fraction, leaf area index, and albedo) into numerical modeling. Our results show that differences in landscape patterns due to changes in land cover and land management have exerted a strong influence on summer climate in China. During 2001 and 2010, extensive cooling of up to 1.5°C was found in the Loess Plateau and 1.0°C in northeastern China. In contrast, regional-scale warming was detected in the Tibetan Plateau (0.3°C), Yunnan province (0.4°C), and rapidly expanding urban centers across China (as high as 2°C). Summer precipitation decreased in the northeastern region, with patchy reduction generally <1.8mm/day, but increased in the Loess Plateau, with local spikes up to 2.4mm/day. Our study highlights that human alterations of landscapes have had substantial impacts on summer climate over the entire mainland China, but these impacts varied greatly on the regional scale, including changes in opposite directions. Therefore, effective national-level policies and regional land management strategies for climate change mitigation and adaptation should take explicit account of the spatial heterogeneity of landscape-climate interactions.

How do climatic and management factors affect agricultural ecosystem services? A case study in the agro-pastoral transitional zone of northern China.

Agricultural ecosystem management needs to ensure food production and minimize soil erosion and nitrogen (N) leaching under climate change and increasingly intensive human activity. Thus, the mechanisms through which climatic and management factors affect crop production, soil erosion, and N leaching must be understood in order to ensure food security and sustainable agricultural development. In this study, we adopted the GIS-based Environmental Policy Integrated Climate (EPIC) model to simulate crop production, soil erosion, and N leaching, and used a partial least squares regression model to evaluate the contributions of climate variables (solar radiation, precipitation, wind speed, relative humidity, and maximum and minimum temperature) and management factors (irrigation, fertilization, and crop cultivation area) on agricultural ecosystem services (AES) in the agro-pastoral transitional zone (APTZ) of northern China. The results indicated that crop production and N leaching markedly increased, whereas soil erosion declined from 1980 to 2010 in the APTZ. Management factors had larger effects on the AES than climate change. Among the climatic variables, daily minimum temperature was the most important contributor to the variations in ecosystem services of wheat, maize, and rice. Spatial changes in the cultivated area most affected crop production, soil erosion, and N leaching for majority of the cultivated areas of the three crops, except for the wheat-cultivated area, where the dominant factor for N leaching was fertilization. Although a tradeoff existed between crop production and negative environmental effects, compromises were possible. These findings provide new insights into the effects of climatic and management factors on AES, and have practical implications for improving crop production while minimizing negative environmental impacts.

Impacts of future urban expansion on summer climate and heat-related human health in eastern China.

China is the largest and most rapidly urbanizing nation in the world, and is projected to add an additional 200 million city dwellers by the end of 2030. While this rapid urbanization will lead to vast expansion of built-up areas, the possible climate effect and associated human health impact remain poorly understood. Using a coupled urban-atmospheric model, we first examine potential effects of three urban expansion scenarios to 2030 on summer climate in eastern China. Our simulations indicate extensive warming up to 5°C, 3°C, and 2°C in regard to low- (>0%), high- (>75%), and 100% probability urban growth scenarios, respectively. The partitioning of available energy largely explains the changes in 2-m air temperatures, and increased sensible heat flux with higher roughness length of the underlying urban surface is responsible for the increase of nighttime planetary boundary layer height. In the extreme case (the low-probability expansion pathway), the agglomeration of impervious surfaces substantially reduces low-level atmospheric moisture, consequently resulting in large-scale precipitation reduction. However, the effect of near-surface warming far exceeds that of moisture reduction and imposes non-negligible thermal loads on urban residents. Our study, using a scenario-based approach that accounts for the full range of urban growth uncertainty by 2030, helps better evaluate possible regional climate effects and associated human health outcomes in the most rapidly urbanizing areas of China, and has practical implications for the development of sustainable urban regions that are resilient to changes in both mean and extreme conditions.

Quantifying the impacts of climatic trend and fluctuation on crop yields in northern China.

Climate change plays a critical role in crop yield variations, which has attracted a great deal of concern worldwide. However, the mechanisms of how climatic trend and fluctuations affect crop yields are not well understood and need to be further investigated. Thus, using the GIS-based Environmental Policy Integrated Climate (EPIC) model, we simulated the yields of major crops (i.e., wheat, maize, and rice) and evaluated the impacts of climatic factors on crop yields in the Agro-Pastoral Transitional Zone (APTZ) of northern China between 1980 and 2010. The partial least squares regression model was used to assess the contribution rates of climatic factors (i.e., precipitation, photosynthetically active radiation (PAR), minimum temperature (T min), maximum temperature (T max)) to the variation of crop yields. The Breaks for Additive Season and Trend (BFAST) model was adopted to decompose the climate factors into trend and fluctuation components, and the relative contributions of climate trend and fluctuation were then evaluated. The results indicated that the contributions of climatic factors to yield variations of wheat, maize, and rice were 31.7, 37.7, and 23.1%, respectively. That is, climate change had larger impacts on maize than wheat and rice. More cultivated areas were significantly and positively correlated with precipitation than with other climatic factors due to the limited precipitation in the APTZ. Also, climatic trend component had positive impacts on crop yields in the whole region, whereas the climate fluctuation was associated mainly with the areas where the crop yields decreased. This study helps improve our understanding of the mechanisms of climate change impacts on crop yields, and provides useful scientific information for designing regional-scale strategies of adaptation to climate change.

Impacts of changes in climate and landscape pattern on ecosystem services.

The restoration of degraded vegetation can effectively improve ecosystem services, increase human well-being, and promote regional sustainable development. Understanding the changing trends in ecosystem services and their drivers is an important step in informing decision makers for the development of reasonable landscape management measures. From 2001 to 2014, we analyzed the changing trends in five critical ecosystem services in the Xilingol Grassland, which is typical of grasslands in North China, including net primary productivity (NPP), soil conservation (SC), soil loss due to wind (SL), water yield (WY) and water retention (WR). Additionally, we quantified how climatic factors and landscape patterns affect the five ecosystem services on both annual and seasonal time scales. Overall, the results indicated that vegetation restoration can effectively improve the five grassland ecosystem services, and precipitation (PPT) is the most critical climatic factor. The impact of changes in the normalized difference vegetation index (NDVI) was most readily detectable on the annual time scale, whereas the impact of changes in landscape pattern was most readily detectable on the seasonal time scale. A win-win situation in terms of grassland ecosystem services (e.g., vegetation productivity, SC, WR and reduced SL) can be achieved by increasing grassland aggregation, partitioning the largest grasslands, dividing larger areas of farmland into smaller patches, and increasing the area of appropriate forest stands. Our work may aid policymakers in developing regional landscape management schemes.

Quantifying the effect of trend, fluctuation, and extreme event of climate change on ecosystem productivity.

Climate change comprises three fractions of trend, fluctuation, and extreme event. Assessing the effect of climate change on terrestrial ecosystem requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trend and fluctuation of climate change as well as extremely low temperatures caused by a freezing disaster on ecosystem productivity in Hunan province, China. The partial least squares regression model was used to evaluate the contributions of temperature, precipitation, and photosynthetically active radiation (PAR) to NPP variation. A climatic signal decomposition and contribution assessment model was proposed to decompose climate factors into trend and fluctuation components. Then, we quantitatively evaluated the contributions of each component of climatic factors to NPP variation. The results indicated that the total contribution of the temperature, precipitation, and PAR to NPP variation from 2001 to 2011 in Hunan province is 85 %, and individual contributions of the temperature, precipitation, and PAR to NPP variation are 44 % (including 34 % trend contribution and 10 % fluctuation contribution), 5 % (including 4 % trend contribution and 1 % fluctuation contribution), and 36 % (including 30 % trend contribution and 6 % fluctuation contribution), respectively. The contributions of temperature fluctuation-driven NPP were higher in the north and lower in the south, and the contributions of precipitation trend-driven NPP and PAR fluctuation-driven NPP are higher in the west and lower in the east. As an instance of occasionally triggered disturbance in 2008, extremely low temperatures and a freezing disaster produced an abrupt decrease of NPP in forest and grass ecosystems. These results prove that the climatic trend change brought about great impacts on ecosystem productivity and that climatic fluctuations and extreme events can also alter the ecosystem succession process, even resulting in an alternative trajectory. All of these findings could improve our understanding of the impacts of climate change on the provision of ecosystem functions and services and can also provide a basis for policy makers to apply adaptive measures to overcome the unfavorable influence of climate change.

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China.

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.