The current status and spatial distribution characteristics of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) pollution in farmland soils of 93 cities in 30 administrative regions of China over the past 10 years were investigated by meta-analysis, based on literature data on heavy metals in Chinese farmland soils published in two databases, CNKI and Web of Science, from 2014 to 2023. The soil accumulation index and potential ecological risk index methods were used to evaluate the degree of pollution and potential ecological risk of the eight heavy metals in farmland soil, and principal component analysis was applied to elucidate the contributions of various activities to the risk of heavy metal pollution. The results showed that the heavy metal content in farmland soil in China generally exceeded the regional soil background value, and the proportion of eight heavy metals exceeding the standard in farmland soil in the study area was 38.2%-84.1%. In addition, the arithmetic mean value of Cd in the soil of the study area exceeded the risk screening value for Cd in the “Soil Environmental Quality Control Standard for Agricultural Land Soil Pollution” (GB 15618—2018). The results of the soil accumulation index showed that the degree of pollution of the eight heavy metals in farmland soil was Hg>Cd>Pb>Zn>Cu>Ni>Cr>As, from high to low. The pollution levels of Cd and Hg were high, and areas with mild or high pollution accounted for 69.33% and 65.9% of the study area, respectively. The calculation results of the potential ecological risk index (I_r) indicated that Cd and Hg in farmland soils in the study area were in the range of strong ecological risk. The proportions of Cd and Hg in the areas with I_r>300 were 41.9% and 45.2%, respectively. Principal component analysis revealed that the risk of heavy metal pollution in agricultural soils within the study area was primarily attributed to a combination of agricultural activities, industrial production, natural sources, and various other activities. These three principal components collectively accounted for 72.3% of the variance.

Net Ecosystem Productivity (NEP) of vegetation is a crucial component of the carbon cycle and a significant indicator of an ecosystem's carbon budget. This study analyzes the spatial and temporal distribution characteristics of vegetation carbon sources and sinks in the Beijing-Tianjin-Hebei region, based on MOD17A3 and meteorological data, combined with a soil respiration model. The relationships between vegetation NEP and meteorological factors, the Normalized Difference Vegetation Index (NDVI), and land-use change were explored using trend analysis, correlation analysis, and other methods. The results showed that: 1) From 2000 to 2022, NEP in the Beijing-Tianjin-Hebei region showed a fluctuating upward trend, with an annual growth rate of 5.65 g·m⁻² and an average annual NEP of 108 g·m⁻². The area of carbon sinks increased gradually, reaching a maximum of 95.0% in 2022, and the spatial pattern of NEP was characterized by a “high in the north and low in the south”, which was consistent with the regional elevation and obvious spatial heterogeneity. 2) Over the past 20 years, 98.3% of the area of Beijing-Tianjin-Hebei was characterized by an upward trend in vegetation NEP, and 85.9% of the area was characterized by a significant increase in NEP, which was more concentrated in Chengde, Zhangjiakou, and Beijing. The area with a downward trend in NEP accounted for only 1.72%. Chengde had the highest percentage of area with a significant increase in NEP of 98.2%, whereas Handan had the highest percentage of area with a significant decrease of 1.03%. 3) Vegetation NEP in most areas of the Beijing-Tianjin-Hebei region was positively correlated with precipitation and air temperature, and the mean values of correlation with precipitation and air temperature were 0.500 and 0.160, respectively. The percentage of the area where NEP was significantly positively correlated with precipitation and air temperature was 78.2% and 13.9%, respectively, and precipitation was the key meteorological factor influencing the changes in NEP in the Beijing-Tianjin-Hebei region. The average correlation coefficient between NDVI and NEP was 0.430, and the area with a very significant positive correlation accounted for 58.1%, and the area with a high positive correlation was concentrated in the mountainous areas of northwest Beijing-Tianjin-Hebei. The land use change results showed a significant increase in the area of forested land in Beijing-Tianjin-Hebei during the last 20 years, with increases of 31.4%, 24.0%, and 11.9%, respectively, over the three study periods, which is an important factor driving the rise in vegetation NEP in the region. This study provides a reference basis for the accurate assessment of vegetation carbon sources/sinks in the Beijing-Tianjin-Hebei region and the realization of the “double carbon” goal.

There are abundant vegetation types in Guangdong Province and studying the response of vegetation net primary productivity (NPP) in different ecosystems to climatic factors is important for improving the quality of the ecological environment. Based on land cover type, vegetation NPP, and meteorological observation data, the spatiotemporal characteristics of vegetation NPP in different ecosystems in Guangdong Province and their responses to climate factors were analyzed. The results showed that the average temperature and precipitation in Guangdong Province exhibited a slight upward trend from 2000 to 2020, with area proportions of positive growth accounting for 86.8% and 64.8%, respectively. Sunshine hours showed a downward trend, with the area proportion of negative growth accounting for 82.4%. Vegetation NPP showed a fluctuating upward trend, with an average annual value of 1011 g∙m⁻² and an annual growth value of 6.7 g∙m⁻²∙a⁻¹. The positive growth zone accounted for 91.9% of the provincial area. The average annual NPP of the forest ecosystem and the proportion of positive growth areas were highest at 1107 g∙m⁻² and 95.6%, respectively. The average annual NPP of wetland ecosystems and the proportion of positive growth areas were the lowest, at 686 g∙m⁻² and 89.5%, respectively. Vegetation NPP showed significant positive correlations with temperature, precipitation, and sunshine hours, with correlation coefficients of 0.81, 0.48, and 0.68, respectively. The correlation coefficients all passed the significance test at p=0.001, which showed that temperature had the most significant impact on vegetation NPP, followed by sunshine hours and precipitation. Temperature and sunshine hours had the greatest impact on forest ecosystem NPP, and the smallest impact on wetland ecosystems. Precipitation has the greatest impact on farmland ecosystems and the smallest impact on wetland ecosystems. Regarding response time, the correlation coefficients between NPP and temperature, as well as NPP and sunshine hours, reached their maximum values in the current month, whereas the correlation coefficient between NPP and precipitation reached its maximum in the following month. This means that there were no lags in NPP response to temperature and sunshine hours. Regarding the duration of the impact, the correlation coefficient between temperature and NPP was relatively high from the current month to the following two months, that between sunshine hours and NPP was relatively high in the current month, and that between precipitation and NPP was relatively high from the current month to the following three months. Therefore, the impact of precipitation on NPP was the greatest.

Among all coastal ecosystems, mangrove is the vegetation ecosystem with the highest Gross Primary Production (GPP) per unit area. Under the global climate change, carbon cycle process is quantitatively explored. The total area of mangroves in Guangxi ranks second in China. In this study, we aimed to illuminate the GPP change characteristics of mangroves and to explore the sensitivity of GPP to meteorological factors. Our results would be helpful for understanding the carbon cycle dynamics of mangrove, assisting local policy-makers in taking initiatives to combat climate change, and providing scientific basis for conservation management and ecological restoration of mangrove. Until now, there have been few studies on mangroves GPP in Guangxi which used eddy covariance technology. This study focused on the sandy mangrove in ecological restoration area, located in Beihai, Guangxi. Using eddy covariance technology combined with canopy-based observation technology, we analyzed the monthly average daily changing characteristics, seasonal average daily changing characteristics, monthly cumulative changing characteristics, and annual cumulative changing characteristics for mangrove GPP. In addition, the response models of photosynthetically active radiation, air temperature, surface temperature at 5 cm depth, vapor pressure deficit, and rainfall to GPP at daily and monthly scales were explored using single-factor correlation analysis and multi-factor path analysis. Results showed that the daily average changing curve of GPP presented an inverted “U” shape at monthly and seasonal scales. The monthly cumulative GPP showed a “two-peak and one-trough” trend, with peaks in spring and autumn and troughs in summer. The mangrove canopy vegetation index results indicated that the troughs in summer were due to the outbreak of insect pests. The annual cumulated GPP showed a slow increasing trend, and was 1284.11, 1286.67, 1362.10 and 1382.19 g∙m⁻²∙a⁻¹ in 2019-2022, respectively. The average annual cumulated GPP was 1328. 77 g∙m⁻²∙a⁻¹ from 2019 to 2022, and was significantly lower than that of the southeast coastal observation stations, resulting from the soil type, community structure and external disturbance in the study area. Photosynthetically active radiation and air temperature had the greatest direct impact on mangrove GPP, while 5 cm soil surface temperature had the greatest indirect impact on mangrove GPP. Overall, the GPP of sandy mangroves was lower than that of the southeast coastal areas. With the implementation of ecological restoration projects, the GPP increased slowly, but pests and diseases had a great impact on mangroves GPP. Thus, implementations of pest control-related projects are necessary for the improvement of the carbon sink function for mangroves.

Gansu Province, as a crucial component of the national ecological security barrier in Western China, has experienced significant vegetation cover changes in recent years that are directly related to ecosystem restoration and environmental protection. Fractional Vegetation Cover (FVC) data from 2000 to 2020 were used, with 16 influencing factors selected from both natural and anthropogenic aspects, including climate, topography, soil, and human activity. Trend analysis, geodetection, and partial least squares structural equation modeling (PLS-SEM) were applied to explore the dynamics and drivers of vegetation cover changes across different arid and humid regions and temporal periods in Gansu Province. The results indicate that: 1) from 2000 to 2020, the Fractional Vegetation Cover (FVC) in Gansu Province exhibited a continuous overall improvement, with a significant increase in areas with high vegetation cover. Notably, the most pronounced improvements were observed in the Longdong Plateau, Longzhong Plateau, and the southern areas of the Shule River. 2) This period also highlighted significant spatial variations in vegetation cover across zones with different moisture conditions. Arid and semi-arid areas showed relatively slower vegetation improvements than other areas, which were heavily influenced by fluctuations in precipitation and land-use practices. In contrast, the semi-humid and humid zones represented significant improvements in vegetation cover, benefiting from favorable climatic conditions, proactive ecological projects, and increased in soil organic carbon content. 3) Precipitation and land use changes emerged as the primary explanatory variables for FVC, and reforestation projects actively contributed to the increase in vegetation cover. However, unsustainable land use and urbanization processes have led to vegetation degradation. Over time, the influence of climate on FVC has become increasingly positive, whereas the negative impact of unreasonable human activities on FVC remains relatively stable and significant, partially offsetting the positive effects of grain for green programs. In addition, the effect of soil organic carbon content on FVC declined significantly and was indirectly positively affected by climate. 4) Utilizing the Partial Least Squares Structural Equation Modeling (PLS-SEM) framework, this study effectively delineates the driving roles of natural and anthropogenic factors on vegetation cover and explores the strengths and pathways of these interactions between natural factors, anthropogenic factors, and vegetation cover. Comprehensive analysis of vegetation cover changes in Gansu Province not only enhances the understanding of regional vegetation dynamics, but also provides scientific support for ecological restoration and environmental management initiatives.

In this study, soil degradation and nitrogen limitation in alpine meadows were addressed, and the effects of organic acids in plant root exudates on soil carbon and nitrogen mineralization were clarified. In an incubation experiment, the response of common organic acids in Kobresia myosuroides (Villars) Foiri, Gueldenstaedtia diversifolia Maxim, and Anemone rivularis Buch-Ham. were investigated for soil carbon and nitrogen mineralization in southeastern Tibet. Acetic, lactic, and fumaric acids significantly increased the content of soil available nitrogen and phosphorus but had no effect on soil total nitrogen and phosphorus. The rate of soil carbon mineralization gradually decreased with increasing cultivation time under the influence of the different organic acids. Lactic acid and 10 mg·L⁻¹ acetic acid first promoted and then inhibited the soil carbon mineralization rate over time, whereas fumaric acid generally inhibited soil carbon mineralization. In addition, except for 10 mg·L⁻¹ lactic acid, which significantly reduced cumulative soil carbon mineralization, the other concentrations of organic acids had no significant effect on cumulative soil carbon mineralization. Correlation analysis showed a significant negative correlation between acetic acid and cumulative soil carbon mineralization (r=−0.796*). The different organic acids had no significant effect on the net ammonification rate of the soil, whereas medium-to-high concentrations of acetic acid inhibited net nitrification and net nitrogen mineralization. The addition of lactic and fumaric acids had no significant effect on the net nitrification rate or the net nitrogen mineralization rate. Correlation analysis showed that acetic acid was significantly negatively correlated with the net nitrogen mineralization rate (r=−0.785*). Soil carbon mineralization was positively correlated with pH and total nitrogen, whereas the correlation between soil nitrogen mineralization and soil environmental factors differed significantly, depending on the presence of organic acids. In summary, acetic acid is the main organic acid affecting soil carbon and nitrogen mineralization, and the organic acids in root exudates, combined with soil environmental factors, regulate soil carbon and nitrogen mineralization. This study provides a scientific basis for determining carbon and nitrogen sequestration and the development of soil management strategies in ecologically fragile areas.

Heavily polluting enterprises are the main sources of pollution and carbon emissions in China. Investigating the spatiotemporal differentiation characteristics and driving factors of the synergistic effects of pollution and carbon reduction in these enterprises is crucial for further promoting the coordinated governance of pollution and carbon reduction in heavy-pollution enterprises, achieving the goal of "dual carbon" and sustainable economic development. For this purpose, 100 A-share listed companies in China's heavy-pollution industry from 2008 to 2022 were selected as the sample. The Spatiotemporal Geographically Weighted Regression (GTWR) model and kriging spatial interpolation were used to analyze the spatiotemporal differentiation characteristics of the coordinated governance of pollution and carbon emission reduction of heavily polluting enterprises. Additionally, the dual fixed-effects model was employed to analyze the driving factors of the synergistic effects of pollution and carbon reduction in heavy-pollution enterprises and further reveal the heterogeneity of these factors based on the regression results of the GTWR. The results showed the following. (1) From a temporal perspective, since 2008, the synergistic effects of pollution and carbon emission reductions in China's heavily polluting industries have generally exhibited an upward trend, with the mean value increasing from 0.476 in 2008 to 0.490 in 2022. (2) In terms of spatial characteristics, the synergistic effects in the eastern, central, and western regions are 0.413‒0.810, 0.395‒0.662, and 0.187‒0.550, respectively. Initially, the synergistic effect in the eastern and central regions was higher than that in other regions. However, as the collaborative governance of pollution and carbon reduction progressed, differences among the regions gradually diminished. (3) Energy consumption is significantly negatively correlated with the synergistic effect of pollution and carbon reduction in heavy-pollution enterprises, whereas total factor productivity and green technological innovation are significantly positively correlated with the synergistic effect. The driving effects of energy consumption and total factor productivity were more pronounced in the eastern region, whereas the role of green technological innovation was more prominent in the western region. The intensity of environmental regulation and public environmental attention played moderating roles in the driving factors of pollution and carbon emission reduction. This study not only expands the research perspective on the synergistic effect of pollution and carbon reduction in heavy pollution enterprises but also provides insight for China to promote the reduction in pollution and carbon emissions in these enterprises.

Global climate change has increasingly affected terrestrial ecosystems. The occurrence of extreme events such as high temperatures and droughts poses challenges to ecosystem services and biodiversity. Grassland ecosystems store approximately one-third of the world’s terrestrial carbon reserves and play pivotal roles in the global carbon cycle. The net primary productivity (NPP) of grasslands serves as an essential indicator of the adaptability and responsiveness of a system to climate and soil change, offering valuable insights for improving the precision of global carbon cycle models. However, the mechanisms by which grassland ecosystems respond to environmental changes across different climate zones and humidity conditions remain complex and unclear, posing challenges for effective management and conservation of grasslands. In this study, a comprehensive dataset was constructed using the observed NPP data of grasslands worldwide, covering climate factors, such as temperature, radiation, and precipitation, as well as soil factors, such as soil water content, bulk density, and soil particle composition. Through regression analysis and the random forest algorithm, the responses of grassland NPP to environmental factors in different climatic zones are systematically discussed. Regression analysis helped to identify the quantitative effects of climate and soil factors on grassland NPP, whereas random forest algorithms revealed the relative importance and complex nonlinear relationships of each factor. In addition, an asymmetry index was used to analyze the response of grassland NPP to precipitation change, revealing the adaptability of grassland systems to precipitation variability under different climatic conditions and further improving the understanding of the grassland ecosystem response model. In arid regions, grassland NPP is primarily limited by water availability, with minimal influences from other climatic factors and soil properties. These findings provide valuable guidance for grassland management in arid areas, emphasizing the importance of water resource management for maintaining and boosting the productivity and resilience of grassland ecosystems in these regions. Conversely, the response of grassland NPP to environmental factors in humid climatic zones is complex. Grassland NPP was significantly influenced by energy factors such as solar radiation and temperature. Soil factors such as soil water content and bulk density also play crucial roles. This suggests that, under relatively adequate water conditions, grassland ecosystems in humid zones exhibit a more significant range of response mechanisms to environmental fluctuations. Grasslands in these areas must adapt not only to variations in climate factors but also to changes in soil conditions to maintain ecological balance and productivity. Therefore, grassland management in humid areas should adopt an integrated approach that considers the interaction between climate and soil conditions to enhance the resilience and sustainability of grassland systems. In terms of precipitation response asymmetry, this study revealed distinct response patterns for grassland NPP across different climate zones. In arid regions, grassland NPP exhibits a pronounced positive response to precipitation under conditions of high solar radiation, low vapor pressure deficit (VPD), and high soil sand content. This pattern indicates that grassland ecosystems in arid regions develop high efficiency in utilizing sporadic precipitation events, allowing for rapid increases in productivity under limited water input conditions. This phenomenon highlights the adaptability of grassland ecosystems in arid zones to effectively utilize short-term precipitation, thereby enhancing their survival capacity in response to the dual stresses of drought and high temperatures. Additionally, in humid climate zones, grassland NPP showed a more marked positive response to precipitation under moderate levels of precipitation and temperature as well as in soils with lower clay content. This finding reveals that, in humid regions, grassland productivity peaks under moderate precipitation levels, whereas excessive rainfall may lead to decreased soil aeration, thereby inhibiting root respiration and ultimately reducing productivity. This pattern indicates the need for appropriate management of soil moisture in humid areas to avoid the negative impacts of excessive precipitation and to maintain ecological health and grassland productivity. Finally, we identified a “threshold effect” on the response of grassland NPP to environmental factors. Grassland NPP demonstrated a positive response to changes in environmental variables up to a certain threshold, beyond which the response may weaken or even turn negative. This threshold effect was particularly pronounced under extreme climatic conditions, indicating the vulnerability of grassland ecosystems to such extremes. For example, in humid regions, when precipitation levels exceed an optimal threshold, a decline in soil aeration can lead to a reduction in the grassland NPP. These results suggest that management practices should focus on maintaining environmental variables within optimal thresholds for grassland ecosystems to enhance their resilience to climate extremes and preserve their productivity and stability. Future research could expand this study by examining the specific response mechanisms of different vegetation types, such as grasslands and shrublands, to climate change and by analyzing the long-term dynamic changes in ecosystems under shifting climate conditions. Exploring the role of microbial communities in grassland ecosystems, particularly their functions in carbon and nitrogen cycling, could offer a more comprehensive understanding of grassland diversity and stability. Incorporating remote sensing technology, ecological modeling, and artificial intelligence algorithms can further enhance the accuracy of predictive models for climate adaptation, laying the scientific foundation for tackling the complexities of future climate change. In conclusion, this study systematically uncovered the intricate mechanisms by which grassland ecosystems respond to climate and soil factors across diverse climate zones, by utilizing a comprehensive global dataset of grassland NPP. These findings provide essential data to enhance global carbon cycle models and lay a solid theoretical foundation for future grassland management and climate adaptation strategies. Beyond providing actionable recommendations for grassland management and ecological restoration, this study provides scientific insights crucial for maintaining grassland ecosystem resilience in the face of intensifying climate challenges. Finally, this study has far-reaching implications for understanding the global response of ecosystems to climate change, reinforcing the urgent need for informed and sustainable ecological practices.

Litter input influences the soil organic carbon (SOC) mineralization process, with its effect primarily governed by litter C/N, soil fertility, and temperature conditions. However, the combined impact of these three factors remains unclear. This study used low-fertility soil (LF) and high-fertility soil (HF), adding seven different C/N ratio litters and setting incubation temperatures of 23 ℃ and 33 ℃, with constant temperature and no light exposure. CO₂ emissions were dynamically monitored to investigate how SOC mineralization responds to the three factors. Results showed that litter addition significantly increased peak CO₂ emission rates, and litter with a C/N ratio less than 30 had a more pronounced effect on peak CO₂ emission rates compared to litter with a C/N ratio greater than 30. The peak CO₂ emission rate was also affected by soil fertility and incubation temperature, with the highest peak CO₂ emission rate observed under the HF-33 ℃ condition. Litter with a C/N ratio below 30 significantly increased cumulative CO₂ emissions, with maximum increases of 407%, 304%, 345% and 160% under LF-23 ℃, LF-33 ℃, HF-23 ℃ and HF-33 ℃ conditions, respectively. Correlation analysis showed a negative relationship between SOC mineralization rate and litter C/N ratio, suggesting that lower-quality litter inhibits SOC mineralization. Under LF-23 ℃, LF-33 ℃, HF-23 ℃ and HF-33 ℃ conditions, compared to litter with the lowest C/N ratio (CN1), adding litter with the highest C/N ratio (CN7) reduced SOC mineralization rates by 3.53, 3.04, 1.71 and 2.06 times, respectively. Soil fertility influenced SOC mineralization, with the SOC mineralization rate in HF being 1.29 to 2.66 times higher than in LF. The effect of incubation temperature on SOC mineralization showed significant differences in HF, and compared to the CK, litter addition in HF significantly reduced the temperature sensitivity (Q₁₀) of SOC mineralization. Using the PLS-PM model, the study concluded that SOC mineralization results from the combined effects of litter C/N, soil fertility, and incubation temperature. Specifically, the litter C/N ratio exerted a significant negative effect on SOC mineralization, while soil fertility had a major positive effect, and the effect of temperature was relatively minor. The results contribute to a better understanding of how the input of exogenous organic matter with different C/N ratios affects SOC mineralization under various soil fertility and temperature conditions, as well as the underlying combined effects.

Per- and polyfluoroalkyl substances (PFASs) are a typical group of persistent organic pollutants widely distributed in environmental and biological media. Their potential toxicity poses a serious threat to the ecological and environmental safety of the country. In recent years, these chemicals have attracted significant attention and have been included on the list of emerging pollutants in China. To improve the chemical management system and promptly respond to the environmental hazards of PFASs, maintain China’s ecological security, and protect the new development pattern with a new safety system, this study summarized the types and physicochemical properties of PFASs and the pollution status of these pollutants in environmental media such as ambient air in industrial, non-industrial, and polar regions, surface water, tap water, drinking water, site soil, farmland soil, and biological media such as human tissues and mammals. In addition, a risk quotient (RQs) approach was used to assess the ecological risk of PFASs based on the pollution status of PFASs in the water and soil environments in some regions of China. A higher ecological risk from PFASs has been found in some water bodies and around industrial fluoride parks, which could pose a significant threat to the country’s ecological safety. Second, PFASs toxicity mainly manifests as neurotoxicity, immunotoxicity, reproductive toxicity, hepatorenal toxicity, pulmonary toxicity, and endocrine disruption. Toxicity mechanisms include imbalanced intracellular calcium homeostasis, regulation of cellular signaling pathways, and interaction with nuclear receptors. Finally, recent policy measures to control PFASs and the effects of the implementation of some measures in the United States, the European Union, and Japan were introduced, the formulation and implementation experience was summarized, and the control and governance mechanisms of PFASs were analyzed from the aspects of science and technology, economy, and politics compared with China's national conditions, leading to opinions and suggestions for future research on the control of emerging pollutants, such as PFASs. This study provides an overview of material properties, associated toxicities, ecological risks, and control measures for PFASs. It emphasizes the importance of controlling PFASs, and provides new ideas and foundations for the treatment and control of emerging pollutants such as PFASs in the future.

The period from 2000 to 2020 was a period of rapid economic and social development in China, during which the uncontrolled expansion of ecological zones caused great damage. To achieve high quality and sustainable development, protection and restoration are required. Accurate identification of the spatial distribution of regional ecological vulnerability and its evolutionary pattern is an important premise and foundation for the precise implementation of ecological protection and restoration measures. Currently, there is a lack of research on the ecological vulnerability of plateau pastoral areas, and few studies have analyzed in detail the current ecological status and pressure faced by a particular region. The Sanjiangyuan region is an important ecological source and water-supply area in China. In order to investigate the spatial distribution and spatial-temporal evolution of ecological vulnerability in this area, this study, based on the model of “sensitivity-recovery-pressure”, selected 14 indicators that have an important influence on the ecology of the Sanjiangyuan region, and combined the principal component analysis method and geographic detector to analyze the ecological vulnerability of the area in 2000, 2010 and 2011, as well as the ecological stress of the area. Combined with principal component analysis and geodetector, we analyzed the ecological vulnerability of the region in 2000, 2010 and 2020, and revealed its driving mechanism. The results showed that (1) the ecological vulnerability of the Sanjiangyuan region is dominated by mild, moderate and severe vulnerability, with an average area share of 34.5%, 29.9% and 28.6% in the three periods, respectively; the spatial distribution of vulnerability is characterized by a pattern of “high in the north and low in the south”, with obvious regional differences. (2) From 2000 to 2020, the ecological sensitivity, resilience and vulnerability of the Sanjiangyuan region will show a trend of “rising first and falling later”; the ecological pressure degree is in a continuous upward trend with the economic and social development. (3) The spatial pattern of ecological vulnerability was relatively stable, with significant spatial clustering characteristics: the high-high clustering area was mainly distributed in the northern region, and the low-low clustering area was mainly distributed in the southern region with high vegetation coverage and high precipitation. (4) Annual precipitation, dryness, relative humidity, and NDVI were the main drivers of ecological vulnerability in the Sanjiangyuan region, with q-values of 0.811, 0.705, 0.614, and 0.574, respectively. Ecological vulnerability is the result of the integrated effects of multiple factors owing to the interaction between different factors. This study provides a basis for the selection of indicators for the assessment of ecological vulnerability in plateau pastoral areas, and a reference value for the identification of ecological protection areas in the Sanjiangyuan region.

Coastal wetlands serve as crucial carbon sinks with significant carbon sequestration potential in coastal zones, offering a long-term solution for mitigating global climate change. As one of the most important invasive species in Chinese coastal wetlands, Spartina alterniflora has biological characteristics such as strong adaptability, high reproduction rate, rapid growth, and fast spreading compared to native vegetation. This poses a threat to the survival of native wetland vegetation in salt marshes and mangroves and subsequently affects the soil carbon budget, including soil carbon sequestration, carbon decomposition, and lateral carbon transfer. Following photosynthetic carbon assimilation by vegetation, organic carbon is inputted into the soil as litter, root residues, and root exudates. Inorganic carbonates are generated during soil carbon assimilation to achieve fixation of soil inorganic carbon (SIC) fixation. This study summarizes the differences in photosynthetic carbon assimilation capacity between Spartina alterniflora and native vegetation, changes in soil organic carbon in vegetation sources caused by Spartina alterniflora invasion in coastal wetlands, and the effects of Spartina alterniflora invasion on soil inorganic carbon storage in coastal wetlands. In this study, the changes and influencing mechanisms of greenhouse gas carbon dioxide (CO₂) and methane (CH₄) emissions after Spartina alterniflora invasion of coastal wetlands were explored, and the effects of Spartina alterniflora invasion on soil lateral carbon transfer in the form of dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), and particulate organic carbon (POC) in coastal wetlands were analyzed. Finally, this study presents future research prospects and suggestions regarding the impact of invasion on soil carbon budget. It included four aspects: establishing a field observation network in coastal wetlands to expand the research scale, focusing on spatiotemporal variability and driving mechanisms of soil carbon stocks under the invasion of Spartina alterniflora, developing ecosystem dynamics models to systematically quantify and predict the consequences of the invasion, and formulating locally adapted ecological management schemes for coastal wetlands.

Understanding the spatiotemporal evolution of eco-environmental quality (EEQ) is essential for evaluating the combined impact of climate change and human activities on ecosystems. A thorough analysis of the spatiotemporal characteristics and driving factors of the EEQ in Hubei Province can offer valuable insights for developing regional ecological protection and vegetation restoration strategies. This study focused on the synergistic effects of altitude, climate, and human footprint on EEQ evolution. Using EEQ and land use data from 2001 to 2020, along with Theil-Sen Median and Mann-Kendall analyses, this study identifies EEQ evolution patterns and forecasts future trends. Furthermore, by integrating multidimensional data, including altitude, climate, and human footprint, and employing linear correlation analysis and structural equation modeling, this study investigated how natural and anthropogenic factors influence EEQ and suggests strategies to address its decline. The findings revealed that the EEQ index increased with altitude until it reached a turning point between 2000 m and 2200 m, after which it decreased. This pattern was strongly linked to variations in temperature and intensity of human activity at different altitudes. Over the past 20 years, the EEQ in Hubei Province has generally followed a trend of initial improvement followed by a decline, with significant regional differences. Specifically, the EEQ increased in the western mountainous areas, but decreased in the central-southern Jianghan Plain. The structural equation model further showed that temperature positively influenced EEQ in the western mountainous areas, whereas in the Jianghan Plain, EEQ was negatively impacted by the human footprint and positively influenced by solar radiation, with the model explaining 98% and 82% of the variance in these regions, respectively. An analysis of EEQ trends from 2011 to 2020, combined with the Hurst index, suggests that the EEQ in western mountainous areas will continue to improve, whereas it may continue to decline in the Jianghan Plain. In response, this study recommends enhancing ecological protection and promoting vegetation restoration to mitigate the risks associated with declining EEQ. This research not only advances the theoretical understanding of EEQ evolution mechanisms but also provides practical guidance and decision-making support for ecological conservation and sustainable economic development in Hubei Province and similar regions. The innovation of this study lies in its comprehensive integration of multi-source data and diverse analytical methods to thoroughly analyze the complex factors driving EEQ evolution. This approach provides a valuable methodological reference for future research on ecological environments.

The size distribution of the chemical components of particulate matter in the atmosphere is closely related to its source, formation process, environment, and health effects. There are relatively few studies on the characteristics of the particle size distribution of particulate matter in different seasons and the contribution of different sources to coarse and fine particulate matter. Size-resolved aerosol samples were collected in Nanjing during December 2022 (winter) and August 2023 (summer). Samples of coarse and fine particulate matter (PM_2.1-10, PM_2.1) were further analyzed for their carbonaceous compositions and water-soluble inorganic ions. The size distributions and seasonal variations of all the species were characterized. The potential sources of aerosols were quantified using the positive matrix factorization (PMF) model. The results showed that organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) had bimodal distributions in both seasons. Both SO₄²⁻ and NO₃⁻ showed a bimodal distribution during the warm and cold seasons. NH₄⁺ exhibited a unimodal distribution, peaking at 0.43-0.65 μm in both seasons. Regarding the seasonal variation, the concentrations of the main chemical species were higher in winter, with the exception of Na⁺ and SO₄²⁻. Markers of crustal materials, such as Ca²⁺ and Mg²⁺, were mainly found in the coarse mode during summer and winter. Finally, four emission sources were resolved using the PMF model. The results showed that secondary aerosols and biomass burning were the dominant sources of PM_2.1, accounting for 65.7% and 61.0% in winter and summer, respectively. Biomass burning and secondary nitrate dominated PM_2.1 pollution in winter, while secondary sulfate was a major source in summer. For PM_2.1-10, traffic emissions were a major source in winter, with a share of 41.8%. In contrast, biomass burning and secondary nitrate were the main sources of PM_2.1-10 in the summer, contributing approximately 43.9% of the PM_2.1-10 masses. This study investigated the characteristics of the particle size distribution, seasonal variations, and sources of the chemical components of particulate matter, which can provide a scientific basis for the effective prevention and control of air pollution.

Different types of ESs have intricate trade-offs or synergies, and these relationships exhibit strong spatial heterogeneity. Understanding spatial heterogeneity and its driving factors is important for sustainable ecosystem planning and management. Using the Changsha-Zhuzhou-Xiantan Urban Agglomeration (CZTUA) as the study area, we first quantified six important ESs (water conservation (WC), soil conservation (SC), carbon sequestration (CS), habitat quality (HQ), food production (FP), and landscape aesthetics (LA)) in 2020 using the InVEST model and the Intelligent Urban Ecosystem Management System (IUEMS). Then, the correlation coefficients between these ESs were estimated for each 1 km grid to investigate the trade-offs or synergies and their spatial patterns. Finally, logistic regression analysis was used to identify the factors influencing trade-offs or synergies between ESs. The results showed that 1) the spatial patterns of SC, WC, CS, HQ, and LA were high in the southeast and low in the northwest, whereas FP was high in the northwest and low in the southeast in 2020. 2) The trade-offs or synergies between ESs are spatially heterogeneous in the CZTUA. More than 60% of the study area showed synergistic relationships between SC and CS, SC and WC, SC and HQ, SC, and LA, which were mainly distributed in northeastern and southern mountainous areas and western farmlands. Trade-offs between ESs were mainly found in built-up areas and their peripheries. Trade-offs between FP and CS, FP and WC, FP-HQ and FP, and LA covered over 65% of the study area, mainly in the northern plain and southern mountainous areas, and were primarily found in urban and surrounding non-forested areas. 3) The spatial heterogeneity of trade-offs and synergies between ESs is influenced by natural and socioeconomic factors as well as management policies. Synergies between ESs are hindered by steep areas. Synergies between regulating, supporting, and cultural services were promoted by increases in temperature, precipitation, and NDVI. However, synergies between FP and other ESs showed opposite responses to temperature, precipitation, and NDVI increase. Socioeconomic development leads to few synergies or trade-offs between ESs. Ecological protection measures promote synergy between the CS and LA, SC and HQ, SC and LA, SC and CS, and SC and WC.

Mastering the spatio-temporal variations in soil erosion and its economic value is of great significance for the comprehensive management of river basins and the stable performance of soil conservation functions. Most existing studies tend to use the superposition of multi temporal soil erosion spatial distribution maps and equivalence method to explore the spatio-temporal pattern and economic value of soil erosion, but the spatial differentiation and dynamics of soil erosion were often overlooked. Taking Henan Province as an example, based on the RUSLE model, the parameter factors in the model were determined through data such as rainfall, soil particle composition, land use type, digital elevation, and remote sensing images to quantitatively analyze the spatio-temporal distribution characteristics of soil erosion in the region from 2000 to 2020. Exploratory Spatial Data Analysis (ESDA) and the geographical detector method were employed to explore hotspot areas of soil erosion and their driving factors. The economic value of soil conservation was assessed using the replacement cost method. The results show that: 1) the overall erosion area of moderate to mild and above in Henan Province showed a decreasing trend, reaching its lowest point in 2015. 2) The spatial distribution and evolution of soil erosion in Henan Province displayed an obvious spatial aggregation effect, with soil erosion intensity showing a positive spatial correlation (the global Moran’s I index ranged from 0.450 to 0.705). The area of the “high-high” aggregation zones has significantly decreased, and the aggregation trend has shown an overall weakening with slight expansion. The hotspots of soil erosion were primarily distributed in Anyang, Hebi, Jiyuan and Sanmenxia cities. 3) Rainfall and slope were primary environmental drivers affecting soil erosion, with single-factor q values ranging from 77.7% to 79.1% for rainfall and from 43.7% to 82.2% for slope, respectively. Areas with rainfall of 3.28×10²‒6.43×10² mm and steep slopes greater than 29.0° were high-risk areas for soil erosion. Vegetation coverage was found to have a significant inhibitory effect on the soil erosion process, with single-factor q values ranging from 16.1% to 19.4%, and the q values for the interaction of any two factors ranging from 40.0% to 83.9%. 4) The economic values of soil conservation were notably fluctuating, with values of 8.36×10⁹, 8.21×10⁹, 9.26×10⁹, 3.52×10⁹ and 7.17×10⁹ yuan from 2000 to 2020, respectively. The research results can provide theoretical reference and decision-making basis for improving soil conservation function and economic value by clarifying the current situation and driving factors of regional soil erosion.

The study on the changes in the relationship between the importance value of dominant populations and species diversity caused by different grazing intensities can provide theoretical support to the protection of grazing grassland and the restoration of degraded vegetation. This study choosed the Stipa breviflora desert steppe in Inner Mongolia as the research object, adopting a single factor randomized block design (CK, control; MG, moderate grazing; HG, heavy grazing). The survey was conducted on the height, coverage, and density of plant communities in each plot, then calculating the important value of dominant population and species diversity, exploring the relationship between them by comparative analysis and canonical correlation analysis. The results are as follows: With the increase of grazing intensity, the importance value of S. breviflora increased while the species richness index decreased. The dominance index was highest and the diversity index was lowest under the MG treatment. A canonical correlation analysis between the important value of dominant population and the species diversity showed that the cumulative contribution rate was largest in the MG treatment (96.060%) while it’s smallest in the CK treatment (90.160%). The increasing of grazing intensity reduced the complexity and dimension of the relationship between the importance value of dominant populations and species diversity (from 2 canonical correlations to 1 canonical correlation). In CK treatment, the increasing of the importance value of each dominant population would decreased the plant community diversity index, and the increasing of the importance value of Cleistogenes songorica and Allium polyrhizum would increased the plant community evenness index. In MG treatment, the increasing of importance value of S. breviflora would decreased the dominance index. In HG treatment, the increasing in the importance value of S. breviflora and C. songorica reduced the diversity index. For the important value of dominant population and the species diversity index, the correlation with its own typical variables was more complicated, while the correlation with the corresponding typical variables was relatively simple. The number of significant correlation coefficients in CK, MG and HG treatments was 15, 20 and 12, respectively. Therefore, the relationship between the importance value of dominant populations and species diversity was the most complex in MG treatment. In conclusion, the plant community have the most complex in the MG treatment, however, in the HG treatment, the plant community are more susceptible to external environmental interference, and it is relatively difficult to restore the original state after the degradation of grassland plant communities.

Studying the distribution patterns of plant diversity along altitudinal gradients is crucial for the successful restoration of forest vegetation and the conservation of species. To reveal the vertical distribution characteristics of plant diversity in mountainous areas, eight elevations (800, 900, 1000, 1100, 1200, 1300, 1400, and 1500 m) in Nanling Nature Reserve were studied. The distribution pattern of plant diversity at different elevations was analyzed, and the logarithmic Cauchy model was used to fit plant abundance at different elevations. The results showed that 1) there were 290 species belonging to 148 genera and 81 families in eight altitudinal gradient plots in Nanling. 2) The species diversity of Nanling showed a “unimodal” trend along the altitude gradient, and the species diversity index (species richness index 157, Shannon-Wiener index 4.142, Pielou’s evenness index 0.459) was highest at middle altitudes (1000-1300 m). The high-altitude areas (1300-1500 m) had the lowest species richness index (69), Shannon-Wiener index (2.317), and Pielou evenness index (0.197). 3) The phylogenetic diversity of the tree layer (−2.918 to 0.762) differed from species diversity, and phylogenetic diversity showed a discrete structure in general. The environmental filtering effect played an important role in the construction of the Nanling forest community, and the competitive exclusion effect gradually appeared in the high-altitude forests. 4) Habitat restriction and interspecific competition in the middle- and high-altitude communities may weaken the formation potential of dominant species in the tree layer but increase the coexistence probability of rare species in the community. In terms of species protection, humans severely disturb low altitudes, and it is recommended that an ecological red line be set at low altitudes (800-1000 m). High-altitude areas (1300-1500 m) of forest habitats are relatively poor, but are important habitats for many rare and endangered plants. Good growth conditions, such as reduced intensity of interspecific competition and an improved microclimate, should be created for these species. The results of this study deepen our understanding of the changes in plant community biodiversity in Nanling evergreen broad-leaved forests and contribute to the formulation of biodiversity conservation strategies in this region.

Wet and dry deposition processes are the major removal mechanisms for atmospheric pollutants and are important sources of nutrients and toxins in ecosystems. Compared to wet deposition, dry deposition is more difficult to measure directly; thus, an inferential approach is often used to estimate dry deposition fluxes. In this study, size-resolved particle dry deposition velocities (V_d) were calculated using classical parameterization, which was then combined with measured size- and chemically resolved ambient concentrations to estimate the dry deposition fluxes of particulate matter, with a focus on heavy pollution days. The calculated size-resolved V_d of particulate matter varied from 0.037 to 0.50 cm·s⁻¹, with increased values at high wind speeds and low relative humidity. The maximum and minimum values of V_d occurred at 5.8‒9 μm and 0.65‒1.1 μm or 1.1‒2.1 μm, respectively. With a minimum V_d value at a particle size of 1.1 μm, V_d increased as the particle size decreased or increased, reflecting the different dominant microphysical mechanisms of dry deposition for different particle sizes. During the observation period, dry deposition fluxes of particulate matter ranged from 9.41 to 108.71 mg·m⁻²·d⁻¹, with a mean value of 36.65 mg·m⁻²·d⁻¹. The concentration and V_d had a greater influence on the dry deposition fluxes of the coarse and fine particles, respectively. During heavy polluted days, the dry deposition fluxes of particles at each size range showed an upward trend, among which the dry deposition of secondary aerosols of nitrate, sulfate and ammoniums showed an obvious “size distribution shift” phenomenon. Such a phenomenon occurred in both January 2013 and January 2022, indicating that persistent heavily polluted weather in the North China Plain may increase the input of particulate species to the surface ecosystem through dry deposition.

The karst region in eastern Yunnan, China, which is known for its fragile ecosystem, suffers from severe desertification, soil erosion, and landscape fragmentation. This complex background significantly affects soil properties and carbon cycling, and causes difficulties in assessing soil organic carbon (SOC) stocks. Identifying the spatial distribution of SOC and its affecting factors, thus improving the karst SOC sink, is of high significance for achieving carbon neutrality and reducing global warming. In this study, the characteristics of SOC and its affecting factors were examined using geostatistical methods, the Random Forest Model (RF), and the SHapley Additive exPlanations (SHAP) method based on soil survey data. The findings were as follows: 1) SOC in the surface layer varied significantly across the region, ranging from 1.45 to 56.0 g∙kg⁻¹, and the coefficient variation (CV) was approximately 46.7%. 2) Significant differences in SOC existed among different land use types and soil types, and the surface SOC decreased and then increased as elevation increased. 3) Moderate autocorrelation (nugget coefficient: 48.4%) was observed in the spatial distribution of SOC. Total nitrogen (TN), total phosphorus (TP), precipitation, altitude, and pH were the primary influencing factors. Soil TN and TP, as the key factors, explained approximately 88.5% of the spatial variation in SOC. 4) A threshold or peak effect was observed in the impact of key factors on the SOC. For instance, the effect of TN on SOC changed from negative to positive when TN exceeded 1.75 g∙kg⁻¹. The positive effect of TP reached its peak value at 1.50 g∙kg⁻¹. This implies that excessive phosphorus fertilizer input may lead to resource waste rather than improve soil fertility. Altitude also played a significant role in SOC, with the peak value at 1750 m for positive impact. Similarly, the pH had a peak positive effect of approximately 4.45. These findings on the threshold or peak effects of key factors are especially valuable for understanding the complex mechanisms of SOC accumulation in karst regions.