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.

Per- and polyfluoroalkyl substances (PFASs) are a diverse group of emerging persistent organic pollutants (POPs) known for their versatile applications, complicated properties, and associated ecological and health risks through environmental pollution. While previous published reviews have summarized the sources and distribution of PFASs in soil and water ecosystems, this paper aims to fill the crucial gap by a systematic overview of their sources, spatial and temporal distribution, and human health risk assessment in the atmospheric environment. Sources of PFASs in atmosphere include the industrial production and application of fluoropolymers, product consumption, waste treatment, volatilization and sublimation from soil and water environments. The PFASs accumulate in atmospheric particulate matters, showing significant concentration variations across regions and seasons, influenced by the industrial activities, population density, and meteorological parameters. Typically, PFASs have a broader spatial distribution with low concentrations during warm seasons, while the pollution levels are higher and concentrated near emission sources in winter. Over the past decade, the concentration of atmospheric PFASs in China has decreased, but their types have significantly increased, mainly due to the impact of policy measures shifting towards the production of PFASs substitutes. Atmospheric PFASs can enter the human body and induce health risks through the exposure pathways of inhalation, skin uptake, and oral ingestion. Currently, inhalation exposure assessment models are mainly used to assess their health risks. Pollution prevention and control measures in developed regions, such as the United States and Europe, have achieved some reduction in PFAS emissions to environment, but they mostly targeted at single substance, and production is gradually moving towards substitutes with unclear risks. Looking ahead, future research on atmospheric PFASs should delve into the transport and transformation mechanisms, synergistic effects and toxicity risks with other pollutants (e.g., particulate matters), establishing long-term monitoring networks and quantitative source apportionment methods, revealing their health effect mechanisms in depth, and developing systematic and comprehensive human health risk assessment models.

Extensive use of agricultural plastic film as greenhouse and ground cover with low recycling rates results in a significant increase of plastic fragments and microplastics in the soil, consequently affecting the sustainable utilization of agricultural land. This paper focuses on the growth scale, spatial-temporal distribution, and regional differences of agricultural plastic film based on statistical yearbooks.The generation pathways, distribution of microplastics from agricultural film and potential risks of microplastic to farmland in China are analyzed and summarized.Statistical data shows that there is a continuous increase of plastic film usage in China with an annual growth rate of approximately 6.51% during 1994 to 2020. Among them, there is a peak value of usage of agricultural plastic film observed at 2015, in which ground cover film accounted for over 50.0%. Ground cover film is a dominate source of microplastics in farmland soil, especially in the northwest arid oasis regions, reaching up to 38.0 kg∙hm⁻², Microplastics from agricultural film is generally generated through natural, agricultural, and biological pathway depending on microbial activity, plastic types, and environmental conditions. Overall, the long-term planting areas in the northwest and the intensive farming areas in North China, East China, and Southwest China face serious microplastic pollution with levels reaching up to 4.83×10⁴ ind∙kg⁻¹. The porous characteristic of soil allow microplastic particles to migrate through gravity settlement and rainwater infiltration, leading to the microplastic contamination of soil, migration of other pollutants carried by them and subsequent risks to soil structure, soil flora and fauna, microbial communities, and human health. Finally, both the technical development such as raising the lower limit of thickness of polyethylene agricultural film and drawing biodegradation standards, “plastic ban/restriction” policies provide a basis for upgrading the industrial structure of agricultural plastic film, favoring plastic pollution control in China. Source prevention, development of alternative techniques, and close-loop management of agricultural plastic film are effective methods to address current agricultural film pollution, while technological upgrading will be comprehensive solution to improve agricultural plastic pollution control in the future.

Forest soil microorganisms determine the energy flow and material cycle of forest ecosystems, and their community structure and influencing factors are significant to maintain ecosystem stability and respond to global climate change. Phospholipid fatty acids (PLFAs) can be used as biomarkers to directly reflect the biomass and community structure of different microbial communities in soil because they only exist in living microorganisms. This study focuses on soil microorganisms and uses the PLFA method to analyze the community structure, biomass, and physicochemical properties of microorganisms in natural forest soils from all six climate types in China. The main factors affecting the microbial community structure were analyzed using correlation analysis and redundancy analysis methods. The analysis results indicate that there are significant differences in soil density, soil pH, soil litter carbon content, soil organic carbon content, soil total nitrogen content, soil carbon nitrogen ratio, and soil total phosphorus content among the six climate types. There are significant differences in fungal community biomass among the six climate types, with a trend of first increasing and then decreasing as the climate types change from cold zone to temperate zone to tropical zone. The ratio of fungi to bacteria in warm temperate soil is the highest (0.7), significantly higher than that in subtropical and tropical soils (0.4-0.5). The ratio of Gram positive to negative bacteria in tropical and alpine soils is significantly higher than that in other climate types (1.3-1.5), with the lowest in subtropical soils (0.7). The climate (annual average temperature, annual precipitation) and soil physicochemical properties (soil pH, soil density, soil total nitrogen content and soil organic carbon content) are significantly correlated with the soil microbial biomass and community structure represented by PLFAs content (P<0.01). This study summarizes that there is no significant difference in the overall microbial biomass represented by total PLFAs among six climate types, but there are significant differences in soil physicochemical properties and microbial community structure. The main influencing factors of forest soil microbial community structure are annual mean temperature, annual mean precipitation and soil pH value. This study reveals the characteristics of forest soil microbial communities in China as a whole, and providing a basis for us to reveal the response of soil microbial communities to climate change in space.

Soil algae are microscopic organisms widely found in soil. In recent years, research on soil algae has made remarkable progress. This review focuses on the study of soil algae in different habitats (i.e., deserts, croplands, saline soils, mines, forests and tundra). These habitats vary in composition and abundance, reflecting the adaptive capacity of soil algae to specific environmental factors. However, there is a lack of comparison and synthesis across multiple habitats, leading to a poor understanding of the diversity, function, and comparative adaptive strategies of soil algae. Additionally, the response of soil algae to abiotic factors, such as high temperature, high salt, drought and strong ultraviolet radiation has become a hot topic of research. Some studies have revealed that soil algae can secrete nutrients to cope with these stress conditions, improving the soil environment and protecting the growth of other crops. Finally, the physiological and ecological functions of soil algae are summarized, including the following: nitrogen fixation, which can absorb atmospheric nitrogen and increase the nitrogen content of soil algae; carbon fixation, which can absorb atmospheric carbon dioxide through photosynthesis to increase the carbon content of the soil; sugar secretion, which can secrete extracellular polysaccharides to increase soil aggregation and adsorption of harmful heavy metals; and phosphorus solubilization, which can dissolve the insoluble phosphorus of the soil algae and convert it into phosphorus that can be directly absorbed by plants. Phosphorus solubilization can dissolve the insoluble phosphorus of soil algae and convert it into phosphorus that can be directly absorbed by plants. Looking forward, future research should focus on screening dominant algal species in different soil habitats and inoculating the soil through enrichment culture to explore their interrelationships with other soil biomes and reveal the differences in their diversity, community structure and adaptive mechanisms. With the intensification of global climate change, the study of soil algae can provide new clues for us to assess and predict the response and adaptive capacity of soil ecosystems under future climate change. Therefore, summarizing the above discussion, the review can provide some references for people to study and utilize soil algae to improve the soil environment, enhance crop growth, and cope with the challenges of various harsh environments.

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.

Microplastics are becoming one of the important emerging pollutants that threatens the safety of the global water ecosystem. Microplastics have attracted great attention from countries all over the world. When microplastics enter the freshwater environment, they are not only easy to form biofilms on the surface, but also easy to contact with the existing biofilms in the water. However, there is still a lack of research foundation for the study of the interaction between microplastics and biofilms in freshwater. In this paper, the distribution of microplastics in freshwater, the effects of biofilm on the migration and transformation of microplastics, and the effects of microplastics on the microbial community structure of biofilms were systematically reviewed. The effects and potential mechanisms of microplastics on ecological functions such as carbon and nitrogen cycling of biofilms were revealed. Microplastics are widely distributed in freshwater rivers and lakes. The interaction between biofilms and microplastics could significantly alter the properties of microplastics, thereby affecting their environmental behavior and fate in aquatic ecosystems. Biofilms could enrich microplastic particles, increase the speed and depth of microplastic sedimentation, and accelerate the degradation of microplastics. Microplastics in the environment not only have toxic effects on biofilms, leading to negative effects such as slow growth, but also alter the microbial community, enzyme activity and functional gene abundance of biofilms. Microplastics could enhance the carbon cycling function of biofilms by acting as the carrier and carbon source of biofilms, but they also cause biofilms to be damaged and weaken its carbon cycling function. Microplastics could change the living environment of biofilms, the total amount of biofilms, and the enzyme activity and gene abundance related to nitrogen metabolism, thereby affecting the nitrogen cycling function of biofilms. This study proposes that it is necessary to carry out in-depth research on the kinetic process of biofilm adsorption and degradation of microplastics, the internal mechanism of “water-sediment-organism” migration and transformation of microplastics influenced by biofilms, and microbial community structure and function during carbon and nitrogen cycling of biofilms influenced by microplastics under real aquatic ecological conditions. This paper aims to deeply evaluate the potential impacts and risks of microplastic pollution in freshwater ecosystems.

Understanding vegetation dynamics and their response to climate change is essential to improve the carbon sequestration capacity of terrestrial ecosystems in the context of global change. As an important ecological barrier in north China, Inner Mongolia is one of the provinces with the most diverse climate and ecosystem. While net ecosystem productivity (NEP) is strongly associated with climate change, it is unclear whether and how such responses exist in ecologically fragile areas, such as Inner Mongolia, which contains multiple ecological transition zones and vegetation types. In this study, the NEP of vegetation in Inner Mongolia from 2001 to 2020 was estimated by using the net primary productivity and soil respiration models based on remote sensing vegetation index data, land cover data, and meteorological observation data. The temporal and spatial changes of NEP for different vegetation types and their responses to three typical climatic factors including precipitation, temperature, and solar radiation were studied. The results showed that (1) the vegetation NEP in Inner Mongolia gradually decreased from northeast to southwest, and the average NEP was C 61.2 g·m^-2. The average annual NEP of the forest, grassland, and cultivated land was C 270 g·m^-2, 54.7 g·m^-2, and 140 g·m^-2, respectively. (2) From 2001 to 2020, the terrestrial ecosystem carbon sink in Inner Mongolia showed an upward trend, but there were some fluctuations, among which the NEP of forest and grassland showed an upward trend, while the NEP of cropland showed a downward trend. Forest had the largest mean NEP, followed by cropland and grassland. (3) There were significant differences in the response of NEP to climatic factors for different vegetation types, with the NEP of cropland was mainly affected by solar radiation, the NEP of grassland was controlled by precipitation and solar radiation, and the NEP of forest was under the influence of all three climatic factors. This study is of great importance for evaluating the carbon balance of the terrestrial ecosystem in Inner Mongolia, and also for evaluating the carbon sequestration capacity of the ecosystem and studying its carbon cycle mechanism.

With the acceleration of urbanization and industrialization, the dominant function of land use in the Yangtze River Economic Belt has changed dramatically, and the transformation of production, living, and ecological spaces (i.e., the three types of spaces) strengthens its influence on the eco-environmental quality. It is of great significance to study the eco-environmental quality in the Yangtze River Economic Belt from the perspective of the three types of spaces, which can promote the high-quality development of the Yangtze River Economic Belt. Based on the land use remote sensing monitoring data of 2000, 2010 and 2020, we quantitatively analyzed the spatial heterogeneity and its influential factors of 130 cities in Yangtze River Economic Belt by applying statistical methods including the index of eco-environmental quality and Geodetector. The empirical results showed that (1) during 2000-2020, the eco-environmental quality of the Yangtze River Economic Belt was above the average level. More specifically, the eco-environmental quality remained unchanged during 2000-2010 and mainly consisted of two types: medium and relatively high quality; from 2010 to 2020, the level of eco-environmental quality changed, with a decrease in the areas of medium and high quality and an increase in the areas of high quality. (2) There are significant differences in the spatial distribution of eco-environmental quality. The overall eco-environmental quality of the Yangtze River Economic Belt showed the trend of low in the northeast and high in the west, central and southeast. The spatial distribution of eco-environmental quality was consistent from 2000 to 2010. From 2010 to 2020, the eco-environmental quality level in most regions increased, with the medium quality transforming into higher quality and comparatively higher quality transforming into high quality. (3) There were significant differences among the driving factors that influenced the spatial heterogeneity of eco-environmental quality. The dominant driving factors included land use, population density, and slope, and the value of q were 0.776, 0.409 and 0.406, respectively, while the influence of other factors were relatively weak. (4) The mutual effects between any two factors were greater than the impact of a single factor on the spatial differentiation of eco-environmental quality, and the combination of land use degree and other factors was the most important factor affecting the spatial differentiation of eco-environmental quality in the Yangtze River Economic Belt.

Under the background of global warming, the uncertainty in the characteristics of regional dry and wet changes increases. Studying the spatio-temporal evolution trend of meteorological drought under different time scales and identifying the hot spots of drought events are of great significance for agricultural production and drought prevention. Based on the long-term series and multi-time-scale standardized precipitation evapotranspiration index (SPEI) raster data with resolution of 5.5 km generated for Southwest China from 1983 to 2020, this paper constructed four indicators, the maximum lasted drought months (Max_mon), the mean annual drought months (Mean_mon), the count of drought events (C_DE), and the mean lasted months of drought event (MM_DE) (drought events are defined as at least 3 consecutive months with SPEI-1≤-1). And the spatio-temporal evolution of meteorological drought trends and drought events in Southwest China were studied in three time-scales (38, 18 and 10 years) and for four periods (1983-2020, 1983-2000, 2001-2010, and 2011-2020). The results show that (1) the Southwest China is prone to monthly and seasonal droughts. From 1983 to 2020, the Southwest China had experienced periodic dry-wet fluctuations. From 1983 to 2000, southern Sichuan became significantly drier, and so was southern Yunnan from 2001 to 2010, and from 2011 to 2020, the Southwest China was mainly getting wet. (2) The constructed drought intensity indicators Max_mon and Mean_mon can effectively reflect the susceptibility and spatial distribution of meteorological drought in Southwest China. The Max_mon indicator showed that more than 50% of Yunnan and Sichuan were prone to long-term drought for at least 5 months, and the Mean_mon indicator showed that the mean drought intensity in Yunnan increased continuously during the three periods, while Sichuan, Chongqing and Guizhou showed a trend of first increasing and then weakening. (3) The constructed drought event indicators C_DE and MM_DE can effectively identify the hot spots of drought events in different periods. The results show that the hotspots of drought events were in northern Sichuan from 1983 to 2000, in central Yunnan from 2001 to 2010, and in central and northern Yunnan and southern Sichuan from 2011 to 2020. The drought event in Yunnan was the most serious from 2001 to 2010, with an average MM_DE of 4.70 months per time. The SPEI high-resolution products produced in this paper can provide refined meteorological drought distribution information. The constructed drought intensity and drought event indicators based on long-term SPEI can effectively identify the areas with frequent meteorological drought occurrence and the hot spots of drought events in Southwest China. This study has great practical significance for dealing with meteorological and agricultural droughts.

The aboveground biomass of vegetation is an important index reflecting the carbon sequestration capacity of terrestrial ecosystems. Using remote sensing technology to carry out vegetation aboveground biomass estimation and spatial inversion in arid areas can provide an important basis for health assessment and carbon storage estimation in desert oasis ecosystems. Based on field surveys and field sampling data, seven vegetation indices and 13 band variables were extracted from Landsat 8 OLI multispectral images to form four variable combinations for modeling. Support Vector Machine (SVM), Back Propagation Neural Network (BPNN), eXtreme Gradient Boost (XGBoost), and Random Forest (RF), which are four machine learning algorithms, could estimate aboveground biomass by remote sensing and spatial inversion in the delta oasis of Weigan-Kuqa rivers in Xinjiang. The results showed that (1) the vegetation aboveground biomass inversion models constructed by band variables and random frog jump algorithm preferred variables had significantly better estimation accuracy than the total variables and index variables. The prediction abilities were more stable. Compared with SVM and BPNN, the models constructed by XGBoost and RF algorithms had a better estimation effect and could more accurately estimate the aboveground biomass of vegetation in the study area. (2) Among the constructed estimation models, the band variable combined with the Random Forest algorithm had the highest accuracy and the strongest stability. The coefficients of determination for the modeling set and validation set were 0.898 and 0.742, respectively, and the average absolute error was 82.1 g·m^-2 and 79.2 g·m^-2, respectively. The root-mean-square errors were 110.8 g·m^-2 and 132.1 g·m^-2, and the relative analysis errors were both greater than 1.8, so the model had the best fitting effect. (3) The spatial differentiation of aboveground biomass of vegetation in the study area was obvious, showing higher biomass in the oasis area and lower biomass in the desert area and a gradual decreasing trend from the inner oasis to the outer oasis. Compared with the other three machine learning algorithms, the estimation model constructed by the Random Forest algorithm had a better estimation ability and stability and could accurately estimate the aboveground biomass of the arid oasis. In general, the machine learning algorithm model based on optimal variable combinations provides a scientific basis for aboveground biomass inversion.

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.

The study of vegetation changes is of great significance for regional ecological restoration. Taking the coastal areas of China as an example, this study explored spatiotemporal changes in vegetation and their driving forces using the Normalized Difference Vegetation Index (NDVI), in conjunction with data on precipitation, nighttime lights, and other natural and anthropogenic factors. Theil-Sen Median trend analysis, Mann-Kendall test, correlation analysis, Optimal Parameter Geographic Detector (OPGD), and Hurst index were employed at multiple scales. The findings were as follows: 1) the vegetation condition in the research area was good from 2001 to 2020, with an annual average NDVI of 0.762. Among the specific regions, the highest average NDVI value was found in the Northeast China coastal area, followed by the coastal areas of the southern, eastern, and northern regions of China. The overall annual change rate of NDVI was 0.019/10 a (P<0.01). The different regions are listed from high to low according to the rising trend: the southern, northeastern, northern, and eastern coastal regions. Vegetation conditions have continuously improved in the region, and the benefits of ecological projects, such as returning farmland to forests, grasslands, and coastal shelterbelts are continuously emerging. 2) Nighttime lights had the greatest explanatory power among various factors (q=0.354). Human activities showed more significant explanatory power for NDVI than natural factors, generating a positive impact on vegetation change that gradually strengthened over time. 3) The explanatory power of the combination of two factors was greater than that of a single factor, showing both synergistic and nonlinear enhancements. Within the entire region, the most significant interaction effect was observed between soil types ∩ nighttime lights, while in specific regions, it was sunshine hours ∩ nighttime lights (Coastal Northeast China), soil types ∩ nighttime lights (Coastal North China and Coastal East China), and population density ∩ nighttime lights (Coastal South China). Although the integrated influence of natural factors and human activities has increased significantly, human factors have remained dominant. 4) The mean value of the Hurst index was 0.463. Over the next period, certain levels of reversibility in terms of vegetation changes were observed in 66.3% of the study area. The research findings provide scientific support for ecological conservation and high-quality development of China's coastal areas.

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.

Arsenic pollution in paddy fields is a serious problem in China. Pentavalent arsenic is reduced by microorganisms to highly active trivalent arsenic under flooded anaerobic conditions, becoming easy to be absorbed and accumulated by rice, thus threatening human health. On the other hand, rice production requires a large amount of nitrogen fertilizer, and the redox activity of nitrogen in paddy soil is high, which has an important impact on arsenic speciation transformation in paddy field. Based on the summary of the main processes of nitrogen cycling in paddy soils and the characteristics of functional microorganisms, arsenic speciation transformation and related functional microorganisms in paddy soils, the effects of nitrogen cycling processes in paddy soils (nitrification, denitrification, anammox, Feammox and dissimilatory nitrate reduction to ammonium, etc.) on arsenic migration and transformation in paddy soil and the key environmental factors were analyzed in depth. It was concluded that nitrification and denitrification are beneficial to arsenic adsorption and fixation, while anammox, Feammox and dissimilatory nitrate reduction to ammonium can promote the reduction and release of arsenic. In addition, denitrification can be coupled with arsenic demethylation, thus enhancing arsenic toxicity. Among them, the redox process of iron in paddy soil plays an important role, which can be used as a bridge between nitrogen cycle and arsenic migration and transformation. For example, the inhibition of iron reduction by nitrate is beneficial to arsenic adsorption; iron minerals formed by nitrate reduction coupled with iron oxidation promote arsenic adsorption and fixation; Feammox promotes iron reduction, which is beneficial to the reduction and release of adsorbed arsenic. Based on the above summary, it is suggested that the nitrogen cycle process in soil under different redox conditions and its coupling mechanism with arsenic speciation transformation, the main functional microorganisms of Feammox reaction in paddy soil and their contribution to arsenic migration and transformation, and how to directionally regulate the coupling process of nitrogen cycling and arsenic transformation are important scientific issues and main development trends in this field in the future. The solution of the above scientific problems can provide important theoretical support for the research and development of arsenic pollution control technology in paddy fields, and provide a scientific basis for rational nitrogen application in paddy fields to reduce arsenic risk in rice.

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.

Wetland ecosystems have great potential for carbon sinks. However, due to the different climatic conditions and vegetation types, soil organic carbon fractions of wetlands may differ greatly, leading to various influences of soil organic carbon in different types of wetlands affected by soil physical and chemical properties. Therefore, an in-depth understanding of the characteristics of the soil organic carbon fractions is of great significance for the development and protection of coastal wetland ecosystems. In order to explore the characteristics of the soil organic carbon fractions of the wetland, and determine the impacts of the soil physical and chemical properties on organic carbon storage in the Liao River Estuary wetland, five land cover types (Suaeda heteroptera community, reed community, bare land of Guangtan, oil well area, and farming area) were selected. Further, their soil organic carbon fractions and the basic soil physical and chemical properties were analyzed. The results showed that the soil organic carbon (SOC) content of the Liao River Estuary wetland varied significantly among different land use types. The reed community was the richest with (52.6±3.80) g∙kg⁻¹ and the bare land of the bare beach was the least, with (28.2±7.05) g∙kg⁻¹. Under plant cover, the soil had abundant carbon input, favoring soil organic carbon fixation, and this phenomenon decreased with the depth of soil layer. Light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC) and easily oxidized organic carbon (EOC) were significantly correlated with SOC content (P<0.05). The magnitude of correlation was EOC>HFOC>LFOC. The SOC content showed a significant positive correlation with pH and cation exchange, and was not significantly affected by water content and total dissolved solids. This observation may be related to the characteristics of organic carbon fractions. The soil carbon pool in the Liao River Estuary wetland had the largest proportion of HFOC and the smallest proportion of EOC, and the structure of the pool was relatively stable. The pH and cation exchange mainly affected the SOC content by influencing the accumulation rate of HFOC. Therefore, increasing the more stable HFOC storage in wetland soils can enhance the carbon sequestration capacity of wetland soils. The results of the study can provide a reference for coastal wetland ecosystem protection and carbon sink function enhancement.

Exploring the abundance of carbon cycle functional genes in soil microorganisms is important for understanding the mechanism of soil carbon cycling. However, the response characteristics of soil microbial carbon cycle functional gene abundance to different plantation types are still unclear. Based on the metagenomic sequencing data, soil physicochemical properties, and organic carbon components of soil samples from different soil layers (0-20, 20-40, 40-60 cm) under the mixed species plantation with Pinus massoniana and Erythrophleum fordii, as well as their pure plantations in south subtropical China, the differences in microbial functional gene abundance related to soil carbon cycling (carbon fixation, carbon degradation and methane metabolism) between different soil layers of different stands, and the dominant soil environmental factors were analyzed. The results showed that the abundance of soil microbial carbon fixation functional genes (rcbL, MUT and PCCA) in the Pinus massoniana stand was significantly higher than that in the other two stands. This difference was attributed to higher soil total phosphorus (TP) content and significantly lower contents of microbial biomass carbon (MBC), easily oxidizable organic carbon (EOC), particulate organic carbon (POC), and recalcitrant organic carbon (ROC) (P < 0.05). The abundance of carbon degradation functional genes (MAN2C1 and bglB) was significantly higher in the Pinus massoniana stand than that in mixed plantation. These differences were mainly affected by the low content of soil organic carbon (SOC), MBC, dissolved organic carbon (DOC), EOC and ROC in Pinus massoniana plantation. The highest abundance of methane metabolism functional genes (pmoA-amoA, pmoB-amoB and pmoC-amoC) was observed in the Pinus massoniana plantation, which was related to significant negative effects of SOC, MBC, DOC, EOC, and ROC. Additionally, the abundance of microbial carbon cycle functional genes in all three planted forests increased with increasing soil depth, mainly due to the decrease in SOC, C/N ratio, MBC, DOC, EOC and ROC contents. Overall, the Pinus massoniana stand exhibited a relatively high potential for soil microbial carbon cycling, while the soil microbial carbon cycle potential in all three stands increased with soil depth. The composition of soil organic carbon was identified as an important factor regulating the difference in functional gene abundance of soil microbial carbon cycling in these plantations.

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.

Straw return can change the content of soil microbial biomass carbon (SMBC) in farmland, and analyzing changes in SMBC content and its related influencing factors under the conditions of straw returning is pivotal for understanding the mechanism of soil nutrient turnover and carbon cycling driven by straw returning. In this study, a database of 839 groups containing SMBC contents under straw-returned and straw-not-returned conditions was established based on 68 publicly available papers published in China Knowledge and Web of Science databases from 2001 to 2022. The data was grouped by climate type, cultivation method, tillage method, type of straw, amount of nitrogen applied, and amount of returned straw. A meta-analysis was then conducted to comprehensively analyze the variation characteristics of SMBC content under the conditions of straw returning with experimental results under the conditions of no straw returning set as controls. Results showed that 1) straw return significantly increased SMBC content by 51.4% with a confidence interval from 0.373−0.654. The improvement effect on the SMBC content in different soil layers was different, and the SMBC content in shallow and deep layers increased by 47.9% and 42.7%, respectively. 2) The content of SMBC in the temperate monsoon climate zone and subtropical monsoon climate zone increased by 71.0% and 35.8%, respectively, under straw returning, but it showed a significant negative effect on SMBC content in the temperate continental climate zone, with a decrease of 35.6%. 3) The effect of rotary tillage (99.2%) on the increase of SMBC content under different tillage methods was the most obvious, which was about 2.4 times and 4 times that of conventional tillage and no-tillage. 4) The increase of SMBC content in upland was significantly higher than that in paddy field. The response of maize straw to SMBC content was the highest, with an increase of 99.5%, followed by rice straw, with an increase of 30.8%. Wheat straw was the lowest, with a decrease of 5.8%. 5) The effect of nitrogen application rate on SMBC content increased by −34.5% to 183.9%. Under nitrogen application rates of 0−100 kg•hm⁻² and 101−225 kg•hm⁻², straw returning could significantly increase SMBC content, while under the nitrogen application rate of 226−325 kg•hm⁻² and 326−425 kg•hm⁻², straw returning showed a significant negative effect on SMBC content. 6) For the amount of straw returning, when the amount of straw returning was 9000 kg•hm⁻², the increase was 44.2%, but the increase of SMBC content showed a decreasing trend with the increase of straw returning. In conclusion, straw return has a significant influence on SMBC content in Chinese farmland, and the impact extent varies under different climatic types, planting methods, tillage methods, straw types, nitrogen application rates, and straw returning amounts.