Earthworms are known to play an important role in improving soil, decomposing agricultural litter, and enhancing soil fertility and crop yield. The acute toxicity of 17 herbicides to Eisenia fetida was determined by a contact filter paper toxicity bioassay and an artificial soil toxicity bioassay. Results of 48 h by the contact filter paper toxicity bioassay, metamifop was high toxicity to E. fetida with LC₅₀ (median lethal concentration) value of 7.6 μg∙cm^-2; pretilachlor, haloxyfop-R-methyl, and bentazone were moderate toxicity to E. fetida with LC₅₀ values of 10.7, 12.7, and 61.3 μg∙cm^-2, respectively; quinclorac, MCPA-Na, topramezone, glufosinate ammonium, nicosulfuron, and bispyribac-sodium were low toxicity to E. fetida with LC₅₀ values of 143.0, 198.2, 211.1, 466.9, 433.7, and 649.2 μg∙cm^-2, respectively; pyrazosulfuron-ethyl, penoxsulam, pyribenzoxim, cyhalofop-butyl, fluoroglycofen, pendimethalin, and mesotrione were slight toxicity to E. fetida with LC₅₀ values greater than 1000 μg∙cm^-2. Results of 14 d by the artificial soil toxicity bioassay, haloxyfop-R-methyl showed the highest toxicity to E. fetida with LC₅₀ value of 148.9 mg∙kg^-1; followed by pretilachlor, MCPA-Na, pendimethalin, and metamifop, the LC₅₀ values were 211.5, 335.0, 342.4, and 345.7 mg∙kg^-1, respectively; the other tested herbicides were low toxicity to E. fetida with LC₅₀ values greater than 500 mg∙kg^-1. According to the guidelines of environmental safety evaluation for chemical pesticides, the 17 herbicides determined by an artificial soil toxicity bioassay were low toxicity to E. fetida. The results of this study can provide new data information for assessing the ecological risk of herbicides to earthworm, and also provide technical guidance for the safe use of herbicides in agricultural production.

Based on the cloud platform of Google Earth Engine (GEE), Landsat surface reflectance data of Loess Plateau from 1986 to 2021 were de-clouding and fused. The Normalized Difference Vegetation Index (NDVI) was calculated, and fractional vegetation coverage (FVC) was estimated using the pixel dichotomy model. On this basis, with the help of trend analysis, partial correlation analysis and residual analysis, the temporal and spatial variations of FVC and its influencing factors in the Loess Plateau in different time periods (1986-2021, 1986-1999 and 2000-2021) were analyzed. The results show that (1) in terms of time, FVC on the Loess Plateau increased significantly from 1986 to 2021 (Trend=0.0044 a^-1, P<0.01). In different time periods, the increasing trend from 2000 to 2021 (Trend=0.0058 a^-1, P<0.01) was faster than that from 1986 to 1999 (Trend=0.0038 a^-1, P<0.01). The FVC of all vegetation types on the Loess Plateau showed a significant increasing trend (P<0.01), among them, the grassland had the largest increasing trend (Trend=0.0066 a^-1, P<0.01). (2) Spatially, FVC decreased from southeast to northwest in the Loess Plateau. The FVC of the total area showed significant improvement in 1986-2021, 1986-1999 and 2000-2021 by 53.65%, 18.38% and 48.12%, respectively. (3) Elevation and Trend of topographic factors had significant effects on FVC. The value of FVC first decreased, then rose and finally decreased with the elevation, with the maximum value (0.7790) between 3000 m and 3500 m. FVC increased with the increase of Trend, with the maximum value (0.7025) appeared in the range of 25°-45°. The proportion of middle and high coverage and high coverage increased with the increase of Trend, in which the area proportion was the largest in the range of 15°-25° (73.93%). (4) The biased relationship between FVC and annual precipitation, annual mean temperature and solar radiation in the Loess Plateau from 1986 to 2021 were 0.239, 0.093 and -0.006, respectively. The proportions of pixels with significant positive correlations (P<0.05) accounted for 48.50%, 22.51% and 5.96% of the total area. The results of residual analysis showed that human activities was the main driving factor of vegetation dynamic change on the Loess Plateau, and the proportion of pixels that played a positive role was 73.20%.

Grassland is the largest terrestrial ecosystem, which possesses extremely important production and ecological functions. Long-term overutilization and climate change, however, have contributed to degradations of grassland ecosystems worldwide. The natural restoration of degraded grasslands takes long time, and manipulating practices could be indispensable to accelerate the restoration. Although grassland ecological restorations have been studied for several decades in China, the phenomenon of degradation-restoration-re-degradation-re-restoration is common, and grassland degradation has not been comprehensively improved due to the ecological functions have not been paid enough attention. Lately, ecological priority and green development are emphasized, and more attention has been paid to grassland protection and ecological restoration. Restoration of degraded grassland ecosystems is a major problem and daunting task to be solved urgently in China. To provide scientific references for the ecological restoration of degraded grasslands, we reviewed the researches of grassland ecological restoration, as well as the main practical and policy measures. Restoration effects, limiting factors and existing shortcomings of different practical measures (no-tillage sowing, rational grazing, artificial pasture establishment, fence enclosure, tillage and fertilization) were also assessed. On these bases, research directions and suggestions for the grassland ecological restoration in the future were put forth: (1) To establish a modern grass husbandry system and management pattern to fundamentally solve the contradiction between grass and livestock is the prime way to tackle the grassland degradation and ecological restoration; (2) To improve the grassland degradation classification and grading system to provide theoretical bases for ecological restoration; (3) To strengthen the development and utilization of native grass germplasms and soil microorganisms to provide material support for ecological restoration; (4) To break through the theoretical and technical bottlenecks to restore the grasslands full of poisonous weeds; (5) To build a region-classification-grade theoretical and technical system and evaluation system of ecological restoration. Grassland ecological restoration is a complicated, transdisciplinary and systematic engineering, and the key is to strengthen multi-field cooperation.

Microplastics are widely detected in the environment, and microplastics entering the environment generally undergo slow and complex aging processes, affecting their interaction with other pollutants in the environment. In this paper, the aging methods, physical and chemical properties of aged microplastics, pollutant adsorption capacity and interaction mechanism were summarized. There are many aging methods for microplastics, mainly involving physical, chemical and biological methods, and different methods have their own characteristics and applicability. The microplastic surface would become rougher after aging, which results in the increase of the surface area. Meanwhile, ultraviolet and natural aging could increase the oxygen-containing functional groups on the surface and promote its adsorption to other pollutants by hydrophobic action, electrostatic action, complexation, hydrogen bond, van der Waals’ force, and π-π interaction. In view of the shortcomings of the aging of microplastics and their interaction with pollutants, some suggestions were proposed to provide support for microplastic aging and its environmental impacts research, such as microplastic aging under complex conditions and its influence on pollutants adsorption, adsorption mechanism of aged microplastic on heavy metal-organic composite pollution, aging of microplastics in living organisms and its biological toxicity, the release of plastics additives during the process of microplastics aging and its interaction with pollutants and that of aged microplastics with dissolved organic matter and minerals.

The normalized difference vegetation index (NDVI) can effectively reflect the growth of surface vegetation. Studying the driving factors of the spatial distribution of the NDVI is helpful for regional ecological environment protection. Based on the MODIS-NDVI data and the data of eight natural factors in the source region of the Yellow River during 2000-2018, this study used trend analyses to examine the temporal and spatial variation characteristics of the NDVI in the source region of the Yellow River. The spatial heterogeneity and natural driving factors were analyzed by geographical detectors. The study showed that the overall vegetation coverage in the source region of the Yellow River was high. In 2018, the NDVI of 74% of the area was greater than 0.6. The NDVI was comparatively high in the southeast and low in the northwest, and showed an increase in the north and a decrease in the middle. The mean NDVI value had generally increased during 2000-2018, although the trend was not obvious, and the growth rate was 0.013/10 a. Except for the increase in the area of high vegetation coverage, the area of other grades of vegetation coverage decreased. The influence of annual precipitation on the spatial distribution of NDVI was the largest, reaching 0.602. In addition, the influence of elevation was 0.385 and the influence of average annual temperature was 0.296, reflecting the vegetation coverage condition in the source region of the Yellow River. The influence of other natural factors was comparatively smaller. The influence of natural factors on vegetation NDVI showed bivariate enhancement and nonlinear enhancement relationships, so that single factors with smaller impact, such as landform type, slope, and aspect, also had a great influence on vegetation NDVI. The influence of the interaction between annual precipitation and other factors was generally high. In particular, the influence of the interaction between annual precipitation and elevation was the greatest, reaching 0.682. This study showed that the vegetation coverage of the source region of the Yellow River had not increased significantly during 2000-2018. The annual precipitation was a dominant factor affecting the spatial distribution of the NDVI, and the influence of natural factors on vegetation NDVI was interactive. This study contributes to a better understanding of the vegetation coverage in the source region of the Yellow River and the influencing mechanism of vegetation growth.

Quercus is the largest tree species in China with a great potential for carbon sequestration. This study examined the carbon stock and distribution pattern of the natural secondary Quercus mongolica forest under different management modes to provide theoretical bases for evaluating its carbon sink potential in China. To this end, the study employed the random layout and typical sampling method and collected both plant and soil samples for forest ecosystem carbon stock evaluation under three distinctive Q. mongolica forest stands with different management intensities within the Danqinghe Forest Station in Harbin, Heilongjiang province, northeast of China. These three Q. mongolica forest stands were (1) target tree nurture management (40%, 45% and 70% of nurture intensity), (2) comprehensive tree nurture management (45% and 40% of nurture intensity), and (3) undisturbed tree nurture management. The results showed that after 17 years of management practices, the carbon stock of secondary Q. mongolica forest under the undisturbed tree nurture management (279.01 t∙hm^-2) was significantly higher (P<0.05) than that under the other two tree nurture management modes, while the differences between comprehensive tree nurture (218.81 t∙hm^-2) and target tree nurture (183.01 t∙hm^-2) were not significant. The soil layer accounted for the largest share of the stand carbon stock (82.71%-89.56%), followed by the tree layer (9.53%-16.41%), the shrub layer, the herb layer, and the litter layer. The latter three combined only accounted for 1%. Carbon stock of the tree layer varied significantly (P<0.05) among the three management modes. The order of the carbon stock size was: no-disturbance tree nurture (45.78 t∙hm^-2)>comprehensive tree nurture (27.17 t∙hm^-2)>target tree nurture (17.44 t∙hm^-2) (P<0.05). The carbon stock of the shrub layer was significantly larger than that of target tree nurture under comprehensive tree nurture (P<0.05), and the carbon stock of the litter layer was significantly larger than that of comprehensive tree nurture and target tree nurture under no-disturbance tree nurture (P<0.05), while no differences were observed among these three management modes for the herb layer carbon stock. Soil carbon stock under no-disturbance management was significantly higher than that under target tree nurture (P<0.05), but similar with that under comprehensive tree nurture. In conclusion, from the perspective of enhancing the carbon sequestration potential and sustainable management, it is therefore recommended to reduce the management intensity of similar forest stands and optimize management technology measures to achieve multi-objective management of carbon sequestration and improve the quality of forest stands.

The carbon sequestration ability of vegetation is very sensitive to meteorological conditions, so it’s important to investigate the meteorological contribution to carbon sequestration variation for enhancing the ecological environment and achieving the goal of carbon neutralization. Using net primary productivity data and ground meteorological observation data, this study examined the spatiotemporal distribution variation of vegetation carbon sequestration and its meteorological contribution, using correlation analysis and model simulation. The results showed that the carbon sequestration ability of vegetation was strong in most areas of Guangdong. The order of regions based on their average carbon sequestration over the years in a descending order was as follows: North Guangdong, West Guangdong, East Guangdong, and the Pearl River Delta. The carbon sequestration had a fluctuating upward trend in Guangdong Province from 2001 to 2020. The annual average carbon sequestration of vegetation ranged from 838.7 g∙m^-2 to 1070.8 g∙m^-2, and the 20-year average carbon sequestration of vegetation was 981.2 g∙m^-2. In terms of the seasonal variation, the carbon sequestration of vegetation had the largest value in summer and the smallest in winter. The interannual fluctuation of vegetation carbon sequestration in winter and spring was large, while that in summer and autumn was gentle. For the monthly variation, the lowest carbon sequestration value appeared in January and the highest in July. With the quantitative simulation of Integrated Biosphere Simulator (IBIS) model, it was found that the impact of meteorological factors on vegetation carbon sequestration was positively driven, and the meteorological contribution to vegetation carbon sequestration accounted for 48.4% in recent 20 years. Among these factors, temperature had the strongest impact on vegetation carbon sequestration, followed by precipitation and sunshine. The vegetation carbon sequestration had no lag in the response to sunshine and temperature, and had one to two months lag in the response to precipitation.

The ecological security pattern is the basis for ensuring regional ecological security and an important means for human beings to maintain green, healthy, and sustainable development. Under the background of increasingly prominent global ecological problems, the ecological security pattern has become a hot area of ecosystem research. Strengthening the study of ecological security pattern is of great significance for maintaining the integrity of the ecosystem structure and function, protecting biodiversity, ensuring regional ecological security, and improving human well-being. Based on “conceptual analyses, fundamental framework, research progress and prospects”, this article comprehensively and systematically reviewed research results on ecological security patterns at home and abroad. The following conclusions were drawn after summarizing the research methods, scales, and contents in the literature: (1) The basic research framework of "source identification-resistance surface construction-corridor extraction" needs to be developed; (2) the identification of ecological source areas lacks a unified scientific standard, and the relationship between supply and demand of ecosystem services has not been considered; (3) the extraction method of ecological corridor needs to be further optimized; (4) there is a lack of consideration of the interrelationship between geospatial linkage and ecosystem functions; (5) The research on the coupling relationship between natural ecosystems and socio-economic systems is relatively weak. Future research may focus on the following aspects: (1) integrated research of multi-model, multi-method, and multi-technology; (2) quantitative research on dynamic consideration of ecological safety standards; (3) realistic implementation research of the game of interests of all parties; (4) research on ecological security prediction, early warning, and regulation management; (5) research on the construction of ecological security patterns serving national strategies.

Microplastics can interact with organic pollutants and change their toxic effects on organisms. The existing literature mainly summarizes research on one single aspect, such as the adsorption/desorption of organic pollutants by microplastics or the combined toxicity of organic pollutants and microplastics. However, a comprehensive review of both issues is absent. This paper summarized the effects of microplastic characteristics, environmental factors, and types/properties of organic pollutants on adsorption-desorption. The molecular structure, functional groups, and crystallinity of microplastics affected their adsorption and desorption of organic pollutants. The capacity of microplastics to adsorb/desorb organic pollutants increased with the decrease of the particle size. The adsorption/desorption ability of microplastics was enhanced by the aging process for hydrophilic organic pollutants, but decreased for hydrophobic organic pollutants. With the increase of temperature, pH and salinity, the adsorption capacity of microplastics towards organic pollutants improved first and then decreased. Organic pollutants with benzene ring structure and strong hydrophobicity were easily adsorbed on the surface of microplastics. In addition, this paper reviewed the joint toxicity of microplastic and organic pollutants for organisms at individual, cellular and molecular levels. Microplastics combined with organic pollutants showed antagonistic or synergistic effects on the growth/reproduction, immune system, reactive oxygen species, and gene expression of aquatic organisms. The carrier function of microplastics could promote the absorption and transport of organic pollutants by plants, leading to synergistic toxic effects on plant growth, photosynthesis, and the defense system. The extracellular secretion, cell growth, structure and function of microorganisms changed in the presence of the combined effects of microplastics and organic pollutants. Microplastics modified (enhanced or weakened) the enrichment of organic pollutants in earthworms, and thus induced abnormal gene expression, oxidative stress response, and the changes of metabolites. In the future, the adsorption-desorption behavior of microplastics on organic pollutants should be analyzed based on the actual environmental conditions. Additionally, the combined toxic effects of microplastic and organic pollutants should be studied at the gene, protein, and metabolic levels. Finally, the contributions of plastic additives to toxic effects should be further examined.

Net primary productivity (NPP) is the basis for characterizing the material and energy cycle of the ecosystem, which is one of the important components of regional and global carbon cycle. In order to reveal the spatiotemporal change characteristics and driving mechanism of NPP in China from 2001 to 2020, based on MOD17A3HGF data products, the spatiotemporal change and future development trend of NPP in China were analyzed by Sen trend analysis, Mann-Kendall significance test and Hurst index. The relative roles of climate change and human activities in the process of NPP change were quantitatively analyzed by using correlation and residual analysis methods. The results showed that (1) China’s NPP presented a spatial distribution pattern of high in the southeast and low in the northwest, showing a fluctuating upward trend in time, with an upward rate of 2.86 g·m^-2·a^-1. The spatial change remained unchanged. The area with a significant increase in NPP was significantly larger than the area with a significant decrease. In the future, 84.38% of China's regional NPP will continue to increase or change from a decreasing to an increasing trend. (2) NPP was positively correlated with precipitation and temperature as a whole, of which precipitation had a more significant impact on NPP. The areas with significant positive correlations between NPP and precipitation were mainly distributed in the north of the Yangtze River. The areas with significant positive correlations with temperature were mainly distributed in the central and north of the Qinghai Tibet Plateau, the southeast of the Yunnan Guizhou Plateau, the southeast coastal area and the south of Shandong. (3) Both climate change and human activities played an important role in the NPP improvement areas, but there were significant spatial differences in their relative roles in NPP improvement areas. The vegetation improvement areas dominated by climate change were mainly concentrated in the northeast, north China, Sichuan Basin and the middle and lower reaches of the Yangtze River plain, while the vegetation improvement areas dominated by human activities were mainly concentrated in central, southwest and northwest China. The impacts of climate change and human activities on vegetation degradation were relatively consistent in spatial distribution. The impacts of climate change on NPP degradation areas were slight, but human activities were the main factors causing NPP degradation.

Qinghai Lake is an important barrier for maintaining ecological security in the northeast of Qinghai-Tibet Plateau, and its water level changes are an indicator and regulator of changes in the climate and ecological environment of Qinghai-Tibet Plateau. This paper used the water level observation data of Xiashe Hydrological Station from 1961 to 2020 to analyze the characteristics of the water level change of Qinghai Lake. Based on the meteorological observation data of Qinghai Lake basin, it revealed the cause of the water level change, and combined the meteorological influence factors during the water level rise period and the forecast data of future climate change to simulate and predict the water level change of Qinghai Lake from 2021 to 2050, aiming to provide scientific basis and reference for the ecological environment protection planning and management of the lake area. The main conclusions of the study were as follows, (1) the average annual water level of Qinghai Lake from 1961 to 2020 was 3194.36 m. From 1961 to 2004, the annual average water level of Qinghai Lake showed a significant downward trend, with a decline rate of 0.76 m/10 a. Since 2005, the annual average water level of Qinghai Lake had stopped falling and rebounded, with an increase rate of 2.01 m/10 a, and the average water level in 2020 would reach 3196.34 m. (2) The water level change was mainly controlled by the alternating wet and dry climate factors, and the amount of precipitation was the most important factor, the continuous rise of water levels since 2005 was mainly due to the simultaneous increase in summer rainfall and rainfall intensity under global warming conditions. Surface runoff and groundwater recharge also played a role. In addition, the active environmental protection activities of human beings were also very beneficial to the rise of the water level of Qinghai Lake. (3) The forecast under the scenario of moderate greenhouse gas emissions showed that the water level of Qinghai Lake would continue to increase from 2021 to 2050, and the water level of Qinghai Lake would increase by 1.63 m from 2021 to 2030, 1.85 m from 2031 to 2040, and 2.00 m from 2041 to 2050. The water level of Qinghai Lake would reach 3200 m in 2041 and 3201.82 m in 2050.

The quantitative assessment of net ecosystem productivity (NEP) and its influencing factors is helpful to further understand the regional carbon cycle and its driving mechanism. As one of the sensitive regions to climate change, the study on temporal and spatial variation characteristics of NEP in the Yellow River Basin and its climate driving factors is of great significance for clarifying the characteristics of terrestrial carbon sink pattern in northern China. Therefore, based on estimation model of NEP, the spatiotemporal evolution characteristics of NEP in the Yellow River Basin and its driving mechanisms from 2000 to 2020 were analyzed by trend analysis, correlation analysis, cluster analysis and other methods in this study. Results were shown as follows: (1) the annual average NEP in the Yellow River Basin was 92.7 g·m^-2, showing carbon sink as a whole. For the spatial distribution, the NEP in the Yellow River Basin showed an increasing trend from the west to the east. There was an obvious spatial aggregation effect on NEP in the Yellow River Basin, in which the high-value and low-value aggregation areas accounted for 32.6% and 41.7% of the basin area, respectively. (2) The NEP in the Yellow River Basin had generally increased since 2000, with an average annual increase of 4.7 g·m^-2. In particular, 62.4% of the regions had a significant increase in NEP, and the carbon sequestration capacity of vegetation had been significantly improved. In different regions, the increase rate of NEP in the middle reaches of the Yellow River was the largest, with an average annual increase of 7.8 g·m^-2. For different vegetation types, the NEP of evergreen forest increased most significantly, and the proportion of area with a significant increasing trend was the highest, reaching 82.8%. (3) From the perspective of future trends, the average Hurst index of NEP in the Yellow River Basin was 0.74, which was characterized as strong sustainability. The NEP showed a significant increase trend, and the proportion of the area that would maintain strong sustainability in the future would reach 56.2%, indicating that the carbon sequestration capacity in most areas of the Yellow River Basin would continue to increase in the future. (4) From the climate correlation analysis, NEP in the Yellow River Basin was positively correlated with precipitation and negatively correlated with sunshine hours. However, the impact of temperature on NEP was not significant. In terms of the influence range of key climatic factors, the precipitation had the largest influence area (70%), followed by sunshine (19.3%), and temperature (10.7%). Therefore, the precipitation was considered to be the dominant climatic factor determining the spatial distribution of NEP in the Yellow River Basin.

Exploring vegetation change and its response to climate change and human activities is very important for scientific and efficient management of regional ecosystems. Based on Normalized Difference Vegetation Index (NDVI), Standardized Precipitation Evapotranspiration Index (SPEI), annual precipitation and annual air temperature data, the spatiotemporal variation characteristics of NDVI from 1998 to 2018 and its driving forces in Songliao river basin were analyzed using Theil-Sen Median trend analysis, Mann-Kendall test, and residual analysis. The results showed that the annual NDVI from 1998 to 2018 in the river basin ranged from 0.72 to 0.82, showing an extremely significant improvement with an overall increase rate of 0.0041/a. Especially during 2000-2005 and 2009-2014, the increase rate was relatively high, with the values of 0.0137/a and 0.0092/a, respectively. The spatial variation rate per decade ranged from -0.44 to 0.44. The vegetation in 92.85% of the regions showed an improvement trend, while only 7.15% showed a degradation trend. The degradation areas were mainly distributed in the west of the Greater Khingan Mountains, Bohai Bay and the capital cities of the provinces in Northeast China. The impacts of climatic change on NDVI ranged from -1.4×10^-3/a to 1.6×10^-3/a, while the impacts of human activities ranged from -3.6×10^-3/a to 4.0×10^-3/a. 3.77% and 62.84% of the basin with significantly improved vegetation were driven by climate change and human activities, respectively. The contribution rate of human activities was more than 70% in 79.40% of the basin, the regions where climate change had a negative impact on NDVI were mainly distributed in the left bank of Hailar River and the southwest of the Greater Khingan Mountains, and the regions where human activities had a negative impact were mainly distributed in the northeast urban agglomeration and the west of the Greater Khingan Mountains. For different land use types, the contribution rate of human activities to NDVI was significantly higher than that of climate change. The contribution rate of human activities to forest vegetation change was the largest, followed by cropland, unutilized land and grassland in the vegetation improvement area, and the contribution rate to grassland vegetation change was the largest, followed by unutilized land, forest, and Cropland. It is suggested that more attention should be paid to the protection of grassland and unutilized land in the high-quality development strategy planning of Northeast China.

Vegetation change is an important indicator of ecological environment monitoring. Using NDVI (Normal Difference Vegetation Index) to monitor the dynamics of vegetation change and study its influencing factors is of great significance to the sustainable development of the ecological environment. We select the SPOT/VEGETATION NDVI dataset of the Bohai coastal from 2000 to 2018, and adopted correlation analysis, stability evaluation, trend analysis to analyze the dynamic changes of regional vegetation and its responses to climate changes and LUCC at the pixel and regional scales. The results show that: (1) On the regional scale, the vegetation coverage of the Bohai coastal region improved significantly from 2000 to 2018, along with the average value of GS_NDVI (Growing Season NDVI) increased from 0.6267 to 0.6755. (2) On the pixel scale, the number of pixels showing an improvement trend accounted for 62.23%, and 24.62% of the pixels showed degradation trend. Furthermore, the northern cities of the study area showed a more obvious improvement trend and higher stability. Central cities (mainly including Tianjin and Tangshan), inshore and urban expansion regions have obvious degradation trends and poor stability. Moreover, the nearer the distance to the coast line, the weaker of the stability was. (3) The influences of climate on the GS_NDVI variation were limited (the number of pixels with significant correlation was less than 10%), and the correlation between precipitation and GS_NDVI was much closer than temperature. (4) The spatial pattern of GS_NDVI in the study area was mainly determined by the land use pattern. Urban expansion was a key factor for vegetation degradation, and LUCC driven by human activities was the main factor leading to the degradation and unstable changes of GS_NDVI.

Planting pattern is the key factor affecting the carbon sink and economic benefits of farmland ecosystem. To optimize reginal cropping systems, develop low-carbon green agriculture, and ensure sustainable agriculture development, it is of great importance to clarify the carbon sink characteristics and economic benefits under different planting patterns. In this study, a field experiment was conducted from 2020 to 2021 in southern Anhui, China, including four planting patterns: single-cropping rice, tobacco-rice rotation, rice-wheat rotation, and ratoon rice. Life cycle assessment was used to evaluate the net carbon sink and economic benefits. In addition, the carbon footprint compositions and influencing factors of different cropping patterns and crops were investigated. The results showed that, (1) the economic net income followed the order of tobacco-rice rotation>ratoon rice>rice-wheat rotation> single-cropping rice. The high output value of tobacco contributed to the high income of tobacco-rice rotation. The highest rice yield was found in the ratoon rice cultivation, in which the total grain yield of the first and regeneration seasons was 12921.5 kg∙hm^-2. (2) The net carbon sink followed the order of rice-wheat rotation>ratoon rice>single-cropping rice>tobacco-rice rotation. Compared with the rice-wheat rotation, N₂O emission and total carbon emission were significantly decreased by 37.2% and 9.2%, respectively, in ratoon rice. The CH₄ and N₂O emission accounted for 54.5% and 18.0% of carbon footprint in ratoon rice. (3) CH₄ emission was reduced through controlling farmland water, increasing fertilizer use efficiency, and leaving piles appropriately for ratoon rice, which is vital to control carbon emissions. The carbon footprint of flue-cured tobacco (Nicotiana tabacum L.) was mainly consisted of N₂O, chemical fertilizer, and agricultural film, and each of them accounted for more than 20% of the total emissions. In addition, the proportion of labor force (accounted for 11.7%) and fuel oil (accounted for 12.7%) in flue-cured tobacco planting were much higher than those in rice and wheat. (4) The tobacco-rice rotation obtained higher economic benefits and the high harvest of both tobacco leaves and grain yield. However, the carbon sink was negative in tobacco-rice rotation. It is necessary to study how to mechanization production and energy saving and consumption reduction of tobacco leaf baking. The ratoon rice obtained high grain yield in rice, and was low in input cost and carbon emissions, consistent with the national carbon peak and neutrality goals. In conclusion, this study quantitatively evaluated the carbon sink and economic benefits of different planting patterns, and provided a technical model and theoretical basis for energy saving, emission reduction and low-carbon green agriculture.

Since land use change is an important representation of human-nature interactions, it is of great significance to study the spatial-temporal pattern and driving factors of land use change for the planning and implementation of the national strategy of ecological protection and high-quality development in the Yellow River Basin. With the data on land use of the Yellow River basin in 2000, 2010 and 2020, the characteristics and driving factors of land-use change were explored by means of the spatial analysis and mathematical statistics at the different scales. The results show that (1) the multi-year average proportions of grassland and farmland in the Yellow River basin were 47.9%±0.38% and 26.5%±0.69% respectively. Grassland was widely distributed in the middle and upper reaches, while farmland was concentrated in the lower reaches, indicating their responsibilities of ensuring national ecological security and food security in their corresponding regions. (2) The intensity of land use in 2010-2020 was much higher than that in 2000-2010 with the area of land use change and comprehensive land use dynamic degree increased by about 8 and 15 times, respectively. (3) Land use changes in the Yellow River Basin from 2000 to 2020 were characterized by the increase in urban land, grasslands and forests and decrease in farmland, that is, the urban land was expanded by 1.08×10⁴ km² with 58% of newly-increased area converted from farmland which was mainly occurred in the urban agglomerations in the middle and lower reaches of the Yellow River. Grasslands and forests were increased by 0.91×10⁴ km² with 75% of newly-increased area converted from farmland, which mainly occurred in the source area, as well as Qinghai and Gansu, the upstream areas of the Yellow River. The farmland was reduced by 1.30×10⁴ km² with 48% and 37% of them converted into urban land and grasslands, which mainly occurred in the plain areas of the middle and lower reaches of the Yellow River. (4) The land use changes in the Yellow River Basin were mainly driven by the factors, such as climate change, socio-economic development and policy implementation. Comprehensively driven by the warming and wetting climate, ecological protection and restoration policies and project implementation, the areas of forest and grass and watershed wetlands have increased and the quality of the ecosystem has also improved. However, under the background of increasing population scale and rapid economic development, the agricultural land has been seriously occupied for construction land. Therefore, the conflict between urbanization and ecological protection is becoming more prominent.

Quantitative assessment of the impact of climate change and human activities on terrestrial ecosystem carbon cycle is of great significance for understanding of vegetation change driving mechanism, ecological construction and protection. Based on the actual net primary productivity (NPP) calculated by the model Biome-BGC from 2000 to 2019 and the potential net primary productivity calculated by the climate model, this paper quantitatively analyzed the impact of climate change and human activities on vegetation ecosystem in Shaanxi Province. The results showed that the change of vegetation NPP in Shaanxi Province was mainly driven by climate, accounting for 11.96% of the total area. Climate superimposed with the influence of human activities which played a more important role, accounting for 86.93% of the total area. The increase of vegetation NPP in Shaanxi Province accounted for 98.06% of the total area. Among this, 11.93% of the total area was driven by climate factors, which mainly distributed in the agricultural areas of Guanzhong area and Hanzhong Basin. 86.13% of the total area was driven by human activities, which mainly distributed in northern and southern Shaanxi. These results indicated that the ecological construction projects such as returning farmland to forest and natural forest protection have made remarkable achievements in the two regions. The reduced area accounts for 0.83% of the total area. Among this, 0.03% of the total area was driven by climate factors and distributed throughout the province, while 0.8% of the total area caused by human activities distributed in the surrounding areas of cities and towns and was mainly attributed to urban construction. There was no change in NPP in 1.11% of the total area. In conclusion, the changes of vegetation NPP in Shaanxi Province were mainly affected by climate and human activities, with the latter being the main driving force.

In forest soils, bacterial communities are shaped by nutrient availability and biotic interactions. In turn, dynamics of soil bacterial communities contribute to essential soil processes involved in nutrients cycling and productivity maintaining. Knowledge of change in soil bacterial communities with forest succession process is limited. In this study, we analyzed soil bacterial community composition, structure and diversity using Illumina Miseq platform in different successional forests in Dinghushan National Nature Reserve. The successional forests included a pine forest (PF), a pine and broadleaved mixed forest (MF), and a monsoon-evergreen broadleaved forest (BF), representing early-, middle-, and advanced-successional stages, respectively, in southern China. Results showed that soil nutrient condition was improved along the successional process as indicated by the increased soil organic carbon, total nitrogen, total phosphorus, available phosphorus and soil water content from PF to BF. Proteobacteria, Actinobacteria and Acidobacteria were the dominant soil bacteria phyla in these forests. Soil bacterial community structure changed significantly along forest succession process (P<0.05). The relative abundances of Proteobacteria and Actinobacteria were relatively comparable in forests at different successional stages. The relative abundances of Acidobacteria and Planctomycetes were significantly increased from PF to BF (P<0.05), whereas that of Chloroflexi showed a decreasing tend. The abundance of k-strategy bacteria (e.g., Acidobacteria) was significantly higher in advanced-successional forest than that in early-successional forest (P<0.05), while the abundance of r-strategy bacteria (e.g., Proteobacteria) did not vary significantly in these successional forests. Soil bacteria diversity index, indicated by Shannon index, increased from early- to mid-successional forests and decreased from mid- to advanced-successional forest, resulting in the highest Shannon index in MF compared to PF and BF. Soil bacteria richness index, indicated by Chao1 index, increased from early- to advanced-successional forests. It was found that soil organic carbon, total nitrogen, soil water content, pH and nitrate were the dominant factors affecting the soil bacterial community in these successional forests. Our results suggest that soil dominant bacterial community may shift from r-strategists to k-strategists with successional process from pine forest to evergreen broadleaved forest in Dinghushan National Nature Reserve.

The state-owned forest regions are the key regions to implement carbon neutralization in China. Accurate estimations of carbon storage and carbon sequestration potential of forest vegetation are of great significance for making strategies to cope with climate change and for coordinating regional eco-economy-social development. Based on the data of forest resource survey type II, the carbon storage and density of forest vegetation in the key state-owned forest region of Daxing’ anling, Heilongjiang Province were estimated by using the volume-biomass method on the basis of tree species (groups) and age groups. Based on the space-time substitution method, the carbon sequestration potential of forest vegetation was evaluated according to the ecological regionalization of forest vegetation and the type of zonality climax community. The results showed that (1) the total carbon storage and average carbon density of forest vegetation were 2.7246×10⁸ Mg and 39.46 Mg∙hm^-2, respectively. The proportion of carbon storage in arbor forest was 99.93%, and its average carbon density was 4.00 times of that in shrub wood and 3.72 times of that in open forest. (2) The carbon storage and carbon density of forest vegetation varied greatly in different regions. The regions of Xinlin Forestry Bureau (3.4497×10⁷ Mg) and Panzhong National Nature Reserve (1.0936×10⁶ Mg) had the highest and lowest carbon storage, respectively. The regions with the highest and lowest carbon densities were Shuanghe National Nature Reserve (59.68 Mg∙hm^-2) and Pan National Nature Reserve (22.11 Mg∙hm^-2). The establishment of nature reserves and reasonable and ordered human intervention both played positive roles in improving the carbon sequestration capacity of forest vegetation. (3) The proportion of carbon storage in Larix gmelini forest was nearly half of the total carbon storage in the research area, and the average carbon density of Pinus sylvestris var. mongolica forest was much higher than that of other forest types. (4) In general, forests for timber and for seed production had the largest carbon storage and average carbon density. (5) The half-mature forest is the age group with the largest carbon storage, and the average carbon density rose with the increase of age. (6) The carbon sequestration potential in total was 1.9367×10⁸ Mg, mainly owing to the growth of existing forest vegetation. To sum up, it is recommended to strengthen the theoretical research and technological research on the protection and restoration of natural secondary forests, to improve the quality and stability of forest ecosystems, to enhance their capacity to sequester carbon and increase sink, and to innovate the management of forest vegetation carbon sink, as well as to broaden the value realization path of ecological products in the forest carbon sink.

The study of the structural characteristics of desert plant diversity in Hexi Corridor and its response to environmental factors is conducive to protecting plant diversity in fragile arid areas and maintaining the stability of desert ecosystem. This paper explored the changing rules of α and β diversity of desert plants in Hexi Corridor and their responses to environmental factors by setting up sample plots along the decreasing natural precipitation gradients from southeast to northwest in Hexi Corridor. The results showed that (1) Margalef richness index (R) ranged from 1.22 to 8.22, Simpson dominance index (D) ranged from 0.25 to 0.97, Shannon-Wiener diversity index (H') ranged from 0.05 to 1.52, and Pielou evenness index (E) ranged from 0.08 to 0.90, indicating that desert plant species in Hexi Corridor are small in number and unevenly distributed, and a few species show a great advantage. (2) In terms of plant β diversity, Bray-Curtis distance index (d_BC) was generally high, the average value of Bray-Curtis distance index in the east and middle of Hexi corridor was 0.91, and that in the west was 0.78. The average value of the Bray-Curtis distance index between the eastern and central sample plots (the average annual precipitation was more than 50 mm) and the western sample plots (the average annual precipitation was about 50 mm) was mostly 1.00, indicating that the similarity of desert plants between the eastern and western regions is extremely low. (3) Spearman analysis and redundancy analysis of α diversity and environmental factors showed that α diversity was affected by soil water content, soil nitrogen and phosphorus, specific humidity, average annual wind speed, average mean precipitation and short wave radiation, among which specific humidity and average annual wind speed had higher explanation rates, which were 35.4% and 19.8% respectively. (4) Mantel test of β diversity and environmental factors showed that β diversity is significantly related to soil, climate, latitude and longitude. Compared with other environmental factors, the specific humidity and average mean precipitation had higher correlation coefficients, which were 0.40 and 0.36 respectively. To sum up, the plant diversity in Hexi Corridor desert is under a combined influence of water, average annual wind speed, average mean temperature, total radiation intensity and soil nutrients, with water playing the major role.