Diversity Patterns of Eukaryotic Phytoplankton in the Medog Section of the Yarlung Zangbo River.

As one of the important biodiversity conservation areas in China, the ecosystem in the lower reaches of the Yarlung Zangbo River is fragile, and is particularly sensitive to global changes. To reveal the diversity pattern of phytoplankton, the metabarcode sequencing was employed in the Medog section of the lower reaches of the Yarlung Zangbo River during autumn 2019 in present study. The phytoplankton assemblies can be significantly divided into the main stem and the tributaries; there are significant differences in the phytoplankton biomass, alpha and beta diversity between the main stem and the tributaries. While both the main stem and the tributaries are affected by dispersal limitation, the phytoplankton assemblages in the entire lower reaches are primarily influenced by heterogeneous selection. Community dissimilarity and assembly process were significantly correlated with turbidity, electrical conductivity, and nitrogen nutrition. The tributaries were the main source of the increase in phytoplankton diversity in the lower reaches of the Yarlung Zangbo River. Such diversity pattern of phytoplankton in the lower reach may be caused by the special habitat in Medog, that is, the excessive flow velocity, and the significant spatial heterogeneity in physical and chemical factors between stem and tributaries. Based on the results and conclusions obtained in present study, continuous long-term monitoring is essential to assess and quantify the impact of global changes on phytoplankton.

Mitigation Measures Could Aggravate Unbalanced Nitrogen and Phosphorus Emissions from Land-Use Activities.

Socioeconomic factors and mitigation potentials are essential drivers of the dynamics of nutrient emissions, yet these drivers are rarely examined at broad spatiotemporal scales. Here, we combine material flow analysis and geospatial analysis to examine the past and future changes of nitrogen and phosphorus emissions in China. Results show that anthropogenic nitrogen and phosphorus emissions increased by 17% and 32% during 2000-2019, respectively. Meanwhile, many regions witnessed decreasing nitrogen emissions but rising phosphorus discharged to waterbody, leading to a 20% decrease in the nitrogen/phosphorus ratio. In addition to many prominent factors like fertilizer use, the increasing impervious land area around cities is a notable factor driving the emissions, indicating the urgency to limit building expansion, especially in North China Plain and other less-developed regions. Improving land-use efficiency and consuming behaviors could reduce nitrogen and phosphorus emissions by 65-77% in 2030, but the nitrogen/phosphorus ratio will increase unintendedly due to larger reduction potentials for phosphorus, which may deteriorate the aquatic ecosystem. We highlight that nitrogen and phosphorus emissions should be reduced with coordinated but differentiated measures by prioritizing nitrogen reduction through cropland and food-system management.

Spatio-temporal evolution and the driving factors of municipal solid waste in Chinese different geographical regions between 2002 and 2020.

Urbanization and economic development have contributed to the rapid and massive generation of municipal solid waste (MSW) and significant changes in spatial patterns, which are becoming a serious pollution problem. Previously, macroscopic studies on the driving factors of MSW have been widely conducted at the national level, but the exploration of the driving factors in different geographical regions on a regional scale has not received much attention in the previous literature. This study is based on China, spatial patterns were analyzed using spatial autocorrelation and movement of center of gravity, and time series clustering was used to explore temporal trends. Subsequently, Geodector was adopted to quantify the relationship between MSW generation and driving factors. The results of the study are as follows: 1) By analyzing the spatial pattern of MSW, this study found that MSW showed a spatial pattern of high in the southeast and low in the northwest during 2002-2020, and its separating line was the same as the Hu-line; the average center of gravity of MSW generation in the past 20 years was always located in Henan Province and shifted southward by 339.7 km. 2) The local spatial autocorrelation analysis results showed that the Low-Low clusters moved from southeast to northwest from 2002 to 2020, increasing to 20 cities. High-High clusters mainly appeared in the East Coast and South Coast regions, increasing from 8 to 17 cities in the last 20 years. 3) The analysis of driving factors by Geodetector revealed that Urbanization is the most critical dimension factor influencing MSW generation, with the strongest impact on the East Coast region. The next dimension is Economy, which has the most significant impact on MSW generation in the North West region. Energy is the third dimension that influences MSW generation, with the greatest impact on the North Coast region. The results of this study reveal trends in the spatial and temporal distribution of MSW in different geographic regions of China over the past 20 years and the impact of their driving factors, which can help the Chinese government take action to control MSW in a site-specific manner.

Landsat observations of total suspended solids concentrations in the Pearl River Estuary, China, over the past 36 years.

Information on long-term trends in total suspended solids (TSS) is critical for assessing aquatic ecosystems. However, the long-term patterns of TSS concentration (CTSS) and its latent drivers have not been well investigated. In this study, we developed and validated three semi-analysis algorithms for deriving CTSS using Landsat images. Subsequently, the long-term trends in CTSS in the Pearl River Estuary (PRE) from 1987 to 2022 and the driving factors were clarified. The developed algorithms yielded excellent performance in estimating CTSS, with mean absolute percentage errors <25% and root mean square errors of <13 mg/L. Long-term Landsat observations showed an overall decreasing trend and significant spatiotemporal dynamics of the CTSS in the PRE from 1987 to 2022. The analysis of driving factors suggested that industrial sewage, cropland, forests and grasslands, and built-up land were the four potential driving forces that explained 87.81% of the long-term variation in CTSS. This study not only provides 36-year recorded datasets of CTSS in estuary water, but also offers new insights into the complex mechanisms that regulate CTSS spatiotemporal dynamics for water resource management.

Exploring China's water scarcity incorporating surface water quality and multiple existing solutions.

Water scarcity has threatened the sustainability of human life, ecosystem evolution, and socio-economic development. However, previous studies have often lacked a comprehensive consideration of the impact of water quality and existing solutions, such as inter-basin water transfer and unconventional water resources, on water scarcity. In this paper, an improved approach was proposed to quantify water scarcity levels by comprehensively considering surface water quality and multiple solutions. China's water scarcity was first assessed at a high spatial resolution on a monthly basis over the 5-year period from 2014 to 2018. Then, the driving factors including water quality and solutions were identified by a geographic detector model. Finally, an in-depth investigation was conducted to unravel the effects of water quantity solutions (i.e., inter-basin water transfer and unconventional water use), and water quality solutions (i.e., improving surface water quality) on alleviating water scarcity. Based on monthly assessments considering water quality and multiple existing solutions, the results showed that over half of the national population (∼777 million) faced water scarcity for at least one month of the year. Agricultural water use and inadequate water quality were the main driving factors responsible for China's water scarcity. Over four-fifths of the national population (∼1.10 billion) could benefit from alleviated water scarcity through a combination of water quantity and quality solutions. However, the existing solutions considered were insufficient to completely resolve water scarcity in China, especially in Northern China, persisting as a challenging issue. The results obtained from this study provided a better understanding of China's water scarcity, which could contribute to guiding future efforts aimed at alleviating water scarcity and ensuring water security in China.

Development and application of a comprehensive evaluation index system for groundwater quality evolution patterns.

In recent years, driven by rapid socio-economic development and intensified human activities, the groundwater quality has exhibited a concerning trend of degradation. The challenge lies in integrating the impacts of both natural and anthropogenic factors to establish a scientific evaluation framework for the evolution of groundwater quality. This study adopts the model of driving forces - pressures - state - impacts - responses (DPSIR) proposed by the European Environment Agency, in conjunction with the Analytic Hierarchy Process (AHP) and Information Entropy Theory (IET), and the Water Quality Index (WQI) evaluation methods, to construct an evaluation index system for groundwater quality evolution that encompasses driving forces, state, and response systems. Initially, twelve indicators relevant to groundwater quality are quantified by screening across three systems, and a functional relationship between the categorization and scoring of each indicator is established. Subsequently, the weights for each system and indicator are obtained through the AHP, and the objective weights of the indicators are determined using the IET. The scores of each indicator are then comprehensively calculated. Finally, based on the defined types of groundwater quality evolution patterns, an integrated assessment of the evolution of groundwater quality over various time periods is conducted. Taking the Shijiazhuang region as a case study and analyzing the hydrochemical data of groundwater from 1985 to 2015, the results indicate a shift in the groundwater quality evolution pattern from one dominated by natural factors to one primarily influenced by human activities (The comprehensive score of the evaluation index system has increased from 1.84 to 3.25). Among these, the application of fertilizers emerges as the most important driving factors affecting groundwater quality. Particularly, nitrate and total hardness (TH) have emerged as the most salient indicators of quality degradation, with a significant escalation in their composite scores. At the outset, nitrate registered a score of 0.408, while TH scored 0.326; yet, these values have sharply ascended to 0.716 and 0.467, respectively, by the advanced stage. The study concludes with a discussion on the accuracy, strengths, limitations, and applicability of the evaluation index system. The establishment of this evaluation framework provides a scientific basis for the management and protection of groundwater resources and serves as a reference for identifying groundwater quality evolution patterns in other regions.

Internal transformation and damming regulate the longitudinal variation of DOM bioavailability in a large river.

Understanding the spatial patterns of dissolved organic matter (DOM) and factors that influence them is crucial for maintaining river ecosystem functions and riverine health, considering the significant role of DOM in water quality and aquatic ecosystems. Nevertheless, there is limited knowledge regarding the spatial variation of DOM bioavailability and the factors driving them in large river systems. This study involved 39 sampling locations along the main stem of the Changjiang River, spanning its entire length (>5000 km) during a dry season. Spatial patterns of DOM were assessed by measurements of DOC concentrations and eight fluorescence DOM indices, namely fluorescence index (FI-A and FI-B), Trytophan/Tyrosine, Humic A, Humic C, humification indices (HIX-A and HIX-B), and Freshness index (ß/α). The results revealed that the water DOM in the main stem of the Changjiang River primarily originated from terrestrial sources. A decline in DOM bioavailability was observed from the upper to the lower basin, aligning with the carbon processing prediction rather than the river continuum concept (RCC). The pure effect of physicochemical factors (25.30%) was greater than that of geographic factors (9.40%). The internal transformation processes determined the significant longitudinal decreases of DOM bioavailability. While no significant difference in DOM bioavailability was observed between reaches before and after the dams, the construction of dams was found to improve DOM bioavailability at the subsection scale and reduce the spatial autocorrelation of DOM bioavailability across the entire basin.

Deciphering the key factors affecting pesticide residue risk in vegetable ecosystem.

Soil contamination, particularly from pesticide residues, presents a significant challenge to the sustainable development of agricultural ecosystems. Identifying the key factors influencing soil pesticide residue risk and implementing effective measures to mitigate their risks at the source are essential. Here, we collected soil samples and conducted a comprehensive survey among local farmers in the Three Gorges Reserve Area, a major agricultural production region in Southwest China. Subsequently, employing a dual analytical approach combining structural equation modeling (SEM) and random forest modeling (RFM), we examined the effects of various factors on pesticide residue accumulation in vegetable ecosystems. Our SEM analysis revealed that soil characteristics (path coefficient 0.85) and cultivation factor (path coefficient 0.84) had the most significant effect on pesticide residue risk, while the farmer factors indirectly influenced pesticide residues by impacting both cultivation factors and soil characteristics. Further exploration using RFM identified the three most influential factors contributing to pesticide residue risk as cation exchange capacity (CEC) (account for 18.84%), cultivation area (account for 14.12%), and clay content (account for 13.01%). Based on these findings, we carried out experimental trials utilizing Integrated Pest Management (IPM) technology, resulting in a significant reduction in soil pesticide residues and notable improvements in crop yields. Therefore, it is recommended that governmental efforts should prioritize enhanced training for vegetable farmers, promotion of eco-friendly plant protection methods, and regulation of agricultural environments to ensure sustainable development.

Recent advance of microbial mercury methylation in the environment.

Methylmercury formation is mainly driven by microbial-mediated process. The mechanism of microbial mercury methylation has become a crucial research topic for understanding methylation in the environment. Pioneering studies of microbial mercury methylation are focusing on functional strain isolation, microbial community composition characterization, and mechanism elucidation in various environments. Therefore, the functional genes of microbial mercury methylation, global isolations of Hg methylation strains, and their methylation potential were systematically analyzed, and methylators in typical environments were extensively reviewed. The main drivers (key physicochemical factors and microbiota) of microbial mercury methylation were summarized and discussed. Though significant progress on the mechanism of the Hg microbial methylation has been explored in recent decade, it is still limited in several aspects, including (1) molecular biology techniques for identifying methylators; (2) characterization methods for mercury methylation potential; and (3) complex environmental properties (environmental factors, complex communities, etc.). Accordingly, strategies for studying the Hg microbial methylation mechanism were proposed. These strategies include the following: (1) the development of new molecular biology methods to characterize methylation potential; (2) treating the environment as a micro-ecosystem and studying them from a holistic perspective to clearly understand mercury methylation; (3) a more reasonable and sensitive inhibition test needs to be considered. KEY POINTS: • Global Hg microbial methylation is phylogenetically and functionally discussed. • The main drivers of microbial methylation are compared in various condition. • Future study of Hg microbial methylation is proposed.

Identification of factors driving the spatial distribution of molybdenum (Mo) in topsoil in the Longitudinal Range-Gorge Region of Southwestern China using the Geodetector model.

As a key component of plant nitrogen-fixing enzymes and a variety of human coenzyme factors, molybdenum (Mo) plays an essential role in supporting both plant growth and human health. Soil is a key medium for the cycling of Mo in the biosphere. However, the driving anthropogenic and natural factors governing the spatial distribution of Mo in soil and their interactions are not well understood. To determine the factors that affect the spatial patterns of Mo in topsoil, 6980 samples were collected from the Longitudinal Range-Gorge Region (Linshui County, Sichuan Province, China). In this area, tall mountains are adjacent to deep valleys. Topsoil with enriched Mo is mostly distributed in mountainous areas. The most important factors influencing Mo in topsoil are soil parent materials (q = 0.482), altitude (q = 0.256), and soil type (q = 0.259). There are synergistic effects among the various driving factors [q(X1 âˆ© X2) > Max[q(X1), q(X2)]]. The Geodetector model was used to validate the magnitude of the interaction effects. The contribution to interacting factors is nonlinearly enhanced when the contribution of a single factor was low (any two factors of aspect, road distance, land use type, and S). The contribution to interacting factors is enhanced bidirectionally when the contribution of a single factor was high (any two factors of altitude, soil type, soil parent material, OM, and TFe2O3). When the contribution of one factor is high and the other is low, the contributing to interacting factors is mostly enhanced bidirectionally and a few are nonlinearly enhanced.

Spatial and temporal differentiation and its driving factors of air quality in the economic circle of Shandong Province during 2013-2020.

As the negative repercussions of environmental devastation, such as air quality decline and air pollution, become more apparent, environmental consciousness is growing across the world, forcing nations to take steps to mitigate the damage. China pledged to achieve air quality improvement goal to combat global environment issue, yet the spatial-temporal differentiation and its driving factors of environment-meteorology-economic index for air quality are not fully analysed. To promote regional collaborative control of air pollution and achieve sustainable urban development, spatial and temporal different and its driving factors of air quality in Shandong Province during 2013-2020. Results revealed that concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), and carbon monoxide (CO-95per) exhibited decreasing trend (SO2 concentrations decreasing 84 % and CO-95per concentrations decreasing 90 %). Air quality was improved from inland areas to coastal areas. Pollutant indicators of SO2, NO2, PM10, PM2.5, and CO-95per demonstrated significant positive correlation (P < 0.05). Air temperature and precipitation are significantly negatively correlated with concentrations of SO2, NO2, PM10, PM2.5, and CO-95per but significantly positively correlated with ozone (O3-8 h). SO2, NO2, PM2.5, PM10, CO-95per, and proportion of days with heavy pollution are strongly positively correlated with proportion of secondary industry but strongly negatively correlated with proportion of tertiary industry and volume of household waste. Except for O3-8 h, pollutant index of Provincial Capital Economic Circle (PCEC) and Southern Shandong Economic Circle (SSEC) has significant negative correlation (P < 0.05) with regional gross domestic product and investment in environmental protection; however, investment in environmental protection of Eastern Shandong Economic Circle (ESEC) has no significant correlation with air pollution index. There was significant negative correlation between vegetable sowing area and SSEC pollutant index. The relationship between pollution emission and investment in environmental protection has shifted from high pollution-low investment to low pollution-low investment in PCEC, ESEC and SSEC, and the inflection point was in 2020 for PCEC, 2019 for ESEC, and 2020 for SSEC. Those results provide empirical evidence and theoretical support for the improvement of regional air quality, aiming to achieve high-quality development. According to these findings, it has been found that meteorological elements, pollutant emission, socio-economic factors and agricultural data affect air quality. Those results could provide meaningful and significant supporting for synergistic regulation of diverse pollutants.

The relative impacts of vegetation, topography and weather on landscape patterns of burn severity in subtropical forests of southern China.

Understanding the landscape patterns of burn severity is vital for managing fire-prone ecosystems. Relatively limited research has been done about fire and burn severity patterns in subtropical forests. Here, we derived the pre-fire forest type data from a global land-cover product at 30 m resolution based on time-series Landsat imageries. Using Landsat 8 OLI remote sensing imagery and field-based composite burn index (CBI), this study spatially mapped the burn severity of 27 forest fires in the subtropical forest ecosystems in southern China from 2017 to 2021. The landscape pattern of patches with different burn severity was quantified using landscape indices. In addition, factors influencing the patterns of burn severity across the landscape were determined using the Geodetector model. Burn severity of patches varied significantly over space. High burn severity was common in forest patches with low fragmentation, low patch density, and regular shape. In contrast, moderate and low burn severity was prevalent in patches with smaller patch size, high patch density, and complex shapes. Extensively burned forest patches were located at higher elevations, while more fragmented patches were located in gently sloping areas. Topographic factors were the most significant factors influencing variances in burn severity across the forest patches, followed by weather conditions. Compared to low elevation areas, vegetation types at the high elevation areas (dominated by Masson pine) are more singular, with higher fuel loads, thus resulting in a more regularly-shaped distribution of highly severe burning patches. A detailed understanding of burn severity patterns and driving factors in a landscape can help develop sustainable forest management and restoration strategies. Practically, fire managers should conduct mechanical fuel treatments or thinning of forests at high-elevation areas to reduce the potential of severe fire behavior and the continuity of fire spread.

Decoupling relationship between logistics growth and carbon emissions and driving factors in Chongqing: A novel decomposition framework.

A comprehensive understanding of the logistics decoupling status and driving factors is of immense theoretical and practical importance for rationally formulating low-carbon logistics policies and accelerating the realization of high-quality development. Present study introduces the logarithmic mean Divisia index method (LMDI) decomposition technique into Tapio index model, extends traditional decoupling model, and establishes a new analytical framework for the decoupling relationship between logistics growth and carbon emissions. Using long-term data from Chongqing (1997-2021), this study investigated the Chongqing logistics decoupling relationship and driving factors. The study found the following: (1) Chongqing logistics carbon emissions show phased changes and face greater pressure to reduce emissions. (2) The decoupling status of logistics growth and carbon emissions is predominantly expansive and weak decoupling, with an overall evolutionary trend of "expansive decoupling-weak decoupling-strong decoupling. The average decoupling index in 2013-2021 was 0.5523, indicating a decreasing trend; however, there was still a large gap in realizing a strong decoupling goal. (3) The energy consumption intensity effect facilitates logistics carbon decoupling, the economic scale effect has a strong inhibiting effect, and the industrial structure effect and transportation intensity effect are staged. Finally, targeted policy recommendations are proposed to expedite logistics carbon emissions decoupling in Chongqing.

Global trade-driven transfer of atmospheric polycyclic aromatic hydrocarbon emissions and associated human inhalation exposure risk.

Polycyclic aromatic hydrocarbons (PAHs) are of significant public concern because of their toxicity and long-range transport potential. Extensive studies have been conducted to explore the source-receptor relationships of PAHs via atmospheric transport. However, the transfer of trade-driven regional and global PAHs is poorly understood. This study estimated the virtual PAHs emission transfer embodied in global trade from 2004 to 2014 and simulated the impact of international trade on global contamination and associated human inhalation exposure risk of PAHs. Results show that trade-driven PAHs flowed primarily from developed to less-developed regions, particularly in those regions with intensive heavy industries and transportation. As the result, international trade resulted in an increasing risk of lung cancer induced by exposure to PAHs (27.8% in China, 14.7% in India, and 11.3% in Southeast Asia). In contrast, we found decreasing risks of PAHs-induced lung cancer in Western Europe (63.2%) and the United States (45.9%) in 2004. Our findings indicate that final demand and emission intensity are the key driving factors contributing to rising and falling consumption-based PAHs emissions and related health risk respectively. The results could provide a useful reference for global collaboration in the reduction of PAHs pollution and related health risks.

Characterization of driving factors for the long-term succession of bloom-forming cyanobacterial genera in Lake Erhai, southwest China.

Cyanobacterial blooms pose a global environmental concern, with various genera contributing to their formation. The harmfulness of cyanobacterial blooms varies depending on the specific genus, yet the factors triggering their formation remain incompletely understood. This study conducted qPCR of sediment DNA in Lake Erhai to reconstruct the historical succession of three common bloom-forming cyanobacterial genera (i.e., Microcystis, Dolichospermum, and Aphanizomenon). The driving factors and their corresponding thresholds were identified, and human activities related to driving factors were evaluated. The results revealed two successions in the past century. The first succession transitioned from Aphanizomenon (1902-1978) to Microcystis and Dolichospermum (1978-1999), driven by TN:TP and TP. The second succession shifted from Microcystis and Dolichospermum (1978-1999) to Microcystis (1999-2010), driven by TP, TN:TP, and temperature. The thresholds of TP and TN:TP for the Microcystis bloom were 0.023 mg/L and 17, respectively. TN:TP was significantly influenced by domestic pollution and crop farming in both successions, while TP was significantly impacted by domestic pollution in the first succession and by pollution from crop and dairy farming in the second succession. These results shed light on the underlying mechanism responsible for the blooms of various cyanobacterial genera and could serve as a valuable reference for effectively preventing and controlling nutrient input in the watershed.

Dynamic monitoring of aboveground biomass in inner Mongolia grasslands over the past 23 Years using GEE and analysis of its driving forces.

Aboveground biomass (AGB) in grasslands directly reflects the net primary productivity, making it a sensitive indicator of grassland resource quality and ecological degradation. Accurately estimating AGB over large regions to reveal long-term AGB evolution trends remains a formidable challenge. In this study, we divided Inner Mongolia Autonomous Region (IMAR) grasslands into three study regions based on their spatial distribution of grassland types. We combined remote sensing data with ground-based sample data collected over the past 19 years from 6114 field plots using the Google Earth Engine platform. We constructed random forest (RF) and traditional regression AGB inversion models for each region and selected the best-performing model through accuracy assessment to estimate IMAR grassland AGB for the period 2000-2022. We also examined the trends in AGB changes and identified the driving forces affecting IMAR grasslands through the application of Theil-Sen estimation, Mann-Kendall trend analysis, and the Geodetector model. The main findings are as follows: (1) Compared with the univariate parametric traditional regression model, the AGB monitoring accuracy of the multivariate non-parametric RF model in the three study regions increased by 5.94%, 5.08% and 19.14%, respectively. (2) The average AGB per unit area of IMAR grasslands from 2000 to 2022 was 731.41 kg/hm2, with alpine meadow having the highest average AGB (1271.70 kg/hm2) and temperate grassland desertification having the lowest (469.06 kg/hm2). IMAR grasslands exhibited an overall increasing trend in AGB over the past 23 years (6.01 kg/hm2•yr), with the increasing trend covering 83.52% of the grassland area and the decreasing trend covering 16.48%. (3) Spatially, IMAR grassland AGB showed a gradual decline from northeast to southwest and exhibited an increasing trend with increasing longitude (45.423 kg/hm2 per degree) and latitude (71.9 kg/hm2 per degree). (4) Meteorological factors were the most significant factors affecting IMAR grassland AGB, with precipitation (five-year average q value of 0.61) being the most prominent. In the western part of IMAR, where precipitation is consistently limited throughout the year, the primary drivers of influence were human activities, with particular emphasis on the number of livestock (with a five-year average q value of 0.44). It is evident that reducing human activity disturbance and pressure in fragile grassland areas or implementing near-natural restoration measures will be beneficial for the sustainable development of grassland ecosystems. The results of this research hold substantial reference importance for the protection and restoration of grasslands, the supervision and administration of grassland resources, as well as the development of policies related to grassland management.

Combating land degradation through human efforts: Ongoing challenges for sustainable development of global drylands.

Drylands, as highly vulnerable ecosystems, support environmental functions and human well-being. Nevertheless, widespread land degradation and desertification present significant global and regional environmental challenges, with limited consensus on their area and degree. This study used time-series vegetation productivity and meteorological data from 2000 to 2020 to quantify global land degradation trends and driving factors in drylands. The results show a notable restoration of land degradation in drylands worldwide, with the area of improved land exceeding the degraded area by 1.4 times, although the threat of degradation persists. India and China emerge as pioneers in effective land improvement strategies, offering valuable experiences for other regions. Combined effects, as quantitatively distinguished by our established model, dominate the degradation and improvement processes. Notably, human activities play a decisive role in influencing land degradation trends, with the potential for either exacerbation or reversal. This study provides new perspectives on environmental health and human activities from global and regional observations. Finally, our research provides scientific support for desertification control and contributes to the overall advancement of the SDGs globally.

Response of phytoplankton community to dissolved organic matter composition and lake trophic state.

Human activities, intensified urbanization and climate changes altered source and quantity of dissolved organic matter (DOM), complicating its interaction with phytoplankton in aquatic ecosystems. However, relationship between DOM and phytoplankton in urban lakes strongly disturbed by human activities was still unclear. Thus, a whole-year sampling campaign was conducted in the Tangxun Lake, China's largest urban lake, to reveal the interaction between DOM and phytoplankton. Results indicated that trophic state in the Tangxun Lake varied from mesotrophic to moderately eutrophic. Parallel factor analysis method combined with excitation-emission matrix fluorescence spectroscopy revealed that DOM in the Tangxun Lake consisted of three components, two protein-like components (C1, C3), and one humic-like component (C2). Protein-like components occupied 80% ± 11% of total CDOM pool, mainly due to urbanization driving DOM to be more protein-like, less humic-like. Besides, DOM in the Tangxun Lake was mainly autochthonous input and more recently formed. Furthermore, a total of 129 phytoplankton species were identified, belonging to 78 genera and 7 phyla. Tangxun Lake's phytoplankton community structure was dominated by the Chlorophyta-Bacillariophyta-Cyanophyta type. The temporal succession of phytoplankton varied significantly. It was found that the abundance of Cryptophyta and Cyanophyta were predominant in the mesotrophic state, while Cyanophyta and Bacillariophyta were prevailing in the eutrophic and middle-eutrophic states. As for the interaction between DOM and phytoplankton, results demonstrated that phytoplankton biomass was significantly positively correlated with a (254), a proxy of DOM abundance. Moreover, phytoplankton abundance and biomass significantly positively correlated with autochthonous and freshly released DOM, indicating that the more autochthonous and freshly released DOM, the higher phytoplankton abundance and biomass. Overall, this study provides profound environmental implications for aquatic ecosystem management, especially those strongly affected by human activities.

Effects of understory intercropping with salt-tolerant legumes on soil organic carbon pool in coastal saline-alkali land.

Phytoremediation through understory intercropping with salt-tolerant legumes (forest-green manure composite patterns) efficiently and sustainably enhances saline-alkali soils, while significantly improving the stability of monoculture forest ecosystems and the efficacy of soil upgrades. However, exactly how forest-green manure patterns regulate the dynamics of the soil organic carbon (SOC) pool and related mechanisms remain unclear. For this study, a pure forest was used as the control, and three leguminous herbaceous plants (M. sativa, S. cannabina, and C. pallida) were intercropped under two forest stand types (T. hybrid 'Zhongshanshan' and C. illinoensis). The variable characteristics and control factors of SOC and its components under different patterns were elucidated by analyzing the soil physical and chemical properties, enzyme activities, and microbial communities. The results revealed that the composite pattern improved soil salinization and increased the activities of ß-1,4-glucosidase, polyphenol oxidase, peroxidase (PER), invertase (INV), and urease, as well as the carbon pool management index and the proportion of active organic carbon. At the T. hybrid 'Zhongshanshan' experimental site, planting M. sativa effectively increased the total carbon (TC) content. The ammonium nitrogen, soil moisture content, total phosphorus, alkaline phosphatase, PER, and polyphenol oxidase were the primary driving factors that affected the SOC pool. At the C. illinoensis experimental site, S. cannabina planting was observed to increase the TC content, with the TC, exchangeable Na+, ß-1,4-N-acetylglucosaminidase, and INV being the main driving factors that impacted the SOC pool. The composite pattern can indirectly influence the SOC pool by altering the soil properties to regulate the microbial community. Further, it was found that soil inorganic carbon (SIC) was the main contributor to increasing the soil carbon pool following the short-term planting of legumes; thus, there may have been a transfer process that occurred from the SOC to SIC. Our study suggests that the forest-green manure pattern has more positive effects on improving soil quality and the carbon pool in saline-alkali land.

Navigating the path to dual carbon goals: Understanding the driving forces of energy transition welfare performance.

China's double carbon target aims to improve human well-being and sustainable development. Energy transformation welfare performance (ETWP) is the efficiency of energy transition (ET) in enhancing human well-being. ETWP considers both human well-being and sustainable development. Research on its driving force is helpful in achieving the double carbon goal. Thus, this paper used Logarithmic Mean Divisia Index Model, Fixed Panel Regression Model and Grey Relational Analysis Model to analyze China's ETWP from 2006 to 2022 and predicted ETWP of 31 provinces from 2023 to 2030. The results showed that: (1) ETWP had two rising periods in 2006-2014 and 2015-2022. (2) The government's rationalization policy on energy and environment and technological innovation ability were fundamental driving forces for improving ETWP. (3) There were obvious spatial and temporal distinctions in ETWP, and it would bring out different degrees in most areas. Thus, ET should be promoted by improving the ecological environment and resource utilization efficiency; The importance of the role of scientific and technological innovation and policies should be focused on in promoting ETWP; ET policies based on local developments should be formulated and the energy structure should be changed.