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Wuliangsu Lake is the largest lake wetland in the Yellow River basin, it is the Northern Sand Belt of China, which is essential to maintaining ecological security in northern China and the areas downstream. With the increasing environmental problems, the basin has become a sensitive and complex geographical unit, and a better understanding of the level of ecosystem health in the basin is helpful for policymakers in developing measures for ecological restoration and eco-space management. In this study, we proposed an improved VORS model containing ecosystem vigor, organization, resilience and services to assess the ecosystem health in the Wuliangsu Lake Basin in 2000, 2011, and 2022. To improve spatial precision, the study area was partitioned into grids measuring 2 km × 2 km each. The results indicated that: (1) the ecosystem health showed a slight increase trend, which indicated by the increase level grids reached 94 % in 2000–2022 change. (2) The reduction in vegetation cover decreased the ecosystem vigor, which was indicated by the weak level increased from 22 % in 2000 to 73 % in 2022. Ecosystem structure becomes more complex enhanced the ecosystem organization, the value increased from 0.3 to 0.6 in 2000 to 0.6–0.8 in 2022. Ecosystem resilience slightly declined in 2011 and 2022, ecosystem services were relatively stable but were dominated by weak levels. (3) The majority land use type in the study area is farmland, and the ecosystem vigor decreases as the area of grassland decreases to farmland in these 22 years. The ecosystem’s structure was enhanced and the land use structure was progressively brought into balance. Changes in all four parameters of ecosystem health assessment are related to land use, and changes in ecosystem health are likewise related to land use changes. The improved VORS model constructed for the Wuliangsu Lake Basin objectively reflect the basin’s state of ecosystem health, and provide a reference for ecological restoration and basin regional planning.

Peatland degradation causes a number of environmental problems ranging from greenhouse gas (GHG) emissions to subsidence and ecosystem loss. Degraded peatlands, covering just 0.3 % of Earth’s land area (500,000 km2), disproportionately contribute 5 % of GHG emissions, exacerbating the climate crisis. Once degraded, restoring peatland ecosystem functions often presents a considerable challenge because degradation affects several interconnected components in peatlands: the peat body, hydrology, and vegetation. The planning and implementation of effective peatland restoration strategies requires the accurate mapping of degradation. This review examines how remote sensing has been used to examine the components of peatland degradation. A conceptual 3D space was created using the three components of peat, hydrology, and vegetation. Within this three-dimensional space, five groups of studies were identified, representing each one of the three dimensions individually, or addressing two or three of them simultaneously. Of 115 relevant articles, 54 % solely addressed vegetation degradation, 18 % evaluated two dimensions equally, while just 10 % of all studies examined all three dimensions. These results highlight a lack of remote sensing-based research that considers all aspects of peatland degradation and their interdependence simultaneously. By synthesizing our findings into three descriptive peatland degradation scenarios (a boreal landscape, a temperate large peatland complex and a temperate small raised bog), we present rapid and efficient methods and resources for a more holistic approach to degradation mapping and monitoring. Consequently, such comprehensive assessments integrating different historical and current remote sensing data should be carried out more frequently. They allow the visualization of ecological consequences of peatland degradation and promote peatland restoration in all parts of these tripartite ecosystems.

Diverse land use patterns exhibit varying effects on water quality across different seasons and spatial scales. However, current studies on the correlation between land use and water quality in single small-scale basins no longer meet the needs of regional coordinated development. Simultaneous comparative analysis of multiple large-scale basins can promote water environmental protection in different basins, but there is currently limited relevant research. In this study, the data from 86 sampling points across seven major river basins in China were analyzed. Multivariate statistical analysis and the redundancy analysis (RDA) were employed to investigate the influence of land use patterns on water quality at different seasons and spatial scales. The results indicated notable differences in water quality across various seasons and locations. Except for higher pH and permanganate index (COD) concentrations in the wet season in the Songhua River Basin and higher COD concentrations in the Pearl River Basin, the concentrations of all parameters in other basins are higher in the dry season. PH and COD exhibited considerable spatial variations within basins, while dissolved oxygen (DO) and ammonia nitrogen (NH4+-N) showed smaller variations. RDA showed that land use had a more pronounced effect on water quality during the dry season in the Yangtze, Liao and Pearl River Basins, while the impact was greater in the wet season in the four basins of the Yellow, Huai, Hai and Songhua River Basins. At the spatial scale, the 2000 m buffer zone had the most significant impact within the Yangtze, Hai and Liao River Basins, while the 1000 m buffer zone had the greatest impact in the Huai and Pearl River Basins. For the Yellow and Songhua River Basins, the buffer zone was 500 m during the wet season and 1000 m and 2000 m during the dry season, respectively. The research findings can offer a scientific foundation for the development of basin-specific land management policies and water quality protection measures in different basins from a multi-scale perspective.

China has implemented policies to promote fuel ethanol development and achieve its dual-carbon goal. Under the policy, the significant modifications will occur in the allocation of land use resources within ethanol raw material cultivation regions. In the process of land use change, ensuring food provision and protecting the regional carbon sink are also crucial for sustainable development. This study explores carbon distribution in the Guiping section of the Yujiang River basin, where bioethanol raw materials are cultivated. Using the CLUE-S model, a multi-objective model prioritizing economic and ecological benefits is constructed. Four scenarios (i.e., the natural expansion scenario (NES); the food conservation scenario (FCS); the bioethanol feedstock conservation scenario (BCS), and the carbon sinks conservation scenario (CCS) are simulated, predicting land resource distribution by 2030. The total carbon sink decreased by 285.60 gC·m−2·a−1, showing a seasonal trend of higher levels in summer and lower levels in winter. In 2030, the total carbon sink decreased in the NES scenario, while it increased in the FCS and BCS scenarios. The CCS scenario had the largest increase, approximately 582.27 × 103 tC. These simulated scenarios consider various economic and environmental factors, providing a scientific basis for the efficient allocation of regional land resources. They also have significant implications for local energy, economic, and environmentally sustainable development, as well as promoting the achievement of carbon neutrality.

High-intensity land development has led to numerous ecological problems, severely threatening regional sustainable development. Resilience is key to maintaining regional sustainable development. This study focuses on the Taohe River Basin and constructs an ecological resilience evaluation model based on the framework of ecosystem adaptability, ecosystem resistance, and ecosystem recovery from the perspective of resilient ecosystem functions. Using software such as InVEST and Fragstats, the study assesses the spatiotemporal changes in ecological resilience in the Taohe River Basin. Based on the ecological resilience pattern, ecological sources were identified, resistance surfaces were constructed, and ecological corridors were extracted, thereby establishing an ecological resilience security pattern for the Taohe River Basin. During the study period, the level of ecological resilience in the Taohe River Basin showed a gradual upward trend. A total of 33 ecological source areas were identified, accounting for 27.57 % of the total area of the Taohe River Basin. Seventy ecological corridors were identified, with a total length of 6478.63 km and an average length of 92.55 km. Combining the topography, ecological background conditions, and current urban development status of the Taohe River Basin, an ecological security pattern of “two screens, two corridors, five areas, and multiple points” was constructed, along with corresponding optimization suggestions. The research results are of great significance for optimizing spatial layout, maintaining regional ecological security, and promoting regional integrated development. Additionally, they provide new ideas for assessing regional ecological resilience.

Purpose: To effectively operate river water quality under current fourth-phase Total Maximum Daily Load (TMDL) management system, we built a machine learning model that predicts whether water quality goals are achieved for the entire Nakdong river watershed in Korea. Methods: First, to consider the effects of land use type on the runoff characteristics of pollutants, K-means clustering was used to classify the watershed into three areas: agricultural areas, forest areas, and urban areas. Next, we developed a machine learning model to predict the achievement of BOD, TP, and TOC water quality goals in the different rainfall seasons. At this time, the Isolated Forest and ADASYN machine learning techniques were used to preprocess the training data. Finally, SHAP was used to find the factors with the greatest effects on the achievement of water quality goals. Results: This model’s average prediction results for TP, BOD, and TOC showed accuracy ranging from 0.6 to 1.0. Meteorological factors, particularly monthly precipitation and average temperature, were found to highly influence the model predictions for all land use types. In the landscape metrics, ED showed a high level of importance in all land use types. CONTAG was the main factor in agricultural areas; ED, LPI, CONTAG, COHESION and SHDI were the main factors in forest areas; and PD, ED, SHDI, and COHESION were the main factors in urban areas. Conclusion: The monthly precipitation and average temperature significantly affected whether the TMDL water quality goals were achieved in all sub watersheds, and the landscape metrics calculated as highly influenced factors differed depending on the land use type. Therefore, customized watershed management according to land use characteristics is necessary. These results provide valuable ideas for land use managers and landscape planners to achieve water quality goals through the management of non-point source pollution.

Oasis ecosystems in dryland regions take on crucial significance in human survival and development since the quality of these regions that are characterized by ecological environments directly affects the well-being and socio-economic progress of their residents. Accordingly, it is of utmost importance to evaluate changes in ecological environment quality (EEQ) and gain insights into how land use transformation affects the local ecological condition, thus guiding the sustainable development of the dryland oasis. In this study, we evaluated the EEQ of the Middle Heihe River (MHR) from 1985 to 2020 by constructing the dryland oasis ecological index (DOEI) through the Google Earth Engine (GEE) platform. Moreover, we investigated how land use transformation influenced the EEQ of the MHR. Results suggested that (1) the DOEI can effectively capture the comprehensive dynamics of long-term EEQ changes in MHR, providing a more accurate representation of land type characteristics. (2) The EEQ in MHR generally exhibited a trend of initial improvement, followed by deterioration. The desert-oasis transition zone acts as the most significant area of EEQ changes in the MHR. The mutual transformation among cropland, grassland and desert is the primary factor for EEQ in the MHR. (3) The expansion of cropland in the MHR pronouncedly affected the EEQ. However, this continuous expansion may impose greater stress on water resources while potentially threatening ecological degradation in the lower reaches of the river basin. The DOEI built through the GEE platform is capable of indicating the spatiotemporal status of the EEQ in the dryland oasis, which holds significant implications for studying the interaction between human activities and EEQ in the dryland oasis.

Ecosystems are vulnerable to accelerated climate change, population pressure, and urbanization, so ecological vulnerability assessments and impact analyses are essential if regional development is to be managed sustainably. This study develops a novel assessment framework based on resilience-sensitivity. Various techniques—including the landscape index, the ecological elasticity limit model, and the soil erosion equation—are incorporated to examine spatiotemporal variation characteristics across diverse ecological systems of China’s Jiangsu province through the decade 2010–2020, to reveal mechanisms by which various factors influence vulnerability. We arrived at a stable average yearly ecological vulnerability index value of 0.56–0.57, and found high vulnerability concentrated in cities and townships, areas along the Yangtze River, and the province’s northern coast. Results also show that vulnerability is affected more by ecological sensitivity than by ecological resilience. Stepping up from one ecological sensitivity class to another has the greatest impact on the probability of an upward step in ecological vulnerability class, accounting for 16.2% of the total area undergoing such a change. Urbanization rates and differences in human-induced landscape composition were the main factors, and their cumulative contribution to ecological vulnerability variations ranged from 59.3% to 65.8%. We found our proposed framework capable of enhancing the strength and applicability of ecological vulnerability assessments, specifically in areas with extensive river and lake networks. The framework could be used in assessments throughout China, and very likely beyond.

A detailed exploration of the nexus between land use change (LUC) and ecosystem service value (ESV) at the urban level is crucial for fostering high-quality urban economic growth alongside the sustainable management of land resources. This study focuses on Jiangsu Province, employing an enhanced and refined ESV assessment model to perform a dynamic examination of the spatial and temporal variations in land use and ESV across the region from 2000 to 2020. Additionally, it delves into the intricate coupled coordination dynamics between land use intensity and ESV by developing a coupled coordination model. Key findings include: (1) Jiangsu Province experienced notable land use transformations over the two decades, with a marked reduction in cropland and a significant expansion of construction sites being the most prominent shifts. (2) The ESV in Jiangsu Province has exhibited fluctuating trends over the past 20 years, with water bodies and agricultural lands serving as the cornerstone for the province's ESV. Areas with high ESV are predominantly located around the Yangtze River's water bodies, along the coastline, and around lakes and radiate outward from these aquatic centers. (3) The coupling between LUC and ESV in Jiangsu Province has been upward, albeit with pronounced city disparities. This coupling displays distinct spatial patterns, characterized by higher levels in the east and lower levels in the west, as well as higher levels in the north and lower levels in the south. The outcomes of this analysis offer valuable insights and policy recommendations for enhancing land use planning, refining land use configurations, and promoting the synergistic development of land use and ecosystem service functions in Jiangsu Province.

We compared the structural and functional attributes of Neotropical macroinvertebrate communities between two natural, two agricultural, and two urban streams. We quantified food resource availability, community structure, secondary production, and consumer–resource interaction strength, attributing them to environmental characteristics. In agricultural streams, secondary production was significantly reduced compared to natural streams, reaching the lowest reported estimates for tropical streams (0.08–0.69 g DW·m−2·year−1 in agricultural streams vs. 1.1–15.8 g DW·m−2·year−1 in natural streams). This decline was primarily attributed to habitat degradation caused by siltation and channelization, alongside stronger top-down pressure in agricultural streams. Conversely, urban streams exhibited a substantial increase in secondary production, ranking among the highest estimates for tropical streams (25.6–191.2 g DW·m−2·year−1). The high secondary production in urban streams was primarily due to substantial increases in fine benthic organic matter, likely originating from poorly treated wastewater. Along with higher resource availability, we also observed a lack of, or insufficient, top-down control by macroinvertebrate predators or fish, which may have promoted higher secondary production in urban streams. This study is the first to quantify land use impacts on energy flows in stream communities in a region particularly threatened by land use change. Future studies should address multifunctional responses to land use changes in both the tropical and temperate realms to shed new light on how stream ecosystem functions in different biomes respond to human impacts. Our findings highlight the urgent need for effective management strategies tailored to address the environmental characteristics of tropical stream ecosystems.

As soil fungi are major players in the carbon accumulation process, the two main fungal degraders in topsoil, Ascomycetes and Basidiomycetes, were investigated as indicators of land use effectiveness in increasing soil carbon accumulation and soil function. The study focused on the soil organic carbon content increase in a 20-year short rotation forest cycle with broadleaf woody plantations compared to a nearby arable cropping system. Total fungi, Ascomycota and Basidiomycota, were quantified in terms of DNA copy number, with specific probes using SYBR® Green I dye on the QuantStudio™ 3D digital PCR system (dPCR). Previously, next generation sequencing analysis using a general primer confirmed that Ascomycota and Basidiomycota were the most represented phyla and that fungal community composition significantly differed between treatments. A range of key soil enzyme activities for the C-cycle were also assessed. Total organic carbon content (TOC), microbial biomass in term of dsDNA and enzyme activities significantly increased in woody plantations compared to arable soil. The TOC increase differed significantly also between wood species, Salix and Robina gave the greatest increase (+30 and 20 % respectively), followed by Populus (+12), microbial biomass highly correlated with TOC showing the same trend. Total fungi, Ascomycota and Basidiomycota increased significantly in three woody plantations compared to the arable soil system. Ascomycota in the woody plantations increased two to four times (average 3144 n copies µl−1 of DNA) compared to the arable soil (1419 n copies µl−1); Basidiomycota were almost absent in arable soil (av. 94n copies µl−1) and increased five to six times in woody plantations (av. 490 n copies µl−1). Total fungi and ascomycetes correlated strongly with microbial biomass and TOC, whereas basidiomycetes did not. These findings showed that Ascomycota represent the largest portion of fungi in agricultural soils even after a 20-years short rotation forest cycle and they can be taken as indicators of carbon accumulation processes. Therefore, this study suggests that joining the Ascomycetes quantity in the topsoil to the Ascomycota:Basidiomycota ratio seems a good option when setting regional strategies for improving C accrual in farmland with the short-term afforestation.

Ecosystems in inland river basins are crucial for maintaining socioeconomic stability in arid regions. As a result, an essential tool for tracking ecosystem changes is the measurement of ecosystem service value (ESV). Using land use changes in the Aksu River Basin (ARB) from 2002 to 2021 as an example, the response of land use variations to the ESV in the basin was examined. Using the equivalency coefficients of ecosystem service values adapted for the specific Chinese context, nine different types of ecosystem service values were assessed using the Getis-Ord Gi* statistical technique and Spearman rank correlation analysis. The findings revealed that (1) the pattern of land use change in the ARB has changed significantly over the past 20 years, with grassland and unused land being the dominant land types in the ARB, both accounting for more than 74 % of the total area of the study area. Changes in dynamics were more pronounced for each land use type, with all land use types exhibiting positive dynamics, except for grassland and unused land, which exhibited negative dynamics. (2) The total ESV in the study area increased from 48.06 billion yuan in 2002 to 52.59 billion yuan in 2011 and then decreased to 49.37 billion yuan in 2021. Grassland was the main ecological land type, and the total ESV showed an increasing and then a decreasing trend. (3) There was clear geographical and temporal variation in the ESV distribution, with hotspots primarily located in the northern section of the ARB and coldspots primarily dispersed in the east-central region. (4) Each land use type's sensitivity index was less than 1, showing that the ecological value coefficient (VC) had a small impact on ESV. Policymakers should be aware of the significant effects that land use changes have on ESV as a result, and they should take steps to modify the land use structure, particularly to encourage ecological goals. The above discussion will support the sustainable development of ARB in a variety of ways.

Carbon-use efficiency (CUE) and water-use efficiency (WUE) are critical parameters for evaluating the exchange of carbon and water in ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activity to CUE and WUE is essential in the context of global warming and rapid land use transformation. This study assessed spatiotemporal variations in CUE and WUE and evaluated their interconnections with climate factors through comprehensive trend and partial correlation analyses. Furthermore, it explored the responses of CUE and WUE variations to climate change and human activities across distinct geographical zones in China from 2001 to 2019, employing multiple regression residual trend analysis. Our analysis suggested that annual average CUE was 0.57 and annual average WUE was 1.47 g C kg−1H2O. Spatially, CUE demonstrated an increase in northern China but a decline in the southern regions, while WUE exhibited a contrasting trend. Generally, CUE exhibited a positive correlation with increased precipitation (PRE) and solar radiation (RAD) but displayed a negative association with elevated air temperature (TEM). Conversely, WUE showed an increase with greater PRE and TEM but a decrease with heightened RAD. Notably, it was revealed that human activities exerted a more significant impact on CUE and WUE in China than climate change. However, climate change played an important role in some areas with low populations, such as the Qinghai–Tibet Plateau. The results will improve the understanding of the carbon and water coupled process in terrestrial ecosystems, which is helpful to optimize the allocation of ecological resources and maintain ecosystem balance.

Water yield (WY) ecosystem service is an important ecological indicator in assessing water availability and sustainability. Although it was widely acknowledged that WY was mainly driven by land use change and climate factor, the intrinsic driving mechanisms remained unclear. Here, we selected the Chengdu-Chongqing District in Southwest China as the study area, using the InVEST model, structural equation modeling, and scenario analysis to exhaustively reveal the past and future WY changes and contribution rate of driving factors. The results demonstrated that the study area experienced rapid forest expansion and urbanization at the expense of cropland and grassland in the last 30 years. In this region, WY increased by approximately ∼130 mm during 1990–2020, attributed mainly to the contribution of precipitation (>90 %), and secondary to potential evapotranspiration and land use change. It was projected that by the end of the 21st century, WY would increase by about 20 % under SSP585 scenario compared to the historical average. We found that every 100 mm increase of precipitation would produce an additional 62–65 mm of WY, with higher precipitation resulting larger WY coefficient due to energy constraint there. Further, we also found that the elevation factor played a direct and negative role (standardized path coefficient, b = −0.4, p

Exploring the spatiotemporal dynamics of ecosystem services (ESs) and their drivers is a crucial but challenging task for improving ecosystem management and human well-being. However, few studies have focused on the evolution and mechanisms of ESs in typical upper watersheds in arid/semi-arid regions. Thus, this study examined the upper Fenhe watershed (UFW) in the Yellow River region, and aim to evaluate the spatiotemporal changes in ESs and ES bundles (ESBs) during 2000–2020. To this end, we utilized multi-source data, the InVEST model, and the K-means clustering algorithm. We then determined the contributions of various factors driving ESs using the geo-detector method (GDM). The results revealed that: (1) ESs exhibited spatial variation by county and ES type, and the overall trends were primarily reflected in the decrease in soil conservation (-11.04 t/hm2·a) and the increase in water yield (41.14 t/hm2·a). (2) Cluster analysis resulted in the designation of four types of ESBs in the study area during 2000–2020. (3) The spatiotemporal variation in ESs in the UFW was predominantly affected by natural factors, such as precipitation and sunshine hours. Our results provide a valuable reference for the ecological management and sustainable development of watersheds.

The rapid development leads to changes in the environment, including increasing pollution and changes in the landscape. The aim of the research was to analyse the content of rare earth elements (REEs) and yttrium (Y) in soil and Taraxacum officinale in various representative cities for Europe (in term of size and population), as well as to evaluate their content in relation to the specific economic and spatial conditions (land use) and landscape pattern. The research was conducted in three cities from Poland: Poznań (big city), Ostrów Wielkopolski (medium city) and Słupca (small city). Descriptive statistics and Spearman correlation were performed to identify the relationship between REE and Y content and land use, as well as landscape pattern. The investigation revealed that the average content of REEs and Y in soil was the highest in Poznań, while in dandelion roots and leaves in Ostrów Wielkopolski. In Słupca, the content of the analysed elements in the soil was at an average level and mostly at the lowest in the roots and leaves of dandelion. The REE and Y content were more associated with the specific economic and spatial conditions of cites and land use than its size or population. The relationship between landscape metrics and analysed elements were more pronounced for dandelion leaves than for roots or soil. However, two landscape metrics – largest patch index and Shannon’s diversity index implied that landscape diversity might contribute to reduction of REE and Y content in the environment. The new approach for REE and Y accumulation in the environment in relation to land use and landscape pattern, as well as in different sizes of cities, give the possibility to broader applications in urban areas.

With the global alterations in ecological conditions and population growth, the study of production-living-ecological space (PLES) offers a new perspective in balancing land resource utilization with the sustainable development of society, economy, and environment. China has incorporated the optimization of PLES into its sustainable development strategy. However, research concerning the PLES functions within wetland ecosystems remains notably sparse. Wetlands, distinguished by their unique ecosystem, command a special place in the realm of production, living and ecology research. Their importance is multifaceted, stemming from their roles in ecology, economy, and socio-cultural dimensions, and further accentuated by their distinct geographical, climatic, and biodiversity attributes. In light of this, the Xianghai Wetland Nature Reserve in Jilin, China, was chosen as the focal point of this study to probe into the coupling coordination degree of its PLES functions. The study commenced with a thorough analysis of the changes in land use types from 2000 to 2020 using a land use transition matrix model. Following this, a customized land use function assessment framework called LUF-PLE was formulated, offering a quantitative assessment of the Xianghai wetland’s production, living, and ecological space functions and shedding light on their spatiotemporal dynamics. Finally, a coupling coordination degree model (CCDM) was employed to elucidate the evolution of the PLES functions of Xianghai wetlands. Key findings revealed that: (1) the Xianghai wetland’s PLES coupling coordination degree exhibited a pattern of decline, stabilizing post-2010, with the most pronounced dip observed between 2000–2010; (2) the coordination between production and living functions was notably subdued, whereas the coordination between production and ecological functions saw the steepest decline. In the future, a sustainable wetland development strategy should be formulated and implemented based on the observed trends in coupling coordination and the spatiotemporal differentiation of production-liveling-ecological functions in the local context. This research furnishes scientific substantiation and serves as a reference for the sustainable stewardship and preservation of wetlands.

Rapid global industrialization has resulted in irreversible environmental degradation, with one pressing issue being the escalating problem of land contamination induced by heavy metals (HMs). This phenomenon not only inflicts lasting harm on plants and microorganisms within the affected regions but also imposes significant losses on various industrial chains, particularly in the realm of agriculture. A noteworthy illustration is the soil contamination in the Taojia River Basin, Hunan Province, China, attributed to mining activities. Therefore, this study is dedicated to examining the passivation of active-state lead (Pb) and cadmium (Cd) in the cultivated fields of the Taojia River Basin. To achieve this, two passivating agents, namely bentonite (referred to as passivator-P) and an acidifying soil agent known as “Shi Di Jia” (referred to as passivator-S), were employed, along with a control group (CK). The passivation of Pb primarily relies on cation exchange adsorbed on the passivator's surface, while the passivation of Cd is intricately linked to total nitrogen content (TN). Indoor incubation tests were conducted to assess Pb and Cd in the soil. Additionally, an analysis of various soil health indicators and their relationships with microbial dynamics and soil enzymes was undertaken. The findings revealed that passivator-P exhibited greater efficacy in the passivation of Pb at concentrations of 3% and 5%, while higher concentrations of passivator-S demonstrated increased effectiveness in passivating Cd. Concerning bacterial diversity, the soil pH post-passivation showed a positive correlation with the Observed_species index, whereas Pb and Cd exhibited negative associations with the Chao1 index. Regarding fungal diversity, soil TN post-passivation displayed a positive correlation with the Simpson index. It is concluded that adding passivator-P at a 3% concentration proved to be the optimal passivating agent for Pb-contaminated soils in the Taojia River Basin. Although passivator-S demonstrated lesser efficacy in passivating Pb, it proved to be suitable for Cd passivation. These findings offer a crucial reference for passivation passivation remediation in the Taojia River area and other sites with similar characteristics, shedding light on the impacts on soil organisms. The implications underscore the necessity for site-specific remediation strategies and a holistic approach to addressing HMs contamination.

In order to attain sustainable carbon management and reduce greenhouse gas emissions, it is imperative to obtain comprehensive data on estimated carbon emissions. This study presents an accounting framework that incorporates environmental parameters in land use to account for the spatial heterogeneity of carbon emissions. In the framework, carbon emissions were estimated based on direct and indirect emissions from where their emissions were generated. Environmental parameters are incorporated as spatial variables in the process of estimating carbon emissions from land use to obtain spatially explicit carbon emission information. In this study, the Demonstration Zone of Green and Integrated Ecological Development of the Yangtze River Delta (demonstration area) is taken as a case study to verify the applicability of the framework. The findings clearly show the spatial association between the spatial distribution of carbon emissions and land use-related carbon emissions. The study outcomes are valuable in facilitating the demonstration area's attainment of sustainable development objectives. The case study can also provide insights into the Yangtze River Delta's carbon emission management and sustainable development practices.

Sustainable water management requires an in-depth understanding of dissolved inorganic nitrogen (DIN) in watersheds. However, it remains challenging in the context of intensifying human-induced and naturally impacted stresses in a changing environment. A spatially explicit interpretable machine-learning method was proposed based on the annual variation in land use/cover, Catchment Land Surface Model, Noah land surface model, population dynamics, and nightlight in a coastal Chinese watershed. The proposed model was effective for delineating DIN processes and sources in watersheds. The d (index of agreement), R2 (coefficient of determination), |PBIAS| (percent bias), and KGE (Kling-Gupta efficiency)during the training period were 0.91–0.98, 0.76–0.96, 0.38–3.12, and 0.73–0.87, respectively. The d, R2, |PBIAS|, and KGE during the testing period were 0.85–0.94, 0.56–0.79, 3.59–6.18, and 0.65–0.86, respectively. NH4+-N in the watersheds may be strongly related to the effects of urbanization within the watersheds while the agricultural activities may modify the patterns of NO3–-N in the watersheds. The NH4+-N was highly related to the urbanization effects, which contributed 20 %–30 % of the riverine NH4+-N in the North River. In contrast, agricultural activities may modify patterns of NO3–-N in watersheds, and agricultural activities in the West River contributed 50 %–70 % riverine NO3–-N in the watershed. Moreover, urbanization may alter the water content, soil properties, and regional climate patterns within the watersheds, while repeated DIN input through agricultural activities in the agricultural watersheds may change the nitrogen processes in the soil and groundwater. Paired with agricultural activities, dams or reservoirs may amplify NH4+-N to watersheds with modifying the advection and diffusion of DIN from agricultural activities, and increasing sediments in the watersheds. This study demonstrated the potentials of the proposed method in tracking DIN pollution and provided new insights into nutrient management in the watersheds under intensifying human-nature interactions.

Most of the current studies on the flood susceptibility of the Tibetan Plateau (TP) have relied on historical observations, lacking future projections and are not conductive to adaptive strategy optimization. Here, we examine the dynamics of flood susceptibility using a logistic regression model. When combined with climate and land use changes, the flood susceptibility in the TP is projected to increase under three Shared Socioeconomic Pathways (SSP). By the 2090 s, compared to the baseline period (1960–2020), the areas classified as very highly susceptible will experience an increase of 3.63 %, 6.17 %, and 15.26 % under the SSP126, SSP245, and SSP585 scenarios, respectively. The regions with high (4.98 %) and very high (6.88 %) flood susceptibility are primarily concentrated in densely populated areas located in the eastern and southern parts of the TP. As significant factors influencing flood susceptibility, the mean annual precipitation in the TP is expected to increase by 114 mm, 135 mm, and 223 mm from the baseline to the 2090 s under the SSP126, SSP245, and SSP585 scenarios, respectively. Additionally, the mean annual temperature is projected to rise by 2.2 ℃, 3.5 ℃, and 7.1 ℃, respectively. Furthermore, there will be a substantial expansion in the built-up area within the TP, with the percentage of built-up area increasing from 0.12 % in 2020 to 0.32 % by 2095. Our findings provide a quantitative assessment of how both natural environmental factors and human disturbances contribute to the susceptibility of the TP to flooding. Moving forward, it is expected that the built-up area on the northeastern edge of the TP will experience significant growth, resulting in an increased vulnerability to floods. Therefore, it is imperative to implement rational land use and land cover planning measures in order to mitigate the impact of flood disasters.

Global warming caused by massive carbon emissions poses a serious threat to the environment and human beings. Dynamic monitoring of the spatio-temporal evolution of carbon emissions is an essential way to achieve carbon reduction goals, especially in coastal areas like Guangdong Province faced with dual challenges of massive carbon emissions and rigorous reduction targets. To reveal the spatio-temporal characteristics of carbon emissions and provide a basis for further fine-grained carbon emission reduction strategies, we analyzed spatio-temporal distribution characteristics of carbon emissions in Guangdong Province at the county-level scale from 2000 to 2020. Based on the land-use data obtained from the Data Center for Resources and Environmental Sciences of the Chinese Academy of Sciences and energy consumption data from the Statistical Yearbook, the carbon emission of each county is estimated, and the spatio-temporal evolutionary features of them are explored by a series of methods of the exploratory spatio-temporal data analysis (ESTDA). The shift of spatial distribution characteristics and gravity center is further revealed with the standard deviational ellipse and gravity center migration analysis.The results reveal that the net carbon emissions increased from 6179.229 × 104 tons to 20765.723 × 104 tons during 2000–2020. The net carbon emissions of county-level administrative regions show a significant positive spatial correlation, and the spatial convergence shows a trend of first decreasing and then increasing. The spatio-temporal pattern of carbon emissions has an obvious path dependence and locked spatial features, and shows a gradually strengthening trend. The spatial distribution of carbon emissions formed a stable “northeast-southwest” pattern, and the gravity center of carbon emissions in the past 20 years has been distributed between 113.208°–113.357°E and 22.760°–22.878°N, tending slightly shifting to the northeast. The results of the study can help understand the spatio-temporal evolution of carbon emissions in Guangdong, and provide a reference for formulating effective carbon reduction policies.

Coal-electricity base cities (CEBs) are coal-based electric energy centralized and sustained production and output cities built following China’s strategic energy layout, in regions with abundant coal resources, and by the integrated coal-electricity production model. However, CEBs are mainly located in the ecologically fragile area, and coal mining activities and anthropogenic pressures caused a series of land ecological effects such as dramatic land resources change, the alleviation of land supply and demand conflict, and land damage surrounding mining area. Currently, there is not enough research on land use in CEBs, and less attention has been paid to variation ecological system response. Aiming at this problem, the research constructed a modeling framework for evaluating the spatial and temporal evolution of land use characteristics and ecological response of CEBs land use from the perspective of “Economic-Social-Natural” by adopting methods of land transfer matrix, cluster analysis, ecological niche theory, and center of gravity model. Shendong mining area was accordingly chosen as the research region to explore the multidimensional land use dynamic evolution by bringing into the evaluating framework. Therefore, the Shendong area was accordingly chosen as the research region, and land is used as the spatial carrier to explore the evaluation effect of the model framework. The result showed that grassland played a considerable role in the procedure of land transformation with the greatest utilization degree, followed by cultivated land and used land. For ecological niche, mining land and water area dominated the core economic niche, mining land, and construction land occupied the social niche, mining land controlled mostly natural niche and comprehensive niche value. In terms of ecologically integrated and comprehensive quantitative evaluation response, the production functional area, living functional area, and ecological functional area of CEBs were also quantitatively depicted and evaluated. Ecological management should focus on the downtown area of Shenmu and optimize land use patterns by increasing vegetation cover. This study combines different types of indicators to derive regional differences in ecological niches, providing an assessment method for decision makers and stakeholders to optimize land use structure and improve the ecological benefits of CEBs.

Land exhibits distinct carbon source/sink states under varying utilization conditions. Under the climate change environment, developing low-carbon land use optimization strategies has become an urgent problem. Thus, this study examines the characteristics of land use carbon emissions (LUCE) resulting from land use and land cover change (LUCC) in Chongqing under five shared socioeconomic pathways (SSPs). The results show: (1) From 2000 to 2020, the LUCE in Chongqing increased significantly and then decreased slightly. The improvement of energy technology can limit carbon emissions from expanding construction. (2) In 2030, Chongqing will have the highest LUCE in SSP5 scenario, followed by SSP4 scenario, and the lowest in SSP2 scenario. However, some districts and counties in Chongqing City have the opposite situation to the whole research area. (3) In the study area, LUCE exhibits a significant positive spatial correlation with Moran's indices of 0.48, 0.27, and 0.39 in 2000, 2010, and 2020, respectively. Carbon emissions in Chongqing primarily concentrate in the main urban areas, with high-emission areas spreading outward from specific centers in the districts and counties. In 2030, spatial LUCE aggregation will decrease significantly, especially in the SSP3 scenario, with a Moran's index of 0.25. When adjusting the land use structure, policymakers need to implement differentiated land use management strategies, considering the characteristics of LUCE and their development directions. This study confirms that socioeconomic development has a direct impact on LUCE. The results of this study provide a reference for the government’s land-use assessment, achieving low-carbon development goals, and identifying regional development patterns.

Based on the natural resource endowment perspective, this paper examines how landscape patterns change over time and how ecosystem service value (ESV) responds to these changes, which plays an important role in rationalizing land use to make international wetland cities more sustainable. To identify the spatial and temporal variations in landscape patterns and ESV in Nanchang City and to investigate their relationships between them, six periods of land use data and associated socio-economic data from 1995 to 2020 were chosen as a sample of international wetland cities. The findings demonstrated that during the study period, the land use pattern of Nanchang City formed a landscape pattern dominated by cropland and supplemented by wetland, construction land, and woodland. And the ESV increased from 18,887.96 to 20,900.44 million yuan, with a total increase of 10.66 % in 25 years. Among them, the contribution of wetlands to the ESV was more than 71 %. The study also discovered that changes in landscape patterns significantly affect the ESV in Nanchang City, and the impact of landscape changes on the ESV varies among lands. In addition, although the ESV in Nanchang City has increased, there is still a risk of landscape fragility. This paper proposes relevant suggestions for increasing the ESV in Nanchang City by identifying key landscape pattern characteristics.

Are we losing water mostly due to climate change? This study delves into that question. The main innovation of this research lies in developing a methodology that forecasts future shifts in water resources through the use of nondimensional indicators, such as Landscape Hydric Potential (LHP), caused by climate change scenarios, land use and land cover (LULC) projections, and a combination of both factors. The LHP method draws upon a range of indicators that shape the geosphere at the catchment scale, namely: hydrogeological conditions, soil conditions, climatic conditions, geomorphological conditions, and LULC. The analysis was carried out for 33 catchments located in the Upper Vistula River Basin in East-Central Europe. The study was conducted in the following stages. First, LHP values were calculated for the present conditions. Subsequently, an analysis of anticipated changes in LULC and in climate were conducted for the near and far future. Lastly, simulations were performed to project how LHP might evolve, considering potential changes in climate and LULC over time. The results have shown that under current climatic conditions, mountainous catchments are characterized by higher LHP values than catchments located in highlands or plains. Agricultural areas are projected to experience the largest changes in LULC. Climatic water balance indicate minimal changes, irrespective of time horizon. Our studies conclude that changes in predicted LULC could have a more significant impact on LHP values than the projected climate change.

Green and blue spaces are an important part of a healthy urban environment. This study evaluates temporal patterns of urban green and blue space structure changes in Kraków, Poland over the last two decades (2002–2022). Annual land use time series of the following variables were employed: green spaces, blue spaces, forest land, meadows, pastures, and leisure land. The analysed data were provided by the Head Office of Geodesy and Cartography in Poland from the public cadastral register. The paper employed statistical methods, including the Mann-Kendall (MK) test for monotonic trend. It further used the Akaike information criterion, an approach founded on the information theory, to select one of four potential models (linear, quadratic, power, or logarithmic). The results indicate a trend in each of the six series. The area of green spaces has been demonstrated to decline while blue spaces grew. The most significant changes from 2002 to 2022 occurred in the area of meadows, which shrunk by 509 ha and in pastures, which declined by 351 ha. Forests and wooded areas grew by 324 ha and leisure lands by 1 ha, while blue spaces expanded by 160 ha in total. The results can be useful for drawing up informed, sustainable governance strategies for urban green and blue spaces. The research is relevant to the urban environment because the distribution of urban green and blue spaces is critical for ecosystem services. Moreover, such research is not common, which is indicative of its originality and confirmed by the bibliometric analysis.

Sichuan hilly area is located in southwest China, which have many hilly area, is a densely populated, economically active, frequent geological disasters area. In this paper, Neijiang City in the region is taken as the test sample. This article, which analyzes Land-Use and Land-Cover Changes (LUCC), meteorological and hydrological data from 2015 to 2020, takes Neijiang City in this region as the research object. We explored the relationship between geological disasters such as collapse and landslides that often occur in the natural ecological environment with LUCC and meteorological and hydrological factors, using GIS spatial analysis and statistical analysis methods. The research results indicate that geological disasters mainly occur in farmland areas. The density of geological disaster points is highest within urban areas, making them the most prone to geological disasters. Geological disasters are more densely distributed in the area within 600 to 800 m from the river. There is a strong correlation between the average rainfall amount and the probability of geological disasters occurring. This study provides a scientific basis for the geological disaster risk assessment, prevention and control in this region. It has certain reference significance for the ecological environment governance, land resources planning and management in other similar regions.

As one of the world’s critical ecological regions – often called the “Third Pole” – the Qinghai-Tibet Plateau (QTP) has outstanding ecosystem service values (ESV). However, its variable climate and fragile environmental conditions make it vulnerable to disturbance by human activities. Based on land use data from 2000, 2010, and 2020, we developed three simulated scenarios of land use distribution on the QTP: business as usual (BAU), farmland protection (FP), and ecological protection (EP). Finally, we employed the Sharpe Index to evaluate ecological risk across the QTP. The results showed that from 2000 to 2020, land use change was mainly in the form of conversion of grassland to unused land, totaling an area of 63,717 km2. The ecosystem service value showed an increasing trend, from US$752.6 billion to US$783.0 from 2010 to 2020. The simulation results from the three scenarios revealed significant differences. Farmland area shows a declining trend in both the EP and BAU scenarios, while exhibiting an increasing trend in the FP scenario. Forest area on the plateau experiences a decreasing trend in the EP and BAU scenarios, but shows an increase in the FP scenario, predominantly in the southeastern region, including Sichuan and Yunnan provinces. The ecological risk assessment results indicate that the eastern region has higher ecological risk compared to the western region, highlighting the western region as a priority area for risk control. The expansion of built-up land and unused land has had significant impacts on regional ecological risk. Integrating risk assessment outcomes with land use planning to identify focal areas can provide guidance for the sustainable development of this globally important ecoregion.

Carbon dioxide emission is an important driving factor of global warming and it has threatened the ecological environment and human survival. Among them, land use has led to significant carbon emissions that profoundly affect climate system change. The Yellow River Basin (YRB) is one of the regions with the most concentrated contradictions in population, resources, and environment in China; thus, studying the current situation and land use carbon emissions (LUCE) is significant for mitigating global warming, promoting coordinated emission reduction among different regions in the basin, and achieving ecological conservation and high-quality development of the YRB. This study based on land use and socio-economic data, and is carried out from the perspective of social network analysis. The spatiotemporal variation of LUCE in the YRB was analyzed using the carbon emission coefficient method. The spatial spillover effects of LUCE were discussed using social network analysis methods. The PLUS model was used to simulate the differences in LUCE under different scenarios. The results indicate that: (1) The LUCE in the YRB showed an increasing trend during the study period, with significant differences in spatial distribution. (2) There is a significant spatial spillover effect and correlation between cities in the YRB LUCE network, and cities with superior economic had a greater impact on other cities. (3) In 2030, under the ecological protection scenario, the LUCE in the YRB were the lowest, with a reduction of 2.7 × 106 tons compared to the natural development scenario, further illustrating the importance of ecological land. Compared with previous studies, this study explores the spatial correlation between LUCE in various cities of the YRB from a new perspective of social network analysis. On the other hand, it makes land use prediction for 2030 by setting different land use development scenarios. The research results have broadened the application scope of social network analysis methods, and have important practical significance for promoting carbon reduction in major river basins and scientifically formulating land use policies.

Ecological carrying capacity is key to evaluating sustainable development capacity, and land use change has varying degrees of impact on ecosystems. This study explores the ecological carrying capacity based on land use change, which is important for the conservation and scientific and rational use of ecosystems. Therefore, in this study, three machine learning classification 3algorithms, namely support vector machine, random forest and artificial neural network, were selected for accuracy comparison and analysis based on multi-source data, using Southwest Guangxi Karst-Beibu Gulf as the study area. The Patch-generating Land Use Simulation Model is used to dissect the spatial and temporal changes in ecological carrying capaciyt from 1990 to 2040 and future trends. The results showed that (1) Coupling multiple sources of data and machine learning classification algorithms can ultimately improve land use classification accuracy. The RF is compared and found to be the optimal classification algorithm for this study. (2) The area of arable and grassland gradually decreases between 1990 and 2040, mainly encroached upon by build land; the area of forested land gradually recovers, the watershed fluctuates up and down, and the area of build land gradually increases. (3) The ecological carrying capacity from 1990 to 2040 shows a trend of decreasing and then increasing, and the area of low and medium–low decreases from 2020 to 2040, with arable land and forest land having a stronger potential to increase ecological carrying capacity. Nanning City, Qinzhou City and Chongzuo City are severely damaged. The framework provides an effective tool for exploring future ecological carrying capacity to support the ecological conservation and future sustainable development of the region.

Indices such as the Index of Biotic Integrity (IBI) are often used by management agencies to estimate the abstract property of stream health. These indices are usually predicated on the belief that certain fish species are tolerant to environmental perturbation while others are sensitive. Species are usually designated as either tolerant or sensitive in these analyses based on inherent ecological or taxonomic characteristics. However, previous literature has shown that certain species from ecological or taxonomic “sensitive” groups experience increased abundance in degraded streams. We term such species “cryptic tolerants”. Using a stream fish assemblage dataset of 433 unique sample locations across the state of Alabama and the National Landcover Dataset, our objectives were to 1) identify the most common cryptic tolerant species, 2) investigate how cryptic tolerant species might inflate indices of stream health, and 3) compare an alternative measure of stream health in which species are statistically defined rather than defined using the traditional trait-based approach. We identified cryptic tolerants using Nonmetric Multidimensional Scaling in six ecoregions. A series of regressions revealed that the proportion of cryptic tolerant species decreased in response to an increasing proportion of forested land in catchments while the proportion of true sensitives increased in all ecoregions except for the Cumberland Plateau. An index that simply used the percentage of statistically defined, non-tolerant species generally had lower p-values and higher r2 values than IBI scores when both were regressed against percentage of forest in catchment. However, both indices had low degrees of correlation with expected disturbance, indicating a univariate index may be inadequate to characterize stream health. Our results highlight a potential issue with applying the IBI to diverse southeastern systems in the United States, which may be alleviated by designating species sensitivity based on empirical response to disturbance rather than taxonomic or ecological characteristics.

Agricultural drought can severely reduce crop yields, lead to large economic losses and health impacts. Combined climate and land use variations determine key indicators of agricultural drought, including soil moisture and the Palmer drought severity index (PDSI). This study investigated the use of machine learning (ML) methods for predicting these indicators over Sweden, spanning steep climate and land use gradients. Three data arrangement methods (multi-features, temporal, and spatial) were used and compared in combination with seven ML/deep learning (DL) models (random forest (RF), decision tree, multivariate linear regression, support vector regression, autoregressive integrated moving average (AMIRA), artificial neural network, and convolutional neural network). Seven investigated features, obtained from Google Earth Engine, were used in the ML/DL modeling (soil moisture, PDSI, precipitation, evapotranspiration, elevation, slope and soil texture). The temporal ARIMA model (found most suitable for local scale prediction) and the multi-features RF model (more suitable for national-scale prediction) emerged as best performing for soil moisture prediction (with MAE of 9.1 and 11.95, and R2 of 0.79 and 0.59, respectively). All models generally performed better in predicting the soil moisture than the PDSI indicator of drought. For drought indicator prediction and mapping, previous-year average monthly soil moisture emerged as the most important feature, combined with the four additional corresponding features of PDSI, precipitation, evapotranspiration and elevation.

Complex geological problems caused by natural environment have emerged constantly, causing serious damage to the land use and groundwater ecological environment in the western region. How to deal with the relationship between the above factors and ecological environment protection is a new research topic at present. Broken rock mass, cracks and water inrush during construction can be blocked and reinforced by grouting to achieve environmental protection. Therefore, to develop accurate quantitative models for the hydration of cement and predict the properties of grouting materials plays a crucial role during the protection process. In this study, the hydration product Ca(OH)2 is taken as an example, and the adsorption processes of different functional groups on the surface of Ca(OH)2 were investigated using DFT. The adsorption energy of the (101) surface was −0.38 Ha in sulfonic group, the lowest on different crystal planes of Ca(OH)2, while the adsorption energy of different functional groups is sulfonic group > carboxyl group > amide group > benzene ring. The adsorption energy was the lowest when the hydroxyl and carboxyl ratio was 1:1, suggesting that the adsorption energy and hydration performance in different ratios of hydroxyl and carboxyl groups will also be discrepant. After the adsorption of functional groups with Ca(OH)2, the electron clouds and orbitals rearranged, new characteristic peaks of the s orbital were present in the vicinity of −15 eV, −13 eV, and −10 eV, respectively. Since the relationship between functional groups and cement hydration process of chemical admixtures was explored, the mechanism of the cement hydration reaction and the influence of cement-based admixtures was revealed from an electronic view, also to extract the key influencing factors for the grouting and develop accurate quantitative models to predict and tackle various geo-environmental hazards.

The study of long-term changes to urban green space reveals the reasons for changes in the spatial pattern of urban green space and predicts the future development trends, which is of great importance for urban green space protection and integrated urban development. This study used Markov Chain and PLUS models to explore the spatial and temporal patterns of changes to green space in urban and rural areas in Jinan City during recent rapid urbanization and the driving forces behind them. The results show that from 2000 to 2020, the decrease in urban green space in Jinan City slowed down gradually, and that elevation and population density were the primary factors influencing changes in urban green space. In the simulation projections, the ecologically protected development scenario had a relatively low rate of site change and was more protective of arable land and green space. Ecological conservation development was predicted to result in a decrease in unused urban land and to reflect the advantages of intensive land use. The findings will provide decision-makers with ideas related to the sustainable development of urban green space.

The evaluation of land comprehensive carrying capacity (LCCC) is a popular topic in regional sustainable development and land science research. However, these evaluations are often not objective due to the complexity and nonlinear characteristics of the LCCC evaluation indicators. This study provides a new framework for using machine learning methods to objectively evaluate LCCC. The Driver-Pressure-State-Impact-Response (DPSIR) indicator conceptual framework was used for the spatial visualisation of indicators and was then combined with the random forest (RF) model to optimise the LCCC evaluation. The results showed the following: (1) The accuracy of the integrated RF and DPSIR model was better than that of traditional support vector machine (SVM) and principal component analysis (PCA) methods, indicating that RF model was more suitable for LCCC evaluations. (2) The contribution of the DPSIR indicators after RF optimisation was significantly different from that of the traditional analytic hierarchy process (AHP), the contribution of the influence subsystem (I) (48.7%) was enhanced, while the contribution of the drive subsystem (D) (6.8%) was weakened, demonstrating that after RF optimisation, the DPSIR was more conducive for handling complex nonlinear systems and objectively reflecting indicator contributions. (3) The objective attributes of the DPSIR indicators were optimised through the processing of spatial visualisation models, indicating that RF was suitable for processing evaluations with a multidimensional spatial heterogeneity index system. The LCCC evaluation model can be applied to other carrying capacity case studies and operational processes and provide a scientific method for handling the multidimensional nonlinear evaluation index system and objective evaluation of LCCC.

Due to rapid changes of the agricultural practice, the traditionally managed farmland became currently-one of the most endangered habitats in Europe. Species related to the rural landscape have been facing a great challenge of adaptation to quickly changing conditions. Therefore, recognizing and characterizing highly suitable areas for white storks is very important to plan conservation measures in the era of changes in agriculture and land use. Here, combining nest survey data (811 occupied nest), GIS-data on habitat availability and modelling approach, we characterize the current foraging conditions of the white stork Ciconia ciconia, an indicator of the agricultural habitat biodiversity and an umbrella species for organisms associated with agriculture landscape. The studied population breeds in the Warmińska Refuge Natura 2000 site (N Poland), one of the key breeding areas of this species in Europe. Breeding pair presence was predicted by the area of pasture, meadows, field ponds, and linear water within a 1 km buffer around the nest. The main hotspots of habitat suitability were located in the central and western parts of the study area, characterized by a more traditional model of agriculture. The distance to important foraging habitats does not influence white stork fecundity indicating that landscape composition is important when choosing the breeding site. The pairs with higher number of young were located further from other neighbouring pairs and at the areas with lower density of pairs in general. This is probably linked to the lower competition for food between more distant breeding pairs. Our results show that the traditional agricultural use in mosaics of pastures, meadows and aquatic habitats promotes white storks nesting.

Agricultural intensification has profoundly changed agricultural landscapes with important biodiversity impacts. There is increasing knowledge on the general effects of landscape structure and management practices on plant and animal species but understanding the role of surrounding landscape structure for patch-scale biodiversity is more complex. While it can be reasonably assumed, that adjacent habitats are more important than more distant ones, the importance of landscape structure has often been tested at the landscape scale but rarely at smaller scales such as patch-surroundings. We assessed the influence and interdependences of landscape composition and configuration (LCC) and land use/land cover (LULC) on bird species richness and abundance through a multi-scale analysis with specific focus on the surrounding patches. In two agricultural regions in Switzerland, we collected point data of birds on 36 transects (500 m) and combined them with detailed spatial data on LULC. Bird richness and abundance were correlated to sets of landscape metrics as proxies for LCC computed at the transect-scale as well as for the patch surroundings. We analysed patch LULC as well as the most important patch-surrounding metrics using generalized linear mixed models. The results illustrate that patch LULC is the most important predictor of bird richness and abundance. Woody structures increase bird richness, followed by extensive management on patch scale. On the transect-scale semi-natural structure and heterogeneous LCCs are beneficial for bird richness and abundance. The effect of patch-surrounding structure LCCs is only small and interacts with patch LULC. Birds in grassland benefit from fallows in the surroundings, while in cropland they tend to respond positively to surrounding extensive grassland. Our results highlight that considering surroundings can help improve patch-based biodiversity assessments, which will then better predict the consequences of farmland management and make the outcome more applicable for practice.

As a result of the land degradation it causes, rapid urbanization can severely impact the form and function of the natural environment. Because of the limited availability of natural capital and the ecosystem services they provide in many regions, fluctuations in supply and demand should rigorously considered in decision-making. The Qinghai-Tibetan Plateau (QTP) is a globally-important ecoregion that generates significant ecosystem services value. Focusing on the QTP, we calculated the value change in the supply of ecosystem services using a coefficient table and the change in demand based on population, GDP, and income elasticity. The impact of supply and demand on the scarcity value of ecosystem services (ESSV) was then compared across four representative scenarios. The results showed that the ESSV on the QTP rose considerably between 1990 and 2020, particularly between 2000 and 2010. Between 1990 and 2020, the public-goods services grew faster than private-goods services. The most important element impacting the ESSV was demand-driven scarcity. The level of urbanization gradually increased during 1990–2020, with a consistent distribution of high ESSV and high urbanization across the region. High-High types and Low-Low types had a significant aggregation effect, located primarily in the north and west of the QTP, respectively. The Low-High type was scattered along with the Low-Low type, indicating fragile ecological conditions that merit greater protection from land degradation. The degree of coupling reveals an increasing degree of synergy between ESSV and urbanization on the QTP, indicating potential for more synergistic development.

The study aims to clarify the temporal and spatial evolution characteristics of landscape ecological risk in Hailar River basin in recent 30 years, and to serve for scientific formulation of ecological management strategies. In the study, ecosystem services were used to improve the traditional landscape ecological risk assessment method, and the theoretical basis of landscape ecological risk was clarified using the human-nature system method. The results show that, on the spatial scale, the overall landscape ecological risk of Hailar River basin is characterized by high in the middle and low around. The high-risk areas are mainly located in the transition zone of “urban-grassland” and “urban-forest” in the middle of the basin and the main mining areas, which are distributed in strips along the main roads and rivers. Low risk areas are mainly distributed in the Great Khingan Mountains forest area in the east and north of the basin. In terms of time scale, the landscape ecological risk in the edge of the watershed has always maintained a high proportion of low-risk areas (75.35 %), while the area of high-risk areas in the middle of the watershed has experienced a process of first increasing and then decreasing. In terms of ecological governance, high-risk areas should achieve orderly urban construction and orderly development of mineral resources, and establish a classified management system of natural resources. Low risk areas should continue to promote measures to prohibit logging and limit grazing, and establish a supporting ecological compensation mechanism. The conclusion shows that urbanization, mineral development and management, and the implementation of forest and grass policies are the main driving factors for the change of landscape ecological risks in Hailar River basin. The basic principles of zoning control and human land coordination should be adhered to, and the size of cities and towns should be adjusted reasonably to promote the orderly development of mineral resources and the orderly construction of projects.

• Introduction of a framework for the transition of arable land use functions (TALUF). • Exploration of the direct impact of urban–rural integration (URI) on TALUF. • Identification of significant spatial spillover effects of URI on TALUF. • Investigation of the threshold effect of URI on TALUF. This study examines the impact of urban–rural integration (URI) on the transition of arable land use functions (TALUF), providing both theoretical and empirical insights into how URI can promote TALUF. Utilizing panel data from 41 cities in the Yangtze River Delta (YRD) from 2003 to 2022, this research employs the entropy method, Durbin model, and spatial threshold model to assess the levels of URI and TALUF in the region and examine the direct impact, spatial spillover effects, and threshold effects of URI on TALUF. The findings are: (1) During the study period, both TALUF and URI levels in the YRD showed continuous improvement, although significant spatial imbalances persisted, with regional differentiation gradually diminishing. (2) URI exerts a significant inhibitory effect on TALUF and produces a negative spatial spillover effect. (3) URI exerts a single threshold effect on TALUF: below the economic development threshold of 0.733, URI and its spatial term inhibit TALUF, whereas above this threshold, they promote it. Consequently, fostering high-quality regional economic development, enhancing intercity cooperation, driving agricultural technological innovation, and increasing agricultural input intensity are essential strategies for arable land use policies in the context of URI. [ABSTRACT FROM AUTHOR]

• The identification and quantification methods of NbS measures are innovatively proposed. • The eco-environment quality of Beijing green belts showed a trend of first decline and then recovery in 2005–2020. • The effectiveness of NbS measures in improving eco-environmental quality of Beijing green belts is confirmed. • The influence of NbS measures on eco-environmental quality of Beijing green belts is spatial-heterogeneous. The green belts are indispensable constituents of urban spatial structure, exerting substantial impact on the urban eco-environmental quality. "Nature-based Solutions (NbS)" measures provide a new means to addressing urban sustainability challenges. Taking Beijing green belts as the research object, this study analyzed the change of eco-environmental quality and its driving factors, with a particular focus on the driving effect of NbS measures. Our analyses revealed several key findings. As data from 2005 to 2020 indicate, the process of land use change exhibits a spreading trend from inside to outside, reflecting the characteristics of industrialization-driven urbanization. The eco-environmental quality of the green belts demonstrated a U-shaped trajectory, initially declining before showing signs of recovery. Notably, the first green belt experienced a relatively lower eco-environmental quality, with a persistent decline throughout the studied timeframe. From the perspective of ecological contribution rate, the negative effect of land use change outweighted the positive effect, resulting in an overall decline in eco-environmental quality. This study confirmed the driving effect of NbS measures on eco-environmental quality improvement. Specifically, Green Infrastructure showed a significant driving effect of the two green belts, while Ecological Infrastructure only demonstrated a significant driving effect in the second green belt. In light of these findings, future implementations of NbS measures can be more precisely targeted to optimize the resilience and sustainable development capacity of cities. [ABSTRACT FROM AUTHOR]

• The ecosystem health assessment improved framework included vigor, organization, resilience, and services. • EH in the study area showed a slight increase trend during 2000–2022, and the number of increase level grids reached 94%. • Land use change was a major factor influencing changes in ecosystem health. • In view of the existing ecological problems, ecological protection and restoration suggestions were put forward. Wuliangsu Lake is the largest lake wetland in the Yellow River basin, it is the Northern Sand Belt of China, which is essential to maintaining ecological security in northern China and the areas downstream. With the increasing environmental problems, the basin has become a sensitive and complex geographical unit, and a better understanding of the level of ecosystem health in the basin is helpful for policymakers in developing measures for ecological restoration and eco-space management. In this study, we proposed an improved VORS model containing ecosystem vigor, organization, resilience and services to assess the ecosystem health in the Wuliangsu Lake Basin in 2000, 2011, and 2022. To improve spatial precision, the study area was partitioned into grids measuring 2 km × 2 km each. The results indicated that: (1) the ecosystem health showed a slight increase trend, which indicated by the increase level grids reached 94 % in 2000–2022 change. (2) The reduction in vegetation cover decreased the ecosystem vigor, which was indicated by the weak level increased from 22 % in 2000 to 73 % in 2022. Ecosystem structure becomes more complex enhanced the ecosystem organization, the value increased from 0.3 to 0.6 in 2000 to 0.6–0.8 in 2022. Ecosystem resilience slightly declined in 2011 and 2022, ecosystem services were relatively stable but were dominated by weak levels. (3) The majority land use type in the study area is farmland, and the ecosystem vigor decreases as the area of grassland decreases to farmland in these 22 years. The ecosystem's structure was enhanced and the land use structure was progressively brought into balance. Changes in all four parameters of ecosystem health assessment are related to land use, and changes in ecosystem health are likewise related to land use changes. The improved VORS model constructed for the Wuliangsu Lake Basin objectively reflect the basin's state of ecosystem health, and provide a reference for ecological restoration and basin regional planning. [ABSTRACT FROM AUTHOR]

• Constructed a more realistic ecosystem development model based on circuit theory. • The projected land use and cover changes in 2035 under the four development scenarios provide more adequate data support. • The ecological security pattern restriction scenario (S4) has the highest ecological safety index. • S4 has the best ecological effect and the widest range of high-grade habitats. With the development of the social economy, ecological environment damage has become increasingly serious, and how to better protect ecological security has gradually attracted people's attention. This paper takes Hubei Province in China as the research object, using the PLUS model version 1.4 to design four development scenarios to predict land use and land cover changes (LUCC) in 2035: the natural development scenario (S1), the cultivated land protection scenario (S2), the ecological protection area restriction scenario (S3), and the ecological security pattern (ESP) restriction scenario (S4). The study evaluates the ecological effects under these four different scenarios using Conefor Sensinode 2.6 software, Fragstats v4.2.1 software, and the InVEST model. The conclusions are as follows: (1) ESP has better ecological landscape connectivity. (2) Comparing the ecological security indices of the four scenarios, they are 0.5378, 0.5288, 0.5318, and 0.5405, respectively, with the S4 scenario showing the best protection effect. (3) Comparing the habitat quality of the four scenarios, high-grade habitats degrade under S1 and S2 scenarios; homogenization occurs under S3 and S4 scenarios, but the retention rate of high-grade habitat areas is the highest under the S4 scenario. In conclusion, compared to natural progression and prioritizing cultivated land protection, implementing ecological protection policies yields better ecological effects, and a planned ESP provides more targeted policy recommendations. [ABSTRACT FROM AUTHOR]

• The influence of e aq − donors on products of NO 3 − reduction was discussed. • e aq − generated in three systems were used for NO 3 − photo-reduction. • The products of NO 3 − photo-reduction in three systems were identified and compared. • The mechanism of Fe2+ and SO 3 2− for generating e aq − to reduce NO 3 − was discussed. • Fe2+/SO 3 2−/UV system could reduce NO 3 − in wastewater with over 97 % N 2 selectivity. National parks are public green spaces planned and managed by the state, with the primary purpose of protecting natural ecosystems and cultural heritage. Evaluating the Ecosystem Service Value (ESV) of national parks and clarifying their ecological benefits can provide important scientific basis for the ecological protection and restoration of national parks. Therefore, taking the Northeast China Tiger and Leopard National Park (NCTLNP) as the study area, this research constructs an ESV assessment model based on Land Use and Land Cover Change (LUCC), using vegetation net primary productivity（NPP）as a biomass correction factor to modify the Equivalent Factor Approach (EFA). It aims to explore the spatial–temporal pattern changes of the ESV in the NCTLNP from 2000 to 2022. Additionally, the Future Land Use Simulation (FLUS) model is utilized to simulate the future LUCC pattern and ESV evolution trend under ecological protection. Finally, the spatial Durbin model (SDM)is employed, combining socio-economic and environmental factors such as population, GDP, and PM10 and so on, to reveal the driving mechanism of spatial spillover effects of ESV in the NCTLNP. The results indicate that:①The accuracy of the FLUS model is 93.12% with a Kappa coefficient of 0.87. The main LUCC of the NCTLNP is forest. Before 2020, the ecological land had a shrinking trend, while impervious is in a significant increasing trend. After 2020, there is an opposite trend.The most significant changes in LUCC were found in Wangqing County and Hunchun City. ②The ESV of the NCTLNP shows a fluctuating and increasing trend from 2000 to 2022. It increased from 69.315 billion yuan to 69.809 billion yuan. The main service function of the ecosystem in the study area is the regulatory services, which provide 58.03% of the ESV to the NCTLNP. The Hunchun City and Wangqing County have the fastest increasing rate. ③The ESV of the NCTLNP had a significant negative spillover effect, with spatial spillover coefficients of −0.135 and −0.236, respectively, which led to a siphoning phenomenon in the NCTLNP. Overall, by assessing the ESV of the NCTLNP and revealing the spatial spillover effects in the study area, it can provide a vital scientific foundation for the conservation and management of the national park, which will help to fulfill the sustainable development of the ecosystem and the conservation of biodiversity. [ABSTRACT FROM AUTHOR]

• Establishing a theoretical framework for Spatial Conflicts of Land Use (SCLU). • Delving into SCLU dynamics in arid regions from the ecological environment. • Investigating the spatio-temporal characteristics of SCLU at varied spatial scales and landforms. • Unveiling spatio-temporal effects among driving factors influencing SCLU in Xinjiang. The study of spatial conflicts of land use (SCLU) is an important breakthrough to reveal the evolution mechanism of regional human-land relationship. Accurate identification of SCLU and scientific exploration of its spatio-temporal characteristics of their driving factors are pivotal for regional sustainable development. However, the basic theoretical system of SCLU still needs to be improved, and the spatio-temporal characteristics of SCLU at different spatial scales and landforms as well as the spatio-temporal correlation effects of its driving factors need to be further studied. This study utilizes theoretical models for the identification of SCLU. Employing a comprehensive index approach involving ArcGIS, FRAGSTATS landscape pattern analysis, and the multi-scale geographically weighted regression model, the spatio-temporal characteristics of SCLU are analyzed across different administrative scales and Macro-landforms. The investigation unveils the intrinsic mechanisms of spatio-temporal differentiation driven by various factors from 2000 to 2020 in the arid and semiarid region of Xinjiang, China. Results indicated that: (1) SCLU is a sensitive indicator of human-land interaction, measurable using conflict risk and effect; (2) The SCLU in Xinjiang presents a spatial pattern of "severe conflict around the three mountains and mild conflict around the two basins" and the SCLU transitioned from an outbreak to a relief stage over the past two decades; (3) SCLU varies significantly among landform types, with conflict intensity in Plain > Mountains > Platform > Hill areas; (4) Elevation and slope in natural environmental factors, human footprint and distance of patches from water, from roads, and from railroads in social activity factors have inhibitory effects on SCLU, and GDP, population density, and human impact index in economic development factors have positive effects on SCLU, and focusing on controlling potentially high-conflict risk areas and enhancing the upgrading of ecological quality are key to mitigating SCLU. The results validate the proposed theoretical framework and provide theoretical and practical references for accurately identifying SCLU and optimizing national territory spatial patterns. [ABSTRACT FROM AUTHOR]

[Display omitted] • YREB land structure is stable, landscape is fragmented and connectivity is reduced. • HQ distribution varies significantly, with high HQ widely distributed at best. • High HQ gradually converts to low, with some risk of HQ degradation. • Global view, there are different correlations between different LSPI and HQ. • Local view, LSPI promote or inhibit HQ, with clear spatiotemporal heterogeneity. Recently, rapid economic development of the Yangtze River Economic Belt region in China and the growing problem of regional habitat quality have seriously threatened the process of biodiversity conservation in the Yangtze River Basin. Studying the impact of changes in landscape pattern indexes on habitat quality in the Yangtze River Economic Belt can provide policy insights for biodiversity conservation in the Yangtze River Basin. However, existing studies are still lacking in exploring the effects of changing landscape pattern indices on habitat quality under future scenarios. Based on the land use data of the Yangtze River Economic Belt from 2000 to 2020, this study simulates the land use situation in 2030, and analyzes the landscape pattern indexes and habitat quality during the 30 years, to investigate the impact of landscape pattern indexes on habitat quality at global and local scales through various methods. The results show that landscape patterns were significantly affected by human activities and land use types, with the Yangtze River Economic Belt experiencing increased levels of land use and structural stabilization during the three decades (Shannon Diversity Index increased from 0.90 in 2000 to 0.94 in 2030), fragmentation of the landscape (Landscape fragmentation index increase from 0.094 in 2000 to 0.102 in 2030), and weakened connectivity (contagion index decrease from 48.213 in 2000 to 45.437 in 2030). The Habitat Quality has a large variation in spatial distribution at the county scale, with an average change in habitat quality of 1.04 % from 2000 to 2030, and an overall downward trend. There is a strong localized spatial autocorrelation between landscape pattern indices and habitat quality, with significant spatial heterogeneity and some form of variability at time scales. The results of this study help to further understand the eco-environmental problems of the Yangtze River Economic Belt, and provide theoretical references for the formulation of ecological environmental protection policies and ecological functional area planning. [ABSTRACT FROM AUTHOR]

• The area of the largest 10 patches of ESs decreased by 13.5%. • The largest patches of ESs in the southwest became smaller significantly. • Two key ECs connecting the eastern and central regions have been encroached upon. • The ECs connecting the eastern and central regions should be given priority protection. Rapid urbanization has a comprehensive impact on the patterns of regional ecological security (ESPs) in the Sino-Singapore Guangzhou Knowledge City, China (SSGKC). This study aims to propose recommendations for ensuring regional ecological security by conducting a spatiotemporal dynamic assessment of ESPs. The findings reveal that SSGKC has experienced rapid urbanization in the past decade, resulting in more than doubling of construction land. The results indicate that the area of the largest 10 patches of ESs decreased by 13.5%. Two largest patches of ESs in the southwest became smaller and were out of the top 10 patches in 2020. The expansion of construction land has encroached upon key ecological corridors (ECs). Two ECs connecting the eastern and central regions have shifted southward. Landscape pattern indexes demonstrate that not only has the area of ESs decreased, but they have also become more fragmented. This study also utilized the Urban Development Boundary (UDB) and FLUS model to simulate and predict the potential impact of future land use change on ESPs. Policymakers are advised to optimize the UDB by excluding areas that overlap with ESs and key ECs, in order to minimize the potential occupation of ESs and ECs in the future. The circular ECs connecting the eastern and central regions should be given priority planned and protection. [ABSTRACT FROM AUTHOR]

[Display omitted] • We present a 3D framework to evaluate peatland degradation research. • 54 % of 115 analyzed studies assess vegetation using space- or airborne optical data. • Research addressing vegetation, peat and hydrology in a tripartite system is rare. • Combined remote sensing sources allow more holistic peatland degradation research. Peatland degradation causes a number of environmental problems ranging from greenhouse gas (GHG) emissions to subsidence and ecosystem loss. Degraded peatlands, covering just 0.3 % of Earth's land area (500,000 km2), disproportionately contribute 5 % of GHG emissions, exacerbating the climate crisis. Once degraded, restoring peatland ecosystem functions often presents a considerable challenge because degradation affects several interconnected components in peatlands: the peat body, hydrology, and vegetation. The planning and implementation of effective peatland restoration strategies requires the accurate mapping of degradation. This review examines how remote sensing has been used to examine the components of peatland degradation. A conceptual 3D space was created using the three components of peat, hydrology, and vegetation. Within this three-dimensional space, five groups of studies were identified, representing each one of the three dimensions individually, or addressing two or three of them simultaneously. Of 115 relevant articles, 54 % solely addressed vegetation degradation, 18 % evaluated two dimensions equally, while just 10 % of all studies examined all three dimensions. These results highlight a lack of remote sensing-based research that considers all aspects of peatland degradation and their interdependence simultaneously. By synthesizing our findings into three descriptive peatland degradation scenarios (a boreal landscape, a temperate large peatland complex and a temperate small raised bog), we present rapid and efficient methods and resources for a more holistic approach to degradation mapping and monitoring. Consequently, such comprehensive assessments integrating different historical and current remote sensing data should be carried out more frequently. They allow the visualization of ecological consequences of peatland degradation and promote peatland restoration in all parts of these tripartite ecosystems. [ABSTRACT FROM AUTHOR]

• Impacts of land use on water quality in seven major basins in China at different seasonal and spatial scales are examined. • Dry season land use is strongly correlated with water quality in the YAR, LHR and PER basins, while the YAR, HUR, HAR and SHR basins are wet season. • Water quality in different basins is all related to the scale of land use. • Different basins need to develop basin-specific land use plans from a multi-scale perspective to improve water quality. Diverse land use patterns exhibit varying effects on water quality across different seasons and spatial scales. However, current studies on the correlation between land use and water quality in single small-scale basins no longer meet the needs of regional coordinated development. Simultaneous comparative analysis of multiple large-scale basins can promote water environmental protection in different basins, but there is currently limited relevant research. In this study, the data from 86 sampling points across seven major river basins in China were analyzed. Multivariate statistical analysis and the redundancy analysis (RDA) were employed to investigate the influence of land use patterns on water quality at different seasons and spatial scales. The results indicated notable differences in water quality across various seasons and locations. Except for higher pH and permanganate index (COD) concentrations in the wet season in the Songhua River Basin and higher COD concentrations in the Pearl River Basin, the concentrations of all parameters in other basins are higher in the dry season. PH and COD exhibited considerable spatial variations within basins, while dissolved oxygen (DO) and ammonia nitrogen (NH 4 +-N) showed smaller variations. RDA showed that land use had a more pronounced effect on water quality during the dry season in the Yangtze, Liao and Pearl River Basins, while the impact was greater in the wet season in the four basins of the Yellow, Huai, Hai and Songhua River Basins. At the spatial scale, the 2000 m buffer zone had the most significant impact within the Yangtze, Hai and Liao River Basins, while the 1000 m buffer zone had the greatest impact in the Huai and Pearl River Basins. For the Yellow and Songhua River Basins, the buffer zone was 500 m during the wet season and 1000 m and 2000 m during the dry season, respectively. The research findings can offer a scientific foundation for the development of basin-specific land management policies and water quality protection measures in different basins from a multi-scale perspective. [ABSTRACT FROM AUTHOR]