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As a national strategy, the development of the Yangtze River Economic Belt (YREB) and the ecological protection and high-quality development (HQD) of the Yellow River Basin (YRB) are of great significance for promoting the HQD of the regional economy. Based on the panel data in the YRB and the YREB from 2006 to 2019, this paper constructed an evaluation index system of HQD with five dimensions of "innovation development, coordination development, green development, openness development, and sharing development", and we used the entropy weight method, kernel density method, and Tobit panel model to analyze the differences in the HQD and the similarities and differences of the influencing factors between the two regions. The research findings were as follows: (1) The HQD of the YRB and the YREB was consistent with the national trend, showing a fluctuating upward trend. The HQD of the YRB was always lower than that of the YREB. The kernel density curves in both regions had a rightward trailing pattern, with polarization and unbalanced development. (2) From the perspective of the spatial distribution pattern, the HQD of the YRB presented a spatial distribution characteristic of "high at both ends and low in the middle". In contrast, the HQD of the YREB maintained the characteristic of "high in the east and low in the west". (3) The level of human capital, the level of foreign direct investment, and the economic scale played a significant positive role in improving the HQD of the YRB. The level of human capital, urbanization, foreign direct investment, and economic scale significantly improved the HQD of the YREB. [ABSTRACT FROM AUTHOR]

As human society is entering an era of scarce natural resources, realizing the welfare level of human society is a fundamental requirement to improve sustainable development, while being restrained by the ecological environment. In this paper, we divided ecological welfare performance (EWP) into an ecological economic system and an economic welfare system from the perspective of ecological welfare, and predicted the EWP in the Yellow River Basin Urban Agglomerations (YRBUAs) using the US-NSBM model in two stages. We further explored the dynamic change trend and spatial convergence characteristics in the YRBUAs using the Dagum Gini coefficient, the kernel density estimation method, and the spatial convergence models. The results indicate that there are great spatial variations in EWP in the YRBUAs, where the spatial variation in the downstream is higher than that in the upstream, and the spatial distribution pattern in large- and medium-sized cities is higher than that in small cities. The DEA efficiency could not be realized overall throughout the study period, but it shows an improving trend. At the same time, absolute β convergence and conditional β convergence were observed in the YRBUAs, both overall and between the UAs. This paper provides a basis for analyzing the spatial pattern of EWP and for promoting the coordinated development of urban agglomerations in the YRBUAs, thus serving as a reference for the sustainable development of ecologically sensitive regions in countries across the world. [ABSTRACT FROM AUTHOR]

Ecosystem services are the beneficial goods and services that ecosystems provide to humans. Urbanization is an important feature of human social development. While promoting economic and social development, it also brings about land degradation, resource depletion, environmental pollution and other problems, intensifying the transformation of natural ecosystems into semi-natural and artificial ecosystems, ultimately leading to the loss of ecosystem service functions and declining value. The study of the impact of urbanization on the value of ecosystem services is of critical importance for the conservation of ecosystems and sustainable development. This study examined the spatio-temporal patterns of urbanization's impacts on ecosystem service value in the Yellow River Basin from the perspective of spatio-temporal heterogeneity. Findings: (1) Both the ecosystem service value (ESV) and urbanization level (UL) in the Yellow River Basin were on the rise on the whole, but they were significantly spatially negatively correlated and mainly characterized by the high–low spatial clustering of "low ESV–high UL" and "high ESV–low UL". This negative correlation was gradually weakened with the transformation of the urbanization development mode and ecological restoration projects in the Yellow River Basin. (2) The impacts of the five urbanization subsystems on the value of ecosystem services were diverse. Landscape urbanization had a negative impact on the value of ecosystem services in all regions; economic urbanization and innovation urbanization changed from having a negative to a positive impact; and demographic urbanization and social urbanization had both a positive and a negative impact. (3) To promote the coordinated development of ecological environmental protection and urbanization in the YRB, this paper proposes to change the urbanization development model, implement ecological restoration by zoning, and formulate classified development plans. This study compensates for the shortcomings of current studies that ignore the different impacts of urbanization subsystems on ecosystem service value and lack sufficient consideration of the spatio-temporal heterogeneity characteristics of urbanization and ESVs, enriches the theoretical understanding of the interrelationships between natural and human systems in basin areas, and provides a scientific basis for the rational formulation of urban planning and ecological protection policies in the region, which is of great theoretical and practical significance. [ABSTRACT FROM AUTHOR]

The Yellow River Basin assumes an important ecological and economic function in China. The study of carbon emissions from land use in the nine provinces (regions) of the pathway is important to achieve carbon reduction. Based on the dynamic data of land use, energy, and economic changes in nine provinces (regions) for the past 30 years from 1990 to 2018, this study analyzed the spatial and temporal evolution characteristics of land-use carbon emissions by using the carbon emission coefficient method in the IPCC inventory method and evaluating the low-carbon development model of the nine provinces (regions) by land-use carbon emission intensity. Finally, the LMDI model was used to analyze the factors influencing land-use carbon emissions. The results showed that: (1) in the past 30 years, the net carbon emissions have shown a continuously increasing trend, and the difference in the spatial distribution of carbon emissions in different periods was obvious. The carbon sink effect was not significant enough to offset the carbon emissions generated. (2) The continuously decreasing carbon emission intensity values per unit of GDP indicate that the coordination between land-use and economic development was getting better. (3) The factors of population size, economic size, and land-use structure accelerated land-use carbon emissions, whereas land-use efficiency limited land-use carbon emissions. Accordingly, this paper puts forward some corresponding policy suggestions. [ABSTRACT FROM AUTHOR]

The urban agglomerations in the Yellow River Basin are important carriers for China’s high-quality development. It is an inevitable trend to promote sustainable development and people’s well-being in the urban agglomerations of the Yellow River Basin. A case study of 70 cities of seven urban agglomerations in the Yellow River Basin from 2011 to 2017 is presented. The two-stage super-efficiency network slacks-based measure (Super-NSBM) model considering undesirable outputs is adopted to measure the ecological well-being performance (EWP), and the spatial correlation analysis method is used to analyze the spatio-temporal evolution characteristics of the EWP. The results show that the average EWP of the seven urban agglomerations in the Yellow River Basin was less than 1, showing a trend of firstly rising and then slowly decreasing. The average EWP presents the distribution pattern of the highest in the middle reaches, followed by the upper reaches, and the lowest in the lower reaches of the Yellow River Basin, respectively. The average ecological economic efficiency in the first stage of urban agglomerations of the Yellow River Basin was greater than the average economic well-being efficiency in the second stage. The average EWP in the Yellow River Basin shows local spatial heterogeneity during the study period. Policy measures are proposed to promote the improvement of the EWP of urban agglomerations in the Yellow River Basin. This study can provide reference for the policy formulation of high-quality green development and sustainable construction of urban agglomeration in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Land use change has a significant impact on the sustainability of ecosystems, and ecological security patterns (ESPs) can improve environmental quality through spatial planning. This study explored a multi-scenario ESP framework by integrating future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomeration along the Yellow River Basin (YRB) in Ningxia. The research involved simulating land use change in 2035 under four development scenarios, identifying ecological security networks, and evaluating network stability for each scenario. The study revealed that the ecological sources under different development scenarios, including a natural development scenario (NDS), an economic development scenario (EDS), a food security scenario (FSS), and an ecological protection scenario (EPS), were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity values (OG) for these scenarios were 0.351, 0.466, 0.334, and 0.520, respectively. It was found that under an EPS, the ESPs had the largest area of ecological sources and the most stable ecological network structure, which can effectively protect natural habitats. This study provides a valuable method for identifying ESPs that can respond to diversity and the uncertainty of future development. It can assist decision-makers in enhancing the ecological quality of the study area while considering various development scenarios. [ABSTRACT FROM AUTHOR]

With rapid industrialization and urbanization, the contradiction between the human exploitation of land production and living functions and natural ecosystem service functions has intensified. The issues of how to coordinate the exploitation and conservation functions of land and guide the rational distribution of human activities have become important for global sustainable development, especially considering the realization that multifunctional land use is an effective way to relieve land pressure and improve land use efficiency, that land multifunction has significant spatio-temporal heterogeneity, and that there is a mutual promotion and stress relationship between multifunctional land use. However, few existing studies have discussed the decoupling relationship among land use functions. In this study, a system of 10 sub-functions and 25 indicators was established based on the production function (PDF), living function (LVF), and ecological function (ELF) for 59 cities in the Yellow River Basin (YRB). There are both subjective and objective procedures employed to determine the weights, while an exploratory spatial data analysis is used to analyze the time-based and territorial changes in various functions of land use in the study area from 2000 to 2020. The decoupling relationship between the three functions is detected utilizing the theoretical foundation of the decoupling analysis. The results show that land use is multifunctional, LUFs develop unevenly, and their spatial distribution varies substantially. The results of the decoupling analysis demonstrate that the predominant types of correlations among the land use ELF and PDF and LVF over the research period are strong decoupling and strong negative decoupling correlations, with the former being a dilemma and the latter being a sustainable type of development. [ABSTRACT FROM AUTHOR]

Continued urban expansion (UE) has long been regarded as a huge challenge for climate change mitigation. However, much less is known about how UE affects carbon emissions (CEs), especially in the urban agglomerations of the Yellow River Basin (UAYRB), China. In this regard, this study introduced kernel density analysis, the Gini coefficient, and Markov chains to reveal the UE patterns and carbon emissions intensity (CEI) in the UAYRB at the county level, and explored the spatial heterogeneity of the impact of UE on CEI with the geographically and temporally weighted regression model. The results show that both CEI and UE in the UAYRB showed a steady growing trend during the study period. The kernel density of CEI and UE revealed that CEI in the UAYRB was weakening, while the UE rate continuously slowed down. The Gini coefficients of both CEI and UE in the UAYRB region were at high levels, indicating obvious spatial imbalance. The Markov transfer probability matrix for CEI with a time span of five years showed that CEI growth will still occur over the next five years, while that of UE was more obvious. Meanwhile, counties with a regression coefficient of UE on CEI higher than 0 covered the majority, and the distribution pattern remained quite stable. The regression coefficients of different urban landscape metrics on CEI in the UAYRB varied greatly; except for the landscape shape index, the regression coefficients of the aggregation index, interspersion and juxtaposition index, and patch density overall remained positive. These findings can advance the policy enlightenment of the high-quality development of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Ecotourism is vital for coordinating regional ecological protection with socio-economic development. The Gansu section of the Yellow River Basin is a typical ecologically fragile area in China, and it holds a distinctive position in ecological protection and high-quality development. This study explores spatial differentiation in ecotourist perceptions and their distinct effects on ecotourist satisfaction, revisitation, and recommendation. It uses four cities (Gannan, Linxia, Lanzhou, and Baiyin) in the Gansu section of the Yellow River (mainstream) as examples, employing a questionnaire survey to collect ecotourists' perception data and applying a random forest model and one-way ANOVA for analysis. It was found that: (1) rich ecotourism potential exists in the Gansu section of the Yellow River Basin as an ecologically fragile area; (2) there is spatial differentiation in ecotourist perceptions, and among the four regions, Baiyin stands out for its nature and atmosphere perception, and Lanzhou excels in accessibility and service perception; (3) spatial disparities exist in the influencing factors of ecotourist satisfaction, revisitation, and recommendation. Ecotourists in districts with unique natural resources, such as Gannan and Baiyin, prioritize nature perception, whereas districts with abundant natural resources and an established foundation for ecotourism development, such as Linxia and Lanzhou, emphasize service and atmosphere perception. This study constructs a new research framework to explore spatial variations in ecotourists' perceptions, assisting ecotourism destinations to meet the needs of ecotourists from the supply side, and presents distinctive strategies and recommendations for the development of ecotourism in similar ecologically fragile areas. [ABSTRACT FROM AUTHOR]

The Yellow River Basin has been considered to have the most serious soil erosion in the world, and identifying and mapping the spatial controlling factors would be of great help in adopting targeting strategies for soil erosion prevention. This study used the Universal Soil Loss Equation (USLE) to estimate the spatial and temporal changes in soil erosion from 1985 to 2020 and analyzed the controlling factors. The results indicated that from 1985 to 2020, the average erosion modulus in the Yellow River Basin was 1160.97 t∙km−2∙yr−1, and the erosion modulus in the middle reach was significantly greater than in the lower and upper reaches. Changes in vegetation coverage, rainfall and land use controlled 38.95%, 40.87% and 9.21% of soil erosion changes, respectively. Among them, the area in which soil erosion was decreased due to increased vegetation coverage accounted for 70.77% of the area controlled by vegetation coverage, while the area in which soil erosion was increased due to increased rainfall accounted for 86.62% of the area controlled by rainfall. These results prove the effectiveness of vegetation restoration projects in controlling soil erosion in the Yellow River Basin, but more attention needs to be paid to the impact of rainfall on soil erosion in the future. [ABSTRACT FROM AUTHOR]

An evaluation index system was conducted to determine the urban comprehensive carrying capacity of the Yellow River Basin using four subsystems (resources, society, ecology, and economy). The urban comprehensive carrying capacity level of nine provinces in the Yellow River Basin from 2008 to 2019 was determined using the entropy weight TOPSIS model, and the spatial and temporal dynamics of the urban comprehensive carrying capacity of each province were investigated. There were four key results. (1) The urban comprehensive carrying capacity of the upstream and downstream provinces decreased from 2008 to 2011 and increased from 2011 to 2019; in the midstream provinces, it increased from 2008 to 2011 but decreased after 2011. (2) The urban comprehensive carrying capacity of the Yellow River Basin was "high in the east and west, low in the middle" from 2008 to 2017, while in 2019, the distribution was "high in the west and low in the east." The gap between the urban comprehensive carrying capacities of the nine provinces and regions gradually narrowed over the study period. (3) The urban comprehensive carrying capacity of the Yellow River Basin increased annually during the study period. (4) The urban comprehensive carrying capacity was mainly influenced by the social and ecological subsystems. [ABSTRACT FROM AUTHOR]

Spatiotemporal studies of landscape pattern evolution in traditional villages are beneficial for addressing complex urbanization and global climate change. Using the traditional villages of Jiaxian and Linxian in the Jinshaan Gorge of the Yellow River Basin, this study employed a three-dimensional (3D) analysis involving three spatial scales (macro, meso, and micro), temporal scales (past, present, and future), and variables (humanity, society, and nature) based on the methods of spatiotemporal data analysis (SDA), geographic information system, remote sensing, and landscape pattern index (LPI) by Fragstats. On the macro scale, a significant turning point in ecological conservation awareness was indicated by LPI and SDA. Urban and rural construction land continuously increased because of urbanization. Plowland, grassland, and woodland were the main influencing factors in the evolution of rural settlements, with a 0.42% cumulative transformation rate. On the meso scale, the interactions and mutual promotion of mountain and aquatic environments, aquatic facilities, agricultural production, and cultural heritage have shaped the socioeconomic dimensions of evolution. On the micro scale, with urbanization, some traditional humanistic spaces have lost their original functions. A novel spatiotemporal-variable quantitative model explored the spatiotemporal evolution characteristics of human–land coupling, which can be used for the sustainable development of river basins worldwide. [ABSTRACT FROM AUTHOR]

Located in the middle and upper parts of the Yellow River Basin, Qingshuihe County, Inner Mongolia, is a typical hilly and gully loess region and one of areas under the implementation of major ecological protection and restoration projects in the key ecological areas of Yellow River. Scientifically and accurately constructing a soil quality evaluation system for different types of artificial forest land and evaluating their soil quality are essential because they help optimize the structure of artificial forest land and improve the soil quality in the loess hilly area of Yellow River Basin. In this study, soil from four representative types of artificial forest land in the middle and upper reaches of the Yellow River Basin in Inner Mongolia was selected as the study object, with natural non-forest land as the control. Sixteen soil property indices in five classes, namely, soil texture, acid–base properties, moisture, pore, and nutrient, were screened using correlation analysis, minimum dataset (MDS), and principal component analysis methods, and an MDS of soil quality evaluation was constructed. Results showed that (1) the evaluation indices of artificial forest land soil quality based on the MDS included total potassium content, total phosphorus content, alkali-hydrolyzed nitrogen content, total nitrogen content, sand content, moisture content, and non-capillary porosity. (2) No significant differences were observed in the soil quality index among the MDS, total dataset, and significant dataset (SDS), all of which exhibited significant positive correlations. (3) The soil quality of the different types of forest land was sorted from high to low as follows: mixed coniferous and broad-leaved forests, larch forests, mixed arbor and shrub forests, Armeniaca sibirica forests, and natural non-forest land. [ABSTRACT FROM AUTHOR]

Governmental attention towards the high-quality development of the Yellow River basin has brought new development opportunities for the hotel industry. This study aims to reveal the spatial-temporal evolution patterns and influencing factors of hotels in the Yellow River Basin from 2012 to 2022, based on economic, social, and physical geographic data of 190,000 hotels in the Yellow River flowing. With the help of a GIS technology system, the spatial-temporal evolution patterns of all hotels, star hotels, and ordinary hotels were explored, respectively. Then, the significant influencing factors of these patterns were revealed by using geographic detector and Person correlation analysis. The following conclusions were drawn: (1) the overall scale of the hotel industry in the Yellow River Basin expanded year by year, achieving rapid growth from 2016, and fluctuating around 2020 due to the impact of the novel coronavirus epidemic; the overall spatial distribution had significant regional differences, showing the structural characteristics of "southeast more, northwest less"; (2) there was a great difference in the degree of spatial autocorrelation agglomeration among prefecture-level cities, and the degree of agglomeration of both the hotel industry as a whole and general hotels decreased year by year, showing a random distribution in 2022; star hotels were always distributed randomly. Additionally, a strong synergistic correlation was shown between the number of ordinary hotels and the number of star hotels in local space; (3) overall, the development of the hotel industry was significantly affected by seven factors: structural force, macro force, ecological force, internal power, consumption power, intermediary power, and external power. There were differences in the forces acting on different types of hotels, which gives a pattern recognition in-depth. [ABSTRACT FROM AUTHOR]

Ecological restoration is an important implement to avoid land degradation and improve the sustainability of ecosystems. As a spatial definition of ecological restoration, ecological restoration space (ERS) is recognized to have a positive impact on the environment. However, its spatiotemporal pattern and magnitude of contribution to ecosystem services (ESs) remain uncertain. In this study, an ecological restoration trajectories model was developed to investigate the spatiotemporal pattern and evolution of ERS. The InVEST model and geographically weighted regression were used to evaluate the dynamic relationship between ERS and crucial ESs. Results demonstrated that from 1990 to 2015, the cumulative area of ERS in the Yellow River Basin (YRB) was 184,197.05 km2, with Inner Mongolia, Qinghai, and Shaanxi having the largest distribution. The change in geographical center of three subcategories, forest restoration space (FRS), grassland restoration space (GRS), and shrub restoration space (SRS), showed a pronounced geographical migration. Meanwhile, the distribution of ERS significantly improved the conditions of habitat quality (HQ), carbon storage (CS), and soil conservation (SC) on 75.48%, 71.86%, and 56.75% of the grids, respectively. This study provides a scientific foundation for the ecosystem conservation and land management of the YRB. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to the increasing scarcity of land resources in China. Exploring the spatial-temporal characteristics and influencing factors of urban land use efficiency (LUE) is of great significance for optimizing the allocation efficiency of land resources and promoting regional sustainable development. In this study, the Super-SBM model was used to calculate the urban LUE of the Yellow River Basin from 2009 to 2018. The regional differences and agglomeration characteristics of LUE in the Yellow River Basin were analyzed. Moreover, a panel regression model was used to analyze the influencing factors of LUE. The results showed that the LUE in the Yellow River Basin experienced a process of fluctuation decline during the study period. The regional difference of LUE in the Yellow River Basin was as follows: upper reaches > middle reaches > lower reaches. The hot and cold spots of LUE were relatively stable in spatial distribution during the study period. The hot spots were mainly distributed in Ordos in the upper reaches and Yulin in the middle reaches, while the cold spots were mainly distributed in Henan Province in the lower reaches. Globalization had a positive impact on LUE in the lower reaches. Marketization had a positive impact on LUE in the whole basin and lower reaches, and a negative impact on LUE in the middle reaches. Decentralization had a positive impact on the LUE of the whole basin and the upper reaches, and a negative impact on the LUE of the lower reaches. [ABSTRACT FROM AUTHOR]

The national strategy for ecological protection and high-quality development is raising the ecological security protection to an unprecedented level in the Yellow River Basin (YRB) of China. Due to the explicitly analyzed land cover changes under climate change and rapid urbanization in the YRB area since 1990, land cover dynamic degree index, transfer matrix, and geo-detector method were used to explicate land cover changes and their key driving factors, based on the spatial data of land cover from 1990 to 2020. The results show that grasslands, croplands, and forests are the main land cover types, accounting for 48.37%, 25.05%, and 13.50%, respectively, of the total area in the YRB area. Grassland, cropland, and cropland are the major land cover type, accounting for 61.49%, 37.13%, and 66.33%, respectively, in the upstream, midstream, and downstream of the YRB area. Built-up land has showed a continual increasing trend, and its dynamic degree was up to 3.38% between 2010 and 2020. Population density was a key factor for land cover change, with an average contribution rate of 0.264; then, elevation and temperature also expressed an important role to drive the land cover change in the YRB area during the period from 1990 to 2020. [ABSTRACT FROM AUTHOR]

The regional differences in the Yellow River Basin have increased, and the aggravation of this unbalanced state has seriously restricted the high-quality development of the Yellow River Basin during the accelerated urbanisation that has taken place in recent years. In this regard, heterogeneity in the trends of evolution and the causes of population shrinkage in different regions of the Yellow River Basin can be adopted as targeted countermeasures. The present study uses data from the fifth, sixth, and seventh national censuses and takes the administrative units of different levels in the Yellow River Basin as the object, considering 72 prefecture-level cities within the autonomous prefectures and 595 county-level administrative units in nine provinces (autonomous regions). The population shrinkage coefficient, night light index, bivariate spatial autocorrelation, geographic detectors, and other methods were used, with the final objective of exploring the spatial–temporal distribution pattern and impact mechanism of urban shrinkage from 2000 to 2020. The results of the study show the following: (1) The shrinkage patterns in 2000–2010 (T1) and 2010–2020 (T2) were quite different. From T1 to T2, the shrinkage situation worsened, with the number of districts experiencing population shrinkage increasing from 175 to 373 and the number of districts experiencing continuous night light and shrinkage districts increasing from 146 to 163. (2) The phenomenon of urban shrinkage is spatially scale dependent, with the shrinkage of prefecture-level cities and county-level cities being characterised by both spatial differentiation and spatial nesting relationships. (3) There is a certain inconsistency in the representation of the shrinkage patterns of the nighttime lighting and population data. The nighttime lighting dimension can reflect the structural shrinkage characteristics of the city more accurately and sensitively, and the representation of population loss is lagging. (4) The main impact factors and the intensity of urban shrinkage are the aggravated aging level, the declining level of industrial greening and intensification under market-driven economic structure adjustments, and the decreased natural growth rate in the population structure and public service facilities. [ABSTRACT FROM AUTHOR]

Nighttime light (NTL) images obtained by the Visible Infrared Imaging Radiometer (VIIRS) mounted on the National Polar-orbiting Partnership (NPP) could objectively represent human activities and instantly identify urban shapes on a temporal and spatial scale. From 2013 to 2020, the built-up areas of eight provincial capital cities were extracted using NPP/VIIRS NTL data to examine the dynamic changes in city expansion and socioeconomic development in the Yellow River Basin during the urbanization process. The spatial characteristics of urban built-up area expansion were generated using the eight-quadrant analysis method and combined with the statistical data of population and (gross domestic product) GDP to analyze the correlations between the light intensity of built-up areas, population and GDP; this enables an understanding of the changes in population and economy in the development of urban built-up area expansion. The findings show that: (1) unbalanced city development existed in the Yellow River Basin's upper, middle, and lower reaches, and the expansion and light intensity of cities in the upper reaches were slower than those in the middle and lower reaches; (2) the spatial differentiation of urban expansion was significant between each of the reaches in the Yellow River Basin, and greatly influenced by natural geographical elements; and (3) positive correlation exists between light intensity, population, and GDP in the built-up areas of the middle and lower reaches, while the correlations in the upper reaches were not stable. In conclusion, light data indirectly reflects urban development and could be used as a substitute variable for socioeconomic development indicators under certain conditions. [ABSTRACT FROM AUTHOR]

Production–living–ecological space (PLES) is the main body of the optimization of the development and protection pattern of territorial space, and the spatial conflict in PLES reflects a struggle for ecological protection and socio-economic development in the process of spatial development and utilization. The Yellow River Basin is one of the most concentrated and prominent areas of spatial conflict of PLES in China. Therefore, clarifying the spatio-temporal pattern of PLES of the region and scientifically identifying the characteristics of its spatial conflict will significantly improve the efficiency of comprehensive utilization of spatial resources, promote the integrated and orderly development of resource elements in the basin, and eventually achieve the strategic goals of ecological protection and high-quality development of the Yellow River Basin. In this research, the CA–Markov model was applied to simulate the spatio-temporal pattern of PLES in the Yellow River Basin from 2010 to 2025, and the landscape ecology method was adopted to construct the spatial conflict of the PLES measurement model for identifying the spatio-temporal trends of conflicts and their intensity. The results reveal that, from 2010 to 2025, ecological–production space (EPS) dominates the PLES in the Yellow River Basin, as its total area remains stable amid fluctuations; living–production space (LPS) shows the most notable change, as it grows yearly along with urbanization and industrialization process of the region; the transition between ecological–production space (EPS) and production–ecological space (PES) is the most frequent, and the two also account for the largest area. Spatial conflict of PLES in the Yellow River Basin is mainly reflected in the encroachment of LPS on other PLES, concentrated in the regions from Hekou Town to the left bank of Longmen, Fen River, Shizuishan to the southern bank of Hekou Town, and Daxia River and Tao River in the Yellow River Basin. From 2010 to 2025, the space conflict composite index of PLES (SCCI) of most regions in the basin lies within 0.7, which is a stable or basically controllable level. Among the 29 tertiary water resource divisions in the Yellow River Basin, the SCCI of 15 indicate a major, decreasing trend. [ABSTRACT FROM AUTHOR]

Droughts and floods have proven to be threats to food security worldwide. This research used the standardized precipitation index (SPI) to examine the spatiotemporal characteristics of drought and wet events from 1961 to 2020 in the Yellow River basin (YRB). Grain yield data were combined to assess how drought and wet frequency have affected the agricultural system. The occurrence frequency of drought was greater than that of wetness in time, drought frequency decreased, and wetness increased. Spatially, the frequency of drought in all provinces except Shanxi was higher than that of wetness. The grain yield per unit area of the YRB was generally highest in Shandong province and lowest in Gansu province. The grain yield per unit area have shown a significant growth trend in the nine provinces of the YRB since 1961. Drought had a negative effect on the grain yield per unit area in each province, while wetness had a positive effect on the grain yield per unit area in all provinces except Shandong. In general, the influence of drought on grain yield per unit area decreased, while the influence of wetness on grain yield per unit area increased. The results indicate that human activities are effective against preventing and controlling drought and wet disasters and can provide a reference for other parts of the world. [ABSTRACT FROM AUTHOR]

Land use and land cover change is an important driving force for changes in ecosystem services. We defined several important human-induced land cover change processes such as Ecological Restoration Project, Cropland Expansion, Land Degradation, and Urbanization by the land use/land cover transition matrix method. We studied human-induced land cover changes in the Yellow River Basin from 1980 to 2015 and evaluated its impact on ecosystem service values by the benefit transfer method and elasticity coefficient. The results show that the cumulative area of human-induced land cover change reaches 65.71 million ha from 1980 to 2015, which is close to the total area of the Yellow River Basin. Before 2000, Ecological Restoration Project was the most important human-induced land cover change process. However, due to the large amount of cropland expansion and land degradation, the area of natural vegetation was reduced and the ecosystem value declined. Since 2000, due to the implementation of the “Grain for Green” program, the natural vegetation of upstream area and midstream area of Yellow River Basin has been significantly improved. This implies that under an appropriate policy framework, a small amount of human-induced land cover change can also improve ecosystem services significantly. [ABSTRACT FROM AUTHOR]