Carrying Capacity and Coupling Coordination of Water and Land Resources Systems in Arid and Semi-arid Areas: A Case Study of Yulin City, China

Quantitatively assessing the carrying capacity of water and land resources systems in arid and semi-arid areas is crucial for achieving the 2030 Sustainable Development Goals.In this work,taking Yulin City in China as a case study and employing the Criteria Importance Through Intercriteria Correlation(CRITIC)method,a modified model of coupling degree was developed to evaluate the car-rying capacity of water and land resources systems endowment and utilization,as well as their coupling coordination degree from 2013 to 2020.Our findings indicate that the water and land resources of Yulin are diminishing due to declines in agriculture,higher industrial water use,and wetland shrinkage.However,reallocating domestic water for ecological sustainability and reducing sloping farmland can mitigate this trend of decline.Temporally,as the coupling coordination between water and land resources system endowment in Yulin continuously improved,the coupling coordination between water and land resources system utilization first decreased and then in-creased with 2016 as the turning point.Spatially,the carrying capacity of water and land resources systems,the coupling coordination degree between water and land resources system endowment,and the coupling coordination degree between water and land resources system utilization in Yulin exhibited the same pattern of being higher in the six northern counties than in the six southern counties.Improving the water resources endowment is vital for the highly efficient use of water and land resources.

Enhancing transboundary natural tourism resources governance:unveiling the spatial pattern and its influencing factors

Tourism resources that span provincial boundaries in China play a pivotal role in regional development,yet effective governance poses persistent challenges.This study addresses this issue by constructing a comprehensive database of transboundary natural tourism resources(TNTR)through amalgamation of diverse data sources.Utilizing the Getis-Ord Gi^(*),kernel density estimation,and geographical detectors,we scrutinize the spatial patterns of TNTR,focusing on both named and unnamed entities,while exploring the influencing factors.Our findings reveal 7883 identified TNTR in China,with mountain tourism resources emerging as the predominant type.Among provinces,Hunan boasts the highest count,while Shanghai exhibits the lowest.Southern China demonstrates a pronounced clustering trend in TNTR distribution,with the spatial arrangement of biological landscapes appearing more random compared to geological and water landscapes.Western China,characterized by intricate terrain,exhibits fewer TNTR,concurrently unveiling a significant presence of unnamed natural tourism resources.Crucially,administrative segmentation influences TNTR development,generating disparities in regional goals,developmental stages and intensities,and management approaches.In response to these variations,we advocate for strengthening the naming of the unnamed transboundary tourism resources,constructing a geographic database of TNTR for government and establishing a collaborative management mechanism based on TNTR database.Our research contributes to elucidating the intricate landscape of TNTR,offering insights for tailored governance strategies in the realm of cross-provincial tourism resource management.

Off-farm employment,agriculture production activities,and household dietary diversity in environmentally and economically vulnerable areas of Asia

Access to off-farm employment has been expected to be a critical approach to ending hunger and all forms of malnutrition,two important targets of achieving Zero Hunger.This study aims to investigate the role of off-farm employment in improving dietary diversity through substitution effect and complementary effect with agricultural production activities and income effect.This study adopts Poisson/Tobit/Probit/OLS regressions and the instrument variable method based on the primary survey data collected among 1,282 households at 12 sites in environmentally and economically vulnerable areas of China,Nepal,Cambodia,Thailand,and Myanmar in 2019.The results show that off-farm employment is positively associated with household dietary diversity and the consumption of flesh meat,fish and other aquatic animals,fruits,and milk and dairy products,which are rich in protein and micronutrients.The results of mechanism analysis show that off-farm employment contributes to household dietary diversity by improving crop diversity,especially for poor households,boosting the probability of livestock raising for households with the middle one-third disposal income,and increasing household income.The positive association between off-farm employment and household dietary diversity is much higher for households with the bottom one-third disposal income,low illiteracy,and from upper-middle income countries.These findings imply that off-farm employment does play a vital role in achieving multiple benefits of poverty alleviation,malnutrition reduction,and agrobiodiversity conservation in environmentally and economically vulnerable areas.However,it may enlarge the gaps in dietary diversity between households with low human capital and from low and lower-middle income countries and those with high human capital and from middle-high countries.

Species-specific and generalized allometric biomass models for eight Fagaceae species in the understory of evergreen broadleaved forests in subtropical China

Quantifying the biomass of saplings in the regeneration component is critical for understanding biogeochemical processes of forest ecosystems.However,accurate allometric equations have yet to be developed in sufficient detail.To develop species-specific and generalized allometric equations,154 saplings of eight Fagaceae tree species in subtropical China’s evergreen broadleaved forests were collected.Three dendrometric variables,root collar diameter(d),height(h),and crown area(ca)were applied in the model by the weighted nonlinear seemingly unrelated regression method.Using only d as an input variable,the species-specific and generalized allometric equations estimated the aboveground biomass reasonably,with R _(adj)^(2) values generally>0.85.Adding h and/or ca improved the fitting of some biomass components to a certain extent.Generalized equations showed a relatively large coefficient of variation but comparable bias to species-specific equations.Only in the absence of species-specific equations at a given location are generalized equations for mixed species recommended.The developed regression equations can be used to accurately calculate the aboveground biomass of understory Fagaceae regeneration trees in China’s subtropical evergreen broadleaved forests.

Deformation,structure and potential hazard of a landslide based on InSAR in Banbar county,Xizang(Tibet)

The Tibetan Plateau is characterized by complex geological conditions and a relatively fragile ecological environment.In recent years,there has been continuous development and increased human activity in the Tibetan Plateau region,leading to a rising risk of landslides.The landslide in Banbar County,Xizang(Tibet),have been perturbed by ongoing disturbances from human engineering activities,making it susceptible to instability and displaying distinct features.In this study,small baseline subset synthetic aperture radar interferometry(SBAS-InSAR)technology is used to obtain the Line of Sight(LOS)deformation velocity field in the study area,and then the slope-orientation deformation field of the landslide is obtained according to the spatial geometric relationship between the satellite’s LOS direction and the landslide.Subsequently,the landslide thickness is inverted by applying the mass conservation criterion.The results show that the movement area of the landslide is about 6.57×10^(4)m^(2),and the landslide volume is about 1.45×10^(6)m^(3).The maximum estimated thickness and average thickness of the landslide are 39 m and 22 m,respectively.The thickness estimation results align with the findings from on-site investigation,indicating the applicability of this method to large-scale earth slides.The deformation rate of the landslide exhibits a notable correlation with temperature variations,with rainfall playing a supportive role in the deformation process and displaying a certain lag.Human activities exert the most substantial influence on the spatial heterogeneity of landslide deformation,leading to the direct impact of several prominent deformation areas due to human interventions.Simultaneously,utilizing the long short-term memory(LSTM)model to predict landslide displacement,and the forecast results demonstrate the effectiveness of the LSTM model in predicting landslides that are in a continuous development and movement phase.The landslide is still active,and based on the spatial heterogeneity of landslide deformation,new recommendations have been proposed for the future management of the landslide in order to mitigate potential hazards associated with landslide instability.

Failure evaluation and control factor analysis of slope block instability along traffic corridor in Southeastern Tibet

The instability of slope blocks occurred frequently along traffic corridor in Southeastern Tibet(TCST),which was primarily controlled by the rock mass structures.A rapid method evaluating the control effects of rock mass structures was proposed through field statistics of the slopes and rock mass structures along TCST,which combined the stereographic projection method,modified M-JCS model,and limit equilibrium theory.The instabilities of slope blocks along TCST were then evaluated rapidly,and the different control factors of instability were analyzed.Results showed that the probabilities of toppling(5.31%),planar(16.15%),and wedge(35.37%)failure of slope blocks along TCST increased sequentially.These instability modes were respectively controlled by the anti-dip joint,the joint parallel to slope surface with a dip angle smaller than the slope angle(singlejoint),and two groups of joints inclined out of the slope(double-joints).Regarding the control effects on slope block instability,the stabilization ability of doublejoints(72.7%),anti-dip joint(67.4%),and single-joint(57.6%)decreased sequentially,resulting in different probabilities of slope block instability.Additionally,nearby regional faults significantly influenced the joints,leading to spatial heterogeneity and segmental clustering in the stabilization ability provided by joints to the slope blocks.Consequently,the stability of slope blocks gradually weakened as they approached the fault zones.This paper can provide guidance and assistance for investigating the development characteristics of rock mass structures and the stability of slope blocks.

Drivers,Trends,and Patterns of Changing Vegetation-greenness in Nansha Islands,China from 2016 to 2022

Changes in vegetation status generally also represents changes in the ecological health of islands and reefs(IRs).However,studies are limited of drivers and trends of vegetation change of Nansha Islands,China and how they relate to climate change and human activities.To resolve this limitation,we studied changes to the Normalized Difference Vegetation Index(NDVI)vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions.Trends of vegetation greenness were analyzed using Sen's slope and Mann-Kendall test at two spatial scales(pixel and island),and driving factor analyses were performed by time-lagged partial correlation analyses.These were related to impacts from human activities and climatic factors under normal(temperature,precipitation,radiation,and Normalized Difference Built-up Index(NDBI))and extreme conditions(wind speed and latitude of IRs)from 2016 to 2022.Results showed:1)among the 22 IRs,NDVI increased/decreased significantly in 15/4 IRs,respectively.Huayang Reef had the highest NDVI change-rate(0.48%/mon),and Zhongye Island had the lowest(–0.29%/mon).Local spatial patterns were in one of two forms:dotted-form,and degradation in banded-form.2)Under normal conditions,human activities(characterized by NDBI)had higher impacts on vegetation-greenness than other factors.3)Under extreme conditions,wind speed(R^(2)=0.2337,P<0.05)and latitude(R^(2)=0.2769,P<0.05)provided limited explanation for changes from typhoon events.Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations‘Ocean Decade’initiative.

Ecological environmental quality evaluation and driving factor analysis of the Lijiang River Basin,based on Google Earth Engine

For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.

Irrigation and nitrogen fertiliser optimisation in protected vegetable fields of northern China:Achieving environmental and agronomic sustainability

Globally,sub-optimal use of nitrogen (N) fertiliser and elevated N irrigation groundwater have led to high leached nitrate (NO_(3)^(–)) losses from protected vegetable field systems.Optimising fertiliser and irrigation management in different soil types is crucial to reduce future N loads from such systems.The present 4-year study examined leached N loads from lysimeter monitoring arrays set up across 18 protected vegetable system sites encompassing the dominant soil types of northern China.The treatments applied at each field site were:1) a high N and high irrigation input treatment (HNHI);2) a low N but high irrigation input treatment (LNHI) and 3) a low N with low irrigation input treatment (LNLI).Results showed that the mean annual leached total nitrogen loads from the HNHI,LNHI and LNLI treatments were 325,294 and 257 kg N ha^(–1) in the fluvo-aquic soil,114,100 and 78 kg N ha^(–1) in the cinnamon soil and 79,68 and 57 kg N ha^(–1) in the black soil,respectively.The N dissolved in irrigation water in the fluvo-aquic soil areas was 8.26-fold higher than in the cinnamon areas.A structural equation model showed that N fertiliser inputs and leaching water amounts explained 14.7 and 81.8%of the variation of leached N loads,respectively.Correspondingly,reducing irrigation water by 21.5%decreased leached N loads by 20.9%,while reducing manure N and chemical N inputs by 22 and 25%decreased leached N loads by only 9.5%. This study highlights that protected vegetable fields dominated by fluvo-aquic soil need management to curtail leached N losses in northern China.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Attributes of Specialized Households'Resilience and Its Impact on Rural Industrial Advancement:A Case Study of National Musical Instrument Production Specialized Households in Lankao County,Henan,China

Specialized households serve as the primary units within specialized villages in China,and their capacity to withstand risks and external influences significantly shapes the future trajectory of specialized villages and the overall vitality of the rural economy.In this study,we established a measurement indicator system based on the definition of specialized households’resilience,elucidating the logical connection between specialized households’resilience and rural industrial development in China.The musical instrument industry in Lankao County,Henan Province of China,was employed as a case;survey data,the entropy method,and an obstacle diagnosis model were used to examine how instrument production specialized households responded to the challenges posed by Corona Virus Disease 2019(COVID-19)and the tightening of national environmental protection policies,yielding the following key findings:1)there exists substantial variation in the comprehensive resilience levels among different specialized households;2)the ability to learn and adapt is the most significant contributor to the overall resilience level of specialized households;3)technological proficiency and access to skilled talent emerge as pivotal factors influencing specialized households’resilience;4)the positioning of specialized households within the industrial supply chain and the stability of their income have a direct bearing on their resilience level.The influence of specialized households’resilience on industrial development primarily manifests in the following ways:stronger resilience correlates with increased stability in production and sales,fostering a more proactive approach to future actions.However,heightened exposure to the external macroeconomic environment can lead to a higher rate of export reduction.To enhance the development resilience of entities like specialized households and family farms,and to invigorate rural economic development,escalating investments in rural science and technology and prioritizing the training of technical talent become imperative.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

Parameterization, sensitivity, and uncertainty of 1-D thermodynamic thin-ice thickness retrieval

Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input variables.This article examines the deviation of the classical model’s TIT output when using different parameterization schemes and the sensitivity of the output to the ice thickness.Moreover,it estimates the uncertainty of the output in response to the uncertainties of the input variables.The parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow conductivity.Measured input parameters include air temperature,ice surface temperature,and wind speed.Among the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice conductivity.The sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and depth.The retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved data.From in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be high.The resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement error.The results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and−0.005 m,respectively.

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin,China

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

Assessment of Nitrogen Fixation, Uptake, and Leaching in Maize/Soybean Intercropping System at Varied Soil Depths and under Phosphorus Application in Chinese Agricultural Settings

The study of Nitrogen fixation, uptake, and leaching at different soil depths in the co-cultivation of maize and soybean under phosphorus fertilization is important for sustainable agriculture. This study was conducted in Quzhou, Hebei Province, China, with MC812 maize and Jidou12 soybean varieties. Soil samples were taken from each plot to create a composite sample. The results show that nitrogen concentration varies at different depths and is higher in all treatments between 40 and 100 cm. Incorporating intercropping of maize and soybeans into farming practices can lead to more sustainable and environmentally friendly agriculture in China.

Assessing the Influence of Phosphorus Fertilization on the Growth and Yield of Maize/Soybean Intercrop by Analyzing Nitrogen Uptake

Intercropping, particularly the combination of maize and soybeans, has been widely recognized for its potential to improve nitrogen uptake and promote sustainable agriculture. This study examines the patterns of nitrogen uptake in maize and soybean intercropping systems under different growth stages and phosphorus fertilization levels and investigates the influence of nitrogen uptake on growth parameters such as plant height, leaf area, and biomass accumulation in the maize/soybean intercrop under different phosphorus fertilization regimes. The study also collected chlorophyll samples at different growth stages of maize in monoculture and intercropping with maize or soybean. The results showed that plant height was greater in V10 in both fertilized and unfertilized treatments for intercropped maize and soybean, and chlorophyll concentration was higher in VT intercropped maize. The results also showed a higher accumulation of biomass. Understanding the growth dynamics of these plants in monoculture and intercropping systems and the impact of fertilization practices is crucial for optimizing crop productivity and sustainability in agricultural systems.

The Impact of the Energy Transition and Sustainable Development Goals on Mineral Resource Availability in Africa

Understanding and predicting the impact of the global energy transition and the United Nations Sustainable Development Goals (SDGs) on global mineral demand and African supply is challenging. This study uses a resource nexus approach to investigate and analyze the impact of this transition on energy and water demand and CO2 emissions using three annual material demand scenarios. The results indicate that African mining will consume more energy by 2050, leading to an increase in cumulative demand for energy (from 98 to 14,577 TWh) and water (from 15,013 to 223,000 million m3), as well as CO2 emissions (1318 and 19,561 Gg CO2e). In contrast, only a modest increase in energy demand (207 TWh) will be required by 2050 to achieve the SDGs. Therefore, the African mining industry should reduce its energy consumption and invest more in the renewable energy sector to support the global energy transition.

Spatial Equity of Basic Education Resources and Coordinated Regional Development in Xinjiang, China

Public services,including education,are important elements that affect people’s living standards.Promoting spatial equity in education resources is a crucial indicator of China’s coordinated regional development in the new era.Xinjiang,a border area and home to many ethnic minorities,is a relatively underdeveloped region in China.Optimizing the cross-regional allocation of basic education resources and forming a coordinated regional development is of great significance for achieving the general goal of social stability and long-term peace in Xinjiang.This study adopts a spatial equity analysis framework that incorporates spatial scale,time dimension,factor indicators,and educational stages.The Gini coefficient is used to examine the variability of spatial equity of educational resources in Xinjiang.Results show that the spatial variability of educational resources in Xinjiang increases as the spatial scale becomes lower.The coefficients of variability at provincial,prefectural,and county levels are 0.207,0.257,and 0.302,respectively.The spatial variability shows an increasing trend before 2010 and decreases significantly after 2010.In terms of elementary indicators,the spatial variability of the number of schools per 10000 people is the largest,with Gini coefficients in the range of 0.207-0.302.The teacher-student ratio has a Gini coefficient in the range of 0.068-0.174,and class size has a Gini coefficient in the range of 0.040-0.058.In terms of educational stages,the spatial variability is most prominent in elementary schools,with a coefficient of variation of 0.246-0.339.Senior high schools have a coefficient of variation of 0.220-0.260,while junior high schools are the most balanced,with a coefficient of variation of0.181-0.235.The study also discussed the coupling and coordination relationship between educational resources and regional economic development in Xinjiang.Economic development plays a facilitating role in promoting balanced education,and the coupling and coordination is higher in northern Xinjiang than in southern Xinjiang.The 14 regions and states in Xinjiang form a high-high coordination type,a medium-medium coordination type,and a high-low uncoordinated type.Finally,the study analyzed the reasons for the spatial equity variability of educational resources,including administrative governance levels,information technology construction levels,common national language penetration,and superior talent attraction environments.

Spatial pattern of urban-rural integration in China and the impact of geography

Urban-rural integration (URI) is a global challenge that is highly related to inequalities, poverty, economic growth, and other Sustainable Development Goals (SDGs). Existing research has evaluated the extent of URI and explored its influencing factors, but urban-rural linkages are seldom incorporated in evaluation systems, and geographical factors are rarely recognized as the influencing factors. We construct a URI framework including regional economy, rural development, urban-rural linkage, and urban-rural gap. Based on a dataset consisting of 1,669 counties in China in 2020, we reveal the spatial pattern of URI and find a high correlation between the spatial pattern of URI and the relief degree of land surface (RDLS). Using structural equation modeling, we discover that topography has direct ( − 0.18, p < 0.001) and indirect ( − 0.17, p < 0.001) effects on URI. The indirect negative effects are mediated through the infrastructure, and the combination of localized advantages and modern technical conditions could mitigate the negative impact of topography. Finally, we identify 742 counties as lagging regions in URI, which can be clustered into eight types. Our findings could facilitate policy designing for those countries striving for integrated and sustainable development of urban and rural areas.

The indispensable role of resilience in rational landslide risk management for social sustainability

Landslide disasters reflect the conflict between human society and the natural environment,posing challenges to the sustainable development of mountain regions.Identification of potential landslides,estimation of the degree of damage and potential losses of elements at risk,and control of the loss are the major tasks of landslide risk management.Resilience is defined as a social system’s comprehensive abilities to cope with disasters,including the abilities to prepare,anticipate,preserve,absorb,respond,resist,recover,mitigate,learn,and adapt.As an indispensable role,resilience enables more rational landslide risk management for social sustainability.However,quantitative landslide risk management does not pay sufficient attention to the role of resilience.Hence,in this paper,the role of resilience in a landslide risk management framework is systematically discussed.A quantita-tive landslide risk management framework consists of hazard analysis,exposure analysis,risk estimation,risk evaluation,and risk control.In hazard analysis,resilience assessment could help identify potential landslides that could cause significant damage due to the poor resilience of the elements at risk.Resilience assessment in exposure analysis might aid in identifying the most vulnerable elements or regions to certain landslides.Consid-eration of resilience in risk estimation aids in the calculation of indirect losses and improves the results of direct losses analysis.In risk evaluation,resilience as a disaster-coping ability will impact the social system’s landslide risk tolerance threshold.Enhancing resilience is an essential strategy to reduce the vulnerability of social sys-tems.We also proposed that the efficient use of risk information will increase the accuracy of landslide resilience assessments.