Overview of the Shenzhen Emergency Medical Service Call Pattern

BACKGROUND:In Shenzhen,the Emergency Medical Service(EMS) system has been in service since 1997.This study aims to examine the operation of Shenzhen 120 EMS center and to identify the reasons of calling EMS.METHODS:In this retrospective quantitative descriptive study,the data from the Shenzhen 120 EMS registry in 2011 were analyzed.RESULTS:Shenzhen 120 EMS center is a communication command center.When the number of 120 are dialed,it is forwarded to the closest appropriate hospital for ambulance dispatch.In2011,the Shenzhen 120 EMS center received 153 160 ambulance calls,with an average of 420 calls per day.Calling emergency services was mainly due to traffic accidents.Trauma and other acute diseases constituted a majority of ambulance transports.The adult patients aged 15-60 years are the principal users of EMS.There are no recognized 'paramedic' doctors and nurses.The pre-hospital emergency service is under the operation of emergency departments of hospitals.Shenzhen at present does not have specialized pre-hospital training for doctors and nurses in posttrauma management.Moreover,specialized pre-hospital training,financial support,and public health education on proper use of EMS should be emphasized.CONCLUSION:The Shenzhen 120 EMS center has its own epidemiology characteristics.Traumatic injury and traffic accident are the main reasons for calling ambulance service.In-depth study emphasizing the distribution and characteristics of trauma patients is crucial to the future development of EMS.

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River,China

The identification of dominant driving factors for different ecosystem services(ESs)is crucial for ecological conservation and sustainable development.However,the spatial heterogeneity of the dominant driving factors affecting various ESs has not been adequately elucidated,particularly in ecologically fragile regions.This study employed the integrated valuation of ESs and trade-offs(InVEST)model to evaluate four ESs,namely,water yield(WY),soil conservation(SC),habitat quality(HQ),and carbon storage(CS),and then to identify the dominant driving factors of spatiotemporal differentiation of ES and further to characterize the spatial heterogeneity characteristics of the dominant driving factors in the eco-fragile areas of the upper Yellow River,China from 2000 to 2020.The results demonstrated that WY exhibited northeast-high and northwest-low patterns in the upper Yellow River region,while high values of SC and CS were distributed in central forested areas and a high value of HQ was distributed in vast grassland areas.The CS,WY,and SC exhibited decreasing trends over time.The most critical factors affecting WY,SC,HQ,and CS were the actual evapotranspiration,precipitation,slope,and normalized difference vegetation index,respectively.In addition,the effects of different factors on various ESs exhibited spatial heterogeneity.These results could provide spatial decision support for eco-protection and rehabilitation in ecologically fragile areas.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Deep Reinforcement Learning-Based Task Offloading and Service Migrating Policies in Service Caching-Assisted Mobile Edge Computing

Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.

Cloud Datacenter Selection Using Service Broker Policies:A Survey

Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.

Call for Papers——Feature Topic Vol.22,No.2,2025 Efficient Cooperative Transmission over Satellite Internet for 6G

Satellite Internet,as a strategic public information infrastructure,can effectively bridge the limitations of traditional terrestrial network coverage,support global coverage and deep space exploration,and greatly enhance the range of network information services accessible to humans.With the transition of terrestrial mobile communication networks from the 5G era,which provides access to information anywhere,to the 6G era,which seeks to connect everything,the construction of satellite Internet,which promises a"network reaching everywhere and service is ubiquitous",has become the consensus of the industry's development and the focus of global scientific and technological innovation.

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

Detection of Real-Time Distributed Denial-of-Service (DDoS) Attacks on Internet of Things (IoT) Networks Using Machine Learning Algorithms

The primary concern of modern technology is cyber attacks targeting the Internet of Things.As it is one of the most widely used networks today and vulnerable to attacks.Real-time threats pose with modern cyber attacks that pose a great danger to the Internet of Things(IoT)networks,as devices can be monitored or service isolated from them and affect users in one way or another.Securing Internet of Things networks is an important matter,as it requires the use of modern technologies and methods,and real and up-to-date data to design and train systems to keep pace with the modernity that attackers use to confront these attacks.One of the most common types of attacks against IoT devices is Distributed Denial-of-Service(DDoS)attacks.Our paper makes a unique contribution that differs from existing studies,in that we use recent data that contains real traffic and real attacks on IoT networks.And a hybrid method for selecting relevant features,And also how to choose highly efficient algorithms.What gives the model a high ability to detect distributed denial-of-service attacks.the model proposed is based on a two-stage process:selecting essential features and constructing a detection model using the K-neighbors algorithm with two classifier algorithms logistic regression and Stochastic Gradient Descent classifier(SGD),combining these classifiers through ensemble machine learning(stacking),and optimizing parameters through Grid Search-CV to enhance system accuracy.Experiments were conducted to evaluate the effectiveness of the proposed model using the CIC-IoT2023 and CIC-DDoS2019 datasets.Performance evaluation demonstrated the potential of our model in robust intrusion detection in IoT networks,achieving an accuracy of 99.965%and a detection time of 0.20 s for the CIC-IoT2023 dataset,and 99.968%accuracy with a detection time of 0.23 s for the CIC-DDoS 2019 dataset.Furthermore,a comparative analysis with recent related works highlighted the superiority of our methodology in intrusion detection,showing improvements in accuracy,recall,and detection time.

Influence of varied drought types on soil conservation service within the framework of climate change:insights from the Jinghe River Basin,China

Severe soil erosion and drought are the two main factors affecting the ecological security of the Loess Plateau,China.Investigating the influence of drought on soil conservation service is of great importance to regional environmental protection and sustainable development.However,there is little research on the coupling relationship between them.In this study,focusing on the Jinghe River Basin,China as a case study,we conducted a quantitative evaluation on meteorological,hydrological,and agricultural droughts(represented by the Standardized Precipitation Index(SPI),Standardized Runoff Index(SRI),and Standardized Soil Moisture Index(SSMI),respectively)using the Variable Infiltration Capacity(VIC)model,and quantified the soil conservation service using the Revised Universal Soil Loss Equation(RUSLE)in the historical period(2000-2019)and future period(2026-2060)under two Representative Concentration Pathways(RCPs)(RCP4.5 and RCP8.5).We further examined the influence of the three types of drought on soil conservation service at annual and seasonal scales.The NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP)dataset was used to predict and model the hydrometeorological elements in the future period under the RCP4.5 and RCP8.5 scenarios.The results showed that in the historical period,annual-scale meteorological drought exhibited the highest intensity,while seasonal-scale drought was generally weakest in autumn and most severe in summer.Drought intensity of all three types of drought will increase over the next 40 years,with a greater increase under the RCP4.5 scenario than under the RCP8.5 scenario.Furthermore,the intra-annual variation in the drought intensity of the three types of drought becomes smaller under the two future scenarios relative to the historical period(2000-2019).Soil conservation service exhibits a distribution pattern characterized by high levels in the southwest and southeast and lower levels in the north,and this pattern has remained consistent both in the historical and future periods.Over the past 20 years,the intra-annual variation indicated peak soil conservation service in summer and lowest level in winter;the total soil conservation of the Jinghe River Basin displayed an upward trend,with the total soil conservation in 2019 being 1.14 times higher than that in 2000.The most substantial impact on soil conservation service arises from annual-scale meteorological drought,which remains consistent both in the historical and future periods.Additionally,at the seasonal scale,meteorological drought exerts the highest influence on soil conservation service in winter and autumn,particularly under the RCP4.5 and RCP8.5 scenarios.Compared to the historical period,the soil conservation service in the Jinghe River Basin will be significantly more affected by drought in the future period in terms of both the affected area and the magnitude of impact.This study conducted beneficial attempts to evaluate and predict the dynamic characteristics of watershed drought and soil conservation service,as well as the response of soil conservation service to different types of drought.Clarifying the interrelationship between the two is the foundation for achieving sustainable development in a relatively arid and severely eroded area such as the Jinghe River Basin.

Service Function Chain Migration in LEO Satellite Networks

With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.

Spatiotemporal variations in ecosystem services and their trade-offs and synergies against the background of the gully control and land consolidation project on the Loess Plateau,China

Studying the spatiotemporal variations in ecosystem services and their interrelationships on the Loess Plateau against the background of the gully control and land consolidation(GCLC)project has significant implications for ecological protection and quality development of the Yellow River Basin.Therefore,in this study,we took Yan'an City,Shaanxi Province of China,as the study area,selected four typical ecosystem services,including soil conservation service,water yield service,carbon storage service,and habitat quality service,and quantitatively evaluated the spatiotemporal variation characteristics and trade-offs and synergies of ecosystem services from 2010 to 2018 using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.We also analysed the relationship between the GCLC project and regional ecosystem service changes in various regions(including 1 city,2 districts,and 10 counties)of Yan'an City and proposed a coordinated development strategy between the GCLC project and the ecological environment.The results showed that,from 2010 to 2018,soil conservation service decreased by 7.76%,while the other three ecosystem services changed relatively little,with water yield service increasing by 0.56% and carbon storage service and habitat quality service decreasing by 0.16% and 0.14%,respectively.The ecological environment of Yan'an City developed in a balanced way between 2010 and 2018,and the four ecosystem services showed synergistic relationships,among which the synergistic relationships between soil conservation service and water yield service and between carbon storage service and habitat quality service were significant.The GCLC project had a negative impact on the ecosystem services of Yan'an City,and the impact on carbon storage service was more significant.This study provides a theoretical basis for the scientific evaluation of the ecological benefits of the GCLC project and the realization of a win-win situation between food security and ecological security.

Exploring the Spatiotemporal Changes and Driving Forces of Ecosystem Services of Zhejiang Coasts,China,Under Sustainable Development Goals

Ecosystem services(ESs)refer to the continuous provisioning of ecosystem goods and services that benefit human beings.Over recent decades,rapid urbanization has exerted significant pressure on coastal ecosystems,resulting in biodiversity and habitat loss,environmental pollution,and the depletion of natural resources.In response to these environmental challenges,the Sustainable Development Goals(SDGs)were proposed.Given the pressing need to address these issues,understanding the changes in ESs under the SDGs is crucial for formulating specific ecological strategies.In this study,we first analyzed land use and cover change in the Zhejiang coasts of China during 2000–2020.Then,we investigated the spatiotemporal configuration of ESs by integrating carbon storage(CS),soil retention(SR),habitat quality(HQ)and water yield(WY)using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model.The driving mechanisms of ESs,which varied by space and time,were also explored using the Geo-detector method.The results revealed that,over the past two decades:1)the Zhejiang coasts have experienced a significant increase of 2783.72 km^(2) in built-up land areas and a continuous decrease in farmland areas due to rapid urbanization;2)owing to higher precipitation,extensive vegetation cover,and reduced anthropogenic disturbances,forests emerge as a crucial land use type for maintaining ecosystem services such as HQ,CS,WY,and SR;3)ESs have generally declined across the entire Zhejiang coasts,with a significant decrease observed in the northern areas and an increase in the southern areas spatially;4)the expansion of built-up land areas emerged as the primary factor affecting ecosystem services,while the vegetation factor has been increasingly significant and is expected to become predominant in the near future.Our study provides insights of understanding of ecosystem service theory and emphasizing the importance of preserving biodiversity for long-term sustainable development,and valuable scientific references to support the ecological management decision-making for local governments.

Multi-scenario Simulation of the Impact of Land Use Change on the Ecosystem Service Value in the Suzhou-Wuxi-Changzhou Metropolitan Area,China

As the most economically developed metropolitan area in China’s Yangtze River Delta,the rapid changing land use patterns of Suzhou-Wuxi-Changzhou(Su-Xi-Chang) metropolitan area have profound impacts on the ecosystem service value(ESV).Based on the patterns of land use change and the ESV change in Su-Xi-Chang metropolitan area from 2000 to 2020,we set up four scenarios:natural development scenario,urban development scenario,arable land protection scenario and ecological protection scenario,and simulated the impact of land use changes on the ESV in these scenarios.The results showed that:1) the area of built-up land in the Su-XiChang metropolitan area increased significantly from 2000 to 2020,and the area of other types of land decreased.Arable land underwent the highest transfer-out area,and was primarily converted into built-up land.The total ESV of Su-Xi-Chang metropolitan area increased initially then declined from 2000–2020,and the value of almost all individual ecosystem services decreased.2) Population density,GDP per area,night lighting intensity,and road network density can negatively impact the ESV.3) The total ESV loss under the natural development and urban development scenarios was high,and the expansion of the built-up land and the drastic shrinkage of the arable land contributed to the ESV decline under both scenarios.The total ESV under arable land protection and ecological protection scenarios increases,and therefore these scenarios are suitable for future land use optimization in Su-Xi-Chang.This study could provide a certain reference for land use planning and allocation,and offer guidance for the rational allocation of land resources.

A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Networks

Video streaming applications have grown considerably in recent years.As a result,this becomes one of the most significant contributors to global internet traffic.According to recent studies,the telecommunications industry loses millions of dollars due to poor video Quality of Experience(QoE)for users.Among the standard proposals for standardizing the quality of video streaming over internet service providers(ISPs)is the Mean Opinion Score(MOS).However,the accurate finding of QoE by MOS is subjective and laborious,and it varies depending on the user.A fully automated data analytics framework is required to reduce the inter-operator variability characteristic in QoE assessment.This work addresses this concern by suggesting a novel hybrid XGBStackQoE analytical model using a two-level layering technique.Level one combines multiple Machine Learning(ML)models via a layer one Hybrid XGBStackQoE-model.Individual ML models at level one are trained using the entire training data set.The level two Hybrid XGBStackQoE-Model is fitted using the outputs(meta-features)of the layer one ML models.The proposed model outperformed the conventional models,with an accuracy improvement of 4 to 5 percent,which is still higher than the current traditional models.The proposed framework could significantly improve video QoE accuracy.

Which Neighborhoods Have Easier Access to Online Home Delivery Services?A Spatiotemporal Accessibility Analysis in Nanjing,China

The rise in online home delivery services(OHDS)has had a significant impact on how urban services are supplied and used in recent years.Studies on the spatial accessibility of OHDS are emerging,but few is known about the temporal dimension of OHDS accessibility as well as the geographic and socioeconomic differences in the spatiotemporal accessibility of OHDS.This study measures the spatiotemporal accessibility of four types of OHDS,namely leisure,fresh and convenient,medical,and catering services.The geographic and socioeconomic disparities in the spatiotemporal accessibility of these four types of OHDS are then identified using spatial statistical methods and the Kruskal-Wallis test(K-W test).The case study in Nanjing,China,suggests that:1)spatiotemporal accessibility better reflects the temporal variation of OHDS accessibility and avoids overestimation of OHDS accessibility when only considering its spatial dimension.2)The spatiotemporal accessibility of OHDS varies geographically and socioeconomically.Neighborhoods located in the main city or neighborhoods with higher housing prices,higher population density,and higher point of interest(POI)mix have better OHDS spatiotemporal accessibility.Our study contributes to the understanding of OHDS accessibility from a spatiotemporal perspective,and the empirical insights can assist policymakers in creating intervention plans that take into account variations in OHDS spatiotemporal accessibility.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Spatio-temporal evolution and topographic gradient effect of land use and ecosystem service value in the Lhasa River Basin

The Lhasa River Basin forms an essential human settlement area in the southern part of the Qinghai-Tibet Plateau.This study employed ecosystem service value(ESV)evaluation model,terrain gradient grading,and Geodetector to analyze land use and ESV in the Lhasa River Basin from 1985 to 2020.The findings reveal that:(1)From 1985 to 2020,grassland was the dominant land use.There was a trend of grassland reduction and the expansion of other land types.(2)ESV has increased over the research period(with a total increase of 0.84%),with higher values in the southeast and lower values in the northwest.Grassland contributed the most to ESV,and climate regulation and hydrological regulation were the ecosystem services that contribute the most to ESV.(3)Natural factors like NDVI and altitude,as well as economic factors like population density and distance from roads,influenced the spatial differentiation of ESV,the explanatory power of NDVI reached up to 0.47.The interaction between factors had a greater impact than individual factors.These research results can provide theoretical support for national spatial planning and ecological environment protection in the Lhasa River Basin and other similar areas.

Coupling Coordination Analysis of Cropland Intensification and Agroecosystem Services:Evidence from Loess Plateau in Shaanxi Province,China

One of the greatest challenges in the agroecosystem is to improve cropland intensification while preserving agroecosystem services.While many studies have investigated the effect of cropland intensification on agroecosystem service,the interactive coupling and coordination among these factors remain largely unexplored.In view of this,this study performed a case study of the Loess Plateau in Shaanxi Province,China and constructed comprehensive evaluation models to quantify the cropland intensification and agroecosystem service in this area.Balance analysis and the coupling coordination degree model were used to evaluate the interactive relationship between cropland intensification and agroecosystem service,and statistical analysis and spatial autocorrelation were used to analyze the spatial characteristics and potential mechanism of the coupling coordination.Results show that both the cropland intensification and agroecosystem service in the study area were relatively low yet gradually increased from 2000 to 2020.Agroecosystem service lag was identified as the dominant unbalanced development type.Improving the supply capacity of agroecosystem services plays a key role in the balanced development of cropland in the Loess Plateau.The coupling coordination degree between cropland intensification and agroecosystem service ranges from basic coordination to serious incoordination.Therefore,cropland intensification practices in the area should be optimized to enhance this coordination degree.An upward trend was also observed in the coupling coordination degree from2000 to 2020.The withdrawal of marginal cropland in the Grain for Green program is one of the most important reasons for this trend,especially for the northern region.Around 83.6%of the high-high clusters are concentrated in the southern region of the Loess Plateau,whereas 70.5%of the low-low clusters are distributed in the northern region.These clustering characteristics are mainly attributed to the environmental suitability of these areas for agriculture and their degree of economic development.

Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin,Northwest China

The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China,exhibiting typical mountain-oasis-desert distribution characteristics.In recent decades,climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems.However,the trade-offs and synergies between ecosystem services(ESs)have not been thoroughly examined.This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs.Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)and Revised Wind Erosion Equation(RWEQ)using land use/land cover(LULC),climate,vegetation,soil,and hydrological data,we quantified the spatiotemporal changes in the five principal ESs(carbon storage,water yield,food production,wind and sand prevention,and habitat quality)of the watershed from 1995 to 2020.Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs.The findings reveal that water yield,carbon storage,and habitat quality exhibited relatively high levels in the upstream,while food production and wind and sand prevention dominated the midstream and downstream,respectively.Furthermore,carbon storage,food production,wind and sand prevention,and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020.Specifically,carbon storage,wind and sand prevention,and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream.Food production in the midstream showed a continuously increasing trend during the study period.Trade-off relationships were identified between water yield and wind and sand prevention,water yield and carbon storage,food production and water yield,and habitat quality and wind and sand prevention.Prominent temporal and spatial synergistic relationships were observed between different ESs,notably between carbon storage and habitat quality,carbon storage and food production,food production and wind and sand prevention,and food production and habitat quality.Water resources emerged as a decisive factor for the sustainable development of the basin,thus highlighting the intricate trade-offs and synergies between water yield and the other four services,particularly the relationship with food production,which warrants further attention.This research is of great significance for the protection and sustainable development of river basins in arid areas.