Impacts of multi-scenario land use change on ecosystem services and ecological security pattern: A case study of the Yellow River Delta

The Yellow River Delta(YRD), a critical economic zone along China's eastern coast, also functions as a vital ecological reserve in the lower Yellow River. Amidst rapid industrialization and urbanization, the region has witnessed significant land use/cover changes(LUCC), impacting ecosystem services(ES) and ecological security patterns(ESP). Investigating LUCC's effects on ES and ESP in the YRD is crucial for ecological security and sustainable development. This study utilized the PLUS model to simulate 2030 land use scenarios, including natural development(NDS), economic development(EDS), and ecological protection scenarios(EPS). Subsequently, the InVEST model and circuit theory were applied to assess ES and ESP under varying LUCC scenarios from 2010 to 2030. Findings indicate:(1) Notable LUCC from 2010 to 2030, marked by decreasing cropland and increasing construction land and water bodies.(2) From 2010 to 2020, improvements were observed in carbon storage,water yield, soil retention, and habitat quality, whereas 2020–2030 saw increases in water yield and soil retention but declines in habitat quality and carbon storage. Among the scenarios, EPS showed superior performance in all four ES.(3) Between 2010 and 2030, ecological sources, corridors, and pinchpoints expanded, displaying significant spatial heterogeneity. The EPS scenario yielded the most substantial increases in ecological sources,corridors, and pinchpoints, totaling 582.89 km^(2), 645.03 km^(2),and 64.43 km^(2), respectively. This study highlights the importance of EPS, offering insightful scientific guidance for the YRD's sustainable development.

Multi-scenario Simulation for 2060 and Driving Factors of the Eco-spatial Carbon Sink in the Beibu Gulf Urban Agglomeration, China

Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China's urban agglomerations. This study applied the Future Land Use Simulation(FLUS) model to predict the land use pattern of the ecological space of the Beibu Gulf urban agglomeration, in 2060 under ecological priority, agricultural priority and urbanized priority scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs(In VEST) model was employed to analyse the spatial changes in ecological space carbon storage in each scenario from 2020 to 2060. Then, this study used a Geographically Weighted Regression(GWR) model to determine the main driving factors that influence the changes in land carbon sinking capacity. The results of the study can be summarised as follows: firstly, the agricultural and ecological priority scenarios will achieve balanced urban expansion and environmental protection of resources in an ecological space. The urbanized priority scenario will reduce the carbon sinking capacity. Among the simulation scenarios for 2060, carbon storage in the urbanized priority scenario will decrease by 112.26 × 10^(6) t compared with that for 2020 and the average carbon density will decrease by 0.96 kg/m^(2) compared with that for 2020. Carbon storage in the agricultural priority scenario will increase by 84.11 × 10^(6) t, and the average carbon density will decrease by 0.72 kg/m^(2). Carbon storage in the ecological priority scenario will increase by 3.03 × 10^(6) t, and the average carbon density will increase by 0.03 kg/m^(2). Under the premise that the population of the town will increases continuously, the ecological priority development approach may be a wise choice.Secondly, slope, distance to river and elevation are the most important factors that influence the carbon sink pattern of the ecological space in the Beibu Gulf urban agglomeration, followed by GDP, population density, slope direction and distance to traffic infrastructure.At the same time, urban space expansion is the main cause of the changes of this natural factors. Thirdly, the decreasing trend of ecological space is difficult to reverse, so reasonable land use policy to curb the spatial expansion of cities need to be made.

Integrating ecosystem services evaluation and landscape pattern analysis into urban planning based on scenario prediction and regression model

Urban planning has become a widely concern for minimizing the negative effects of urban expansion on terrestrial ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness and shortcomings of urban expansion management strategies. A three-step method was applied to Yinchuan Plain in the northwestern of China, including(1)analyzing the relationship between landscape pattern and ecosystem service values through mathematical statistics;(2) predicting landscape pattern and ecosystem services change under different scenarios based on cellular automaton model(SLEUTH-3r model); and(3) designing and validating optimized scenario through integrating historical analysis experiments and future multi-comparison suggestions. Results have suggested that landscape composition and configuration can significantly affect regional ecosystem service values, especially the connectivity and shape of landscape. Compact urban growth policy and medium environment protection policy are the appropriate setting for urban expansion plan. Optimization validation of the combined designed scenario implied the reliability of this method. Our results highlighted the significance of integrating application of landscape pattern analysis, ecosystem service value evaluation,model simulation and multi-scenario prediction in urban planning.

Simulation and prediction of multi-scenario evolution of ecological space based on FLUS model: A case study of the Yangtze River Economic Belt, China

Building the Yangtze River Economic Belt(YREB)is one of China’s three national development policies in the new era.The ecological environment of the Yangtze River Economic Belt must be protected not only for regional economic development but also for regional ecological security and ecological progress in this region.This paper takes the ecological space of the Yangtze River Economic Belt as the research object,based on land use data in 2010 and 2015,and uses the FLUS model to simulate and predict the ecological space of the research area in 2035.The variation of the research area’s ecological space area and its four sub-zones has remarkable stability under diverse situations.Both the production space priority scenarios(S1)and living space priority scenarios(S2)saw a fall in ecological space area,with the former experiencing the highest reduction(a total reduction of 25,212 km^(2)).Under the ecological space priority scenarios(S3)and comprehensive space optimization scenario(S4),the ecological space area increased,and the ecological space area expanded even more under the former scenario(a total growth of 23,648 km^(2)).In Yunnan-Guizhou,the ecological space is relatively stable,with minimal signs of change.In Sichuan-Chongqing,the Sichuan Basin,Zoige Grassland,and Longmen Mountains were significant regions of area changes in ecological space.In the middle reaches of the Yangtze River,the ecological space changes mainly occur in the Wuyi Mountains,Mufu Mountains,and Dabie Mountains,as well as the surrounding waters of Dongting Lake.The Yangtze River Delta’s changes were mainly observed in the eastern Dabie Mountains and Jianghuai Hills.

T-Ring无线电综合测试场的构建(英文)

Outfield testing is an effective measure to check the performance of wireless networks and facilities.Current outfield testing environment has inherent fluctuation due to the wireless propagation condition and has other disadvantages such as nonsupport for multiple scenarios,and low-level yet high-cost auto-control capability.In this paper,the conception of a radio testing environment,known as T-Ring(Integrated-Testing Ring),is proposed.It is based on a novel fitting degree evaluation frame.The testing ring can achieve high level of fitting degree to the real network so that the fluctuation of the wireless environment will be under control or even eliminated.This paper will choose some typical performance indicators and obtain corresponding statistical data in both the real network and system level simulation.A complete set of procedures is also given in this paper to evaluate the fitting degree of testing results and simulation results.It proves that the simulation highly fits to the real network and the simulation configuration can be used to construct the testing ring.At the same time,the advanced radio testing ring integrates multiple radio access technologies,scenarios and facilities from different manufacturers.It can improve the efficiency of wireless outfield testing and lower the cost of operators and manufacturers.

Will Coal Price Fluctuations Affect Renewable Energy Substitution and Carbon Emission? A Computable General Equilibrium-Based Study of China

Changes in the energy price system will determine the direction of evolution of the energy industry structure.As a country where coal is the dominant energy source,what is the effect of coal price fluctuations on China’s industry development costs and energy consumption structure?To investigate this problem,this paper utilized an economy–energy–environment computable general equilibrium model.In this study,four aspects were analyzed:Energy supply side,proportion of renewable energy consumption,macroeconomy,and changes in CO_(2) emissions.The results of this study show that an increase of 10%–20%in coal prices contributes to a shift into using renewable energy,which leads to energy saving and emission reduction.Renewable energy and clean energy rose by 0.57%–4.47%in the energy structure,but this has a certain negative impact on the macroeconomy.The gross domestic product(GDP)fell by 0.07%–0.18%.As a result,the decline in coal prices became an obstacle to renewable energy substitution and energy conservation.In addition,we put forward policy suggestions according to the results in energy,economic,and environmental effects.

User Satisfaction-Aware Edge Computation Offloading in 5G Multi-Scenario

Edge computation offloading has made some progress in the fifth generation mobile network(5G).However,load balancing in edge computation offloading is still a challenging problem.Meanwhile,with the continuous pursuit of low execution latency in 5G multi-scenario,the functional requirements of edge computation offloading are further exacerbated.Given the above challenges,we raise a unique edge computation offloading method in 5G multi-scenario,and consider user satisfaction.The method consists of three functional parts:offloading strategy generation,offloading strategy update,and offloading strategy optimization.First,the offloading strategy is generated by means of a deep neural network(DNN),then update the offloading strategy by updating the DNN parameters.Finally,we optimize the offloading strategy based on changes in user satisfaction.In summary,compared to existing optimization methods,our proposal can achieve performance close to the optimum.Massive simulation results indicate the latency of the execution of our method on the CPU is under 0.1 seconds while improving the average computation rate by about 10%.