Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analy...Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orien...Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orientation,rendering it inseparable from being merely a derivative of geographical science or technology.This paper defines geographical engineering and introduces its development history through the lens of Chinese geographical engineering praxises.Furthermore,it is highlighted the logical and functional consistency between the theory of human-earth system and the praxis of geographical engineering.Six modern cases of geographical engineering projects are presented in detail to demonstrate the points and characteristics of different types of modern geographical engineering.Geographical engineering serves as an engine for promoting integrated geography research,and in response to the challenge posed by fragmented geographies,this paper advocates for an urgent revitalization of geographical engineering.The feasibility of revitalizing geographical engineering is guaranteed because it aligns with China’s national strategies.展开更多
Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different educ...Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.展开更多
The alpine ecosystem has great potential for carbon sequestration.Soil organic carbon(SOC)and total nitrogen(TN)are highly sensitive to climate change,and their dynamics are crucial to revealing the effect of climate ...The alpine ecosystem has great potential for carbon sequestration.Soil organic carbon(SOC)and total nitrogen(TN)are highly sensitive to climate change,and their dynamics are crucial to revealing the effect of climate change on the structure,function,and services of the ecosystem.However,the spatial distribution and controlling factors of SOC and TN across various soil layers and vegetation types within this unique ecosystem remain inadequately understood.In this study,256 soil samples in 89 sites were collected from the Three River Headwaters Region(TRHR)in China to investigate SOC and TN and to explore the primary factors affecting their distribution,including soil,vegetation,climate,and geography factors.The results show that SOC and TN contents in 0-20,20-40,40-60,and 60-80 cm soil layers are 24.40,18.03,14.04,12.40 g/kg and 2.46,1.90,1.51,1.17 g/kg,respectively;with higher concentrations observed in the southeastern region compared to the northwest of the TRHR.One-way analysis of variance reveals that SOC and TN levels are elevated in the alpine meadow and the alpine shrub relative to the alpine steppe in the 0-60 cm soil layers.The structural equation model explores that soil water content is the main controlling factor affecting the variation of SOC and TN.Moreover,the geography,climate,and vegetation factors notably indirectly affect SOC and TN through soil factors.Therefore,it can effectively improve soil water and nutrient conditions through vegetation restoration,soil improvement,and grazing management,and the change of SOC and TN can be fully understood by establishing monitoring networks to better protect soil carbon and nitrogen.展开更多
Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base ...Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.展开更多
Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable developm...Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development.This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD)region from 1990 to 2018 by integrating Geographical Information System(GIS)spatial analysis and landscape pattern indices,and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP).Moreover,we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region.Results show that:1)development intensity of construction land continued to increase from 7.54%in 1990 to 13.44%in 2018,primarily by occupying farmland.The landscape fragmentation of construction land in the YRD region decreased,and landscape dominance increased.Spatially,the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land,whereas the western part shows a high degree of fragmentation,revealing distinct spatial gradient differentiation characteristics.The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions.2)Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD.The industrial structure significantly influences the conversion of farmland to construction land.Additionally,infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land.Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3)The core driving factors for the development intensity of construction land in central cities primarily lies in transportation,whereas for non-central cities,besides transportation,the year-end balance of per capita savings deposits of urban and rural residents also play a significant role.The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level,respectively.This study informs refined spatial optimization and regional high-quality integrated development.展开更多
Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term La...Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term Landsat satellite images acquired from 1997 to 2020 to quantify the impact of changes in hydrological connectivity induced by S.alterniflora on neighboring vegetation com-munities.The results showed that S.alterniflora rapidly expanded in the estuary area at a rate of 4.91 km^(2)/yr from 2010 to 2020.At the same time,the hydrological connectivity of the area and the distribution of S.salsa changed significantly.Small tidal creeks dominated the S.alterniflora landscape.The number of tidal creeks increased significantly,but their average length decreased and they tended to develop in a horizontal tree-like pattern.Affected by the changes in hydrological connectivity due to the S.alterniflora invasion,the area of S.salsa decreased by 41.1%,and the degree of landscape fragmentation increased from 1997 to 2020.Variations in the Largest Patch Index(LPI)indicated that the S.alterniflora landscape had become the dominant landscape type in the Yellow River Estuary.The res-ults of standard deviation ellipse(SDE)and Pearson’s correlation analyses indicated that a well-developed hydrological connectivity could promote the maintenance of the S.salsa landscape.The degradation of most S.salsa communities is caused by the influence of S.alterniflora on the morphological characteristics of the hydrological connectivity of tidal creek systems.展开更多
Quantifying and mapping how ecosystem services impact agricultural competitiveness is crucial for attaining the Sustainable Development Goals of United Nations.However,few study quantified agricultural competitiveness...Quantifying and mapping how ecosystem services impact agricultural competitiveness is crucial for attaining the Sustainable Development Goals of United Nations.However,few study quantified agricultural competitiveness and mapped the effects of ecosystem services on agricultural competitiveness using multiple models.In this study,multi-source data from 2000 to 2020 were utilized to establish the indicator system of agricultural competitiveness;five ecosystem services were quantified using computation models;Geographic Information System(GIS)spatial analysis was used to explore the spatial patterns of agricultural competitiveness and ecosystem services;geographic detector models were applied to investigate the effects and driving mechanisms of ecosystem services on agricultural competitiveness.Shandong Province of China was selected as the case study area.The results demonstrated that:1)there was a significant increase in agricultural competitiveness during the study period,with high levels observed mainly in the east region of the study area.2)The spatial distribution patterns of ecosystem services and agricultural competitiveness primarily exhibited High-High and Low-Low Cluster types.3)Habitat quality emerged as the main driving factor of agricultural competitiveness in 2000 and 2020,while water yield played a substantial role in 2010.4)The coupling of two ecosystem services exerted a greater effect on agricultural competitiveness compared to individual ecosystem service.The innovations of this study are constructing an indicator system to quantify agricultural competitiveness,and exploring the effects of ecosystem services on agricultural competitiveness.This study proposed an indicator system to quantify agricultural competitiveness,which can be applied in other regions,and explored the effects of ecosystem services on agricultural competitiveness.The findings of this study can serve as valuable insights for policymakers to formulate tailored agricultural development policies that take into account the synergistic effects of ecosystem services on agricultural competitiveness.展开更多
In the era of the digital economy,digital trade has demonstrated strong vitality,becoming a crucial driving force for the highquality development of national and regional economies.However,understanding the resilience...In the era of the digital economy,digital trade has demonstrated strong vitality,becoming a crucial driving force for the highquality development of national and regional economies.However,understanding the resilience of digital trade in the face of external crises is an important topic.Taking the backdrop of Sino-US trade friction,this paper constructs a resilience index system for digital trade.It utilizes entropy method,kernel density estimation,and ArcGIS mapping to calculate and visually analyze the resilience of China’s digital trade from 2017 to 2021.Additionally,a Tobit model is constructed to explore the main influencing factors of digital trade resilience patterns.The research findings indicate:1)temporally,during the period of Sino-US trade friction,China’s digital trade resilience shows an overall upward trend,but there are regional differences in resilience levels across the country,with a severe polarization phenomenon.2)Spatially,high resilience is observed in the eastern and central regions of China,while the western and northeastern regions exhibit low resilience.3)From a dimensional perspective,the resistance of digital trade resilience displays a spatial distribution of high values in the east and low values in the west.The recovery force is aggregated along coastal areas,and the renewal force tends to aggregate along the eastern coastline.4)Factors such as economic scale,industrial structure,urbanization rate,government fiscal expenditure,and technological talents significantly promote the enhancement of digital trade resilience.This study reveals the dynamic characteristics and influencing factors of digital trade resilience in responding to external shocks,providing theoretical basis and policy suggestions for enhancing digital trade resilience,and promoting high-quality economic development in China.展开更多
This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking an...This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking and neutrality goals.This research ana-lyzes the spatial characteristics of carbon metabolism from 2000 to 2020 and uses models to identify stable carbon sink areas,positive carbon flow corridors,and carbon sequestration nodes.The goal is to construct a carbon metabolism spatial security pattern(CMSSP)and propose territorial ecological restoration strategies under different development demand scenarios.The results show the following:1)in 2020,the study area’s carbon sink decreased by 8.29×10^(4) t C/yr compared with that in 2010 and by 10.83×10^(4) t C/yr compared with that in 2000.High-carbon sinks were found mainly in mountainous areas,whereas low-carbon sinks are concentrated in urban con-struction land,rural residential areas,and land margins.2)From 2000 to 2020,the spatial security pattern of carbon metabolism tended to be‘high in the middle of the east and west and low in the gulf.’In 2000,2010,and 2020,16 stable carbon sinks were identified.The carbon energy flow density in Guangxi was greater than that in Guangdong and Hainan,with positive carbon flow corridors located primarily in Guangxi and Guangdong.The number of carbon sequestration nodes remained stable at approximately 15,mainly in Guangxi and Hainan.3)Scenario simulations revealed that under the Nature-based mild restoration scenario,the carbon sink rate will reach 611.85×10^(4) t C/yr by 2030 and increase to 612.45×10^(4) t C/yr by 2060,with stable carbon sinks increasing to 18.In the restora-tion scenario based on Anti-globalization,the carbon sink will decrease from 610.24×10^(4) t C/yr in 2030 to 605.19×10^(4) t C/yr in 2060,with the disappearance of some positive carbon flow corridors and stable carbon sinks.Under the Human-based sustainable restoration scenario,the carbon sink area will decrease from 607.00×10^(4) t C/yr in 2030 to 596.39×10^(4) t C/yr in 2060,with carbon sink areas frag-menting and positive carbon flow corridors becoming less dense.4)On the basis of the current and predicted CMSSPs,this study ex-plores spatial ecological restoration strategies for high-carbon storage areas in bay urban agglomerations at four levels:the land control region,urban agglomeration structure system,carbon sink structure and bay structure control region.展开更多
The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and...The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.展开更多
In recent years,rapid urbanization has had a profound impact on landscape stability.As a typical example of China's rapid urbanization,Hangzhou has also experienced significant landscape changes,which have profoun...In recent years,rapid urbanization has had a profound impact on landscape stability.As a typical example of China's rapid urbanization,Hangzhou has also experienced significant landscape changes,which have profoundly affected its ecological stability.Taking Hangzhou as an example,this study integrates land use change data from 1980 to 2020,combines dynamic simulation and ecological modeling techniques,and carries out a comprehensive analysis of historical trends and future predictions,to provide valuable insights into the complex interactions between urban expansion and landscape stability.The results indicate that:1)between 1980 and2020,Hangzhou experienced a significant increase in construction land at the expense of arable land,leading to a gradual decline in landscape stability,though the downward trend has slowed in recent years.2)The spatial distribution of landscape stability shows clear aggregation patterns,with lower stability concentrated in economically active flatlands and higher stability in the mountainous western regions.3)By 2040,further urban expansion is predicted to occur alongside increased landscape integration,reflecting the positive effects of ecological protection strategies.This study highlights the universal challenges of balancing economic growth with ecological stability in rapidly urbanizing regions.The combination of advanced simulation models and spatiotemporal analysis demonstrates a replicable framework for assessing urban expansion's ecological impacts.These findings underscore the importance of tailoring urban planning and ecological policies to address regional disparities,providing valuable insights for sustainable urban development and landscape management globally.展开更多
Coastal wetlands are crucial for the‘blue carbon sink’,significantly contributing to regulating climate change.This study util-ized 160 soil samples,35 remote sensing features,and 5 geo-climatic data to accurately e...Coastal wetlands are crucial for the‘blue carbon sink’,significantly contributing to regulating climate change.This study util-ized 160 soil samples,35 remote sensing features,and 5 geo-climatic data to accurately estimate the soil organic carbon stocks(SOCS)in the coastal wetlands of Tianjin and Hebei,China.To reduce data redundancy,simplify model complexity,and improve model inter-pretability,Pearson correlation analysis(PsCA),Boruta,and recursive feature elimination(RFE)were employed to optimize features.Combined with the optimized features,the soil organic carbon density(SOCD)prediction model was constructed by using multivariate adaptive regression splines(MARS),extreme gradient boosting(XGBoost),and random forest(RF)algorithms and applied to predict the spatial distribution of SOCD and estimate the SOCS of different wetland types in 2020.The results show that:1)different feature combinations have a significant influence on the model performance.Better prediction performance was attained by building a model using RFE-based feature combinations.RF has the best prediction accuracy(R^(2)=0.587,RMSE=0.798 kg/m^(2),MAE=0.660 kg/m^(2)).2)Optical features are more important than radar and geo-climatic features in the MARS,XGBoost,and RF algorithms.3)The size of SOCS is related to SOCD and the area of each wetland type,aquaculture pond has the highest SOCS,followed by marsh,salt pan,mud-flat,and sand shore.展开更多
Changes in river cross-section morphology have decisive influences on the flood discharge and sand transport capacity of rivers;thus,these changes strongly reflect the vitality of a river.In this paper,based on the ri...Changes in river cross-section morphology have decisive influences on the flood discharge and sand transport capacity of rivers;thus,these changes strongly reflect the vitality of a river.In this paper,based on the river cross-section and water and sediment data of two different periods(1974−1987 and 2007−2021),the trend analysis,change-point analysis and sediment rating curve method were used to analyze the change process of river cross-section morphology and its response to streamflow and sediment changes in the main river stream of the Yellow River at the Longmen hydrological station.From 1974 to 1987(except in 1977),the riverbed experi-enced siltation,and the riverbed elevation rose.Conversely,from 2007 to 2021,the riverbed experienced scouring,and the riverbed el-evation gradually decreased.The cross-section shape changed from rectangular to U-shaped(deeper on the right side)at the Longmen cross-section.The changes in streamflow and sediment processes significantly impacted the evolution of river cross-section.Stream-flow(P<0.05),sediment discharge(P<0.01),and the sediment load coefficients(P<0.01)decreased significantly.The relationship between the water depth and sediment load coefficients followed a power function.The decreasing trend in sediment discharge was sig-nificantly stronger than that in streamflow.Suspended sediment particles tended to become finer.The sediment rating curve indicates that the sediment supply from upstream decreased while the erosive power in the river channel increased,leading to a gradual decline in riverbed elevation at the Longmen cross-section from 2007 to 2021.These findings help us better understand the impacts of ecological restoration on changes in river streamflow and sediment during river evolution.展开更多
The Three Gorges Project,the largest water conservation initiative globally,is located within the Three Gorges Reservoir Area(TGRA),a critical zone for water conservation and ecological protection.There is an urgent n...The Three Gorges Project,the largest water conservation initiative globally,is located within the Three Gorges Reservoir Area(TGRA),a critical zone for water conservation and ecological protection.There is an urgent need to better understand and protect the evolving water conservation functions of the TGRA,alongside identifying the driving mechanisms within its ecological barrier re-gion.This paper explores the spatial and temporal evolution of water conservation function in the TGRA from 1990 to 2020 and its fu-ture trends under different development scenarios from 2020 to 2030.Key driving factors influencing the water conservation function are identified,and a comprehensive development scenario is proposed.The findings indicate a general upward trend in the water conser-vation function of the TGRA,characterized by an initial increase,a subsequent decline,and a final recovery.Moreover,land use changes are found to be the primary factor driving these variations,followed by climatic factors such as precipitation.Under various de-velopment scenarios,the prioritization of water conservation outcomes is ranked as follows:ecological protection>cropland protec-tion>natural development>urban development.The results of this study offer valuable insights for balancing economic development with ecological preservation.展开更多
Land use change is a fundamental factor affecting ecosystem’s structures and functions.However,few studies have explored the ecological disturbance caused by land use change from a combined structural and functional ...Land use change is a fundamental factor affecting ecosystem’s structures and functions.However,few studies have explored the ecological disturbance caused by land use change from a combined structural and functional perspective.In this study,the ecological structural disturbance index(SDI)and functional disturbance index(FDI)were introduced to quantitatively evaluate ecological disturbance caused by land use change in a typical karst area—Huangping County,Guizhou Province,China during 2009–2019.Results show that although the area of ecological land increased during past 10 yr,there had been a fragmentation trend of ecological land.Agricultural occupation was more severe than construction encroachment on ecological land.The grids with negative structural disturbance were consistent with areas of obvious dynamic loss and gain of ecological land.Ecological fragmentation had a greater impact than habitat gain in grids with negative structural disturbance.The ecosystem service functions of supply,adjustment,support,and culture were obviously affected by land use change,and the total FDI reflects the trade-off among them.Negative FDI values were easily observed in the rocky desertification area or water and soil loss area.The combination analysis of the SDI and FDI indicated the characteristic of codirectional ecologically structural and functional disturbance in the majority of grids.The findings improve our understanding of multiple relationships among ecological disturbances and provide valuable information for guiding land use activities.展开更多
As the core of spatial planning in China,delineation of the production-living-ecological space(PLES)refers to dividing the overall land use into three functional spaces.Spatial units are optimally configured as the mo...As the core of spatial planning in China,delineation of the production-living-ecological space(PLES)refers to dividing the overall land use into three functional spaces.Spatial units are optimally configured as the most suitable functional type,while beset by various uncertainties.Weight uncertainties,being affected by subjective preferences,are highly arbitrary and seriously affect PLES.Taking Xuzhou as the study area,this paper studies the perturbation mechanism and response measure of weight uncertainties on PLES.First,weight samples are obtained through quasi-random sampling to serve as sources of uncertainties for input into the optimized delineation of PLES.Next,the Monte Carlo simulation is applied to simulate the spatial probability distribution of PLES.The global sensitivity analysis method is then adopted to identify the main sources that cause uncertainties in the delineation of PLES.Subsequently,the flexible space(FS)of PLES at a certain level of significance is formulated by comparing the distribution probabilities of spatial units for different functional spaces,acting as a countermeasure for the perturbation.The results show that weight uncertainties bring disturbances to the PLES by affecting the multi-criteria evaluation(MCE)of PLES delineation.The PLES is affected by the weight uncertainties of the factors alone or through interactions with other weights.FS is the spatial response measure of PLES when uncertainties occurred at a certain level of significance.The study introduces the perspective of uncertainty for PLES,which contributes toward improving the scientificity and reliability of PLES.展开更多
Urban open spaces(UOS)play a crucial role in enhancing city livability and resident well-being,yet there remains a gap in utilizing social media to analyze changes in UOS utilization across different COVID(Corona Viru...Urban open spaces(UOS)play a crucial role in enhancing city livability and resident well-being,yet there remains a gap in utilizing social media to analyze changes in UOS utilization across different COVID(Corona Virus Disease)-19 phases.Our research applied Sina Weibo data to scrutinize UOS engagement across pre-pandemic(2019),pandemic(2021),and post-pandemic(2023)periods in Lanzhou City,China,revealing evolving spatiotemporal patterns and highlighting the pandemic's impact on UOS usage.Initially,scenic mountains and urban parks dominated visitor preferences in 2019.However,during the pandemic,there was a trend towards destinations that combined elements of tourism,business,entertainment,and culture,reflecting a growing appetite for diverse experiences.Despite this shift,the post-pandemic period did not see a complete return to pre-pandemic travel patterns,with a noticeable decline in visits to traditional green open spaces during lockdowns.We identified key attractions in main urban areas,highlighting geographical variations in tourism and Cultural Ecosystem Services(CES)distribution that warrant further attention.The post-pandemic landscape reveals a resurging interest in green-blue spaces and nature-focused tourism,highlighting a continued preference for cultural and natural experiences,and emphasizing the need to harmonize development with the preservation of natural and cultural heritage.This study introduces the use of social media data across pandemic phases to guide UOS management,offering insights for creating resilient,multifunctional urban spaces that address public needs and enhance community well-being.展开更多
The rapid development of digital technologies has driven the emergence and popularization of online-to-offline(O2O)retail,reshaping the retail landscape in urban China.However,spatial distribution characteristics and ...The rapid development of digital technologies has driven the emergence and popularization of online-to-offline(O2O)retail,reshaping the retail landscape in urban China.However,spatial distribution characteristics and influencing mechanisms of emerging O2O retail have not been thoroughly investigated in extant studies.Taking the central urban area of Guangzhou as the case,this study utilized multi-source data and machine learning methods to explore the distribution characteristics of O2O retail space and to further identify the nonlinear effects of the built environment,sociodemographic,and economic factors on its distribution.The results revealed that O2O retail space exhibited a‘single-center’distribution pattern,in contrast to the‘multi-center’distribution pattern of traditional retail space.This finding supported the diffusion of innovation hypothesis,highlighting that the expansion of O2O retail modes first spread from traditional developed retail space.Furthermore,spatial heterogeneities were observed across different types of O2O retail space,with O2O in-store showing a‘core-periphery’spatial structure as described by Central Place Theory,whereas O2O delivery displaying a‘horizontal,non-hierarchical,and multi-centered’network structure following Central Flow Theory.Compared to traditional retail space,the distribution of O2O retail space was more influenced by sociodemographic factors such as the proportion of youth,education level,and income level,but less affected by the built environment factors like office and building density.Furthermore,nonlinear effects of these influencing factors on the distribution of O2O retail space were identified,which enriched the existing literature by highlighting effective ranges and threshold effects.These findings provided valuable insights into O2O retail space development in the context of digital transformation.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.42371192)Natural Science Foundation of Hunan Province(No.2023JJ30100)Social Science Foundation of Hunan Province(No.23ZDAJ023,23YBA133)。
文摘Cities are important carriers of green innovation.The foundation for accelerating China's ecological civilization construction and fostering regionally coordinated and sustainable development is quantitative analysis of the spatial evolution pattern and influencing factors of urban green innovation,as well as revealing the development differences between regions.This study's research object includes 284 Chinese cities that are at the prefecture level or above,excluding Xizang,Hong Kong,Macao,and Taiwan of China due to incomplete data.The spatial evolution characteristics of urban green innovation in China between 2005 and 2021 are comprehensively described using the gravity center model and boxplot analysis.The factors that affect urban green innovation are examined using the spatial Durbin model(SDM).The findings indicate that:1)over the period of the study,the gravity center of urban green innovation in China has always been distributed in the Henan-Anhui border region,showing a migration characteristic of‘initially shifting northeast,subsequently southeast',and the migration speed has gradually increased.2)Although there are also noticeable disparities in east-west,the north-south gap is the main cause of the shift in China's urban green innovation gravity center.The primary areas of urban green innovation in China are the cities with green innovation levels higher than the median.3)The main influencing factor of urban green innovation is the industrial structure level.The effect of the financial development level,the government intervention level,and the openness to the outside world degree on urban green innovation is weakened in turn.The environmental regulation degree is not truly influencing urban green innovation.The impact of various factors on green innovation across cities of different sizes,exhibiting heterogeneity.This study is conducive to broadening the academic community's comprehension of the spatial evolution characteristics of urban green innovation and offering a theoretical framework for developing policies for the all-encompassing green transformation of social and economic growth.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
基金Under the auspices of National Natural Science Foundation of China(No.42293270)。
文摘Throughout the contemporary Chinese history of geography,geographical engineering has consistently played a pivotal role as a fundamental scientific activity.It possesses its distinct ontological basis and value orientation,rendering it inseparable from being merely a derivative of geographical science or technology.This paper defines geographical engineering and introduces its development history through the lens of Chinese geographical engineering praxises.Furthermore,it is highlighted the logical and functional consistency between the theory of human-earth system and the praxis of geographical engineering.Six modern cases of geographical engineering projects are presented in detail to demonstrate the points and characteristics of different types of modern geographical engineering.Geographical engineering serves as an engine for promoting integrated geography research,and in response to the challenge posed by fragmented geographies,this paper advocates for an urgent revitalization of geographical engineering.The feasibility of revitalizing geographical engineering is guaranteed because it aligns with China’s national strategies.
基金Under the auspices of Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-196)。
文摘Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.
基金supported by the National Science Foundation for Distinguished Young Scholars(No.42425107)Ecological Civilization Special Project of Key Research&and Development Program in Gansu Province(No.24YFFA009)the Top Talent Project of Gansu Province,Chinese Academy of Sciences Young Crossover Team Project(No.JCTD-2022-18)。
文摘The alpine ecosystem has great potential for carbon sequestration.Soil organic carbon(SOC)and total nitrogen(TN)are highly sensitive to climate change,and their dynamics are crucial to revealing the effect of climate change on the structure,function,and services of the ecosystem.However,the spatial distribution and controlling factors of SOC and TN across various soil layers and vegetation types within this unique ecosystem remain inadequately understood.In this study,256 soil samples in 89 sites were collected from the Three River Headwaters Region(TRHR)in China to investigate SOC and TN and to explore the primary factors affecting their distribution,including soil,vegetation,climate,and geography factors.The results show that SOC and TN contents in 0-20,20-40,40-60,and 60-80 cm soil layers are 24.40,18.03,14.04,12.40 g/kg and 2.46,1.90,1.51,1.17 g/kg,respectively;with higher concentrations observed in the southeastern region compared to the northwest of the TRHR.One-way analysis of variance reveals that SOC and TN levels are elevated in the alpine meadow and the alpine shrub relative to the alpine steppe in the 0-60 cm soil layers.The structural equation model explores that soil water content is the main controlling factor affecting the variation of SOC and TN.Moreover,the geography,climate,and vegetation factors notably indirectly affect SOC and TN through soil factors.Therefore,it can effectively improve soil water and nutrient conditions through vegetation restoration,soil improvement,and grazing management,and the change of SOC and TN can be fully understood by establishing monitoring networks to better protect soil carbon and nitrogen.
基金Under the National Key R&D Program Key Project(No.2021YFC3201201)National Natural Science Foundation of China(No.52360032)+2 种基金Basic Scientific Research Business Fee Project of Colleges And Universities Directly Under the Inner Mongolia Autonomous Region(No.JBYYWF2022001)Development Plan of Innovation Team of Colleges And Universities in Inner Mongolia Autonomous Region(No.NMGIRT2313)the Innovation Team of‘Grassland Talents’。
文摘Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.
基金Under the auspices of the National Natural Science Foundation of China(No.42301470,42171389)。
文摘Scientifically understanding the evolution of urbanization and analysing the coupling mechanism of human-land systems are important foundations for solving spatial conflicts and promoting regional sustainable development.This study analyzed the spatiotemporal evolution and landscape pattern change of construction land in the Yangtze River Delta(YRD)region from 1990 to 2018 by integrating Geographical Information System(GIS)spatial analysis and landscape pattern indices,and revealed its driving mechanism by XGBoost and SHapley Additive ex Planations(SHAP).Moreover,we compared the disparities in the core driving factors for construction land evolution in cities with diverse development orientations within the YRD region.Results show that:1)development intensity of construction land continued to increase from 7.54%in 1990 to 13.44%in 2018,primarily by occupying farmland.The landscape fragmentation of construction land in the YRD region decreased,and landscape dominance increased.Spatially,the eastern part of the YRD exhibits a high degree of spatial agglomeration of construction land,whereas the western part shows a high degree of fragmentation,revealing distinct spatial gradient differentiation characteristics.The landscape dominance of the construction land in the eastern region of the YRD is higher than that in the western and northern regions.2)Transportation and infrastructure exert the highest contribution rate on development intensity changes of construction land in the YRD.The industrial structure significantly influences the conversion of farmland to construction land.Additionally,infrastructure plays a crucial role in shaping the spatial agglomeration patterns of construction land.Population distribution is the dominant factor determining the regularity of the landscape shape of construction land.3)The core driving factors for the development intensity of construction land in central cities primarily lies in transportation,whereas for non-central cities,besides transportation,the year-end balance of per capita savings deposits of urban and rural residents also play a significant role.The area change of construction land occupying farmland in central and non-central cities is mainly driven by industrial structure and economic level,respectively.This study informs refined spatial optimization and regional high-quality integrated development.
基金Under the auspices of Key Program of the National Natural Science Foundation of China(No.U2006215,U1806218)the National Key R&D Program of China(No.2017YFC0505902)。
文摘Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term Landsat satellite images acquired from 1997 to 2020 to quantify the impact of changes in hydrological connectivity induced by S.alterniflora on neighboring vegetation com-munities.The results showed that S.alterniflora rapidly expanded in the estuary area at a rate of 4.91 km^(2)/yr from 2010 to 2020.At the same time,the hydrological connectivity of the area and the distribution of S.salsa changed significantly.Small tidal creeks dominated the S.alterniflora landscape.The number of tidal creeks increased significantly,but their average length decreased and they tended to develop in a horizontal tree-like pattern.Affected by the changes in hydrological connectivity due to the S.alterniflora invasion,the area of S.salsa decreased by 41.1%,and the degree of landscape fragmentation increased from 1997 to 2020.Variations in the Largest Patch Index(LPI)indicated that the S.alterniflora landscape had become the dominant landscape type in the Yellow River Estuary.The res-ults of standard deviation ellipse(SDE)and Pearson’s correlation analyses indicated that a well-developed hydrological connectivity could promote the maintenance of the S.salsa landscape.The degradation of most S.salsa communities is caused by the influence of S.alterniflora on the morphological characteristics of the hydrological connectivity of tidal creek systems.
基金Under the auspices of the National Key Research and Development Program of China(No.2022YFC3204404)。
文摘Quantifying and mapping how ecosystem services impact agricultural competitiveness is crucial for attaining the Sustainable Development Goals of United Nations.However,few study quantified agricultural competitiveness and mapped the effects of ecosystem services on agricultural competitiveness using multiple models.In this study,multi-source data from 2000 to 2020 were utilized to establish the indicator system of agricultural competitiveness;five ecosystem services were quantified using computation models;Geographic Information System(GIS)spatial analysis was used to explore the spatial patterns of agricultural competitiveness and ecosystem services;geographic detector models were applied to investigate the effects and driving mechanisms of ecosystem services on agricultural competitiveness.Shandong Province of China was selected as the case study area.The results demonstrated that:1)there was a significant increase in agricultural competitiveness during the study period,with high levels observed mainly in the east region of the study area.2)The spatial distribution patterns of ecosystem services and agricultural competitiveness primarily exhibited High-High and Low-Low Cluster types.3)Habitat quality emerged as the main driving factor of agricultural competitiveness in 2000 and 2020,while water yield played a substantial role in 2010.4)The coupling of two ecosystem services exerted a greater effect on agricultural competitiveness compared to individual ecosystem service.The innovations of this study are constructing an indicator system to quantify agricultural competitiveness,and exploring the effects of ecosystem services on agricultural competitiveness.This study proposed an indicator system to quantify agricultural competitiveness,which can be applied in other regions,and explored the effects of ecosystem services on agricultural competitiveness.The findings of this study can serve as valuable insights for policymakers to formulate tailored agricultural development policies that take into account the synergistic effects of ecosystem services on agricultural competitiveness.
基金Under the auspices of National Natural Science Foundation of China(No.42471205)the General Scientific Research Project of Zhejiang Provincial Department of Education(No.2024JYTYB12)the Philosophy and Social Science Planning Project of Zhejiang Province(No.23NDJC109YB)。
文摘In the era of the digital economy,digital trade has demonstrated strong vitality,becoming a crucial driving force for the highquality development of national and regional economies.However,understanding the resilience of digital trade in the face of external crises is an important topic.Taking the backdrop of Sino-US trade friction,this paper constructs a resilience index system for digital trade.It utilizes entropy method,kernel density estimation,and ArcGIS mapping to calculate and visually analyze the resilience of China’s digital trade from 2017 to 2021.Additionally,a Tobit model is constructed to explore the main influencing factors of digital trade resilience patterns.The research findings indicate:1)temporally,during the period of Sino-US trade friction,China’s digital trade resilience shows an overall upward trend,but there are regional differences in resilience levels across the country,with a severe polarization phenomenon.2)Spatially,high resilience is observed in the eastern and central regions of China,while the western and northeastern regions exhibit low resilience.3)From a dimensional perspective,the resistance of digital trade resilience displays a spatial distribution of high values in the east and low values in the west.The recovery force is aggregated along coastal areas,and the renewal force tends to aggregate along the eastern coastline.4)Factors such as economic scale,industrial structure,urbanization rate,government fiscal expenditure,and technological talents significantly promote the enhancement of digital trade resilience.This study reveals the dynamic characteristics and influencing factors of digital trade resilience in responding to external shocks,providing theoretical basis and policy suggestions for enhancing digital trade resilience,and promoting high-quality economic development in China.
基金Under the auspices of the National Natural Science Foundation of China(No.52268008)。
文摘This study focuses on urgent research on restoring and enhancing carbon storage capacity in the Beibu Gulf Urban Agglomer-ation of China,a key area in the‘Belt and Road’Initiative,which aligns with carbon peaking and neutrality goals.This research ana-lyzes the spatial characteristics of carbon metabolism from 2000 to 2020 and uses models to identify stable carbon sink areas,positive carbon flow corridors,and carbon sequestration nodes.The goal is to construct a carbon metabolism spatial security pattern(CMSSP)and propose territorial ecological restoration strategies under different development demand scenarios.The results show the following:1)in 2020,the study area’s carbon sink decreased by 8.29×10^(4) t C/yr compared with that in 2010 and by 10.83×10^(4) t C/yr compared with that in 2000.High-carbon sinks were found mainly in mountainous areas,whereas low-carbon sinks are concentrated in urban con-struction land,rural residential areas,and land margins.2)From 2000 to 2020,the spatial security pattern of carbon metabolism tended to be‘high in the middle of the east and west and low in the gulf.’In 2000,2010,and 2020,16 stable carbon sinks were identified.The carbon energy flow density in Guangxi was greater than that in Guangdong and Hainan,with positive carbon flow corridors located primarily in Guangxi and Guangdong.The number of carbon sequestration nodes remained stable at approximately 15,mainly in Guangxi and Hainan.3)Scenario simulations revealed that under the Nature-based mild restoration scenario,the carbon sink rate will reach 611.85×10^(4) t C/yr by 2030 and increase to 612.45×10^(4) t C/yr by 2060,with stable carbon sinks increasing to 18.In the restora-tion scenario based on Anti-globalization,the carbon sink will decrease from 610.24×10^(4) t C/yr in 2030 to 605.19×10^(4) t C/yr in 2060,with the disappearance of some positive carbon flow corridors and stable carbon sinks.Under the Human-based sustainable restoration scenario,the carbon sink area will decrease from 607.00×10^(4) t C/yr in 2030 to 596.39×10^(4) t C/yr in 2060,with carbon sink areas frag-menting and positive carbon flow corridors becoming less dense.4)On the basis of the current and predicted CMSSPs,this study ex-plores spatial ecological restoration strategies for high-carbon storage areas in bay urban agglomerations at four levels:the land control region,urban agglomeration structure system,carbon sink structure and bay structure control region.
基金Under the auspices of National Natural Science Foundation of China(No.42201374,42071359)。
文摘The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.
基金Under the auspices of Zhejiang Provincial Natural Science Foundation of China(No.LY19C160007)。
文摘In recent years,rapid urbanization has had a profound impact on landscape stability.As a typical example of China's rapid urbanization,Hangzhou has also experienced significant landscape changes,which have profoundly affected its ecological stability.Taking Hangzhou as an example,this study integrates land use change data from 1980 to 2020,combines dynamic simulation and ecological modeling techniques,and carries out a comprehensive analysis of historical trends and future predictions,to provide valuable insights into the complex interactions between urban expansion and landscape stability.The results indicate that:1)between 1980 and2020,Hangzhou experienced a significant increase in construction land at the expense of arable land,leading to a gradual decline in landscape stability,though the downward trend has slowed in recent years.2)The spatial distribution of landscape stability shows clear aggregation patterns,with lower stability concentrated in economically active flatlands and higher stability in the mountainous western regions.3)By 2040,further urban expansion is predicted to occur alongside increased landscape integration,reflecting the positive effects of ecological protection strategies.This study highlights the universal challenges of balancing economic growth with ecological stability in rapidly urbanizing regions.The combination of advanced simulation models and spatiotemporal analysis demonstrates a replicable framework for assessing urban expansion's ecological impacts.These findings underscore the importance of tailoring urban planning and ecological policies to address regional disparities,providing valuable insights for sustainable urban development and landscape management globally.
基金Under the auspices of National Natural Science Foundation of China(No.42101393,41901375,52274166)Hebei Natural Science Foundation(No.D2022209005,D2023209008)Central Guided Local Science and Technology Development Fund Project of Hebei Province(No.236Z3305G,246Z4201G)Key Research and Development Program of Science and Technology Plan of Tangshan,China(No.22150221J)。
文摘Coastal wetlands are crucial for the‘blue carbon sink’,significantly contributing to regulating climate change.This study util-ized 160 soil samples,35 remote sensing features,and 5 geo-climatic data to accurately estimate the soil organic carbon stocks(SOCS)in the coastal wetlands of Tianjin and Hebei,China.To reduce data redundancy,simplify model complexity,and improve model inter-pretability,Pearson correlation analysis(PsCA),Boruta,and recursive feature elimination(RFE)were employed to optimize features.Combined with the optimized features,the soil organic carbon density(SOCD)prediction model was constructed by using multivariate adaptive regression splines(MARS),extreme gradient boosting(XGBoost),and random forest(RF)algorithms and applied to predict the spatial distribution of SOCD and estimate the SOCS of different wetland types in 2020.The results show that:1)different feature combinations have a significant influence on the model performance.Better prediction performance was attained by building a model using RFE-based feature combinations.RF has the best prediction accuracy(R^(2)=0.587,RMSE=0.798 kg/m^(2),MAE=0.660 kg/m^(2)).2)Optical features are more important than radar and geo-climatic features in the MARS,XGBoost,and RF algorithms.3)The size of SOCS is related to SOCD and the area of each wetland type,aquaculture pond has the highest SOCS,followed by marsh,salt pan,mud-flat,and sand shore.
基金Under the auspices of the National Natural Science Foundation of China(No.42277354,U2243211)Fundamental Research Funds for the Hebei University of Water Resources and Electric Engineering(No.SYKY2113)Science Research Project of Hebei Education Department(No.QN2025293)。
文摘Changes in river cross-section morphology have decisive influences on the flood discharge and sand transport capacity of rivers;thus,these changes strongly reflect the vitality of a river.In this paper,based on the river cross-section and water and sediment data of two different periods(1974−1987 and 2007−2021),the trend analysis,change-point analysis and sediment rating curve method were used to analyze the change process of river cross-section morphology and its response to streamflow and sediment changes in the main river stream of the Yellow River at the Longmen hydrological station.From 1974 to 1987(except in 1977),the riverbed experi-enced siltation,and the riverbed elevation rose.Conversely,from 2007 to 2021,the riverbed experienced scouring,and the riverbed el-evation gradually decreased.The cross-section shape changed from rectangular to U-shaped(deeper on the right side)at the Longmen cross-section.The changes in streamflow and sediment processes significantly impacted the evolution of river cross-section.Stream-flow(P<0.05),sediment discharge(P<0.01),and the sediment load coefficients(P<0.01)decreased significantly.The relationship between the water depth and sediment load coefficients followed a power function.The decreasing trend in sediment discharge was sig-nificantly stronger than that in streamflow.Suspended sediment particles tended to become finer.The sediment rating curve indicates that the sediment supply from upstream decreased while the erosive power in the river channel increased,leading to a gradual decline in riverbed elevation at the Longmen cross-section from 2007 to 2021.These findings help us better understand the impacts of ecological restoration on changes in river streamflow and sediment during river evolution.
基金Under the auspices of Key Project of the Ministry of Water Resources(No.E202291801,E203101901)National Key R&D Program of China(No.2019QZKK0401)。
文摘The Three Gorges Project,the largest water conservation initiative globally,is located within the Three Gorges Reservoir Area(TGRA),a critical zone for water conservation and ecological protection.There is an urgent need to better understand and protect the evolving water conservation functions of the TGRA,alongside identifying the driving mechanisms within its ecological barrier re-gion.This paper explores the spatial and temporal evolution of water conservation function in the TGRA from 1990 to 2020 and its fu-ture trends under different development scenarios from 2020 to 2030.Key driving factors influencing the water conservation function are identified,and a comprehensive development scenario is proposed.The findings indicate a general upward trend in the water conser-vation function of the TGRA,characterized by an initial increase,a subsequent decline,and a final recovery.Moreover,land use changes are found to be the primary factor driving these variations,followed by climatic factors such as precipitation.Under various de-velopment scenarios,the prioritization of water conservation outcomes is ranked as follows:ecological protection>cropland protec-tion>natural development>urban development.The results of this study offer valuable insights for balancing economic development with ecological preservation.
基金Under the auspices of the National Natural Science Foundation of China(No.41661088,32101593,42361028)Science and Technology Program of Guizhou Province(No.Qiankehe Zhongyindi[2023]005)+1 种基金2024 Humanities and Social Science Research Project of Guizhou Provincial Department of Education(No.24RWZX007)Graduate Research Fund Project of Guizhou Province(No.2024YJSKYJJ153)。
文摘Land use change is a fundamental factor affecting ecosystem’s structures and functions.However,few studies have explored the ecological disturbance caused by land use change from a combined structural and functional perspective.In this study,the ecological structural disturbance index(SDI)and functional disturbance index(FDI)were introduced to quantitatively evaluate ecological disturbance caused by land use change in a typical karst area—Huangping County,Guizhou Province,China during 2009–2019.Results show that although the area of ecological land increased during past 10 yr,there had been a fragmentation trend of ecological land.Agricultural occupation was more severe than construction encroachment on ecological land.The grids with negative structural disturbance were consistent with areas of obvious dynamic loss and gain of ecological land.Ecological fragmentation had a greater impact than habitat gain in grids with negative structural disturbance.The ecosystem service functions of supply,adjustment,support,and culture were obviously affected by land use change,and the total FDI reflects the trade-off among them.Negative FDI values were easily observed in the rocky desertification area or water and soil loss area.The combination analysis of the SDI and FDI indicated the characteristic of codirectional ecologically structural and functional disturbance in the majority of grids.The findings improve our understanding of multiple relationships among ecological disturbances and provide valuable information for guiding land use activities.
基金Under the auspices of National Natural Science Foundation of China(No.42171248,42371273)。
文摘As the core of spatial planning in China,delineation of the production-living-ecological space(PLES)refers to dividing the overall land use into three functional spaces.Spatial units are optimally configured as the most suitable functional type,while beset by various uncertainties.Weight uncertainties,being affected by subjective preferences,are highly arbitrary and seriously affect PLES.Taking Xuzhou as the study area,this paper studies the perturbation mechanism and response measure of weight uncertainties on PLES.First,weight samples are obtained through quasi-random sampling to serve as sources of uncertainties for input into the optimized delineation of PLES.Next,the Monte Carlo simulation is applied to simulate the spatial probability distribution of PLES.The global sensitivity analysis method is then adopted to identify the main sources that cause uncertainties in the delineation of PLES.Subsequently,the flexible space(FS)of PLES at a certain level of significance is formulated by comparing the distribution probabilities of spatial units for different functional spaces,acting as a countermeasure for the perturbation.The results show that weight uncertainties bring disturbances to the PLES by affecting the multi-criteria evaluation(MCE)of PLES delineation.The PLES is affected by the weight uncertainties of the factors alone or through interactions with other weights.FS is the spatial response measure of PLES when uncertainties occurred at a certain level of significance.The study introduces the perspective of uncertainty for PLES,which contributes toward improving the scientificity and reliability of PLES.
基金Under the auspices of National Natural Science Foundation of China(No.42401232,72050001)Natural Science Foundation of Gansu Province(No.24JRRA419)Research Funds for Blue Green Infrastructure Planning and Ecological Restoration in Mining Cities(No.071124044/(24)0315)。
文摘Urban open spaces(UOS)play a crucial role in enhancing city livability and resident well-being,yet there remains a gap in utilizing social media to analyze changes in UOS utilization across different COVID(Corona Virus Disease)-19 phases.Our research applied Sina Weibo data to scrutinize UOS engagement across pre-pandemic(2019),pandemic(2021),and post-pandemic(2023)periods in Lanzhou City,China,revealing evolving spatiotemporal patterns and highlighting the pandemic's impact on UOS usage.Initially,scenic mountains and urban parks dominated visitor preferences in 2019.However,during the pandemic,there was a trend towards destinations that combined elements of tourism,business,entertainment,and culture,reflecting a growing appetite for diverse experiences.Despite this shift,the post-pandemic period did not see a complete return to pre-pandemic travel patterns,with a noticeable decline in visits to traditional green open spaces during lockdowns.We identified key attractions in main urban areas,highlighting geographical variations in tourism and Cultural Ecosystem Services(CES)distribution that warrant further attention.The post-pandemic landscape reveals a resurging interest in green-blue spaces and nature-focused tourism,highlighting a continued preference for cultural and natural experiences,and emphasizing the need to harmonize development with the preservation of natural and cultural heritage.This study introduces the use of social media data across pandemic phases to guide UOS management,offering insights for creating resilient,multifunctional urban spaces that address public needs and enhance community well-being.
基金Under the auspices of National Natural Science Foundation of China(No.42271206)Guangdong Philosophy and Social Science Foundation(No.GD22XGL08)+1 种基金Basic and Applied Basic Research Foundation of Guangzhou(No.2024A04J4541)the Fundamental Research Funds for the Central Universities(No.2024ZYGXZR025,2024ZYGXZR003)。
文摘The rapid development of digital technologies has driven the emergence and popularization of online-to-offline(O2O)retail,reshaping the retail landscape in urban China.However,spatial distribution characteristics and influencing mechanisms of emerging O2O retail have not been thoroughly investigated in extant studies.Taking the central urban area of Guangzhou as the case,this study utilized multi-source data and machine learning methods to explore the distribution characteristics of O2O retail space and to further identify the nonlinear effects of the built environment,sociodemographic,and economic factors on its distribution.The results revealed that O2O retail space exhibited a‘single-center’distribution pattern,in contrast to the‘multi-center’distribution pattern of traditional retail space.This finding supported the diffusion of innovation hypothesis,highlighting that the expansion of O2O retail modes first spread from traditional developed retail space.Furthermore,spatial heterogeneities were observed across different types of O2O retail space,with O2O in-store showing a‘core-periphery’spatial structure as described by Central Place Theory,whereas O2O delivery displaying a‘horizontal,non-hierarchical,and multi-centered’network structure following Central Flow Theory.Compared to traditional retail space,the distribution of O2O retail space was more influenced by sociodemographic factors such as the proportion of youth,education level,and income level,but less affected by the built environment factors like office and building density.Furthermore,nonlinear effects of these influencing factors on the distribution of O2O retail space were identified,which enriched the existing literature by highlighting effective ranges and threshold effects.These findings provided valuable insights into O2O retail space development in the context of digital transformation.
