Ecosystem services,which include water yield services,have been incorporated into decision processes of regional land use planning and sustainable development.Spatial pattern characteristics and identification of fact...Ecosystem services,which include water yield services,have been incorporated into decision processes of regional land use planning and sustainable development.Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making.However,there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services.In this study,we used the Hengduan Mountain region in southwest China,with obvious spatial heterogeneity,as the research site.The water yield module in the InVEST software was used to simulate the spatial distribution of water yield.Also,quantitative attribution analysis was conducted for various geomorphological and climatic zones in the Hengduan Mountain region by using the geographical detector method.Influencing factors,such as climate,topography,soil,vegetation type,and land use type and pattern,were taken into consideration for this analysis.Four key findings were obtained.First,water yield spatial heterogeneity is influenced most by climate-related factors,where precipitation and evapotranspiration are the dominant factors.Second,the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphological and climatic zones.In flat areas,the influence of evapotranspiration is higher than that of precipitation.As relief increases,the importance of precipitation increases and eventually,it becomes the most influential factor.Evapotranspiration is the most influential factor in a plateau climate zone,while in the mid-subtropical zone,precipitation is the main controlling factor.Third,land use type is also an important driving force in flat areas.Thus,more attention should be paid to urbanization and land use planning,which involves land use changes,to mitigate the impact on water yield spatial pattern.The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas,shrub areas,and areas with slope<5°and 250-350 should be recognized as water yield important zones,while the corresponding elevation values are different among different geomorphological and climatic zones.Therefore,the spatial heterogeneity and influencing factors in different zones should be fully con-sidered while planning the maintenance and protection of water yield services in the Hengduan Mountain region.展开更多
Urban flooding is caused by multiple factors,which seriously restricts the sustainable development of society.Understanding the driving factors of urban flooding is pivotal to alleviating flood disasters.Although the ...Urban flooding is caused by multiple factors,which seriously restricts the sustainable development of society.Understanding the driving factors of urban flooding is pivotal to alleviating flood disasters.Although the effects of various factors on urban flooding have been extensively evaluated,few studies consider both interregional flood connection and interactions between driving factors.In this study,driving factors of urban flooding were analyzed based on the water tracer method and the optimal parameters-based geographical detector(OPGD).An urban flood simulation model coupled with the water tracer method was constructed to simulate flooding.Furthermore,interregional flood volume connection was analyzed based on simulation results.Subsequently,driving force of urban flooding factors and interactions between them were quantified using the OPGD model.Taking Haidian Island in Hainan Province,China as an example,the coupled model simulation results show that sub-catchment H6 is the region experiencing the most severe flooding and sub-catchment H9 contributes the most to overall flooding in the study area.The results of subsequent driving effect analysis show that elevation is the factor with the maximum single-factor driving force(0.772) and elevation ∩ percentage of building area is the pair of factors with the maximum two-factor driving force(0.968).In addition,the interactions between driving factors have bivariable or nonlinear enhancement effects.The interactions between two factors strengthen the influence of each factor on urban flooding.This study contributes to understanding the cause of urban flooding and provides a reference for urban flood risk mitigation.展开更多
Land use/cover change(LUCC)is a measure that offers insights into the interaction between human activities and the natural environment,which significantly impacts the ecological environment of a region.Based on data f...Land use/cover change(LUCC)is a measure that offers insights into the interaction between human activities and the natural environment,which significantly impacts the ecological environment of a region.Based on data from the period from 2000 to 2020 regarding land use,topography,climate,the economy,and population,this study investigates the spatial and temporal evolution of land use in the Liuchong River Basin,examining the inte-raction between human activities and the natural environment using the land use dynamics model,the transfer matrix model,the kernel density model,and the geodetic detector.The results indicate that:(1)The type of land cover in Liuchong River Basin primarily comprises cropland,forest,and shrubs,with the land use change mode mainly consisting of an increase in the impervious area and a decrease in surface area covered by shrubs.(2)The dynamic degree for single land use of barren,impervious,and waters indicates a significant increase,with areas covered by shrubs decreasing by 9.37%.In addition,the change in the degree of single land use for other types of cover is more stable,with the degree of comprehensive land use being 7.95%.The areas experiencing the greatest land use change in the watershed went through conditions that can be described as“sporadic distribution”to“dis-persed”to“relatively concentrated”.(3)Air temperature,rainfall,and elevation are important factors driving land use changes in the Liuchong River Basin.The impact of nighttime lighting,gross domestic product(GDP),and norma-lized difference vegetation index(NDVI)on land use change have gradually increased over time.The results of the interaction detection indicated that the explanatory power of the interaction between the driving factors in each pe-riod for land-use changes was always greater than that of any single factor.The results of this study offer evi-dence-based support and scientific references for spatial planning,soil and water conservation,and ecological restoration in a watershed.展开更多
Scrub typhus is a significant public health issue with a wide distribution and is influenced by various determinants.However,in order to effectively eradicate scrub typhus,it is crucial to identify the specific factor...Scrub typhus is a significant public health issue with a wide distribution and is influenced by various determinants.However,in order to effectively eradicate scrub typhus,it is crucial to identify the specific factors that contribute to its incidence at a detailed level.Therefore,the objective of our study is to identify these influencing factors,examine the spatial variations in incidence,and analyze the interplay of two factors on scrub typhus incidence,so as to provide valuable experience for the prevention and treatment of scrub typhus in Gannan and to alleviate the economic burden of the local population.This study employed spatial autocorrelation analyses to examine the dependent variable and ordinary least squares model residuals.Additionally,spatial regression modelling and geographical detector were used to analyze the factors influencing the annual mean 14-year incidence of scrub typhus in the streets/townships of Gannan region from 2008 to 2021.The results of spatial1 autocorrelation analyses indicated the presence of spatial correlation.Among the global spatial regression models,the spatial lag model was found to be the best fitting model(log likelihood ratio?319.3029,AIC?666.6059).The results from the SLM analysis indicated that DEM,mean temperature,and mean wind speed were the primary factors influencing the occurrence of scrub typhus.For the local spatial regression models,the multiscale geographically weighted regression was determined to be the best fitting model(adjusted R2?0.443,AICc?726.489).Further analysis using the MGWR model revealed that DEM had a greater impact in Xinfeng and Longnan,while the southern region was found to be more susceptible to scrub typhus due to mean wind speed.The geographical detector results revealed that the incidence of scrub typhus was primarily influenced by annual average normalized difference vegetation index.Additionally,the interaction between GDP and the percentage of grassland area had a significant impact on the incidence of scrub typhus(q?0.357).This study illustrated the individual and interactive effects of natural environmental factors and socio-economic factors on the incidence of scrub typhus;and elucidated the specific factors affecting the incidence of scrub typhus in various streets/townships.The findings of this study can be used to develop effective interventions for the prevention and control of scrub typhus.展开更多
Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multi...Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multiple biological characteristics and social factors but also factors can play a role.Few studies have assessed the exact and interactive influence of each factor promoting schistosomiasis transmission.Methods:We used a series of different detectors(i.e.,specific detector,risk detector,ecological detector and interaction detector)to evaluate separate and interactive effects of the environmental factors on schistosomiasis prevalence.Specifically,(i)specific detector quantifies the impact of a risk factor on an observed spatial disease pattern,which were ranked statistically by a value of Power of Determinate(PD)calculation;(ii)risk detector detects high risk areas of a disease on the condition that the study area is stratified by a potential risk factor;(iii)ecological detector explores whether a risk factor is more significant than another in controlling the spatial pattern of a disease;(iv)interaction detector probes whether two risk factors when taken together weaken or enhance one another,or whether they are independent in developing a disease.Infection data of schistosomiasis based on conventional surveys were obtained at the county level from the health authorities in Anhui Province,China and used in combination with information from Chinese weather stations and internationally available environmental data.Results:The specific detector identified various factors of potential importance as follows:Proximity to Yangtze River(0.322)>Land cover(0.285)>sunshine hours(0.256)>population density(0.109)>altitude(0.090)>the normalized different vegetation index(NDVI)(0.077)>land surface temperature at daytime(LST_(day))(0.007).The risk detector indicated that areas of schistosomiasis high risk were located within a buffer distance of 50 km from Yangtze River.The ecological detector disclosed that the factors investigated have significantly different effects.The interaction detector revealed that interaction between the factors enhanced their main effects in most cases.Conclusion:Proximity to Yangtze River had the strongest effect on schistosomiasis prevalence followed by land cover and sunshine hours,while the remaining factors had only weak influence.Interaction between factors played an even more important role in influencing schistosomiasis prevalence than each factor on its own.High risk regions influenced by strong interactions need to be targeted for disease control intervention.展开更多
Surface albedo directly affects the radiation balance and surface heat budget,and is a crucial variable in local and global climate research.In this study,the spatial and temporal distribution of the surface albedo is...Surface albedo directly affects the radiation balance and surface heat budget,and is a crucial variable in local and global climate research.In this study,the spatial and temporal distribution of the surface albedo is analysed for Beijing in 2015,and the corresponding individual and interactive driving forces of different explanatory factors are quantitatively assessed based on geographical detectors.The results show that surface albedo is high in the southeast and low in the northwest of Beijing,with the greatest change occurring in winter and the smallest change occurring in spring.The minimum and maximum annual surface albedo values occurred in autumn and winter,respectively,and showed significant spatial and temporal heterogeneity.LULC,NDVI,elevation,slope,temperature,and precipitation each had a significant influence on the spatial pattern of albedo,yielding explanatory power values of 0.537,0.625,0.512,0.531,0.515 and 0.190,respectively.Some explanatory factors have significant differences in influencing the spatial distribution of albedo,and there is significant interaction between them which shows the bivariate enhancement result.Among them,the interaction between LULC and NDVI was the strongest,with a q-statistic of 0.710,while the interaction between temperature and precipitation was the weakest,with a q-statistic of 0.531.The results of this study provide a scientific basis for understanding the spatial and temporal distribution characteristics of surface albedo in Beijing and the physical processes of energy modules in regional climate and land surface models.展开更多
Resource-based cities are the most important players in responding to climate change and achieving low carbon development in China.An analysis of relevant data(such as the energy consumption)showed an inter-city diffe...Resource-based cities are the most important players in responding to climate change and achieving low carbon development in China.An analysis of relevant data(such as the energy consumption)showed an inter-city differentiation of CO2 emissions from energy consumption,and suggested an influence of the Industrial Enterprises above Designated Size(IEDS)in resource-based industrial cities at the prefecture level and above in different regions.Then by geographical detector technology,the sizes of each influencing mechanism on CO2 emissions from energy consumption of the IEDS were probed.This analysis showed that significant spatial differences exist for CO2 emissions from energy consumption and revealed several factors which influence the IEDS in resource-based cities.(1)In terms of unit employment,Eastern and Western resource-based cities are above the overall level of all resource-based cities;and only Coal resource-based cities far exceeded the overall level among all of the cities in the analysis.(2)In terms of unit gross industrial output value,the Eastern,Central and Western resources-based cities are all above the overall level for all the cities.Here also,only Coal resource-based cities far exceeded the overall level of all resources-based cities.Economic scale and energy structure are the main factors influencing CO2 emissions from energy consumption of the IEDS in resource-based cities.The factors influencing CO2 emissions in different regions and types of resource-based cities show significant spatial variations,and the degree of influence that any given factor exerts varies among different regions and types of resource-based cities.Therefore,individualized recommendations should be directed to different regions and types of resource-based cities,so that the strategies and measures of industrial low carbon and transformation should vary greatly according to the specific conditions that exist in each city.展开更多
Background:A remarkable drop in tuberculosis(TB)incidence has been achieved in China,although in 2019 it was still considered the second most communicable disease.However,TB’s spatial features and risk factors in urb...Background:A remarkable drop in tuberculosis(TB)incidence has been achieved in China,although in 2019 it was still considered the second most communicable disease.However,TB’s spatial features and risk factors in urban areas remain poorly understood.This study aims to identify the spatial diferentiations and potential infuencing factors of TB in highly urbanized regions on a fne scale.Methods:This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou,China.TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention.Before using Pearson correlation and a geographical detector(GD)to identify potential infuencing factors,we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales.Results:Owing to its strong spatial autocorrelation(Moran’s I=0.33,Z=4.71),the 2 km×2 km grid was selected as the spatial scale.At this level,TB incidence was closely associated with most socioeconomic variables(0.31<r<0.76,P<0.01).Of fve environmental factors,only the concentration of fne particulate matter displayed signifcant correlation(r=0.21,P<0.05).Similarly,in terms of q values derived from the GD,socioeconomic variables had stronger explanatory abilities(0.08<q<0.57)for the spatial diferentiation of the 2017 incidence of TB than environmental variables(0.06<q<0.27).Moreover,a much larger proportion(0.16<q<0.89)of the spatial diferentiation was interpreted by pairwise interactions,especially those(0.60<q<0.89)related to the 2016 incidence of TB,ofcially appointed medical institutions,bus stops,and road density.Conclusions:The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably infuenced by several socioeconomic and environmental factors and their pairwise interactions on a fne scale.We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou.Our study provides helpful clues for local authorities implementing more efective intervention measures to reduce TB incidence in China’s municipal areas,which are featured by both a high degree of urbanization and a high incidence of TB.展开更多
The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the a...The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the air quality in the NKEFAs.This study presented the current status of the air quality in the NKEFAs and its driving factors using the geographic detector q-statistic method.The air quality in the NKEFAs was overall better than individual cities and urban agglomeration in eastern coast provinces of China,accounting for 9.21%of the days with air quality at Level III or above.The primary air pollutant was PM_(10),followed by PM_(2.5),with lower concentrations of the remaining pollutants.Pollution was more severe in the sand fixation areas,where air pollution was worst in spring and best in autumn,contrasting with other NKEFAs and individual cities and urban agglomerations.The main influencing factors of air quality index(AQI)in the NKEFAs were land use type,wind speed,and relative humidity also weighted more heavily than factors such as industrial pollution and anthropogenic emissions,and most of these influence factors have two types of interactive effects:binary and nonlinear enhancements.These results indicated that air pollution in the NKEFAs was not related with the emission by intensive economic development.Thus,the policies taking the NKEFAs as restricted development zones were effective,but the air pollution caused by PM_(10) also showed the ecological status in the NKEFAs,especially at sand fixation areas was not quite optimistic,and more strict environmental protection measures should be taken to improve the ecological status in these NKEFAs.展开更多
There is an issue of groundwater overexploitation in Ningjiang District,Songyuan City,Jilin Province,which has led to land subsidence.To investigate the influence of hydrological elements on surface deformation in Nin...There is an issue of groundwater overexploitation in Ningjiang District,Songyuan City,Jilin Province,which has led to land subsidence.To investigate the influence of hydrological elements on surface deformation in Ningjiang District,surface deformation data were obtained by the small baseline subset interferometry synthetic aperture radar(SBAS-InSAR)technique.Initially,Sentinel-1B data were utilized to observe surface deformation in Ningjiang District from 2017 to 2021 with SBAS-InSAR.Subsequently,the geographical detector was employed to quantitatively assess the relationship between land subsidence and its influencing factors.Furthermore,multivariate singular spectrum analysis(M-SSA)was employed to identify periodic fluctuations in surface deformation and groundwater level,revealing the temporal lag between fluctuations in surface deformation and groundwater level.The findings demonstrate that the distance to water bodies accounts for the largest share of subsidence variation,with subsidence shaped by the combined impact of many factors.The results of interaction detection indicate that the interplay between the distance to water bodies and precipitation exhibits the most significant joint explanatory capacity for surface deformation.The observed seasonal cyclical fluctuations in groundwater level and surface deformation indicate a substantial influence of groundwater on surface deformation in the Ningjiang District.展开更多
Human-wildlife conflict(HWC)and its socioeconomic impacts are a pressing global issue.Accurately quantifying HWCs and their interaction with residential development is crucial for rural revitalization and biodiversity...Human-wildlife conflict(HWC)and its socioeconomic impacts are a pressing global issue.Accurately quantifying HWCs and their interaction with residential development is crucial for rural revitalization and biodiversity conservation efforts.This study investigates the interplay between rural residential expansion(RRE)with humanelephant conflict(HEC)in southern Yunnan Province using high-accuracy yearly land use/land cover data and Asian elephant accident data.A piecewise regression along with several metrics,including expansion intensity,rate of rural residential land,and residential density,were employed to analyze the spatial-temporal change characteristics of RRE.Then,a geographical detector and a bivariate spatial autocorrelation model were used to reveal the driving mechanisms of RRE,with particular emphasis on the spatial relations between RRE and HECs.The results indicate that HECs had a significant negative impact on RRE,exhibiting higher expansion intensity and rate of rural residential land in non-HEC areas than in HEC areas.High spatiotemporal consistency between accelerated RRE and intensified HECs occurred from 2010 onwards,which aligns with the year when the trend of settlement area expansion changed.RRE activities and ensuing land use conversions led to increased occurrences of HECs,which negatively affected the RRE.Compared to HECs,topography and locational factors exhibited a secondary effect on RRE activities.The findings underscore reciprocal feedback mechanisms between RRE and HECs and the elevated risk of adverse interactions between humans and elephants within the range of China’s wild elephants,providing theoretical support for coordinating conservation initiatives for Asian elephants with rural revitalization in the border areas of Southwest China.展开更多
Scientific understanding of the trade-offs between services is crucial for the scientific management and protection of ecosystems and the formulation of resource management policies.This study integrated meteorologica...Scientific understanding of the trade-offs between services is crucial for the scientific management and protection of ecosystems and the formulation of resource management policies.This study integrated meteorological,land use,and soil data to assess the ecosystem services,namely,water yield(WY),soil erosion(SE),and carbon sinks(CS),in peak-cluster depression basins on the Sino-Vietnamese border in China during 2000-2020.It analyzed the trade-offs and synergistic relationships among the three ecosystem services and their time-lag effects and driving mechanisms with the help of pixel-by-pixel time-lag intercorrelation and geographical de-tector methods.Results show that:1)from 2000 to 2020,the key ecosystem service indicators in the peak-cluster depression basins on the Sino-Vietnamese border in China demonstrated a significant and synergistic trend of positive change.The WY increased at a rate of 11.99 mm/yr,CS increased at a rate of 2.44 g C/(m^(2)∙yr),and SE decreased at a rate of 0.06 t/(ha∙yr).2)Most areas showed a synergistic relationship across the three ecosystem services,and the areas with a trade-off relationship were mostly concentrated in Baise City and the southwest of Chongzuo City,Guangxi.3)The time-lag effect between SE and WY was mostly concentrated in 0 yr,that between SE and CS was mostly concentrated in 5 yr,and that between CS and WY was mostly concentrated in 1 yr.4)Population density was the controlling factor between SE and WY.Vegetation coverage factor is the main controlling factor between SE and CS.The lithologic factor is the main controlling factor between CS and WY.Studying the trade-off relationship of ecosystem services at spatial and tem-poral scales on the Sino-Vietnamese border in China karst areas can provide a basis for regional ecological construction and develop-ment strategies,and it is conducive to meeting regional interest needs,maximizing comprehensive benefits,balancing the ecological en-vironment,and achieving regional sustainable development.展开更多
Regular quantitative assessments of regional ecological environment quality(EEQ)and driving force analyses are highly important for environmental protection and sustainable development.Northern China is a typical clim...Regular quantitative assessments of regional ecological environment quality(EEQ)and driving force analyses are highly important for environmental protection and sustainable development.Northern China is a typical climate-sensitive and ecologically vulnerable area,however,the changes in EEQ in this region and their underlying causes remain unclear.Traditional evaluations of EEQ rely primarily on the remote sensing ecological index(RSEI),which lacks assessments of indicators such as greenness(NDVI),humidity(WET),heat(LST),and dryness(NDBSI).To address these issues,this study employs the principal component analysis method and the Google Earth Engine to construct an RSEI suitable for long-term and large-scale applications and analyzes the spatio-temporal variations in the RSEI,NDVI,WET,NDBSI,and LST.Additionally,geographical detectors are utilized to analyze the driving factors affecting EEQ.The results indicate the following.(1)The RSEI shows a fluctuating upward trend,with an average value of 0.4566,indicating a gradual improvement in EEQ.The EEQ exhibited significant spatial heterogeneity,with a pattern of lower values in the west and higher values in the east.(2)The NDVI and WET exhibit fluctuating increasing trends,indicating improvements in both indices.The NDBSI shows a fluctuating decreasing trend,whereas the LST presents a fluctuating increasing trend,suggesting an improvement in the NDBSI and a slight deterioration in the LST.NDVI and WET demonstrate a spatial pattern characterized by low values in the west and high values in the east.NDBSI and LST demonstrate a spatial pattern characterized by low values in the east and high values in the west.(3)Land use types and precipitation are the primary driving factors influencing the spatial differentiation of the EEQ.The explanatory power of these driving factors significantly increases under their interactions,particularly the interaction between land use types and other driving factors.This study fills the gap in existing EEQ evaluations that analyze only the RSEI without considering the NDVI,WET,NDBSI,and LST.The findings provide new insights for EEQ assessments and serve as a scientific reference for environmental protection and sustainable development.展开更多
This study investigated the spatio-temporal variation characteristics of ecosystem service value(ESV)alongside its driving influencing factors,thereby offering valuable theoretical insights for the sustainable develop...This study investigated the spatio-temporal variation characteristics of ecosystem service value(ESV)alongside its driving influencing factors,thereby offering valuable theoretical insights for the sustainable development of Jingzhou City,Hubei Province.Based on the land use data for Jingzhou City from 2000 to 2020,this study quantified the value of the ecological environment using the equivalent factor method.Furthermore,it analyzed and elucidated the spatio-temporal heterogeneity and driving mechanisms of ecosystem services in Jingzhou City.The results indicated that between 2000 and 2020,cultivated land(66.40%)and water area(18.82%)were the predominant land use types in Jingzhou City.The areas of water area and construction land exhibited a growth trend during this period.Construction land had the highest rate of land use change,followed by water area and cultivated land.Land use transitions primarily occurred between cultivated land and water area,as well as between cultivated land and construction land.The total value of ecosystem services in Jingzhou City increased by 165.07%from 2000 to 2020.ESV exhibited an upward trend from 2000 to 2015,followed by a gradual decline from 2015 to 2020.The ranking of individual ecosystem services,in descending order,was as follows:regulation services,supporting services,provisioning services,and cultural services.High-value ESV areas were predominantly situated in the water area of Lake Honghu,while low-value regions were mainly found in the cultivated land in the central and western parts of Jingzhou City.The spatial differentiation of ESV in Jingzhzou City was influenced by both natural and socio-economic factors,with natural factors exerting a more significant impact than socioeconomic factors.Specifically,the Normalized Difference Vegetation Index(NDVI)was the dominant environmental factor,while GDP plays a synergistic role.展开更多
As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification...As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.展开更多
The health of cropland systems is directly related to the degree of food security guarantee,and the‘quantity-quality-ecology as a whole’protection is of great significance for maintaining the health of cropland syst...The health of cropland systems is directly related to the degree of food security guarantee,and the‘quantity-quality-ecology as a whole’protection is of great significance for maintaining the health of cropland systems.Taking the typical black soil region in Northeast China(TBSN)as an example,this paper combined the concept of‘quantity-quality-ecology as a whole’protection with crop-land systems health,constructed a health assessment model for cropland systems,and used Google Earth Engine to conduct a quantitat-ive analysis of the temporal and spatial evolution of cropland systems health in TBSN during 2003–2023.By coupling the geographical detector and the Multi-scale Geographically Weighted Regression(MGWR)model,the driving factors of cropland health changes were explored.The study finds that during the research period,the health status of cropland systems in TBSN showed a slight downward trend,and the distribution pattern of cropland systems health gradually shifted from‘better in the east’to‘high in the northeast and low in the southwest’.Changes in average annual sunshine duration,relative humidity,and precipitation had a significant impact on the spa-tial differentiation of cropland systems health in the early stages,and were considered as dominant factors.Meanwhile,the influence of dual dominant factors in the natural environment on cropland systems health is increasing.Furthermore,the MGWR model performed better in revealing the complex relationships between natural and social factors and changes in cropland systems health,demonstrating the significant spatial heterogeneity of the impacts of natural environment and human activities on cropland systems health.The re-search can provide scientific guidance for the sustainable development of TBSN and formulate more precise and effective cropland pro-tection policies.展开更多
Understanding the influencing factors of ecosystem services(ESs)and their relationships is essential for sustainable ecosystem management in degraded alpine ecosystems.There is a lack of integrated multi-model approac...Understanding the influencing factors of ecosystem services(ESs)and their relationships is essential for sustainable ecosystem management in degraded alpine ecosystems.There is a lack of integrated multi-model approaches to explore the multidimensional influences on ESs and their relationships in alpine ecosystems.Taking the Daxing'anling forest area,Inner Mongolia(DFAIM)as a case study,this study used the integrated valuation of ecosystem services and trade-offs(InVEST)model to quantify four ESs—soil conservation(SC),water yield(WY),carbon storage(CS),and habitat quality(HQ)—from 2013 to 2018.We adopted root mean square deviation(RMSD)and coupling coordination degree models(CCDM)to analyze their relationships,and integrated three complementary approaches—optimal parameter-based geographical detector model(OPGDM),gradient boosting regression tree model(GBRTM),and quantile regression model(QRM)—to reveal multidimensional influencing factors.Key findings include the following:(1)From 2013 to 2018,WY,SC,and HQ declined while CS increased.WY was primarily influenced by mean annual precipitation(MAP),forest ratio(RF),and soil bulk density(SBD);CS and HQ by RF and population density(PD);and SC by slope(S),RF,and MAP.Mean annual temperature(MAT),gross domestic product(GDP),and road network density(RND)showed increasing negative impacts.(2)Low trade-off intensity(TI<0.15)dominated all ES pairs,with RF,MAP,PD,and normalized difference vegetation index(NDVI)being the dominant factors.The factor interactions primarily showed two-factor enhancement patterns.(3)The average coupling coordination degree(CCD)of the four ESs was low and declined over time,with low-CCD areas becoming increasingly prevalent.RF,S,SBD,and NDVI positively influenced CCD,while PD,MAT,GDP,and RND had increasing negative impacts,with over 62%of the factor interactions exceeding the individual factor effects.In summary,ES supply generally decreased.Local relationships showed moderate coordination,while overall relationships indicated primary dysfunction.Land use and natural factors primarily shaped these ES and their relationships,while climate and socioeconomic changes diminished ES supply and intensified competition.We recommend enhancing the resilience of natural systems rather than replacing them,establishing climate adaptation monitoring systems,and promoting conservation tillage and cross-departmental coordination mechanisms for collaborative ES optimization.These results provide valuable insights into the sustainable management of alpine ecosystems.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
The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ec...The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.展开更多
Terrain and geological formation are crucial natural environmental factors that constrain land use and land cover changes.Studying their regulatory role in regional land use and land cover changes is significant for g...Terrain and geological formation are crucial natural environmental factors that constrain land use and land cover changes.Studying their regulatory role in regional land use and land cover changes is significant for guiding regional land resource management.Taking the Danjiang River Basin in the Qinling Mountains of China as an example,this paper incorporates terrain(elevation,slope,and aspect)factors and geological formation to comprehensively analyse the differentiation characteristics of land use spatial patterns based on the examination of land use changes in 2000,2010,and 2020.Moreover,the geographical detector is employed to compare and analyse the effect of each factor on the spatial heterogeneity of land use.The results show that:(1)From 2000 to 2020,the areas of arable land and forestland in the Danjiang River Basin decreased while the areas of grassland,water areas,construction land,and unused land continuously increased.The comprehensive land use dynamics index was+0.09%,indicating a generally low level of land development.(2)Differences in the natural environmental factors of terrain and geological formation have a significant controlling effect on the spatial heterogeneity of land use.Specifically,there are notable differences in the advantageous distribution characteristics of various land use types across different levels of influencing factors.(3)The factor detection results reveal that geological formation has the strongest influence on the spatial heterogeneity of land use,followed by elevation and slope while aspect has the weakest influence.After the interaction among the factors,they nonlinearly enhance the explanation of spatial heterogeneity in land use.Overall,the influence of geological formation on the spatial heterogeneity of land use is greater than that of terrain factors.This study provides new geological evidence for natural resource management departments to conduct regional spatial planning,ecological and environmental protection and restoration,and land structure optimization and adjustment.展开更多
基金National Basic Research Program of China,No.2015CB452702National Natural Science Foundation of China,No.41571098.No.41530749+1 种基金National Key R&D Program of China,No.2017YFC1502903Major Consulting Project of Strategic Development Institute,Chinese Academy of Sciences,No.Y02015001。
文摘Ecosystem services,which include water yield services,have been incorporated into decision processes of regional land use planning and sustainable development.Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making.However,there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services.In this study,we used the Hengduan Mountain region in southwest China,with obvious spatial heterogeneity,as the research site.The water yield module in the InVEST software was used to simulate the spatial distribution of water yield.Also,quantitative attribution analysis was conducted for various geomorphological and climatic zones in the Hengduan Mountain region by using the geographical detector method.Influencing factors,such as climate,topography,soil,vegetation type,and land use type and pattern,were taken into consideration for this analysis.Four key findings were obtained.First,water yield spatial heterogeneity is influenced most by climate-related factors,where precipitation and evapotranspiration are the dominant factors.Second,the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphological and climatic zones.In flat areas,the influence of evapotranspiration is higher than that of precipitation.As relief increases,the importance of precipitation increases and eventually,it becomes the most influential factor.Evapotranspiration is the most influential factor in a plateau climate zone,while in the mid-subtropical zone,precipitation is the main controlling factor.Third,land use type is also an important driving force in flat areas.Thus,more attention should be paid to urbanization and land use planning,which involves land use changes,to mitigate the impact on water yield spatial pattern.The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas,shrub areas,and areas with slope<5°and 250-350 should be recognized as water yield important zones,while the corresponding elevation values are different among different geomorphological and climatic zones.Therefore,the spatial heterogeneity and influencing factors in different zones should be fully con-sidered while planning the maintenance and protection of water yield services in the Hengduan Mountain region.
基金supported by the National Natural Science Foundation of China(Grant No.52379019,42477501)the Key Research and Development Program of Ningxia Hui Autonomous Region(Grant No.2022BEG02020).
文摘Urban flooding is caused by multiple factors,which seriously restricts the sustainable development of society.Understanding the driving factors of urban flooding is pivotal to alleviating flood disasters.Although the effects of various factors on urban flooding have been extensively evaluated,few studies consider both interregional flood connection and interactions between driving factors.In this study,driving factors of urban flooding were analyzed based on the water tracer method and the optimal parameters-based geographical detector(OPGD).An urban flood simulation model coupled with the water tracer method was constructed to simulate flooding.Furthermore,interregional flood volume connection was analyzed based on simulation results.Subsequently,driving force of urban flooding factors and interactions between them were quantified using the OPGD model.Taking Haidian Island in Hainan Province,China as an example,the coupled model simulation results show that sub-catchment H6 is the region experiencing the most severe flooding and sub-catchment H9 contributes the most to overall flooding in the study area.The results of subsequent driving effect analysis show that elevation is the factor with the maximum single-factor driving force(0.772) and elevation ∩ percentage of building area is the pair of factors with the maximum two-factor driving force(0.968).In addition,the interactions between driving factors have bivariable or nonlinear enhancement effects.The interactions between two factors strengthen the influence of each factor on urban flooding.This study contributes to understanding the cause of urban flooding and provides a reference for urban flood risk mitigation.
基金The National Natural Science Foundation of China (U1812401)The Science and Technology Support Plan in Guizhou Province (G[2020]4Y016)+1 种基金The 2019 Philosophy and Social Science Planning Key Topics in Guizhou Province (19GZZD07)The Guizhou Provincial Water Resources Science and Technology Funding Program (KT202108)。
文摘Land use/cover change(LUCC)is a measure that offers insights into the interaction between human activities and the natural environment,which significantly impacts the ecological environment of a region.Based on data from the period from 2000 to 2020 regarding land use,topography,climate,the economy,and population,this study investigates the spatial and temporal evolution of land use in the Liuchong River Basin,examining the inte-raction between human activities and the natural environment using the land use dynamics model,the transfer matrix model,the kernel density model,and the geodetic detector.The results indicate that:(1)The type of land cover in Liuchong River Basin primarily comprises cropland,forest,and shrubs,with the land use change mode mainly consisting of an increase in the impervious area and a decrease in surface area covered by shrubs.(2)The dynamic degree for single land use of barren,impervious,and waters indicates a significant increase,with areas covered by shrubs decreasing by 9.37%.In addition,the change in the degree of single land use for other types of cover is more stable,with the degree of comprehensive land use being 7.95%.The areas experiencing the greatest land use change in the watershed went through conditions that can be described as“sporadic distribution”to“dis-persed”to“relatively concentrated”.(3)Air temperature,rainfall,and elevation are important factors driving land use changes in the Liuchong River Basin.The impact of nighttime lighting,gross domestic product(GDP),and norma-lized difference vegetation index(NDVI)on land use change have gradually increased over time.The results of the interaction detection indicated that the explanatory power of the interaction between the driving factors in each pe-riod for land-use changes was always greater than that of any single factor.The results of this study offer evi-dence-based support and scientific references for spatial planning,soil and water conservation,and ecological restoration in a watershed.
基金provided by the Science and Technology Program of Jiangxi Provincial Health andWellness Commission(Grant No.SKJP220226866).
文摘Scrub typhus is a significant public health issue with a wide distribution and is influenced by various determinants.However,in order to effectively eradicate scrub typhus,it is crucial to identify the specific factors that contribute to its incidence at a detailed level.Therefore,the objective of our study is to identify these influencing factors,examine the spatial variations in incidence,and analyze the interplay of two factors on scrub typhus incidence,so as to provide valuable experience for the prevention and treatment of scrub typhus in Gannan and to alleviate the economic burden of the local population.This study employed spatial autocorrelation analyses to examine the dependent variable and ordinary least squares model residuals.Additionally,spatial regression modelling and geographical detector were used to analyze the factors influencing the annual mean 14-year incidence of scrub typhus in the streets/townships of Gannan region from 2008 to 2021.The results of spatial1 autocorrelation analyses indicated the presence of spatial correlation.Among the global spatial regression models,the spatial lag model was found to be the best fitting model(log likelihood ratio?319.3029,AIC?666.6059).The results from the SLM analysis indicated that DEM,mean temperature,and mean wind speed were the primary factors influencing the occurrence of scrub typhus.For the local spatial regression models,the multiscale geographically weighted regression was determined to be the best fitting model(adjusted R2?0.443,AICc?726.489).Further analysis using the MGWR model revealed that DEM had a greater impact in Xinfeng and Longnan,while the southern region was found to be more susceptible to scrub typhus due to mean wind speed.The geographical detector results revealed that the incidence of scrub typhus was primarily influenced by annual average normalized difference vegetation index.Additionally,the interaction between GDP and the percentage of grassland area had a significant impact on the incidence of scrub typhus(q?0.357).This study illustrated the individual and interactive effects of natural environmental factors and socio-economic factors on the incidence of scrub typhus;and elucidated the specific factors affecting the incidence of scrub typhus in various streets/townships.The findings of this study can be used to develop effective interventions for the prevention and control of scrub typhus.
基金This research was supported by the National Natural Science Foundation of China(81673239)the National Science Fund for Distinguished Young Scholars(No.81325017)+1 种基金Chang Jiang Scholars Program(No.T2014089)the Fourth Round of Three-Year Public Health Action Plan of Shanghai,China(15GWZK0202,15GWZK0101).
文摘Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multiple biological characteristics and social factors but also factors can play a role.Few studies have assessed the exact and interactive influence of each factor promoting schistosomiasis transmission.Methods:We used a series of different detectors(i.e.,specific detector,risk detector,ecological detector and interaction detector)to evaluate separate and interactive effects of the environmental factors on schistosomiasis prevalence.Specifically,(i)specific detector quantifies the impact of a risk factor on an observed spatial disease pattern,which were ranked statistically by a value of Power of Determinate(PD)calculation;(ii)risk detector detects high risk areas of a disease on the condition that the study area is stratified by a potential risk factor;(iii)ecological detector explores whether a risk factor is more significant than another in controlling the spatial pattern of a disease;(iv)interaction detector probes whether two risk factors when taken together weaken or enhance one another,or whether they are independent in developing a disease.Infection data of schistosomiasis based on conventional surveys were obtained at the county level from the health authorities in Anhui Province,China and used in combination with information from Chinese weather stations and internationally available environmental data.Results:The specific detector identified various factors of potential importance as follows:Proximity to Yangtze River(0.322)>Land cover(0.285)>sunshine hours(0.256)>population density(0.109)>altitude(0.090)>the normalized different vegetation index(NDVI)(0.077)>land surface temperature at daytime(LST_(day))(0.007).The risk detector indicated that areas of schistosomiasis high risk were located within a buffer distance of 50 km from Yangtze River.The ecological detector disclosed that the factors investigated have significantly different effects.The interaction detector revealed that interaction between the factors enhanced their main effects in most cases.Conclusion:Proximity to Yangtze River had the strongest effect on schistosomiasis prevalence followed by land cover and sunshine hours,while the remaining factors had only weak influence.Interaction between factors played an even more important role in influencing schistosomiasis prevalence than each factor on its own.High risk regions influenced by strong interactions need to be targeted for disease control intervention.
基金The Major Project of High Resolution Earth Observation System(06-Y30F04-9001-2022)The National Natural Science Foundation of China(41471423)。
文摘Surface albedo directly affects the radiation balance and surface heat budget,and is a crucial variable in local and global climate research.In this study,the spatial and temporal distribution of the surface albedo is analysed for Beijing in 2015,and the corresponding individual and interactive driving forces of different explanatory factors are quantitatively assessed based on geographical detectors.The results show that surface albedo is high in the southeast and low in the northwest of Beijing,with the greatest change occurring in winter and the smallest change occurring in spring.The minimum and maximum annual surface albedo values occurred in autumn and winter,respectively,and showed significant spatial and temporal heterogeneity.LULC,NDVI,elevation,slope,temperature,and precipitation each had a significant influence on the spatial pattern of albedo,yielding explanatory power values of 0.537,0.625,0.512,0.531,0.515 and 0.190,respectively.Some explanatory factors have significant differences in influencing the spatial distribution of albedo,and there is significant interaction between them which shows the bivariate enhancement result.Among them,the interaction between LULC and NDVI was the strongest,with a q-statistic of 0.710,while the interaction between temperature and precipitation was the weakest,with a q-statistic of 0.531.The results of this study provide a scientific basis for understanding the spatial and temporal distribution characteristics of surface albedo in Beijing and the physical processes of energy modules in regional climate and land surface models.
基金The Ministry of Education on Cultivate Project Fund of Philosophy and Social Science Research Development Report(13JBGP004)
文摘Resource-based cities are the most important players in responding to climate change and achieving low carbon development in China.An analysis of relevant data(such as the energy consumption)showed an inter-city differentiation of CO2 emissions from energy consumption,and suggested an influence of the Industrial Enterprises above Designated Size(IEDS)in resource-based industrial cities at the prefecture level and above in different regions.Then by geographical detector technology,the sizes of each influencing mechanism on CO2 emissions from energy consumption of the IEDS were probed.This analysis showed that significant spatial differences exist for CO2 emissions from energy consumption and revealed several factors which influence the IEDS in resource-based cities.(1)In terms of unit employment,Eastern and Western resource-based cities are above the overall level of all resource-based cities;and only Coal resource-based cities far exceeded the overall level among all of the cities in the analysis.(2)In terms of unit gross industrial output value,the Eastern,Central and Western resources-based cities are all above the overall level for all the cities.Here also,only Coal resource-based cities far exceeded the overall level of all resources-based cities.Economic scale and energy structure are the main factors influencing CO2 emissions from energy consumption of the IEDS in resource-based cities.The factors influencing CO2 emissions in different regions and types of resource-based cities show significant spatial variations,and the degree of influence that any given factor exerts varies among different regions and types of resource-based cities.Therefore,individualized recommendations should be directed to different regions and types of resource-based cities,so that the strategies and measures of industrial low carbon and transformation should vary greatly according to the specific conditions that exist in each city.
文摘Background:A remarkable drop in tuberculosis(TB)incidence has been achieved in China,although in 2019 it was still considered the second most communicable disease.However,TB’s spatial features and risk factors in urban areas remain poorly understood.This study aims to identify the spatial diferentiations and potential infuencing factors of TB in highly urbanized regions on a fne scale.Methods:This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou,China.TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention.Before using Pearson correlation and a geographical detector(GD)to identify potential infuencing factors,we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales.Results:Owing to its strong spatial autocorrelation(Moran’s I=0.33,Z=4.71),the 2 km×2 km grid was selected as the spatial scale.At this level,TB incidence was closely associated with most socioeconomic variables(0.31<r<0.76,P<0.01).Of fve environmental factors,only the concentration of fne particulate matter displayed signifcant correlation(r=0.21,P<0.05).Similarly,in terms of q values derived from the GD,socioeconomic variables had stronger explanatory abilities(0.08<q<0.57)for the spatial diferentiation of the 2017 incidence of TB than environmental variables(0.06<q<0.27).Moreover,a much larger proportion(0.16<q<0.89)of the spatial diferentiation was interpreted by pairwise interactions,especially those(0.60<q<0.89)related to the 2016 incidence of TB,ofcially appointed medical institutions,bus stops,and road density.Conclusions:The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably infuenced by several socioeconomic and environmental factors and their pairwise interactions on a fne scale.We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou.Our study provides helpful clues for local authorities implementing more efective intervention measures to reduce TB incidence in China’s municipal areas,which are featured by both a high degree of urbanization and a high incidence of TB.
基金This work was supported by the National Key Research and Development Plan of China(Grant No.2016YFC0500205)the Research on Multi_Level Complex Spatial Data Model and the Consistency(No.41571391).
文摘The establishment of the National Key Ecological Function Areas(NKEFAs)is an important measure for national ecological security,but the current ecological and environmental evaluation of NKEFAs lacks research on the air quality in the NKEFAs.This study presented the current status of the air quality in the NKEFAs and its driving factors using the geographic detector q-statistic method.The air quality in the NKEFAs was overall better than individual cities and urban agglomeration in eastern coast provinces of China,accounting for 9.21%of the days with air quality at Level III or above.The primary air pollutant was PM_(10),followed by PM_(2.5),with lower concentrations of the remaining pollutants.Pollution was more severe in the sand fixation areas,where air pollution was worst in spring and best in autumn,contrasting with other NKEFAs and individual cities and urban agglomerations.The main influencing factors of air quality index(AQI)in the NKEFAs were land use type,wind speed,and relative humidity also weighted more heavily than factors such as industrial pollution and anthropogenic emissions,and most of these influence factors have two types of interactive effects:binary and nonlinear enhancements.These results indicated that air pollution in the NKEFAs was not related with the emission by intensive economic development.Thus,the policies taking the NKEFAs as restricted development zones were effective,but the air pollution caused by PM_(10) also showed the ecological status in the NKEFAs,especially at sand fixation areas was not quite optimistic,and more strict environmental protection measures should be taken to improve the ecological status in these NKEFAs.
文摘There is an issue of groundwater overexploitation in Ningjiang District,Songyuan City,Jilin Province,which has led to land subsidence.To investigate the influence of hydrological elements on surface deformation in Ningjiang District,surface deformation data were obtained by the small baseline subset interferometry synthetic aperture radar(SBAS-InSAR)technique.Initially,Sentinel-1B data were utilized to observe surface deformation in Ningjiang District from 2017 to 2021 with SBAS-InSAR.Subsequently,the geographical detector was employed to quantitatively assess the relationship between land subsidence and its influencing factors.Furthermore,multivariate singular spectrum analysis(M-SSA)was employed to identify periodic fluctuations in surface deformation and groundwater level,revealing the temporal lag between fluctuations in surface deformation and groundwater level.The findings demonstrate that the distance to water bodies accounts for the largest share of subsidence variation,with subsidence shaped by the combined impact of many factors.The results of interaction detection indicate that the interplay between the distance to water bodies and precipitation exhibits the most significant joint explanatory capacity for surface deformation.The observed seasonal cyclical fluctuations in groundwater level and surface deformation indicate a substantial influence of groundwater on surface deformation in the Ningjiang District.
基金supported by the National Natural Science Foundation of China(Grant No.41971239)the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0402)+1 种基金Lancang-Mekong Cooperation Project on China-Laos Cross-border Asian Elephant Habitat Quality Assessment(Grant No.102169221100000009022)the Graduate Research Innovation Project of Yunnan University(Grant No.2021Y368).
文摘Human-wildlife conflict(HWC)and its socioeconomic impacts are a pressing global issue.Accurately quantifying HWCs and their interaction with residential development is crucial for rural revitalization and biodiversity conservation efforts.This study investigates the interplay between rural residential expansion(RRE)with humanelephant conflict(HEC)in southern Yunnan Province using high-accuracy yearly land use/land cover data and Asian elephant accident data.A piecewise regression along with several metrics,including expansion intensity,rate of rural residential land,and residential density,were employed to analyze the spatial-temporal change characteristics of RRE.Then,a geographical detector and a bivariate spatial autocorrelation model were used to reveal the driving mechanisms of RRE,with particular emphasis on the spatial relations between RRE and HECs.The results indicate that HECs had a significant negative impact on RRE,exhibiting higher expansion intensity and rate of rural residential land in non-HEC areas than in HEC areas.High spatiotemporal consistency between accelerated RRE and intensified HECs occurred from 2010 onwards,which aligns with the year when the trend of settlement area expansion changed.RRE activities and ensuing land use conversions led to increased occurrences of HECs,which negatively affected the RRE.Compared to HECs,topography and locational factors exhibited a secondary effect on RRE activities.The findings underscore reciprocal feedback mechanisms between RRE and HECs and the elevated risk of adverse interactions between humans and elephants within the range of China’s wild elephants,providing theoretical support for coordinating conservation initiatives for Asian elephants with rural revitalization in the border areas of Southwest China.
基金Under the auspices of National Natural Science Foundation of China(No.42061020)Natural Science Foundation of Guangxi Zhuang Autonomous Region(No.2018JJA150135)+2 种基金Guangxi Key Research and Development Program(No.AA18118038)Science and Technology Department of Guangxi Zhuang Autonomous Region(No.2019AC20088)High Level Talent Introduction Project of Beibu Gulf University(No.2019KYQD28)。
文摘Scientific understanding of the trade-offs between services is crucial for the scientific management and protection of ecosystems and the formulation of resource management policies.This study integrated meteorological,land use,and soil data to assess the ecosystem services,namely,water yield(WY),soil erosion(SE),and carbon sinks(CS),in peak-cluster depression basins on the Sino-Vietnamese border in China during 2000-2020.It analyzed the trade-offs and synergistic relationships among the three ecosystem services and their time-lag effects and driving mechanisms with the help of pixel-by-pixel time-lag intercorrelation and geographical de-tector methods.Results show that:1)from 2000 to 2020,the key ecosystem service indicators in the peak-cluster depression basins on the Sino-Vietnamese border in China demonstrated a significant and synergistic trend of positive change.The WY increased at a rate of 11.99 mm/yr,CS increased at a rate of 2.44 g C/(m^(2)∙yr),and SE decreased at a rate of 0.06 t/(ha∙yr).2)Most areas showed a synergistic relationship across the three ecosystem services,and the areas with a trade-off relationship were mostly concentrated in Baise City and the southwest of Chongzuo City,Guangxi.3)The time-lag effect between SE and WY was mostly concentrated in 0 yr,that between SE and CS was mostly concentrated in 5 yr,and that between CS and WY was mostly concentrated in 1 yr.4)Population density was the controlling factor between SE and WY.Vegetation coverage factor is the main controlling factor between SE and CS.The lithologic factor is the main controlling factor between CS and WY.Studying the trade-off relationship of ecosystem services at spatial and tem-poral scales on the Sino-Vietnamese border in China karst areas can provide a basis for regional ecological construction and develop-ment strategies,and it is conducive to meeting regional interest needs,maximizing comprehensive benefits,balancing the ecological en-vironment,and achieving regional sustainable development.
基金National Natural Science Foundation of China,No.41971268。
文摘Regular quantitative assessments of regional ecological environment quality(EEQ)and driving force analyses are highly important for environmental protection and sustainable development.Northern China is a typical climate-sensitive and ecologically vulnerable area,however,the changes in EEQ in this region and their underlying causes remain unclear.Traditional evaluations of EEQ rely primarily on the remote sensing ecological index(RSEI),which lacks assessments of indicators such as greenness(NDVI),humidity(WET),heat(LST),and dryness(NDBSI).To address these issues,this study employs the principal component analysis method and the Google Earth Engine to construct an RSEI suitable for long-term and large-scale applications and analyzes the spatio-temporal variations in the RSEI,NDVI,WET,NDBSI,and LST.Additionally,geographical detectors are utilized to analyze the driving factors affecting EEQ.The results indicate the following.(1)The RSEI shows a fluctuating upward trend,with an average value of 0.4566,indicating a gradual improvement in EEQ.The EEQ exhibited significant spatial heterogeneity,with a pattern of lower values in the west and higher values in the east.(2)The NDVI and WET exhibit fluctuating increasing trends,indicating improvements in both indices.The NDBSI shows a fluctuating decreasing trend,whereas the LST presents a fluctuating increasing trend,suggesting an improvement in the NDBSI and a slight deterioration in the LST.NDVI and WET demonstrate a spatial pattern characterized by low values in the west and high values in the east.NDBSI and LST demonstrate a spatial pattern characterized by low values in the east and high values in the west.(3)Land use types and precipitation are the primary driving factors influencing the spatial differentiation of the EEQ.The explanatory power of these driving factors significantly increases under their interactions,particularly the interaction between land use types and other driving factors.This study fills the gap in existing EEQ evaluations that analyze only the RSEI without considering the NDVI,WET,NDBSI,and LST.The findings provide new insights for EEQ assessments and serve as a scientific reference for environmental protection and sustainable development.
文摘This study investigated the spatio-temporal variation characteristics of ecosystem service value(ESV)alongside its driving influencing factors,thereby offering valuable theoretical insights for the sustainable development of Jingzhou City,Hubei Province.Based on the land use data for Jingzhou City from 2000 to 2020,this study quantified the value of the ecological environment using the equivalent factor method.Furthermore,it analyzed and elucidated the spatio-temporal heterogeneity and driving mechanisms of ecosystem services in Jingzhou City.The results indicated that between 2000 and 2020,cultivated land(66.40%)and water area(18.82%)were the predominant land use types in Jingzhou City.The areas of water area and construction land exhibited a growth trend during this period.Construction land had the highest rate of land use change,followed by water area and cultivated land.Land use transitions primarily occurred between cultivated land and water area,as well as between cultivated land and construction land.The total value of ecosystem services in Jingzhou City increased by 165.07%from 2000 to 2020.ESV exhibited an upward trend from 2000 to 2015,followed by a gradual decline from 2015 to 2020.The ranking of individual ecosystem services,in descending order,was as follows:regulation services,supporting services,provisioning services,and cultural services.High-value ESV areas were predominantly situated in the water area of Lake Honghu,while low-value regions were mainly found in the cultivated land in the central and western parts of Jingzhou City.The spatial differentiation of ESV in Jingzhzou City was influenced by both natural and socio-economic factors,with natural factors exerting a more significant impact than socioeconomic factors.Specifically,the Normalized Difference Vegetation Index(NDVI)was the dominant environmental factor,while GDP plays a synergistic role.
基金the National Natural Science Foundation of China(Grant No.42301336)the Open Research Fund of Henan Provincial Key Laboratory of Hydrosphere and Watershed Water Security(Grant No.HWWSF202302).
文摘As a major worldwide issue,desertification poses significant threats to ecosystem stability and long-term socioeconomic growth.Within China,the Mu Us Sandy land represents a crucial region for studying desertification phenomena.Comprehending how desertification risks are distributed spatially and what mechanisms drive them remains fundamental for implementing effective strategies in land management and risk mitigation.Our research evaluated desertification vulnerability across the Mu Us Sandy land by applying the MEDALUS model,while investigating causal factors via geographical detector methodology.Findings indicated that territories with high desertification vulnerability extend across 71,401.7 km^(2),constituting 76.87%of the entire region,while zones facing extreme desertification hazard cover 20,578.9 km^(2)(22.16%),primarily concentrated in a band-like pattern along the western boundary of the Mu Us Sandy land.Among the four primary indicators,management quality emerged as the most significant driver of desertification susceptibility,followed by vegetation quality and soil quality.Additionally,drought resistance,land use intensity,and erosion protection were identified as the key factors driving desertification sensitivity.The investigation offers significant theoretical perspectives that can guide the formulation of enhanced strategies for controlling desertification and promoting sustainable land resource utilization within the Mu Us Sandy land region.
基金Under the auspices of National Natural Science Foundation Youth Fund Project(No.41701424)Open Research Fund of State Key Laboratory of Remote Sensing Science(No.OFSLRSS201716)+1 种基金Jilin Province Science and Technology Development Plan Project(No.20240701167FG)Science and Technology Research Project of Education Department of Jilin Province(No.JJKH20230502KJ)。
文摘The health of cropland systems is directly related to the degree of food security guarantee,and the‘quantity-quality-ecology as a whole’protection is of great significance for maintaining the health of cropland systems.Taking the typical black soil region in Northeast China(TBSN)as an example,this paper combined the concept of‘quantity-quality-ecology as a whole’protection with crop-land systems health,constructed a health assessment model for cropland systems,and used Google Earth Engine to conduct a quantitat-ive analysis of the temporal and spatial evolution of cropland systems health in TBSN during 2003–2023.By coupling the geographical detector and the Multi-scale Geographically Weighted Regression(MGWR)model,the driving factors of cropland health changes were explored.The study finds that during the research period,the health status of cropland systems in TBSN showed a slight downward trend,and the distribution pattern of cropland systems health gradually shifted from‘better in the east’to‘high in the northeast and low in the southwest’.Changes in average annual sunshine duration,relative humidity,and precipitation had a significant impact on the spa-tial differentiation of cropland systems health in the early stages,and were considered as dominant factors.Meanwhile,the influence of dual dominant factors in the natural environment on cropland systems health is increasing.Furthermore,the MGWR model performed better in revealing the complex relationships between natural and social factors and changes in cropland systems health,demonstrating the significant spatial heterogeneity of the impacts of natural environment and human activities on cropland systems health.The re-search can provide scientific guidance for the sustainable development of TBSN and formulate more precise and effective cropland pro-tection policies.
基金funded primarily by the Central Public Welfare Research Institutes Basic Research Business Funds to Support the Administration’s Central Work Project(Grant No.CAFYBB2023ZA003-4)the National Natural Science Foundation of China(Grant Nos.31170593 and 31570633)National Forestry and Grassland Administration Forestry Under the Project“Forestry Major Issues Research”(Grant Nos.500102-1776 and 500102-5110).
文摘Understanding the influencing factors of ecosystem services(ESs)and their relationships is essential for sustainable ecosystem management in degraded alpine ecosystems.There is a lack of integrated multi-model approaches to explore the multidimensional influences on ESs and their relationships in alpine ecosystems.Taking the Daxing'anling forest area,Inner Mongolia(DFAIM)as a case study,this study used the integrated valuation of ecosystem services and trade-offs(InVEST)model to quantify four ESs—soil conservation(SC),water yield(WY),carbon storage(CS),and habitat quality(HQ)—from 2013 to 2018.We adopted root mean square deviation(RMSD)and coupling coordination degree models(CCDM)to analyze their relationships,and integrated three complementary approaches—optimal parameter-based geographical detector model(OPGDM),gradient boosting regression tree model(GBRTM),and quantile regression model(QRM)—to reveal multidimensional influencing factors.Key findings include the following:(1)From 2013 to 2018,WY,SC,and HQ declined while CS increased.WY was primarily influenced by mean annual precipitation(MAP),forest ratio(RF),and soil bulk density(SBD);CS and HQ by RF and population density(PD);and SC by slope(S),RF,and MAP.Mean annual temperature(MAT),gross domestic product(GDP),and road network density(RND)showed increasing negative impacts.(2)Low trade-off intensity(TI<0.15)dominated all ES pairs,with RF,MAP,PD,and normalized difference vegetation index(NDVI)being the dominant factors.The factor interactions primarily showed two-factor enhancement patterns.(3)The average coupling coordination degree(CCD)of the four ESs was low and declined over time,with low-CCD areas becoming increasingly prevalent.RF,S,SBD,and NDVI positively influenced CCD,while PD,MAT,GDP,and RND had increasing negative impacts,with over 62%of the factor interactions exceeding the individual factor effects.In summary,ES supply generally decreased.Local relationships showed moderate coordination,while overall relationships indicated primary dysfunction.Land use and natural factors primarily shaped these ES and their relationships,while climate and socioeconomic changes diminished ES supply and intensified competition.We recommend enhancing the resilience of natural systems rather than replacing them,establishing climate adaptation monitoring systems,and promoting conservation tillage and cross-departmental coordination mechanisms for collaborative ES optimization.These results provide valuable insights into the sustainable management of alpine ecosystems.
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funded by the Central University D Project(HFW230600022)National Natural Science Foundation of China(71973021)+1 种基金National Natural Science Foundation Youth Funding Project(72003022)Heilongjiang Province University Think Tank Open Topic(ZKKF2022173).
文摘The scientific assessment of ecosystem ser-vice value(ESV)plays a critical role in regional ecologi-cal protection and management,rational land use planning,and the establishment of ecological security barriers.The ecosystem service value of the Northeast Forest Belt from 2005 to 2020 was assessed,focusing on spatial–temporal changes and the driving forces behind these dynamics.Using multi-source data,the equivalent factor method,and geo-graphic detectors,we analyzed natural and socio-economic factors affecting the region.which was crucial for effective ecological conservation and land-use planning.Enhanced the effectiveness of policy formulation and land use plan-ning.The results show that the ESV of the Northeast Forest Belt exhibits an overall increasing trend from 2005 to 2020,with forests and wetlands contributing the most.However,there are significant differences between forest belts.Driven by natural and socio-economic factors,the ESV of forest belts in Heilongjiang and Jilin provinces showed significant growth.In contrast,the ESV of Forest Belts in Liaoning and Inner Mongolia of China remains relatively stable,but the spatial differentiation within these regions is characterized by significant clustering of high-value and low-value areas.Furthermore,climate regulation and hydrological regulation services were identified as the most important ecological functions in the Northeast Forest Belt,contributing greatly to regional ecological stability and human well-being.The ESV in the Northeast Forest Belt is improved during the study period,but the stability of the ecosystem is still chal-lenged by the dual impacts of natural and socio-economic factors.To further optimize regional land use planning and ecological protection policies,it is recommended to prior-itize the conservation of high-ESV areas,enhance ecological restoration efforts for wetlands and forests,and reasonably control the spatial layout of urban expansion and agricul-tural development.Additionally,this study highlights the importance of tailored ecological compensation policies and strategic land-use planning to balance environmental protec-tion and economic growth.
基金supported by Geological survey project of China Geological Survey(DD20230481,DD20242461)。
文摘Terrain and geological formation are crucial natural environmental factors that constrain land use and land cover changes.Studying their regulatory role in regional land use and land cover changes is significant for guiding regional land resource management.Taking the Danjiang River Basin in the Qinling Mountains of China as an example,this paper incorporates terrain(elevation,slope,and aspect)factors and geological formation to comprehensively analyse the differentiation characteristics of land use spatial patterns based on the examination of land use changes in 2000,2010,and 2020.Moreover,the geographical detector is employed to compare and analyse the effect of each factor on the spatial heterogeneity of land use.The results show that:(1)From 2000 to 2020,the areas of arable land and forestland in the Danjiang River Basin decreased while the areas of grassland,water areas,construction land,and unused land continuously increased.The comprehensive land use dynamics index was+0.09%,indicating a generally low level of land development.(2)Differences in the natural environmental factors of terrain and geological formation have a significant controlling effect on the spatial heterogeneity of land use.Specifically,there are notable differences in the advantageous distribution characteristics of various land use types across different levels of influencing factors.(3)The factor detection results reveal that geological formation has the strongest influence on the spatial heterogeneity of land use,followed by elevation and slope while aspect has the weakest influence.After the interaction among the factors,they nonlinearly enhance the explanation of spatial heterogeneity in land use.Overall,the influence of geological formation on the spatial heterogeneity of land use is greater than that of terrain factors.This study provides new geological evidence for natural resource management departments to conduct regional spatial planning,ecological and environmental protection and restoration,and land structure optimization and adjustment.
